ONNX Backends for Eager Evaluation#
Backend class: OnnxInferenceBackendPyEval.
<<<
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_pyeval 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 07:11:49.423194 BEGIN
---------------------------------
---------------------------------
2023-02-04 07:12:16.104468 END
---------------------------------
testsRun=2492 errors=145 skipped=1254
unexpectedSuccesses=0 expectedFailures=0
ratio=0.882876
---------------------------------
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/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op_numpy_helper.py:8: 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) ... ok
test_adagrad_multiple_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_adam_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_adam_multiple_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_add_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_add_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_add_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_random.py:69: 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.
TENSOR_TYPE_TO_NP_TYPE[self.dtype] if self.dtype > 0
FAIL
test_bernoulli_double_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_random.py:138: 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.
None if self.dtype == 0 else TENSOR_TYPE_TO_NP_TYPE[self.dtype])
somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_cast.py:26: 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.
self._dtype = TENSOR_TYPE_TO_NP_TYPE[self.to]
FAIL
test_bernoulli_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_bernoulli_seed_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bernoulli_seed_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_bitshift_left_uint16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ok
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) ... ok
test_bitwise_and_i32_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_and_ui64_bcast_3v1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_and_ui8_bcast_4v3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_not_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_not_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_not_4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_or_i16_4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_or_i32_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_or_ui64_bcast_3v1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_or_ui8_bcast_4v3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_xor_i16_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_xor_i32_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_xor_ui64_bcast_3v1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_bitwise_xor_ui8_bcast_4v3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_blackmanwindow_cpu (__main__.OnnxBackendNodeModelTest) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_window.py:48: 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.
self.dtype = TENSOR_TYPE_TO_NP_TYPE[self.output_datatype]
ERROR
test_blackmanwindow_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_blackmanwindow_symmetric_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
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) ... ok
test_center_crop_pad_crop_and_pad_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_center_crop_pad_crop_axes_chw_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_center_crop_pad_crop_axes_chw_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_center_crop_pad_crop_axes_hwc_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_center_crop_pad_crop_axes_hwc_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_center_crop_pad_crop_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_center_crop_pad_crop_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_center_crop_pad_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_center_crop_pad_pad_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ERROR
test_clip_default_min_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_default_min_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_clip_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_clip_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_clip_inbounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_inbounds_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_clip_outbounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_outbounds_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_clip_splitbounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_clip_splitbounds_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_col2im_5d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_col2im_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_col2im_dilations_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_col2im_pads_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_col2im_strides_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ok
test_constant_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... FAIL
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) ... FAIL
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) ... ok
test_dft_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_dft_inverse_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ok
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) ... FAIL
test_dynamicquantizelinear_max_adjusted_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_dynamicquantizelinear_max_adjusted_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_dynamicquantizelinear_min_adjusted_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_dynamicquantizelinear_min_adjusted_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_edge_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ok
test_elu_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_elu_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_elu_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... FAIL
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) ... ok
test_group_normalization_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_group_normalization_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_gru_batchwise_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_gru_defaults_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_gru_seq_length_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_gru_with_initial_bias_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_hammingwindow_cpu (__main__.OnnxBackendNodeModelTest) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_window.py:107: 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.
self.dtype = TENSOR_TYPE_TO_NP_TYPE[self.output_datatype]
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) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_window.py:80: 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.
self.dtype = TENSOR_TYPE_TO_NP_TYPE[self.output_datatype]
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) ... ok
test_hardsigmoid_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardsigmoid_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_hardsigmoid_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
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) ... ok
test_loop11_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_loop13_seq_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
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) ... FAIL
test_lstm_defaults_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_lstm_with_initial_bias_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_lstm_with_peepholes_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
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) ... ok
test_max_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_int64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_int8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_one_input_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_two_inputs_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_uint16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_max_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... FAIL
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) ... ok
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) ... ok
test_min_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_int64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_int8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_one_input_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_two_inputs_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_uint16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_min_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mish_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mish_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_broadcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mod_int64_fmod_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
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) ... ok
test_momentum_multiple_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ok
test_mvn_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_mvn_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_mvn_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_neg_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_nesterov_momentum_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
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) ... FAIL
test_onehot_with_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
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) ... ok
test_pow_types_float32_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... FAIL
test_range_float_type_positive_delta_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_range_float_type_positive_delta_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_range_int32_type_negative_delta_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_range_int32_type_negative_delta_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_reciprocal_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reciprocal_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_l1.py:50: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
numpy.abs(data), axis=axes if axes else None,
ok
test_reduce_l1_default_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_sum.py:75: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
return (numpy.sum(data, axis=axes if axes else None,
ok
test_reduce_l1_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_default_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_do_not_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_do_not_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_keep_dims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_keep_dims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_negative_axes_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_negative_axes_keep_dims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_negative_axes_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l1_negative_axes_keep_dims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l2_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_default_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l2_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_default_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l2_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_do_not_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l2_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_do_not_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l2_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_keep_dims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l2_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_keep_dims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l2_negative_axes_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_negative_axes_keep_dims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_l2_negative_axes_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_l2_negative_axes_keep_dims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_asc_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_asc_axes_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_default_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_reduce_log_sum_default_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_desc_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_desc_axes_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_log_sum_exp.py:60: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
tax = tuple(axes) if axes else None
ok
test_reduce_log_sum_exp_default_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_default_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_do_not_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_do_not_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_negative_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_log_sum_negative_axes_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_max_default_axes_keepdim_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_max_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_max_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_max_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_max_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_max_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_max_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_max_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_mean_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_mean.py:49: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
return (numpy.mean(data, axis=axes if axes else None,
ok
test_reduce_mean_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_mean_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_mean_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_mean_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_mean_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_mean_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_mean_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_min_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_min_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_min_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_min_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_min_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_min_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_min_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_min_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_prod_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_prod_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_prod_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_prod_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_prod_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_prod_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_prod_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_prod_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_sum_square.py:48: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
return (numpy.sum(numpy.square(data), axis=axes if axes else None,
ok
test_reduce_sum_square_default_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_default_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_do_not_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_do_not_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_negative_axes_keepdims_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reduce_sum_square_negative_axes_keepdims_random_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reflect_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_relu_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_relu_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_reshape_allowzero_reordered_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
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) ... FAIL
test_resize_downsample_scales_cubic_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_downsample_scales_cubic_antialias_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_resize_downsample_scales_cubic_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_downsample_scales_linear_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_downsample_scales_linear_antialias_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_resize_downsample_scales_linear_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_downsample_scales_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_downsample_sizes_cubic_antialias_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_resize_downsample_sizes_cubic_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_downsample_sizes_linear_antialias_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_resize_downsample_sizes_linear_pytorch_half_pixel_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_downsample_sizes_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ok
test_resize_upsample_scales_cubic_A_n0p5_exclude_outside_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_resize_upsample_scales_cubic_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_upsample_scales_cubic_asymmetric_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_upsample_scales_cubic_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_upsample_scales_linear_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_upsample_scales_linear_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ok
test_resize_upsample_sizes_cubic_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ok
