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| attention = attention.masked_fill(torch.all(causal_mask, dim=-1, keepdim=True), 0.0) | ||
| # Some rows might be completely masked out so we fill them with zero instead of NaN | ||
| if window_size[0] >= 0 or window_size[1] >= 0: | ||
| attention = attention.masked_fill(torch.all(local_mask, dim=-1, keepdim=True), 0.0) |
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tianleiwu
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Nov 16, 2023
tianleiwu
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Nov 16, 2023
yufenglee
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Nov 16, 2023
kleiti
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Mar 22, 2024
### Description Implement preliminary version of local (sliding window) attention. Currently only supported by Flash Attention (sm >= 80, Linux). Currently only supports sliding attention with a large cached kv. ### Motivation and Context This change enables to run Mistral and other models which use sliding window attention.
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Description
Implement preliminary version of local (sliding window) attention. Currently only supported by Flash Attention (sm >= 80, Linux). Currently only supports sliding attention with a large cached kv.
Motivation and Context
This change enables to run Mistral and other models which use sliding window attention.