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Changed prints out for logging.info

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envy-ai 2025-04-18 16:59:45 -04:00
parent 676b934364
commit f2f7404152
2 changed files with 8 additions and 8 deletions
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2
comfy/sd.py
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@ -829,7 +829,7 @@ def load_text_encoder_state_dicts(state_dicts=[], embedding_directory=None, clip
clip_target.tokenizer = comfy.text_encoders.lumina2.LuminaTokenizer
tokenizer_data["spiece_model"] = clip_data[0].get("spiece_model", None)
elif te_model == TEModel.LLAMA3_8:
print("Single LLAMA3_8 for HiDreams")
logging.info("Single LLAMA3_8 for HiDreams")
clip_target.clip = comfy.text_encoders.hidream.hidream_clip(False, **llama_detect(clip_data), clip_g=False, t5=False)
clip_target.tokenizer = comfy.text_encoders.hidream.HiDreamTokenizer
else:

14
comfy/text_encoders/hidream.py
View File

@ -98,13 +98,13 @@ class HiDreamTEModel(torch.nn.Module):
if len(token_weight_pairs_g) > 0 or len(token_weight_pairs_l) > 0:
if self.clip_l is not None:
print("Encoding clip_l token weights")
logging.info("Encoding clip_l token weights")
lg_out, l_pooled = self.clip_l.encode_token_weights(token_weight_pairs_l)
else:
l_pooled = torch.zeros((1, 768), device=comfy.model_management.intermediate_device())
if self.clip_g is not None:
print("Encoding clip_g token weights")
logging.info("Encoding clip_g token weights")
g_out, g_pooled = self.clip_g.encode_token_weights(token_weight_pairs_g)
else:
g_pooled = torch.zeros((1, 1280), device=comfy.model_management.intermediate_device())
@ -113,27 +113,27 @@ class HiDreamTEModel(torch.nn.Module):
pooled = torch.cat((l_pooled, g_pooled), dim=-1)
if self.t5xxl is not None:
print("Encoding t5 token weights")
logging.info("Encoding t5 token weights")
t5_output = self.t5xxl.encode_token_weights(token_weight_pairs_t5)
t5_out, t5_pooled = t5_output[:2]
if self.llama is not None:
print("Encoding llama token weights")
logging.info("Encoding llama token weights")
ll_output = self.llama.encode_token_weights(token_weight_pairs_llama)
ll_out, ll_pooled = ll_output[:2]
ll_out = ll_out[:, 1:]
if t5_out is None:
print("Loading t5_out from disk")
logging.info("Loading t5_out from disk")
t5_path = folder_paths.get_full_path_or_raise("hidream_empty_latents", "t5_out.pt")
t5_out = torch.load(t5_path, map_location=comfy.model_management.intermediate_device())
if ll_out is None:
print("No llama encoder found, filling with zeroes")
logging.info("No llama encoder found, filling with zeroes")
ll_out = torch.zeros((1, 32, 1, 4096), device=comfy.model_management.intermediate_device())
if pooled is None:
print("Loading pooled from disk")
logging.info("Loading pooled from disk")
pooled_path = folder_paths.get_full_path_or_raise("hidream_empty_latents", "pooled.pt")
pooled = torch.load(pooled_path, map_location=comfy.model_management.intermediate_device())