test_resize_upsample_sizes_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_upsample_sizes_nearest_floor_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_resize_upsample_sizes_nearest_not_larger_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ERROR
test_scatter_elements_with_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_scatter_elements_with_duplicate_indices_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_scatter_elements_with_negative_indices_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_scatter_elements_with_reduction_max_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_scatter_elements_with_reduction_min_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_scatter_elements_without_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_scatter_with_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_scatter_without_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_scatternd_add_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_scatternd_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_scatternd_max_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_scatternd_min_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_scatternd_multiply_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
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) ... ok
test_selu_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_selu_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_selu_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... FAIL
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) ... ok
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) ... ok
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) ... ok
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) ... ok
test_softmax_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softmax_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ok
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) ... ok
test_softplus_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softplus_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softplus_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softplus_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softsign_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softsign_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softsign_example_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_softsign_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_spacetodepth_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_spacetodepth_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_1d_uneven_split_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_split_2d_uneven_split_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_split_equal_parts_1d_opset13_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_equal_parts_1d_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_equal_parts_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ok
test_split_variable_parts_1d_opset13_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_variable_parts_1d_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_variable_parts_2d_opset13_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_variable_parts_2d_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_variable_parts_default_axis_opset13_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_variable_parts_default_axis_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_zero_size_splits_opset13_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_split_zero_size_splits_opset18_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... FAIL
test_strnormalizer_export_monday_casesensintive_nochangecase_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_strnormalizer_export_monday_casesensintive_upper_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_strnormalizer_export_monday_empty_output_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_strnormalizer_export_monday_insensintive_upper_twodim_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
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) ... ok
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) ... FAIL
test_thresholdedrelu_default_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
test_thresholdedrelu_default_expanded_ver18_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
test_thresholdedrelu_example_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
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) ... ok
test_training_dropout_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_training_dropout_default_mask_cpu (__main__.OnnxBackendNodeModelTest) ... ok
test_training_dropout_mask_cpu (__main__.OnnxBackendNodeModelTest) ... ok
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) ... ok
test_AvgPool1d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_AvgPool2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_AvgPool2d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_AvgPool3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_AvgPool3d_stride1_pad0_gpu_input_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_AvgPool3d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_BatchNorm1d_3d_input_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... 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) ... ERROR
test_Conv1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv1d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv1d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv1d_pad1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv1d_pad1size1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv1d_pad2_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv1d_pad2size1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv1d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv2d_depthwise_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv2d_depthwise_padded_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv2d_depthwise_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv2d_depthwise_with_multiplier_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv2d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv2d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv2d_groups_thnn_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv2d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv2d_padding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv2d_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv3d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv3d_dilated_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv3d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv3d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv3d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Conv3d_stride_padding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_ConvTranspose2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_ConvTranspose2d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_ELU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_Embedding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_Embedding_sparse_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_GLU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_GLU_dim_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
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) ... ERROR
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) ... ok
test_ReLU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_ReflectionPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
test_ReplicationPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
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) ... ok
test_Tanh_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
test_ZeroPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
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) ... ok
test_operator_add_size1_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_add_size1_right_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_add_size1_singleton_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_addconstant_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_addmm_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_basic_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
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) ... ERROR
test_operator_convtranspose_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
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) ... ok
test_operator_non_float_params_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_pad_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_params_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_permute2_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_pow_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_pow.py:19: RuntimeWarning: invalid value encountered in power
return (numpy.power(a, b).astype(a.dtype), )
ok
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) ... ERROR
test_operator_selu_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_sqrt_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_sqrt.py:22: RuntimeWarning: invalid value encountered in sqrt
return (numpy.sqrt(x), )
ok
test_operator_symbolic_override_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
test_operator_symbolic_override_nested_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_operator_view_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ok
test_bvlc_alexnet_cpu (__main__.OnnxBackendRealModelTest) ... ERROR
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) ... ERROR
test_sequence_model2_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
test_sequence_model3_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
test_sequence_model4_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_sequence_model5_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
test_sequence_model6_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
test_sequence_model7_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
test_sequence_model8_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
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) ... FAIL
test_strnorm_model_monday_casesensintive_nochangecase_cpu (__main__.OnnxBackendSimpleModelTest) ... FAIL
test_strnorm_model_monday_casesensintive_upper_cpu (__main__.OnnxBackendSimpleModelTest) ... FAIL
test_strnorm_model_monday_empty_output_cpu (__main__.OnnxBackendSimpleModelTest) ... FAIL
test_strnorm_model_monday_insensintive_upper_twodim_cpu (__main__.OnnxBackendSimpleModelTest) ... FAIL
test_strnorm_model_nostopwords_nochangecase_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
======================================================================
ERROR: test_bernoulli_seed_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "_mt19937.pyx", line 178, in numpy.random._mt19937.MT19937._legacy_seeding
TypeError: 'float' object cannot be interpreted as an integer
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_random.py", line 74, in _run
state = self._get_state(self.seed)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_random.py", line 55, in _get_state
state = numpy.random.RandomState(seed=self.seed)
File "mtrand.pyx", line 185, in numpy.random.mtrand.RandomState.__init__
File "_mt19937.pyx", line 166, in numpy.random._mt19937.MT19937._legacy_seeding
File "_mt19937.pyx", line 186, in numpy.random._mt19937.MT19937._legacy_seeding
TypeError: Cannot cast scalar from dtype('float64') to dtype('int64') according to the rule 'safe'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 239, in run
raise TypeError( # pragma: no cover
TypeError: Issues with types <class 'numpy.ndarray'> (operator Bernoulli).
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_random.Bernoulli'>, inputs=['x'].
======================================================================
ERROR: test_bernoulli_seed_expanded_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "_mt19937.pyx", line 178, in numpy.random._mt19937.MT19937._legacy_seeding
TypeError: 'float' object cannot be interpreted as an integer
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_random.py", line 142, in _run
state = self._get_state(self.seed)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_random.py", line 55, in _get_state
state = numpy.random.RandomState(seed=self.seed)
File "mtrand.pyx", line 185, in numpy.random.mtrand.RandomState.__init__
File "_mt19937.pyx", line 166, in numpy.random._mt19937.MT19937._legacy_seeding
File "_mt19937.pyx", line 186, in numpy.random._mt19937.MT19937._legacy_seeding
TypeError: Cannot cast scalar from dtype('float64') to dtype('int64') according to the rule 'safe'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 239, in run
raise TypeError( # pragma: no cover
TypeError: Issues with types <class 'numpy.ndarray'> (operator RandomUniformLike).
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_random.RandomUniformLike'>, inputs=['x'].
======================================================================
ERROR: test_blackmanwindow_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 202, in assert_similar_outputs
cls.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 198, in assert_similar_outputs
np.testing.assert_equal(len(outputs), len(ref_outputs))
TypeError: object of type 'numpy.float32' has no len()
======================================================================
ERROR: test_blackmanwindow_symmetric_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 202, in assert_similar_outputs
cls.assert_similar_outputs(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 198, in assert_similar_outputs
np.testing.assert_equal(len(outputs), len(ref_outputs))
TypeError: object of type 'numpy.float32' has no len()
======================================================================
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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 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_clip_default_int8_max_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same 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/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same shape () != (3, 4, 5)
======================================================================
ERROR: test_clip_default_max_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same shape () != (3, 4, 5)
======================================================================
ERROR: test_clip_default_min_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same shape () != (3, 4, 5)
======================================================================
ERROR: test_clip_example_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same shape () != (3,)
======================================================================
ERROR: test_clip_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same shape () != (3, 4, 5)
======================================================================
ERROR: test_clip_inbounds_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same shape () != (3,)
======================================================================
ERROR: test_clip_outbounds_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same shape () != (3,)
======================================================================
ERROR: test_clip_splitbounds_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same shape () != (3,)
======================================================================
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 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 348, in create_inference_session
return OnnxSubOnnx(content)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop_convert.py", line 56, in __init__
OnnxOperator.__init__(self, *inputs, output_names=output_names)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 1423, in __init__
raise RuntimeError( # pragma: no cover
RuntimeError: Operator '?' expects a number of inputs in [1, 1000000000.0] not 0 (expected opset=None, class opset=1)
======================================================================
ERROR: test_group_normalization_epsilon_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 258, in _init
node.setup_runtime(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 240, in setup_runtime
self.ops_ = load_op(self.onnx_node, desc=self.desc,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
return lo(onnx_node, desc=desc, options=options)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 91, in load_op
cl = onnx_load_op(options.get('domain', ''),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/reference/ops/_op_list.py", line 294, in load_op
raise RuntimeContextError(
onnx.reference.op_run.RuntimeContextError: No registered implementation for operator 'GroupNormalization' and domain '', the operator has a context dependent function. but argument node or input_types is not defined.
======================================================================
ERROR: test_group_normalization_example_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 258, in _init
node.setup_runtime(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 240, in setup_runtime
self.ops_ = load_op(self.onnx_node, desc=self.desc,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
return lo(onnx_node, desc=desc, options=options)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 91, in load_op
cl = onnx_load_op(options.get('domain', ''),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/reference/ops/_op_list.py", line 294, in load_op
raise RuntimeContextError(
onnx.reference.op_run.RuntimeContextError: No registered implementation for operator 'GroupNormalization' and domain '', the operator has a context dependent function. but argument node or input_types is not defined.
