Modules#

Summary#

module

truncated documentation

__init__

module mlprodict Python runtime for ONNX and others tools to help converting investigate issues with ONNX models. source on GitHub

__init__

module mlprodict.asv_benchmark Shortcuts to asv_benchmark. source on GitHub

__init__

module mlprodict.cli Shortcut to cli. source on GitHub

__init__

module mlprodict.grammar.cc Shortcuts to cc. source on GitHub

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module mlprodict.grammar.grammar_sklearn Shortcuts to grammar_sklearn. source on GitHub

__init__

module mlprodict.grammar.grammar_sklearn.grammar Shortcuts to grammar. source on GitHub

__init__

module mlprodict.npy Shortcut to npy. .. versionadded:: 0.6 source on GitHub

__init__

module mlprodict.npy._cache Cache documentation for OnnxOps. .. versionadded:: 0.9 source on GitHub

__init__

module mlprodict.onnx_conv Shortcut to onnx_conv. Importing this file means importing sklearn-onnx. source on GitHub

__init__

module mlprodict.onnx_conv.onnx_ops Shortcuts to onnx_ops. source on GitHub

__init__

module mlprodict.onnx_conv.operator_converters Shortcut to operator_converters. source on GitHub

__init__

module mlprodict.onnx_conv.scorers Shortcuts to scorers. source on GitHub

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module mlprodict.onnx_conv.sklconv Shortcuts to sklconv. source on GitHub

__init__

module mlprodict.onnx_tools Shortcut to onnx_tools. source on GitHub

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module mlprodict.onnx_tools.onnx_grammar Shortcut to onnx_grammar. source on GitHub

__init__

module mlprodict.onnx_tools.optim Shortcuts to onnx_tools.optim. source on GitHub

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module mlprodict.onnxrt Shortcut to onnxrt. source on GitHub

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module mlprodict.onnxrt.doc Helper for documentation. source on GitHub

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module mlprodict.onnxrt.ops_cpu Shortcut to ops_cpu. source on GitHub

__init__

module mlprodict.onnxrt.ops_empty Shortcut to ops_cpu. source on GitHub

__init__

module mlprodict.onnxrt.ops_onnxruntime Shortcut to ops_cpu. source on GitHub

__init__

module mlprodict.onnxrt.ops_shape Shortcut to ops_shape. source on GitHub

__init__

module mlprodict.onnxrt.ops_whole Shortcut to ops_whole. source on GitHub

__init__

module mlprodict.onnxrt.validate Functions to validate converted models and runtime. source on GitHub

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module mlprodict.onnxrt.validate.data Datasets to tests models. source on GitHub

__init__

module mlprodict.plotting Shortcuts to plotting. source on GitHub

__init__

module mlprodict.sklapi Shortcut to sklapi. Importing this file imports sklearn-onnx as well. source on GitHub

__init__

module mlprodict.testing Shortcut to testing. source on GitHub

__init__

module mlprodict.testing.einsum Shortcut to testing.einsum. source on GitHub

__init__

module mlprodict.testing.experimental_c_impl Shortcut to testing.experimental_c. source on GitHub

__init__

module mlprodict.testing.test_utils Inspired from sklearn-onnx, handles two backends. source on GitHub

__init__

module mlprodict.tools Shortcuts to tools. source on GitHub

__main__

module mlprodict.__main__ Implements command line python -m mlprodict <command> <args>. source on GitHub

_create_asv_helper

module mlprodict.asv_benchmark._create_asv_helper Functions to creates a benchmark based on asv for many regressors and classifiers. source on GitHub

_element_unary

module mlprodict.onnxrt.ops_shape._element_unary Computes shape inference for element wise operators with one input. source on GitHub

_element_wise

module mlprodict.onnxrt.ops_shape._element_wise Computes shape inference for element wise operators. source on GitHub

_main_onnx_optim

module mlprodict.onnx_tools.optim._main_onnx_optim Calls all possible ONNX optimisations. source on GitHub

_new_ops

module mlprodict.onnxrt.ops_cpu._new_ops Defines new operators. source on GitHub

_onnx_check_model

module mlprodict.onnx_tools._onnx_check_model Python implementation of onnx.checker.check_model. source on GitHub

_onnx_optimisation_common

module mlprodict.onnx_tools.optim._onnx_optimisation_common Common functions to reduce the number of nodes of an ONNX graphs. source on GitHub

_op

module mlprodict.onnxrt.ops_cpu._op Shortcut to ops_cpu. source on GitHub

_op

module mlprodict.onnxrt.ops_empty._op Shortcut to ops_onnxruntime. source on GitHub

_op

module mlprodict.onnxrt.ops_onnxruntime._op Shortcut to ops_onnxruntime. source on GitHub

_op_classifier_string

module mlprodict.onnxrt.ops_cpu._op_classifier_string Common class for classifiers supporting strings. source on GitHub

_op_helper

module mlprodict.onnxrt.ops_cpu._op_helper Runtime operator. source on GitHub

_op_list

module mlprodict.onnxrt.ops_cpu._op_list Imports runtime operators. source on GitHub

_op_numpy_helper

module mlprodict.onnxrt.ops_cpu._op_numpy_helper numpy redundant functions. source on GitHub

_op_onnx_numpy.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu._op_onnx_numpy C++ helpers of ONNX operators. source on GitHub

_op_shape_op

module mlprodict.onnxrt.ops_shape._op_shape_op Computes shape inference for onnx operators. source on GitHub

_validate_problems_helper

module mlprodict.onnxrt.validate._validate_problems_helper Validates runtime for many :scikit-learn: operators. The submodule relies on onnxconverter_common, sklearn-onnx. source on GitHub

api_extension

module mlprodict.grammar.grammar_sklearn.grammar.api_extension Implements decorators to extend the API. source on GitHub

asv2csv

module mlprodict.cli.asv2csv Command line about exporting asv results into a dataframe. source on GitHub

asv_bench

module mlprodict.cli.asv_bench Command line about validation of prediction runtime. source on GitHub

asv_exports

module mlprodict.asv_benchmark.asv_exports Functions to help exporting json format into text. source on GitHub

asv_options_helper

module mlprodict.tools.asv_options_helper Functions to show shortened options in asv benchmarks. source on GitHub

backend

module mlprodict.onnxrt.backend ONNX Backend for OnnxInference. :: import unittest from onnx.backend.test import BackendTest backend_test = BackendTest(backend, __name__) back_test.include(‘.*add.*’) globals().update(backend_test.enable_report().test_cases) unittest.main() source on GitHub

backend_micropy

module mlprodict.onnxrt.backend_micropy ONNX Backend for OnnxInference. :: import unittest from contextlib import redirect_stdout, redirect_stderr from io import StringIO from onnx.backend.test import BackendTest import mlprodict.onnxrt.backend_micropy as backend back_test = BackendTest(backend, __name__) 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) buffer = StringIO() print(’———————————’) 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(“testsRun=%d errors=%d skipped=%d unexpectedSuccesses=%d “ “expectedFailures=%d” % ( testsRun, errors, skipped, 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)) source on GitHub

