nodes/ModelTC-ComfyUI-Lightx2vWrapper
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refactor: streamline model and tokenizer path handling in Lightx2vWanVideo classes

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This commit is contained in:
GACLove
2025-06-10 16:51:28 +08:00
parent 3f75753007
commit 001c49c0c5
1 changed files with 12 additions and 11 deletions
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nodes.py
+12 -11
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@@ -253,12 +253,12 @@ class Lightx2vWanVideoT5EncoderLoader:
if model_dir:
model_path = Path(model_dir)
model_path = model_path / model_name
tokenizer_path = model_path / "google" / "umt5-xxl"
else:
model_path = Path(model_name)
assert model_path.exists(), f"T5 model path {model_path} does not exist. Please provide a valid model path or set model_dir."
tokenizer_path = model_path.parent / "google" / "umt5-xxl"
assert tokenizer_path.exists(), f"Tokenizer path {tokenizer_path} does not exist. Please provide a valid tokenizer path or set model_dir."
tokenizer_path = model_path.parent / "google" / "umt5-xxl"
assert tokenizer_path.exists(), f"Tokenizer path {tokenizer_path} does not exist. Please provide a valid tokenizer path or set model_dir."
if device == "cuda":
init_device = comfy_mm.get_torch_device()
@@ -267,7 +267,7 @@ class Lightx2vWanVideoT5EncoderLoader:
init_device = torch.device("cpu")
cpu_offload = True
t5_encoder = LightX2VEncoderFactory.create_t5_encoder(model_name, tokenizer_path, dtype, init_device, cpu_offload)
t5_encoder = LightX2VEncoderFactory.create_t5_encoder(model_path, tokenizer_path, dtype, init_device, cpu_offload)
return (t5_encoder,)
@@ -427,14 +427,9 @@ class Lightx2vWanVideoClipVisionEncoderLoader:
if model_dir:
model_path = Path(model_dir)
model_path = model_path / model_name
tokenizer_file_path = model_path / tokenizer_path
else:
model_path = Path(model_name)
assert model_path.exists(), f"CLIP model path {model_path} does not exist. Please provide a valid model path or set model_dir."
tokenizer_file_path = model_path / tokenizer_path
assert tokenizer_file_path.exists(), (
f"Tokenizer path {tokenizer_file_path} does not exist. Please provide a valid model path or set model_dir."
)
if device == "cuda":
init_device = comfy_mm.get_torch_device()
@@ -649,9 +644,13 @@ class Lightx2vWanVideoModelLoader:
{"default": "flash_attn3"},
),
"cpu_offload": ("BOOLEAN", {"default": False}),
"offload_granularity": (
["block", "phase"],
{"default": "phase"},
),
},
"optional": {
"mm_type": ("STRING", {"default": "None"}),
"mm_type": ("STRING", {"default": None}),
"teacache_args": ("LIGHT_TEACACHEARGS", {"default": None}),
"lora_path": ("STRING", {"default": None}),
"lora_strength": (
@@ -677,6 +676,7 @@ class Lightx2vWanVideoModelLoader:
precision: str,
device: str,
attention_type: str,
offload_granularity: str,
mm_type: str | None = None,
lora_path: str | None = None,
lora_strength: float = 1.0,
@@ -737,7 +737,7 @@ class Lightx2vWanVideoModelLoader:
"attention_type": attention_type,
"lora_path": lora_path if lora_path and lora_path.strip() else None,
"strength_model": lora_strength,
"offload_granularity": "block",
"offload_granularity": offload_granularity,
}
config.update(**config_json)
@@ -809,6 +809,7 @@ class Lightx2vWanVideoSampler:
model_config.seed = seed
model_config.enable_cfg = False if math.isclose(cfg_scale, 1.0) else True
logging.info(f"Loaded update config:\n {model_config}")
# wan_runner.set_target_shape
num_channels_latents = model_config.get("num_channels_latents", 16)