======================================================================
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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
ERROR: test_identity_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 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_loop13_seq_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
ERROR: test_lstm_with_peepholes_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_lstm.py", line 84, in _run
sequence_lens = numpy.squeeze(sequence_lens, axis=0)
File "<__array_function__ internals>", line 180, in squeeze
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py", line 1545, in squeeze
return squeeze(axis=axis)
ValueError: cannot select an axis to squeeze out which has size not equal to one
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_lstm.LSTM'>, inputs=['X', 'W', 'R', 'B', 'sequence_lens', 'initial_h', 'initial_c', 'P'].
======================================================================
ERROR: test_mvn_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 258, in _init
node.setup_runtime(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 240, in setup_runtime
self.ops_ = load_op(self.onnx_node, desc=self.desc,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
return lo(onnx_node, desc=desc, options=options)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 232, in load_op
return cl(onnx_node, {'log': None})
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 172, in <lambda>
new_cls = lambda *args, sess=sess: OpFunction(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 814, in __init__
self.attributes_ = {
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 815, in <dictcomp>
name: getattr(self, name)
AttributeError: 'OpFunction' object has no attribute 'axes'
======================================================================
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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
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_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_optional.py", line 20, in _run
raise TypeError( # pragma: no cover
TypeError: Unexpected type <class 'numpy.ndarray'> for x.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 239, in run
raise TypeError( # pragma: no cover
TypeError: Issues with types <class 'numpy.ndarray'> (operator OptionalGetElement).
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_optional.OptionalGetElement'>, inputs=['optional_input'].
======================================================================
ERROR: test_optional_get_element_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
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_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_optional.py", line 20, in _run
raise TypeError( # pragma: no cover
TypeError: Unexpected type <class 'numpy.ndarray'> for x.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 239, in run
raise TypeError( # pragma: no cover
TypeError: Issues with types <class 'numpy.ndarray'> (operator OptionalGetElement).
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_optional.OptionalGetElement'>, inputs=['optional_input'].
======================================================================
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/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 348, in create_inference_session
return OnnxSubOnnx(content)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop_convert.py", line 56, in __init__
OnnxOperator.__init__(self, *inputs, output_names=output_names)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 1423, in __init__
raise RuntimeError( # pragma: no cover
RuntimeError: Operator '?' expects a number of inputs in [1, 1000000000.0] not 0 (expected opset=None, class opset=1)
======================================================================
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/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 348, in create_inference_session
return OnnxSubOnnx(content)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop_convert.py", line 56, in __init__
OnnxOperator.__init__(self, *inputs, output_names=output_names)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 1423, in __init__
raise RuntimeError( # pragma: no cover
RuntimeError: Operator '?' expects a number of inputs in [1, 1000000000.0] not 0 (expected opset=None, class opset=1)
======================================================================
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/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 348, in create_inference_session
return OnnxSubOnnx(content)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop_convert.py", line 56, in __init__
OnnxOperator.__init__(self, *inputs, output_names=output_names)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 1423, in __init__
raise RuntimeError( # pragma: no cover
RuntimeError: Operator '?' expects a number of inputs in [1, 1000000000.0] not 0 (expected opset=None, class opset=1)
======================================================================
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/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 332, in run
prepared_model = self.backend.prepare(model, device)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
return cls.prepare(binm, device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
inf = cls.create_inference_session(model)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 348, in create_inference_session
return OnnxSubOnnx(content)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop_convert.py", line 56, in __init__
OnnxOperator.__init__(self, *inputs, output_names=output_names)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 1423, in __init__
raise RuntimeError( # pragma: no cover
RuntimeError: Operator '?' expects a number of inputs in [1, 1000000000.0] not 0 (expected opset=None, class opset=1)
======================================================================
ERROR: test_optional_has_element_empty_optional_input_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'NoneType' object has no attribute 'dtype'
======================================================================
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_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_optional.py", line 34, in _run
raise TypeError( # pragma: no cover
TypeError: Unexpected type <class 'numpy.ndarray'> for x.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 239, in run
raise TypeError( # pragma: no cover
TypeError: Issues with types <class 'numpy.ndarray'> (operator OptionalHasElement).
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_optional.OptionalHasElement'>, inputs=['optional_input'].
======================================================================
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_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_optional.py", line 34, in _run
raise TypeError( # pragma: no cover
TypeError: Unexpected type <class 'numpy.ndarray'> for x.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 239, in run
raise TypeError( # pragma: no cover
TypeError: Issues with types <class 'numpy.ndarray'> (operator OptionalHasElement).
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_optional.OptionalHasElement'>, inputs=['optional_input'].
======================================================================
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_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_l2.py", line 55, in _run
numpy.square(data), axis=self.axes,
AttributeError: 'ReduceL2_18' object has no attribute 'axes'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 244, in run
raise AttributeError( # pragma: no cover
AttributeError: Issues with types <class 'numpy.ndarray'>, <class 'numpy.ndarray'> (operator ReduceL2_18).
======================================================================
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_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_l2.py", line 55, in _run
numpy.square(data), axis=self.axes,
AttributeError: 'ReduceL2_18' object has no attribute 'axes'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 244, in run
raise AttributeError( # pragma: no cover
AttributeError: Issues with types <class 'numpy.ndarray'>, <class 'numpy.ndarray'> (operator ReduceL2_18).
======================================================================
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_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_l2.py", line 55, in _run
numpy.square(data), axis=self.axes,
AttributeError: 'ReduceL2_18' object has no attribute 'axes'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 244, in run
raise AttributeError( # pragma: no cover
AttributeError: Issues with types <class 'numpy.ndarray'>, <class 'numpy.ndarray'> (operator ReduceL2_18).
======================================================================
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_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_l2.py", line 55, in _run
numpy.square(data), axis=self.axes,
AttributeError: 'ReduceL2_18' object has no attribute 'axes'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 244, in run
raise AttributeError( # pragma: no cover
AttributeError: Issues with types <class 'numpy.ndarray'>, <class 'numpy.ndarray'> (operator ReduceL2_18).
======================================================================
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_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_l2.py", line 55, in _run
numpy.square(data), axis=self.axes,
AttributeError: 'ReduceL2_18' object has no attribute 'axes'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 244, in run
raise AttributeError( # pragma: no cover
AttributeError: Issues with types <class 'numpy.ndarray'>, <class 'numpy.ndarray'> (operator ReduceL2_18).
======================================================================
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_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_l2.py", line 55, in _run
numpy.square(data), axis=self.axes,
AttributeError: 'ReduceL2_18' object has no attribute 'axes'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 244, in run
raise AttributeError( # pragma: no cover
AttributeError: Issues with types <class 'numpy.ndarray'>, <class 'numpy.ndarray'> (operator ReduceL2_18).
======================================================================
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_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_l2.py", line 55, in _run
numpy.square(data), axis=self.axes,
AttributeError: 'ReduceL2_18' object has no attribute 'axes'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 244, in run
raise AttributeError( # pragma: no cover
AttributeError: Issues with types <class 'numpy.ndarray'>, <class 'numpy.ndarray'> (operator ReduceL2_18).
======================================================================
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_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_l2.py", line 55, in _run
numpy.square(data), axis=self.axes,
AttributeError: 'ReduceL2_18' object has no attribute 'axes'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 244, in run
raise AttributeError( # pragma: no cover
AttributeError: Issues with types <class 'numpy.ndarray'>, <class 'numpy.ndarray'> (operator ReduceL2_18).
======================================================================
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_cpu/op_reduce_log_sum.py", line 51, in _run
res = numpy.sum(data, axis=axes, keepdims=self.keepdims)
File "<__array_function__ internals>", line 180, in sum
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py", line 2298, in sum
return _wrapreduction(a, np.add, 'sum', axis, dtype, out, keepdims=keepdims,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py", line 86, in _wrapreduction
return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
TypeError: only integer scalar arrays can be converted to a scalar index
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_log_sum.py", line 56, in _run
raise TypeError(
TypeError: Unable to reduce shape (3, 4, 5) with axes=array([], dtype=int64).
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 239, in run
raise TypeError( # pragma: no cover
TypeError: Issues with types <class 'numpy.ndarray'>, <class 'numpy.ndarray'> (operator ReduceLogSum_18).