backend_ort

module mlprodict.onnxrt.backend_ort ONNX Backend for OnnxInference. :: import unittest from contextlib import redirect_stdout, redirect_stderr from io import StringIO from onnx.backend.test import BackendTest import mlprodict.onnxrt.backend_ort as backend back_test = BackendTest(backend, __name__) 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) buffer = StringIO() print(’———————————’) 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(“testsRun=%d errors=%d skipped=%d unexpectedSuccesses=%d “ “expectedFailures=%d” % ( testsRun, errors, skipped, 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)) source on GitHub

backend_py

module mlprodict.onnxrt.backend_py ONNX Backend for OnnxInference. :: import unittest from contextlib import redirect_stdout, redirect_stderr from io import StringIO from onnx.backend.test import BackendTest import mlprodict.onnxrt.backend_py as backend back_test = BackendTest(backend, __name__) 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) buffer = StringIO() print(’———————————’) 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(“testsRun=%d errors=%d skipped=%d unexpectedSuccesses=%d “ “expectedFailures=%d” % ( testsRun, errors, skipped, 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)) source on GitHub

backend_pyc

module mlprodict.onnxrt.backend_pyc ONNX Backend for OnnxInference. :: import unittest from contextlib import redirect_stdout, redirect_stderr from io import StringIO from onnx.backend.test import BackendTest import mlprodict.onnxrt.backend_pyc as backend back_test = BackendTest(backend, __name__) 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) buffer = StringIO() print(’———————————’) 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(“testsRun=%d errors=%d skipped=%d unexpectedSuccesses=%d “ “expectedFailures=%d” % ( testsRun, errors, skipped, 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)) source on GitHub

backend_pyeval

module mlprodict.onnxrt.backend_pyeval ONNX Backend for OnnxInference. :: import unittest from contextlib import redirect_stdout, redirect_stderr from io import StringIO from onnx.backend.test import BackendTest import mlprodict.onnxrt.backend_pyeval as backend back_test = BackendTest(backend, __name__) 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) buffer = StringIO() print(’———————————’) 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(“testsRun=%d errors=%d skipped=%d unexpectedSuccesses=%d “ “expectedFailures=%d” % ( testsRun, errors, skipped, 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)) source on GitHub

backend_shape

module mlprodict.onnxrt.backend_shape ONNX Backend for OnnxInference. :: import unittest from contextlib import redirect_stdout, redirect_stderr from io import StringIO from onnx.backend.test import BackendTest import mlprodict.onnxrt.backend_shape as backend back_test = BackendTest(backend, __name__) 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) buffer = StringIO() print(’———————————’) 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(“testsRun=%d errors=%d skipped=%d unexpectedSuccesses=%d “ “expectedFailures=%d” % ( testsRun, errors, skipped, 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)) source on GitHub

blas_lapack

module mlprodict.testing.einsum.blas_lapack Direct calls to libraries BLAS and LAPACK. source on GitHub

c_compilation

module mlprodict.grammar.cc.c_compilation Helpers to compile C. source on GitHub

cdist_score

module mlprodict.onnx_conv.scorers.cdist_score Implementation of a dummy score using cdist. source on GitHub

cleaning

module mlprodict.tools.cleaning Better display. source on GitHub

code_helper

module mlprodict.tools.code_helper A couple of tools unrelated to what the package does. source on GitHub

common_asv_skl

module mlprodict.asv_benchmark.common_asv_skl Common class for all benchmarks testing converted models from scikit-learn with asv. The benchmark can be run through file run_asv.sh on Linux or run_asv.bat on Windows. .. warning:: On Windows, you should avoid cloning the repository on a folder with a long full name. Visual Studio tends to abide by the rule of the maximum path length even though the system is told otherwise. source on GitHub

compress

module mlprodict.onnx_tools.compress Functions to simplify, compress an ONNX graph. .. versionadded:: 0.9 source on GitHub

conv_lightgbm

module mlprodict.onnx_conv.operator_converters.conv_lightgbm Modified converter from LightGbm.py. source on GitHub

conv_transfer_transformer

module mlprodict.onnx_conv.operator_converters.conv_transfer_transformer Converters for models from mlinsights. source on GitHub

conv_xgboost

module mlprodict.onnx_conv.operator_converters.conv_xgboost Modified converter from XGBoost.py. source on GitHub

convert

module mlprodict.onnx_conv.convert Overloads a conversion function. source on GitHub

convert_validate

module mlprodict.cli.convert_validate Command line about validation of prediction runtime. source on GitHub

create_asv

module mlprodict.asv_benchmark.create_asv Functions to creates a benchmark based on asv for many regressors and classifiers. source on GitHub

direct_blas_lapack.cpython-39-x86_64-linux-gnu

module mlprodict.testing.einsum.direct_blas_lapack Direct calls to libraries BLAS and LAPACK. The wrapper for GEMM still does not work for matrices which are not square. source on GitHub

doc_helper

module mlprodict.onnxrt.doc.doc_helper Documentation helper. source on GitHub

doc_write_helper

module mlprodict.onnxrt.doc.doc_write_helper Documentation helper. source on GitHub

einsum

module mlprodict.cli.einsum Command line to check einsum scenarios. source on GitHub

einsum_bench

module mlprodict.testing.einsum.einsum_bench Function to measure the performance of einsum decomposition. source on GitHub

einsum_fct

module mlprodict.testing.einsum.einsum_fct Main functions decomposing einsum computation into more simple functions. source on GitHub

einsum_impl

module mlprodict.testing.einsum.einsum_impl Main functions decomposing einsum computation into more simple functions. source on GitHub

einsum_impl_classes

module mlprodict.testing.einsum.einsum_impl_classes Classes representing the sequence of matrix operations to implement einsum computation. source on GitHub

einsum_impl_ext

module mlprodict.testing.einsum.einsum_impl_ext Functions implemented einsum computation for two matrices having the same dimensions. source on GitHub

einsum_ml

module mlprodict.testing.einsum.einsum_ml Functions used to predict the cost of a transposition. source on GitHub

exc

module mlprodict.grammar.grammar_sklearn.grammar.exc Exception definition. source on GitHub

excs

module mlprodict.onnxrt.excs Exceptions. source on GitHub

experimental

module mlprodict.testing.experimental Experimental implementation. source on GitHub

experimental_c.cpython-39-x86_64-linux-gnu

module mlprodict.testing.experimental_c_impl.experimental_c C++ experimental implementations. source on GitHub

filename_helper

module mlprodict.tools.filename_helper A couple of tools related to filenames. source on GitHub

function_transformer_converters

module mlprodict.onnx_conv.sklconv.function_transformer_converters Rewrites some of the converters implemented in sklearn-onnx. source on GitHub

g_sklearn_identify

module mlprodict.grammar.grammar_sklearn.g_sklearn_identify Helpers to identify an interpreter. source on GitHub

g_sklearn_linear_model

module mlprodict.grammar.grammar_sklearn.g_sklearn_linear_model List of interpreted from scikit-learn model. source on GitHub

