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final changes

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This commit is contained in:
Yousef Rafat 2025-10-13 19:28:54 +03:00
parent 4908e7412e
commit 4653b9008d
11 changed files with 73 additions and 73 deletions
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2
comfy/clip_vision.py
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@ -19,6 +19,8 @@ class Output:
def clip_preprocess(image, size=224, mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711], crop=True, resize_mode="bicubic"):
image = image[:, :, :, :3] if image.shape[3] > 3 else image
if image.dtype == torch.uint8:
image = image.float() / 255.0
mean = torch.tensor(mean, device=image.device, dtype=image.dtype)
std = torch.tensor(std, device=image.device, dtype=image.dtype)
image = image.movedim(-1, 1)

2
comfy/ldm/hunyuan_foley/model.py
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@ -885,6 +885,8 @@ class HunyuanVideoFoley(nn.Module):
clip_feat, sync_feat, cond = torch.cat([uncond_1, clip_feat]), torch.cat([uncond_2, sync_feat]), torch.cat([cond_neg, cond_pos])
clip_feat = clip_feat.view(2, -1, 768)
self.conditions = (clip_feat, sync_feat, cond)
else:
clip_feat, sync_feat, cond = self.conditions

1
comfy/ldm/hunyuan_foley/syncformer.py
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@ -957,6 +957,7 @@ class Synchformer(nn.Module):
)
def forward(self, vis):
vis = vis.to(next(self.parameters()).dtype)
vis = vis.permute(0, 1, 3, 2, 4, 5) # (B, S, C, Tv, H, W)
vis = self.vfeat_extractor(vis)
return vis

4
comfy/ldm/hunyuan_foley/vae.py
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@ -223,6 +223,7 @@ class FoleyVae(torch.nn.Module):
return self.synchformer(x)
def video_encoding(self, video, step):
video = video.to(torch.uint8)
video = torch.stack([self.syncformer_preprocess(t) for t in video])
t, c, h, w = video.shape
@ -237,8 +238,9 @@ class FoleyVae(torch.nn.Module):
data = video.as_strided(
size=(nseg, seg_len, c, h, w),
stride=(stride_t * step, stride_t, stride_c, stride_h, stride_w),
)
).contiguous()
data = data.unsqueeze(0) # b
data = rearrange(data, "b s t c h w -> (b s) 1 t c h w")
data = data.float()
return data, nseg, lambda x: rearrange(x, "(b s) 1 t d -> b (s t) d", b=1)

25
comfy/ldm/modules/attention.py
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@ -1164,26 +1164,17 @@ class MultiheadAttentionComfyv(nn.Module):
error_msgs,
)
def forward(self, src, k = None, v = None, attn_mask = None, key_padding_mask = None):
def forward(self, src, k=None, v=None, attn_mask=None, key_padding_mask=None):
self._q_proj, self._k_proj, self._v_proj = [
t.to(src.device).to(src.dtype)
for t in (self._q_proj, self._k_proj, self._v_proj)
]
self._q_proj, self._k_proj, self._v_proj = [t.to(src.device).to(src.dtype) for t in (self._q_proj, self._k_proj, self._v_proj)]
q = self._q_proj(src)
if k is None:
k = self._k_proj(src)
if v is None:
v = self._v_proj(src)
k, v = k.to(src.device).to(src.dtype), v.to(src.device).to(src.dtype)
k = self._k_proj(src if k is None else k.to(src.device).to(src.dtype))
v = self._v_proj(src if v is None else v.to(src.device).to(src.dtype))
if k is v:
if q is k:
q = k = v = q.transpose(1, 0)
else:
q, k = (x.transpose(1, 0) for x in (q, k))
v = k
else:
q, k, v = (x.transpose(1, 0) for x in (q, k, v))
output = optimized_attention(q, k, v, self.num_heads, mask = attn_mask)
output = optimized_attention(q, k, v, self.num_heads, mask=attn_mask)
return self.out_proj(output)
# comfyui implementation of nn.TransformerEncoderLayer

6
comfy_extras/nodes_video.py
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@ -94,13 +94,15 @@ class EncodeVideo(io.ComfyNode):
chunk = chunk.to(model_dtype)
if hasattr(vae, "encode"):
try:
if chunk.ndim > 5:
raise ValueError("chunk.ndim > 5")
chunk = chunk.movedim(1, -1)
out = vae.encode(chunk)
except:
except Exception:
out = model.encode(chunk)
else:
chunk = chunk.movedim(1, -1)
out = vae.encode_image(chunk, crop=False, resize_mode="bilinear")
out = vae.encode_image(chunk.to(torch.uint8), crop=False, resize_mode="bilinear")
out = out["image_embeds"]
out_cpu = out.cpu()