Keep activations in bidirectional LSTM (fixes: https://github.com/onnx/tensorflow-onnx/issues/2211) #2234
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MaximeChurin
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Thanks for your contributions. Yes, please follow the way in bigru_rewriter.py to read activations from those LSTMs. |
MaximeChurin
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thanks@fatcat-z |
The CI failures are caused by tf 1.15. For compatibility, we might need to check if they are None before we call decode() method. |
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good catch @fatcat-z , I made the change and the tests passed but now it differs a bit from the bigru implem. If you have any suggestions please make it via GitHub code review suggestion |
fatcat-z
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Oct 12, 2023
* Support ResizeArea op. Signed-off-by: Jay Zhang <jiz@microsoft.com> --------- Signed-off-by: Jay Zhang <jiz@microsoft.com> Signed-off-by: Me <me@example.com>
Signed-off-by: Me <me@example.com>
Signed-off-by: Me <me@example.com>
Signed-off-by: Me <me@example.com>
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fatcat-z
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The forward and backward LSTMs have their correct activations but as soon as we rewrite it to a bidirectional this attribute is skipped and we get the default activations.
I am not sure how to write it in the
rewriterfile, you have something similar in the bigru so let me know if you prefer the syntax with decode and comprehension list