g_sklearn_main

module mlprodict.grammar.grammar_sklearn.g_sklearn_main Main functions to convert machine learned model from scikit-learn model. source on GitHub

g_sklearn_preprocessing

module mlprodict.grammar.grammar_sklearn.g_sklearn_preprocessing Converters from scikit-learn model. source on GitHub

g_sklearn_tree

module mlprodict.grammar.grammar_sklearn.g_sklearn_tree List of converters from scikit-learn model. source on GitHub

g_sklearn_type_helpers

module mlprodict.grammar.grammar_sklearn.g_sklearn_type_helpers Tiny helpers for scikit-learn exporters. source on GitHub

gactions

module mlprodict.grammar.grammar_sklearn.grammar.gactions Action definition. source on GitHub

gactions_num

module mlprodict.grammar.grammar_sklearn.grammar.gactions_num Action definition. source on GitHub

gactions_tensor

module mlprodict.grammar.grammar_sklearn.grammar.gactions_tensor Action definition. source on GitHub

gmlactions

module mlprodict.grammar.grammar_sklearn.grammar.gmlactions Actions definition. source on GitHub

graph_schema_helper

module mlprodict.onnx_tools.optim.graph_schema_helper Functions to help guessing the final graph structure. source on GitHub

graphs

module mlprodict.tools.graphs Alternative to dot to display a graph. .. versionadded:: 0.7 source on GitHub

gtypes

module mlprodict.grammar.grammar_sklearn.grammar.gtypes Types definition. source on GitHub

lgbm_helper

module mlprodict.onnx_conv.helpers.lgbm_helper Helpers to speed up the conversion of Lightgbm models or transform it. source on GitHub

model_checker

module mlprodict.onnx_tools.model_checker Investigate issues happening with float32. source on GitHub

model_info

module mlprodict.tools.model_info Functions to help get more information about the models. source on GitHub

model_verification

module mlprodict.testing.model_verification Complex but recurring testing functions. source on GitHub

nb_helper

module mlprodict.nb_helper Helpers for notebooks. source on GitHub

node_visitor_translator

module mlprodict.onnx_tools.onnx_grammar.node_visitor_translator One class which visits a syntax tree. source on GitHub

numpy_helper

module mlprodict.onnx_tools.exports.numpy_helper Numpy helpers for the conversion from onnx to numpy. source on GitHub

numpy_onnx_impl

module mlprodict.npy.numpy_onnx_impl numpy functions implemented with onnx. .. versionadded:: 0.6 .. versionchanged:: 0.7 source on GitHub

numpy_onnx_impl_body

module mlprodict.npy.numpy_onnx_impl_body Design to implement graph as parameter. .. versionadded:: 0.8 source on GitHub

numpy_onnx_impl_skl

module mlprodict.npy.numpy_onnx_impl_skl numpy functions implemented with onnx. .. versionadded:: 0.6 source on GitHub

numpy_onnx_pyrt

module mlprodict.npy.numpy_onnx_pyrt numpy functions implemented with onnx and compiled with this python runtime. .. versionadded:: 0.6 source on GitHub

numpy_onnx_pyrt_skl

module mlprodict.npy.numpy_onnx_pyrt_skl numpy functions implemented with onnx and compiled with this python runtime. .. versionadded:: 0.6 source on GitHub

onnx2py_helper

module mlprodict.onnx_tools.onnx2py_helper Functions which converts ONNX object into readable python objects. source on GitHub

onnx_backend

module mlprodict.testing.onnx_backend Tests with onnx backend. source on GitHub

onnx_code

module mlprodict.cli.onnx_code Command line to check einsum scenarios. source on GitHub

onnx_complex

module mlprodict.onnx_conv.onnx_ops.onnx_complex Custom operators for complex numbers. source on GitHub

onnx_export

module mlprodict.onnx_tools.onnx_export Exports an ONNX graph in a way it can we created again with a python script. It relies on jinja2 and autopep8. .. versionadded:: 0.7 source on GitHub

onnx_export_templates

module mlprodict.onnx_tools.onnx_export_templates Templates to export an ONNX graph in a way it can we created again with a python script. .. versionadded:: 0.7 source on GitHub

onnx_fft

module mlprodict.onnx_conv.onnx_ops.onnx_fft Custom operators for FFT. source on GitHub

onnx_gradient_op

module mlprodict.onnx_conv.onnx_ops.onnx_gradient_op Custom operators for gradient numbers. source on GitHub

onnx_helper

module mlprodict.onnx_tools.optim.onnx_helper Statistics on ONNX models. source on GitHub

onnx_inference

module mlprodict.onnxrt.onnx_inference Implements a class able to compute the predictions from on an ONNX model. source on GitHub

onnx_inference_exports

module mlprodict.onnxrt.onnx_inference_exports Extensions to class OnnxInference. source on GitHub

onnx_inference_node

module mlprodict.onnxrt.onnx_inference_node OnnxInferenceNode definition. source on GitHub

onnx_inference_ort_helper

module mlprodict.tools.onnx_inference_ort_helper Helpers for onnxruntime. source on GitHub

onnx_manipulations

module mlprodict.onnx_tools.onnx_manipulations Implements a class able to compute the predictions from on an ONNX model. source on GitHub

onnx_micro_runtime

module mlprodict.onnxrt.onnx_micro_runtime Micro runtime for ONNX. .. versionadded:: 0.6 source on GitHub

onnx_numpy_annotation

module mlprodict.npy.onnx_numpy_annotation numpy annotations. .. versionadded:: 0.6 source on GitHub

onnx_numpy_compiler

module mlprodict.npy.onnx_numpy_compiler Implements numpy functions with onnx and a runtime. .. versionadded:: 0.6 source on GitHub

onnx_numpy_wrapper

module mlprodict.npy.onnx_numpy_wrapper Wraps numpy functions into onnx. .. versionadded:: 0.6 source on GitHub

onnx_optimisation

module mlprodict.onnx_tools.optim.onnx_optimisation Optimisations of ONNX graphs. source on GitHub

onnx_optimisation_identity

module mlprodict.onnx_tools.optim.onnx_optimisation_identity Optimisation of ONNX graphs. source on GitHub

onnx_optimisation_redundant

module mlprodict.onnx_tools.optim.onnx_optimisation_redundant Optimisation of ONNX graphs. source on GitHub

onnx_optimisation_unused

module mlprodict.onnx_tools.optim.onnx_optimisation_unused Optimisation of ONNX graphs. source on GitHub

onnx_pipeline

module mlprodict.sklapi.onnx_pipeline A pipeline which serializes into ONNX steps by steps. source on GitHub

onnx_shape_inference

module mlprodict.onnxrt.onnx_shape_inference Runtime to infer shapes. .. versionadded:: 0.9 source on GitHub

onnx_sklearn_wrapper

module mlprodict.npy.onnx_sklearn_wrapper Helpers to use numpy API to easily write converters for scikit-learn classes for onnx. .. versionadded:: 0.6 source on GitHub

