ONNX Backends for onnxruntime1#
Backend class: OnnxInferenceBackendOrt
.
<<<
import unittest
import sys
from datetime import datetime
from contextlib import redirect_stdout, redirect_stderr
from io import StringIO
from onnx.backend.test import BackendTest
from onnx import __version__ as onnx_version
from onnxruntime import __version__ as ort_version
from numpy import __version__ as npy_version
import mlprodict.onnxrt.backend_ort as backend
back_test = BackendTest(backend, __name__)
back_test.include('.*_cpu')
back_test.exclude('.*_blvc_.*')
back_test.exclude('.*_densenet_.*')
back_test.exclude('.*_densenet121_.*')
back_test.exclude('.*_inception_.*')
back_test.exclude('.*_resnet50_.*')
back_test.exclude('.*_shufflenet_.*')
back_test.exclude('.*_squeezenet_.*')
back_test.exclude('.*_vgg19_.*')
back_test.exclude('.*_zfnet512_.*')
globals().update(back_test.enable_report().test_cases)
print('---------------------------------')
print('python', sys.version)
print('onnx', onnx_version)
print('onnxruntime', ort_version)
print('numpy', npy_version)
print('---------------------------------')
print(datetime.now(), "BEGIN")
print('---------------------------------')
buffer = StringIO()
if True:
with redirect_stdout(buffer):
with redirect_stderr(buffer):
res = unittest.main(verbosity=2, exit=False)
else:
res = unittest.main(verbosity=2, exit=False)
testsRun = res.result.testsRun
errors = len(res.result.errors)
skipped = len(res.result.skipped)
unexpectedSuccesses = len(res.result.unexpectedSuccesses)
expectedFailures = len(res.result.expectedFailures)
print('---------------------------------')
print(datetime.now(), "END")
print('---------------------------------')
print("testsRun=%d errors=%d skipped=%d" % (testsRun, errors, skipped))
print("unexpectedSuccesses=%d expectedFailures=%d" % (
unexpectedSuccesses, expectedFailures))
ran = testsRun - skipped
print("ratio=%f" % (1 - errors * 1.0 / ran))
print('---------------------------------')
lines = buffer.getvalue().split('\n')
print("\n".join(line for line in lines
if "skipped 'no matched include pattern'" not in line))
>>>
---------------------------------
python 3.9.1 (default, Jan 18 2021, 16:35:58)
[GCC 8.3.0]
onnx 1.13.0
onnxruntime 1.13.1
numpy 1.23.5
---------------------------------
2023-02-04 07:11:06.208338 BEGIN
---------------------------------
---------------------------------
2023-02-04 07:11:46.489833 END
---------------------------------
testsRun=2492 errors=352 skipped=1254
unexpectedSuccesses=0 expectedFailures=0
ratio=0.715670
---------------------------------
test_abs_cpu (__main__.OnnxBackendNodeModelTest) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py:17: DeprecationWarning: Please use `coo_matrix` from the `scipy.sparse` namespace, the `scipy.sparse.coo` namespace is deprecated.
from scipy.sparse.coo import coo_matrix
somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py:207: DeprecationWarning: `np.object` is a deprecated alias for the builtin `object`. To silence this warning, use `object` by itself. Doing this will not modify any behavior and is safe.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
if ref_outputs[i].dtype == np.object:
ok
test_acos_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_acos_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_acosh_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_acosh_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_adagrad_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_adagrad_multiple_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_adam_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_adam_multiple_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_add_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_add_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_add_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_and2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_and3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_and4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_and_bcast3v1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_and_bcast3v2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_and_bcast4v2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_and_bcast4v3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_and_bcast4v4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_default_axis_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_default_axis_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_default_axis_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_default_axis_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_keepdims_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_keepdims_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_negative_axis_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_negative_axis_keepdims_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_negative_axis_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_negative_axis_keepdims_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_no_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_no_keepdims_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_no_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmax_no_keepdims_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_default_axis_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_default_axis_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_default_axis_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_default_axis_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_keepdims_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_keepdims_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_negative_axis_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_negative_axis_keepdims_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_negative_axis_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_negative_axis_keepdims_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_no_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_no_keepdims_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_no_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_argmin_no_keepdims_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_asin_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_asin_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_asinh_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_asinh_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_atan_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_atan_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_atanh_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_atanh_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_averagepool_1d_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_averagepool_2d_ceil_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_averagepool_2d_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_averagepool_2d_pads_count_include_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_averagepool_2d_pads_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_averagepool_2d_precomputed_pads_count_include_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_averagepool_2d_precomputed_pads_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_averagepool_2d_precomputed_same_upper_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_averagepool_2d_precomputed_strides_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_averagepool_2d_same_lower_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_averagepool_2d_same_upper_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_averagepool_2d_strides_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_averagepool_3d_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_basic_conv_with_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_basic_conv_without_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_batchnorm_epsilon_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_batchnorm_epsilon_training_mode_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_batchnorm_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_batchnorm_example_training_mode_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bernoulli_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_bernoulli_double_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_bernoulli_double_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_bernoulli_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_bernoulli_seed_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_bernoulli_seed_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_bitshift_left_uint16_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitshift_left_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitshift_left_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitshift_left_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitshift_right_uint16_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitshift_right_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitshift_right_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitshift_right_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_and_i16_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_and_i32_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_and_ui64_bcast_3v1d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_and_ui8_bcast_4v3d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_not_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_not_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_not_4d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_or_i16_4d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_or_i32_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_or_ui64_bcast_3v1d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_or_ui8_bcast_4v3d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_xor_i16_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_xor_i32_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_xor_ui64_bcast_3v1d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitwise_xor_ui8_bcast_4v3d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_blackmanwindow_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_blackmanwindow_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_blackmanwindow_symmetric_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_blackmanwindow_symmetric_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cast_BFLOAT16_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_cast_DOUBLE_to_FLOAT16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cast_DOUBLE_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cast_FLOAT16_to_DOUBLE_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cast_FLOAT16_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cast_FLOAT_to_BFLOAT16_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_cast_FLOAT_to_DOUBLE_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cast_FLOAT_to_FLOAT16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cast_FLOAT_to_STRING_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_cast_STRING_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_BFLOAT16_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_castlike_BFLOAT16_to_FLOAT_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_castlike_DOUBLE_to_FLOAT16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_DOUBLE_to_FLOAT16_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_DOUBLE_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_DOUBLE_to_FLOAT_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_FLOAT16_to_DOUBLE_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_FLOAT16_to_DOUBLE_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_FLOAT16_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_FLOAT16_to_FLOAT_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_FLOAT_to_BFLOAT16_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_castlike_FLOAT_to_BFLOAT16_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_castlike_FLOAT_to_DOUBLE_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_FLOAT_to_DOUBLE_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_FLOAT_to_FLOAT16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_FLOAT_to_FLOAT16_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_FLOAT_to_STRING_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_castlike_FLOAT_to_STRING_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_castlike_STRING_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_castlike_STRING_to_FLOAT_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_ceil_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_ceil_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_celu_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_celu_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_center_crop_pad_crop_and_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_center_crop_pad_crop_and_pad_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_center_crop_pad_crop_axes_chw_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_center_crop_pad_crop_axes_chw_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_center_crop_pad_crop_axes_hwc_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_center_crop_pad_crop_axes_hwc_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_center_crop_pad_crop_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_center_crop_pad_crop_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_center_crop_pad_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_center_crop_pad_pad_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_clip_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_default_inbounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_default_inbounds_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_default_int8_inbounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_default_int8_inbounds_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_default_int8_max_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_default_int8_max_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_clip_default_int8_min_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_default_int8_min_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_clip_default_max_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_default_max_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_default_min_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_default_min_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_inbounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_inbounds_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_outbounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_outbounds_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_splitbounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_splitbounds_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_col2im_5d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_col2im_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_col2im_dilations_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_col2im_pads_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_col2im_strides_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_compress_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_compress_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_compress_default_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_compress_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_concat_1d_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_concat_1d_axis_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_concat_2d_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_concat_2d_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_concat_2d_axis_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_concat_2d_axis_negative_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_concat_3d_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_concat_3d_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_concat_3d_axis_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_concat_3d_axis_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_concat_3d_axis_negative_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_concat_3d_axis_negative_3_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_constant_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_constant_pad_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_constant_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_constantofshape_float_ones_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_constantofshape_int_shape_zero_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_constantofshape_int_zeros_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_conv_with_autopad_same_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_conv_with_strides_and_asymmetric_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_conv_with_strides_no_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_conv_with_strides_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_convinteger_with_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_convinteger_without_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_convtranspose_1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_convtranspose_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_convtranspose_autopad_same_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_convtranspose_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_convtranspose_dilations_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_convtranspose_kernel_shape_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_convtranspose_output_shape_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_convtranspose_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_convtranspose_pads_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cos_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cos_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cosh_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cosh_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cumsum_1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cumsum_1d_exclusive_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cumsum_1d_reverse_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cumsum_1d_reverse_exclusive_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cumsum_2d_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cumsum_2d_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_cumsum_2d_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_depthtospace_crd_mode_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_depthtospace_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dequantizelinear_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dequantizelinear_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_det_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_det_nd_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dft_axis_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_dft_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_dft_inverse_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_div_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_div_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_div_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_div_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_dropout_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dropout_default_mask_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dropout_default_mask_ratio_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dropout_default_old_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dropout_default_ratio_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dropout_random_old_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dynamicquantizelinear_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dynamicquantizelinear_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dynamicquantizelinear_max_adjusted_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dynamicquantizelinear_max_adjusted_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dynamicquantizelinear_min_adjusted_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dynamicquantizelinear_min_adjusted_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_edge_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_einsum_batch_diagonal_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_einsum_batch_matmul_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_einsum_inner_prod_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_einsum_sum_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_einsum_transpose_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_elu_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_elu_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_elu_default_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_elu_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_elu_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_elu_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_equal_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_equal_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_erf_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_exp_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_exp_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_expand_dim_changed_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_expand_dim_unchanged_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_eyelike_populate_off_main_diagonal_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_eyelike_with_dtype_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_eyelike_without_dtype_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_flatten_axis0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_flatten_axis1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_flatten_axis2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_flatten_axis3_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_flatten_default_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_flatten_negative_axis1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_flatten_negative_axis2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_flatten_negative_axis3_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_flatten_negative_axis4_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_floor_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_floor_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gather_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gather_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gather_2d_indices_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gather_elements_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gather_elements_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gather_elements_negative_indices_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gather_negative_indices_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gathernd_example_float32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gathernd_example_int32_batch_dim1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gathernd_example_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gemm_all_attributes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gemm_alpha_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gemm_beta_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gemm_default_matrix_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gemm_default_no_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gemm_default_scalar_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gemm_default_single_elem_vector_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gemm_default_vector_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gemm_default_zero_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gemm_transposeA_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gemm_transposeB_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_globalaveragepool_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_globalaveragepool_precomputed_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_globalmaxpool_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_globalmaxpool_precomputed_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_greater_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_greater_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_greater_equal_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_greater_equal_bcast_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_greater_equal_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_greater_equal_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gridsample_aligncorners_true_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gridsample_bicubic_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gridsample_bilinear_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gridsample_border_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gridsample_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gridsample_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gridsample_reflection_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gridsample_zeros_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_group_normalization_epsilon_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_group_normalization_epsilon_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_group_normalization_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_group_normalization_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_gru_batchwise_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_gru_defaults_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gru_seq_length_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gru_with_initial_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hammingwindow_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hammingwindow_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hammingwindow_symmetric_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hammingwindow_symmetric_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hannwindow_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hannwindow_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hannwindow_symmetric_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hannwindow_symmetric_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardmax_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardmax_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardmax_axis_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardmax_default_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardmax_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardmax_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardmax_one_hot_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardsigmoid_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardsigmoid_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardsigmoid_default_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_hardsigmoid_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardsigmoid_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_hardsigmoid_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_hardswish_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardswish_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_identity_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_identity_opt_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_identity_sequence_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_if_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_if_opt_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_if_seq_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_instancenorm_epsilon_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_instancenorm_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_isinf_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_isinf_negative_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_isinf_positive_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_isnan_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_2d_axis0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_2d_axis0_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_2d_axis0_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_2d_axis1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_2d_axis1_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_2d_axis1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_2d_axis_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_2d_axis_negative_1_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_2d_axis_negative_1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_2d_axis_negative_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_2d_axis_negative_2_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_2d_axis_negative_2_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_3d_axis0_epsilon_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_3d_axis0_epsilon_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_3d_axis0_epsilon_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_3d_axis1_epsilon_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_3d_axis1_epsilon_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_3d_axis1_epsilon_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_3d_axis2_epsilon_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_3d_axis2_epsilon_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_3d_axis2_epsilon_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_3d_axis_negative_1_epsilon_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_3d_axis_negative_1_epsilon_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_3d_axis_negative_2_epsilon_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_3d_axis_negative_2_epsilon_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_3d_axis_negative_3_epsilon_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_3d_axis_negative_3_epsilon_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_4d_axis0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis0_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis0_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_4d_axis1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis1_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_4d_axis2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis2_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis2_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_4d_axis3_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis3_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis3_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_4d_axis_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis_negative_1_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis_negative_1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_4d_axis_negative_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis_negative_2_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis_negative_2_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_4d_axis_negative_3_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis_negative_3_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis_negative_3_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_4d_axis_negative_4_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis_negative_4_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_4d_axis_negative_4_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_layer_normalization_default_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_default_axis_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_layer_normalization_default_axis_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_leakyrelu_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_leakyrelu_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_leakyrelu_default_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_leakyrelu_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_leakyrelu_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_leakyrelu_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_less_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_less_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_less_equal_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_less_equal_bcast_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_less_equal_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_less_equal_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_log_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_log_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_axis_0_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_axis_0_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_logsoftmax_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_axis_1_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_axis_1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_logsoftmax_axis_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_axis_2_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_axis_2_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_logsoftmax_default_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_default_axis_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_default_axis_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_logsoftmax_example_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_example_1_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_example_1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_logsoftmax_large_number_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_large_number_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_large_number_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_logsoftmax_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_negative_axis_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_logsoftmax_negative_axis_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_loop11_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_loop13_seq_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_loop16_seq_none_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_lrn_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_lrn_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_lstm_batchwise_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_lstm_defaults_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_lstm_with_initial_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_lstm_with_peepholes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_matmul_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_matmul_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_matmul_4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_matmulinteger_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_float16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_float32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_float64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_int16_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_max_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_int64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_int8_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_max_one_input_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_two_inputs_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_uint16_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_max_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_maxpool_1d_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_2d_ceil_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_2d_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_2d_dilations_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_2d_pads_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_2d_precomputed_pads_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_2d_precomputed_same_upper_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_2d_precomputed_strides_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_2d_same_lower_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_2d_same_upper_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_2d_strides_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_2d_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_3d_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_with_argmax_2d_precomputed_pads_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxpool_with_argmax_2d_precomputed_strides_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_maxunpool_export_with_output_shape_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_maxunpool_export_without_output_shape_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mean_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mean_one_input_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mean_two_inputs_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_melweightmatrix_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_float16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_float32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_float64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_int16_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_min_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_int64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_int8_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_min_one_input_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_two_inputs_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_uint16_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_min_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_mish_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_mish_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_mod_broadcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_int64_fmod_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_mixed_sign_float16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_mixed_sign_float32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_mixed_sign_float64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_mixed_sign_int16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_mixed_sign_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_mixed_sign_int64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_mixed_sign_int8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_uint16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_momentum_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_momentum_multiple_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_mul_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mul_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mul_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mul_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_mvn_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mvn_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mvn_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_neg_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nesterov_momentum_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_nllloss_NC_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NC_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1_mean_weight_negative_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1_mean_weight_negative_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1_weight_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1_weight_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_no_weight_reduction_mean_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_no_weight_reduction_mean_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_reduction_mean_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_reduction_mean_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_reduction_sum_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_reduction_sum_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_with_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_with_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_with_weight_reduction_mean_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_with_weight_reduction_mean_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_with_weight_reduction_sum_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_with_weight_reduction_sum_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_with_weight_reduction_sum_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2_with_weight_reduction_sum_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2d3_none_no_weight_negative_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2d3_none_no_weight_negative_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2d3_sum_weight_high_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2d3_sum_weight_high_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2d3d4d5_mean_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2d3d4d5_mean_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2d3d4d5_none_no_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nllloss_NCd1d2d3d4d5_none_no_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nonmaxsuppression_center_point_box_format_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nonmaxsuppression_flipped_coordinates_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nonmaxsuppression_identical_boxes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nonmaxsuppression_limit_output_size_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nonmaxsuppression_single_box_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nonmaxsuppression_suppress_by_IOU_and_scores_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nonmaxsuppression_suppress_by_IOU_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nonmaxsuppression_two_batches_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nonmaxsuppression_two_classes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nonzero_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_not_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_not_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_not_4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_onehot_negative_indices_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_onehot_with_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_onehot_with_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_onehot_without_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_optional_get_element_optional_sequence_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_optional_get_element_optional_tensor_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_optional_get_element_sequence_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_optional_get_element_tensor_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_optional_has_element_empty_no_input_name_optional_input_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_optional_has_element_empty_no_input_name_tensor_input_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_optional_has_element_empty_no_input_optional_input_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_optional_has_element_empty_no_input_tensor_input_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_optional_has_element_empty_optional_input_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_optional_has_element_optional_input_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_optional_has_element_tensor_input_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_or2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_or3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_or4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_or_bcast3v1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_or_bcast3v2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_or_bcast4v2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_or_bcast4v3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_or_bcast4v4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_pow_bcast_array_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_pow_bcast_scalar_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_pow_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_pow_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_pow_types_float32_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_pow_types_float32_int64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_pow_types_float32_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_pow_types_float32_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_pow_types_int32_float32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_pow_types_int32_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_pow_types_int64_float32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_pow_types_int64_int64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_prelu_broadcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_prelu_broadcast_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_prelu_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_prelu_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_qlinearconv_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_qlinearmatmul_2D_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_qlinearmatmul_3D_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_quantizelinear_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_quantizelinear_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_range_float_type_positive_delta_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_range_float_type_positive_delta_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_range_int32_type_negative_delta_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_range_int32_type_negative_delta_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reciprocal_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reciprocal_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_default_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_default_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_do_not_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_do_not_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_keep_dims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_keep_dims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_negative_axes_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_negative_axes_keep_dims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_negative_axes_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l1_negative_axes_keep_dims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_default_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_default_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_do_not_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_do_not_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_keep_dims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_keep_dims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_negative_axes_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_negative_axes_keep_dims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_negative_axes_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_negative_axes_keep_dims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_asc_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_asc_axes_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_default_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_default_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_desc_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_desc_axes_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_default_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_default_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_do_not_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_do_not_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_negative_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_negative_axes_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_max_default_axes_keepdim_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_max_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_max_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_max_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_max_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_max_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_max_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_max_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_mean_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_mean_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_mean_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_mean_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_mean_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_mean_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_mean_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_mean_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_min_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_min_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_min_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_min_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_min_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_min_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_min_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_min_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_prod_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_prod_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_prod_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_prod_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_prod_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_prod_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_prod_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_prod_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_empty_axes_input_noop_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_default_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_default_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_do_not_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_do_not_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_negative_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_sum_square_negative_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reflect_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_relu_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_relu_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reshape_allowzero_reordered_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reshape_extended_dims_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reshape_negative_dim_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reshape_negative_extended_dims_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reshape_one_dim_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reshape_reduced_dims_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reshape_reordered_all_dims_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reshape_reordered_last_dims_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reshape_zero_and_negative_dim_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reshape_zero_dim_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_downsample_scales_cubic_A_n0p5_exclude_outside_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_scales_cubic_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_scales_cubic_antialias_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_scales_cubic_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_scales_linear_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_scales_linear_antialias_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_scales_linear_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_scales_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_sizes_cubic_antialias_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_sizes_cubic_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_sizes_linear_antialias_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_sizes_linear_pytorch_half_pixel_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_sizes_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_sizes_nearest_not_larger_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_downsample_sizes_nearest_not_smaller_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_tf_crop_and_resize_axes_2_3_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_tf_crop_and_resize_axes_3_2_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_tf_crop_and_resize_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_scales_cubic_A_n0p5_exclude_outside_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_scales_cubic_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_scales_cubic_asymmetric_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_scales_cubic_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_scales_linear_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_scales_linear_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_scales_nearest_axes_2_3_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_scales_nearest_axes_3_2_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_scales_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_sizes_cubic_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_sizes_nearest_axes_2_3_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_sizes_nearest_axes_3_2_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_sizes_nearest_ceil_half_pixel_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_sizes_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_sizes_nearest_floor_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_sizes_nearest_not_larger_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reversesequence_batch_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reversesequence_time_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_rnn_seq_length_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_roialign_aligned_false_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_roialign_aligned_true_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_round_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_scan9_sum_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_scan_sum_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_scatter_elements_with_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_scatter_elements_with_duplicate_indices_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_scatter_elements_with_negative_indices_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_scatter_elements_with_reduction_max_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_scatter_elements_with_reduction_min_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_scatter_elements_without_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_scatter_with_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_scatter_without_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_scatternd_add_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_scatternd_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_scatternd_max_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_scatternd_min_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_scatternd_multiply_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sce_NCd1_mean_weight_negative_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1_mean_weight_negative_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1_mean_weight_negative_ii_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1_mean_weight_negative_ii_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3_none_no_weight_negative_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3_none_no_weight_negative_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3_sum_weight_high_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3_sum_weight_high_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3d4d5_mean_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3d4d5_mean_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3d4d5_mean_weight_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3d4d5_mean_weight_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3d4d5_none_no_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3d4d5_none_no_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_3d_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_3d_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_3d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_no_weight_ii_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_no_weight_ii_3d_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_no_weight_ii_3d_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_no_weight_ii_3d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_no_weight_ii_4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_no_weight_ii_4d_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_no_weight_ii_4d_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_no_weight_ii_4d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_no_weight_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_no_weight_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_no_weight_ii_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_no_weight_ii_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_ii_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_ii_3d_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_ii_3d_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_ii_3d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_ii_4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_ii_4d_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_ii_4d_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_ii_4d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_ii_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_ii_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_mean_weight_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_none_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_none_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_none_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_none_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_none_weights_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_none_weights_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_none_weights_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_none_weights_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_sum_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_sum_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_sum_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sce_sum_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_selu_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_selu_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_selu_default_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_selu_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_selu_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_selu_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_insert_at_back_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_insert_at_front_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_map_add_1_sequence_1_tensor_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_map_add_1_sequence_1_tensor_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_map_add_2_sequences_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_map_add_2_sequences_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_map_extract_shapes_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_map_extract_shapes_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_map_identity_1_sequence_1_tensor_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_map_identity_1_sequence_1_tensor_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_map_identity_1_sequence_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_map_identity_1_sequence_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_map_identity_2_sequences_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sequence_map_identity_2_sequences_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_shape_clip_end_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_shape_clip_start_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_shape_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_shape_end_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_shape_end_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_shape_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_shape_start_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_shape_start_1_end_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_shape_start_1_end_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_shape_start_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_shrink_hard_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_shrink_hard_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_shrink_soft_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_shrink_soft_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sigmoid_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sigmoid_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sign_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_simple_rnn_batchwise_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_simple_rnn_defaults_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_simple_rnn_with_initial_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sin_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sin_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sinh_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sinh_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_size_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_size_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_slice_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_slice_default_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_slice_default_steps_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_slice_end_out_of_bounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_slice_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_slice_neg_steps_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_slice_negative_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_slice_start_out_of_bounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_axis_0_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_axis_0_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_softmax_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_axis_1_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_axis_1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_softmax_axis_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_axis_2_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_axis_2_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_softmax_default_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_default_axis_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_default_axis_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_softmax_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_softmax_large_number_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_large_number_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_large_number_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_softmax_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_negative_axis_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_negative_axis_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_softplus_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softplus_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softplus_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_softplus_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_softsign_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softsign_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softsign_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_softsign_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_spacetodepth_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_spacetodepth_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_1d_uneven_split_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_split_2d_uneven_split_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_split_equal_parts_1d_opset13_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_equal_parts_1d_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_split_equal_parts_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_split_equal_parts_2d_opset13_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_equal_parts_default_axis_opset13_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_equal_parts_default_axis_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_split_variable_parts_1d_opset13_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_variable_parts_1d_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_split_variable_parts_2d_opset13_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_variable_parts_2d_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_split_variable_parts_default_axis_opset13_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_variable_parts_default_axis_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_split_zero_size_splits_opset13_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_zero_size_splits_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sqrt_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sqrt_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_squeeze_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_squeeze_negative_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_stft_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_stft_with_window_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_strnormalizer_export_monday_casesensintive_lower_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_strnormalizer_export_monday_casesensintive_nochangecase_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_strnormalizer_export_monday_casesensintive_upper_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_strnormalizer_export_monday_empty_output_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_strnormalizer_export_monday_insensintive_upper_twodim_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_strnormalizer_nostopwords_nochangecase_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sub_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sub_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sub_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sub_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_sum_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sum_one_input_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_sum_two_inputs_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tan_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tan_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tanh_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tanh_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tfidfvectorizer_tf_batch_onlybigrams_skip0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tfidfvectorizer_tf_batch_onlybigrams_skip5_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tfidfvectorizer_tf_batch_uniandbigrams_skip5_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tfidfvectorizer_tf_only_bigrams_skip0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tfidfvectorizer_tf_onlybigrams_levelempty_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tfidfvectorizer_tf_onlybigrams_skip5_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tfidfvectorizer_tf_uniandbigrams_skip5_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_thresholdedrelu_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_thresholdedrelu_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_thresholdedrelu_default_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_thresholdedrelu_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_thresholdedrelu_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_thresholdedrelu_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_tile_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tile_precomputed_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_top_k_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_top_k_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_top_k_smallest_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_training_dropout_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_training_dropout_default_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_training_dropout_default_mask_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_training_dropout_mask_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_training_dropout_zero_ratio_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_training_dropout_zero_ratio_mask_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_transpose_all_permutations_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_transpose_all_permutations_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_transpose_all_permutations_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_transpose_all_permutations_3_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_transpose_all_permutations_4_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_transpose_all_permutations_5_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_transpose_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tril_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tril_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tril_one_row_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tril_out_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tril_out_pos_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tril_pos_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tril_square_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tril_square_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_tril_zero_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_triu_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_triu_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_triu_one_row_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_triu_out_neg_out_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_triu_out_pos_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_triu_pos_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_triu_square_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_triu_square_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_triu_zero_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_unique_not_sorted_without_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_unique_sorted_with_axis_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_unique_sorted_with_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_unique_sorted_with_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_unique_sorted_without_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_unsqueeze_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_unsqueeze_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_unsqueeze_axis_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_unsqueeze_negative_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_unsqueeze_three_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_unsqueeze_two_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_unsqueeze_unsorted_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_upsample_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_where_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_where_long_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_xor2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_xor3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_xor4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_xor_bcast3v1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_xor_bcast3v2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_xor_bcast4v2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_xor_bcast4v3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_xor_bcast4v4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_AvgPool1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_AvgPool1d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_AvgPool2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_AvgPool2d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_AvgPool3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_AvgPool3d_stride1_pad0_gpu_input_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_AvgPool3d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_BatchNorm1d_3d_input_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/plotting/text_plot.py:469: DeprecationWarning: `mapping.TENSOR_TYPE_TO_NP_TYPE` is now deprecated and will be removed in the next release or so.To silence this warning, please use `helper.{self._future_function}` instead.
return TENSOR_TYPE_TO_NP_TYPE[TensorProto.FLOAT] # pylint: disable=E1101
ERROR
test_BatchNorm2d_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_BatchNorm2d_momentum_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_BatchNorm3d_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_BatchNorm3d_momentum_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_ConstantPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv1d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv1d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv1d_pad1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv1d_pad1size1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv1d_pad2_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv1d_pad2size1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv1d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv2d_depthwise_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv2d_depthwise_padded_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv2d_depthwise_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv2d_depthwise_with_multiplier_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv2d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv2d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv2d_groups_thnn_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv2d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv2d_padding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv2d_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv3d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv3d_dilated_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv3d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv3d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv3d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Conv3d_stride_padding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_ConvTranspose2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_ConvTranspose2d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_ELU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Embedding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Embedding_sparse_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_GLU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_GLU_dim_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_LeakyReLU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_LeakyReLU_with_negval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Linear_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Linear_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_LogSoftmax_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_MaxPool1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_MaxPool1d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_MaxPool1d_stride_padding_dilation_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_MaxPool2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_MaxPool2d_stride_padding_dilation_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_MaxPool3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_MaxPool3d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_MaxPool3d_stride_padding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_PReLU_1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_PReLU_1d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_PReLU_2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_PReLU_2d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_PReLU_3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_PReLU_3d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_PixelShuffle_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_PoissonNLLLLoss_no_reduce_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_ReLU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_ReflectionPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_ReplicationPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_SELU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Sigmoid_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Softmax_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Softmin_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Softplus_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Softsign_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Tanh_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_ZeroPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_log_softmax_dim3_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_log_softmax_lastdim_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_softmax_functional_dim3_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_softmax_lastdim_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_operator_add_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_add_size1_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_add_size1_right_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_add_size1_singleton_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_addconstant_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_addmm_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_basic_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_chunk_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_clip_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_concat2_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_conv_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_convtranspose_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_exp_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_flatten_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_index_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_max_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_maxpool_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_min_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_mm_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_non_float_params_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/plotting/text_plot.py:475: DeprecationWarning: `mapping.TENSOR_TYPE_TO_NP_TYPE` is now deprecated and will be removed in the next release or so.To silence this warning, please use `helper.{self._future_function}` instead.
return TENSOR_TYPE_TO_NP_TYPE[TensorProto.INT64] # pylint: disable=E1101
ERROR
test_operator_pad_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_params_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_permute2_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_pow_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_reduced_mean_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_reduced_mean_keepdim_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_reduced_sum_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_reduced_sum_keepdim_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_repeat_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_repeat_dim_overflow_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_selu_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_sqrt_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_symbolic_override_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_symbolic_override_nested_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_view_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_bvlc_alexnet_cpu (__main__.OnnxBackendRealModelTest) ... ok
test_densenet121_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_densenet121_.*"'
test_densenet121_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_densenet121_.*"'
test_inception_v1_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_inception_.*"'
test_inception_v1_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_inception_.*"'
test_inception_v2_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_inception_.*"'
test_inception_v2_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_inception_.*"'
test_resnet50_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_resnet50_.*"'
test_resnet50_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_resnet50_.*"'
test_shufflenet_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_shufflenet_.*"'
test_shufflenet_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_shufflenet_.*"'
test_squeezenet_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_squeezenet_.*"'
test_squeezenet_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_squeezenet_.*"'
test_vgg19_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_vgg19_.*"'
test_vgg19_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_vgg19_.*"'
test_zfnet512_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_zfnet512_.*"'
test_zfnet512_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_zfnet512_.*"'
test_expand_shape_model1_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_expand_shape_model2_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_expand_shape_model3_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_expand_shape_model4_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_gradient_of_add_and_mul_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
test_gradient_of_add_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
test_sequence_model1_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_sequence_model2_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_sequence_model3_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_sequence_model4_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_sequence_model5_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_sequence_model6_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_sequence_model7_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_sequence_model8_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_shrink_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_sign_model_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_single_relu_model_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_strnorm_model_monday_casesensintive_lower_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_strnorm_model_monday_casesensintive_nochangecase_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_strnorm_model_monday_casesensintive_upper_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_strnorm_model_monday_empty_output_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_strnorm_model_monday_insensintive_upper_twodim_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_strnorm_model_nostopwords_nochangecase_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
======================================================================
ERROR: test_adagrad_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Adagrad(-1) is not a registered function/op
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Adagrad(-1) is not a registered function/op'
opset: domain='ai.onnx.preview.training' version=1
input: name='R' type=dtype('float32') shape=[]
input: name='T' type=dtype('int64') shape=[]
input: name='X' type=dtype('float32') shape=[1]
input: name='G' type=dtype('float32') shape=[1]
input: name='H' type=dtype('float32') shape=[1]
Adagrad[ai.onnx.preview.training](R, T, X, G, H, decay_factor=0.10, epsilon=0.00, norm_coefficient=0.00) -> X_new, H_new
output: name='X_new' type=dtype('float32') shape=[1]
output: name='H_new' type=dtype('float32') shape=[1].