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_reduce_log_sum.ReduceLogSum_18'>, inputs=['data', 'axes'].
======================================================================
ERROR: test_reshape_allowzero_reordered_cpu (__main__.OnnxBackendNodeModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reshape.py", line 38, in _run
return (reshape_reference_implementation(data, shape), )
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reshape.py", line 26, in reshape_reference_implementation
reshaped = numpy.reshape(data, new_shape)
File "<__array_function__ internals>", line 180, in reshape
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py", line 298, in reshape
return _wrapfunc(a, 'reshape', newshape, order=order)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py", line 57, in _wrapfunc
return bound(*args, **kwds)
ValueError: cannot reshape array of size 0 into shape (3,4,4)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_reshape.Reshape_14'>, inputs=['data', 'shape'].
======================================================================
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/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 233, in _run
output = _interpolate_nd(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 190, in _interpolate_nd
scale_factors = numpy.array(output_size) / numpy.array(data.shape)
ValueError: operands could not be broadcast together with shapes (2,) (4,)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_resize.Resize'>, inputs=['X', '', '', 'sizes'].
======================================================================
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/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 233, in _run
output = _interpolate_nd(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 190, in _interpolate_nd
scale_factors = numpy.array(output_size) / numpy.array(data.shape)
ValueError: operands could not be broadcast together with shapes (2,) (4,)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_resize.Resize'>, inputs=['X', '', '', 'sizes'].
======================================================================
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/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 233, in _run
output = _interpolate_nd(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 190, in _interpolate_nd
scale_factors = numpy.array(output_size) / numpy.array(data.shape)
ValueError: operands could not be broadcast together with shapes (2,) (4,)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_resize.Resize'>, inputs=['X', 'roi', '', 'sizes'].
======================================================================
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/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 233, in _run
output = _interpolate_nd(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 190, in _interpolate_nd
scale_factors = numpy.array(output_size) / numpy.array(data.shape)
ValueError: operands could not be broadcast together with shapes (2,) (4,)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_resize.Resize'>, inputs=['X', 'roi', '', 'sizes'].
======================================================================
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/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 233, in _run
output = _interpolate_nd(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 192, in _interpolate_nd
output_size = (scale_factors * numpy.array(data.shape)).astype(int)
ValueError: operands could not be broadcast together with shapes (2,) (4,)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_resize.Resize'>, inputs=['X', '', 'scales'].
======================================================================
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/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 233, in _run
output = _interpolate_nd(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 192, in _interpolate_nd
output_size = (scale_factors * numpy.array(data.shape)).astype(int)
ValueError: operands could not be broadcast together with shapes (2,) (4,)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_resize.Resize'>, inputs=['X', '', 'scales'].
======================================================================
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/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 233, in _run
output = _interpolate_nd(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 190, in _interpolate_nd
scale_factors = numpy.array(output_size) / numpy.array(data.shape)
ValueError: operands could not be broadcast together with shapes (2,) (4,)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_resize.Resize'>, inputs=['X', '', '', 'sizes'].
======================================================================
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/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 233, in _run
output = _interpolate_nd(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 190, in _interpolate_nd
scale_factors = numpy.array(output_size) / numpy.array(data.shape)
ValueError: operands could not be broadcast together with shapes (2,) (4,)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_resize.Resize'>, inputs=['X', '', '', 'sizes'].
======================================================================
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/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 233, in _run
output = _interpolate_nd(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_resize.py", line 190, in _interpolate_nd
scale_factors = numpy.array(output_size) / numpy.array(data.shape)
ValueError: operands could not be broadcast together with shapes (2,) (4,)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_resize.Resize'>, inputs=['X', '', '', 'sizes'].
======================================================================
ERROR: test_scan_sum_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_scan.py", line 96, in _run
outputs = self._run_meth(inputs)
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 637, in run
res = OpRunBinary.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 564, in run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y have different dtype: <class 'NoneType'> != <class 'NoneType'> (<class 'mlprodict.onnxrt.ops_cpu.op_add.Add'>)
======================================================================
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_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_scatter_elements.py", line 77, in _run
res = scatter_elements(data, indices, updates, axis=self.axis)
AttributeError: 'ScatterElements' object has no attribute 'axis'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 244, in run
raise AttributeError( # pragma: no cover
AttributeError: Issues with types <class 'numpy.ndarray'>, <class 'numpy.ndarray'>, <class 'numpy.ndarray'> (operator ScatterElements).
======================================================================
ERROR: test_scatter_with_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 258, in _init
node.setup_runtime(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 240, in setup_runtime
self.ops_ = load_op(self.onnx_node, desc=self.desc,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
return lo(onnx_node, desc=desc, options=options)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 91, in load_op
cl = onnx_load_op(options.get('domain', ''),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/reference/ops/_op_list.py", line 315, in load_op
raise RuntimeImplementationError(
onnx.reference.op_run.RuntimeImplementationError: No registered implementation for operator 'Scatter' and domain '', schema.has_function is False, schema.has_context_dependent_function is False. You may either add one or skip the test in 'reference_evaluator_bakcend_test.py'. Available implementations:
Abs, Acos, Acosh, Add, And, ArgMax, ArgMin, Asin, Asinh, Atan, Atanh,
AttributeHasValue, AveragePool, BatchNormalization, Bernoulli,
BitShift, BitwiseAnd, BitwiseNot, BitwiseOr, BitwiseXor,
BlackmanWindow, Cast, CastLike, Ceil, Celu, CenterCropPad, Clip,
Col2Im, Compress, Concat, ConcatFromSequence, Constant,
ConstantOfShape, Conv, ConvInteger, ConvTranspose, Cos, Cosh, CumSum,
DFT, DepthToSpace, DequantizeLinear, Det, Div, Dropout,
DynamicQuantizeLinear, Einsum, Elu, Equal, Erf, Exp, Expand, EyeLike,
Flatten, Floor, GRU, Gather, GatherElements, GatherND, Gemm,
GlobalAveragePool, GlobalMaxPool, Greater, GreaterOrEqual, GridSample,
HammingWindow, HannWindow, HardSigmoid, Hardmax, Identity, If,
InstanceNormalization, IsInf, IsNaN, LRN, LSTM, LayerNormalization,
LeakyRelu, Less, LessOrEqual, Log, LogSoftmax, Loop, LpNormalization,
MatMul, MatMulInteger, Max, MaxPool, MaxUnpool, Mean, MelWeightMatrix,
Min, Mod, Mul, Neg, NegativeLogLikelihoodLoss, NonMaxSuppression,
NonZero, Not, OneHot, OpFunction, OpRun, Optional, OptionalGetElement,
OptionalHasElement, Or, PRelu, Pad, Pow, QLinearConv, QLinearMatMul,
QuantizeLinear, RNN, RandomNormal, RandomNormalLike, RandomUniform,
RandomUniformLike, Range, Reciprocal, ReduceL1, ReduceL2,
ReduceLogSum, ReduceLogSumExp, ReduceMax, ReduceMean, ReduceMin,
ReduceProd, ReduceSum, ReduceSumSquare, Relu, Reshape, Resize,
ReverseSequence, RoiAlign, Round, STFT, Scan, ScatterElements,
ScatterND, Selu, SequenceAt, SequenceConstruct, SequenceEmpty,
SequenceErase, SequenceInsert, SequenceLength, SequenceMap, Shape,
Shrink, Sigmoid, Sign, Sin, Sinh, Size, Slice, Softmax,
SoftmaxCrossEntropyLoss, Softplus, Softsign, SpaceToDepth, Split,
SplitToSequence, Sqrt, Squeeze, StringNormalizer, Sub, Sum, Tan, Tanh,
TfIdfVectorizer, ThresholdedRelu, Tile, TopK, Transpose, Trilu,
Unique, Unsqueeze, Upsample, Where, Xor
======================================================================
ERROR: test_scatter_without_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 258, in _init
node.setup_runtime(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 240, in setup_runtime
self.ops_ = load_op(self.onnx_node, desc=self.desc,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
return lo(onnx_node, desc=desc, options=options)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 91, in load_op
cl = onnx_load_op(options.get('domain', ''),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/reference/ops/_op_list.py", line 315, in load_op
raise RuntimeImplementationError(
onnx.reference.op_run.RuntimeImplementationError: No registered implementation for operator 'Scatter' and domain '', schema.has_function is False, schema.has_context_dependent_function is False. You may either add one or skip the test in 'reference_evaluator_bakcend_test.py'. Available implementations:
Abs, Acos, Acosh, Add, And, ArgMax, ArgMin, Asin, Asinh, Atan, Atanh,
AttributeHasValue, AveragePool, BatchNormalization, Bernoulli,
BitShift, BitwiseAnd, BitwiseNot, BitwiseOr, BitwiseXor,
BlackmanWindow, Cast, CastLike, Ceil, Celu, CenterCropPad, Clip,
Col2Im, Compress, Concat, ConcatFromSequence, Constant,
ConstantOfShape, Conv, ConvInteger, ConvTranspose, Cos, Cosh, CumSum,
DFT, DepthToSpace, DequantizeLinear, Det, Div, Dropout,
