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Fix some OOM issues with split and sub quad attention.
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@ -222,9 +222,14 @@ def attention_split(q, k, v, heads, mask=None):
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mem_free_total = model_management.get_free_memory(q.device)
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if _ATTN_PRECISION =="fp32":
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element_size = 4
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else:
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element_size = q.element_size()
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gb = 1024 ** 3
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tensor_size = q.shape[0] * q.shape[1] * k.shape[1] * q.element_size()
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modifier = 3 if q.element_size() == 2 else 2.5
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tensor_size = q.shape[0] * q.shape[1] * k.shape[1] * element_size
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modifier = 3 if element_size == 2 else 2.5
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mem_required = tensor_size * modifier
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steps = 1
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@ -83,7 +83,8 @@ def _summarize_chunk(
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)
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max_score, _ = torch.max(attn_weights, -1, keepdim=True)
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max_score = max_score.detach()
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torch.exp(attn_weights - max_score, out=attn_weights)
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attn_weights -= max_score
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torch.exp(attn_weights, out=attn_weights)
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exp_weights = attn_weights.to(value.dtype)
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exp_values = torch.bmm(exp_weights, value)
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max_score = max_score.squeeze(-1)
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