onnx/sklearn-onnx

Project: sklearn-onnx (GitHub Link)

sklearn-onnx-master
- LICENSE
- .azure-pipelines
  - linux-conda-CI.yml
  - win32-conda-CI.yml
  - linux-CI-nightly.yml
  - win32-CI-nightly.yml
- setup.py
- benchmarks
  - bench_plot_onnxruntime_logreg.py
  - bench_plot_onnxruntime_random_forest.py
  - bench_plot_onnxruntime_decision_tree.py
- requirements-dev.txt
- skl2onnx
  - proto
    - __init__.py
    - onnx_helper_modified.py
  - algebra
    - sklearn_ops.py
    - onnx_subgraph_operator_mixin.py
    - custom_ops.py
    - type_helper.py
    - onnx_ops.py
    - __init__.py
    - onnx_operator.py
    - onnx_operator_mixin.py
    - automation.py
    - graph_state.py
    - complex_functions.py
  - _parse.py
  - _supported_operators.py
  - convert.py
  - helpers
    - investigate.py
    - __init__.py
    - onnx_helper.py
    - onnx_rare_helper.py
  - common
    - _apply_operation.py
    - _topology.py
    - exceptions.py
    - utils_checking.py
    - utils_classifier.py
    - _container.py
    - shape_calculator.py
    - _registration.py
    - data_types.py
    - tree_ensemble.py
    - __init__.py
    - utils.py
    - interface.py
  - shape_calculators
    - linear_regressor.py
    - polynomial_features.py
    - voting_regressor.py
    - support_vector_machines.py
    - text_vectorizer.py
    - mixture.py
    - flatten.py
    - function_transformer.py
    - k_means.py
    - array_feature_extractor.py
    - voting_classifier.py
    - gaussian_process.py
    - identity.py
    - svd.py
    - one_vs_rest_classifier.py
    - nearest_neighbours.py
    - ordinal_encoder.py
    - label_encoder.py
    - random_projection.py
    - k_bins_discretiser.py
    - one_hot_encoder.py
    - imputer.py
    - dict_vectorizer.py
    - __init__.py
    - scaler.py
    - tfidf_transformer.py
    - cast_op.py
    - power_transformer.py
    - label_binariser.py
    - grid_search_cv.py
    - linear_classifier.py
    - concat.py
    - cross_decomposition.py
    - zip_map.py
  - __init__.py
  - sklapi
    - cast_transformer.py
    - __init__.py
  - operator_converters
    - linear_regressor.py
    - polynomial_features.py
    - voting_regressor.py
    - support_vector_machines.py
    - stacking.py
    - multilayer_perceptron.py
    - function_transformer.py
    - k_means.py
    - id_op.py
    - array_feature_extractor.py
    - voting_classifier.py
    - gaussian_process.py
    - dict_vectoriser.py
    - one_vs_rest_classifier.py
    - nearest_neighbours.py
    - ordinal_encoder.py
    - label_encoder.py
    - normaliser.py
    - random_projection.py
    - sgd_classifier.py
    - k_bins_discretiser.py
    - ransac_regressor.py
    - _gp_kernels.py
    - one_hot_encoder.py
    - flatten_op.py
    - concat_op.py
    - ada_boost.py
    - multiply_op.py
    - tfidf_vectoriser.py
    - bagging.py
    - text_vectoriser.py
    - decomposition.py
    - gaussian_mixture.py
    - gradient_boosting.py
    - common.py
    - __init__.py
    - tfidf_transformer.py
    - cast_op.py
    - decision_tree.py
    - scaler_op.py
    - binariser.py
    - power_transformer.py
    - label_binariser.py
    - feature_selection.py
    - grid_search_cv.py
    - naive_bayes.py
    - linear_classifier.py
    - calibrated_classifier_cv.py
    - cross_decomposition.py
    - imputer_op.py
    - zip_map.py
    - random_forest.py
- tests_onnxmltools
  - test_xgboost_converters.py
  - test_lightgbm.py
- setup.cfg
- README.md
- tests
  - test_sklearn_count_vectorizer_converter.py
  - test_sklearn_feature_union.py
  - test_sklearn_one_vs_rest_classifier_converter.py
  - test_sklearn_grid_search_cv_converter.py
  - test_sklearn_svm_converters.py
  - datasets
    - small_titanic.csv
  - test_sklearn_dict_vectorizer_converter.py
  - test_sklearn_tfidf_vectorizer_converter_regex.py
  - test_sklearn_label_encoder_converter.py
  - test_supported_converters.py
  - test_sklearn_decision_tree_converters.py
  - test_sklearn_glm_classifier_converter.py
  - test_applied_functions.py
  - test_onnx_helper.py
  - test_algebra_double.py
  - test_sklearn_adaboost_converter.py
  - test_sklearn_tfidf_vectorizer_converter_pipeline.py
  - test_sklearn_concat.py
  - test_utils
    - utils_backend_onnxruntime.py
    - tests_helper.py
    - __init__.py
    - main.py
    - utils_backend.py
  - test_sklearn_tfidf_vectorizer_converter.py
