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[V1] Support sliding window attention (#9679)
Signed-off-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>
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@ -82,8 +82,10 @@ class FlashAttentionImpl(AttentionImpl):
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if alibi_slopes is not None:
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alibi_slopes = torch.tensor(alibi_slopes, dtype=torch.float32)
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self.alibi_slopes = alibi_slopes
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self.sliding_window = ((sliding_window, sliding_window)
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if sliding_window is not None else (-1, -1))
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if sliding_window is None:
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self.sliding_window = (-1, -1)
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else:
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self.sliding_window = (sliding_window - 1, 0)
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self.kv_cache_dtype = kv_cache_dtype
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if logits_soft_cap is None:
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# In flash-attn, setting logits_soft_cap as 0 means no soft cap.
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@ -93,12 +95,6 @@ class FlashAttentionImpl(AttentionImpl):
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assert self.num_heads % self.num_kv_heads == 0
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self.num_queries_per_kv = self.num_heads // self.num_kv_heads
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if sliding_window is not None:
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# NOTE(woosuk): flash-attn's sliding window does not work with
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# paged KV cache.
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raise ValueError(
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"Sliding window is not supported in FlashAttention.")
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support_head_sizes = FlashAttentionBackend.get_supported_head_sizes()
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if head_size not in support_head_sizes:
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raise ValueError(
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