onnx_speed_up

module mlprodict.sklapi.onnx_speed_up Speeding up scikit-learn with onnx. .. versionadded:: 0.7 source on GitHub

onnx_tokenizer

module mlprodict.onnx_conv.onnx_ops.onnx_tokenizer Custom operator Tokenizer. source on GitHub

onnx_tokenizer

module mlprodict.sklapi.onnx_tokenizer Wrapper tokenizrs implemented in onnxruntime-extensions. source on GitHub

onnx_tools

module mlprodict.onnx_tools.onnx_tools Functions to manipulate ONNX file. source on GitHub

onnx_transformer

module mlprodict.sklapi.onnx_transformer Wraps runtime into a scikit-learn transformer. source on GitHub

onnx_translation

module mlprodict.onnx_tools.onnx_grammar.onnx_translation One class which visits a syntax tree. source on GitHub

onnx_translator

module mlprodict.onnx_tools.onnx_grammar.onnx_translator One class which visits a syntax tree. source on GitHub

onnx_variable

module mlprodict.npy.onnx_variable Intermediate class between numpy and onnx. .. versionadded:: 0.6 source on GitHub

onnx_version

module mlprodict.npy.onnx_version Identifies a version of a function. .. versionadded:: 0.6 source on GitHub

op_abs

module mlprodict.onnxrt.ops_cpu.op_abs Runtime operator. source on GitHub

op_acos

module mlprodict.onnxrt.ops_cpu.op_acos Runtime operator. source on GitHub

op_acosh

module mlprodict.onnxrt.ops_cpu.op_acosh Runtime operator. source on GitHub

op_adagrad

module mlprodict.onnxrt.ops_cpu.op_adagrad Runtime operator. source on GitHub

op_adam

module mlprodict.onnxrt.ops_cpu.op_adam Runtime operator. source on GitHub

op_add

module mlprodict.onnxrt.ops_cpu.op_add Runtime operator. source on GitHub

op_and

module mlprodict.onnxrt.ops_cpu.op_and Runtime operator. source on GitHub

op_argmax

module mlprodict.onnxrt.ops_cpu.op_argmax Runtime operator. source on GitHub

op_argmin

module mlprodict.onnxrt.ops_cpu.op_argmin Runtime operator. source on GitHub

op_array_feature_extractor

module mlprodict.onnxrt.ops_cpu.op_array_feature_extractor Runtime operator. source on GitHub

op_asin

module mlprodict.onnxrt.ops_cpu.op_asin Runtime operator. source on GitHub

op_asinh

module mlprodict.onnxrt.ops_cpu.op_asinh Runtime operator. source on GitHub

op_atan

module mlprodict.onnxrt.ops_cpu.op_atan Runtime operator. source on GitHub

op_atanh

module mlprodict.onnxrt.ops_cpu.op_atanh Runtime operator. source on GitHub

op_average_pool

module mlprodict.onnxrt.ops_cpu.op_average_pool Runtime operator. source on GitHub

op_batch_normalization

module mlprodict.onnxrt.ops_cpu.op_batch_normalization Runtime operator. source on GitHub

op_binarizer

module mlprodict.onnxrt.ops_cpu.op_binarizer Runtime operator. source on GitHub

op_bitshift

module mlprodict.onnxrt.ops_cpu.op_bitshift Runtime operator. source on GitHub

op_broadcast_gradient_args

module mlprodict.onnxrt.ops_cpu.op_broadcast_gradient_args Runtime operator. source on GitHub

op_cast

module mlprodict.onnxrt.ops_cpu.op_cast Runtime operator. source on GitHub

op_category_mapper

module mlprodict.onnxrt.ops_cpu.op_category_mapper Runtime operator. source on GitHub

op_cdist

module mlprodict.onnxrt.ops_cpu.op_cdist Runtime operator. source on GitHub

op_ceil

module mlprodict.onnxrt.ops_cpu.op_ceil Runtime operator. source on GitHub

op_celu

module mlprodict.onnxrt.ops_cpu.op_celu Runtime operator. source on GitHub

op_clip

module mlprodict.onnxrt.ops_cpu.op_clip Runtime operator. source on GitHub

op_complex_abs

module mlprodict.onnxrt.ops_cpu.op_complex_abs Runtime operator. source on GitHub

op_compress

module mlprodict.onnxrt.ops_cpu.op_compress Runtime operator. source on GitHub

op_concat

module mlprodict.onnxrt.ops_cpu.op_concat Runtime operator. source on GitHub

op_concat_from_sequence

module mlprodict.onnxrt.ops_cpu.op_concat_from_sequence Runtime operator. source on GitHub

op_constant

module mlprodict.onnxrt.ops_cpu.op_constant Runtime operator. source on GitHub

op_constant_of_shape

module mlprodict.onnxrt.ops_cpu.op_constant_of_shape Runtime operator. source on GitHub

op_conv

module mlprodict.onnxrt.ops_cpu.op_conv Runtime operator. source on GitHub

op_conv_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_conv_ Implements runtime for operator Conv. The code is inspired from conv.cc in onnxruntime. source on GitHub

op_conv_helper

module mlprodict.onnxrt.ops_cpu.op_conv_helper Helpers for operators Conv, ConvTranspose. source on GitHub

op_conv_helper_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_conv_helper_ Helpers for convolution functions, inspired from conv_transpose.cc in onnxruntime. source on GitHub

op_conv_transpose

module mlprodict.onnxrt.ops_cpu.op_conv_transpose Runtime operator. source on GitHub

op_conv_transpose_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_conv_transpose_ Implements runtime for operator Conv. The code is inspired from conv_transpose.cc in onnxruntime. source on GitHub

op_cos

module mlprodict.onnxrt.ops_cpu.op_cos Runtime operator. source on GitHub

op_cosh

module mlprodict.onnxrt.ops_cpu.op_cosh Runtime operator. source on GitHub

op_cum_sum

module mlprodict.onnxrt.ops_cpu.op_cum_sum Runtime operator. source on GitHub

op_debug

module mlprodict.onnxrt.ops_cpu.op_debug Runtime operator. source on GitHub

op_depth_to_space

module mlprodict.onnxrt.ops_cpu.op_depth_to_space Runtime operator. source on GitHub

op_dequantize_linear

module mlprodict.onnxrt.ops_cpu.op_dequantize_linear Runtime operator. source on GitHub

op_det

module mlprodict.onnxrt.ops_cpu.op_det Runtime operator. source on GitHub

op_dft

module mlprodict.onnxrt.ops_cpu.op_dft Runtime operator. source on GitHub

op_dict_vectorizer

module mlprodict.onnxrt.ops_cpu.op_dict_vectorizer Runtime operator. source on GitHub

