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make test_eager_matches_sdpa_inference less flaky - #34512
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ydshieh
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Oct 30, 2024
ydshieh
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Oct 30, 2024
ydshieh
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Oct 30, 2024
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gante
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Oct 31, 2024
ArthurZucker
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Oct 31, 2024
| if model.get_output_embeddings() is None: | ||
| self.skipTest("DoLa is not supported for models that don't have output embeddings") | ||
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| logits_processor_kwargs = self._get_logits_processor_kwargs(do_sample=True, config=model.config) |
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do sample is random no?
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I am using the same value as in generation_kwargs = {...} a few line below.
Yes it is random but this method is test_...._sample so makes sense.
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* try * try * try * try * try * try * update * update * update * update * update * update * update --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
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What does this PR do?
With
torch.bfloat16the numerical difference/instability occurs quite often, especially with multiple hidden layers.This PR first changes
test_eager_matches_sdpa_inferenceto create models with only 1 hidden layer.number of failures per 500 runs
Then it relaxes the condition a bit: only checks 80% of the sequences. If the results match on those 80%, the test pass.
This makes the test much less flaky. On 500 runs, it pass (for llama, mistral, idefics2 and Llava)
Finally, change the image size of
llavaandVipLlavafrom30to8so the sequence length is much smaller and avoid numerical issues.