======================================================================
ERROR: test_adagrad_multiple_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Adagrad(-1) is not a registered function/op
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Adagrad(-1) is not a registered function/op'
opset: domain='ai.onnx.preview.training' version=1
input: name='R' type=dtype('float32') shape=[]
input: name='T' type=dtype('int64') shape=[]
input: name='X1' type=dtype('float32') shape=[1]
input: name='X2' type=dtype('float32') shape=[2]
input: name='G1' type=dtype('float32') shape=[1]
input: name='G2' type=dtype('float32') shape=[2]
input: name='H1' type=dtype('float32') shape=[1]
input: name='H2' type=dtype('float32') shape=[2]
Adagrad[ai.onnx.preview.training](R, T, X1, X2, G1, G2, H1, H2, decay_factor=0.10, epsilon=0.00, norm_coefficient=0.00) -> X1_new, X2_new, H1_new, H2_new
output: name='X1_new' type=dtype('float32') shape=[1]
output: name='X2_new' type=dtype('float32') shape=[2]
output: name='H1_new' type=dtype('float32') shape=[1]
output: name='H2_new' type=dtype('float32') shape=[2].
======================================================================
ERROR: test_adam_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Adam(-1) is not a registered function/op
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Adam(-1) is not a registered function/op'
opset: domain='ai.onnx.preview.training' version=1
input: name='R' type=dtype('float32') shape=[]
input: name='T' type=dtype('int64') shape=[]
input: name='X' type=dtype('float32') shape=[2]
input: name='G' type=dtype('float32') shape=[2]
input: name='V' type=dtype('float32') shape=[2]
input: name='H' type=dtype('float32') shape=[2]
Adam[ai.onnx.preview.training](R, T, X, G, V, H, alpha=0.95, beta=0.10, epsilon=0.00, norm_coefficient=0.00) -> X_new, V_new, H_new
output: name='X_new' type=dtype('float32') shape=[2]
output: name='V_new' type=dtype('float32') shape=[2]
output: name='H_new' type=dtype('float32') shape=[2].
======================================================================
ERROR: test_adam_multiple_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Adam(-1) is not a registered function/op
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Adam(-1) is not a registered function/op'
opset: domain='ai.onnx.preview.training' version=1
input: name='R' type=dtype('float32') shape=[]
input: name='T' type=dtype('int64') shape=[]
input: name='X1' type=dtype('float32') shape=[1]
input: name='X2' type=dtype('float32') shape=[2]
input: name='G1' type=dtype('float32') shape=[1]
input: name='G2' type=dtype('float32') shape=[2]
input: name='V1' type=dtype('float32') shape=[1]
input: name='V2' type=dtype('float32') shape=[2]
input: name='H1' type=dtype('float32') shape=[1]
input: name='H2' type=dtype('float32') shape=[2]
Adam[ai.onnx.preview.training](R, T, X1, X2, G1, G2, V1, V2, H1, H2, alpha=0.95, beta=0.85, norm_coefficient=0.00) -> X1_new, X2_new, V1_new, V2_new, H1_new, H2_new
output: name='X1_new' type=dtype('float32') shape=[1]
output: name='X2_new' type=dtype('float32') shape=[2]
output: name='V1_new' type=dtype('float32') shape=[1]
output: name='V2_new' type=dtype('float32') shape=[2]
output: name='H1_new' type=dtype('float32') shape=[1]
output: name='H2_new' type=dtype('float32') shape=[2].
======================================================================
ERROR: test_add_uint8_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(14) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(14) node with name '''
opset: domain='' version=14
input: name='x' type=dtype('uint8') shape=[3, 4, 5]
input: name='y' type=dtype('uint8') shape=[3, 4, 5]
Add(x, y) -> sum
output: name='sum' type=dtype('uint8') shape=[3, 4, 5].
======================================================================
ERROR: test_bitshift_left_uint16_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BitShift(11) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BitShift(11) node with name '''
opset: domain='' version=11
input: name='x' type=dtype('uint16') shape=[3]
input: name='y' type=dtype('uint16') shape=[3]
BitShift(x, y, direction=b'LEFT') -> z
output: name='z' type=dtype('uint16') shape=[3].
======================================================================
ERROR: test_bitshift_right_uint16_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BitShift(11) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BitShift(11) node with name '''
opset: domain='' version=11
input: name='x' type=dtype('uint16') shape=[3]
input: name='y' type=dtype('uint16') shape=[3]
BitShift(x, y, direction=b'RIGHT') -> z
output: name='z' type=dtype('uint16') shape=[3].
======================================================================
ERROR: test_bitwise_and_i16_3d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('int16') shape=[3, 4, 5]
input: name='y' type=dtype('int16') shape=[3, 4, 5]
BitwiseAnd(x, y) -> bitwiseand
output: name='bitwiseand' type=dtype('int16') shape=[3, 4, 5].
======================================================================
ERROR: test_bitwise_and_i32_2d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('int32') shape=[3, 4]
input: name='y' type=dtype('int32') shape=[3, 4]
BitwiseAnd(x, y) -> bitwiseand
output: name='bitwiseand' type=dtype('int32') shape=[3, 4].
======================================================================
ERROR: test_bitwise_and_ui64_bcast_3v1d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('uint64') shape=[3, 4, 5]
input: name='y' type=dtype('uint64') shape=[5]
BitwiseAnd(x, y) -> bitwiseand
output: name='bitwiseand' type=dtype('uint64') shape=[3, 4, 5].
======================================================================
ERROR: test_bitwise_and_ui8_bcast_4v3d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('uint8') shape=[3, 4, 5, 6]
input: name='y' type=dtype('uint8') shape=[4, 5, 6]
BitwiseAnd(x, y) -> bitwiseand
output: name='bitwiseand' type=dtype('uint8') shape=[3, 4, 5, 6].
======================================================================
ERROR: test_bitwise_not_2d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('int32') shape=[3, 4]
BitwiseNot(x) -> bitwise_not
output: name='bitwise_not' type=dtype('int32') shape=[3, 4].
======================================================================
ERROR: test_bitwise_not_3d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('uint16') shape=[3, 4, 5]
BitwiseNot(x) -> bitwise_not
output: name='bitwise_not' type=dtype('uint16') shape=[3, 4, 5].
======================================================================
ERROR: test_bitwise_not_4d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('uint8') shape=[3, 4, 5, 6]
BitwiseNot(x) -> bitwise_not
output: name='bitwise_not' type=dtype('uint8') shape=[3, 4, 5, 6].
======================================================================
ERROR: test_bitwise_or_i16_4d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('int8') shape=[3, 4, 5, 6]
input: name='y' type=dtype('int8') shape=[3, 4, 5, 6]
BitwiseOr(x, y) -> bitwiseor
output: name='bitwiseor' type=dtype('int8') shape=[3, 4, 5, 6].
======================================================================
ERROR: test_bitwise_or_i32_2d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('int32') shape=[3, 4]
input: name='y' type=dtype('int32') shape=[3, 4]
BitwiseOr(x, y) -> bitwiseor
output: name='bitwiseor' type=dtype('int32') shape=[3, 4].
======================================================================
ERROR: test_bitwise_or_ui64_bcast_3v1d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('uint64') shape=[3, 4, 5]
input: name='y' type=dtype('uint64') shape=[5]
BitwiseOr(x, y) -> bitwiseor
output: name='bitwiseor' type=dtype('uint64') shape=[3, 4, 5].
======================================================================
ERROR: test_bitwise_or_ui8_bcast_4v3d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('uint8') shape=[3, 4, 5, 6]
input: name='y' type=dtype('uint8') shape=[4, 5, 6]
BitwiseOr(x, y) -> bitwiseor
output: name='bitwiseor' type=dtype('uint8') shape=[3, 4, 5, 6].
======================================================================
ERROR: test_bitwise_xor_i16_3d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('int16') shape=[3, 4, 5]
input: name='y' type=dtype('int16') shape=[3, 4, 5]
BitwiseXor(x, y) -> bitwisexor
output: name='bitwisexor' type=dtype('int16') shape=[3, 4, 5].
======================================================================
ERROR: test_bitwise_xor_i32_2d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('int32') shape=[3, 4]
input: name='y' type=dtype('int32') shape=[3, 4]
BitwiseXor(x, y) -> bitwisexor
output: name='bitwisexor' type=dtype('int32') shape=[3, 4].
======================================================================
ERROR: test_bitwise_xor_ui64_bcast_3v1d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('uint64') shape=[3, 4, 5]
input: name='y' type=dtype('uint64') shape=[5]
BitwiseXor(x, y) -> bitwisexor
output: name='bitwisexor' type=dtype('uint64') shape=[3, 4, 5].
======================================================================
ERROR: test_bitwise_xor_ui8_bcast_4v3d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('uint8') shape=[3, 4, 5, 6]
input: name='y' type=dtype('uint8') shape=[4, 5, 6]
BitwiseXor(x, y) -> bitwisexor
output: name='bitwisexor' type=dtype('uint8') shape=[3, 4, 5, 6].
======================================================================
ERROR: test_cast_BFLOAT16_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 185, in _init
self.graph_ = self.to_sequence(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 619, in to_sequence
variables[obj.name] = _var_as_dict(obj)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 402, in _var_as_dict
elem_type = _elem_type_as_str(t.elem_type)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 332, in _elem_type_as_str
raise NotImplementedError( # pragma: no cover
NotImplementedError: elem_type '16' is unknown
fields:
['__abs__',
'__add__',
'__and__',
'__bool__',
'__ceil__',
'__class__',
'__delattr__',
'__dir__',
'__divmod__',
'__doc__',
'__eq__',
'__float__',
'__floor__',
'__floordiv__',
'__format__',
'__ge__',
'__getattribute__',
'__getnewargs__',
'__gt__',
'__hash__',
'__index__',
'__init__',
'__init_subclass__',
'__int__',
'__invert__',
'__le__',
'__lshift__',
'__lt__',
'__mod__',
'__mul__',
'__ne__',
'__neg__',
'__new__',
'__or__',
'__pos__',
'__pow__',
'__radd__',
'__rand__',
'__rdivmod__',
'__reduce__',
'__reduce_ex__',
'__repr__',
'__rfloordiv__',
'__rlshift__',
'__rmod__',
'__rmul__',
'__ror__',
'__round__',
'__rpow__',
'__rrshift__',
'__rshift__',
'__rsub__',
'__rtruediv__',
'__rxor__',
'__setattr__',
'__sizeof__',
'__str__',
'__sub__',
'__subclasshook__',
'__truediv__',
'__trunc__',
'__xor__',
'as_integer_ratio',
'bit_length',
'conjugate',
'denominator',
'from_bytes',
'imag',
'numerator',
'real',
'to_bytes']
-----
<class 'int'>.
======================================================================
ERROR: test_cast_FLOAT_to_BFLOAT16_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 185, in _init
self.graph_ = self.to_sequence(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 629, in to_sequence
outputs[obj.name] = _var_as_dict(obj)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 402, in _var_as_dict
elem_type = _elem_type_as_str(t.elem_type)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 332, in _elem_type_as_str
raise NotImplementedError( # pragma: no cover
NotImplementedError: elem_type '16' is unknown
fields:
['__abs__',
'__add__',
'__and__',
'__bool__',
'__ceil__',
'__class__',
'__delattr__',
'__dir__',
'__divmod__',
'__doc__',
'__eq__',
'__float__',
'__floor__',
'__floordiv__',
'__format__',
'__ge__',
'__getattribute__',
'__getnewargs__',
'__gt__',
'__hash__',
'__index__',
'__init__',
'__init_subclass__',
'__int__',
'__invert__',
'__le__',
'__lshift__',
'__lt__',
'__mod__',
'__mul__',
'__ne__',
'__neg__',
'__new__',
'__or__',
'__pos__',
'__pow__',
'__radd__',
'__rand__',
'__rdivmod__',
'__reduce__',
'__reduce_ex__',
'__repr__',
'__rfloordiv__',
'__rlshift__',
'__rmod__',
'__rmul__',
'__ror__',
'__round__',
'__rpow__',
'__rrshift__',
'__rshift__',
'__rsub__',
'__rtruediv__',
'__rxor__',
'__setattr__',
'__sizeof__',
'__str__',
'__sub__',
'__subclasshook__',
'__truediv__',
'__trunc__',
'__xor__',
'as_integer_ratio',
'bit_length',
'conjugate',
'denominator',
'from_bytes',
'imag',
'numerator',
'real',
'to_bytes']
-----
<class 'int'>.
======================================================================
ERROR: test_castlike_BFLOAT16_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 185, in _init
self.graph_ = self.to_sequence(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 619, in to_sequence
variables[obj.name] = _var_as_dict(obj)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 402, in _var_as_dict
elem_type = _elem_type_as_str(t.elem_type)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 332, in _elem_type_as_str
raise NotImplementedError( # pragma: no cover
NotImplementedError: elem_type '16' is unknown
fields:
['__abs__',
'__add__',
'__and__',
'__bool__',
'__ceil__',
'__class__',
'__delattr__',
'__dir__',
'__divmod__',
'__doc__',
'__eq__',
'__float__',
'__floor__',
'__floordiv__',
'__format__',
'__ge__',
'__getattribute__',
'__getnewargs__',
'__gt__',
'__hash__',
'__index__',
'__init__',
'__init_subclass__',
'__int__',
'__invert__',
'__le__',
'__lshift__',
'__lt__',
'__mod__',
'__mul__',
'__ne__',
'__neg__',
'__new__',
'__or__',
'__pos__',
'__pow__',
'__radd__',
'__rand__',
'__rdivmod__',
'__reduce__',
'__reduce_ex__',
'__repr__',
'__rfloordiv__',
'__rlshift__',
'__rmod__',
'__rmul__',
'__ror__',
'__round__',
'__rpow__',
'__rrshift__',
'__rshift__',
'__rsub__',
'__rtruediv__',
'__rxor__',
'__setattr__',
'__sizeof__',
'__str__',
'__sub__',
'__subclasshook__',
'__truediv__',
'__trunc__',
'__xor__',
'as_integer_ratio',
'bit_length',
'conjugate',
'denominator',
'from_bytes',
'imag',
'numerator',
'real',
'to_bytes']
-----
<class 'int'>.
======================================================================
ERROR: test_castlike_BFLOAT16_to_FLOAT_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 185, in _init
self.graph_ = self.to_sequence(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 619, in to_sequence
variables[obj.name] = _var_as_dict(obj)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 402, in _var_as_dict
elem_type = _elem_type_as_str(t.elem_type)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 332, in _elem_type_as_str
raise NotImplementedError( # pragma: no cover
NotImplementedError: elem_type '16' is unknown
fields:
['__abs__',
'__add__',
'__and__',
'__bool__',
'__ceil__',
'__class__',
'__delattr__',
'__dir__',
'__divmod__',
'__doc__',
'__eq__',
'__float__',
'__floor__',
'__floordiv__',
'__format__',
'__ge__',
'__getattribute__',
'__getnewargs__',
'__gt__',
'__hash__',
'__index__',
'__init__',
'__init_subclass__',
'__int__',
'__invert__',
'__le__',
'__lshift__',
'__lt__',
'__mod__',
'__mul__',
'__ne__',
'__neg__',
'__new__',
'__or__',
'__pos__',
'__pow__',
'__radd__',
'__rand__',
'__rdivmod__',
'__reduce__',
'__reduce_ex__',
'__repr__',
'__rfloordiv__',
'__rlshift__',
'__rmod__',
'__rmul__',
'__ror__',
'__round__',
'__rpow__',
'__rrshift__',
'__rshift__',
'__rsub__',
'__rtruediv__',
'__rxor__',
'__setattr__',
'__sizeof__',
'__str__',
'__sub__',
'__subclasshook__',
'__truediv__',
'__trunc__',
'__xor__',
'as_integer_ratio',
'bit_length',
'conjugate',
'denominator',
'from_bytes',
'imag',
'numerator',
'real',
'to_bytes']
-----
<class 'int'>.
======================================================================
ERROR: test_castlike_FLOAT_to_BFLOAT16_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 185, in _init
self.graph_ = self.to_sequence(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 619, in to_sequence
variables[obj.name] = _var_as_dict(obj)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 402, in _var_as_dict
elem_type = _elem_type_as_str(t.elem_type)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 332, in _elem_type_as_str
raise NotImplementedError( # pragma: no cover
NotImplementedError: elem_type '16' is unknown
fields:
['__abs__',
'__add__',
'__and__',
'__bool__',
'__ceil__',
'__class__',
'__delattr__',
'__dir__',
'__divmod__',
'__doc__',
'__eq__',
'__float__',
'__floor__',
'__floordiv__',
'__format__',
'__ge__',
'__getattribute__',
'__getnewargs__',
'__gt__',
'__hash__',
'__index__',
'__init__',
'__init_subclass__',
'__int__',
'__invert__',
'__le__',
'__lshift__',
'__lt__',
'__mod__',
'__mul__',
'__ne__',
'__neg__',
'__new__',
'__or__',
'__pos__',
'__pow__',
'__radd__',
'__rand__',
'__rdivmod__',
'__reduce__',
'__reduce_ex__',
'__repr__',
'__rfloordiv__',
'__rlshift__',
'__rmod__',
'__rmul__',
'__ror__',
'__round__',
'__rpow__',
'__rrshift__',
'__rshift__',
'__rsub__',
'__rtruediv__',
'__rxor__',
'__setattr__',
'__sizeof__',
'__str__',
'__sub__',
'__subclasshook__',
'__truediv__',
'__trunc__',
'__xor__',
'as_integer_ratio',
'bit_length',
'conjugate',
'denominator',
'from_bytes',
'imag',
'numerator',
'real',
'to_bytes']
-----
<class 'int'>.
======================================================================
ERROR: test_castlike_FLOAT_to_BFLOAT16_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 185, in _init
self.graph_ = self.to_sequence(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 619, in to_sequence
variables[obj.name] = _var_as_dict(obj)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 402, in _var_as_dict
elem_type = _elem_type_as_str(t.elem_type)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 332, in _elem_type_as_str
raise NotImplementedError( # pragma: no cover
NotImplementedError: elem_type '16' is unknown
fields:
['__abs__',
'__add__',
'__and__',
'__bool__',
'__ceil__',
'__class__',
'__delattr__',
'__dir__',
'__divmod__',
'__doc__',
'__eq__',
'__float__',
'__floor__',
'__floordiv__',
'__format__',
'__ge__',
'__getattribute__',
'__getnewargs__',
'__gt__',
'__hash__',
'__index__',
'__init__',
'__init_subclass__',
'__int__',
'__invert__',
'__le__',
'__lshift__',
'__lt__',
'__mod__',
'__mul__',
'__ne__',
'__neg__',
'__new__',
'__or__',
'__pos__',
'__pow__',
'__radd__',
'__rand__',
'__rdivmod__',
'__reduce__',
'__reduce_ex__',
'__repr__',
'__rfloordiv__',
'__rlshift__',
'__rmod__',
'__rmul__',
'__ror__',
'__round__',
'__rpow__',
'__rrshift__',
'__rshift__',
'__rsub__',
'__rtruediv__',
'__rxor__',
'__setattr__',
'__sizeof__',
'__str__',
'__sub__',
'__subclasshook__',
'__truediv__',
'__trunc__',
'__xor__',
'as_integer_ratio',
'bit_length',
'conjugate',
'denominator',
'from_bytes',
'imag',
'numerator',
'real',
'to_bytes']
-----
<class 'int'>.
======================================================================
ERROR: test_center_crop_pad_crop_and_pad_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[20, 8, 3]
input: name='shape' type=dtype('int64') shape=[3]
CenterCropPad(x, shape) -> y
output: name='y' type=dtype('float32') shape=[10, 10, 3].
======================================================================
ERROR: test_center_crop_pad_crop_and_pad_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[20, 8, 3]
input: name='shape' type=dtype('int64') shape=[3]
Constant(value=[2]) -> CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_k2
Shape(x) -> CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_x_shape
Max(CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_x_shape, shape) -> CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_padded_sh
Sub(CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_padded_sh, CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_x_shape) -> CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_pad_amount
Div(CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_pad_amount, CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_k2) -> CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_pad_amount_left
Sub(CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_pad_amount, CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_pad_amount_left) -> CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_pad_amount_right
Concat(CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_pad_amount_left, CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_pad_amount_right, axis=0) -> CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_pads
Pad(x, CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_pads) -> CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_padded_input
Shape(CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_padded_input) -> CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_x_shape2
Sub(CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_x_shape2, shape) -> CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_sh_diff
Div(CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_sh_diff, CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_k2) -> CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_start_dims
Add(CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_start_dims, shape) -> CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_end_dims
Slice(CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_padded_input, CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_start_dims, CenterCropPad_test_center_crop_pad_crop_and_pad_expanded_function_end_dims) -> y
output: name='y' type=dtype('float32') shape=[10, 10, 3].
======================================================================
ERROR: test_center_crop_pad_crop_axes_chw_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 20, 8]
input: name='shape' type=dtype('int64') shape=[2]
CenterCropPad(x, shape, axes=[1,2]) -> y
output: name='y' type=dtype('float32') shape=[3, 10, 9].
======================================================================
ERROR: test_center_crop_pad_crop_axes_chw_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 20, 8]
input: name='shape' type=dtype('int64') shape=[2]
Constant(value=[2]) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_k2
Constant(value_ints=[1,2]) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_axes_input
Shape(x) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_x_shape_alldims
Gather(CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_x_shape_alldims, CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_axes_input) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_x_shape
Max(CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_x_shape, shape) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_padded_sh
Sub(CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_padded_sh, CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_x_shape) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_pad_amount
Div(CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_pad_amount, CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_k2) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_pad_amount_left
Sub(CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_pad_amount, CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_pad_amount_left) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_pad_amount_right
Concat(CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_pad_amount_left, CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_pad_amount_right, axis=0) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_pads
Pad(x, CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_pads, , CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_axes_input) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_padded_input
Shape(CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_padded_input) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_x_shape_alldims2
Gather(CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_x_shape_alldims2, CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_axes_input) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_x_shape2
Sub(CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_x_shape2, shape) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_sh_diff
Div(CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_sh_diff, CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_k2) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_start_dims
Add(CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_start_dims, shape) -> CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_end_dims
Slice(CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_padded_input, CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_start_dims, CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_end_dims, CenterCropPad_test_center_crop_pad_crop_axes_chw_expanded_function_axes_input) -> y
output: name='y' type=dtype('float32') shape=[3, 10, 9].
======================================================================
ERROR: test_center_crop_pad_crop_axes_hwc_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[20, 8, 3]
input: name='shape' type=dtype('int64') shape=[2]
CenterCropPad(x, shape, axes=[0,1]) -> y
output: name='y' type=dtype('float32') shape=[10, 9, 3].
======================================================================
ERROR: test_center_crop_pad_crop_axes_hwc_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[20, 8, 3]
input: name='shape' type=dtype('int64') shape=[2]
Constant(value=[2]) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_k2
Constant(value_ints=[0,1]) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_axes_input
Shape(x) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_x_shape_alldims
Gather(CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_x_shape_alldims, CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_axes_input) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_x_shape
Max(CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_x_shape, shape) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_padded_sh
Sub(CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_padded_sh, CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_x_shape) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_pad_amount
Div(CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_pad_amount, CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_k2) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_pad_amount_left
Sub(CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_pad_amount, CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_pad_amount_left) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_pad_amount_right
Concat(CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_pad_amount_left, CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_pad_amount_right, axis=0) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_pads
Pad(x, CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_pads, , CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_axes_input) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_padded_input
Shape(CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_padded_input) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_x_shape_alldims2
Gather(CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_x_shape_alldims2, CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_axes_input) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_x_shape2
Sub(CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_x_shape2, shape) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_sh_diff
Div(CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_sh_diff, CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_k2) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_start_dims
Add(CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_start_dims, shape) -> CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_end_dims
Slice(CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_padded_input, CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_start_dims, CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_end_dims, CenterCropPad_test_center_crop_pad_crop_axes_hwc_expanded_function_axes_input) -> y
output: name='y' type=dtype('float32') shape=[10, 9, 3].
======================================================================
ERROR: test_center_crop_pad_crop_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[20, 10, 3]
input: name='shape' type=dtype('int64') shape=[3]
CenterCropPad(x, shape) -> y
output: name='y' type=dtype('float32') shape=[10, 7, 3].