op_div

module mlprodict.onnxrt.ops_cpu.op_div Runtime operator. source on GitHub

op_dropout

module mlprodict.onnxrt.ops_cpu.op_dropout Runtime operator. source on GitHub

op_einsum

module mlprodict.onnxrt.ops_cpu.op_einsum Runtime operator. source on GitHub

op_elu

module mlprodict.onnxrt.ops_cpu.op_elu Runtime operator. source on GitHub

op_equal

module mlprodict.onnxrt.ops_cpu.op_equal Runtime operator. source on GitHub

op_erf

module mlprodict.onnxrt.ops_cpu.op_erf Runtime operator. source on GitHub

op_exp

module mlprodict.onnxrt.ops_cpu.op_exp Runtime operator. source on GitHub

op_expand

module mlprodict.onnxrt.ops_cpu.op_expand Runtime operator. source on GitHub

op_expression

module mlprodict.onnxrt.ops_cpu.op_expression Runtime operator. source on GitHub

op_eyelike

module mlprodict.onnxrt.ops_cpu.op_eyelike Runtime operator. source on GitHub

op_feature_vectorizer

module mlprodict.onnxrt.ops_cpu.op_feature_vectorizer Runtime operator. source on GitHub

op_fft

module mlprodict.onnxrt.ops_cpu.op_fft Runtime operator. source on GitHub

op_fft2d

module mlprodict.onnxrt.ops_cpu.op_fft2d Runtime operator. source on GitHub

op_flatten

module mlprodict.onnxrt.ops_cpu.op_flatten Runtime operator. source on GitHub

op_floor

module mlprodict.onnxrt.ops_cpu.op_floor Runtime operator. source on GitHub

op_fused_matmul

module mlprodict.onnxrt.ops_cpu.op_fused_matmul Runtime operator. source on GitHub

op_gather

module mlprodict.onnxrt.ops_cpu.op_gather Runtime operator. source on GitHub

op_gather_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_gather_ Implements runtime for operator Gather. The code is inspired from tfidfvectorizer.cc in onnxruntime. source on GitHub

op_gather_elements

module mlprodict.onnxrt.ops_cpu.op_gather_elements Runtime operator. source on GitHub

op_gathernd

module mlprodict.onnxrt.ops_cpu.op_gathernd Runtime operator. source on GitHub

op_gemm

module mlprodict.onnxrt.ops_cpu.op_gemm Runtime operator. source on GitHub

op_global_average_pool

module mlprodict.onnxrt.ops_cpu.op_global_average_pool Runtime operator. source on GitHub

op_greater

module mlprodict.onnxrt.ops_cpu.op_greater Runtime operator. source on GitHub

op_grid_sample

module mlprodict.onnxrt.ops_cpu.op_grid_sample Runtime operator. source on GitHub

op_grid_sample_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_grid_sample_ Implements runtime for operator GridSample. The code is inspired from pool.cc in onnxruntime. source on GitHub

op_gru

module mlprodict.onnxrt.ops_cpu.op_gru Runtime operator. source on GitHub

op_hard_sigmoid

module mlprodict.onnxrt.ops_cpu.op_hard_sigmoid Runtime operator. source on GitHub

op_hardmax

module mlprodict.onnxrt.ops_cpu.op_hardmax Runtime operator. source on GitHub

op_identity

module mlprodict.onnxrt.ops_cpu.op_identity Runtime operator. source on GitHub

op_if

module mlprodict.onnxrt.ops_cpu.op_if Runtime operator. source on GitHub

op_imputer

module mlprodict.onnxrt.ops_cpu.op_imputer Runtime operator. source on GitHub

op_inverse

module mlprodict.onnxrt.ops_cpu.op_inverse Runtime operator. source on GitHub

op_isinf

module mlprodict.onnxrt.ops_cpu.op_isinf Runtime operator. source on GitHub

op_isnan

module mlprodict.onnxrt.ops_cpu.op_isnan Runtime operator. source on GitHub

op_label_encoder

module mlprodict.onnxrt.ops_cpu.op_label_encoder Runtime operator. source on GitHub

op_layer_normalization

module mlprodict.onnxrt.ops_cpu.op_layer_normalization Runtime operator. source on GitHub

op_leaky_relu

module mlprodict.onnxrt.ops_cpu.op_leaky_relu Runtime operator. source on GitHub

op_less

module mlprodict.onnxrt.ops_cpu.op_less Runtime operator. source on GitHub

op_linear_classifier

module mlprodict.onnxrt.ops_cpu.op_linear_classifier Runtime operator. source on GitHub

op_linear_regressor

module mlprodict.onnxrt.ops_cpu.op_linear_regressor Runtime operator. source on GitHub

op_log

module mlprodict.onnxrt.ops_cpu.op_log Runtime operator. source on GitHub

op_log_softmax

module mlprodict.onnxrt.ops_cpu.op_log_softmax Runtime operator. source on GitHub

op_loop

module mlprodict.onnxrt.ops_cpu.op_loop Runtime operator. .. versionadded:: 0.7 source on GitHub

op_lp_normalization

module mlprodict.onnxrt.ops_cpu.op_lp_normalization Runtime operator. source on GitHub

op_lrn

module mlprodict.onnxrt.ops_cpu.op_lrn Runtime operator. source on GitHub

op_lstm

module mlprodict.onnxrt.ops_cpu.op_lstm Runtime operator. source on GitHub

op_matmul

module mlprodict.onnxrt.ops_cpu.op_matmul Runtime operator. source on GitHub

op_max

module mlprodict.onnxrt.ops_cpu.op_max Runtime operator. source on GitHub

op_max_pool

module mlprodict.onnxrt.ops_cpu.op_max_pool Runtime operator. source on GitHub

op_max_pool_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_max_pool_ Implements runtime for operator MaxPool. The code is inspired from pool.cc in onnxruntime. source on GitHub

op_mean

module mlprodict.onnxrt.ops_cpu.op_mean Runtime operator. source on GitHub

op_min

module mlprodict.onnxrt.ops_cpu.op_min Runtime operator. source on GitHub

op_mod

module mlprodict.onnxrt.ops_cpu.op_mod Runtime operator. source on GitHub

op_momentum

module mlprodict.onnxrt.ops_cpu.op_momentum Runtime operator. source on GitHub

op_mul

module mlprodict.onnxrt.ops_cpu.op_mul Runtime operator. source on GitHub

op_neg

module mlprodict.onnxrt.ops_cpu.op_neg Runtime operator. source on GitHub

op_negative_log_likelihood_loss

module mlprodict.onnxrt.ops_cpu.op_negative_log_likelihood_loss Runtime operator. source on GitHub

op_non_max_suppression

module mlprodict.onnxrt.ops_cpu.op_non_max_suppression Runtime operator. source on GitHub

op_non_max_suppression_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_non_max_suppression_ Implements runtime for operator NonMaxSuppression. The code is inspired from non_max_suppression.cc in onnxruntime. source on GitHub

op_non_zero

module mlprodict.onnxrt.ops_cpu.op_non_zero Runtime operator. source on GitHub

op_normalizer

module mlprodict.onnxrt.ops_cpu.op_normalizer Runtime operator. source on GitHub

op_not

module mlprodict.onnxrt.ops_cpu.op_not Runtime operator. source on GitHub

op_one_hot

module mlprodict.onnxrt.ops_cpu.op_one_hot Runtime operator. source on GitHub

op_one_hot_encoder

module mlprodict.onnxrt.ops_cpu.op_one_hot_encoder Runtime operator. source on GitHub