  - test_sklearn_voting_classifier_converter.py
  - test_parsing_options.py
  - test_sklearn_pipeline.py
  - test_sklearn_bagging_converter.py
  - test_algebra_onnx_operators.py
  - test_sklearn_documentation.py
  - test_onnx_rare_helper.py
  - test_sklearn_count_vectorizer_converter_bug.py
  - test_sklearn_tfidf_vectorizer_converter_char.py
  - test_algebra_symbolic.py
  - test_sklearn_power_transformer.py
  - test_sklearn_tfidf_transformer_converter.py
  - test_other_converter_library_pipelines.py
  - test_sklearn_gaussian_mixture_converter.py
  - test_sklearn_mlp_converter.py
  - test_sklearn_tfidf_vectorizer_converter_dataset.py
  - test_algebra_onnx_operators_opset.py
  - test_sklearn_sgd_classifier_converter.py
  - test_shapes.py
  - test_sklearn_imputer_converter.py
  - test_sklearn_glm_regressor_converter.py
  - test_algebra_test_helper.py
  - test_sklearn_tfidf_transformer_converter_sparse.py
  - test_sklearn_k_means_converter.py
  - test_sklearn_k_bins_discretiser_converter.py
  - test_sklearn_one_hot_encoder_converter.py
  - test_algebra_onnx_operator_mixin_syntax.py
  - test_sklearn_naive_bayes_converter.py
  - test_op10.py
  - test_sklearn_gradient_boosting_converters.py
  - test_sklearn_gaussian_process.py
  - test_sklearn_calibrated_classifier_cv_converter.py
  - test_sklearn_array_feature_extractor.py
  - test_algebra_custom_model.py
  - test_sklearn_label_binariser_converter.py
  - test_sklearn_feature_selection_converters.py
  - test_algebra_onnx_operators_sub_estimator.py
  - test_sklearn_function_transformer_converter.py
  - test_sklearn_perceptron_converter.py
  - test_algebra_onnx_operators_sparse.py
  - test_algebra_converters.py
  - test_investigate.py
  - test_sklearn_normalizer_converter.py
  - bug.onnx
  - test_sklearn_binarizer_converter.py
  - test_sklearn_cast_transformer.py
  - test_sklearn_nearest_neighbour_converter.py
  - test_sklearn_random_forest_converters.py
  - test_sklearn_stacking.py
  - test_sklearn_random_projection.py
  - test_sklearn_scaler_converter.py
  - test_sklearn_passive_aggressive_classifier_converter.py
  - test_custom_transformer.py
  - test_topology_prune.py
  - test_sklearn_truncated_svd.py
  - test_algebra_onnx_doc.py
  - benchmark.py
  - test_scikit_pandas.py
  - test_sklearn_polynomial_features_converter.py
  - test_algebra_onnx_operators_scan.py
  - test_sklearn_voting_regressor_converter.py
  - test_sklearn_pipeline_within_pipeline.py
  - test_sklearn_custom_nmf.py
  - test_sklearn_pls_regression.py
  - test_sklearn_ordinal_encoder.py
  - test_sklearn_pca_converter.py
  - test_algebra_cascade.py
- requirements.txt
- .gitignore
- docs
  - exts
    - sphinx_skl2onnx_extension.py
  - supported.rst
  - examples
    - plot_pipeline_xgboost.py
    - plot_custom_parser.py
    - plot_gpr.py
    - plot_convert_zipmap.py
    - plot_nmf.py
    - plot_convert_model.py
    - plot_convert_decision_function.py
    - plot_pipeline.py
    - plot_convert_syntax.py
    - plot_onnx_operators.py
    - plot_complex_pipeline.py
    - plot_custom_parser_alternative.py
    - README.txt
    - plot_backend.py
    - plot_errors_onnxruntime.py
    - plot_intermediate_outputs.py
    - plot_benchmark_cdist.py
    - plot_black_op.py
    - plot_cast_transformer.py
    - plot_custom_model.py
    - plot_investigate_pipeline.py
    - plot_metadata.py
    - plot_tfidfvectorizer.py
    - plot_pipeline_lightgbm.py
    - plot_benchmark_pipeline.py
  - parameterized.rst
  - tutorial.rst
  - options.rst
  - api_summary.rst
  - tests
    - test_documentation_examples.py
  - index.rst
  - conf.py
  - pipeline.rst

Linux	Windows

Introduction

sklearn-onnx converts scikit-learn models to ONNX. Once in the ONNX format, you can use tools like ONNX Runtime for high performance scoring.

Documentation

Full documentation including tutorials is available at http://onnx.ai/sklearn-onnx/.

You may also find answers in existing issues or submit a new one.

Installation

You can install from PyPi:

pip install skl2onnx

Or you can install from the source with the latest changes.

pip install git+https://github.com/onnx/sklearn-onnx.git

If you install sklearn-onnx from its source code, you must set the environment variable ONNX_ML=1 before installing the onnx package.

Contribute

We welcome contributions in the form of feedback, ideas, or code.

License

MIT License