nodes/kijai-ComfyUI-DynamiCrafterWrapper
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Fix old model loader node

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kijai
2024-07-03 20:32:25 +03:00
parent 86d0fa80ce
commit 86e825e48a
1 changed files with 16 additions and 8 deletions
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nodes.py
+16 -8
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@@ -261,6 +261,7 @@ class DynamiCrafterModelLoader:
CATEGORY = "DynamiCrafterWrapper"
def loadmodel(self, dtype, ckpt_name, fp8_unet=False):
device = mm.get_torch_device()
mm.soft_empty_cache()
custom_config = {
'dtype': dtype,
@@ -270,7 +271,9 @@ class DynamiCrafterModelLoader:
if not hasattr(self, 'model') or self.model == None or custom_config != self.current_config:
self.current_config = custom_config
model_path = folder_paths.get_full_path("checkpoints", ckpt_name)
ckpt_base_name = os.path.basename(ckpt_name)
ckpt_base_name = os.path.basename(model_path)
print(f"Loading model from: {model_path}")
base_name, _ = os.path.splitext(ckpt_base_name)
if 'toon' in base_name and '512' in base_name:
config_file=os.path.join(script_directory, "configs", "tooncrafter_512_interp.yaml")
@@ -288,24 +291,29 @@ class DynamiCrafterModelLoader:
model_config = config.pop("model", OmegaConf.create())
model_config['params']['unet_config']['params']['use_checkpoint']=False
self.model = instantiate_from_config(model_config)
self.model = load_model_checkpoint(self.model, model_path)
self.model.eval()
if dtype == "auto":
try:
if mm.should_use_fp16():
self.model.to(convert_dtype('fp16'))
precision = (convert_dtype('fp16'))
elif mm.should_use_bf16():
self.model.to(convert_dtype('bf16'))
precision = (convert_dtype('bf16'))
else:
self.model.to(convert_dtype('fp32'))
precision = (convert_dtype('fp32'))
except:
raise AttributeError("ComfyUI version too old, can't autodetect properly. Set your dtype manually.")
else:
self.model.to(convert_dtype(dtype))
precision = (convert_dtype(dtype))
with (init_empty_weights() if is_accelerate_available else nullcontext()):
self.model = instantiate_from_config(model_config)
self.model = load_model_checkpoint(self.model, model_path, precision, device)
self.model.to(precision).to(device).eval()
if fp8_unet:
self.model.model.diffusion_model = self.model.model.diffusion_model.to(torch.float8_e4m3fn)
print(f"Model using dtype: {self.model.dtype}")
dcmodel = {
'model': self.model,
'model_name': ckpt_name,