======================================================================
ERROR: test_center_crop_pad_crop_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[20, 10, 3]
input: name='shape' type=dtype('int64') shape=[3]
Constant(value=[2]) -> CenterCropPad_test_center_crop_pad_crop_expanded_function_k2
Shape(x) -> CenterCropPad_test_center_crop_pad_crop_expanded_function_x_shape
Max(CenterCropPad_test_center_crop_pad_crop_expanded_function_x_shape, shape) -> CenterCropPad_test_center_crop_pad_crop_expanded_function_padded_sh
Sub(CenterCropPad_test_center_crop_pad_crop_expanded_function_padded_sh, CenterCropPad_test_center_crop_pad_crop_expanded_function_x_shape) -> CenterCropPad_test_center_crop_pad_crop_expanded_function_pad_amount
Div(CenterCropPad_test_center_crop_pad_crop_expanded_function_pad_amount, CenterCropPad_test_center_crop_pad_crop_expanded_function_k2) -> CenterCropPad_test_center_crop_pad_crop_expanded_function_pad_amount_left
Sub(CenterCropPad_test_center_crop_pad_crop_expanded_function_pad_amount, CenterCropPad_test_center_crop_pad_crop_expanded_function_pad_amount_left) -> CenterCropPad_test_center_crop_pad_crop_expanded_function_pad_amount_right
Concat(CenterCropPad_test_center_crop_pad_crop_expanded_function_pad_amount_left, CenterCropPad_test_center_crop_pad_crop_expanded_function_pad_amount_right, axis=0) -> CenterCropPad_test_center_crop_pad_crop_expanded_function_pads
Pad(x, CenterCropPad_test_center_crop_pad_crop_expanded_function_pads) -> CenterCropPad_test_center_crop_pad_crop_expanded_function_padded_input
Shape(CenterCropPad_test_center_crop_pad_crop_expanded_function_padded_input) -> CenterCropPad_test_center_crop_pad_crop_expanded_function_x_shape2
Sub(CenterCropPad_test_center_crop_pad_crop_expanded_function_x_shape2, shape) -> CenterCropPad_test_center_crop_pad_crop_expanded_function_sh_diff
Div(CenterCropPad_test_center_crop_pad_crop_expanded_function_sh_diff, CenterCropPad_test_center_crop_pad_crop_expanded_function_k2) -> CenterCropPad_test_center_crop_pad_crop_expanded_function_start_dims
Add(CenterCropPad_test_center_crop_pad_crop_expanded_function_start_dims, shape) -> CenterCropPad_test_center_crop_pad_crop_expanded_function_end_dims
Slice(CenterCropPad_test_center_crop_pad_crop_expanded_function_padded_input, CenterCropPad_test_center_crop_pad_crop_expanded_function_start_dims, CenterCropPad_test_center_crop_pad_crop_expanded_function_end_dims) -> y
output: name='y' type=dtype('float32') shape=[10, 7, 3].
======================================================================
ERROR: test_center_crop_pad_pad_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[10, 7, 3]
input: name='shape' type=dtype('int64') shape=[3]
CenterCropPad(x, shape) -> y
output: name='y' type=dtype('float32') shape=[20, 10, 3].
======================================================================
ERROR: test_center_crop_pad_pad_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[10, 7, 3]
input: name='shape' type=dtype('int64') shape=[3]
Constant(value=[2]) -> CenterCropPad_test_center_crop_pad_pad_expanded_function_k2
Shape(x) -> CenterCropPad_test_center_crop_pad_pad_expanded_function_x_shape
Max(CenterCropPad_test_center_crop_pad_pad_expanded_function_x_shape, shape) -> CenterCropPad_test_center_crop_pad_pad_expanded_function_padded_sh
Sub(CenterCropPad_test_center_crop_pad_pad_expanded_function_padded_sh, CenterCropPad_test_center_crop_pad_pad_expanded_function_x_shape) -> CenterCropPad_test_center_crop_pad_pad_expanded_function_pad_amount
Div(CenterCropPad_test_center_crop_pad_pad_expanded_function_pad_amount, CenterCropPad_test_center_crop_pad_pad_expanded_function_k2) -> CenterCropPad_test_center_crop_pad_pad_expanded_function_pad_amount_left
Sub(CenterCropPad_test_center_crop_pad_pad_expanded_function_pad_amount, CenterCropPad_test_center_crop_pad_pad_expanded_function_pad_amount_left) -> CenterCropPad_test_center_crop_pad_pad_expanded_function_pad_amount_right
Concat(CenterCropPad_test_center_crop_pad_pad_expanded_function_pad_amount_left, CenterCropPad_test_center_crop_pad_pad_expanded_function_pad_amount_right, axis=0) -> CenterCropPad_test_center_crop_pad_pad_expanded_function_pads
Pad(x, CenterCropPad_test_center_crop_pad_pad_expanded_function_pads) -> CenterCropPad_test_center_crop_pad_pad_expanded_function_padded_input
Shape(CenterCropPad_test_center_crop_pad_pad_expanded_function_padded_input) -> CenterCropPad_test_center_crop_pad_pad_expanded_function_x_shape2
Sub(CenterCropPad_test_center_crop_pad_pad_expanded_function_x_shape2, shape) -> CenterCropPad_test_center_crop_pad_pad_expanded_function_sh_diff
Div(CenterCropPad_test_center_crop_pad_pad_expanded_function_sh_diff, CenterCropPad_test_center_crop_pad_pad_expanded_function_k2) -> CenterCropPad_test_center_crop_pad_pad_expanded_function_start_dims
Add(CenterCropPad_test_center_crop_pad_pad_expanded_function_start_dims, shape) -> CenterCropPad_test_center_crop_pad_pad_expanded_function_end_dims
Slice(CenterCropPad_test_center_crop_pad_pad_expanded_function_padded_input, CenterCropPad_test_center_crop_pad_pad_expanded_function_start_dims, CenterCropPad_test_center_crop_pad_pad_expanded_function_end_dims) -> y
output: name='y' type=dtype('float32') shape=[20, 10, 3].
======================================================================
ERROR: test_clip_default_int8_max_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Less(13) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Less(13) node with name '''
opset: domain='' version=13
input: name='x' type=dtype('int8') shape=[3, 4, 5]
input: name='max' type=dtype('int8') shape=[]
Less(max, x) -> Clip_test_clip_default_int8_max_expanded_function_input_large_than_max
Where(Clip_test_clip_default_int8_max_expanded_function_input_large_than_max, max, x) -> y
output: name='y' type=dtype('int8') shape=[3, 4, 5].
======================================================================
ERROR: test_clip_default_int8_min_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Less(13) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Less(13) node with name '''
opset: domain='' version=13
input: name='x' type=dtype('int8') shape=[3, 4, 5]
input: name='min' type=dtype('int8') shape=[]
Less(x, min) -> Clip_test_clip_default_int8_min_expanded_function_input_less_than_min
Where(Clip_test_clip_default_int8_min_expanded_function_input_less_than_min, min, x) -> y
output: name='y' type=dtype('int8') shape=[3, 4, 5].
======================================================================
ERROR: test_col2im_5d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[1, 10, 12]
input: name='image_shape' type=dtype('int64') shape=[3]
input: name='block_shape' type=dtype('int64') shape=[3]
Col2Im(input, image_shape, block_shape) -> output
output: name='output' type=dtype('float32') shape=[1, 2, 3, 4, 5].
======================================================================
ERROR: test_col2im_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[1, 5, 5]
input: name='image_shape' type=dtype('int64') shape=[2]
input: name='block_shape' type=dtype('int64') shape=[2]
Col2Im(input, image_shape, block_shape) -> output
output: name='output' type=dtype('float32') shape=[1, 1, 5, 5].
======================================================================
ERROR: test_col2im_dilations_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[1, 4, 5]
input: name='image_shape' type=dtype('int64') shape=[2]
input: name='block_shape' type=dtype('int64') shape=[2]
Col2Im(input, image_shape, block_shape, dilations=[1,5]) -> output
output: name='output' type=dtype('float32') shape=[1, 1, 6, 6].
======================================================================
ERROR: test_col2im_pads_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[1, 5, 15]
input: name='image_shape' type=dtype('int64') shape=[2]
input: name='block_shape' type=dtype('int64') shape=[2]
Col2Im(input, image_shape, block_shape, pads=[0,1,0,1]) -> output
output: name='output' type=dtype('float32') shape=[1, 1, 5, 5].
======================================================================
ERROR: test_col2im_strides_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[1, 9, 4]
input: name='image_shape' type=dtype('int64') shape=[2]
input: name='block_shape' type=dtype('int64') shape=[2]
Col2Im(input, image_shape, block_shape, strides=[2,2]) -> output
output: name='output' type=dtype('float32') shape=[1, 1, 5, 5].
======================================================================
ERROR: test_constant_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 107, in run
v = next(iter(inputs.values()))
StopIteration
======================================================================
ERROR: test_constant_pad_axes_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[1, 3, 4, 5]
input: name='pads' type=dtype('int64') shape=[4]
input: name='value' type=dtype('float32') shape=[]
input: name='axes' type=dtype('int64') shape=[2]
Pad(x, pads, value, axes, mode=b'constant') -> y
output: name='y' type=dtype('float32') shape=[1, 3, 4, 12].
======================================================================
ERROR: test_constant_pad_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[1, 3, 4, 5]
input: name='pads' type=dtype('int64') shape=[8]
input: name='value' type=dtype('float32') shape=[]
Pad(x, pads, value, mode=b'constant') -> y
output: name='y' type=dtype('float32') shape=[1, 3, 7, 12].
======================================================================
ERROR: test_div_uint8_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Div(14) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Div(14) node with name '''
opset: domain='' version=14
input: name='x' type=dtype('uint8') shape=[3, 4, 5]
input: name='y' type=dtype('uint8') shape=[3, 4, 5]
Div(x, y) -> z
output: name='z' type=dtype('uint8') shape=[3, 4, 5].
======================================================================
ERROR: test_edge_pad_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('int32') shape=[1, 3, 4, 5]
input: name='pads' type=dtype('int64') shape=[8]
Pad(x, pads, mode=b'edge') -> y
output: name='y' type=dtype('int32') shape=[1, 3, 6, 7].
======================================================================
ERROR: test_elu_default_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value_float=1.0) -> Elu_test_elu_default_expanded_function_Alpha
CastLike(Elu_test_elu_default_expanded_function_Alpha, x) -> Elu_test_elu_default_expanded_function_AlphaCast
Constant(value=0.0) -> Elu_test_elu_default_expanded_function_Zero
CastLike(Elu_test_elu_default_expanded_function_Zero, x) -> Elu_test_elu_default_expanded_function_ZeroCast
Less(x, Elu_test_elu_default_expanded_function_ZeroCast) -> Elu_test_elu_default_expanded_function_XLessThanZero
Constant(value=1.0) -> Elu_test_elu_default_expanded_function_One
CastLike(Elu_test_elu_default_expanded_function_One, x) -> Elu_test_elu_default_expanded_function_OneCast
Exp(x) -> Elu_test_elu_default_expanded_function_ExpX
Sub(Elu_test_elu_default_expanded_function_ExpX, Elu_test_elu_default_expanded_function_OneCast) -> Elu_test_elu_default_expanded_function_ExpXSubOne
Mul(Elu_test_elu_default_expanded_function_AlphaCast, Elu_test_elu_default_expanded_function_ExpXSubOne) -> Elu_test_elu_default_expanded_function_AlphaMulExpXSubOne
Where(Elu_test_elu_default_expanded_function_XLessThanZero, Elu_test_elu_default_expanded_function_AlphaMulExpXSubOne, x) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_elu_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3]
Constant(value_float=2.0) -> Elu_test_elu_example_expanded_function_Alpha
CastLike(Elu_test_elu_example_expanded_function_Alpha, x) -> Elu_test_elu_example_expanded_function_AlphaCast
Constant(value=0.0) -> Elu_test_elu_example_expanded_function_Zero
CastLike(Elu_test_elu_example_expanded_function_Zero, x) -> Elu_test_elu_example_expanded_function_ZeroCast
Less(x, Elu_test_elu_example_expanded_function_ZeroCast) -> Elu_test_elu_example_expanded_function_XLessThanZero
Constant(value=1.0) -> Elu_test_elu_example_expanded_function_One
CastLike(Elu_test_elu_example_expanded_function_One, x) -> Elu_test_elu_example_expanded_function_OneCast
Exp(x) -> Elu_test_elu_example_expanded_function_ExpX
Sub(Elu_test_elu_example_expanded_function_ExpX, Elu_test_elu_example_expanded_function_OneCast) -> Elu_test_elu_example_expanded_function_ExpXSubOne
Mul(Elu_test_elu_example_expanded_function_AlphaCast, Elu_test_elu_example_expanded_function_ExpXSubOne) -> Elu_test_elu_example_expanded_function_AlphaMulExpXSubOne
Where(Elu_test_elu_example_expanded_function_XLessThanZero, Elu_test_elu_example_expanded_function_AlphaMulExpXSubOne, x) -> y
output: name='y' type=dtype('float32') shape=[3].
======================================================================
ERROR: test_elu_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value_float=2.0) -> Elu_test_elu_expanded_function_Alpha
CastLike(Elu_test_elu_expanded_function_Alpha, x) -> Elu_test_elu_expanded_function_AlphaCast
Constant(value=0.0) -> Elu_test_elu_expanded_function_Zero
CastLike(Elu_test_elu_expanded_function_Zero, x) -> Elu_test_elu_expanded_function_ZeroCast
Less(x, Elu_test_elu_expanded_function_ZeroCast) -> Elu_test_elu_expanded_function_XLessThanZero
Constant(value=1.0) -> Elu_test_elu_expanded_function_One
CastLike(Elu_test_elu_expanded_function_One, x) -> Elu_test_elu_expanded_function_OneCast
Exp(x) -> Elu_test_elu_expanded_function_ExpX
Sub(Elu_test_elu_expanded_function_ExpX, Elu_test_elu_expanded_function_OneCast) -> Elu_test_elu_expanded_function_ExpXSubOne
Mul(Elu_test_elu_expanded_function_AlphaCast, Elu_test_elu_expanded_function_ExpXSubOne) -> Elu_test_elu_expanded_function_AlphaMulExpXSubOne
Where(Elu_test_elu_expanded_function_XLessThanZero, Elu_test_elu_expanded_function_AlphaMulExpXSubOne, x) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_group_normalization_epsilon_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 2, 2]
input: name='scale' type=dtype('float32') shape=[2]
input: name='bias' type=dtype('float32') shape=[2]
GroupNormalization(x, scale, bias, epsilon=0.01, num_groups=2) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 2, 2].
======================================================================
ERROR: test_group_normalization_epsilon_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 2, 2]
input: name='scale' type=dtype('float32') shape=[2]
input: name='bias' type=dtype('float32') shape=[2]
Cast(scale, to=1) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_ScaleT
Constant(value=[0.0099999...) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_FloatEpsilon
Cast(GroupNormalization_test_group_normalization_epsilon_expanded_function_FloatEpsilon, to=1) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_Epsilon
Shape(x) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_XShape
Shape(x, start=1, end=2) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_C
Constant(value=[2]) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_NumGroups
Div(GroupNormalization_test_group_normalization_epsilon_expanded_function_C, GroupNormalization_test_group_normalization_epsilon_expanded_function_NumGroups) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_GroupSize
Shape(x, start=0, end=1) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_N
Shape(x, start=2) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_InstanceShape
Concat(GroupNormalization_test_group_normalization_epsilon_expanded_function_N, GroupNormalization_test_group_normalization_epsilon_expanded_function_NumGroups, GroupNormalization_test_group_normalization_epsilon_expanded_function_GroupSize, GroupNormalization_test_group_normalization_epsilon_expanded_function_InstanceShape, axis=0) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_NewShape
Reshape(x, GroupNormalization_test_group_normalization_epsilon_expanded_function_NewShape) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_XReshaped
Constant(value_ints=[0,0,-1]) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_Shape3D
Reshape(GroupNormalization_test_group_normalization_epsilon_expanded_function_XReshaped, GroupNormalization_test_group_normalization_epsilon_expanded_function_Shape3D) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_X3D
Mul(GroupNormalization_test_group_normalization_epsilon_expanded_function_X3D, GroupNormalization_test_group_normalization_epsilon_expanded_function_X3D) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_Square
Constant(value=[2]) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_Axes2
ReduceMean(GroupNormalization_test_group_normalization_epsilon_expanded_function_X3D, GroupNormalization_test_group_normalization_epsilon_expanded_function_Axes2) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_Mean
Mul(GroupNormalization_test_group_normalization_epsilon_expanded_function_Mean, GroupNormalization_test_group_normalization_epsilon_expanded_function_Mean) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_SquareOfMean
ReduceMean(GroupNormalization_test_group_normalization_epsilon_expanded_function_Square, GroupNormalization_test_group_normalization_epsilon_expanded_function_Axes2) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_MeanOfSquare
Sub(GroupNormalization_test_group_normalization_epsilon_expanded_function_MeanOfSquare, GroupNormalization_test_group_normalization_epsilon_expanded_function_SquareOfMean) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_Var
Add(GroupNormalization_test_group_normalization_epsilon_expanded_function_Var, GroupNormalization_test_group_normalization_epsilon_expanded_function_Epsilon) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_VarPlusEpsilon
Sqrt(GroupNormalization_test_group_normalization_epsilon_expanded_function_VarPlusEpsilon) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_StdDev
Sub(GroupNormalization_test_group_normalization_epsilon_expanded_function_X3D, GroupNormalization_test_group_normalization_epsilon_expanded_function_Mean) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_Deviation
Div(GroupNormalization_test_group_normalization_epsilon_expanded_function_Deviation, GroupNormalization_test_group_normalization_epsilon_expanded_function_StdDev) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_Normalized
Constant(value_ints=[1,-1,1]) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_ScaleShape
Reshape(GroupNormalization_test_group_normalization_epsilon_expanded_function_ScaleT, GroupNormalization_test_group_normalization_epsilon_expanded_function_ScaleShape) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_ScaleReshaped
Mul(GroupNormalization_test_group_normalization_epsilon_expanded_function_ScaleReshaped, GroupNormalization_test_group_normalization_epsilon_expanded_function_Normalized) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_Scaled
Cast(bias, to=1) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_BiasT
Reshape(GroupNormalization_test_group_normalization_epsilon_expanded_function_BiasT, GroupNormalization_test_group_normalization_epsilon_expanded_function_ScaleShape) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_BiasReshaped
Add(GroupNormalization_test_group_normalization_epsilon_expanded_function_Scaled, GroupNormalization_test_group_normalization_epsilon_expanded_function_BiasReshaped) -> GroupNormalization_test_group_normalization_epsilon_expanded_function_Biased
Reshape(GroupNormalization_test_group_normalization_epsilon_expanded_function_Biased, GroupNormalization_test_group_normalization_epsilon_expanded_function_XShape) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 2, 2].
======================================================================
ERROR: test_group_normalization_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 2, 2]
input: name='scale' type=dtype('float32') shape=[2]
input: name='bias' type=dtype('float32') shape=[2]
GroupNormalization(x, scale, bias, num_groups=2) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 2, 2].
======================================================================
ERROR: test_group_normalization_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 2, 2]
input: name='scale' type=dtype('float32') shape=[2]
input: name='bias' type=dtype('float32') shape=[2]
Cast(scale, to=1) -> GroupNormalization_test_group_normalization_example_expanded_function_ScaleT
Constant(value=[9.9999997...) -> GroupNormalization_test_group_normalization_example_expanded_function_FloatEpsilon
Cast(GroupNormalization_test_group_normalization_example_expanded_function_FloatEpsilon, to=1) -> GroupNormalization_test_group_normalization_example_expanded_function_Epsilon
Shape(x) -> GroupNormalization_test_group_normalization_example_expanded_function_XShape
Shape(x, start=1, end=2) -> GroupNormalization_test_group_normalization_example_expanded_function_C
Constant(value=[2]) -> GroupNormalization_test_group_normalization_example_expanded_function_NumGroups
Div(GroupNormalization_test_group_normalization_example_expanded_function_C, GroupNormalization_test_group_normalization_example_expanded_function_NumGroups) -> GroupNormalization_test_group_normalization_example_expanded_function_GroupSize
Shape(x, start=0, end=1) -> GroupNormalization_test_group_normalization_example_expanded_function_N
Shape(x, start=2) -> GroupNormalization_test_group_normalization_example_expanded_function_InstanceShape
Concat(GroupNormalization_test_group_normalization_example_expanded_function_N, GroupNormalization_test_group_normalization_example_expanded_function_NumGroups, GroupNormalization_test_group_normalization_example_expanded_function_GroupSize, GroupNormalization_test_group_normalization_example_expanded_function_InstanceShape, axis=0) -> GroupNormalization_test_group_normalization_example_expanded_function_NewShape
Reshape(x, GroupNormalization_test_group_normalization_example_expanded_function_NewShape) -> GroupNormalization_test_group_normalization_example_expanded_function_XReshaped
Constant(value_ints=[0,0,-1]) -> GroupNormalization_test_group_normalization_example_expanded_function_Shape3D
Reshape(GroupNormalization_test_group_normalization_example_expanded_function_XReshaped, GroupNormalization_test_group_normalization_example_expanded_function_Shape3D) -> GroupNormalization_test_group_normalization_example_expanded_function_X3D
Mul(GroupNormalization_test_group_normalization_example_expanded_function_X3D, GroupNormalization_test_group_normalization_example_expanded_function_X3D) -> GroupNormalization_test_group_normalization_example_expanded_function_Square
Constant(value=[2]) -> GroupNormalization_test_group_normalization_example_expanded_function_Axes2
ReduceMean(GroupNormalization_test_group_normalization_example_expanded_function_X3D, GroupNormalization_test_group_normalization_example_expanded_function_Axes2) -> GroupNormalization_test_group_normalization_example_expanded_function_Mean
Mul(GroupNormalization_test_group_normalization_example_expanded_function_Mean, GroupNormalization_test_group_normalization_example_expanded_function_Mean) -> GroupNormalization_test_group_normalization_example_expanded_function_SquareOfMean
ReduceMean(GroupNormalization_test_group_normalization_example_expanded_function_Square, GroupNormalization_test_group_normalization_example_expanded_function_Axes2) -> GroupNormalization_test_group_normalization_example_expanded_function_MeanOfSquare
Sub(GroupNormalization_test_group_normalization_example_expanded_function_MeanOfSquare, GroupNormalization_test_group_normalization_example_expanded_function_SquareOfMean) -> GroupNormalization_test_group_normalization_example_expanded_function_Var
Add(GroupNormalization_test_group_normalization_example_expanded_function_Var, GroupNormalization_test_group_normalization_example_expanded_function_Epsilon) -> GroupNormalization_test_group_normalization_example_expanded_function_VarPlusEpsilon
Sqrt(GroupNormalization_test_group_normalization_example_expanded_function_VarPlusEpsilon) -> GroupNormalization_test_group_normalization_example_expanded_function_StdDev
Sub(GroupNormalization_test_group_normalization_example_expanded_function_X3D, GroupNormalization_test_group_normalization_example_expanded_function_Mean) -> GroupNormalization_test_group_normalization_example_expanded_function_Deviation
Div(GroupNormalization_test_group_normalization_example_expanded_function_Deviation, GroupNormalization_test_group_normalization_example_expanded_function_StdDev) -> GroupNormalization_test_group_normalization_example_expanded_function_Normalized
Constant(value_ints=[1,-1,1]) -> GroupNormalization_test_group_normalization_example_expanded_function_ScaleShape
Reshape(GroupNormalization_test_group_normalization_example_expanded_function_ScaleT, GroupNormalization_test_group_normalization_example_expanded_function_ScaleShape) -> GroupNormalization_test_group_normalization_example_expanded_function_ScaleReshaped
Mul(GroupNormalization_test_group_normalization_example_expanded_function_ScaleReshaped, GroupNormalization_test_group_normalization_example_expanded_function_Normalized) -> GroupNormalization_test_group_normalization_example_expanded_function_Scaled
Cast(bias, to=1) -> GroupNormalization_test_group_normalization_example_expanded_function_BiasT
Reshape(GroupNormalization_test_group_normalization_example_expanded_function_BiasT, GroupNormalization_test_group_normalization_example_expanded_function_ScaleShape) -> GroupNormalization_test_group_normalization_example_expanded_function_BiasReshaped
Add(GroupNormalization_test_group_normalization_example_expanded_function_Scaled, GroupNormalization_test_group_normalization_example_expanded_function_BiasReshaped) -> GroupNormalization_test_group_normalization_example_expanded_function_Biased
Reshape(GroupNormalization_test_group_normalization_example_expanded_function_Biased, GroupNormalization_test_group_normalization_example_expanded_function_XShape) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 2, 2].
======================================================================
ERROR: test_gru_batchwise_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.RuntimeException: [ONNXRuntimeError] : 6 : RUNTIME_EXCEPTION : Exception during initialization: /onnxruntime_src/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.h:55 onnxruntime::DeepCpuGruOp::DeepCpuGruOp(const onnxruntime::OpKernelInfo&) layout_ == 0 was false. Batchwise recurrent operations (layout == 1) are not supported. If you need support create a github issue with justification.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 6 : RUNTIME_EXCEPTION : Exception during initialization: /onnxruntime_src/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.h:55 onnxruntime::DeepCpuGruOp::DeepCpuGruOp(const onnxruntime::OpKernelInfo&) layout_ == 0 was false. Batchwise recurrent operations (layout == 1) are not supported. If you need support create a github issue with justification.
'
opset: domain='' version=14
input: name='X' type=dtype('float32') shape=[3, 1, 2]
input: name='W' type=dtype('float32') shape=[1, 18, 2]
input: name='R' type=dtype('float32') shape=[1, 18, 6]
GRU(X, W, R, hidden_size=6, layout=1) -> Y, Y_h
output: name='Y' type=dtype('float32') shape=[3, 1, 1, 6]
output: name='Y_h' type=dtype('float32') shape=[3, 1, 6].
======================================================================
ERROR: test_hardsigmoid_default_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value_float=0.20000000298023224) -> HardSigmoid_test_hardsigmoid_default_expanded_function_Alpha
CastLike(HardSigmoid_test_hardsigmoid_default_expanded_function_Alpha, x) -> HardSigmoid_test_hardsigmoid_default_expanded_function_AlphaCast
Mul(x, HardSigmoid_test_hardsigmoid_default_expanded_function_AlphaCast) -> HardSigmoid_test_hardsigmoid_default_expanded_function_AlphaMulX
Constant(value_float=0.5) -> HardSigmoid_test_hardsigmoid_default_expanded_function_Beta
CastLike(HardSigmoid_test_hardsigmoid_default_expanded_function_Beta, x) -> HardSigmoid_test_hardsigmoid_default_expanded_function_BetaCast
Add(HardSigmoid_test_hardsigmoid_default_expanded_function_AlphaMulX, HardSigmoid_test_hardsigmoid_default_expanded_function_BetaCast) -> HardSigmoid_test_hardsigmoid_default_expanded_function_AlphaMulXAddBeta
Constant(value=0.0) -> HardSigmoid_test_hardsigmoid_default_expanded_function_Zero
CastLike(HardSigmoid_test_hardsigmoid_default_expanded_function_Zero, x) -> HardSigmoid_test_hardsigmoid_default_expanded_function_ZeroCast
Constant(value=1.0) -> HardSigmoid_test_hardsigmoid_default_expanded_function_One
CastLike(HardSigmoid_test_hardsigmoid_default_expanded_function_One, x) -> HardSigmoid_test_hardsigmoid_default_expanded_function_OneCast
Min(HardSigmoid_test_hardsigmoid_default_expanded_function_AlphaMulXAddBeta, HardSigmoid_test_hardsigmoid_default_expanded_function_OneCast) -> HardSigmoid_test_hardsigmoid_default_expanded_function_MinOneOrAlphaMulXAddBeta
Max(HardSigmoid_test_hardsigmoid_default_expanded_function_MinOneOrAlphaMulXAddBeta, HardSigmoid_test_hardsigmoid_default_expanded_function_ZeroCast) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_hardsigmoid_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3]
Constant(value_float=0.5) -> HardSigmoid_test_hardsigmoid_example_expanded_function_Alpha
CastLike(HardSigmoid_test_hardsigmoid_example_expanded_function_Alpha, x) -> HardSigmoid_test_hardsigmoid_example_expanded_function_AlphaCast
Mul(x, HardSigmoid_test_hardsigmoid_example_expanded_function_AlphaCast) -> HardSigmoid_test_hardsigmoid_example_expanded_function_AlphaMulX
Constant(value_float=0.6000000238418579) -> HardSigmoid_test_hardsigmoid_example_expanded_function_Beta
CastLike(HardSigmoid_test_hardsigmoid_example_expanded_function_Beta, x) -> HardSigmoid_test_hardsigmoid_example_expanded_function_BetaCast
Add(HardSigmoid_test_hardsigmoid_example_expanded_function_AlphaMulX, HardSigmoid_test_hardsigmoid_example_expanded_function_BetaCast) -> HardSigmoid_test_hardsigmoid_example_expanded_function_AlphaMulXAddBeta
Constant(value=0.0) -> HardSigmoid_test_hardsigmoid_example_expanded_function_Zero
CastLike(HardSigmoid_test_hardsigmoid_example_expanded_function_Zero, x) -> HardSigmoid_test_hardsigmoid_example_expanded_function_ZeroCast
Constant(value=1.0) -> HardSigmoid_test_hardsigmoid_example_expanded_function_One
CastLike(HardSigmoid_test_hardsigmoid_example_expanded_function_One, x) -> HardSigmoid_test_hardsigmoid_example_expanded_function_OneCast
Min(HardSigmoid_test_hardsigmoid_example_expanded_function_AlphaMulXAddBeta, HardSigmoid_test_hardsigmoid_example_expanded_function_OneCast) -> HardSigmoid_test_hardsigmoid_example_expanded_function_MinOneOrAlphaMulXAddBeta
Max(HardSigmoid_test_hardsigmoid_example_expanded_function_MinOneOrAlphaMulXAddBeta, HardSigmoid_test_hardsigmoid_example_expanded_function_ZeroCast) -> y
output: name='y' type=dtype('float32') shape=[3].
