Fix SDPA dispatch & make SDPA CI compatible with torch<2.1.1 #27940
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LysandreJik
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Dec 11, 2023
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Ok, looks good, would like @ArthurZucker to take a quick look before merging. Will cherry-pick this for the release.
| @@ -1244,6 +1244,7 @@ def _autoset_attn_implementation( | |||
| # Here we use config._attn_implementation_internal to check whether the attention implementation was explicitely set by the user. | |||
| # The property `PretrainedConfig._attn_implementation` is never `None`, for backward compatibility (always fall back on "eager"). | |||
| # The `hasattr` here is used as some Transformers tests for some reason do not call PretrainedConfig __init__ (e.g. test_no_super_init_config_and_model) | |||
| requested_attn_implementation = None | |||
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Should this be "default" instead?
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No, the idea here is to check whether the user passed attn_implementation="eager", attn_implementation="sdpa" or attn_implementation="sdpa" explicitly when loading the model from from_pretrained or from_config.
In case attn_implementation is explicitly set, we hard error if a dependency is missing (torch>=2.1.1, model does not support SDPA), otherwise we smoothly fall back on eager.
ArthurZucker
approved these changes
Dec 11, 2023
| config = cls._check_and_enable_sdpa(config, hard_check_only=hard_check_only) | ||
| elif not hard_check_only: | ||
| config = cls._check_and_enable_sdpa( | ||
| config, hard_check_only=False if requested_attn_implementation is None else True |
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As per title.
On torch==2.0.1, these do pass
On torch==2.1.1, these do pass (#26572 (comment))
There was a bug where even though we manually request
attn_implementation="eager", we would still go into the SDPA controlflow and hard check that the requirements are fine. Which is not what we want.