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Fix Mega chunking error when using decoder-only model #25765

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merged 3 commits into from
Sep 5, 2023
Merged

Fix Mega chunking error when using decoder-only model #25765

merged 3 commits into from
Sep 5, 2023

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tanaymeh
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@tanaymeh tanaymeh commented Aug 25, 2023 •
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What does this PR do?

This PR aims to fix the error caused by MegaModel when the is_decoder setting is used in conjunction with use_chunking and chunk_size settings.

The error is described in detail here.

Fixes #23331

Who can review?

@ArthurZucker

@tanaymeh tanaymeh changed the title Fix Mega chunking error when using decoder-only model. Fix Mega chunking error when using decoder-only model Aug 26, 2023
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Hey! Feel free to ping me when the PR is ready for review 😉

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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint.

@tanaymeh tanaymeh marked this pull request as ready for review August 28, 2023 10:10
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@ArthurZucker You may review it now!

ArthurZucker
ArthurZucker reviewed Aug 28, 2023
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Nice! Can you add a test in the testing suite? This way we can make sure the chunking mode is properly tested!

@tanaymeh
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tanaymeh commented Aug 28, 2023 •
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Will do. Two questions regarding this:

  1. For the test of chunking, I should only check the expected sizes of output or something else?
  2. Conceptually, do you see any troubles with this solution in its current state? I am a little suspicious because of how simple the solution was 😅

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  1. Yes you could check expected sizes on a smaller model (using the small configs)
  2. I don't really see a problem since the attention mask created use the newly defined sequence length, and the code was already very clean so probably juste a typo!

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tanaymeh commented Sep 4, 2023 •
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Thanks for confirming @ArthurZucker. I have added a test that checks here if the attentions returned in the CausalLMOutputWithCrossAttentions have their last dimension (shape[-1]), which is supposed to be sequence_length is equal to the chunk_size or not.

If the checks I added in modeling_mega.py are correct, it will use chunk_size instead of the actual sequence_length.

Is this correct, or shall I make any changes?

Update: The tests are failing because of an error in Wav2Vec2 model, here: test_modeling_wav2vec2.py::Wav2Vec2RobustModelTest::test_model_for_pretraining

A Github Pull should fix it.

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ArthurZucker approved these changes Sep 4, 2023
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This is nice! Thanks for the long due fix 😉

tests/models/mega/test_modeling_mega.py Outdated Show resolved Hide resolved
tests/models/mega/test_modeling_mega.py Outdated Show resolved Hide resolved
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tanaymeh commented Sep 5, 2023 •
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Added your suggested changes @ArthurZucker! With input_mask, the mega tests now pass.

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Perfect! If you can just rebase on main to make sure the CIs are green?

@tanaymeh tanaymeh force-pushed the fix_mega_chunking_errors branch from ae262e5 to aa2ff48 Compare September 5, 2023 18:49
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tanaymeh commented Sep 5, 2023

Perfect! If you can just rebase on main to make sure the CIs are green?

Done @ArthurZucker!

@ArthurZucker ArthurZucker merged commit b8def68 into huggingface:main Sep 5, 2023
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Congrats on the PR 🚀 thanks for fixing!

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tanaymeh commented Sep 5, 2023

Thanks a lot for helping @ArthurZucker!

parambharat pushed a commit to parambharat/transformers that referenced this pull request Sep 26, 2023
@tanaymeh @parambharat
Fix Mega chunking error when using decoder-only model (huggingface#25765
e6f5eea 
)

* add: potential fix to mega chunking in decoder only model bug

* add: decoder with chunking test

* add: input_mask passed with input_ids
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RuntimeError: The size of tensor a (16) must match the size of tensor b (16000) at non-singleton dimension 2
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