======================================================================
ERROR: test_hardsigmoid_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value_float=0.5) -> HardSigmoid_test_hardsigmoid_expanded_function_Alpha
CastLike(HardSigmoid_test_hardsigmoid_expanded_function_Alpha, x) -> HardSigmoid_test_hardsigmoid_expanded_function_AlphaCast
Mul(x, HardSigmoid_test_hardsigmoid_expanded_function_AlphaCast) -> HardSigmoid_test_hardsigmoid_expanded_function_AlphaMulX
Constant(value_float=0.6000000238418579) -> HardSigmoid_test_hardsigmoid_expanded_function_Beta
CastLike(HardSigmoid_test_hardsigmoid_expanded_function_Beta, x) -> HardSigmoid_test_hardsigmoid_expanded_function_BetaCast
Add(HardSigmoid_test_hardsigmoid_expanded_function_AlphaMulX, HardSigmoid_test_hardsigmoid_expanded_function_BetaCast) -> HardSigmoid_test_hardsigmoid_expanded_function_AlphaMulXAddBeta
Constant(value=0.0) -> HardSigmoid_test_hardsigmoid_expanded_function_Zero
CastLike(HardSigmoid_test_hardsigmoid_expanded_function_Zero, x) -> HardSigmoid_test_hardsigmoid_expanded_function_ZeroCast
Constant(value=1.0) -> HardSigmoid_test_hardsigmoid_expanded_function_One
CastLike(HardSigmoid_test_hardsigmoid_expanded_function_One, x) -> HardSigmoid_test_hardsigmoid_expanded_function_OneCast
Min(HardSigmoid_test_hardsigmoid_expanded_function_AlphaMulXAddBeta, HardSigmoid_test_hardsigmoid_expanded_function_OneCast) -> HardSigmoid_test_hardsigmoid_expanded_function_MinOneOrAlphaMulXAddBeta
Max(HardSigmoid_test_hardsigmoid_expanded_function_MinOneOrAlphaMulXAddBeta, HardSigmoid_test_hardsigmoid_expanded_function_ZeroCast) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_identity_opt_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 185, in _init
self.graph_ = self.to_sequence(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 619, in to_sequence
variables[obj.name] = _var_as_dict(obj)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 459, in _var_as_dict
dtype['optional'] = _var_as_dict(optional)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 558, in _var_as_dict
return dict(optional=True, elem_type=_var_as_dict(var.elem_type))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 553, in _var_as_dict
d[n] = _var_as_dict(at)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 560, in _var_as_dict
raise NotImplementedError( # pragma: no cover
NotImplementedError: Unable to guess which object it is type is <class 'onnx.onnx_ml_pb2.Sequence'> value is 'elem_type {\n tensor_type {\n elem_type: 1\n shape {\n dim {\n dim_value: 5\n }\n }\n }\n}\n' (hasattr(var,'type')=False, var.type=None
ByteSize
Clear
ClearExtension
ClearField
CopyFrom
DESCRIPTOR
DiscardUnknownFields
Extensions
FindInitializationErrors
FromString
HasExtension
HasField
IsInitialized
ListFields
MergeFrom
MergeFromString
ParseFromString
RegisterExtension
SerializePartialToString
SerializeToString
SetInParent
UnknownFields
WhichOneof
_CheckCalledFromGeneratedFile
_SetListener
__class__
__deepcopy__
__delattr__
__dir__
__doc__
__eq__
__format__
__ge__
__getattribute__
__getstate__
__gt__
__hash__
__init__
__init_subclass__
__le__
__lt__
__module__
__ne__
__new__
__reduce__
__reduce_ex__
__repr__
__setattr__
__setstate__
__sizeof__
__slots__
__str__
__subclasshook__
__unicode__
_extensions_by_name
_extensions_by_number
elem_type
======================================================================
ERROR: test_identity_sequence_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_if_opt_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 185, in _init
self.graph_ = self.to_sequence(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 629, in to_sequence
outputs[obj.name] = _var_as_dict(obj)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 459, in _var_as_dict
dtype['optional'] = _var_as_dict(optional)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 558, in _var_as_dict
return dict(optional=True, elem_type=_var_as_dict(var.elem_type))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 553, in _var_as_dict
d[n] = _var_as_dict(at)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 560, in _var_as_dict
raise NotImplementedError( # pragma: no cover
NotImplementedError: Unable to guess which object it is type is <class 'onnx.onnx_ml_pb2.Sequence'> value is 'elem_type {\n tensor_type {\n elem_type: 1\n shape {\n dim {\n dim_value: 5\n }\n }\n }\n}\n' (hasattr(var,'type')=False, var.type=None
ByteSize
Clear
ClearExtension
ClearField
CopyFrom
DESCRIPTOR
DiscardUnknownFields
Extensions
FindInitializationErrors
FromString
HasExtension
HasField
IsInitialized
ListFields
MergeFrom
MergeFromString
ParseFromString
RegisterExtension
SerializePartialToString
SerializeToString
SetInParent
UnknownFields
WhichOneof
_CheckCalledFromGeneratedFile
_SetListener
__class__
__deepcopy__
__delattr__
__dir__
__doc__
__eq__
__format__
__ge__
__getattribute__
__getstate__
__gt__
__hash__
__init__
__init_subclass__
__le__
__lt__
__module__
__ne__
__new__
__reduce__
__reduce_ex__
__repr__
__setattr__
__setstate__
__sizeof__
__slots__
__str__
__subclasshook__
__unicode__
_extensions_by_name
_extensions_by_number
elem_type
======================================================================
ERROR: test_layer_normalization_2d_axis0_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[3, 4]
input: name='W' type=dtype('float32') shape=[3, 4]
input: name='B' type=dtype('float32') shape=[3, 4]
Constant(value=9.99999974...) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Zero1D
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_XShape, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_PrefixShape
Sub(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Rank, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_ReducedShape
Flatten(X, axis=0) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_XU, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_XU) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_XU, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Square, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Var, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_XU, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Deviation, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Scaled, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Biased, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_2d_axis0_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[3, 4]
output: name='Mean' type=dtype('float32') shape=[1, 1]
output: name='InvStdDev' type=dtype('float32') shape=[1, 1].
======================================================================
ERROR: test_layer_normalization_2d_axis1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[3, 4]
input: name='W' type=dtype('float32') shape=[4]
input: name='B' type=dtype('float32') shape=[4]
Constant(value=9.99999974...) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Zero1D
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_XShape, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_PrefixShape
Sub(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Rank, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_ReducedShape
Flatten(X, axis=1) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_XU, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_XU) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_XU, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Square, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Var, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_XU, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Deviation, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Scaled, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Biased, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_2d_axis1_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[3, 4]
output: name='Mean' type=dtype('float32') shape=[3, 1]
output: name='InvStdDev' type=dtype('float32') shape=[3, 1].
======================================================================
ERROR: test_layer_normalization_2d_axis_negative_1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[3, 4]
input: name='W' type=dtype('float32') shape=[4]
input: name='B' type=dtype('float32') shape=[4]
Constant(value=9.99999974...) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Zero1D
Constant(value=[-1]) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_XShape, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_PrefixShape
Neg(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_ReducedShape
Flatten(X, axis=-1) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_XU, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_XU) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_XU, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Square, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Var, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_XU, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Deviation, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Scaled, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Biased, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_2d_axis_negative_1_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[3, 4]
output: name='Mean' type=dtype('float32') shape=[3, 1]
output: name='InvStdDev' type=dtype('float32') shape=[3, 1].
======================================================================
ERROR: test_layer_normalization_2d_axis_negative_2_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[3, 4]
input: name='W' type=dtype('float32') shape=[3, 4]
input: name='B' type=dtype('float32') shape=[3, 4]
Constant(value=9.99999974...) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Zero1D
Constant(value=[-2]) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_XShape, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_PrefixShape
Neg(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_ReducedShape
Flatten(X, axis=-2) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_XU, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_XU) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_XU, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Square, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Var, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_XU, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Deviation, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Scaled, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Biased, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_2d_axis_negative_2_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[3, 4]
output: name='Mean' type=dtype('float32') shape=[1, 1]
output: name='InvStdDev' type=dtype('float32') shape=[1, 1].
======================================================================
ERROR: test_layer_normalization_3d_axis0_epsilon_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 5]
input: name='W' type=dtype('float32') shape=[2, 3, 5]
input: name='B' type=dtype('float32') shape=[2, 3, 5]
Constant(value=0.10000000...) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Zero1D
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_XShape, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_PrefixShape
Sub(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Rank, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_ReducedShape
Flatten(X, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_XU) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Square, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Var, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Deviation, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Scaled, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Biased, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_3d_axis0_epsilon_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 5]
output: name='Mean' type=dtype('float32') shape=[1, 1, 1]
output: name='InvStdDev' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_layer_normalization_3d_axis1_epsilon_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 5]
input: name='W' type=dtype('float32') shape=[3, 5]
input: name='B' type=dtype('float32') shape=[3, 5]
Constant(value=0.10000000...) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Zero1D
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_XShape, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_PrefixShape
Sub(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Rank, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_ReducedShape
Flatten(X, axis=1) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_XU) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Square, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Var, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Deviation, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Scaled, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Biased, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_3d_axis1_epsilon_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 5]
output: name='Mean' type=dtype('float32') shape=[2, 1, 1]
output: name='InvStdDev' type=dtype('float32') shape=[2, 1, 1].
======================================================================
ERROR: test_layer_normalization_3d_axis2_epsilon_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 5]
input: name='W' type=dtype('float32') shape=[5]
input: name='B' type=dtype('float32') shape=[5]
Constant(value=0.10000000...) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Zero1D
Constant(value=[2]) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_XShape, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_PrefixShape
Sub(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Rank, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_ReducedShape
Flatten(X, axis=2) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_XU) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Square, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Var, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Deviation, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Scaled, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Biased, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_3d_axis2_epsilon_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 5]
output: name='Mean' type=dtype('float32') shape=[2, 3, 1]
output: name='InvStdDev' type=dtype('float32') shape=[2, 3, 1].
======================================================================
ERROR: test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 5]
input: name='W' type=dtype('float32') shape=[5]
input: name='B' type=dtype('float32') shape=[5]
Constant(value=0.10000000...) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Zero1D
Constant(value=[-1]) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_XShape, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_PrefixShape
Neg(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_ReducedShape
Flatten(X, axis=-1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_XU) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Square, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Var, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Deviation, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Scaled, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Biased, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_3d_axis_negative_1_epsilon_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 5]
output: name='Mean' type=dtype('float32') shape=[2, 3, 1]
output: name='InvStdDev' type=dtype('float32') shape=[2, 3, 1].
======================================================================
ERROR: test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 5]
input: name='W' type=dtype('float32') shape=[3, 5]
input: name='B' type=dtype('float32') shape=[3, 5]
Constant(value=0.10000000...) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Zero1D
Constant(value=[-2]) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_XShape, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_PrefixShape
Neg(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_ReducedShape
Flatten(X, axis=-2) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_XU) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Square, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Var, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Deviation, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Scaled, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Biased, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_3d_axis_negative_2_epsilon_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 5]
output: name='Mean' type=dtype('float32') shape=[2, 1, 1]
output: name='InvStdDev' type=dtype('float32') shape=[2, 1, 1].
======================================================================
ERROR: test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 5]
input: name='W' type=dtype('float32') shape=[2, 3, 5]
input: name='B' type=dtype('float32') shape=[2, 3, 5]
Constant(value=0.10000000...) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Zero1D
Constant(value=[-3]) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_XShape, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_PrefixShape
Neg(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_ReducedShape
Flatten(X, axis=-3) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_XU) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Square, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Var, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_XU, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Deviation, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Scaled, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Biased, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_3d_axis_negative_3_epsilon_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 5]
output: name='Mean' type=dtype('float32') shape=[1, 1, 1]
output: name='InvStdDev' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_layer_normalization_4d_axis0_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 4, 5]
input: name='W' type=dtype('float32') shape=[2, 3, 4, 5]
input: name='B' type=dtype('float32') shape=[2, 3, 4, 5]
Constant(value=9.99999974...) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Zero1D
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_XShape, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_PrefixShape
Sub(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Rank, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_ReducedShape
Flatten(X, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_XU) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Square, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Var, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Deviation, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Scaled, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Biased, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis0_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 4, 5]
output: name='Mean' type=dtype('float32') shape=[1, 1, 1, 1]
output: name='InvStdDev' type=dtype('float32') shape=[1, 1, 1, 1].
======================================================================
ERROR: test_layer_normalization_4d_axis1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 4, 5]
input: name='W' type=dtype('float32') shape=[3, 4, 5]
input: name='B' type=dtype('float32') shape=[3, 4, 5]
Constant(value=9.99999974...) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Zero1D
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_XShape, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_PrefixShape
Sub(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Rank, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_ReducedShape
Flatten(X, axis=1) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_XU) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Square, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Var, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Deviation, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Scaled, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Biased, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis1_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 4, 5]
output: name='Mean' type=dtype('float32') shape=[2, 1, 1, 1]
output: name='InvStdDev' type=dtype('float32') shape=[2, 1, 1, 1].
======================================================================
ERROR: test_layer_normalization_4d_axis2_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 4, 5]
input: name='W' type=dtype('float32') shape=[4, 5]
input: name='B' type=dtype('float32') shape=[4, 5]
Constant(value=9.99999974...) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Zero1D
Constant(value=[2]) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_XShape, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_PrefixShape
Sub(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Rank, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_ReducedShape
Flatten(X, axis=2) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_XU) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Square, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Var, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Deviation, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Scaled, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Biased, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis2_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 4, 5]
output: name='Mean' type=dtype('float32') shape=[2, 3, 1, 1]
output: name='InvStdDev' type=dtype('float32') shape=[2, 3, 1, 1].
======================================================================
ERROR: test_layer_normalization_4d_axis3_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 4, 5]
input: name='W' type=dtype('float32') shape=[5]
input: name='B' type=dtype('float32') shape=[5]
Constant(value=9.99999974...) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Zero1D
Constant(value=[3]) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_XShape, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_PrefixShape
Sub(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Rank, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_ReducedShape
Flatten(X, axis=3) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_XU) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Square, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Var, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Deviation, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Scaled, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Biased, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis3_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 4, 5]
output: name='Mean' type=dtype('float32') shape=[2, 3, 4, 1]
output: name='InvStdDev' type=dtype('float32') shape=[2, 3, 4, 1].
======================================================================
ERROR: test_layer_normalization_4d_axis_negative_1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 4, 5]
input: name='W' type=dtype('float32') shape=[5]
input: name='B' type=dtype('float32') shape=[5]
Constant(value=9.99999974...) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Zero1D
Constant(value=[-1]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_XShape, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_PrefixShape
Neg(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_ReducedShape
Flatten(X, axis=-1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_XU) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Square, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Var, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Deviation, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Scaled, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Biased, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis_negative_1_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 4, 5]
output: name='Mean' type=dtype('float32') shape=[2, 3, 4, 1]
output: name='InvStdDev' type=dtype('float32') shape=[2, 3, 4, 1].
======================================================================
ERROR: test_layer_normalization_4d_axis_negative_2_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 4, 5]
input: name='W' type=dtype('float32') shape=[4, 5]
input: name='B' type=dtype('float32') shape=[4, 5]
Constant(value=9.99999974...) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Zero1D
Constant(value=[-2]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_XShape, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_PrefixShape
Neg(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_ReducedShape
Flatten(X, axis=-2) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_XU) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Square, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Var, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Deviation, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Scaled, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Biased, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis_negative_2_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 4, 5]
output: name='Mean' type=dtype('float32') shape=[2, 3, 1, 1]
output: name='InvStdDev' type=dtype('float32') shape=[2, 3, 1, 1].
======================================================================
ERROR: test_layer_normalization_4d_axis_negative_3_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 4, 5]
input: name='W' type=dtype('float32') shape=[3, 4, 5]
input: name='B' type=dtype('float32') shape=[3, 4, 5]
Constant(value=9.99999974...) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Zero1D
Constant(value=[-3]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_XShape, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_PrefixShape
Neg(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_ReducedShape
Flatten(X, axis=-3) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_XU) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Square, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Var, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Deviation, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Scaled, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Biased, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis_negative_3_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 4, 5]
output: name='Mean' type=dtype('float32') shape=[2, 1, 1, 1]
output: name='InvStdDev' type=dtype('float32') shape=[2, 1, 1, 1].
======================================================================
ERROR: test_layer_normalization_4d_axis_negative_4_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 4, 5]
input: name='W' type=dtype('float32') shape=[2, 3, 4, 5]
input: name='B' type=dtype('float32') shape=[2, 3, 4, 5]
Constant(value=9.99999974...) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Zero1D
Constant(value=[-4]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_XShape, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_PrefixShape
Neg(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_ReducedShape
Flatten(X, axis=-4) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_XU) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Square, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Var, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_XU, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Deviation, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Scaled, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Biased, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_4d_axis_negative_4_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 4, 5]
output: name='Mean' type=dtype('float32') shape=[1, 1, 1, 1]
output: name='InvStdDev' type=dtype('float32') shape=[1, 1, 1, 1].
======================================================================
ERROR: test_layer_normalization_default_axis_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[2, 3, 4, 5]
input: name='W' type=dtype('float32') shape=[5]
input: name='B' type=dtype('float32') shape=[5]
Constant(value=9.99999974...) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_FloatEpsilon
Cast(LayerNormalization_test_layer_normalization_default_axis_expanded_function_FloatEpsilon, to=1) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_Epsilon
Shape(X) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_XShape
Size(LayerNormalization_test_layer_normalization_default_axis_expanded_function_XShape) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_Rank
Constant(value=[0]) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_Zero1D
Constant(value=[-1]) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_Axis1D
Slice(LayerNormalization_test_layer_normalization_default_axis_expanded_function_XShape, LayerNormalization_test_layer_normalization_default_axis_expanded_function_Zero1D, LayerNormalization_test_layer_normalization_default_axis_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_PrefixShape
Neg(LayerNormalization_test_layer_normalization_default_axis_expanded_function_Axis1D) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_NumReducedAxes
ConstantOfShape(LayerNormalization_test_layer_normalization_default_axis_expanded_function_NumReducedAxes, value=[1]) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_SuffixShape
Concat(LayerNormalization_test_layer_normalization_default_axis_expanded_function_PrefixShape, LayerNormalization_test_layer_normalization_default_axis_expanded_function_SuffixShape, axis=0) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_ReducedShape
Flatten(X, axis=-1) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_X2D
Cast(LayerNormalization_test_layer_normalization_default_axis_expanded_function_X2D, to=1) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_XU
Mul(LayerNormalization_test_layer_normalization_default_axis_expanded_function_XU, LayerNormalization_test_layer_normalization_default_axis_expanded_function_XU) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_Square
Constant(value=[1]) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_Axes_1
ReduceMean(LayerNormalization_test_layer_normalization_default_axis_expanded_function_XU, LayerNormalization_test_layer_normalization_default_axis_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_Mean2D
Mul(LayerNormalization_test_layer_normalization_default_axis_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_default_axis_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_SquareOfMean
ReduceMean(LayerNormalization_test_layer_normalization_default_axis_expanded_function_Square, LayerNormalization_test_layer_normalization_default_axis_expanded_function_Axes_1) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_MeanOfSquare
Sub(LayerNormalization_test_layer_normalization_default_axis_expanded_function_MeanOfSquare, LayerNormalization_test_layer_normalization_default_axis_expanded_function_SquareOfMean) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_Var
Add(LayerNormalization_test_layer_normalization_default_axis_expanded_function_Var, LayerNormalization_test_layer_normalization_default_axis_expanded_function_Epsilon) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_VarPlusEpsilon
Sqrt(LayerNormalization_test_layer_normalization_default_axis_expanded_function_VarPlusEpsilon) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_StdDev
Reciprocal(LayerNormalization_test_layer_normalization_default_axis_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_InvStdDev2D
Reshape(LayerNormalization_test_layer_normalization_default_axis_expanded_function_InvStdDev2D, LayerNormalization_test_layer_normalization_default_axis_expanded_function_ReducedShape) -> InvStdDev
Sub(LayerNormalization_test_layer_normalization_default_axis_expanded_function_XU, LayerNormalization_test_layer_normalization_default_axis_expanded_function_Mean2D) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_Deviation
Div(LayerNormalization_test_layer_normalization_default_axis_expanded_function_Deviation, LayerNormalization_test_layer_normalization_default_axis_expanded_function_StdDev) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_Normalized
Cast(LayerNormalization_test_layer_normalization_default_axis_expanded_function_Normalized, to=1) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_NormalizedT
Flatten(W, axis=0) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_Scale2D
Mul(LayerNormalization_test_layer_normalization_default_axis_expanded_function_NormalizedT, LayerNormalization_test_layer_normalization_default_axis_expanded_function_Scale2D) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_Scaled
Flatten(B, axis=0) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_B2D
Add(LayerNormalization_test_layer_normalization_default_axis_expanded_function_Scaled, LayerNormalization_test_layer_normalization_default_axis_expanded_function_B2D) -> LayerNormalization_test_layer_normalization_default_axis_expanded_function_Biased
Reshape(LayerNormalization_test_layer_normalization_default_axis_expanded_function_Biased, LayerNormalization_test_layer_normalization_default_axis_expanded_function_XShape) -> Y
Reshape(LayerNormalization_test_layer_normalization_default_axis_expanded_function_Mean2D, LayerNormalization_test_layer_normalization_default_axis_expanded_function_ReducedShape) -> Mean
output: name='Y' type=dtype('float32') shape=[2, 3, 4, 5]
output: name='Mean' type=dtype('float32') shape=[2, 3, 4, 1]
output: name='InvStdDev' type=dtype('float32') shape=[2, 3, 4, 1].
======================================================================
ERROR: test_logsoftmax_axis_0_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value=[0]) -> LogSoftmax_test_logsoftmax_axis_0_expanded_function_axes
ReduceMax(x, LogSoftmax_test_logsoftmax_axis_0_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_axis_0_expanded_function_X_ReduceMax
Sub(x, LogSoftmax_test_logsoftmax_axis_0_expanded_function_X_ReduceMax) -> LogSoftmax_test_logsoftmax_axis_0_expanded_function_X_Sub
Exp(LogSoftmax_test_logsoftmax_axis_0_expanded_function_X_Sub) -> LogSoftmax_test_logsoftmax_axis_0_expanded_function_X_Exp
ReduceSum(LogSoftmax_test_logsoftmax_axis_0_expanded_function_X_Exp, LogSoftmax_test_logsoftmax_axis_0_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_axis_0_expanded_function_X_ReduceSum
Log(LogSoftmax_test_logsoftmax_axis_0_expanded_function_X_ReduceSum) -> LogSoftmax_test_logsoftmax_axis_0_expanded_function_X_Log
Sub(LogSoftmax_test_logsoftmax_axis_0_expanded_function_X_Sub, LogSoftmax_test_logsoftmax_axis_0_expanded_function_X_Log) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_logsoftmax_axis_1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value=[1]) -> LogSoftmax_test_logsoftmax_axis_1_expanded_function_axes
ReduceMax(x, LogSoftmax_test_logsoftmax_axis_1_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_axis_1_expanded_function_X_ReduceMax
Sub(x, LogSoftmax_test_logsoftmax_axis_1_expanded_function_X_ReduceMax) -> LogSoftmax_test_logsoftmax_axis_1_expanded_function_X_Sub
Exp(LogSoftmax_test_logsoftmax_axis_1_expanded_function_X_Sub) -> LogSoftmax_test_logsoftmax_axis_1_expanded_function_X_Exp
ReduceSum(LogSoftmax_test_logsoftmax_axis_1_expanded_function_X_Exp, LogSoftmax_test_logsoftmax_axis_1_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_axis_1_expanded_function_X_ReduceSum
Log(LogSoftmax_test_logsoftmax_axis_1_expanded_function_X_ReduceSum) -> LogSoftmax_test_logsoftmax_axis_1_expanded_function_X_Log
Sub(LogSoftmax_test_logsoftmax_axis_1_expanded_function_X_Sub, LogSoftmax_test_logsoftmax_axis_1_expanded_function_X_Log) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_logsoftmax_axis_2_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value=[2]) -> LogSoftmax_test_logsoftmax_axis_2_expanded_function_axes
ReduceMax(x, LogSoftmax_test_logsoftmax_axis_2_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_axis_2_expanded_function_X_ReduceMax
Sub(x, LogSoftmax_test_logsoftmax_axis_2_expanded_function_X_ReduceMax) -> LogSoftmax_test_logsoftmax_axis_2_expanded_function_X_Sub
Exp(LogSoftmax_test_logsoftmax_axis_2_expanded_function_X_Sub) -> LogSoftmax_test_logsoftmax_axis_2_expanded_function_X_Exp
ReduceSum(LogSoftmax_test_logsoftmax_axis_2_expanded_function_X_Exp, LogSoftmax_test_logsoftmax_axis_2_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_axis_2_expanded_function_X_ReduceSum
Log(LogSoftmax_test_logsoftmax_axis_2_expanded_function_X_ReduceSum) -> LogSoftmax_test_logsoftmax_axis_2_expanded_function_X_Log
Sub(LogSoftmax_test_logsoftmax_axis_2_expanded_function_X_Sub, LogSoftmax_test_logsoftmax_axis_2_expanded_function_X_Log) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_logsoftmax_default_axis_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value=[-1]) -> LogSoftmax_test_logsoftmax_default_axis_expanded_function_axes
ReduceMax(x, LogSoftmax_test_logsoftmax_default_axis_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_default_axis_expanded_function_X_ReduceMax
Sub(x, LogSoftmax_test_logsoftmax_default_axis_expanded_function_X_ReduceMax) -> LogSoftmax_test_logsoftmax_default_axis_expanded_function_X_Sub
Exp(LogSoftmax_test_logsoftmax_default_axis_expanded_function_X_Sub) -> LogSoftmax_test_logsoftmax_default_axis_expanded_function_X_Exp
ReduceSum(LogSoftmax_test_logsoftmax_default_axis_expanded_function_X_Exp, LogSoftmax_test_logsoftmax_default_axis_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_default_axis_expanded_function_X_ReduceSum
Log(LogSoftmax_test_logsoftmax_default_axis_expanded_function_X_ReduceSum) -> LogSoftmax_test_logsoftmax_default_axis_expanded_function_X_Log
Sub(LogSoftmax_test_logsoftmax_default_axis_expanded_function_X_Sub, LogSoftmax_test_logsoftmax_default_axis_expanded_function_X_Log) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_logsoftmax_example_1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[1, 3]
Constant(value=[-1]) -> LogSoftmax_test_logsoftmax_example_1_expanded_function_axes
ReduceMax(x, LogSoftmax_test_logsoftmax_example_1_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_example_1_expanded_function_X_ReduceMax
Sub(x, LogSoftmax_test_logsoftmax_example_1_expanded_function_X_ReduceMax) -> LogSoftmax_test_logsoftmax_example_1_expanded_function_X_Sub
Exp(LogSoftmax_test_logsoftmax_example_1_expanded_function_X_Sub) -> LogSoftmax_test_logsoftmax_example_1_expanded_function_X_Exp
ReduceSum(LogSoftmax_test_logsoftmax_example_1_expanded_function_X_Exp, LogSoftmax_test_logsoftmax_example_1_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_example_1_expanded_function_X_ReduceSum
Log(LogSoftmax_test_logsoftmax_example_1_expanded_function_X_ReduceSum) -> LogSoftmax_test_logsoftmax_example_1_expanded_function_X_Log
Sub(LogSoftmax_test_logsoftmax_example_1_expanded_function_X_Sub, LogSoftmax_test_logsoftmax_example_1_expanded_function_X_Log) -> y
output: name='y' type=dtype('float32') shape=[1, 3].
