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RuntimeError: GRU with linear_before_reset is not supported in Tensorflow. #853
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This is a known limitation in conversion using Tensorflow APIs. The support status for onnx-tf 1.7 can be found here, https://github.com/onnx/onnx-tensorflow/blob/master/doc/support_status_v1_7_0.md |
Ok Are there any alternatives to bypass this error |
Change the GRU linear_before_reset to 0 or remove the attribute in onnx model. Contribution to support of this attribute is highly welcome! |
@chinhuang007, force the attribure linear_before_reset to 0 seems to cause some dimension error, is there any plan to support this feature, I saw tf.keras.layers.GRU has the argument reset_after=false, but I failed after trying. |
any fix now? i still get the same error |
I had the same problem |
1 similar comment
I had the same problem |
I didn't experience any change in dimensions when forcing linear_before_reset to 0, but the values are definitely incorrect. It looks like there's a PR from years ago that solved this issue but was left to the wayside while waiting to update to tf2.0: #452 would love to see it updated as needed and implemented as it appears to be the only thing blocking pytorch -> tf conversion with GRUs at this point |
@ALL, did anyone find a way to resolve this issue? Any suggestions would help greatly. Thanks |
I think I have implemented it, but I don't know if it works correctly because I don't have enough ONNX files for testing. It's a topic that's over a year old, so no one will be interested in it. https://github.com/PINTO0309/onnx2tf/blob/main/onnx2tf/ops/GRU.py |
Please find the error log:
ONNX Version used - 1.8
ONNX-TF Version Used - 1.7
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