Add support for torch>=2, torchvision>=0.15.2, onnx>=1.14 #483
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Looks like torch script compile was generating an OnnxPad operation with None passed to constant_value argument. This was causing a crash in the execution engine. This was uncovered after fixing a bug of handling prim::Constant Op correctly.
Little hack to pin ONNX ir_version to 8 if onnxruntime version is less than 1.15. This should get fixed soon with update of onnx package. See microsoft/onnxruntime#15874
It works but its slow.
Version update
Seems like ONNX has switched to using / characters in node names. This was causing issues with expression parsing because output port ids are used in expressions.
…nto fix_torch_v2
Keras model serialized in examples/TensorFlow/Keras/kr_N_model.h5 is failing to load on new TF version. Getting: TypeError: weight_decay is not a valid argument, kwargs should be empty for `optimizer_experimental.Optimizer`.
Keras model serialized in examples/TensorFlow/Keras/kr_N_model.h5 is failing to load. Getting: TypeError: weight_decay is not a valid argument, kwargs should be empty for `optimizer_experimental.Optimizer`. Can't reproduce locally, trying this suggested fix: https://stackoverflow.com/questions/74667876/typeerror-weight-decay-is-not-a-valid-argument-kwargs-should-be-empty-for-opt
Re-enable full testing of package on 3.10
Looks like scikit-learn wheels aren't available for 3.11. Getting compilation errors.
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Thanks @davidt0x, will try it out. |
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Miscellaneous changes to support latest versions of torch, torchvsion, and ONNX. This adds tests for more torchvision models. I also paired down the torchvision tests to speed things up. There are a couple marked as xfail that I still need to work on.
@pgleeson, I cleaned up some stuff in the CI as well.