======================================================================
ERROR: test_logsoftmax_large_number_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[2, 4]
Constant(value=[-1]) -> LogSoftmax_test_logsoftmax_large_number_expanded_function_axes
ReduceMax(x, LogSoftmax_test_logsoftmax_large_number_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_large_number_expanded_function_X_ReduceMax
Sub(x, LogSoftmax_test_logsoftmax_large_number_expanded_function_X_ReduceMax) -> LogSoftmax_test_logsoftmax_large_number_expanded_function_X_Sub
Exp(LogSoftmax_test_logsoftmax_large_number_expanded_function_X_Sub) -> LogSoftmax_test_logsoftmax_large_number_expanded_function_X_Exp
ReduceSum(LogSoftmax_test_logsoftmax_large_number_expanded_function_X_Exp, LogSoftmax_test_logsoftmax_large_number_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_large_number_expanded_function_X_ReduceSum
Log(LogSoftmax_test_logsoftmax_large_number_expanded_function_X_ReduceSum) -> LogSoftmax_test_logsoftmax_large_number_expanded_function_X_Log
Sub(LogSoftmax_test_logsoftmax_large_number_expanded_function_X_Sub, LogSoftmax_test_logsoftmax_large_number_expanded_function_X_Log) -> y
output: name='y' type=dtype('float32') shape=[2, 4].
======================================================================
ERROR: test_logsoftmax_negative_axis_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value=[-1]) -> LogSoftmax_test_logsoftmax_negative_axis_expanded_function_axes
ReduceMax(x, LogSoftmax_test_logsoftmax_negative_axis_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_negative_axis_expanded_function_X_ReduceMax
Sub(x, LogSoftmax_test_logsoftmax_negative_axis_expanded_function_X_ReduceMax) -> LogSoftmax_test_logsoftmax_negative_axis_expanded_function_X_Sub
Exp(LogSoftmax_test_logsoftmax_negative_axis_expanded_function_X_Sub) -> LogSoftmax_test_logsoftmax_negative_axis_expanded_function_X_Exp
ReduceSum(LogSoftmax_test_logsoftmax_negative_axis_expanded_function_X_Exp, LogSoftmax_test_logsoftmax_negative_axis_expanded_function_axes, keepdims=1) -> LogSoftmax_test_logsoftmax_negative_axis_expanded_function_X_ReduceSum
Log(LogSoftmax_test_logsoftmax_negative_axis_expanded_function_X_ReduceSum) -> LogSoftmax_test_logsoftmax_negative_axis_expanded_function_X_Log
Sub(LogSoftmax_test_logsoftmax_negative_axis_expanded_function_X_Sub, LogSoftmax_test_logsoftmax_negative_axis_expanded_function_X_Log) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_loop16_seq_none_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 185, in _init
self.graph_ = self.to_sequence(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 619, in to_sequence
variables[obj.name] = _var_as_dict(obj)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 459, in _var_as_dict
dtype['optional'] = _var_as_dict(optional)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 558, in _var_as_dict
return dict(optional=True, elem_type=_var_as_dict(var.elem_type))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 553, in _var_as_dict
d[n] = _var_as_dict(at)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 560, in _var_as_dict
raise NotImplementedError( # pragma: no cover
NotImplementedError: Unable to guess which object it is type is <class 'onnx.onnx_ml_pb2.Sequence'> value is 'elem_type {\n tensor_type {\n elem_type: 1\n shape {\n }\n }\n}\n' (hasattr(var,'type')=False, var.type=None
ByteSize
Clear
ClearExtension
ClearField
CopyFrom
DESCRIPTOR
DiscardUnknownFields
Extensions
FindInitializationErrors
FromString
HasExtension
HasField
IsInitialized
ListFields
MergeFrom
MergeFromString
ParseFromString
RegisterExtension
SerializePartialToString
SerializeToString
SetInParent
UnknownFields
WhichOneof
_CheckCalledFromGeneratedFile
_SetListener
__class__
__deepcopy__
__delattr__
__dir__
__doc__
__eq__
__format__
__ge__
__getattribute__
__getstate__
__gt__
__hash__
__init__
__init_subclass__
__le__
__lt__
__module__
__ne__
__new__
__reduce__
__reduce_ex__
__repr__
__setattr__
__setstate__
__sizeof__
__slots__
__str__
__subclasshook__
__unicode__
_extensions_by_name
_extensions_by_number
elem_type
======================================================================
ERROR: test_lstm_batchwise_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.RuntimeException: [ONNXRuntimeError] : 6 : RUNTIME_EXCEPTION : Exception during initialization: /onnxruntime_src/onnxruntime/core/providers/cpu/rnn/lstm_base.h:52 onnxruntime::LSTMBase::LSTMBase(const onnxruntime::OpKernelInfo&) layout_ == 0 was false. Batchwise recurrent operations (layout == 1) are not supported. If you need support create a github issue with justification.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 6 : RUNTIME_EXCEPTION : Exception during initialization: /onnxruntime_src/onnxruntime/core/providers/cpu/rnn/lstm_base.h:52 onnxruntime::LSTMBase::LSTMBase(const onnxruntime::OpKernelInfo&) layout_ == 0 was false. Batchwise recurrent operations (layout == 1) are not supported. If you need support create a github issue with justification.
'
opset: domain='' version=14
input: name='X' type=dtype('float32') shape=[3, 1, 2]
input: name='W' type=dtype('float32') shape=[1, 28, 2]
input: name='R' type=dtype('float32') shape=[1, 28, 7]
LSTM(X, W, R, hidden_size=7, layout=1) -> Y, Y_h
output: name='Y' type=dtype('float32') shape=[3, 1, 1, 7]
output: name='Y_h' type=dtype('float32') shape=[3, 1, 7].
======================================================================
ERROR: test_max_int16_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Max(13) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Max(13) node with name '''
opset: domain='' version=13
input: name='data_0' type=dtype('int16') shape=[3]
input: name='data_1' type=dtype('int16') shape=[3]
Max(data_0, data_1) -> result
output: name='result' type=dtype('int16') shape=[3].
======================================================================
ERROR: test_max_int8_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Max(13) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Max(13) node with name '''
opset: domain='' version=13
input: name='data_0' type=dtype('int8') shape=[3]
input: name='data_1' type=dtype('int8') shape=[3]
Max(data_0, data_1) -> result
output: name='result' type=dtype('int8') shape=[3].
======================================================================
ERROR: test_max_uint16_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Max(13) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Max(13) node with name '''
opset: domain='' version=13
input: name='data_0' type=dtype('uint16') shape=[3]
input: name='data_1' type=dtype('uint16') shape=[3]
Max(data_0, data_1) -> result
output: name='result' type=dtype('uint16') shape=[3].
======================================================================
ERROR: test_max_uint8_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Max(13) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Max(13) node with name '''
opset: domain='' version=13
input: name='data_0' type=dtype('uint8') shape=[3]
input: name='data_1' type=dtype('uint8') shape=[3]
Max(data_0, data_1) -> result
output: name='result' type=dtype('uint8') shape=[3].
======================================================================
ERROR: test_min_int16_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Min(13) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Min(13) node with name '''
opset: domain='' version=13
input: name='data_0' type=dtype('int16') shape=[3]
input: name='data_1' type=dtype('int16') shape=[3]
Min(data_0, data_1) -> result
output: name='result' type=dtype('int16') shape=[3].
======================================================================
ERROR: test_min_int8_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Min(13) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Min(13) node with name '''
opset: domain='' version=13
input: name='data_0' type=dtype('int8') shape=[3]
input: name='data_1' type=dtype('int8') shape=[3]
Min(data_0, data_1) -> result
output: name='result' type=dtype('int8') shape=[3].
======================================================================
ERROR: test_min_uint16_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Min(13) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Min(13) node with name '''
opset: domain='' version=13
input: name='data_0' type=dtype('uint16') shape=[3]
input: name='data_1' type=dtype('uint16') shape=[3]
Min(data_0, data_1) -> result
output: name='result' type=dtype('uint16') shape=[3].
======================================================================
ERROR: test_min_uint8_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Min(13) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Min(13) node with name '''
opset: domain='' version=13
input: name='data_0' type=dtype('uint8') shape=[3]
input: name='data_1' type=dtype('uint8') shape=[3]
Min(data_0, data_1) -> result
output: name='result' type=dtype('uint8') shape=[3].
======================================================================
ERROR: test_mish_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[10000]
Mish(X) -> Y
output: name='Y' type=dtype('float32') shape=[10000].
======================================================================
ERROR: test_mish_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[10000]
Softplus(X) -> Mish_test_mish_expanded_function_Softplus_X
Tanh(Mish_test_mish_expanded_function_Softplus_X) -> Mish_test_mish_expanded_function_TanHSoftplusX
Mul(X, Mish_test_mish_expanded_function_TanHSoftplusX) -> Y
output: name='Y' type=dtype('float32') shape=[10000].
======================================================================
ERROR: test_momentum_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Momentum(-1) is not a registered function/op
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Momentum(-1) is not a registered function/op'
opset: domain='ai.onnx.preview.training' version=1
input: name='R' type=dtype('float32') shape=[]
input: name='T' type=dtype('int64') shape=[]
input: name='X' type=dtype('float32') shape=[2]
input: name='G' type=dtype('float32') shape=[2]
input: name='V' type=dtype('float32') shape=[2]
Momentum[ai.onnx.preview.training](R, T, X, G, V, alpha=0.95, beta=0.10, mode=b'standard', norm_coefficient=0.00) -> X_new, V_new
output: name='X_new' type=dtype('float32') shape=[2]
output: name='V_new' type=dtype('float32') shape=[2].
======================================================================
ERROR: test_momentum_multiple_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Momentum(-1) is not a registered function/op
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Momentum(-1) is not a registered function/op'
opset: domain='ai.onnx.preview.training' version=1
input: name='R' type=dtype('float32') shape=[]
input: name='T' type=dtype('int64') shape=[]
input: name='X1' type=dtype('float32') shape=[1]
input: name='X2' type=dtype('float32') shape=[2]
input: name='G1' type=dtype('float32') shape=[1]
input: name='G2' type=dtype('float32') shape=[2]
input: name='H1' type=dtype('float32') shape=[1]
input: name='H2' type=dtype('float32') shape=[2]
Momentum[ai.onnx.preview.training](R, T, X1, X2, G1, G2, H1, H2, alpha=0.95, beta=0.85, mode=b'standard', norm_coefficient=0.00) -> X1_new, X2_new, V1_new, V2_new
output: name='X1_new' type=dtype('float32') shape=[1]
output: name='X2_new' type=dtype('float32') shape=[2]
output: name='V1_new' type=dtype('float32') shape=[1]
output: name='V2_new' type=dtype('float32') shape=[2].
======================================================================
ERROR: test_mul_uint8_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Mul(14) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Mul(14) node with name '''
opset: domain='' version=14
input: name='x' type=dtype('uint8') shape=[3, 4, 5]
input: name='y' type=dtype('uint8') shape=[3, 4, 5]
Mul(x, y) -> z
output: name='z' type=dtype('uint8') shape=[3, 4, 5].
======================================================================
ERROR: test_mvn_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[3, 3, 3, 1]
Constant(value=2.0) -> MeanVarianceNormalization_test_mvn_expanded_function_Exponent
Pow(X, MeanVarianceNormalization_test_mvn_expanded_function_Exponent) -> MeanVarianceNormalization_test_mvn_expanded_function_X_squared
Constant(value=9.99999971...) -> MeanVarianceNormalization_test_mvn_expanded_function_Epsilon
Constant(value_ints=[0,2,3]) -> MeanVarianceNormalization_test_mvn_expanded_function_axes
ReduceMean(X, MeanVarianceNormalization_test_mvn_expanded_function_axes) -> MeanVarianceNormalization_test_mvn_expanded_function_X_RM
Pow(MeanVarianceNormalization_test_mvn_expanded_function_X_RM, MeanVarianceNormalization_test_mvn_expanded_function_Exponent) -> MeanVarianceNormalization_test_mvn_expanded_function_EX_squared
ReduceMean(MeanVarianceNormalization_test_mvn_expanded_function_X_squared, MeanVarianceNormalization_test_mvn_expanded_function_axes) -> MeanVarianceNormalization_test_mvn_expanded_function_E_Xsquared
Sub(MeanVarianceNormalization_test_mvn_expanded_function_E_Xsquared, MeanVarianceNormalization_test_mvn_expanded_function_EX_squared) -> MeanVarianceNormalization_test_mvn_expanded_function_Variance
Sqrt(MeanVarianceNormalization_test_mvn_expanded_function_Variance) -> MeanVarianceNormalization_test_mvn_expanded_function_STD
Add(MeanVarianceNormalization_test_mvn_expanded_function_STD, MeanVarianceNormalization_test_mvn_expanded_function_Epsilon) -> MeanVarianceNormalization_test_mvn_expanded_function_Processed_STD
Sub(X, MeanVarianceNormalization_test_mvn_expanded_function_X_RM) -> MeanVarianceNormalization_test_mvn_expanded_function_X_variance
Div(MeanVarianceNormalization_test_mvn_expanded_function_X_variance, MeanVarianceNormalization_test_mvn_expanded_function_Processed_STD) -> Y
output: name='Y' type=dtype('float32') shape=[3, 3, 3, 1].
======================================================================
ERROR: test_nesterov_momentum_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Momentum(-1) is not a registered function/op
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Momentum(-1) is not a registered function/op'
opset: domain='ai.onnx.preview.training' version=1
input: name='R' type=dtype('float32') shape=[]
input: name='T' type=dtype('int64') shape=[]
input: name='X' type=dtype('float32') shape=[2]
input: name='G' type=dtype('float32') shape=[2]
input: name='V' type=dtype('float32') shape=[2]
Momentum[ai.onnx.preview.training](R, T, X, G, V, alpha=0.95, beta=1.00, mode=b'nesterov', norm_coefficient=0.01) -> X_new, V_new
output: name='X_new' type=dtype('float32') shape=[2]
output: name='V_new' type=dtype('float32') shape=[2].
======================================================================
ERROR: test_optional_get_element_optional_sequence_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 185, in _init
self.graph_ = self.to_sequence(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 619, in to_sequence
variables[obj.name] = _var_as_dict(obj)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 459, in _var_as_dict
dtype['optional'] = _var_as_dict(optional)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 558, in _var_as_dict
return dict(optional=True, elem_type=_var_as_dict(var.elem_type))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 553, in _var_as_dict
d[n] = _var_as_dict(at)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 560, in _var_as_dict
raise NotImplementedError( # pragma: no cover
NotImplementedError: Unable to guess which object it is type is <class 'onnx.onnx_ml_pb2.Sequence'> value is 'elem_type {\n tensor_type {\n elem_type: 6\n shape {\n dim {\n dim_value: 4\n }\n }\n }\n}\n' (hasattr(var,'type')=False, var.type=None
ByteSize
Clear
ClearExtension
ClearField
CopyFrom
DESCRIPTOR
DiscardUnknownFields
Extensions
FindInitializationErrors
FromString
HasExtension
HasField
IsInitialized
ListFields
MergeFrom
MergeFromString
ParseFromString
RegisterExtension
SerializePartialToString
SerializeToString
SetInParent
UnknownFields
WhichOneof
_CheckCalledFromGeneratedFile
_SetListener
__class__
__deepcopy__
__delattr__
__dir__
__doc__
__eq__
__format__
__ge__
__getattribute__
__getstate__
__gt__
__hash__
__init__
__init_subclass__
__le__
__lt__
__module__
__ne__
__new__
__reduce__
__reduce_ex__
__repr__
__setattr__
__setstate__
__sizeof__
__slots__
__str__
__subclasshook__
__unicode__
_extensions_by_name
_extensions_by_number
elem_type
======================================================================
ERROR: test_optional_get_element_optional_tensor_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='optional_input' type='?' shape=None
OptionalGetElement(optional_input) -> output
output: name='output' type=dtype('float32') shape=[4].
======================================================================
ERROR: test_optional_get_element_sequence_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='optional_input' type='?' shape=None
OptionalGetElement(optional_input) -> output
output: name='output' type='?' shape=None.
======================================================================
ERROR: test_optional_get_element_tensor_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='optional_input' type=dtype('float32') shape=[4]
OptionalGetElement(optional_input) -> output
output: name='output' type=dtype('float32') shape=[4].
======================================================================
ERROR: test_optional_has_element_empty_no_input_name_optional_input_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
OptionalHasElement() -> output
output: name='output' type=dtype('bool') shape=[].
======================================================================
ERROR: test_optional_has_element_empty_no_input_name_tensor_input_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
OptionalHasElement() -> output
output: name='output' type=dtype('bool') shape=[].
======================================================================
ERROR: test_optional_has_element_empty_no_input_optional_input_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
OptionalHasElement() -> output
output: name='output' type=dtype('bool') shape=[].
======================================================================
ERROR: test_optional_has_element_empty_no_input_tensor_input_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
OptionalHasElement() -> output
output: name='output' type=dtype('bool') shape=[].
======================================================================
ERROR: test_optional_has_element_empty_optional_input_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='optional_input' type='?' shape=None
OptionalHasElement(optional_input) -> output
output: name='output' type=dtype('bool') shape=[].
======================================================================
ERROR: test_optional_has_element_optional_input_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='optional_input' type='?' shape=None
OptionalHasElement(optional_input) -> output
output: name='output' type=dtype('bool') shape=[].
======================================================================
ERROR: test_optional_has_element_tensor_input_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='optional_input' type='?' shape=None
OptionalHasElement(optional_input) -> output
output: name='output' type=dtype('bool') shape=[].
======================================================================
ERROR: test_pow_types_float32_uint32_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Pow(15) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Pow(15) node with name '''
opset: domain='' version=15
input: name='x' type=dtype('float32') shape=[3]
input: name='y' type=dtype('uint32') shape=[3]
Pow(x, y) -> z
output: name='z' type=dtype('float32') shape=[3].
======================================================================
ERROR: test_pow_types_float32_uint64_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Pow(15) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Pow(15) node with name '''
opset: domain='' version=15
input: name='x' type=dtype('float32') shape=[3]
input: name='y' type=dtype('uint64') shape=[3]
Pow(x, y) -> z
output: name='z' type=dtype('float32') shape=[3].
======================================================================
ERROR: test_reduce_l1_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
ReduceL1(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_l1_default_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
Abs(data) -> ReduceL1_test_reduce_l1_default_axes_keepdims_example_expanded_function_data_abs
ReduceSum(ReduceL1_test_reduce_l1_default_axes_keepdims_example_expanded_function_data_abs, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_l1_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
ReduceL1(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_l1_default_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
Abs(data) -> ReduceL1_test_reduce_l1_default_axes_keepdims_random_expanded_function_data_abs
ReduceSum(ReduceL1_test_reduce_l1_default_axes_keepdims_random_expanded_function_data_abs, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_l1_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceL1(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_l1_do_not_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Abs(data) -> ReduceL1_test_reduce_l1_do_not_keepdims_example_expanded_function_data_abs
ReduceSum(ReduceL1_test_reduce_l1_do_not_keepdims_example_expanded_function_data_abs, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_l1_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceL1(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_l1_do_not_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Abs(data) -> ReduceL1_test_reduce_l1_do_not_keepdims_random_expanded_function_data_abs
ReduceSum(ReduceL1_test_reduce_l1_do_not_keepdims_random_expanded_function_data_abs, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_l1_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceL1(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l1_keep_dims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Abs(data) -> ReduceL1_test_reduce_l1_keep_dims_example_expanded_function_data_abs
ReduceSum(ReduceL1_test_reduce_l1_keep_dims_example_expanded_function_data_abs, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l1_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceL1(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l1_keep_dims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Abs(data) -> ReduceL1_test_reduce_l1_keep_dims_random_expanded_function_data_abs
ReduceSum(ReduceL1_test_reduce_l1_keep_dims_random_expanded_function_data_abs, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l1_negative_axes_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceL1(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l1_negative_axes_keep_dims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Abs(data) -> ReduceL1_test_reduce_l1_negative_axes_keep_dims_example_expanded_function_data_abs
ReduceSum(ReduceL1_test_reduce_l1_negative_axes_keep_dims_example_expanded_function_data_abs, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l1_negative_axes_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceL1(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l1_negative_axes_keep_dims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Abs(data) -> ReduceL1_test_reduce_l1_negative_axes_keep_dims_random_expanded_function_data_abs
ReduceSum(ReduceL1_test_reduce_l1_negative_axes_keep_dims_random_expanded_function_data_abs, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l2_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
ReduceL2(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_l2_default_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
Mul(data, data) -> ReduceL2_test_reduce_l2_default_axes_keepdims_example_expanded_function_data_square
ReduceSum(ReduceL2_test_reduce_l2_default_axes_keepdims_example_expanded_function_data_square, axes, keepdims=1) -> ReduceL2_test_reduce_l2_default_axes_keepdims_example_expanded_function_sum_square
Cast(ReduceL2_test_reduce_l2_default_axes_keepdims_example_expanded_function_sum_square, to=1) -> ReduceL2_test_reduce_l2_default_axes_keepdims_example_expanded_function_sum_square_dbl
Sqrt(ReduceL2_test_reduce_l2_default_axes_keepdims_example_expanded_function_sum_square_dbl) -> ReduceL2_test_reduce_l2_default_axes_keepdims_example_expanded_function_sqrt
CastLike(ReduceL2_test_reduce_l2_default_axes_keepdims_example_expanded_function_sqrt, data) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_l2_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
ReduceL2(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_l2_default_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
Mul(data, data) -> ReduceL2_test_reduce_l2_default_axes_keepdims_random_expanded_function_data_square
ReduceSum(ReduceL2_test_reduce_l2_default_axes_keepdims_random_expanded_function_data_square, axes, keepdims=1) -> ReduceL2_test_reduce_l2_default_axes_keepdims_random_expanded_function_sum_square
Cast(ReduceL2_test_reduce_l2_default_axes_keepdims_random_expanded_function_sum_square, to=1) -> ReduceL2_test_reduce_l2_default_axes_keepdims_random_expanded_function_sum_square_dbl
Sqrt(ReduceL2_test_reduce_l2_default_axes_keepdims_random_expanded_function_sum_square_dbl) -> ReduceL2_test_reduce_l2_default_axes_keepdims_random_expanded_function_sqrt
CastLike(ReduceL2_test_reduce_l2_default_axes_keepdims_random_expanded_function_sqrt, data) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_l2_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceL2(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_l2_do_not_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Mul(data, data) -> ReduceL2_test_reduce_l2_do_not_keepdims_example_expanded_function_data_square
ReduceSum(ReduceL2_test_reduce_l2_do_not_keepdims_example_expanded_function_data_square, axes, keepdims=0) -> ReduceL2_test_reduce_l2_do_not_keepdims_example_expanded_function_sum_square
Cast(ReduceL2_test_reduce_l2_do_not_keepdims_example_expanded_function_sum_square, to=1) -> ReduceL2_test_reduce_l2_do_not_keepdims_example_expanded_function_sum_square_dbl
Sqrt(ReduceL2_test_reduce_l2_do_not_keepdims_example_expanded_function_sum_square_dbl) -> ReduceL2_test_reduce_l2_do_not_keepdims_example_expanded_function_sqrt
CastLike(ReduceL2_test_reduce_l2_do_not_keepdims_example_expanded_function_sqrt, data) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_l2_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceL2(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_l2_do_not_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Mul(data, data) -> ReduceL2_test_reduce_l2_do_not_keepdims_random_expanded_function_data_square
ReduceSum(ReduceL2_test_reduce_l2_do_not_keepdims_random_expanded_function_data_square, axes, keepdims=0) -> ReduceL2_test_reduce_l2_do_not_keepdims_random_expanded_function_sum_square
Cast(ReduceL2_test_reduce_l2_do_not_keepdims_random_expanded_function_sum_square, to=1) -> ReduceL2_test_reduce_l2_do_not_keepdims_random_expanded_function_sum_square_dbl
Sqrt(ReduceL2_test_reduce_l2_do_not_keepdims_random_expanded_function_sum_square_dbl) -> ReduceL2_test_reduce_l2_do_not_keepdims_random_expanded_function_sqrt
CastLike(ReduceL2_test_reduce_l2_do_not_keepdims_random_expanded_function_sqrt, data) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_l2_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceL2(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l2_keep_dims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Mul(data, data) -> ReduceL2_test_reduce_l2_keep_dims_example_expanded_function_data_square
ReduceSum(ReduceL2_test_reduce_l2_keep_dims_example_expanded_function_data_square, axes, keepdims=1) -> ReduceL2_test_reduce_l2_keep_dims_example_expanded_function_sum_square
Cast(ReduceL2_test_reduce_l2_keep_dims_example_expanded_function_sum_square, to=1) -> ReduceL2_test_reduce_l2_keep_dims_example_expanded_function_sum_square_dbl
Sqrt(ReduceL2_test_reduce_l2_keep_dims_example_expanded_function_sum_square_dbl) -> ReduceL2_test_reduce_l2_keep_dims_example_expanded_function_sqrt
CastLike(ReduceL2_test_reduce_l2_keep_dims_example_expanded_function_sqrt, data) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l2_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceL2(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l2_keep_dims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Mul(data, data) -> ReduceL2_test_reduce_l2_keep_dims_random_expanded_function_data_square
ReduceSum(ReduceL2_test_reduce_l2_keep_dims_random_expanded_function_data_square, axes, keepdims=1) -> ReduceL2_test_reduce_l2_keep_dims_random_expanded_function_sum_square
Cast(ReduceL2_test_reduce_l2_keep_dims_random_expanded_function_sum_square, to=1) -> ReduceL2_test_reduce_l2_keep_dims_random_expanded_function_sum_square_dbl
Sqrt(ReduceL2_test_reduce_l2_keep_dims_random_expanded_function_sum_square_dbl) -> ReduceL2_test_reduce_l2_keep_dims_random_expanded_function_sqrt
CastLike(ReduceL2_test_reduce_l2_keep_dims_random_expanded_function_sqrt, data) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l2_negative_axes_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceL2(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l2_negative_axes_keep_dims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Mul(data, data) -> ReduceL2_test_reduce_l2_negative_axes_keep_dims_example_expanded_function_data_square
ReduceSum(ReduceL2_test_reduce_l2_negative_axes_keep_dims_example_expanded_function_data_square, axes, keepdims=1) -> ReduceL2_test_reduce_l2_negative_axes_keep_dims_example_expanded_function_sum_square
Cast(ReduceL2_test_reduce_l2_negative_axes_keep_dims_example_expanded_function_sum_square, to=1) -> ReduceL2_test_reduce_l2_negative_axes_keep_dims_example_expanded_function_sum_square_dbl
Sqrt(ReduceL2_test_reduce_l2_negative_axes_keep_dims_example_expanded_function_sum_square_dbl) -> ReduceL2_test_reduce_l2_negative_axes_keep_dims_example_expanded_function_sqrt
CastLike(ReduceL2_test_reduce_l2_negative_axes_keep_dims_example_expanded_function_sqrt, data) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l2_negative_axes_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceL2(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_l2_negative_axes_keep_dims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Mul(data, data) -> ReduceL2_test_reduce_l2_negative_axes_keep_dims_random_expanded_function_data_square
ReduceSum(ReduceL2_test_reduce_l2_negative_axes_keep_dims_random_expanded_function_data_square, axes, keepdims=1) -> ReduceL2_test_reduce_l2_negative_axes_keep_dims_random_expanded_function_sum_square
Cast(ReduceL2_test_reduce_l2_negative_axes_keep_dims_random_expanded_function_sum_square, to=1) -> ReduceL2_test_reduce_l2_negative_axes_keep_dims_random_expanded_function_sum_square_dbl
Sqrt(ReduceL2_test_reduce_l2_negative_axes_keep_dims_random_expanded_function_sum_square_dbl) -> ReduceL2_test_reduce_l2_negative_axes_keep_dims_random_expanded_function_sqrt
CastLike(ReduceL2_test_reduce_l2_negative_axes_keep_dims_random_expanded_function_sqrt, data) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2, 1].
