History#
current - 2022-05-30 - 0.00Mb#
issue 64: Fixes bug introduced by recent updates (2022-05-29)
issue 62: Adds a notebook about convolution (2022-05-27)
issue 63: Add GraphProto to the documentation (2022-04-28)
issue 60: Extends notebook coverage (2022-03-07)
issue 59: Removes unnecessary exceptions (2022-03-06)
issue 58: Uses new API to retrieve gradient for a model (2022-03-03)
issue 57: Fix opset for ai.onnx.ml in examples after updating to onnx==1.11 (2022-02-22)
issue 56: Renames Z into Y_grad in loss functions returning grad (2022-02-14)
issue 55: Removes unncessary nodes in onnx_derivative (2022-02-14)
issue 54: Implements a function which returns the gradient (2022-02-13)
0.4.293 - 2022-02-11 - 0.07Mb#
0.4.274 - 2022-01-29 - 0.06Mb#
issue 48: Checks gradients are identical to scikit-learn for neural networks (2022-01-25)
issue 47: Compare gradient values with scikit-learn (2022-01-25)
issue 45: Adds an example about classification (2022-01-23)
issue 44: Uses bind_ortvalue_input instead of bind_input to be faster (2022-01-23)
issue 32: Implements classificiation loss (2022-01-23)
issue 43: Fixes the training of a binary classifier with weights (2022-01-22)
issue 42: Implements binary log loss for first API of orttraining (2022-01-22)
issue 41: Refactors to improve profiling analysis (fix penalty, export onnx graphs) (2022-01-15)
issue 40: Improves training fwbw with caching. (2022-01-14)
issue 37: Improves performance of caching (2022-01-09)
issue 36: Makes sure all plt.show() have been disabled in examples (2022-01-04)
issue 35: Reduces the number of calls to bind_ortvalue (2022-01-04)
0.3.245 - 2022-01-03 - 0.06Mb#
issue 34: Implements L1, L2 losses for partial training (2022-01-03)
issue 31: Implements penalty when running the gradient (2022-01-03)
issue 33: Implements more loss functions (2022-01-02)
issue 30: Implements different learning rate strategies (2022-01-01)
issue 26: Implements learning rate from neural network (2022-01-01)
issue 29: Fixes #16, support weights while training (2021-12-30)
issue 16: Support weights when training a model (2021-12-30)
issue 28: Replaces OrtValue by C_OrtValue everywhere (2021-12-19)
issue 24: Be more consistent with OrtValue, OrtDevice, C and python versions (2021-12-19)
issue 27: Uses C_OrtDevice everywhere (2021-12-16)
issue 15: Add example with TrainingAgent (error gradient outside) (2021-12-14)
issue 25: Implements optimizers with forward, backward functionalities (2021-12-04)
issue 21: Implements a mechanism that update training weights with SGDRegressor or MLPRegressor (2021-12-04)
issue 23: Extend documentation (2021-12-01)
issue 22: Move learning_rate logic in a separate class (2021-12-01)
issue 20: Experiment markdown rendering (2021-12-01)
issue 19: Implements training with forward, backward (2021-12-01)
issue 18: Adds classes to train an ONNX gradient with TrainingAgent (2021-11-27)
issue 17: Minimize the number of data copy while training a model (2021-11-26)
issue 14: Optimize DataLoader to use iobinding (avoir copy) (2021-11-26)
issue 13: Adds function plot_onnxs (2021-11-25)
issue 12: Add more examples (2021-11-19)
0.2.122 - 2021-10-31 - 0.03Mb#
0.2.117 - 2021-10-26 - 0.03Mb#
issue 11: Automates nvprof logs retrieval (2021-10-26)
issue 10: Add parameter to evaluate the model on test data while training (2021-10-12)
issue 9: Refactoring documentation (2021-10-08)
issue 8: Add example to look into neural network on GPU (2021-10-07)
issue 7: Refactoring (2021-10-04)
issue 6: Add examples with orttraining (2021-10-04)
issue 5: Fix examples, update documentation (2021-09-28)
issue 4: Complex scenarios (2021-07-12)
issue 3: Replaces OnnxSubOperator by OnnxSubEstimator (2021-03-31)
0.1.0 - 2020-07-09 - 0.04Mb#
issue 1: Add an example on black list, while list of operators. (2020-07-09)