Save ONNX model in file #4671
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Save ONNX model in file #4671
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orttraining/orttraining/test/python/orttraining_test_orttrainer_frontend.py
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* Add ORTTrainerOptions class for the new pytorch frontend (#4382) Add ORTTrainerOptions class and some placeholders * Add _ORTTrainerModelDesc to perform validation for model description (#4416) * Add Loss Scaler classes to the new frontend (#4306) * Add TrainStepInfo used on the new frontend API (#4256) * Add Optimizer classes to the new frontend (#4280) * Add LRScheduler implementation (#4357) * Add basic ORTTrainer API (#4435) This PR presents the public API for ORTTrainer for the short term development. It also validates and saves input parameters, which will be used in the next stages, such as building ONNX model, post processing the model and configuring the training session * Add opset_version into ORTTrainerOptions and change type of ORTTrainer.loss_fn (#4592) * Update ModelDescription and minor fix on ORTTrainer ctor (#4605) * Update ModelDescription and minor fix on ORTTrainer/ORTTrainerOptions This PR keeps the public API intact, but changes how model description is stored on the backend Currently, users creates a dict with two lists of tuples. One list called 'inputs' and each tuple has the following format tuple(name, shape). The second list is called 'outputs' and each tuple can be either tuple(name, shape) or tuple(name, shape, is_loss). With this PR, when this dict is passed in to ORTTrainer, it is fully validated as usual. However, tuples are internally replaced by namedtuples and all output tuples will have tuple(name, shape, is_loss) format instead of is_loss being optionally present. Additionally to that normalization in the internal representation (which eases coding), two internal methods were created to replace a namedtuple(name, shape) to namedtuple(name, shape, dtype) or namedtuple(name, shape, is_loss, dtype) dependeing whether the tuple is an input or output. This is necessary as ORTTRainer finds out data types of each input/output during model export to onnx. Finally, a minor fix was done on ORTTrainer. It could initialize ORTTrainerOptions incorrectly when options=None * Rename input name for test * Add ONNX Model Export to New Frontend (#4612) Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net> Co-authored-by: Thiago Crepaldi <[email protected]> * Create training session + minor improvements (#4668) Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net> * Save ONNX model in file (#4671) Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net> * Add eval step (#4674) Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net> * Add train_step (#4677) Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net> * Add LR Scheduler (#4694) Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net> Co-authored-by: Thiago Crepaldi <[email protected]> * Add deterministic compute tests (#4716) Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net> Co-authored-by: Thiago Crepaldi <[email protected]> * Add legacy vs experimental ORTTrainer accuracy comparison (#4727) Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net> Co-authored-by: Thiago Crepaldi <[email protected]> * Add Mixed precision/LossScaler + several fixes (#4739) Additionally to the mixed precision/loss scaler code, this PR includes: * Fix CUDA training * Add optimization_step into TrainStepInfo class * Refactor LRSCheduler to use optimization_step instead of step * Updated several default values at ORTTrainerOptions * Add initial Gradient Accumulation supported. Untested * Fix ONNX model post processing * Refactor unit tests * Add ONNX BERT example + minor fixes (#4757) * Fix training issue when passing ONNX file into ORTTrainer Co-authored-by: Thiago Crepaldi <[email protected]> Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net> * Add Dynamic Shape support (#4758) * Update DeepSpeed Zero Stage option to a separate option group (#4772) * Add support to fetches (#4777) * Add Gradient Accumulation Steps support (#4793) * Fix Dynamic Axes feature and add unit test (#4795) * Add frozen weights test (#4807) * Move new pytorch front-end to 'experimental' namespace (#4814) * Fix build Co-authored-by: Rayan-Krishnan <[email protected]> Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
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Must be merged after #4668
This PR: