History

current - 2019-09-15 - 0.00Mb

  • issue57: ONNX: handles dataframe when converting a model (2019-09-15)

  • issue56: ONNX: implements cdist operator (2019-09-12)

  • issue54: ONNX: fix summary, it produces multiple row when model are different when opset is different (2019-09-12)

  • issue51: ONNX: measure the time performance obtained by using optimization (2019-09-11)

  • issue52: ONNC-cli: add a command line to optimize an onnx model (2019-09-10)

  • issue49: ONNX optimization: remove redundant subparts of a graph (2019-09-09)

  • issue48: ONNX optimization: reduce the number of Identity nodes (2019-09-09)

  • issue47: Implements statistics on onnx graph and sklearn models, add them to the documentation (2019-09-06)

  • issue46: Implements KNearestNeibhorsRegressor supporting batch mode (ONNX) (2019-08-31)

  • issue45: KNearestNeighborsRegressor (2019-08-30)

  • issue44: Add an example to look into the performance of every node for a particular dataset (2019-08-30)

  • issue43: LGBMClassifier has wrong shape (2019-08-29)

0.2.452 - 2019-08-28 - 0.13Mb

  • issue42: Adds a graph which visually summarize the validating benchmark (ONNX). (2019-08-27)

  • issue41: Enables to test multiple number of features at the same time (ONNX) (2019-08-27)

  • issue40: Add a parameter to change the number of featuress when validating a model (ONNX). (2019-08-26)

  • issue39: Add a parameter to dump all models even if they don’t produce errors when being validated (ONNX) (2019-08-26)

  • issue24: support double for TreeEnsembleClassifier (python runtime ONNX) (2019-08-23)

  • issue38: See issue on onnxmltools. https://github.com/onnx/onnxmltools/issues/321 (2019-08-19)

  • issue35: Supports parameter time_kwargs in the command line (ONNX) (2019-08-09)

  • issue34: Add intervals when measuring time ratios between scikit-learn and onnx (ONNX) (2019-08-09)

  • issue31: Implements shape inference for the python runtime (ONNX) (2019-08-06)

  • issue15: Tells operator if the execution can be done inplace for unary operators (ONNX). (2019-08-06)

  • issue27: Bug fix (2019-08-02)

  • issue23: support double for TreeEnsembleRegressor (python runtime ONNX) (2019-08-02)

0.2.363 - 2019-08-01 - 0.11Mb

  • issue26: Tests all converters in separate processeses to make it easier to catch crashes (2019-08-01)

  • issue25: Ensures operator clip returns an array of the same type (ONNX Python Runtime) (2019-07-30)

  • issue22: Implements a function to shake an ONNX model and test float32 conversion (2019-07-28)

  • issue21: Add customized converters (2019-07-28)

  • issue20: Enables support for TreeEnsemble operators in python runtime (ONNX). (2019-07-28)

  • issue19: Enables support for SVM operators in python runtime (ONNX). (2019-07-28)

  • issue16: fix documentation, visual graph are not being rendered in notebooks (2019-07-23)

  • issue18: implements python runtime for SVM (2019-07-20)

0.2.272 - 2019-07-15 - 0.09Mb

  • issue17: add a mechanism to use ONNX with double computation (2019-07-15)

  • issue13: add automated benchmark of every scikit-learn operator in the documentation (2019-07-05)

  • issue12: implements a way to measure time for each node of the ONNX graph (2019-07-05)

  • issue11: implements a better ZipMap node based on dedicated container (2019-07-05)

  • issue8: implements runtime for decision tree (2019-07-05)

  • issue7: implement python runtime for scaler, pca, knn, kmeans (2019-07-05)

  • issue10: implements full runtime with onnxruntime not node by node (2019-06-16)

  • issue9: implements a onnxruntime runtime (2019-06-16)

  • issue6: first draft of a python runtime for onnx (2019-06-15)

  • issue5: change style highlight-ipython3 (2018-01-05)

0.1.11 - 2017-12-04 - 0.03Mb