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Thanks ! I don"t see why sliding window attention shouldn't be supported with SDPA because the only difference vs the eager attention implementation is on the attention mask. Passing arbitrary attention masks in SDPA should be supported without any problem IMO

I have the same problem here, why sdpa not support window attention? Is there any problems not been solved? @ArthurZucker

@ehuaa the way the window attention is implemented in Mistral original code base is by changing the attention mask to a "more custom" attention mask to not attend to tokens that are before sliding_windows. Check out more by looking into the details of this method:

@ehuaa the way the window attention is implemented in Mistral original code base is by changing the attention mask to a "more custom" attention mask to not attend to tokens that are before sliding_windows. Check out more by looking into the details of this method:

transformers/src/transformers/modeling_attn_mask_utils.py

Line 145 in d90acc1

def _make_causal_mask(

The point that I tried to convey is that passing that attention mask is supported I think in SDPA so you can implicitly get SDPA + sliding window attention by just passing that correct attention mask. Let me know if this makes sense to you!

@younesbelkada Thank you for your quick reply! Your solution above can pass a custom mask to sdpa, and i think this way is the same as passing sliding_window param to this function.
https://github.com/huggingface/transformers/blob/main/src/transformers/models/mistral/modeling_mistral.py#L1006-L1023