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daquexian avatar daquexian commented on August 25, 2024 1

I have merged #42 and released v0.2.6. could you please try again with this latest version?

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daquexian avatar daquexian commented on August 25, 2024

Thanks for your issue!

What are "split_predict" and "lift_lexical_references" used for? I thought they are legacy passes and only useful for the caffe2 backend. Please correct me if I am wrong.

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BowenBao avatar BowenBao commented on August 25, 2024

Thanks for your issue!

What are "split_predict" and "lift_lexical_references" used for? I thought they are legacy passes and only useful for the caffe2 backend. Please correct me if I am wrong.

Hi @daquexian , yes this is a case from Caffe2 backend test. The background is that we are updating ONNX version under PyTorch, and was trying the onnxoptimizer module due to the dependency of Caffe2 on onnx.optimize. This error came up for these tests

TestCaffe2Backend_opset9::test_dynamic_loop
TestCaffe2Backend_opset9::test_loop
TestCaffe2Backend_opset9::test_nested_loops

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daquexian avatar daquexian commented on August 25, 2024

Is caffe2 backend still used? If needed I will take a look at it. Another choice is dropping the support for "lift_lexical_references" and "split_predict" passes if the only user -- caffe2 backend is deprecated.

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neginraoof avatar neginraoof commented on August 25, 2024

Hi @daquexian
Caffe2 backend is not updated recently, but the existing code and tests for older opsets are maintained as part of the repo.
This issue looks like a bug in the split_init_and_predict logic where nodes that are not in the predic net get deleted.

This is the CI for updating ONNX (currently failing): pytorch/pytorch#55889

Could you please take a look?
Thanks

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neginraoof avatar neginraoof commented on August 25, 2024

cc @gramalingam and @askhade
FYI, this issue is currently blocking the use of onnx/optimizer for us in: pytorch/pytorch#55889

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daquexian avatar daquexian commented on August 25, 2024

@BowenBao @neginraoof I'll take a look today tomorrow 😂

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neginraoof avatar neginraoof commented on August 25, 2024

@daquexian
Thanks for your help. This is currently needed for ONNX in PyTorch. Do you think we can help with anything here?
I can prepare a PR for split pass.

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daquexian avatar daquexian commented on August 25, 2024

I can prepare a PR for split pass.

Could you please submit a pr if applicable? I'm quite busy these days. 🤣 I'll take a look at this problem but it will help a lot if you also submit a pr

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neginraoof avatar neginraoof commented on August 25, 2024

@daquexian This is high priority for us as mentioned. Could you please take a look at the PR: #41

Thanks.

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neginraoof avatar neginraoof commented on August 25, 2024

I created a duplicate to check CI failures: #42

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neginraoof avatar neginraoof commented on August 25, 2024

@daquexian Also, would you please help us with the CI workflow issue?

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