DynamicQuantizeLinear, Einsum, Elu, Equal, Erf, Exp, Expand, EyeLike,
Flatten, Floor, GRU, Gather, GatherElements, GatherND, Gemm,
GlobalAveragePool, GlobalMaxPool, Greater, GreaterOrEqual, GridSample,
HammingWindow, HannWindow, HardSigmoid, Hardmax, Identity, If,
InstanceNormalization, IsInf, IsNaN, LRN, LSTM, LayerNormalization,
LeakyRelu, Less, LessOrEqual, Log, LogSoftmax, Loop, LpNormalization,
MatMul, MatMulInteger, Max, MaxPool, MaxUnpool, Mean, MelWeightMatrix,
Min, Mod, Mul, Neg, NegativeLogLikelihoodLoss, NonMaxSuppression,
NonZero, Not, OneHot, OpFunction, OpRun, Optional, OptionalGetElement,
OptionalHasElement, Or, PRelu, Pad, Pow, QLinearConv, QLinearMatMul,
QuantizeLinear, RNN, RandomNormal, RandomNormalLike, RandomUniform,
RandomUniformLike, Range, Reciprocal, ReduceL1, ReduceL2,
ReduceLogSum, ReduceLogSumExp, ReduceMax, ReduceMean, ReduceMin,
ReduceProd, ReduceSum, ReduceSumSquare, Relu, Reshape, Resize,
ReverseSequence, RoiAlign, Round, STFT, Scan, ScatterElements,
ScatterND, Selu, SequenceAt, SequenceConstruct, SequenceEmpty,
SequenceErase, SequenceInsert, SequenceLength, SequenceMap, Shape,
Shrink, Sigmoid, Sign, Sin, Sinh, Size, Slice, Softmax,
SoftmaxCrossEntropyLoss, Softplus, Softsign, SpaceToDepth, Split,
SplitToSequence, Sqrt, Squeeze, StringNormalizer, Sub, Sum, Tan, Tanh,
TfIdfVectorizer, ThresholdedRelu, Tile, TopK, Transpose, Trilu,
Unique, Unsqueeze, Upsample, Where, Xor
======================================================================
ERROR: test_sequence_insert_at_back_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
ERROR: test_sequence_insert_at_front_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
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/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
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/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
ERROR: test_sequence_map_add_2_sequences_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
ERROR: test_sequence_map_add_2_sequences_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
ERROR: test_sequence_map_extract_shapes_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
ERROR: test_sequence_map_extract_shapes_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
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/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
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/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
ERROR: test_sequence_map_identity_1_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
ERROR: test_sequence_map_identity_1_sequence_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
ERROR: test_sequence_map_identity_2_sequences_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
ERROR: test_sequence_map_identity_2_sequences_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 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in f
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2753, in <genexpr>
key = tuple((m.dtype, m.shape) for m in evaluated_inputs)
AttributeError: 'list' object has no attribute 'dtype'
======================================================================
ERROR: test_shrink_hard_expanded_ver18_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same shape (5,) != ()
======================================================================
ERROR: test_shrink_soft_expanded_ver18_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same shape (5,) != ()
======================================================================
ERROR: test_thresholdedrelu_default_expanded_ver18_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same 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/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same shape (5,) != ()
======================================================================
ERROR: test_thresholdedrelu_expanded_ver18_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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_where.py", line 24, in _run
raise RuntimeError( # pragma: no cover
RuntimeError: x and y should share the same shape (3, 4, 5) != ()
======================================================================
ERROR: test_BatchNorm1d_3d_input_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_BatchNorm2d_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_BatchNorm2d_momentum_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_BatchNorm3d_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_BatchNorm3d_momentum_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_ConstantPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
TypeError: _run() missing 1 required positional argument: 'pads'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 239, in run
raise TypeError( # pragma: no cover
TypeError: Issues with types <class 'numpy.ndarray'> (operator Pad_18).
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_pad.Pad_18'>, inputs=['0'].
======================================================================
ERROR: test_Conv1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv1d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv1d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv1d_pad1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv1d_pad1size1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv1d_pad2_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv1d_pad2size1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv1d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv2d_depthwise_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv2d_depthwise_padded_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv2d_depthwise_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv2d_depthwise_with_multiplier_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv2d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv2d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv2d_groups_thnn_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv2d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv2d_padding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv2d_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv3d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv3d_dilated_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv3d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv3d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv3d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Conv3d_stride_padding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_ConvTranspose2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_ConvTranspose2d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Embedding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Embedding_sparse_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Linear_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_Linear_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_PReLU_1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_PReLU_1d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_PReLU_2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_PReLU_2d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_PReLU_3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_PReLU_3d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_ReflectionPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
TypeError: _run() missing 1 required positional argument: 'pads'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 239, in run
raise TypeError( # pragma: no cover
TypeError: Issues with types <class 'numpy.ndarray'> (operator Pad_18).
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_pad.Pad_18'>, inputs=['0'].
======================================================================
ERROR: test_ReplicationPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
TypeError: _run() missing 1 required positional argument: 'pads'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 239, in run
raise TypeError( # pragma: no cover
TypeError: Issues with types <class 'numpy.ndarray'> (operator Pad_18).
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_pad.Pad_18'>, inputs=['0'].
======================================================================
ERROR: test_ZeroPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
TypeError: _run() missing 1 required positional argument: 'pads'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 239, in run
raise TypeError( # pragma: no cover
TypeError: Issues with types <class 'numpy.ndarray'> (operator Pad_18).
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_pad.Pad_18'>, inputs=['0'].
======================================================================
ERROR: test_operator_conv_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_operator_convtranspose_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_operator_non_float_params_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_operator_pad_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 237, in run
res = self._run(*args, **kwargs)
TypeError: _run() missing 1 required positional argument: 'pads'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 471, in run
res = self.ops_.run(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op.py", line 239, in run
raise TypeError( # pragma: no cover
TypeError: Issues with types <class 'numpy.ndarray'> (operator Pad_18).
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2768, in f
got = oinf.run({k: v for k, v in
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 1069, in _run_sequence_runtime
node.run(values, attributes=attributes)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 475, in run
raise RuntimeError( # pragma: no cover
RuntimeError: Unable to run operator <class 'mlprodict.onnxrt.ops_cpu.op_pad.Pad_18'>, inputs=['0'].
======================================================================
ERROR: test_operator_params_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_operator_repeat_dim_overflow_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 283, in _init
self.inplaces_ = self._guess_inplace(self.input_inplace)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1628, in _guess_inplace
node.enable_inplace_compute(n)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 542, in enable_inplace_compute
(self.ops_ or self.function_).enable_inplace_compute(
AttributeError: 'Tile_9' object has no attribute 'enable_inplace_compute'
======================================================================
ERROR: test_operator_symbolic_override_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_bvlc_alexnet_cpu (__main__.OnnxBackendRealModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, device=device, **kwargs)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 339, in run
outputs = list(prepared_model.run(inputs))
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
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_cpu/__init__.py", line 91, in load_op
cl = onnx_load_op(options.get('domain', ''),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/reference/ops/_op_list.py", line 274, in load_op
raise ValueError(f"Domain must be '' not {domain!r}.")