op_optional

module mlprodict.onnxrt.ops_cpu.op_optional Runtime operator. source on GitHub

op_or

module mlprodict.onnxrt.ops_cpu.op_or Runtime operator. source on GitHub

op_pad

module mlprodict.onnxrt.ops_cpu.op_pad Runtime operator. source on GitHub

op_pow

module mlprodict.onnxrt.ops_cpu.op_pow Runtime operator. source on GitHub

op_prelu

module mlprodict.onnxrt.ops_cpu.op_prelu Runtime operator. source on GitHub

op_qlinear_conv

module mlprodict.onnxrt.ops_cpu.op_qlinear_conv Runtime operator. source on GitHub

op_qlinear_conv_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_qlinear_conv_ Implements runtime for operator QLinearConv. The code is inspired from conv.cc in onnxruntime. source on GitHub

op_quantize_linear

module mlprodict.onnxrt.ops_cpu.op_quantize_linear Runtime operator. source on GitHub

op_random

module mlprodict.onnxrt.ops_cpu.op_random Runtime operator. source on GitHub

op_range

module mlprodict.onnxrt.ops_cpu.op_range Runtime operator. source on GitHub

op_reciprocal

module mlprodict.onnxrt.ops_cpu.op_reciprocal Runtime operator. source on GitHub

op_reduce_l1

module mlprodict.onnxrt.ops_cpu.op_reduce_l1 Runtime operator. source on GitHub

op_reduce_l2

module mlprodict.onnxrt.ops_cpu.op_reduce_l2 Runtime operator. source on GitHub

op_reduce_log_sum

module mlprodict.onnxrt.ops_cpu.op_reduce_log_sum Runtime operator. source on GitHub

op_reduce_log_sum_exp

module mlprodict.onnxrt.ops_cpu.op_reduce_log_sum_exp Runtime operator. source on GitHub

op_reduce_max

module mlprodict.onnxrt.ops_cpu.op_reduce_max Runtime operator. source on GitHub

op_reduce_mean

module mlprodict.onnxrt.ops_cpu.op_reduce_mean Runtime operator. source on GitHub

op_reduce_min

module mlprodict.onnxrt.ops_cpu.op_reduce_min Runtime operator. source on GitHub

op_reduce_prod

module mlprodict.onnxrt.ops_cpu.op_reduce_prod Runtime operator. source on GitHub

op_reduce_sum

module mlprodict.onnxrt.ops_cpu.op_reduce_sum Runtime operator. source on GitHub

op_reduce_sum_square

module mlprodict.onnxrt.ops_cpu.op_reduce_sum_square Runtime operator. source on GitHub

op_relu

module mlprodict.onnxrt.ops_cpu.op_relu Runtime operator. source on GitHub

op_reshape

module mlprodict.onnxrt.ops_cpu.op_reshape Runtime operator. source on GitHub

op_resize

module mlprodict.onnxrt.ops_cpu.op_resize Runtime operator. source on GitHub

op_rfft

module mlprodict.onnxrt.ops_cpu.op_rfft Runtime operator. source on GitHub

op_rnn

module mlprodict.onnxrt.ops_cpu.op_rnn Runtime operator. source on GitHub

op_roi_align

module mlprodict.onnxrt.ops_cpu.op_roi_align Runtime operator. source on GitHub

op_roi_align_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_roi_align_ Implements runtime for operator RoiAlign. The code is inspired from pool.cc in onnxruntime. source on GitHub

op_round

module mlprodict.onnxrt.ops_cpu.op_round Runtime operator. source on GitHub

op_scaler

module mlprodict.onnxrt.ops_cpu.op_scaler Runtime operator. source on GitHub

op_scan

module mlprodict.onnxrt.ops_cpu.op_scan Runtime operator. source on GitHub

op_scatter_elements

module mlprodict.onnxrt.ops_cpu.op_scatter_elements Runtime operator. source on GitHub

op_scatternd

module mlprodict.onnxrt.ops_cpu.op_scatternd Runtime operator. source on GitHub

op_selu

module mlprodict.onnxrt.ops_cpu.op_selu Runtime operator. source on GitHub

op_sequence_at

module mlprodict.onnxrt.ops_cpu.op_sequence_at Runtime operator. .. versionadded:: 0.8 source on GitHub

op_sequence_construct

module mlprodict.onnxrt.ops_cpu.op_sequence_construct Runtime operator. .. versionadded:: 0.7 source on GitHub

op_sequence_empty

module mlprodict.onnxrt.ops_cpu.op_sequence_empty Runtime operator. .. versionadded:: 0.9 source on GitHub

op_sequence_insert

module mlprodict.onnxrt.ops_cpu.op_sequence_insert Runtime operator. .. versionadded:: 0.7 source on GitHub

op_shape

module mlprodict.onnxrt.ops_cpu.op_shape Runtime operator. source on GitHub

op_shrink

module mlprodict.onnxrt.ops_cpu.op_shrink Runtime operator. source on GitHub

op_sigmoid

module mlprodict.onnxrt.ops_cpu.op_sigmoid Runtime operator. source on GitHub

op_sign

module mlprodict.onnxrt.ops_cpu.op_sign Runtime operator. source on GitHub

op_sin

module mlprodict.onnxrt.ops_cpu.op_sin Runtime operator. source on GitHub

op_sinh

module mlprodict.onnxrt.ops_cpu.op_sinh Runtime operator. source on GitHub

op_size

module mlprodict.onnxrt.ops_cpu.op_size Runtime operator. source on GitHub

op_slice

module mlprodict.onnxrt.ops_cpu.op_slice Runtime operator. source on GitHub

op_softmax

module mlprodict.onnxrt.ops_cpu.op_softmax Runtime operator. source on GitHub

op_softmax_cross_entropy_loss

module mlprodict.onnxrt.ops_cpu.op_softmax_cross_entropy_loss Runtime operator. source on GitHub

op_softplus

module mlprodict.onnxrt.ops_cpu.op_softplus Runtime operator. source on GitHub

op_softsign

module mlprodict.onnxrt.ops_cpu.op_softsign Runtime operator. source on GitHub

op_solve

module mlprodict.onnxrt.ops_cpu.op_solve Runtime operator. source on GitHub

op_split

module mlprodict.onnxrt.ops_cpu.op_split Runtime operator. source on GitHub

op_sqrt

module mlprodict.onnxrt.ops_cpu.op_sqrt Runtime operator. source on GitHub

op_squeeze

module mlprodict.onnxrt.ops_cpu.op_squeeze Runtime operator. source on GitHub

op_stft

module mlprodict.onnxrt.ops_cpu.op_stft Runtime operator. source on GitHub

op_string_normalizer

module mlprodict.onnxrt.ops_cpu.op_string_normalizer Runtime operator. source on GitHub

op_sub

module mlprodict.onnxrt.ops_cpu.op_sub Runtime operator. source on GitHub

op_sum

module mlprodict.onnxrt.ops_cpu.op_sum Runtime operator. source on GitHub

op_svm_classifier

module mlprodict.onnxrt.ops_cpu.op_svm_classifier Runtime operator. source on GitHub

