nodes/ModelTC-ComfyUI-Lightx2vWrapper
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refactor: update user-configurable parameters in ConfigManager for improved defaults and remove unused imports

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GACLove
2025-07-14 23:57:31 +08:00
parent c47f4c1b68
commit e2ec826c99
1 changed files with 11 additions and 13 deletions
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lightx2v_nodes/universal_bridge.py
+11 -13
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@@ -11,9 +11,9 @@ import tempfile
from easydict import EasyDict
import asyncio
from .config import get_available_attn_ops, get_available_quant_ops
# from .config import get_available_attn_ops, get_available_quant_ops
from ..lightx2v.lightx2v.utils.set_config import get_default_config, set_config
from ..lightx2v.lightx2v.utils.set_config import get_default_config
from ..lightx2v.lightx2v.infer import init_runner
@@ -171,7 +171,7 @@ class LightX2VBridge:
"""Get or create a runner for the given config."""
# Create a simple key based on essential parameters only
# Only model_cls and model_path are essential for runner identity
key = f"{config.model_cls}_{config.model_path}"
key = f"{config.model_cls}_{config.model_path}" # type:ignore
# If we have a different runner, clear the old one first
if self._current_runner_key != key:
@@ -185,8 +185,6 @@ class LightX2VBridge:
"""Clear cached runner to free memory."""
if self._current_runner is not None:
# Clean up the runner if it has cleanup methods
if hasattr(self._current_runner, "cleanup"):
self._current_runner.cleanup()
self._current_runner = None
self._current_runner_key = None
torch.cuda.empty_cache()
@@ -247,13 +245,13 @@ class ConfigManager:
# 用户可配置的参数（在ComfyUI中显示）
USER_CONFIGURABLE_PARAMS = {
"steps": {"type": "INT", "default": -1, "min": 1, "max": 200, "tooltip": "推理步数 (-1使用默认值)"},
"cfg_scale": {"type": "FLOAT", "default": -1, "min": 0.1, "max": 30, "step": 0.1, "tooltip": "CFG引导强度 (-1使用默认值)"},
"seed": {"type": "INT", "default": -1, "min": -1, "max": 2**32 - 1, "tooltip": "随机种子 (-1随机)"},
"height": {"type": "INT", "default": -1, "min": 64, "max": 2048, "step": 8, "tooltip": "视频高度 (-1使用默认值)"},
"width": {"type": "INT", "default": -1, "min": 64, "max": 2048, "step": 8, "tooltip": "视频宽度 (-1使用默认值)"},
"video_length": {"type": "INT", "default": -1, "min": 1, "max": 300, "tooltip": "视频帧数 (-1使用默认值)"},
"sample_shift": {"type": "INT", "default": -1, "min": 0, "max": 20, "tooltip": "采样偏移 (-1使用默认值)"},
"steps": {"type": "INT", "default": 20, "min": 1, "max": 200, "tooltip": "推理步数 (-1使用默认值)"},
"cfg_scale": {"type": "FLOAT", "default": 7, "min": 0.1, "max": 30, "step": 0.1, "tooltip": "CFG引导强度 (-1使用默认值)"},
"seed": {"type": "INT", "default": 42, "min": -1, "max": 2**32 - 1, "tooltip": "随机种子 (-1随机)"},
"height": {"type": "INT", "default": 640, "min": 64, "max": 2048, "step": 8, "tooltip": "视频高度 (-1使用默认值)"},
"width": {"type": "INT", "default": 640, "min": 64, "max": 2048, "step": 8, "tooltip": "视频宽度 (-1使用默认值)"},
"video_length": {"type": "INT", "default": 1, "min": 1, "max": 300, "tooltip": "视频帧数 (-1使用默认值)"},
"sample_shift": {"type": "INT", "default": 5, "min": 0, "max": 20, "tooltip": "采样偏移 (-1使用默认值)"},
}
@classmethod
@@ -556,7 +554,7 @@ class LightX2VQuantizationConfig:
bridge = LightX2VBridge()
if quantization_preset == "custom":
config = {
config: dict[str, Any] = {
"mm_config": {"mm_type": mm_type},
}
if dit_quantized_ckpt: