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Fix mutable input parameter.

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Talmaj Marinc 2026-04-10 15:14:42 +02:00
parent 63739c324e
commit 955ce480e2
1 changed files with 9 additions and 3 deletions
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12
comfy/ldm/cogvideo/model.py
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@ -260,7 +260,9 @@ class CogVideoXBlock(nn.Module):
self.ff_proj = operations.Linear(dim, inner_dim, bias=ff_bias, device=device, dtype=dtype) self.ff_proj = operations.Linear(dim, inner_dim, bias=ff_bias, device=device, dtype=dtype)
self.ff_out = operations.Linear(inner_dim, dim, bias=ff_bias, device=device, dtype=dtype) self.ff_out = operations.Linear(inner_dim, dim, bias=ff_bias, device=device, dtype=dtype)
def forward(self, hidden_states, encoder_hidden_states, temb, image_rotary_emb=None, transformer_options={}): def forward(self, hidden_states, encoder_hidden_states, temb, image_rotary_emb=None, transformer_options=None):
if transformer_options is None:
transformer_options = {}
text_seq_length = encoder_hidden_states.size(1) text_seq_length = encoder_hidden_states.size(1)
# Norm & modulate # Norm & modulate
@ -428,14 +430,18 @@ class CogVideoXTransformer3DModel(nn.Module):
self.temporal_interpolation_scale = temporal_interpolation_scale self.temporal_interpolation_scale = temporal_interpolation_scale
self.temporal_compression_ratio = temporal_compression_ratio self.temporal_compression_ratio = temporal_compression_ratio
def forward(self, x, timestep, context, ofs=None, transformer_options={}, **kwargs): def forward(self, x, timestep, context, ofs=None, transformer_options=None, **kwargs):
if transformer_options is None:
transformer_options = {}
return comfy.patcher_extension.WrapperExecutor.new_class_executor( return comfy.patcher_extension.WrapperExecutor.new_class_executor(
self._forward, self._forward,
self, self,
comfy.patcher_extension.get_all_wrappers(comfy.patcher_extension.WrappersMP.DIFFUSION_MODEL, transformer_options) comfy.patcher_extension.get_all_wrappers(comfy.patcher_extension.WrappersMP.DIFFUSION_MODEL, transformer_options)
).execute(x, timestep, context, ofs, transformer_options, **kwargs) ).execute(x, timestep, context, ofs, transformer_options, **kwargs)
def _forward(self, x, timestep, context, ofs=None, transformer_options={}, **kwargs): def _forward(self, x, timestep, context, ofs=None, transformer_options=None, **kwargs):
if transformer_options is None:
transformer_options = {}
# ComfyUI passes [B, C, T, H, W] # ComfyUI passes [B, C, T, H, W]
batch_size, channels, t, h, w = x.shape batch_size, channels, t, h, w = x.shape