ValueError: Domain must be '' not 'ai.onnx.preview.training'.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 258, in _init
node.setup_runtime(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 259, in setup_runtime
raise e
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 240, in setup_runtime
self.ops_ = load_op(self.onnx_node, desc=self.desc,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
return lo(onnx_node, desc=desc, options=options)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 94, in load_op
raise MissingOperatorError(
mlprodict.onnxrt.excs.MissingOperatorError: Unable to load class for operator name=Gradient, opset=1, options={'domain': 'ai.onnx.preview.training', 'target_opset': 1, 'ir_version': 7}, _additional_ops={}.
======================================================================
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_cpu/__init__.py", line 91, in load_op
cl = onnx_load_op(options.get('domain', ''),
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/reference/ops/_op_list.py", line 274, in load_op
raise ValueError(f"Domain must be '' not {domain!r}.")
ValueError: Domain must be '' not 'ai.onnx.preview.training'.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 258, in _init
node.setup_runtime(
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 259, in setup_runtime
raise e
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 240, in setup_runtime
self.ops_ = load_op(self.onnx_node, desc=self.desc,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
return lo(onnx_node, desc=desc, options=options)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 94, in load_op
raise MissingOperatorError(
mlprodict.onnxrt.excs.MissingOperatorError: Unable to load class for operator name=Gradient, opset=1, options={'domain': 'ai.onnx.preview.training', 'target_opset': 1, 'ir_version': 7}, _additional_ops={}.
======================================================================
ERROR: test_sequence_model1_cpu (__main__.OnnxBackendSimpleModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_sequence_model2_cpu (__main__.OnnxBackendSimpleModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_sequence_model3_cpu (__main__.OnnxBackendSimpleModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_sequence_model6_cpu (__main__.OnnxBackendSimpleModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 283, in _init
self.inplaces_ = self._guess_inplace(self.input_inplace)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1628, in _guess_inplace
node.enable_inplace_compute(n)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 542, in enable_inplace_compute
(self.ops_ or self.function_).enable_inplace_compute(
AttributeError: 'SequenceLength_12' object has no attribute 'enable_inplace_compute'
======================================================================
ERROR: test_sequence_model7_cpu (__main__.OnnxBackendSimpleModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 71, in run
feeds[inp] = inputs[i]
IndexError: list index out of range
======================================================================
ERROR: test_sequence_model8_cpu (__main__.OnnxBackendSimpleModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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/npy/xop.py", line 2656, in run
return self.f(*inputs, verbose=verbose, fLOG=fLOG,
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py", line 2760, in f
oinf = OnnxInference(model, runtime=runtime)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 140, in __init__
self._init(existing_functions)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 283, in _init
self.inplaces_ = self._guess_inplace(self.input_inplace)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1628, in _guess_inplace
node.enable_inplace_compute(n)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 542, in enable_inplace_compute
(self.ops_ or self.function_).enable_inplace_compute(
AttributeError: 'SequenceLength_12' object has no attribute 'enable_inplace_compute'
======================================================================
FAIL: test_adam_multiple_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: 1 / 1 (100%)
Max absolute difference: 0.003
Max relative difference: 0.004
x: array([0.755959], dtype=float32)
y: array([0.759136], dtype=float32)
======================================================================
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: 4 / 10 (40%)
Max absolute difference: 1.
Max relative difference: 1.
x: array([1., 1., 1., 1., 0., 1., 1., 1., 1., 0.])
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: 4 / 10 (40%)
Max absolute difference: 1.
Max relative difference: 1.
x: array([1., 0., 0., 0., 0., 1., 0., 1., 1., 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., 1., 0., 1., 0., 1., 0., 0., 1.])
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: 4 / 10 (40%)
Max absolute difference: 1.
Max relative difference: 1.
x: array([0., 0., 1., 0., 0., 0., 0., 0., 0., 1.])
y: array([0., 1., 1., 0., 0., 1., 0., 1., 1., 1.])
======================================================================
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 206, in assert_similar_outputs
np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
raise AssertionError(msg)
AssertionError:
Items are not equal:
ACTUAL: dtype('<U32')
DESIRED: dtype('O')
======================================================================
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: 12 / 12 (100%)
x: array([[0.9767611026763916, 0.6048455238342285, 0.7392635941505432,
0.03918779268860817],
[0.28280696272850037, 0.12019655853509903, 0.296140193939209,...
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 206, in assert_similar_outputs
np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
raise AssertionError(msg)
AssertionError:
Items are not equal:
ACTUAL: dtype('<U32')
DESIRED: dtype('O')
======================================================================
FAIL: test_center_crop_pad_crop_axes_hwc_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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
(shapes (10, 8, 3), (10, 9, 3) mismatch)
x: array([[[ 0.376426, -1.099401, 0.298238],
[ 1.326386, -0.694568, -0.149635],
[-0.435154, 1.849264, 0.672295],...
y: array([[[ 0.376426, -1.099401, 0.298238],
[ 1.326386, -0.694568, -0.149635],
[-0.435154, 1.849264, 0.672295],...
======================================================================
FAIL: test_col2im_pads_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: 1 / 25 (4%)
Max absolute difference: 10.
Max relative difference: 0.714
x: array([[[[ 8., 21., 24., 27., 24.],
[ 38., 66., 69., 72., 54.],
[ 68., 111., 114., 117., 84.],...
y: array([[[[ 8., 21., 24., 27., 14.],
[ 38., 66., 69., 72., 54.],
[ 68., 111., 114., 117., 84.],...
======================================================================
FAIL: test_convtranspose_autopad_same_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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
(shapes (1, 2, 7, 7), (1, 2, 6, 6) mismatch)
x: array([[[[ 0., 0., 1., 1., 3., 2., 2.],
[ 0., 0., 1., 1., 3., 2., 2.],
[ 3., 3., 8., 5., 12., 7., 7.],...
y: array([[[[ 0., 0., 1., 1., 3., 2.],
[ 0., 0., 1., 1., 3., 2.],
[ 3., 3., 8., 5., 12., 7.],...
======================================================================
FAIL: test_convtranspose_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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
(shapes (1, 2, 9, 7), (1, 2, 10, 8) mismatch)
x: array([[[[ 0., 0., 1., 1., 3., 2., 2.],
[ 0., 0., 1., 1., 3., 2., 2.],
[ 0., 0., 1., 1., 3., 2., 2.],...
y: array([[[[ 0., 0., 1., 1., 3., 2., 2., 0.],
[ 0., 0., 1., 1., 3., 2., 2., 0.],
[ 0., 0., 1., 1., 3., 2., 2., 0.],...
