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Update VisionSdpaAttention to support memory efficient backend. (#27)

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- Update VisionSdpaAttention to support memory efficient backend. (fc8b0b11b92c381639e616506cca574f1b05af09)


Co-authored-by: warren wang <warrenwjk@users.noreply.huggingface.co>
This commit is contained in:
Cherrytest 2025-09-13 14:38:43 +00:00
parent 2464a795a5
commit 1f0c298e18
1 changed files with 14 additions and 5 deletions
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modeling_dots_vision.py
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@ -274,12 +274,21 @@ class VisionSdpaAttention(nn.Module):
for i in range(1, len(cu_seqlens)): for i in range(1, len(cu_seqlens)):
attention_mask[..., cu_seqlens[i - 1]: cu_seqlens[i], cu_seqlens[i - 1]: cu_seqlens[i]] = True attention_mask[..., cu_seqlens[i - 1]: cu_seqlens[i], cu_seqlens[i - 1]: cu_seqlens[i]] = True
q = q.transpose(0, 1) # Convert q, k, v to 4D to enable : (1, num_heads, seq_length, head_dim)
k = k.transpose(0, 1) q = q.transpose(0, 1).unsqueeze(0) # (1, num_heads, seq_length, head_dim)
v = v.transpose(0, 1) k = k.transpose(0, 1).unsqueeze(0)
v = v.transpose(0, 1).unsqueeze(0)
attn_output = F.scaled_dot_product_attention(q, k, v, attention_mask, dropout_p=0.0) # See: https://github.com/pytorch/pytorch/issues/127523
attn_output = attn_output.transpose(0, 1) if attention_mask.stride(-1) != 1:
attention_mask = torch.empty_like(attention_mask, memory_format=torch.contiguous_format).copy_(attention_mask)
# use memory efficient backend
from torch.nn.attention import SDPBackend, sdpa_kernel
with sdpa_kernel(SDPBackend.EFFICIENT_ATTENTION):
attn_output = F.scaled_dot_product_attention(q, k, v, attention_mask, dropout_p=0.0)
attn_output = attn_output.squeeze(0).transpose(0, 1) # (seq_length, num_heads, head_dim)
attn_output = attn_output.reshape(seq_length, -1) attn_output = attn_output.reshape(seq_length, -1)
attn_output = self.proj(attn_output) attn_output = self.proj(attn_output)