op_svm_classifier_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_svm_classifier_ Implements runtime for operator SVMClassifier. The code is inspired from svm_classifier.cc in onnxruntime. source on GitHub

op_svm_regressor

module mlprodict.onnxrt.ops_cpu.op_svm_regressor Runtime operator. source on GitHub

op_svm_regressor_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_svm_regressor_ Implements runtime for operator SVMRegressor. The code is inspired from svm_regressor.cc in onnxruntime. source on GitHub

op_tan

module mlprodict.onnxrt.ops_cpu.op_tan Runtime operator. source on GitHub

op_tanh

module mlprodict.onnxrt.ops_cpu.op_tanh Runtime operator. source on GitHub

op_tfidfvectorizer

module mlprodict.onnxrt.ops_cpu.op_tfidfvectorizer Runtime operator. source on GitHub

op_tfidfvectorizer_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_tfidfvectorizer_ Implements runtime for operator TfIdfVectorizer. The code is inspired from tfidfvectorizer.cc in onnxruntime. source on GitHub

op_tokenizer

module mlprodict.onnxrt.ops_cpu.op_tokenizer Runtime operator. source on GitHub

op_topk

module mlprodict.onnxrt.ops_cpu.op_topk Runtime operator. source on GitHub

op_transpose

module mlprodict.onnxrt.ops_cpu.op_transpose Runtime operator. source on GitHub

op_tree_ensemble_classifier

module mlprodict.onnxrt.ops_cpu.op_tree_ensemble_classifier Runtime operator. source on GitHub

op_tree_ensemble_classifier_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_tree_ensemble_classifier_ Implements runtime for operator TreeEnsembleClassifier. The code is inspired from tree_ensemble_classifier.cc in onnxruntime. source on GitHub

op_tree_ensemble_classifier_p_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_tree_ensemble_classifier_p_ Implements runtime for operator TreeEnsembleClassifier. The code is inspired from tree_ensemble_Classifier.cc in onnxruntime. source on GitHub

op_tree_ensemble_regressor

module mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor Runtime operator. source on GitHub

op_tree_ensemble_regressor_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_ Implements runtime for operator TreeEnsembleRegressor. The code is inspired from tree_ensemble_regressor.cc in onnxruntime. source on GitHub

op_tree_ensemble_regressor_p_.cpython-39-x86_64-linux-gnu

module mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_p_ Implements runtime for operator TreeEnsembleRegressor. The code is inspired from tree_ensemble_regressor.cc in onnxruntime. source on GitHub

op_trilu

module mlprodict.onnxrt.ops_cpu.op_trilu Runtime operator. source on GitHub

op_unique

module mlprodict.onnxrt.ops_cpu.op_unique Runtime operator. source on GitHub

op_unsqueeze

module mlprodict.onnxrt.ops_cpu.op_unsqueeze Runtime operator. source on GitHub

op_where

module mlprodict.onnxrt.ops_cpu.op_where Runtime operator. source on GitHub

op_window

module mlprodict.onnxrt.ops_cpu.op_window Runtime operator. source on GitHub

op_xor

module mlprodict.onnxrt.ops_cpu.op_xor Runtime operator. source on GitHub

op_yield_op

module mlprodict.onnxrt.ops_cpu.op_yield_op Runtime operator. source on GitHub

op_zipmap

module mlprodict.onnxrt.ops_cpu.op_zipmap Runtime operator. source on GitHub

ops

module mlprodict.onnxrt.ops Loads runtime operator. source on GitHub

optimize

module mlprodict.cli.optimize Command line about model optimisation. source on GitHub

ort_wrapper

module mlprodict.tools.ort_wrapper Wrapper around onnxruntime. .. versionadded:: 0.6 source on GitHub

parse_lightgbm

module mlprodict.onnx_conv.operator_converters.parse_lightgbm Parsers for LightGBM booster. source on GitHub

plotting

module mlprodict.plotting.plotting Shorcuts to plotting functions. source on GitHub

plotting_benchmark

module mlprodict.plotting.plotting_benchmark Useful plots. source on GitHub

plotting_onnx

module mlprodict.plotting.plotting_onnx Useful plots. source on GitHub

plotting_validate_graph

module mlprodict.plotting.plotting_validate_graph Functions to help visualizing performances. source on GitHub

quantized_tensor

module mlprodict.testing.test_utils.quantized_tensor Initializes a quantized tensor from float values. source on GitHub

register

module mlprodict.onnx_conv.register Shortcut to onnx_conv. source on GitHub

register

module mlprodict.onnx_conv.scorers.register Registers new converters. source on GitHub

register_rewritten_converters

module mlprodict.onnx_conv.register_rewritten_converters Rewrites some of the converters implemented in sklearn-onnx. source on GitHub

replay

module mlprodict.cli.replay Command line about validation of prediction runtime. source on GitHub

script_testing

module mlprodict.testing.script_testing Utilies to test script from scikit-learn documentation. source on GitHub

session

module mlprodict.onnxrt.ops_whole.session Shortcut to ops_whole. source on GitHub

shape_container

module mlprodict.onnxrt.ops_shape.shape_container Class ShapeContainer source on GitHub

shape_excs

module mlprodict.onnxrt.ops_shape.shape_excs Errors and exceptions for OnnxShapeInference. source on GitHub

shape_result

module mlprodict.onnxrt.ops_shape.shape_result Class ShapeResult source on GitHub

side_by_side

module mlprodict.onnxrt.validate.side_by_side Helpers to compare executions. source on GitHub

skl2onnx_helper

module mlprodict.onnx_tools.exports.skl2onnx_helper Helpers to run examples created with sklearn-onnx. source on GitHub

skl_model_classifier

module mlprodict.asv_benchmark.template.skl_model_classifier A template to benchmark a model with asv. The benchmark can be run through file run_asv.sh on Linux or run_asv.bat on Windows. .. warning:: On Windows, you should avoid cloning the repository on a folder with a long full name. Visual Studio tends to abide by the rule of the maximum path length even though the system is told otherwise. source on GitHub

skl_model_classifier_raw_scores

module mlprodict.asv_benchmark.template.skl_model_classifier_raw_scores A template to benchmark a model with asv. The benchmark can be run through file run_asv.sh on Linux or run_asv.bat on Windows. .. warning:: On Windows, you should avoid cloning the repository on a folder with a long full name. Visual Studio tends to abide by the rule of the maximum path length even though the system is told otherwise. source on GitHub

skl_model_clustering

module mlprodict.asv_benchmark.template.skl_model_clustering A template to benchmark a model with asv. The benchmark can be run through file run_asv.sh on Linux or run_asv.bat on Windows. .. warning:: On Windows, you should avoid cloning the repository on a folder with a long full name. Visual Studio tends to abide by the rule of the maximum path length even though the system is told otherwise. source on GitHub