======================================================================
FAIL: test_dynamicquantizelinear_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: 2 / 6 (33.3%)
Max absolute difference: 255
Max relative difference: 9.808
x: array([153, 255, 0, 25, 221, 178], dtype=uint8)
y: array([153, 255, 0, 26, 221, 179], dtype=uint8)
======================================================================
FAIL: test_dynamicquantizelinear_max_adjusted_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 / 6 (83.3%)
Max absolute difference: 235
Max relative difference: 5.095
x: array([170, 77, 145, 43, 0, 0], dtype=uint8)
y: array([191, 121, 172, 96, 42, 0], dtype=uint8)
======================================================================
FAIL: test_dynamicquantizelinear_max_adjusted_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: 1 / 6 (16.7%)
Max absolute difference: 255
Max relative difference: 2.656
x: array([191, 121, 172, 95, 42, 0], dtype=uint8)
y: array([191, 121, 172, 96, 42, 0], dtype=uint8)
======================================================================
FAIL: test_dynamicquantizelinear_min_adjusted_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 / 12 (83.3%)
Max absolute difference: 64
Max relative difference: 0.336
x: array([[ 85, 178, 110, 212],
[255, 255, 128, 221],
[255, 255, 255, 199]], dtype=uint8)
y: array([[ 64, 134, 83, 159],
[213, 255, 96, 166],
[249, 255, 191, 149]], dtype=uint8)
======================================================================
FAIL: test_dynamicquantizelinear_min_adjusted_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 / 12 (58.3%)
Max absolute difference: 255
Max relative difference: 3.984
x: array([[ 63, 133, 82, 159],
[212, 255, 95, 165],
[248, 255, 191, 149]], dtype=uint8)
y: array([[ 64, 134, 83, 159],
[213, 255, 96, 166],
[249, 255, 191, 149]], dtype=uint8)
======================================================================
FAIL: test_eyelike_without_dtype_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 206, in assert_similar_outputs
np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
raise AssertionError(msg)
AssertionError:
Items are not equal:
ACTUAL: dtype('float32')
DESIRED: dtype('int32')
======================================================================
FAIL: test_gru_batchwise_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 206, in assert_similar_outputs
np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
raise AssertionError(msg)
AssertionError:
Items are not equal:
ACTUAL: dtype('float64')
DESIRED: dtype('float32')
======================================================================
FAIL: test_gru_defaults_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 206, in assert_similar_outputs
np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
raise AssertionError(msg)
AssertionError:
Items are not equal:
ACTUAL: dtype('float64')
DESIRED: dtype('float32')
======================================================================
FAIL: test_gru_seq_length_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 206, in assert_similar_outputs
np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
raise AssertionError(msg)
AssertionError:
Items are not equal:
ACTUAL: dtype('float64')
DESIRED: dtype('float32')
======================================================================
FAIL: test_gru_with_initial_bias_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 206, in assert_similar_outputs
np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
raise AssertionError(msg)
AssertionError:
Items are not equal:
ACTUAL: dtype('float64')
DESIRED: dtype('float32')
======================================================================
FAIL: test_loop11_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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
(shapes (1,), (5, 1) mismatch)
x: array([13.], dtype=float32)
y: array([[-1.],
[ 1.],
[ 4.],...
======================================================================
FAIL: test_lstm_batchwise_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 206, in assert_similar_outputs
np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
raise AssertionError(msg)
AssertionError:
Items are not equal:
ACTUAL: dtype('float64')
DESIRED: dtype('float32')
======================================================================
FAIL: test_lstm_defaults_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 206, in assert_similar_outputs
np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
raise AssertionError(msg)
AssertionError:
Items are not equal:
ACTUAL: dtype('float64')
DESIRED: dtype('float32')
======================================================================
FAIL: test_lstm_with_initial_bias_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 206, in assert_similar_outputs
np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
raise AssertionError(msg)
AssertionError:
Items are not equal:
ACTUAL: dtype('float64')
DESIRED: dtype('float32')
======================================================================
FAIL: test_maxpool_2d_uint8_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 206, in assert_similar_outputs
np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
raise AssertionError(msg)
AssertionError:
Items are not equal:
ACTUAL: dtype('float64')
DESIRED: dtype('uint8')
======================================================================
FAIL: test_mod_int64_fmod_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: 2 / 6 (33.3%)
Max absolute difference: 3
Max relative difference: 3.
x: array([ 0, -2, 5, 0, 2, 3])
y: array([ 0, 1, 5, 0, -1, 3])
======================================================================
FAIL: test_nesterov_momentum_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: 2 / 2 (100%)
Max absolute difference: 0.252
Max relative difference: 0.085
x: array([1.1313, 2.7052], dtype=float32)
y: array([1.227535, 2.95714 ], dtype=float32)
======================================================================
FAIL: test_onehot_with_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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
(shapes (2, 2, 10), (2, 10, 2) mismatch)
x: array([[[1., 3., 1., 1., 1., 1., 1., 1., 1., 1.],
[1., 1., 1., 1., 1., 1., 1., 1., 1., 3.]],
...
y: array([[[1., 1.],
[3., 1.],
[1., 1.],...
======================================================================
FAIL: test_onehot_with_negative_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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
(shapes (2, 2, 10), (2, 10, 2) mismatch)
x: array([[[1., 3., 1., 1., 1., 1., 1., 1., 1., 1.],
[1., 1., 1., 1., 1., 1., 1., 1., 1., 3.]],
...
y: array([[[1., 1.],
[3., 1.],
[1., 1.],...
======================================================================
FAIL: test_quantizelinear_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: 1 / 6 (16.7%)
Max absolute difference: 255
Max relative difference: 1.962
x: array([128, 129, 129, 255, 1, 0], dtype=uint8)
y: array([128, 129, 130, 255, 1, 0], dtype=uint8)
======================================================================
FAIL: test_range_float_type_positive_delta_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: 1 / 2 (50%)
Max absolute difference: 2.
Max relative difference: 2.
x: array(3., dtype=float32)
y: array([1., 3.], dtype=float32)
======================================================================
FAIL: test_range_int32_type_negative_delta_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: 1 / 2 (50%)
Max absolute difference: 3
Max relative difference: 0.3
x: array(7, dtype=int32)
y: array([10, 7], dtype=int32)
======================================================================
FAIL: 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/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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: 9 / 9 (100%)
Max absolute difference: 0.146
Max relative difference: 0.075
x: array([[[[ 1.471191, 2.78125 , 4.08252 ],
[ 6.711426, 8.021484, 9.322754],
[11.916504, 13.226562, 14.527832]]]], dtype=float32)
y: array([[[[ 1.368127, 2.669501, 4.013337],
[ 6.573625, 7.875 , 9.218835],
[11.948966, 13.250341, 14.594176]]]], dtype=float32)
======================================================================
FAIL: test_resize_downsample_scales_cubic_antialias_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: 4 / 4 (100%)
Max absolute difference: 0.357
Max relative difference: 0.088
x: array([[[[ 2.296296, 4.037037],
[ 9.259258, 10.999999]]]], dtype=float32)
y: array([[[[ 2.518072, 4.285886],
[ 9.589329, 11.357142]]]], dtype=float32)
======================================================================
FAIL: test_resize_downsample_scales_linear_antialias_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: 3 / 4 (75%)
Max absolute difference: 0.208
Max relative difference: 0.072
x: array([[[[ 2.666667, 4.333333],
[ 9.333333, 10.999999]]]], dtype=float32)
y: array([[[[ 2.875, 4.5 ],
[ 9.375, 11. ]]]], dtype=float32)
======================================================================
FAIL: test_resize_downsample_sizes_cubic_antialias_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 / 9 (88.9%)
Max absolute difference: 0.144
Max relative difference: 0.081
x: array([[[[ 1.630787, 3.00463 , 4.378472],
[ 7.126157, 8.5 , 9.873842],
[12.621528, 13.99537 , 15.369213]]]], dtype=float32)
y: array([[[[ 1.775009, 3.120007, 4.465005],
[ 7.155002, 8.5 , 9.844998],
[12.534994, 13.879992, 15.224991]]]], dtype=float32)
======================================================================
FAIL: test_resize_downsample_sizes_linear_antialias_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 / 9 (88.9%)
Max absolute difference: 0.53
Max relative difference: 0.224
x: array([[[[ 1.833333, 3.166667, 4.5 ],
[ 7.166667, 8.5 , 9.833333],
[12.5 , 13.833333, 15.166667]]]], dtype=float32)
y: array([[[[ 2.363636, 3.590909, 4.818182],
[ 7.272727, 8.5 , 9.727273],
[12.181818, 13.409091, 14.636364]]]], dtype=float32)
======================================================================
FAIL: 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/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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: 64 / 64 (100%)
Max absolute difference: 0.234
Max relative difference: 0.154
x: array([[[[ 0.472656, 0.769531, 1.246094, 1.875 , 2.28125 ,
2.910156, 3.386719, 3.683594],
[ 1.660156, 1.957031, 2.433594, 3.0625 , 3.46875 ,...
y: array([[[[ 0.558824, 0.814942, 1.356982, 1.897059, 2.397059,
2.937135, 3.479176, 3.735294],
[ 1.583298, 1.839416, 2.381457, 2.921533, 3.421533,...
======================================================================
FAIL: test_scatter_elements_with_duplicate_indices_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: 1 / 5 (20%)
Max absolute difference: 3.1
Max relative difference: 0.596
x: array([[1. , 2.1, 3. , 4. , 5. ]], dtype=float32)
y: array([[1. , 5.2, 3. , 4. , 5. ]], dtype=float32)
======================================================================
FAIL: test_scatter_elements_with_reduction_min_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: 1 / 5 (20%)
Max absolute difference: 1.
