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Simplify a part

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BigStationW 2025-05-07 01:37:16 +02:00 committed by GitHub
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1 changed files with 8 additions and 13 deletions
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comfy/sd.py
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@ -831,30 +831,25 @@ def load_text_encoder_state_dicts(state_dicts=[], embedding_directory=None, clip
clip_target.clip = comfy.text_encoders.sd2_clip.SD2ClipModel clip_target.clip = comfy.text_encoders.sd2_clip.SD2ClipModel
clip_target.tokenizer = comfy.text_encoders.sd2_clip.SD2Tokenizer clip_target.tokenizer = comfy.text_encoders.sd2_clip.SD2Tokenizer
elif te_model == TEModel.T5_XXL: elif te_model == TEModel.T5_XXL:
common_t5_args = t5xxl_detect(clip_data)
if clip_type == CLIPType.SD3: if clip_type == CLIPType.SD3:
clip_target.clip = comfy.text_encoders.sd3_clip.sd3_clip(clip_l=False, clip_g=False, t5=True, **common_t5_args) clip_target.clip = comfy.text_encoders.sd3_clip.sd3_clip(clip_l=False, clip_g=False, t5=True, **t5xxl_detect(clip_data))
clip_target.tokenizer = comfy.text_encoders.sd3_clip.SD3Tokenizer clip_target.tokenizer = comfy.text_encoders.sd3_clip.SD3Tokenizer
elif clip_type == CLIPType.LTXV: elif clip_type == CLIPType.LTXV:
clip_target.clip = comfy.text_encoders.lt.ltxv_te(**common_t5_args) clip_target.clip = comfy.text_encoders.lt.ltxv_te(**t5xxl_detect(clip_data))
clip_target.tokenizer = comfy.text_encoders.lt.LTXVT5Tokenizer clip_target.tokenizer = comfy.text_encoders.lt.LTXVT5Tokenizer
elif clip_type == CLIPType.PIXART: elif clip_type == CLIPType.PIXART:
clip_target.clip = comfy.text_encoders.pixart_t5.pixart_te(**common_t5_args) clip_target.clip = comfy.text_encoders.pixart_t5.pixart_te(**t5xxl_detect(clip_data))
clip_target.tokenizer = comfy.text_encoders.pixart_t5.PixArtTokenizer clip_target.tokenizer = comfy.text_encoders.pixart_t5.PixArtTokenizer
elif clip_type == CLIPType.WAN: elif clip_type == CLIPType.WAN:
clip_target.clip = comfy.text_encoders.wan.te(**common_t5_args) clip_target.clip = comfy.text_encoders.wan.te(**t5xxl_detect(clip_data))
clip_target.tokenizer = comfy.text_encoders.wan.WanT5Tokenizer clip_target.tokenizer = comfy.text_encoders.wan.WanT5Tokenizer
tokenizer_data["spiece_model"] = clip_data[0].get("spiece_model", None) tokenizer_data["spiece_model"] = clip_data[0].get("spiece_model", None)
elif clip_type == CLIPType.HIDREAM: elif clip_type == CLIPType.HIDREAM:
clip_target.clip = comfy.text_encoders.hidream.hidream_clip(**common_t5_args, clip_target.clip = comfy.text_encoders.hidream.hidream_clip(**t5xxl_detect(clip_data),
clip_l=False, clip_g=False, t5=True, llama=False, dtype_llama=None, llama_scaled_fp8=None) clip_l=False, clip_g=False, t5=True, llama=False, dtype_llama=None, llama_scaled_fp8=None)
clip_target.tokenizer = comfy.text_encoders.hidream.HiDreamTokenizer clip_target.tokenizer = comfy.text_encoders.hidream.HiDreamTokenizer
else: else: #CLIPType.MOCHI or CLIPType.CHROMA
if clip_type == CLIPType.CHROMA: clip_target.clip = comfy.text_encoders.genmo.mochi_te(**t5xxl_detect(clip_data))
logging.debug(f"TEModel.T5_XXL with CLIPType.CHROMA: Using Mochi-like TE (comfy.text_encoders.genmo.mochi_te) for tensor generation.")
else:
logging.debug(f"TEModel.T5_XXL with CLIPType.{clip_type.name if clip_type else 'Unknown'}: Falling to Mochi-like TE (comfy.text_encoders.genmo.mochi_te).")
clip_target.clip = comfy.text_encoders.genmo.mochi_te(**common_t5_args)
clip_target.tokenizer = comfy.text_encoders.genmo.MochiT5Tokenizer clip_target.tokenizer = comfy.text_encoders.genmo.MochiT5Tokenizer
elif te_model == TEModel.T5_XXL_OLD: elif te_model == TEModel.T5_XXL_OLD:
clip_target.clip = comfy.text_encoders.cosmos.te(**t5xxl_detect(clip_data)) clip_target.clip = comfy.text_encoders.cosmos.te(**t5xxl_detect(clip_data))