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put the legacy comments back

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BigStationW 2025-05-07 00:48:34 +02:00 committed by GitHub
parent 62529c4221
commit 0cb5aadce3
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1 changed files with 8 additions and 0 deletions
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comfy/sd.py
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@ -163,10 +163,13 @@ class CLIP:
all_cond_pooled: list[tuple[torch.Tensor, dict[str]]] = []
all_hooks = self.patcher.forced_hooks
if all_hooks is None or not self.use_clip_schedule:
# if no hooks or shouldn't use clip schedule, do unscheduled encode_from_tokens and perform add_dict
return_pooled = "unprojected" if unprojected else True
pooled_dict = self.encode_from_tokens(tokens, return_pooled=return_pooled, return_dict=True)
cond = pooled_dict.pop("cond")
# add/update any keys with the provided add_dict
pooled_dict.update(add_dict)
# add hooks stored on clip
all_cond_pooled.append([cond, pooled_dict])
else:
scheduled_keyframes = all_hooks.get_hooks_for_clip_schedule()
@ -185,6 +188,7 @@ class CLIP:
for scheduled_opts in scheduled_keyframes:
t_range = scheduled_opts[0]
# don't bother encoding any conds outside of start_percent and end_percent bounds
if "start_percent" in add_dict:
if t_range[1] < add_dict["start_percent"]:
continue
@ -194,7 +198,9 @@ class CLIP:
hooks_keyframes = scheduled_opts[1]
for hook, keyframe in hooks_keyframes:
hook.hook_keyframe._current_keyframe = keyframe
# apply appropriate hooks with values that match new hook_keyframe
self.patcher.patch_hooks(all_hooks)
# perform encoding as normal
o = self.cond_stage_model.encode_token_weights(tokens)
cond, pooled = o[:2]
@ -872,6 +878,7 @@ def load_text_encoder_state_dicts(state_dicts=[], embedding_directory=None, clip
clip_target.clip = comfy.text_encoders.sd3_clip.sd3_clip(clip_l=True, clip_g=False, t5=False)
clip_target.tokenizer = comfy.text_encoders.sd3_clip.SD3Tokenizer
elif clip_type == CLIPType.HIDREAM:
# Detect
clip_target.clip = comfy.text_encoders.hidream.hidream_clip(clip_l=True, clip_g=False, t5=False, llama=False, dtype_t5=None, dtype_llama=None, t5xxl_scaled_fp8=None, llama_scaled_fp8=None)
clip_target.tokenizer = comfy.text_encoders.hidream.HiDreamTokenizer
else:
@ -901,6 +908,7 @@ def load_text_encoder_state_dicts(state_dicts=[], embedding_directory=None, clip
clip_g = TEModel.CLIP_G in hidream_dualclip_classes
t5 = TEModel.T5_XXL in hidream_dualclip_classes
llama = TEModel.LLAMA3_8 in hidream_dualclip_classes
# Initialize t5xxl_detect and llama_detect kwargs if needed
t5_kwargs = t5xxl_detect(clip_data) if t5 else {}
llama_kwargs = llama_detect(clip_data) if llama else {}