skl_model_multi_classifier

module mlprodict.asv_benchmark.template.skl_model_multi_classifier A template to benchmark a model with asv. The benchmark can be run through file run_asv.sh on Linux or run_asv.bat on Windows. .. warning:: On Windows, you should avoid cloning the repository on a folder with a long full name. Visual Studio tends to abide by the rule of the maximum path length even though the system is told otherwise. source on GitHub

skl_model_outlier

module mlprodict.asv_benchmark.template.skl_model_outlier A template to benchmark a model with asv. The benchmark can be run through file run_asv.sh on Linux or run_asv.bat on Windows. .. warning:: On Windows, you should avoid cloning the repository on a folder with a long full name. Visual Studio tends to abide by the rule of the maximum path length even though the system is told otherwise. source on GitHub

skl_model_regressor

module mlprodict.asv_benchmark.template.skl_model_regressor A template to benchmark a model with asv. The benchmark can be run through file run_asv.sh on Linux or run_asv.bat on Windows. .. warning:: On Windows, you should avoid cloning the repository on a folder with a long full name. Visual Studio tends to abide by the rule of the maximum path length even though the system is told otherwise. source on GitHub

skl_model_trainable_transform

module mlprodict.asv_benchmark.template.skl_model_trainable_transform A template to benchmark a model with asv. The benchmark can be run through file run_asv.sh on Linux or run_asv.bat on Windows. .. warning:: On Windows, you should avoid cloning the repository on a folder with a long full name. Visual Studio tends to abide by the rule of the maximum path length even though the system is told otherwise. source on GitHub

skl_model_transform

module mlprodict.asv_benchmark.template.skl_model_transform A template to benchmark a model with asv. The benchmark can be run through file run_asv.sh on Linux or run_asv.bat on Windows. .. warning:: On Windows, you should avoid cloning the repository on a folder with a long full name. Visual Studio tends to abide by the rule of the maximum path length even though the system is told otherwise. source on GitHub

skl_model_transform_positive

module mlprodict.asv_benchmark.template.skl_model_transform_positive A template to benchmark a model with asv. The benchmark can be run through file run_asv.sh on Linux or run_asv.bat on Windows. .. warning:: On Windows, you should avoid cloning the repository on a folder with a long full name. Visual Studio tends to abide by the rule of the maximum path length even though the system is told otherwise. source on GitHub

sklearn_helper

module mlprodict.onnx_tools.optim.sklearn_helper Helpers to manipulate scikit-learn models. source on GitHub

svm_converters

module mlprodict.onnx_conv.sklconv.svm_converters Rewrites some of the converters implemented in sklearn-onnx. source on GitHub

tests_helper

module mlprodict.testing.test_utils.tests_helper Inspired from sklearn-onnx, handles two backends. source on GitHub

text_plot

module mlprodict.plotting.text_plot Text representations of graphs. source on GitHub

tf2onnx_helper

module mlprodict.onnx_tools.exports.tf2onnx_helper Helpers to run examples created with function export2tf2onnx(). source on GitHub

tree_converters

module mlprodict.onnx_conv.sklconv.tree_converters Rewrites some of the converters implemented in sklearn-onnx. source on GitHub

utils_backend

module mlprodict.testing.test_utils.utils_backend Inspired from sklearn-onnx, handles two backends. source on GitHub

utils_backend_common

module mlprodict.testing.test_utils.utils_backend_common Inspired from sklearn-onnx, handles two backends. source on GitHub

utils_backend_common_compare

module mlprodict.testing.test_utils.utils_backend_common_compare Inspired from sklearn-onnx, handles two backends. source on GitHub

utils_backend_onnxruntime

module mlprodict.testing.test_utils.utils_backend_onnxruntime Inspired from sklearn-onnx, handles two backends. source on GitHub

utils_backend_python

module mlprodict.testing.test_utils.utils_backend_python Inspired from sklearn-onnx, handles two backends. source on GitHub

validate

module mlprodict.cli.validate Command line about validation of prediction runtime. source on GitHub

validate

module mlprodict.onnxrt.validate.validate Validates runtime for many :scikit-learn: operators. The submodule relies on onnxconverter_common, sklearn-onnx. source on GitHub

validate_benchmark

module mlprodict.onnxrt.validate.validate_benchmark Measures time processing for ONNX models. source on GitHub

validate_benchmark_replay

module mlprodict.onnxrt.validate.validate_benchmark_replay Measures time processing for ONNX models. source on GitHub

validate_difference

module mlprodict.onnxrt.validate.validate_difference Validates runtime for many :scikit-learn: operators. The submodule relies on onnxconverter_common, sklearn-onnx. source on GitHub

validate_helper

module mlprodict.onnxrt.validate.validate_helper Validates runtime for many scikit-learn operators. The submodule relies on onnxconverter_common, sklearn-onnx. source on GitHub

validate_latency

module mlprodict.onnxrt.validate.validate_latency Command line about validation of prediction runtime. source on GitHub

validate_problems

module mlprodict.onnxrt.validate.validate_problems Validates runtime for many :scikit-learn: operators. The submodule relies on onnxconverter_common, sklearn-onnx. source on GitHub

validate_python

module mlprodict.onnxrt.validate.validate_python Helpers to validate python code. source on GitHub

validate_scenarios

module mlprodict.onnx_conv.validate_scenarios Scenario for additional converters. source on GitHub

validate_scenarios

module mlprodict.onnxrt.validate.validate_scenarios Scenarios for validation. source on GitHub

validate_summary

module mlprodict.onnxrt.validate.validate_summary Summarizes results produces by function in validate.py. source on GitHub

verify_code

module mlprodict.testing.verify_code Looks into the code and detects error before finalizing the benchmark. source on GitHub

xop

module mlprodict.npy.xop Xop API to build onnx graphs. Inspired from sklearn-onnx. .. versionadded:: 0.9 source on GitHub

xop_auto

module mlprodict.npy.xop_auto Automates the generation of operators for the documentation for the Xop API. .. versionadded:: 0.9 source on GitHub

xop_auto_import_

module mlprodict.npy.xop_auto_import_ Xop API. Importing this file takes time. It should be avoided. .. versionadded:: 0.9 source on GitHub

xop_convert

module mlprodict.npy.xop_convert Easier API to build onnx graphs. Inspired from skl2onnx. .. versionadded:: 0.9 source on GitHub

xop_helper

module mlprodict.npy.xop_helper Xop helpers. .. versionadded:: 0.9 source on GitHub

xop_opset

module mlprodict.npy.xop_opset Xop API to build onnx graphs. Inspired from sklearn-onnx. .. versionadded:: 0.9 source on GitHub

xop_sphinx

module mlprodict.npy.xop_sphinx Automates the generation of operators for the documentation for the Xop API. :: def setup(app): app.connect(‘builder-inited’, generate_op_doc) .. versionadded:: 0.9 source on GitHub

xop_variable

module mlprodict.npy.xop_variable Xop API to build onnx graphs. Inspired from sklearn-onnx. .. versionadded:: 0.9 source on GitHub

zoo

module mlprodict.tools.zoo Tools to test models from the ONNX Zoo. .. versionadded:: 0.6 source on GitHub