Max relative difference: 0.909
x: array([[1. , 2.1, 3. , 4. , 5. ]], dtype=float32)
y: array([[1. , 1.1, 3. , 4. , 5. ]], dtype=float32)
======================================================================
FAIL: test_scatternd_add_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: 16 / 64 (25%)
Max absolute difference: 15.
Max relative difference: 0.9
x: array([[[1., 1., 1., 1.],
[2., 2., 2., 2.],
[3., 3., 3., 3.],...
y: array([[[ 7., 8., 9., 10.],
[13., 14., 15., 16.],
[18., 17., 16., 15.],...
======================================================================
FAIL: test_scatternd_max_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: 16 / 64 (25%)
Max absolute difference: 6.
Max relative difference: 0.8
x: array([[[1., 1., 1., 1.],
[2., 2., 2., 2.],
[3., 3., 3., 3.],...
y: array([[[5., 5., 5., 5.],
[6., 6., 7., 8.],
[8., 7., 7., 7.],...
======================================================================
FAIL: test_scatternd_min_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: 3 / 64 (4.69%)
Max absolute difference: 3.
Max relative difference: 3.
x: array([[[1., 1., 1., 1.],
[2., 2., 2., 2.],
[3., 3., 3., 3.],...
y: array([[[1., 1., 1., 1.],
[2., 2., 2., 2.],
[3., 3., 3., 3.],...
======================================================================
FAIL: test_scatternd_multiply_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: 16 / 64 (25%)
Max absolute difference: 165.
Max relative difference: 0.982
x: array([[[1., 1., 1., 1.],
[2., 2., 2., 2.],
[3., 3., 3., 3.],...
y: array([[[ 5., 10., 15., 20.],
[ 60., 72., 84., 96.],
[168., 147., 126., 105.],...
======================================================================
FAIL: test_simple_rnn_batchwise_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: 4 / 12 (33.3%)
Max absolute difference: 0.002
Max relative difference: 0.002
x: array([[[[0.905148, 0.905148, 0.905148, 0.905148]]],
...
y: array([[[[0.905148, 0.905148, 0.905148, 0.905148]]],
...
======================================================================
FAIL: test_split_1d_uneven_split_opset18_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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
(shapes (1,), (2,) mismatch)
x: array([1.], dtype=float32)
y: array([1., 2.], dtype=float32)
======================================================================
FAIL: test_split_2d_uneven_split_opset18_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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
(shapes (2, 2), (2, 3) mismatch)
x: array([[ 1., 2.],
[ 9., 10.]], dtype=float32)
y: array([[ 1., 2., 3.],
[ 9., 10., 11.]], dtype=float32)
======================================================================
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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
(shapes (1, 1, 128, 9, 2), (1, 15, 9, 2) mismatch)
x: array([[[[[ 0., 0.],
[ 0., 0.],
[ 0., 0.],...
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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.001, atol=1e-07
(shapes (1, 1, 16, 65, 2), (1, 15, 9, 2) mismatch)
x: array([[[[[ 0. , 0. ],
[ 0. , 0. ],
[ 0. , 0. ],...
y: array([[[[ 55.996273, 0. ],
[ 23.999105, 24.93398 ],
[ -7.99869 , 22.70421 ],...
======================================================================
FAIL: test_strnormalizer_export_monday_casesensintive_lower_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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
(shapes (4,), (3,) mismatch)
x: array(['', 'tuesday', 'wednesday', 'thursday'], dtype=object)
y: array(['tuesday', 'wednesday', 'thursday'], dtype=object)
======================================================================
FAIL: test_strnormalizer_export_monday_casesensintive_nochangecase_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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
(shapes (4,), (3,) mismatch)
x: array(['', 'tuesday', 'wednesday', 'thursday'], dtype=object)
y: array(['tuesday', 'wednesday', 'thursday'], dtype=object)
======================================================================
FAIL: test_strnormalizer_export_monday_casesensintive_upper_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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
(shapes (4,), (3,) mismatch)
x: array(['', 'TUESDAY', 'WEDNESDAY', 'THURSDAY'], dtype=object)
y: array(['TUESDAY', 'WEDNESDAY', 'THURSDAY'], dtype=object)
======================================================================
FAIL: test_strnormalizer_export_monday_empty_output_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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
(shapes (2,), (1,) mismatch)
x: array(['', ''], dtype=object)
y: array([''], dtype=object)
======================================================================
FAIL: test_strnormalizer_export_monday_insensintive_upper_twodim_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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
(shapes (1, 6), (1, 4) mismatch)
x: array([['MONDAY', 'TUESDAY', 'WEDNESDAY', 'MONDAY', 'TUESDAY',
'WEDNESDAY']], dtype=object)
y: array([['TUESDAY', 'WEDNESDAY', 'TUESDAY', 'WEDNESDAY']], dtype=object)
======================================================================
FAIL: test_thresholdedrelu_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: 58 / 60 (96.7%)
Max absolute difference: 2.
Max relative difference: 0.
x: array([[[2. , 2. , 2. , 2.240893, 2. ],
[2. , 2. , 2. , 2. , 2. ],
[2. , 2. , 2. , 2. , 2. ],...
y: array([[[0. , 0. , 0. , 2.240893, 0. ],
[0. , 0. , 0. , 0. , 0. ],
[0. , 0. , 0. , 0. , 0. ],...
======================================================================
FAIL: test_thresholdedrelu_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: 49 / 60 (81.7%)
Max absolute difference: 1.
Max relative difference: 0.
x: array([[[1.764052, 1. , 1. , 2.240893, 1.867558],
[1. , 1. , 1. , 1. , 1. ],
[1. , 1.454273, 1. , 1. , 1. ],...
y: array([[[1.764052, 0. , 0. , 2.240893, 1.867558],
[0. , 0. , 0. , 0. , 0. ],
[0. , 1.454273, 0. , 0. , 0. ],...
======================================================================
FAIL: test_thresholdedrelu_example_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: 4 / 5 (80%)
Max absolute difference: 2.
Max relative difference: 0.
x: array([2. , 2. , 2. , 2. , 2.2], dtype=float32)
y: array([0. , 0. , 0. , 0. , 2.2], dtype=float32)
======================================================================
FAIL: test_strnorm_model_monday_casesensintive_lower_cpu (__main__.OnnxBackendSimpleModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
(shapes (4,), (3,) mismatch)
x: array(['', 'tuesday', 'wednesday', 'thursday'], dtype=object)
y: array(['tuesday', 'wednesday', 'thursday'], dtype=object)
======================================================================
FAIL: test_strnorm_model_monday_casesensintive_nochangecase_cpu (__main__.OnnxBackendSimpleModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
(shapes (4,), (3,) mismatch)
x: array(['', 'tuesday', 'wednesday', 'thursday'], dtype=object)
y: array(['tuesday', 'wednesday', 'thursday'], dtype=object)
======================================================================
FAIL: test_strnorm_model_monday_casesensintive_upper_cpu (__main__.OnnxBackendSimpleModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
(shapes (4,), (3,) mismatch)
x: array(['', 'TUESDAY', 'WEDNESDAY', 'THURSDAY'], dtype=object)
y: array(['TUESDAY', 'WEDNESDAY', 'THURSDAY'], dtype=object)
======================================================================
FAIL: test_strnorm_model_monday_empty_output_cpu (__main__.OnnxBackendSimpleModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
(shapes (2,), (1,) mismatch)
x: array(['MONDAY', 'MONDAY'], dtype=object)
y: array([''], dtype=object)
======================================================================
FAIL: test_strnorm_model_monday_insensintive_upper_twodim_cpu (__main__.OnnxBackendSimpleModelTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "somewhere/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 296, in device_test_func
return test_func(*args, 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 763, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
(shapes (1, 6), (1, 4) mismatch)
x: array([['MONDAY', 'TUESDAY', 'WEDNESDAY', 'MONDAY', 'TUESDAY',
'WEDNESDAY']], dtype=object)
y: array([['TUESDAY', 'WEDNESDAY', 'TUESDAY', 'WEDNESDAY']], dtype=object)
----------------------------------------------------------------------
Ran 2492 tests in 26.622s
FAILED (failures=64, errors=145, skipped=1254)