======================================================================
ERROR: test_reduce_log_sum_asc_axes_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 4, 5]
input: name='axes' type=dtype('int64') shape=[2]
ReduceLogSum(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[5].
======================================================================
ERROR: test_reduce_log_sum_asc_axes_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 4, 5]
input: name='axes' type=dtype('int64') shape=[2]
ReduceSum(data, axes, keepdims=0) -> ReduceLogSum_test_reduce_log_sum_asc_axes_expanded_function_reduced_sum
Log(ReduceLogSum_test_reduce_log_sum_asc_axes_expanded_function_reduced_sum) -> reduced
output: name='reduced' type=dtype('float32') shape=[5].
======================================================================
ERROR: test_reduce_log_sum_default_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 4, 5]
input: name='axes' type=dtype('int64') shape=[None]
ReduceLogSum(data, axes) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_log_sum_default_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 4, 5]
input: name='axes' type=dtype('int64') shape=[None]
ReduceSum(data, axes, keepdims=1) -> ReduceLogSum_test_reduce_log_sum_default_expanded_function_reduced_sum
Log(ReduceLogSum_test_reduce_log_sum_default_expanded_function_reduced_sum) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_log_sum_desc_axes_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 4, 5]
input: name='axes' type=dtype('int64') shape=[2]
ReduceLogSum(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3].
======================================================================
ERROR: test_reduce_log_sum_desc_axes_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 4, 5]
input: name='axes' type=dtype('int64') shape=[2]
ReduceSum(data, axes, keepdims=0) -> ReduceLogSum_test_reduce_log_sum_desc_axes_expanded_function_reduced_sum
Log(ReduceLogSum_test_reduce_log_sum_desc_axes_expanded_function_reduced_sum) -> reduced
output: name='reduced' type=dtype('float32') shape=[3].
======================================================================
ERROR: test_reduce_log_sum_exp_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
ReduceLogSumExp(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float64') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_log_sum_exp_default_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
Cast(data, to=11) -> ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_example_expanded_function_data_double
Exp(ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_example_expanded_function_data_double) -> ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_example_expanded_function_data_exp
ReduceSum(ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_example_expanded_function_data_exp, axes, keepdims=1) -> ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_example_expanded_function_reduced_sum
Log(ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_example_expanded_function_reduced_sum) -> ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_example_expanded_function_reduced_double
CastLike(ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_example_expanded_function_reduced_double, data) -> reduced
output: name='reduced' type=dtype('float64') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_log_sum_exp_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
ReduceLogSumExp(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float64') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_log_sum_exp_default_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
Cast(data, to=11) -> ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_random_expanded_function_data_double
Exp(ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_random_expanded_function_data_double) -> ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_random_expanded_function_data_exp
ReduceSum(ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_random_expanded_function_data_exp, axes, keepdims=1) -> ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_random_expanded_function_reduced_sum
Log(ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_random_expanded_function_reduced_sum) -> ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_random_expanded_function_reduced_double
CastLike(ReduceLogSumExp_test_reduce_log_sum_exp_default_axes_keepdims_random_expanded_function_reduced_double, data) -> reduced
output: name='reduced' type=dtype('float64') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_log_sum_exp_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceLogSumExp(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float64') shape=[3, 2].
======================================================================
ERROR: test_reduce_log_sum_exp_do_not_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Cast(data, to=11) -> ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_example_expanded_function_data_double
Exp(ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_example_expanded_function_data_double) -> ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_example_expanded_function_data_exp
ReduceSum(ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_example_expanded_function_data_exp, axes, keepdims=0) -> ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_example_expanded_function_reduced_sum
Log(ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_example_expanded_function_reduced_sum) -> ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_example_expanded_function_reduced_double
CastLike(ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_example_expanded_function_reduced_double, data) -> reduced
output: name='reduced' type=dtype('float64') shape=[3, 2].
======================================================================
ERROR: test_reduce_log_sum_exp_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceLogSumExp(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float64') shape=[3, 2].
======================================================================
ERROR: test_reduce_log_sum_exp_do_not_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Cast(data, to=11) -> ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_random_expanded_function_data_double
Exp(ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_random_expanded_function_data_double) -> ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_random_expanded_function_data_exp
ReduceSum(ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_random_expanded_function_data_exp, axes, keepdims=0) -> ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_random_expanded_function_reduced_sum
Log(ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_random_expanded_function_reduced_sum) -> ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_random_expanded_function_reduced_double
CastLike(ReduceLogSumExp_test_reduce_log_sum_exp_do_not_keepdims_random_expanded_function_reduced_double, data) -> reduced
output: name='reduced' type=dtype('float64') shape=[3, 2].
======================================================================
ERROR: test_reduce_log_sum_exp_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceLogSumExp(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float64') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_log_sum_exp_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Cast(data, to=11) -> ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_example_expanded_function_data_double
Exp(ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_example_expanded_function_data_double) -> ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_example_expanded_function_data_exp
ReduceSum(ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_example_expanded_function_data_exp, axes, keepdims=1) -> ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_example_expanded_function_reduced_sum
Log(ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_example_expanded_function_reduced_sum) -> ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_example_expanded_function_reduced_double
CastLike(ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_example_expanded_function_reduced_double, data) -> reduced
output: name='reduced' type=dtype('float64') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_log_sum_exp_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceLogSumExp(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float64') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_log_sum_exp_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Cast(data, to=11) -> ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_random_expanded_function_data_double
Exp(ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_random_expanded_function_data_double) -> ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_random_expanded_function_data_exp
ReduceSum(ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_random_expanded_function_data_exp, axes, keepdims=1) -> ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_random_expanded_function_reduced_sum
Log(ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_random_expanded_function_reduced_sum) -> ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_random_expanded_function_reduced_double
CastLike(ReduceLogSumExp_test_reduce_log_sum_exp_keepdims_random_expanded_function_reduced_double, data) -> reduced
output: name='reduced' type=dtype('float64') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_log_sum_exp_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceLogSumExp(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float64') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Cast(data, to=11) -> ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded_function_data_double
Exp(ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded_function_data_double) -> ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded_function_data_exp
ReduceSum(ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded_function_data_exp, axes, keepdims=1) -> ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded_function_reduced_sum
Log(ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded_function_reduced_sum) -> ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded_function_reduced_double
CastLike(ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded_function_reduced_double, data) -> reduced
output: name='reduced' type=dtype('float64') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_log_sum_exp_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceLogSumExp(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float64') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float64') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Cast(data, to=11) -> ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded_function_data_double
Exp(ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded_function_data_double) -> ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded_function_data_exp
ReduceSum(ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded_function_data_exp, axes, keepdims=1) -> ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded_function_reduced_sum
Log(ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded_function_reduced_sum) -> ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded_function_reduced_double
CastLike(ReduceLogSumExp_test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded_function_reduced_double, data) -> reduced
output: name='reduced' type=dtype('float64') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_log_sum_negative_axes_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 4, 5]
input: name='axes' type=dtype('int64') shape=[1]
ReduceLogSum(data, axes) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 5].
======================================================================
ERROR: test_reduce_log_sum_negative_axes_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 4, 5]
input: name='axes' type=dtype('int64') shape=[1]
ReduceSum(data, axes, keepdims=1) -> ReduceLogSum_test_reduce_log_sum_negative_axes_expanded_function_reduced_sum
Log(ReduceLogSum_test_reduce_log_sum_negative_axes_expanded_function_reduced_sum) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 5].
======================================================================
ERROR: test_reduce_max_default_axes_keepdim_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
ReduceMax(data, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_max_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
ReduceMax(data, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_max_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMax(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_max_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMax(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_max_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMax(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_max_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMax(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_max_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMax(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_max_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMax(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_mean_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
ReduceMean(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_mean_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
ReduceMean(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_mean_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMean(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_mean_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMean(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_mean_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMean(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_mean_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMean(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_mean_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMean(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_mean_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMean(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_min_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
ReduceMin(data, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_min_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
ReduceMin(data, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_min_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMin(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_min_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMin(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_min_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMin(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_min_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMin(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_min_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMin(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_min_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceMin(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_prod_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
ReduceProd(data, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_prod_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
ReduceProd(data, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_prod_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceProd(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_prod_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceProd(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_prod_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceProd(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_prod_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceProd(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_prod_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceProd(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_prod_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceProd(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_sum_square_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
ReduceSumSquare(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_sum_square_default_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
Mul(data, data) -> ReduceSumSquare_test_reduce_sum_square_default_axes_keepdims_example_expanded_function_data_square
ReduceSum(ReduceSumSquare_test_reduce_sum_square_default_axes_keepdims_example_expanded_function_data_square, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_sum_square_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
ReduceSumSquare(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_sum_square_default_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[None]
Mul(data, data) -> ReduceSumSquare_test_reduce_sum_square_default_axes_keepdims_random_expanded_function_data_square
ReduceSum(ReduceSumSquare_test_reduce_sum_square_default_axes_keepdims_random_expanded_function_data_square, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[1, 1, 1].
======================================================================
ERROR: test_reduce_sum_square_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceSumSquare(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_sum_square_do_not_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Mul(data, data) -> ReduceSumSquare_test_reduce_sum_square_do_not_keepdims_example_expanded_function_data_square
ReduceSum(ReduceSumSquare_test_reduce_sum_square_do_not_keepdims_example_expanded_function_data_square, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_sum_square_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceSumSquare(data, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_sum_square_do_not_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Mul(data, data) -> ReduceSumSquare_test_reduce_sum_square_do_not_keepdims_random_expanded_function_data_square
ReduceSum(ReduceSumSquare_test_reduce_sum_square_do_not_keepdims_random_expanded_function_data_square, axes, keepdims=0) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 2].
======================================================================
ERROR: test_reduce_sum_square_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceSumSquare(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_sum_square_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Mul(data, data) -> ReduceSumSquare_test_reduce_sum_square_keepdims_example_expanded_function_data_square
ReduceSum(ReduceSumSquare_test_reduce_sum_square_keepdims_example_expanded_function_data_square, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_sum_square_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceSumSquare(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_sum_square_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Mul(data, data) -> ReduceSumSquare_test_reduce_sum_square_keepdims_random_expanded_function_data_square
ReduceSum(ReduceSumSquare_test_reduce_sum_square_keepdims_random_expanded_function_data_square, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_sum_square_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceSumSquare(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_sum_square_negative_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Mul(data, data) -> ReduceSumSquare_test_reduce_sum_square_negative_axes_keepdims_example_expanded_function_data_square
ReduceSum(ReduceSumSquare_test_reduce_sum_square_negative_axes_keepdims_example_expanded_function_data_square, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_sum_square_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
ReduceSumSquare(data, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reduce_sum_square_negative_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 2, 2]
input: name='axes' type=dtype('int64') shape=[1]
Mul(data, data) -> ReduceSumSquare_test_reduce_sum_square_negative_axes_keepdims_random_expanded_function_data_square
ReduceSum(ReduceSumSquare_test_reduce_sum_square_negative_axes_keepdims_random_expanded_function_data_square, axes, keepdims=1) -> reduced
output: name='reduced' type=dtype('float32') shape=[3, 1, 2].
======================================================================
ERROR: test_reflect_pad_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('int32') shape=[1, 3, 4, 5]
input: name='pads' type=dtype('int64') shape=[8]
Pad(x, pads, mode=b'reflect') -> y
output: name='y' type=dtype('int32') shape=[1, 3, 6, 7].
======================================================================
ERROR: test_relu_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value=0.0) -> Relu_test_relu_expanded_function_Zero
CastLike(Relu_test_relu_expanded_function_Zero, x) -> Relu_test_relu_expanded_function_ZeroCast
Max(x, Relu_test_relu_expanded_function_ZeroCast) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_resize_downsample_scales_cubic_A_n0p5_exclude_outside_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, cubic_coeff_a=-0.50, exclude_outside=1, mode=b'cubic') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 3, 3].
======================================================================
ERROR: test_resize_downsample_scales_cubic_align_corners_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, coordinate_transformation_mode=b'align_corners', mode=b'cubic') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 3, 3].
======================================================================
ERROR: test_resize_downsample_scales_cubic_antialias_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, antialias=1, mode=b'cubic') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 2, 2].
======================================================================
ERROR: test_resize_downsample_scales_cubic_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, mode=b'cubic') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 3, 3].
======================================================================
ERROR: test_resize_downsample_scales_linear_align_corners_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 4]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, coordinate_transformation_mode=b'align_corners', mode=b'linear') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 1, 2].
======================================================================
ERROR: test_resize_downsample_scales_linear_antialias_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, antialias=1, mode=b'linear') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 2, 2].
======================================================================
ERROR: test_resize_downsample_scales_linear_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 4]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, mode=b'linear') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 1, 2].
======================================================================
ERROR: test_resize_downsample_scales_nearest_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 4]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, mode=b'nearest') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 1, 2].
======================================================================
ERROR: test_resize_downsample_sizes_cubic_antialias_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='sizes' type=dtype('int64') shape=[4]
Resize(X, , , sizes, antialias=1, mode=b'cubic') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 3, 3].
======================================================================
ERROR: test_resize_downsample_sizes_cubic_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='sizes' type=dtype('int64') shape=[4]
Resize(X, , , sizes, mode=b'cubic') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 3, 3].
======================================================================
ERROR: test_resize_downsample_sizes_linear_antialias_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='sizes' type=dtype('int64') shape=[4]
Resize(X, , , sizes, antialias=1, mode=b'linear') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 3, 3].
======================================================================
ERROR: test_resize_downsample_sizes_linear_pytorch_half_pixel_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='sizes' type=dtype('int64') shape=[4]
Resize(X, , , sizes, coordinate_transformation_mode=b'pytorch_half_pixel', mode=b'linear') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 3, 1].
======================================================================
ERROR: test_resize_downsample_sizes_nearest_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 4]
input: name='sizes' type=dtype('int64') shape=[4]
Resize(X, , , sizes, mode=b'nearest') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 1, 3].
======================================================================
ERROR: test_resize_downsample_sizes_nearest_not_larger_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 4]
input: name='sizes' type=dtype('int64') shape=[2]
Resize(X, , , sizes, axes=[2,3], keep_aspect_ratio_policy=b'not_larger', mode=b'nearest') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 1, 2].
======================================================================
ERROR: test_resize_downsample_sizes_nearest_not_smaller_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 4]
input: name='sizes' type=dtype('int64') shape=[2]
Resize(X, , , sizes, axes=[2,3], keep_aspect_ratio_policy=b'not_smaller', mode=b'nearest') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 2, 3].
======================================================================
ERROR: test_resize_tf_crop_and_resize_axes_2_3_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='roi' type=dtype('float32') shape=[4]
input: name='sizes' type=dtype('int64') shape=[2]
Resize(X, roi, , sizes, axes=[2,3], coordinate_transformation_mode=b'tf_crop_and_resize', mode=b'linear') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 3, 3].
======================================================================
ERROR: test_resize_tf_crop_and_resize_axes_3_2_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='roi' type=dtype('float32') shape=[4]
input: name='sizes' type=dtype('int64') shape=[2]
Resize(X, roi, , sizes, axes=[3,2], coordinate_transformation_mode=b'tf_crop_and_resize', mode=b'linear') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 3, 3].
======================================================================
ERROR: test_resize_tf_crop_and_resize_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='roi' type=dtype('float32') shape=[8]
input: name='sizes' type=dtype('int64') shape=[4]
Resize(X, roi, , sizes, coordinate_transformation_mode=b'tf_crop_and_resize', extrapolation_value=10.00, mode=b'linear') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 3, 3].
======================================================================
ERROR: test_resize_upsample_scales_cubic_A_n0p5_exclude_outside_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, cubic_coeff_a=-0.50, exclude_outside=1, mode=b'cubic') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 8, 8].
======================================================================
ERROR: test_resize_upsample_scales_cubic_align_corners_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, coordinate_transformation_mode=b'align_corners', mode=b'cubic') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 8, 8].
======================================================================
ERROR: test_resize_upsample_scales_cubic_asymmetric_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, coordinate_transformation_mode=b'asymmetric', mode=b'cubic') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 8, 8].
======================================================================
ERROR: test_resize_upsample_scales_cubic_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, mode=b'cubic') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 8, 8].
======================================================================
ERROR: test_resize_upsample_scales_linear_align_corners_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 2]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, coordinate_transformation_mode=b'align_corners', mode=b'linear') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 4, 4].
======================================================================
ERROR: test_resize_upsample_scales_linear_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 2]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, mode=b'linear') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 4, 4].
======================================================================
ERROR: test_resize_upsample_scales_nearest_axes_2_3_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 2]
input: name='scales' type=dtype('float32') shape=[2]
Resize(X, , scales, axes=[2,3], mode=b'nearest') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 4, 6].
======================================================================
ERROR: test_resize_upsample_scales_nearest_axes_3_2_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 2]
input: name='scales' type=dtype('float32') shape=[2]
Resize(X, , scales, axes=[3,2], mode=b'nearest') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 4, 6].
======================================================================
ERROR: test_resize_upsample_scales_nearest_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 2]
input: name='scales' type=dtype('float32') shape=[4]
Resize(X, , scales, mode=b'nearest') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 4, 6].
======================================================================
ERROR: test_resize_upsample_sizes_cubic_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='sizes' type=dtype('int64') shape=[4]
Resize(X, , , sizes, mode=b'cubic') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 9, 10].
======================================================================
ERROR: test_resize_upsample_sizes_nearest_axes_2_3_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 2]
input: name='sizes' type=dtype('int64') shape=[2]
Resize(X, , , sizes, axes=[2,3], mode=b'nearest') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 7, 8].
======================================================================
ERROR: test_resize_upsample_sizes_nearest_axes_3_2_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 2]
input: name='sizes' type=dtype('int64') shape=[2]
Resize(X, , , sizes, axes=[3,2], mode=b'nearest') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 7, 8].
======================================================================
ERROR: test_resize_upsample_sizes_nearest_ceil_half_pixel_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='sizes' type=dtype('int64') shape=[4]
Resize(X, , , sizes, coordinate_transformation_mode=b'half_pixel', mode=b'nearest', nearest_mode=b'ceil') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 8, 8].
======================================================================
ERROR: test_resize_upsample_sizes_nearest_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 2]
input: name='sizes' type=dtype('int64') shape=[4]
Resize(X, , , sizes, mode=b'nearest') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 7, 8].
======================================================================
ERROR: test_resize_upsample_sizes_nearest_floor_align_corners_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='sizes' type=dtype('int64') shape=[4]
Resize(X, , , sizes, coordinate_transformation_mode=b'align_corners', mode=b'nearest', nearest_mode=b'floor') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 8, 8].
======================================================================
ERROR: test_resize_upsample_sizes_nearest_not_larger_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 2, 2]
input: name='sizes' type=dtype('int64') shape=[2]
Resize(X, , , sizes, axes=[2,3], keep_aspect_ratio_policy=b'not_smaller', mode=b'nearest') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 8, 8].
======================================================================
ERROR: test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='X' type=dtype('float32') shape=[1, 1, 4, 4]
input: name='sizes' type=dtype('int64') shape=[4]
Resize(X, , , sizes, coordinate_transformation_mode=b'asymmetric', mode=b'nearest', nearest_mode=b'round_prefer_ceil') -> Y
output: name='Y' type=dtype('float32') shape=[1, 1, 8, 8].
======================================================================
ERROR: test_scatter_elements_with_axis_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[1, 5]
input: name='indices' type=dtype('int64') shape=[1, 2]
input: name='updates' type=dtype('float32') shape=[1, 2]
ScatterElements(data, indices, updates, axis=1) -> y
output: name='y' type=dtype('float32') shape=[1, 5].
======================================================================
ERROR: test_scatter_elements_with_duplicate_indices_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[1, 5]
input: name='indices' type=dtype('int64') shape=[1, 2]
input: name='updates' type=dtype('float32') shape=[1, 2]
ScatterElements(data, indices, updates, axis=1, reduction=b'add') -> y
output: name='y' type=dtype('float32') shape=[1, 5].
======================================================================
ERROR: test_scatter_elements_with_negative_indices_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[1, 5]
input: name='indices' type=dtype('int64') shape=[1, 2]
input: name='updates' type=dtype('float32') shape=[1, 2]
ScatterElements(data, indices, updates, axis=1) -> y
output: name='y' type=dtype('float32') shape=[1, 5].
======================================================================
ERROR: test_scatter_elements_with_reduction_max_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[1, 5]
input: name='indices' type=dtype('int64') shape=[1, 2]
input: name='updates' type=dtype('float32') shape=[1, 2]
ScatterElements(data, indices, updates, axis=1, reduction=b'max') -> y
output: name='y' type=dtype('float32') shape=[1, 5].
======================================================================
ERROR: test_scatter_elements_with_reduction_min_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[1, 5]
input: name='indices' type=dtype('int64') shape=[1, 2]
input: name='updates' type=dtype('float32') shape=[1, 2]
ScatterElements(data, indices, updates, axis=1, reduction=b'min') -> y
output: name='y' type=dtype('float32') shape=[1, 5].
======================================================================
ERROR: test_scatter_elements_without_axis_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[3, 3]
input: name='indices' type=dtype('int64') shape=[2, 3]
input: name='updates' type=dtype('float32') shape=[2, 3]
ScatterElements(data, indices, updates) -> y
output: name='y' type=dtype('float32') shape=[3, 3].
======================================================================
ERROR: test_scatternd_add_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[4, 4, 4]
input: name='indices' type=dtype('int64') shape=[2, 1]
input: name='updates' type=dtype('float32') shape=[2, 4, 4]
ScatterND(data, indices, updates, reduction=b'add') -> y
output: name='y' type=dtype('float32') shape=[4, 4, 4].
======================================================================
ERROR: test_scatternd_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[4, 4, 4]
input: name='indices' type=dtype('int64') shape=[2, 1]
input: name='updates' type=dtype('float32') shape=[2, 4, 4]
ScatterND(data, indices, updates) -> y
output: name='y' type=dtype('float32') shape=[4, 4, 4].
======================================================================
ERROR: test_scatternd_max_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[4, 4, 4]
input: name='indices' type=dtype('int64') shape=[2, 1]
input: name='updates' type=dtype('float32') shape=[2, 4, 4]
ScatterND(data, indices, updates, reduction=b'max') -> y
output: name='y' type=dtype('float32') shape=[4, 4, 4].
======================================================================
ERROR: test_scatternd_min_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[4, 4, 4]
input: name='indices' type=dtype('int64') shape=[2, 1]
input: name='updates' type=dtype('float32') shape=[2, 4, 4]
ScatterND(data, indices, updates, reduction=b'min') -> y
output: name='y' type=dtype('float32') shape=[4, 4, 4].
======================================================================
ERROR: test_scatternd_multiply_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='data' type=dtype('float32') shape=[4, 4, 4]
input: name='indices' type=dtype('int64') shape=[2, 1]
input: name='updates' type=dtype('float32') shape=[2, 4, 4]
ScatterND(data, indices, updates, reduction=b'mul') -> y
output: name='y' type=dtype('float32') shape=[4, 4, 4].
======================================================================
ERROR: test_selu_default_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value_float=1.6732631921768188) -> Selu_test_selu_default_expanded_function_Alpha
CastLike(Selu_test_selu_default_expanded_function_Alpha, x) -> Selu_test_selu_default_expanded_function_AlphaCast
Constant(value_float=1.0507010221481323) -> Selu_test_selu_default_expanded_function_Gamma
CastLike(Selu_test_selu_default_expanded_function_Gamma, x) -> Selu_test_selu_default_expanded_function_GammaCast
Mul(Selu_test_selu_default_expanded_function_GammaCast, x) -> Selu_test_selu_default_expanded_function_Pos
Constant(value=0.0) -> Selu_test_selu_default_expanded_function_Zero
CastLike(Selu_test_selu_default_expanded_function_Zero, x) -> Selu_test_selu_default_expanded_function_ZeroCast
Less(x, Selu_test_selu_default_expanded_function_ZeroCast) -> Selu_test_selu_default_expanded_function_XLessThanZero
Exp(x) -> Selu_test_selu_default_expanded_function_ExpX
Mul(Selu_test_selu_default_expanded_function_AlphaCast, Selu_test_selu_default_expanded_function_ExpX) -> Selu_test_selu_default_expanded_function_AlphaMulExpX
Sub(Selu_test_selu_default_expanded_function_AlphaMulExpX, Selu_test_selu_default_expanded_function_AlphaCast) -> Selu_test_selu_default_expanded_function_AlphaMulExpXSubAlpha
Mul(Selu_test_selu_default_expanded_function_GammaCast, Selu_test_selu_default_expanded_function_AlphaMulExpXSubAlpha) -> Selu_test_selu_default_expanded_function_Neg
Where(Selu_test_selu_default_expanded_function_XLessThanZero, Selu_test_selu_default_expanded_function_Neg, Selu_test_selu_default_expanded_function_Pos) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_selu_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3]
Constant(value_float=2.0) -> Selu_test_selu_example_expanded_function_Alpha
CastLike(Selu_test_selu_example_expanded_function_Alpha, x) -> Selu_test_selu_example_expanded_function_AlphaCast
Constant(value_float=3.0) -> Selu_test_selu_example_expanded_function_Gamma
CastLike(Selu_test_selu_example_expanded_function_Gamma, x) -> Selu_test_selu_example_expanded_function_GammaCast
Mul(Selu_test_selu_example_expanded_function_GammaCast, x) -> Selu_test_selu_example_expanded_function_Pos
Constant(value=0.0) -> Selu_test_selu_example_expanded_function_Zero
CastLike(Selu_test_selu_example_expanded_function_Zero, x) -> Selu_test_selu_example_expanded_function_ZeroCast
Less(x, Selu_test_selu_example_expanded_function_ZeroCast) -> Selu_test_selu_example_expanded_function_XLessThanZero
Exp(x) -> Selu_test_selu_example_expanded_function_ExpX
Mul(Selu_test_selu_example_expanded_function_AlphaCast, Selu_test_selu_example_expanded_function_ExpX) -> Selu_test_selu_example_expanded_function_AlphaMulExpX
Sub(Selu_test_selu_example_expanded_function_AlphaMulExpX, Selu_test_selu_example_expanded_function_AlphaCast) -> Selu_test_selu_example_expanded_function_AlphaMulExpXSubAlpha
Mul(Selu_test_selu_example_expanded_function_GammaCast, Selu_test_selu_example_expanded_function_AlphaMulExpXSubAlpha) -> Selu_test_selu_example_expanded_function_Neg
Where(Selu_test_selu_example_expanded_function_XLessThanZero, Selu_test_selu_example_expanded_function_Neg, Selu_test_selu_example_expanded_function_Pos) -> y
output: name='y' type=dtype('float32') shape=[3].
