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Merge branch 'comfyanonymous:master' into master

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patientx 2025-11-13 00:55:19 +03:00 committed by GitHub
commit 00609a5102
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3 changed files with 16 additions and 12 deletions
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20
comfy/ldm/qwen_image/model.py
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@ -236,10 +236,10 @@ class QwenImageTransformerBlock(nn.Module):
img_mod1, img_mod2 = img_mod_params.chunk(2, dim=-1)
txt_mod1, txt_mod2 = txt_mod_params.chunk(2, dim=-1)
img_normed = self.img_norm1(hidden_states)
img_modulated, img_gate1 = self._modulate(img_normed, img_mod1)
txt_normed = self.txt_norm1(encoder_hidden_states)
txt_modulated, txt_gate1 = self._modulate(txt_normed, txt_mod1)
img_modulated, img_gate1 = self._modulate(self.img_norm1(hidden_states), img_mod1)
del img_mod1
txt_modulated, txt_gate1 = self._modulate(self.txt_norm1(encoder_hidden_states), txt_mod1)
del txt_mod1
img_attn_output, txt_attn_output = self.attn(
hidden_states=img_modulated,
@ -248,16 +248,20 @@ class QwenImageTransformerBlock(nn.Module):
image_rotary_emb=image_rotary_emb,
transformer_options=transformer_options,
)
del img_modulated
del txt_modulated
hidden_states = hidden_states + img_gate1 * img_attn_output
encoder_hidden_states = encoder_hidden_states + txt_gate1 * txt_attn_output
del img_attn_output
del txt_attn_output
del img_gate1
del txt_gate1
img_normed2 = self.img_norm2(hidden_states)
img_modulated2, img_gate2 = self._modulate(img_normed2, img_mod2)
img_modulated2, img_gate2 = self._modulate(self.img_norm2(hidden_states), img_mod2)
hidden_states = torch.addcmul(hidden_states, img_gate2, self.img_mlp(img_modulated2))
txt_normed2 = self.txt_norm2(encoder_hidden_states)
txt_modulated2, txt_gate2 = self._modulate(txt_normed2, txt_mod2)
txt_modulated2, txt_gate2 = self._modulate(self.txt_norm2(encoder_hidden_states), txt_mod2)
encoder_hidden_states = torch.addcmul(encoder_hidden_states, txt_gate2, self.txt_mlp(txt_modulated2))
return encoder_hidden_states, hidden_states

5
comfy/model_management.py
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@ -504,10 +504,7 @@ class LoadedModel:
use_more_vram = lowvram_model_memory
if use_more_vram == 0:
use_more_vram = 1e32
if use_more_vram > 0:
self.model_use_more_vram(use_more_vram, force_patch_weights=force_patch_weights)
else:
self.model.partially_unload(self.model.offload_device, -use_more_vram, force_patch_weights=force_patch_weights)
self.model_use_more_vram(use_more_vram, force_patch_weights=force_patch_weights)
real_model = self.model.model

3
comfy/model_patcher.py
View File

@ -928,6 +928,9 @@ class ModelPatcher:
extra_memory += (used - self.model.model_loaded_weight_memory)
self.patch_model(load_weights=False)
if extra_memory < 0 and not unpatch_weights:
self.partially_unload(self.offload_device, -extra_memory, force_patch_weights=force_patch_weights)
return 0
full_load = False
if self.model.model_lowvram == False and self.model.model_loaded_weight_memory > 0:
self.apply_hooks(self.forced_hooks, force_apply=True)