Onnxcustom

Latest version: v0.4.293

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0.3.245

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* 34: Implements L1, L2 losses for partial training (2022-01-03)
* 31: Implements penalty when running the gradient (2022-01-03)
* 33: Implements more loss functions (2022-01-02)
* 30: Implements different learning rate strategies (2022-01-01)
* 26: Implements learning rate from neural network (2022-01-01)
* 29: Fixes 16, support weights while training (2021-12-30)
* 16: Support weights when training a model (2021-12-30)
* 28: Replaces OrtValue by C_OrtValue everywhere (2021-12-19)
* 24: Be more consistent with OrtValue, OrtDevice, C and python versions (2021-12-19)
* 27: Uses C_OrtDevice everywhere (2021-12-16)
* 15: Add example with TrainingAgent (error gradient outside) (2021-12-14)
* 25: Implements optimizers with forward, backward functionalities (2021-12-04)
* 21: Implements a mechanism that update training weights with SGDRegressor or MLPRegressor (2021-12-04)
* 23: Extend documentation (2021-12-01)
* 22: Move learning_rate logic in a separate class (2021-12-01)
* 20: Experiment markdown rendering (2021-12-01)
* 19: Implements training with forward, backward (2021-12-01)
* 18: Adds classes to train an ONNX gradient with TrainingAgent (2021-11-27)
* 17: Minimize the number of data copy while training a model (2021-11-26)
* 14: Optimize DataLoader to use iobinding (avoir copy) (2021-11-26)
* 13: Adds function plot_onnxs (2021-11-25)
* 12: Add more examples (2021-11-19)

0.2.122

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0.2.117

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* 11: Automates nvprof logs retrieval (2021-10-26)
* 10: Add parameter to evaluate the model on test data while training (2021-10-12)
* 9: Refactoring documentation (2021-10-08)
* 8: Add example to look into neural network on GPU (2021-10-07)
* 7: Refactoring (2021-10-04)
* 6: Add examples with orttraining (2021-10-04)
* 5: Fix examples, update documentation (2021-09-28)
* 4: Complex scenarios (2021-07-12)
* 3: Replaces OnnxSubOperator by OnnxSubEstimator (2021-03-31)

0.1.0

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* 1: Add an example on black list, while list of operators. (2020-07-09)

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