======================================================================
ERROR: test_selu_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value_float=2.0) -> Selu_test_selu_expanded_function_Alpha
CastLike(Selu_test_selu_expanded_function_Alpha, x) -> Selu_test_selu_expanded_function_AlphaCast
Constant(value_float=3.0) -> Selu_test_selu_expanded_function_Gamma
CastLike(Selu_test_selu_expanded_function_Gamma, x) -> Selu_test_selu_expanded_function_GammaCast
Mul(Selu_test_selu_expanded_function_GammaCast, x) -> Selu_test_selu_expanded_function_Pos
Constant(value=0.0) -> Selu_test_selu_expanded_function_Zero
CastLike(Selu_test_selu_expanded_function_Zero, x) -> Selu_test_selu_expanded_function_ZeroCast
Less(x, Selu_test_selu_expanded_function_ZeroCast) -> Selu_test_selu_expanded_function_XLessThanZero
Exp(x) -> Selu_test_selu_expanded_function_ExpX
Mul(Selu_test_selu_expanded_function_AlphaCast, Selu_test_selu_expanded_function_ExpX) -> Selu_test_selu_expanded_function_AlphaMulExpX
Sub(Selu_test_selu_expanded_function_AlphaMulExpX, Selu_test_selu_expanded_function_AlphaCast) -> Selu_test_selu_expanded_function_AlphaMulExpXSubAlpha
Mul(Selu_test_selu_expanded_function_GammaCast, Selu_test_selu_expanded_function_AlphaMulExpXSubAlpha) -> Selu_test_selu_expanded_function_Neg
Where(Selu_test_selu_expanded_function_XLessThanZero, Selu_test_selu_expanded_function_Neg, Selu_test_selu_expanded_function_Pos) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_sequence_insert_at_back_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_sequence_insert_at_front_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_sequence_map_add_1_sequence_1_tensor_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_sequence_map_add_1_sequence_1_tensor_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_sequence_map_add_2_sequences_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_sequence_map_add_2_sequences_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_sequence_map_extract_shapes_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_sequence_map_extract_shapes_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_sequence_map_identity_1_sequence_1_tensor_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_sequence_map_identity_1_sequence_1_tensor_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_sequence_map_identity_1_sequence_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_sequence_map_identity_1_sequence_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_sequence_map_identity_2_sequences_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_sequence_map_identity_2_sequences_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 119, in run
return self.sess._sess.run_with_ort_values(
RuntimeError: Unable to cast Python instance to C++ type (compile in debug mode for details)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 359, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
outs = self._session.run(feeds)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 896, in run
return self._run(inputs, clean_right_away=False, # pylint: disable=E1123
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1401, in _run_whole_runtime
res = self._whole.run(inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in run
{k: v._get_c_value() for k, v in inputs.items()},
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 123, in <dictcomp>
{k: v._get_c_value() for k, v in inputs.items()},
AttributeError: 'list' object has no attribute '_get_c_value'
======================================================================
ERROR: test_shrink_hard_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[5]
Constant(value_float=1.5) -> Shrink_test_shrink_hard_expanded_function_Lambd
CastLike(Shrink_test_shrink_hard_expanded_function_Lambd, x) -> Shrink_test_shrink_hard_expanded_function_LambdCast
Neg(Shrink_test_shrink_hard_expanded_function_LambdCast) -> Shrink_test_shrink_hard_expanded_function_NegLmbda
Less(x, Shrink_test_shrink_hard_expanded_function_NegLmbda) -> Shrink_test_shrink_hard_expanded_function_InputLessThanNegLambda
Constant(value_float=0.0) -> Shrink_test_shrink_hard_expanded_function_Bias
CastLike(Shrink_test_shrink_hard_expanded_function_Bias, x) -> Shrink_test_shrink_hard_expanded_function_BiasCast
Add(x, Shrink_test_shrink_hard_expanded_function_BiasCast) -> Shrink_test_shrink_hard_expanded_function_InputAddBias
Constant(value=0.0) -> Shrink_test_shrink_hard_expanded_function_Zero
CastLike(Shrink_test_shrink_hard_expanded_function_Zero, x) -> Shrink_test_shrink_hard_expanded_function_ZeroCast
Sub(x, Shrink_test_shrink_hard_expanded_function_BiasCast) -> Shrink_test_shrink_hard_expanded_function_InputSubBias
Less(Shrink_test_shrink_hard_expanded_function_LambdCast, x) -> Shrink_test_shrink_hard_expanded_function_LambdaLessThanInput
Where(Shrink_test_shrink_hard_expanded_function_LambdaLessThanInput, Shrink_test_shrink_hard_expanded_function_InputSubBias, Shrink_test_shrink_hard_expanded_function_ZeroCast) -> Shrink_test_shrink_hard_expanded_function_InputSubBiasOrZero
Where(Shrink_test_shrink_hard_expanded_function_InputLessThanNegLambda, Shrink_test_shrink_hard_expanded_function_InputAddBias, Shrink_test_shrink_hard_expanded_function_InputSubBiasOrZero) -> y
output: name='y' type=dtype('float32') shape=[5].
======================================================================
ERROR: test_shrink_soft_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[5]
Constant(value_float=1.5) -> Shrink_test_shrink_soft_expanded_function_Lambd
CastLike(Shrink_test_shrink_soft_expanded_function_Lambd, x) -> Shrink_test_shrink_soft_expanded_function_LambdCast
Neg(Shrink_test_shrink_soft_expanded_function_LambdCast) -> Shrink_test_shrink_soft_expanded_function_NegLmbda
Less(x, Shrink_test_shrink_soft_expanded_function_NegLmbda) -> Shrink_test_shrink_soft_expanded_function_InputLessThanNegLambda
Constant(value_float=1.5) -> Shrink_test_shrink_soft_expanded_function_Bias
CastLike(Shrink_test_shrink_soft_expanded_function_Bias, x) -> Shrink_test_shrink_soft_expanded_function_BiasCast
Add(x, Shrink_test_shrink_soft_expanded_function_BiasCast) -> Shrink_test_shrink_soft_expanded_function_InputAddBias
Constant(value=0.0) -> Shrink_test_shrink_soft_expanded_function_Zero
CastLike(Shrink_test_shrink_soft_expanded_function_Zero, x) -> Shrink_test_shrink_soft_expanded_function_ZeroCast
Sub(x, Shrink_test_shrink_soft_expanded_function_BiasCast) -> Shrink_test_shrink_soft_expanded_function_InputSubBias
Less(Shrink_test_shrink_soft_expanded_function_LambdCast, x) -> Shrink_test_shrink_soft_expanded_function_LambdaLessThanInput
Where(Shrink_test_shrink_soft_expanded_function_LambdaLessThanInput, Shrink_test_shrink_soft_expanded_function_InputSubBias, Shrink_test_shrink_soft_expanded_function_ZeroCast) -> Shrink_test_shrink_soft_expanded_function_InputSubBiasOrZero
Where(Shrink_test_shrink_soft_expanded_function_InputLessThanNegLambda, Shrink_test_shrink_soft_expanded_function_InputAddBias, Shrink_test_shrink_soft_expanded_function_InputSubBiasOrZero) -> y
output: name='y' type=dtype('float32') shape=[5].
======================================================================
ERROR: test_simple_rnn_batchwise_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.RuntimeException: [ONNXRuntimeError] : 6 : RUNTIME_EXCEPTION : Exception during initialization: /onnxruntime_src/onnxruntime/core/providers/cpu/rnn/rnn.h:45 onnxruntime::RNN<T>::RNN(const onnxruntime::OpKernelInfo&) [with T = float] layout_ == 0 was false. Batchwise recurrent operations (layout == 1) are not supported. If you need support create a github issue with justification.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 6 : RUNTIME_EXCEPTION : Exception during initialization: /onnxruntime_src/onnxruntime/core/providers/cpu/rnn/rnn.h:45 onnxruntime::RNN<T>::RNN(const onnxruntime::OpKernelInfo&) [with T = float] layout_ == 0 was false. Batchwise recurrent operations (layout == 1) are not supported. If you need support create a github issue with justification.
'
opset: domain='' version=14
input: name='X' type=dtype('float32') shape=[3, 1, 2]
input: name='W' type=dtype('float32') shape=[1, 4, 2]
input: name='R' type=dtype('float32') shape=[1, 4, 4]
RNN(X, W, R, hidden_size=4, layout=1) -> Y, Y_h
output: name='Y' type=dtype('float32') shape=[3, 1, 1, 4]
output: name='Y_h' type=dtype('float32') shape=[3, 1, 4].
======================================================================
ERROR: test_softmax_axis_0_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value=[0]) -> Softmax_test_softmax_axis_0_expanded_function_axes
ReduceMax(x, Softmax_test_softmax_axis_0_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_axis_0_expanded_function_X_ReduceMax
Sub(x, Softmax_test_softmax_axis_0_expanded_function_X_ReduceMax) -> Softmax_test_softmax_axis_0_expanded_function_X_Sub
Exp(Softmax_test_softmax_axis_0_expanded_function_X_Sub) -> Softmax_test_softmax_axis_0_expanded_function_X_Exp
ReduceSum(Softmax_test_softmax_axis_0_expanded_function_X_Exp, Softmax_test_softmax_axis_0_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_axis_0_expanded_function_X_ReduceSum
Div(Softmax_test_softmax_axis_0_expanded_function_X_Exp, Softmax_test_softmax_axis_0_expanded_function_X_ReduceSum) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_softmax_axis_1_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value=[1]) -> Softmax_test_softmax_axis_1_expanded_function_axes
ReduceMax(x, Softmax_test_softmax_axis_1_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_axis_1_expanded_function_X_ReduceMax
Sub(x, Softmax_test_softmax_axis_1_expanded_function_X_ReduceMax) -> Softmax_test_softmax_axis_1_expanded_function_X_Sub
Exp(Softmax_test_softmax_axis_1_expanded_function_X_Sub) -> Softmax_test_softmax_axis_1_expanded_function_X_Exp
ReduceSum(Softmax_test_softmax_axis_1_expanded_function_X_Exp, Softmax_test_softmax_axis_1_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_axis_1_expanded_function_X_ReduceSum
Div(Softmax_test_softmax_axis_1_expanded_function_X_Exp, Softmax_test_softmax_axis_1_expanded_function_X_ReduceSum) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_softmax_axis_2_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value=[2]) -> Softmax_test_softmax_axis_2_expanded_function_axes
ReduceMax(x, Softmax_test_softmax_axis_2_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_axis_2_expanded_function_X_ReduceMax
Sub(x, Softmax_test_softmax_axis_2_expanded_function_X_ReduceMax) -> Softmax_test_softmax_axis_2_expanded_function_X_Sub
Exp(Softmax_test_softmax_axis_2_expanded_function_X_Sub) -> Softmax_test_softmax_axis_2_expanded_function_X_Exp
ReduceSum(Softmax_test_softmax_axis_2_expanded_function_X_Exp, Softmax_test_softmax_axis_2_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_axis_2_expanded_function_X_ReduceSum
Div(Softmax_test_softmax_axis_2_expanded_function_X_Exp, Softmax_test_softmax_axis_2_expanded_function_X_ReduceSum) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_softmax_default_axis_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value=[-1]) -> Softmax_test_softmax_default_axis_expanded_function_axes
ReduceMax(x, Softmax_test_softmax_default_axis_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_default_axis_expanded_function_X_ReduceMax
Sub(x, Softmax_test_softmax_default_axis_expanded_function_X_ReduceMax) -> Softmax_test_softmax_default_axis_expanded_function_X_Sub
Exp(Softmax_test_softmax_default_axis_expanded_function_X_Sub) -> Softmax_test_softmax_default_axis_expanded_function_X_Exp
ReduceSum(Softmax_test_softmax_default_axis_expanded_function_X_Exp, Softmax_test_softmax_default_axis_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_default_axis_expanded_function_X_ReduceSum
Div(Softmax_test_softmax_default_axis_expanded_function_X_Exp, Softmax_test_softmax_default_axis_expanded_function_X_ReduceSum) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_softmax_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[1, 3]
Constant(value=[-1]) -> Softmax_test_softmax_example_expanded_function_axes
ReduceMax(x, Softmax_test_softmax_example_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_example_expanded_function_X_ReduceMax
Sub(x, Softmax_test_softmax_example_expanded_function_X_ReduceMax) -> Softmax_test_softmax_example_expanded_function_X_Sub
Exp(Softmax_test_softmax_example_expanded_function_X_Sub) -> Softmax_test_softmax_example_expanded_function_X_Exp
ReduceSum(Softmax_test_softmax_example_expanded_function_X_Exp, Softmax_test_softmax_example_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_example_expanded_function_X_ReduceSum
Div(Softmax_test_softmax_example_expanded_function_X_Exp, Softmax_test_softmax_example_expanded_function_X_ReduceSum) -> y
output: name='y' type=dtype('float32') shape=[1, 3].
======================================================================
ERROR: test_softmax_large_number_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[2, 4]
Constant(value=[-1]) -> Softmax_test_softmax_large_number_expanded_function_axes
ReduceMax(x, Softmax_test_softmax_large_number_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_large_number_expanded_function_X_ReduceMax
Sub(x, Softmax_test_softmax_large_number_expanded_function_X_ReduceMax) -> Softmax_test_softmax_large_number_expanded_function_X_Sub
Exp(Softmax_test_softmax_large_number_expanded_function_X_Sub) -> Softmax_test_softmax_large_number_expanded_function_X_Exp
ReduceSum(Softmax_test_softmax_large_number_expanded_function_X_Exp, Softmax_test_softmax_large_number_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_large_number_expanded_function_X_ReduceSum
Div(Softmax_test_softmax_large_number_expanded_function_X_Exp, Softmax_test_softmax_large_number_expanded_function_X_ReduceSum) -> y
output: name='y' type=dtype('float32') shape=[2, 4].
======================================================================
ERROR: test_softmax_negative_axis_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value=[-1]) -> Softmax_test_softmax_negative_axis_expanded_function_axes
ReduceMax(x, Softmax_test_softmax_negative_axis_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_negative_axis_expanded_function_X_ReduceMax
Sub(x, Softmax_test_softmax_negative_axis_expanded_function_X_ReduceMax) -> Softmax_test_softmax_negative_axis_expanded_function_X_Sub
Exp(Softmax_test_softmax_negative_axis_expanded_function_X_Sub) -> Softmax_test_softmax_negative_axis_expanded_function_X_Exp
ReduceSum(Softmax_test_softmax_negative_axis_expanded_function_X_Exp, Softmax_test_softmax_negative_axis_expanded_function_axes, keepdims=1) -> Softmax_test_softmax_negative_axis_expanded_function_X_ReduceSum
Div(Softmax_test_softmax_negative_axis_expanded_function_X_Exp, Softmax_test_softmax_negative_axis_expanded_function_X_ReduceSum) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_softplus_example_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Exp(1) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Exp(1) node with name '''
opset: domain='' version=1
input: name='x' type=dtype('float32') shape=[3]
Constant(value=1.0) -> Softplus_test_softplus_example_expanded_function_one
Exp(x) -> Softplus_test_softplus_example_expanded_function_exp_x
Add(Softplus_test_softplus_example_expanded_function_exp_x, Softplus_test_softplus_example_expanded_function_one) -> Softplus_test_softplus_example_expanded_function_exp_x_add_one
Log(Softplus_test_softplus_example_expanded_function_exp_x_add_one) -> y
output: name='y' type=dtype('float32') shape=[3].
======================================================================
ERROR: test_softplus_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Exp(1) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Exp(1) node with name '''
opset: domain='' version=1
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value=1.0) -> Softplus_test_softplus_expanded_function_one
Exp(x) -> Softplus_test_softplus_expanded_function_exp_x
Add(Softplus_test_softplus_expanded_function_exp_x, Softplus_test_softplus_expanded_function_one) -> Softplus_test_softplus_expanded_function_exp_x_add_one
Log(Softplus_test_softplus_expanded_function_exp_x_add_one) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_softsign_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3]
Abs(x) -> Softsign_test_softsign_example_expanded_function_AbsInput
Constant(value=1.0) -> Softsign_test_softsign_example_expanded_function_One
CastLike(Softsign_test_softsign_example_expanded_function_One, x) -> Softsign_test_softsign_example_expanded_function_OneCast
Add(Softsign_test_softsign_example_expanded_function_OneCast, Softsign_test_softsign_example_expanded_function_AbsInput) -> Softsign_test_softsign_example_expanded_function_OneAddAbsInput
Div(x, Softsign_test_softsign_example_expanded_function_OneAddAbsInput) -> y
output: name='y' type=dtype('float32') shape=[3].
======================================================================
ERROR: test_softsign_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Abs(x) -> Softsign_test_softsign_expanded_function_AbsInput
Constant(value=1.0) -> Softsign_test_softsign_expanded_function_One
CastLike(Softsign_test_softsign_expanded_function_One, x) -> Softsign_test_softsign_expanded_function_OneCast
Add(Softsign_test_softsign_expanded_function_OneCast, Softsign_test_softsign_expanded_function_AbsInput) -> Softsign_test_softsign_expanded_function_OneAddAbsInput
Div(x, Softsign_test_softsign_expanded_function_OneAddAbsInput) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_split_1d_uneven_split_opset18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[7]
Split(input, num_outputs=4) -> output_1, output_2, output_3, output_4
output: name='output_1' type=dtype('float32') shape=[2]
output: name='output_2' type=dtype('float32') shape=[2]
output: name='output_3' type=dtype('float32') shape=[2]
output: name='output_4' type=dtype('float32') shape=[1].
======================================================================
ERROR: test_split_2d_uneven_split_opset18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[2, 8]
Split(input, axis=1, num_outputs=3) -> output_1, output_2, output_3
output: name='output_1' type=dtype('float32') shape=[2, 3]
output: name='output_2' type=dtype('float32') shape=[2, 3]
output: name='output_3' type=dtype('float32') shape=[2, 2].
======================================================================
ERROR: test_split_equal_parts_1d_opset18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[6]
Split(input, axis=0, num_outputs=3) -> output_1, output_2, output_3
output: name='output_1' type=dtype('float32') shape=[2]
output: name='output_2' type=dtype('float32') shape=[2]
output: name='output_3' type=dtype('float32') shape=[2].
======================================================================
ERROR: test_split_equal_parts_2d_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[2, 6]
Split(input, axis=1, num_outputs=2) -> output_1, output_2
output: name='output_1' type=dtype('float32') shape=[2, 3]
output: name='output_2' type=dtype('float32') shape=[2, 3].
======================================================================
ERROR: test_split_equal_parts_default_axis_opset18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[6]
Split(input, num_outputs=3) -> output_1, output_2, output_3
output: name='output_1' type=dtype('float32') shape=[2]
output: name='output_2' type=dtype('float32') shape=[2]
output: name='output_3' type=dtype('float32') shape=[2].
======================================================================
ERROR: test_split_variable_parts_1d_opset18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[6]
input: name='split' type=dtype('int64') shape=[2]
Split(input, split, axis=0) -> output_1, output_2
output: name='output_1' type=dtype('float32') shape=[2]
output: name='output_2' type=dtype('float32') shape=[4].
======================================================================
ERROR: test_split_variable_parts_2d_opset18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[2, 6]
input: name='split' type=dtype('int64') shape=[2]
Split(input, split, axis=1) -> output_1, output_2
output: name='output_1' type=dtype('float32') shape=[2, 2]
output: name='output_2' type=dtype('float32') shape=[2, 4].
======================================================================
ERROR: test_split_variable_parts_default_axis_opset18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[6]
input: name='split' type=dtype('int64') shape=[2]
Split(input, split) -> output_1, output_2
output: name='output_1' type=dtype('float32') shape=[2]
output: name='output_2' type=dtype('float32') shape=[4].
======================================================================
ERROR: test_split_zero_size_splits_opset18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='input' type=dtype('float32') shape=[None]
input: name='split' type=dtype('int64') shape=[3]
Split(input, split) -> output_1, output_2, output_3
output: name='output_1' type=dtype('float32') shape=[None]
output: name='output_2' type=dtype('float32') shape=[None]
output: name='output_3' type=dtype('float32') shape=[None].
======================================================================
ERROR: test_sub_uint8_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Sub(14) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Sub(14) node with name '''
opset: domain='' version=14
input: name='x' type=dtype('uint8') shape=[3, 4, 5]
input: name='y' type=dtype('uint8') shape=[3, 4, 5]
Sub(x, y) -> z
output: name='z' type=dtype('uint8') shape=[3, 4, 5].
======================================================================
ERROR: test_thresholdedrelu_default_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value_float=1.0) -> ThresholdedRelu_test_thresholdedrelu_default_expanded_function_Alpha
CastLike(ThresholdedRelu_test_thresholdedrelu_default_expanded_function_Alpha, x) -> ThresholdedRelu_test_thresholdedrelu_default_expanded_function_AlphaCast
Less(ThresholdedRelu_test_thresholdedrelu_default_expanded_function_AlphaCast, x) -> ThresholdedRelu_test_thresholdedrelu_default_expanded_function_AlphaLessThanX
Constant(value=0.0) -> ThresholdedRelu_test_thresholdedrelu_default_expanded_function_Zero
CastLike(ThresholdedRelu_test_thresholdedrelu_default_expanded_function_Zero, x) -> ThresholdedRelu_test_thresholdedrelu_default_expanded_function_ZeroCast
Where(ThresholdedRelu_test_thresholdedrelu_default_expanded_function_AlphaLessThanX, x, ThresholdedRelu_test_thresholdedrelu_default_expanded_function_ZeroCast) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_thresholdedrelu_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[5]
Constant(value_float=2.0) -> ThresholdedRelu_test_thresholdedrelu_example_expanded_function_Alpha
CastLike(ThresholdedRelu_test_thresholdedrelu_example_expanded_function_Alpha, x) -> ThresholdedRelu_test_thresholdedrelu_example_expanded_function_AlphaCast
Less(ThresholdedRelu_test_thresholdedrelu_example_expanded_function_AlphaCast, x) -> ThresholdedRelu_test_thresholdedrelu_example_expanded_function_AlphaLessThanX
Constant(value=0.0) -> ThresholdedRelu_test_thresholdedrelu_example_expanded_function_Zero
CastLike(ThresholdedRelu_test_thresholdedrelu_example_expanded_function_Zero, x) -> ThresholdedRelu_test_thresholdedrelu_example_expanded_function_ZeroCast
Where(ThresholdedRelu_test_thresholdedrelu_example_expanded_function_AlphaLessThanX, x, ThresholdedRelu_test_thresholdedrelu_example_expanded_function_ZeroCast) -> y
output: name='y' type=dtype('float32') shape=[5].
======================================================================
ERROR: test_thresholdedrelu_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Failed to load model with error: /onnxruntime_src/onnxruntime/core/graph/model_load_utils.h:57 void onnxruntime::model_load_utils::ValidateOpsetForDomain(const std::unordered_map<std::__cxx11::basic_string<char>, int>&, const onnxruntime::logging::Logger&, bool, const string&, int) ONNX Runtime only *guarantees* support for models stamped with official released onnx opset versions. Opset 18 is under development and support for this is limited. The operator schemas and or other functionality may change before next ONNX release and in this case ONNX Runtime will not guarantee backward compatibility. Current official support for domain ai.onnx is till opset 17.
'
opset: domain='' version=18
input: name='x' type=dtype('float32') shape=[3, 4, 5]
Constant(value_float=2.0) -> ThresholdedRelu_test_thresholdedrelu_expanded_function_Alpha
CastLike(ThresholdedRelu_test_thresholdedrelu_expanded_function_Alpha, x) -> ThresholdedRelu_test_thresholdedrelu_expanded_function_AlphaCast
Less(ThresholdedRelu_test_thresholdedrelu_expanded_function_AlphaCast, x) -> ThresholdedRelu_test_thresholdedrelu_expanded_function_AlphaLessThanX
Constant(value=0.0) -> ThresholdedRelu_test_thresholdedrelu_expanded_function_Zero
CastLike(ThresholdedRelu_test_thresholdedrelu_expanded_function_Zero, x) -> ThresholdedRelu_test_thresholdedrelu_expanded_function_ZeroCast
Where(ThresholdedRelu_test_thresholdedrelu_expanded_function_AlphaLessThanX, x, ThresholdedRelu_test_thresholdedrelu_expanded_function_ZeroCast) -> y
output: name='y' type=dtype('float32') shape=[3, 4, 5].
======================================================================
ERROR: test_AvgPool1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 6]
Unsqueeze(0, axes=[3]) -> 1
AveragePool(1, kernel_shape=[2,1], pads=[0,0,0,0], strides=[2,1]) -> 2
Squeeze(2, axes=[3]) -> 3
output: name='3' type=dtype('float32') shape=[2, 3, 3].
======================================================================
ERROR: test_AvgPool1d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 6]
Unsqueeze(0, axes=[3]) -> 1
AveragePool(1, kernel_shape=[2,1], pads=[0,0,0,0], strides=[2,1]) -> 2
Squeeze(2, axes=[3]) -> 3
output: name='3' type=dtype('float32') shape=[2, 3, 3].
======================================================================
ERROR: test_AvgPool2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 6, 6]
AveragePool(0, kernel_shape=[2,2], pads=[0,0,0,0], strides=[2,2]) -> 1
output: name='1' type=dtype('float32') shape=[2, 3, 3, 3].
======================================================================
ERROR: test_AvgPool2d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 6, 6]
AveragePool(0, kernel_shape=[2,2], pads=[0,0,0,0], strides=[2,2]) -> 1
output: name='1' type=dtype('float32') shape=[2, 3, 3, 3].
======================================================================
ERROR: test_AvgPool3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 4, 4, 4]
AveragePool(0, kernel_shape=[2,2,2], pads=[0,0,0,0,0,0], strides=[2,2,2]) -> 1
output: name='1' type=dtype('float32') shape=[2, 3, 2, 2, 2].
======================================================================
ERROR: test_AvgPool3d_stride1_pad0_gpu_input_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 4, 4, 4]
AveragePool(0, kernel_shape=[3,3,3], pads=[0,0,0,0,0,0], strides=[1,1,1]) -> 1
output: name='1' type=dtype('float32') shape=[2, 3, 2, 2, 2].
======================================================================
ERROR: test_AvgPool3d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for AveragePool(1) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 5, 5, 5]
AveragePool(0, kernel_shape=[2,2,2], pads=[0,0,0,0,0,0], strides=[2,2,2]) -> 1
output: name='1' type=dtype('float32') shape=[2, 3, 2, 2, 2].
======================================================================
ERROR: test_BatchNorm1d_3d_input_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BatchNormalization(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BatchNormalization(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[4, 5, 3]
input: name='1' type=dtype('float32') shape=[5]
input: name='2' type=dtype('float32') shape=[5]
input: name='3' type=dtype('float32') shape=[5]
input: name='4' type=dtype('float32') shape=[5]
init: name='1' type=dtype('float32') shape=(5,)
init: name='2' type=dtype('float32') shape=(5,)
init: name='3' type=dtype('float32') shape=(5,)
init: name='4' type=dtype('float32') shape=(5,)
BatchNormalization(0, 1, 2, 3, 4, epsilon=0.00, is_test=1, momentum=0.90) -> 5
output: name='5' type=dtype('float32') shape=[4, 5, 3].
======================================================================
ERROR: test_BatchNorm2d_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BatchNormalization(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BatchNormalization(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 6, 6]
input: name='1' type=dtype('float32') shape=[3]
input: name='2' type=dtype('float32') shape=[3]
input: name='3' type=dtype('float32') shape=[3]
input: name='4' type=dtype('float32') shape=[3]
init: name='1' type=dtype('float32') shape=(3,) -- array([0.736, 0.58 , 0.375], dtype=float32)
init: name='2' type=dtype('float32') shape=(3,) -- array([0., 0., 0.], dtype=float32)
init: name='3' type=dtype('float32') shape=(3,) -- array([0., 0., 0.], dtype=float32)
init: name='4' type=dtype('float32') shape=(3,) -- array([1., 1., 1.], dtype=float32)
BatchNormalization(0, 1, 2, 3, 4, epsilon=0.00, is_test=1, momentum=0.90) -> 5
output: name='5' type=dtype('float32') shape=[2, 3, 6, 6].
======================================================================
ERROR: test_BatchNorm2d_momentum_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BatchNormalization(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BatchNormalization(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 6, 6]
input: name='1' type=dtype('float32') shape=[3]
input: name='2' type=dtype('float32') shape=[3]
input: name='3' type=dtype('float32') shape=[3]
input: name='4' type=dtype('float32') shape=[3]
init: name='1' type=dtype('float32') shape=(3,) -- array([0.532, 0.746, 0.765], dtype=float32)
init: name='2' type=dtype('float32') shape=(3,) -- array([0., 0., 0.], dtype=float32)
init: name='3' type=dtype('float32') shape=(3,) -- array([0., 0., 0.], dtype=float32)
init: name='4' type=dtype('float32') shape=(3,) -- array([1., 1., 1.], dtype=float32)
BatchNormalization(0, 1, 2, 3, 4, epsilon=0.00, is_test=1, momentum=0.20) -> 5
output: name='5' type=dtype('float32') shape=[2, 3, 6, 6].
