Add model detection error hint for lora. (#8880)

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comfyanonymous 2025-07-12 00:49:26 -07:00 committed by GitHub
parent b43916a134
commit b40143984c
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@ -18,6 +18,7 @@ import comfy.ldm.hunyuan3d.vae
import comfy.ldm.ace.vae.music_dcae_pipeline
import yaml
import math
import os
import comfy.utils
@ -977,6 +978,12 @@ def load_gligen(ckpt_path):
model = model.half()
return comfy.model_patcher.ModelPatcher(model, load_device=model_management.get_torch_device(), offload_device=model_management.unet_offload_device())
def model_detection_error_hint(path, state_dict):
filename = os.path.basename(path)
if 'lora' in filename.lower():
return "\nHINT: This seems to be a Lora file and Lora files should be put in the lora folder and loaded with a lora loader node.."
return ""
def load_checkpoint(config_path=None, ckpt_path=None, output_vae=True, output_clip=True, embedding_directory=None, state_dict=None, config=None):
logging.warning("Warning: The load checkpoint with config function is deprecated and will eventually be removed, please use the other one.")
model, clip, vae, _ = load_checkpoint_guess_config(ckpt_path, output_vae=output_vae, output_clip=output_clip, output_clipvision=False, embedding_directory=embedding_directory, output_model=True)
@ -1005,7 +1012,7 @@ def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, o
sd, metadata = comfy.utils.load_torch_file(ckpt_path, return_metadata=True)
out = load_state_dict_guess_config(sd, output_vae, output_clip, output_clipvision, embedding_directory, output_model, model_options, te_model_options=te_model_options, metadata=metadata)
if out is None:
raise RuntimeError("ERROR: Could not detect model type of: {}".format(ckpt_path))
raise RuntimeError("ERROR: Could not detect model type of: {}\n{}".format(ckpt_path, model_detection_error_hint(ckpt_path, sd)))
return out
def load_state_dict_guess_config(sd, output_vae=True, output_clip=True, output_clipvision=False, embedding_directory=None, output_model=True, model_options={}, te_model_options={}, metadata=None):
@ -1177,7 +1184,7 @@ def load_diffusion_model(unet_path, model_options={}):
model = load_diffusion_model_state_dict(sd, model_options=model_options)
if model is None:
logging.error("ERROR UNSUPPORTED DIFFUSION MODEL {}".format(unet_path))
raise RuntimeError("ERROR: Could not detect model type of: {}".format(unet_path))
raise RuntimeError("ERROR: Could not detect model type of: {}\n{}".format(unet_path, model_detection_error_hint(unet_path, sd)))
return model
def load_unet(unet_path, dtype=None):