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Use normal ComfyUI attention in ACE-Steps model #8023

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Merged
comfyanonymous merged 2 commits into from
May 9, 2025
Merged

Use normal ComfyUI attention in ACE-Steps model #8023

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5284548
Use normal ComfyUI attention in ACE-Steps model
blepping May 9, 2025
feb3d75
Let optimized_attention handle output reshape for ACE
blepping May 9, 2025
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15 changes: 4 additions & 11 deletions comfy/ldm/ace/attention.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@
from torch import nn

import comfy.model_management
from comfy.ldm.modules.attention import optimized_attention

class Attention(nn.Module):
def __init__(
Expand Down Expand Up @@ -326,10 +327,6 @@ class CustomerAttnProcessor2_0:
Processor for implementing scaled dot-product attention (enabled by default if you're using PyTorch 2.0).
"""

def __init__(self):
if not hasattr(F, "scaled_dot_product_attention"):
raise ImportError("AttnProcessor2_0 requires PyTorch 2.0, to use it, please upgrade PyTorch to 2.0.")

def apply_rotary_emb(
self,
x: torch.Tensor,
Expand Down Expand Up @@ -435,13 +432,9 @@ def __call__(
attention_mask = attention_mask.view(batch_size, attn.heads, -1, attention_mask.shape[-1])

# the output of sdp = (batch, num_heads, seq_len, head_dim)
# TODO: add support for attn.scale when we move to Torch 2.1
hidden_states = F.scaled_dot_product_attention(
query, key, value, attn_mask=attention_mask, dropout_p=0.0, is_causal=False
)

hidden_states = hidden_states.transpose(1, 2).reshape(batch_size, -1, attn.heads * head_dim)
hidden_states = hidden_states.to(query.dtype)
hidden_states = optimized_attention(
query, key, value, heads=query.shape[1], mask=attention_mask, skip_reshape=True,
).to(query.dtype)

# linear proj
hidden_states = attn.to_out[0](hidden_states)
Expand Down