======================================================================
ERROR: test_BatchNorm3d_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BatchNormalization(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BatchNormalization(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 4, 4, 4]
input: name='1' type=dtype('float32') shape=[3]
input: name='2' type=dtype('float32') shape=[3]
input: name='3' type=dtype('float32') shape=[3]
input: name='4' type=dtype('float32') shape=[3]
init: name='1' type=dtype('float32') shape=(3,) -- array([0.242, 0.961, 0.475], dtype=float32)
init: name='2' type=dtype('float32') shape=(3,) -- array([0., 0., 0.], dtype=float32)
init: name='3' type=dtype('float32') shape=(3,) -- array([0., 0., 0.], dtype=float32)
init: name='4' type=dtype('float32') shape=(3,) -- array([1., 1., 1.], dtype=float32)
BatchNormalization(0, 1, 2, 3, 4, epsilon=0.00, is_test=1, momentum=0.90) -> 5
output: name='5' type=dtype('float32') shape=[2, 3, 4, 4, 4].
======================================================================
ERROR: test_BatchNorm3d_momentum_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BatchNormalization(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for BatchNormalization(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 4, 4, 4]
input: name='1' type=dtype('float32') shape=[3]
input: name='2' type=dtype('float32') shape=[3]
input: name='3' type=dtype('float32') shape=[3]
input: name='4' type=dtype('float32') shape=[3]
init: name='1' type=dtype('float32') shape=(3,) -- array([0.452, 0.16 , 0.689], dtype=float32)
init: name='2' type=dtype('float32') shape=(3,) -- array([0., 0., 0.], dtype=float32)
init: name='3' type=dtype('float32') shape=(3,) -- array([0., 0., 0.], dtype=float32)
init: name='4' type=dtype('float32') shape=(3,) -- array([1., 1., 1.], dtype=float32)
BatchNormalization(0, 1, 2, 3, 4, epsilon=0.00, is_test=1, momentum=0.30) -> 5
output: name='5' type=dtype('float32') shape=[2, 3, 4, 4, 4].
======================================================================
ERROR: test_GLU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Mul(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Mul(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[5, 6]
Split(0, axis=-1) -> 1, 2
Sigmoid(2) -> 3
Mul(1, 3) -> 4
output: name='4' type=dtype('float32') shape=[5, 3].
======================================================================
ERROR: test_GLU_dim_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Mul(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Mul(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[5, 6, 7]
Split(0, axis=1) -> 1, 2
Sigmoid(2) -> 3
Mul(1, 3) -> 4
output: name='4' type=dtype('float32') shape=[5, 3, 7].
======================================================================
ERROR: test_Linear_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Gemm(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Gemm(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[4, 10]
input: name='1' type=dtype('float32') shape=[8, 10]
input: name='2' type=dtype('float32') shape=[8]
init: name='1' type=dtype('float32') shape=(8, 10)
init: name='2' type=dtype('float32') shape=(8,)
Gemm(0, 1, 2, alpha=1.00, beta=1.00, broadcast=1, transB=1) -> 3
output: name='3' type=dtype('float32') shape=[4, 8].
======================================================================
ERROR: test_PReLU_1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for PRelu(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for PRelu(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 4]
input: name='1' type=dtype('float32') shape=[1]
init: name='1' type=dtype('float32') shape=(1,) -- array([0.25], dtype=float32)
PRelu(0, 1) -> 2
output: name='2' type=dtype('float32') shape=[2, 3, 4].
======================================================================
ERROR: test_PReLU_1d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for PRelu(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for PRelu(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 4]
input: name='1' type=dtype('float32') shape=[3]
init: name='1' type=dtype('float32') shape=(3,) -- array([0.25, 0.25, 0.25], dtype=float32)
PRelu(0, 1) -> 2
output: name='2' type=dtype('float32') shape=[2, 3, 4].
======================================================================
ERROR: test_PReLU_2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for PRelu(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for PRelu(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 4, 5]
input: name='1' type=dtype('float32') shape=[1]
init: name='1' type=dtype('float32') shape=(1,) -- array([0.25], dtype=float32)
PRelu(0, 1) -> 2
output: name='2' type=dtype('float32') shape=[2, 3, 4, 5].
======================================================================
ERROR: test_PReLU_2d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for PRelu(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for PRelu(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 4, 5]
input: name='1' type=dtype('float32') shape=[3]
init: name='1' type=dtype('float32') shape=(3,) -- array([0.25, 0.25, 0.25], dtype=float32)
PRelu(0, 1) -> 2
output: name='2' type=dtype('float32') shape=[2, 3, 4, 5].
======================================================================
ERROR: test_PReLU_3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for PRelu(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for PRelu(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 4, 5, 6]
input: name='1' type=dtype('float32') shape=[1]
init: name='1' type=dtype('float32') shape=(1,) -- array([0.25], dtype=float32)
PRelu(0, 1) -> 2
output: name='2' type=dtype('float32') shape=[2, 3, 4, 5, 6].
======================================================================
ERROR: test_PReLU_3d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for PRelu(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for PRelu(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3, 4, 5, 6]
input: name='1' type=dtype('float32') shape=[3]
init: name='1' type=dtype('float32') shape=(3,) -- array([0.25, 0.25, 0.25], dtype=float32)
PRelu(0, 1) -> 2
output: name='2' type=dtype('float32') shape=[2, 3, 4, 5, 6].
======================================================================
ERROR: test_PoissonNLLLLoss_no_reduce_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Mul(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Mul(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[10, 10]
Constant(value=[[-1.38804...) -> 1
Mul(1, 0) -> 3
Exp(0) -> 2
Sub(2, 3) -> 4
output: name='4' type=dtype('float32') shape=[10, 10].
======================================================================
ERROR: test_Softsign_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[3, 2, 5]
Abs(0) -> 1
Constant(value=1.0) -> 2
Add(1, 2, broadcast=1) -> 3
Div(0, 3) -> 4
output: name='4' type=dtype('float32') shape=[3, 2, 5].
======================================================================
ERROR: test_operator_add_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float64') shape=[2, 3]
input: name='1' type=dtype('float64') shape=[3]
Add(0, 1, broadcast=1, axis=1) -> 2
output: name='2' type=dtype('float64') shape=[2, 3].
======================================================================
ERROR: test_operator_add_size1_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float64') shape=[2, 3]
input: name='1' type=dtype('float64') shape=[2, 1]
Add(0, 1, broadcast=1, axis=0) -> 2
output: name='2' type=dtype('float64') shape=[2, 3].
======================================================================
ERROR: test_operator_add_size1_right_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float64') shape=[2, 3]
input: name='1' type=dtype('float64') shape=[3]
Add(0, 1, broadcast=1, axis=1) -> 2
output: name='2' type=dtype('float64') shape=[2, 3].
======================================================================
ERROR: test_operator_add_size1_singleton_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float64') shape=[2, 3]
input: name='1' type=dtype('float64') shape=[1, 3]
Add(0, 1, broadcast=1, axis=0) -> 2
output: name='2' type=dtype('float64') shape=[2, 3].
======================================================================
ERROR: test_operator_addconstant_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float64') shape=[2, 3]
Constant(value=1.0) -> 1
Add(0, 1, broadcast=1) -> 2
output: name='2' type=dtype('float64') shape=[2, 3].
======================================================================
ERROR: test_operator_addmm_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Gemm(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Gemm(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3]
input: name='1' type=dtype('float32') shape=[3, 4]
input: name='2' type=dtype('float32') shape=[4]
Gemm(0, 1, 2, alpha=1.00, beta=1.00, broadcast=1) -> 3
Gemm(0, 1, 3, alpha=1.00, beta=1.00) -> 4
output: name='4' type=dtype('float32') shape=[2, 4].
======================================================================
ERROR: test_operator_basic_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[1]
input: name='1' type=dtype('float32') shape=[1]
Add(0, 1) -> 2
Mul(0, 2) -> 3
Tanh(3) -> 4
Sigmoid(4) -> 5
Neg(5) -> 6
output: name='6' type=dtype('float32') shape=[1].
======================================================================
ERROR: test_operator_mm_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Gemm(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Gemm(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 3]
input: name='1' type=dtype('float32') shape=[3, 4]
Constant(value=[0.0]) -> 2
Gemm(0, 1, 2, alpha=1.00, beta=0.00, broadcast=1) -> 3
output: name='3' type=dtype('float32') shape=[2, 4].
======================================================================
ERROR: test_operator_non_float_params_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('int64') shape=[2, 2]
input: name='1' type=dtype('int64') shape=[2, 2]
init: name='1' type=dtype('int64') shape=(2, 2) -- array([1, 2, 3, 4])
Add(0, 1) -> 2
Mul(0, 2) -> 3
output: name='3' type=dtype('int64') shape=[2, 2].
======================================================================
ERROR: test_operator_params_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Add(6) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[2, 2]
input: name='1' type=dtype('float32') shape=[2, 2]
init: name='1' type=dtype('float32') shape=(2, 2) -- array([1., 2., 3., 4.], dtype=float32)
Add(0, 1) -> 2
Mul(0, 2) -> 3
Tanh(3) -> 4
Sigmoid(4) -> 5
Neg(5) -> 6
output: name='6' type=dtype('float32') shape=[2, 2].
======================================================================
ERROR: test_operator_pow_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 395, in _create_inference_session
sess.initialize_session(providers, provider_options, disabled_optimizers)
onnxruntime.capi.onnxruntime_pybind11_state.NotImplemented: [ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Pow(1) node with name ''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 9 : NOT_IMPLEMENTED : Could not find an implementation for Pow(1) node with name '''
opset: domain='' version=6
input: name='0' type=dtype('float32') shape=[1, 2, 3, 4]
input: name='1' type=dtype('float32') shape=[1, 2, 3, 4]
Pow(0, 1) -> 2
output: name='2' type=dtype('float32') shape=[1, 2, 3, 4].
======================================================================
ERROR: test_gradient_of_add_and_mul_cpu (__main__.OnnxBackendSimpleModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Gradient(-1) is not a registered function/op
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Gradient(-1) is not a registered function/op'
opset: domain='' version=12
opset: domain='ai.onnx.preview.training' version=1
input: name='a' type=dtype('float32') shape=[]
input: name='b' type=dtype('float32') shape=[]
Add(a, b) -> c
Mul(c, a) -> d
Gradient[ai.onnx.preview.training](a, b, xs=b'a',b'b', y=b'd') -> dd_da, dd_db
output: name='d' type=dtype('float32') shape=[]
output: name='dd_da' type=dtype('float32') shape=[]
output: name='dd_db' type=dtype('float32') shape=[].
======================================================================
ERROR: test_gradient_of_add_cpu (__main__.OnnxBackendSimpleModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 87, in __init__
self.sess = InferenceSession(onnx_data, sess_options=sess_options,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 347, in __init__
self._create_inference_session(providers, provider_options, disabled_optimizers)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 386, in _create_inference_session
sess = C.InferenceSession(session_options, self._model_bytes, False, self._read_config_from_model)
onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Gradient(-1) is not a registered function/op
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 268, in create_inference_session
return OnnxInference(model, runtime='onnxruntime1')
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 227, in _init
self._whole = OnnxWholeSession(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_whole/session.py", line 92, in __init__
raise RuntimeError(
RuntimeError: Unable to create InferenceSession due to '[ONNXRuntimeError] : 1 : FAIL : Fatal error: ai.onnx.preview.training:Gradient(-1) is not a registered function/op'
opset: domain='' version=12
opset: domain='ai.onnx.preview.training' version=1
input: name='a' type=dtype('float32') shape=[]
input: name='b' type=dtype('float32') shape=[]
Add(a, b) -> c
Gradient[ai.onnx.preview.training](a, b, xs=b'a',b'b', y=b'c') -> dc_da, dc_db
output: name='c' type=dtype('float32') shape=[]
output: name='dc_da' type=dtype('float32') shape=[]
output: name='dc_db' type=dtype('float32') shape=[].
======================================================================
FAIL: test_bernoulli_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 5 / 10 (50%)
Max absolute difference: 1.
Max relative difference: 1.
x: array([0., 1., 1., 1., 0., 0., 1., 0., 0., 1.])
y: array([0., 1., 1., 0., 0., 1., 0., 1., 1., 1.])
======================================================================
FAIL: test_bernoulli_double_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 8 / 10 (80%)
Max absolute difference: 1.
Max relative difference: 1.
x: array([0., 0., 0., 1., 1., 1., 1., 0., 0., 0.])
y: array([0., 1., 1., 0., 0., 1., 0., 1., 1., 1.])
======================================================================
FAIL: test_bernoulli_double_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 6 / 10 (60%)
Max absolute difference: 1.
Max relative difference: 1.
x: array([0., 0., 0., 0., 0., 0., 1., 1., 0., 0.])
y: array([0., 1., 1., 0., 0., 1., 0., 1., 1., 1.])
======================================================================
FAIL: test_bernoulli_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 7 / 10 (70%)
Max absolute difference: 1.
Max relative difference: 1.
x: array([0., 0., 0., 1., 0., 0., 1., 0., 0., 1.])
y: array([0., 1., 1., 0., 0., 1., 0., 1., 1., 1.])
======================================================================
FAIL: test_bernoulli_seed_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 5 / 10 (50%)
Max absolute difference: 1.
Max relative difference: 1.
x: array([0., 0., 1., 0., 1., 0., 0., 0., 0., 1.], dtype=float32)
y: array([0., 1., 1., 0., 0., 1., 0., 1., 1., 1.], dtype=float32)
======================================================================
FAIL: test_bernoulli_seed_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 5 / 10 (50%)
Max absolute difference: 1.
Max relative difference: 1.
x: array([0., 0., 1., 0., 1., 0., 0., 0., 0., 1.], dtype=float32)
y: array([0., 1., 1., 0., 0., 1., 0., 1., 1., 1.], dtype=float32)
======================================================================
FAIL: test_cast_FLOAT_to_STRING_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 208, in assert_similar_outputs
np.testing.assert_array_equal(outputs[i], ref_outputs[i])
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
Mismatched elements: 3 / 12 (25%)
x: array([['0.9767611', '0.60484552', '0.73926359', '0.039187793'],
['0.28280696', '0.12019656', '0.29614019', '0.11872772'],
['0.31798318', '0.41426298', '0.064147495', '0.6924721']],
dtype=object)
y: array([['0.9767611', '0.6048455', '0.7392636', '0.039187793'],
['0.28280696', '0.12019656', '0.2961402', '0.11872772'],
['0.31798318', '0.41426298', '0.064147495', '0.6924721']],
dtype=object)
======================================================================
FAIL: test_castlike_FLOAT_to_STRING_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 208, in assert_similar_outputs
np.testing.assert_array_equal(outputs[i], ref_outputs[i])
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
Mismatched elements: 3 / 12 (25%)
x: array([['0.9767611', '0.60484552', '0.73926359', '0.039187793'],
['0.28280696', '0.12019656', '0.29614019', '0.11872772'],
['0.31798318', '0.41426298', '0.064147495', '0.6924721']],
dtype=object)
y: array([['0.9767611', '0.6048455', '0.7392636', '0.039187793'],
['0.28280696', '0.12019656', '0.2961402', '0.11872772'],
['0.31798318', '0.41426298', '0.064147495', '0.6924721']],
dtype=object)
======================================================================
FAIL: test_castlike_FLOAT_to_STRING_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 208, in assert_similar_outputs
np.testing.assert_array_equal(outputs[i], ref_outputs[i])
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
Mismatched elements: 3 / 12 (25%)
x: array([['0.9767611', '0.60484552', '0.73926359', '0.039187793'],
['0.28280696', '0.12019656', '0.29614019', '0.11872772'],
['0.31798318', '0.41426298', '0.064147495', '0.6924721']],
dtype=object)
y: array([['0.9767611', '0.6048455', '0.7392636', '0.039187793'],
['0.28280696', '0.12019656', '0.2961402', '0.11872772'],
['0.31798318', '0.41426298', '0.064147495', '0.6924721']],
dtype=object)
======================================================================
FAIL: test_dft_axis_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 10 / 200 (5%)
Max absolute difference: 0.
Max relative difference: 6.613e+10
x: array([[[[ 4.500000e+01, 0.000000e+00],
[-4.999998e+00, 1.538842e+01],
[-4.999992e+00, 6.881907e+00],...
y: array([[[[ 4.500000e+01, 0.000000e+00],
[-5.000000e+00, 1.538842e+01],
[-5.000000e+00, 6.881909e+00],...
======================================================================
FAIL: test_dft_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 10 / 200 (5%)
Max absolute difference: 0.
Max relative difference: 4.689e+09
x: array([[[[ 4.500000e+02, 0.000000e+00],
[ 4.600000e+02, 0.000000e+00],
[ 4.700000e+02, 0.000000e+00],...
y: array([[[[ 4.500000e+02, 0.000000e+00],
[ 4.600000e+02, 0.000000e+00],
[ 4.700000e+02, 0.000000e+00],...
======================================================================
FAIL: test_dft_inverse_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 10 / 200 (5%)
Max absolute difference: 4.101e-05
Max relative difference: 4.689e+09
x: array([[[[ 4.500000e+01, 0.000000e+00],
[ 4.600000e+01, 0.000000e+00],
[ 4.700000e+01, 0.000000e+00],...
y: array([[[[ 4.500000e+01, 0.000000e+00],
[ 4.600000e+01, 0.000000e+00],
[ 4.700000e+01, 0.000000e+00],...
======================================================================
FAIL: test_maxunpool_export_with_output_shape_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 8 / 25 (32%)
Max absolute difference: 8.
Max relative difference: 1.
x: array([[[[0., 0., 0., 0., 0.],
[5., 0., 6., 0., 0.],
[0., 0., 0., 7., 0.],...
y: array([[[[0., 0., 0., 0., 0.],
[0., 5., 0., 6., 0.],
[0., 0., 0., 0., 0.],...
======================================================================
FAIL: test_stft_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 15 / 270 (5.56%)
Max absolute difference: 8.393e-05
Max relative difference: 8.465e-06
x: array([[[[ 1.200000e+02, 0.000000e+00],
[-7.999993e+00, 4.021872e+01],
[-7.999995e+00, 1.931371e+01],...
y: array([[[[ 1.200000e+02, 0.000000e+00],
[-8.000000e+00, 4.021872e+01],
[-8.000000e+00, 1.931371e+01],...
======================================================================
FAIL: test_stft_with_window_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 15 / 270 (5.56%)
Max absolute difference: 6.104e-05
Max relative difference: 3.354e-05
x: array([[[[ 5.599627e+01, 0.000000e+00],
[ 2.399911e+01, 2.493398e+01],
[-7.998686e+00, 2.270421e+01],...
y: array([[[[ 55.996273, 0. ],
[ 23.999105, 24.93398 ],
[ -7.99869 , 22.70421 ],...
======================================================================
FAIL: test_training_dropout_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 23 / 60 (38.3%)
Max absolute difference: 10.212
Max relative difference: 1.
x: array([[[ 0. , 0. , 3.914952, 0. , 0. ],
[-0. , 0. , -0. , -0. , 1.642394],
[ 0. , 0. , 3.044151, 0. , 0. ],...
y: array([[[ 0. , 0. , 0. , 0. , 0. ],
[ -0. , 0. , -0.605429, -0.412875, 0. ],
[ 0.576174, 0. , 0. , 0.4867 , 0. ],...
======================================================================
FAIL: test_training_dropout_default_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 32 / 60 (53.3%)
Max absolute difference: 5.106
Max relative difference: 1.
x: array([[[ 0. , 0. , 1.957476, 0. , 3.735116],
[-0. , 0. , -0.302714, -0.206438, 0.821197],
[ 0. , 2.908547, 1.522075, 0. , 0. ],...
y: array([[[ 3.528105, 0.800314, 1.957476, 4.481786, 0. ],
[-1.954556, 0. , -0.302714, -0.206438, 0. ],
[ 0.288087, 2.908547, 1.522075, 0.24335 , 0. ],...
======================================================================
FAIL: test_training_dropout_default_mask_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 32 / 60 (53.3%)
Max absolute difference: 5.106
Max relative difference: 1.
x: array([[[ 0. , 0. , 1.957476, 0. , 3.735116],
[-0. , 0. , -0.302714, -0.206438, 0.821197],
[ 0. , 2.908547, 1.522075, 0. , 0. ],...
y: array([[[ 3.528105, 0.800314, 1.957476, 4.481786, 0. ],
[-1.954556, 0. , -0.302714, -0.206438, 0. ],
[ 0.288087, 2.908547, 1.522075, 0.24335 , 0. ],...
======================================================================
FAIL: test_training_dropout_mask_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 360, in run
self.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 210, in assert_similar_outputs
np.testing.assert_allclose(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
Mismatched elements: 23 / 60 (38.3%)
Max absolute difference: 10.212
Max relative difference: 1.
x: array([[[ 0. , 0. , 3.914952, 0. , 0. ],
[-0. , 0. , -0. , -0. , 1.642394],
[ 0. , 0. , 3.044151, 0. , 0. ],...
y: array([[[ 0. , 0. , 0. , 0. , 0. ],
[ -0. , 0. , -0.605429, -0.412875, 0. ],
[ 0.576174, 0. , 0. , 0.4867 , 0. ],...
----------------------------------------------------------------------
Ran 2492 tests in 40.216s
FAILED (failures=19, errors=352, skipped=1254)
[runpythonerror]
2023-02-04 07:11:16.736238395 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:16.736661501 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:16.741653360 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:16.742058336 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:16.767103759 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:16.767496845 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:18.405893211 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:18.406289467 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:18.411854590 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:18.412273156 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:18.417331724 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:18.417723880 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:18.422703779 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:18.423111235 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:19.332409760 [E:onnxruntime:, inference_session.cc:1500 operator()] Exception during initialization: /onnxruntime_src/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.h:55 onnxruntime::DeepCpuGruOp::DeepCpuGruOp(const onnxruntime::OpKernelInfo&) layout_ == 0 was false. Batchwise recurrent operations (layout == 1) are not supported. If you need support create a github issue with justification.
2023-02-04 07:11:19.612992505 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:19.613393631 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:19.618325851 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:19.618715577 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:19.651737849 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:19.652134715 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:19.756084570 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:19.756551255 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:19.762329736 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:19.762803531 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:23.179731297 [E:onnxruntime:, inference_session.cc:1500 operator()] Exception during initialization: /onnxruntime_src/onnxruntime/core/providers/cpu/rnn/lstm_base.h:52 onnxruntime::LSTMBase::LSTMBase(const onnxruntime::OpKernelInfo&) layout_ == 0 was false. Batchwise recurrent operations (layout == 1) are not supported. If you need support create a github issue with justification.
2023-02-04 07:11:27.483641157 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:27.484024153 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:27.489527237 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:27.489928203 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:27.495483476 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:27.495886862 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:33.912954314 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:33.913372880 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:33.918304869 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:33.918701995 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:34.007976950 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:34.008382086 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:35.021960933 [E:onnxruntime:, inference_session.cc:1500 operator()] Exception during initialization: /onnxruntime_src/onnxruntime/core/providers/cpu/rnn/rnn.h:45 onnxruntime::RNN<T>::RNN(const onnxruntime::OpKernelInfo&) [with T = float] layout_ == 0 was false. Batchwise recurrent operations (layout == 1) are not supported. If you need support create a github issue with justification.
2023-02-04 07:11:36.512309236 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:36.512715542 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:36.517576792 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:36.517975838 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:36.524117595 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:36.524614190 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:36.541670125 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:36.542153290 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:36.556899029 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:36.557301305 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:36.562787459 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:36.563196415 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.771704652 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.772262116 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.798014192 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.798566396 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.817559422 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.818021847 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.841451477 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.841911333 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.857485663 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.857945708 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.863056386 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.863512621 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.868533280 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.868997535 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.875293810 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.875803115 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.900951718 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.901459453 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.911364481 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.911872666 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.921764404 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.922273019 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.932165578 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.932673403 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.941110706 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.941566041 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.948229993 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.948731538 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.955999033 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.956503898 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.963209130 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.963697955 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.970917401 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.971408596 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.978062198 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.978544833 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.985185735 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.985658440 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:40.992352901 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:40.992820637 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.000040843 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.000520578 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.007216769 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.007677494 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.037836156 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.038298661 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.045337579 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.045784474 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.053381906 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.053842702 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.378978530 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.379503855 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.386369335 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.386904959 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.393893578 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.394399162 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.401192153 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.401705288 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.408591407 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.409089792 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.416297008 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.416784303 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.424415005 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.424906380 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.432005957 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.432484403 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.439233803 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.439708258 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.446457169 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.446945324 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.454233750 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.454704005 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.461068429 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.461512265 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.468818260 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.469281176 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.475985077 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.476437092 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.483902486 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.484362981 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.490875564 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.491315250 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.497154790 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.497555836 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.503431286 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.503900661 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:41.509267776 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:41.509732091 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.100060914 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.100608278 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.106698796 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.107289019 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.113150079 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.113606845 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.118812641 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.119269897 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.125575593 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.126070598 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.145609177 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.146274950 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.151471007 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.151909043 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.157846512 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.158321057 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.163764791 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.164219016 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.190485977 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.190961682 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.228483958 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.228923054 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.234989881 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.235433807 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.240900351 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.241331786 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.247280225 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.247698961 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.261158313 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.261567329 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.277165490 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.277582625 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.305236122 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.305652218 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.321292167 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.321712513 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.333219605 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.333639961 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.360588345 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.361079330 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.376878828 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.377272244 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.382507620 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.382935026 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.388302611 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.388710217 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.394185170 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.394588836 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.400102970 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.400498796 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.405546974 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.405939620 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.948069817 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.948562892 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.953942896 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.954385902 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.960251212 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.960809856 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.981008359 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.981437015 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.986861759 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.987312025 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.993024286 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.993474442 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:42.998607299 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:42.999056154 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.004797306 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.005238551 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.010397368 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.010840244 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.016328247 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.016761383 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.033374213 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.033808458 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.053370348 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.053799033 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.065380235 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.065815641 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.081388101 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.081844086 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.102257347 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.102809091 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.117604620 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.118157244 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.137326048 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.137771793 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.143889711 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.144309596 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.150044318 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.150476733 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.156930527 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.157396222 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.223426866 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.223890951 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.228894480 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.229282856 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.234235725 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.234632051 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.240189664 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.240637659 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.247035274 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.247443260 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.252952593 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.253361259 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.259359977 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.259749593 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.812313023 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.812811098 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.818370381 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.818927875 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.825458048 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.825932214 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.831844213 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.832446627 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.849364403 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.849824289 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.855023876 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.855478581 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.877269898 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.877721363 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.883050799 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.883502774 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.889279005 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.889735380 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.895019516 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.895461301 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.913411647 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.913827593 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.918699493 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.919136909 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.925356765 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.925812061 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.932775449 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.933247074 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:43.941463450 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.
2023-02-04 07:11:43.941873986 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset
2023-02-04 07:11:46.372818633 [W:onnxruntime:, graph.cc:1231 Graph] Initializer pos appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2023-02-04 07:11:46.372866972 [W:onnxruntime:, graph.cc:1231 Graph] Initializer pos_at appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2023-02-04 07:11:46.380764411 [W:onnxruntime:, graph.cc:1231 Graph] Initializer pos_erase appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2023-02-04 07:11:46.380810011 [W:onnxruntime:, graph.cc:1231 Graph] Initializer pos_at appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2023-02-04 07:11:46.389259205 [W:onnxruntime:, graph.cc:1231 Graph] Initializer pos_erase appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2023-02-04 07:11:46.389307584 [W:onnxruntime:, graph.cc:1231 Graph] Initializer pos_insert appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2023-02-04 07:11:46.389329024 [W:onnxruntime:, graph.cc:1231 Graph] Initializer pos_at appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2023-02-04 07:11:46.416099279 [W:onnxruntime:, graph.cc:1231 Graph] Initializer pos_at appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.