nodes/ModelTC-ComfyUI-Lightx2vWrapper
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refactor: improve class attribute handling in LightX2VModularInference for better configuration management; streamline access to current runner and config hash

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This commit is contained in:
gaclove
2025-09-25 12:32:12 +00:00
parent 7f6d4a63af
commit b311e23c0e
1 changed files with 26 additions and 12 deletions
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nodes.py
+26 -12
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@@ -703,6 +703,11 @@ class LightX2VModularInference:
_current_config_hash = None
def __init__(self):
if not hasattr(self.__class__, '_current_runner'):
self.__class__._current_runner = None
if not hasattr(self.__class__, '_current_config_hash'):
self.__class__._current_config_hash = None
self.config_builder = ConfigBuilder()
self.temp_manager = TempFileManager()
self.image_handler = ImageFileHandler()
@@ -821,14 +826,19 @@ class LightX2VModularInference:
logging.info("lightx2v config: " + json.dumps(config, indent=2, ensure_ascii=False))
config_hash = self._get_config_hash(config)
# 安全地访问类属性
current_runner = getattr(self.__class__, '_current_runner', None)
current_config_hash = getattr(self.__class__, '_current_config_hash', None)
needs_reinit = (
self.__class__._current_runner is None or self.__class__._current_config_hash != config_hash or getattr(config, "lazy_load", False)
current_runner is None or current_config_hash != config_hash or getattr(config, "lazy_load", False)
)
logging.info(f"Needs reinit: {needs_reinit}, old config hash: {self.__class__._current_config_hash}, new config hash: {config_hash}")
logging.info(f"Needs reinit: {needs_reinit}, old config hash: {current_config_hash}, new config hash: {config_hash}")
if needs_reinit:
if self.__class__._current_runner is not None:
# self.__class__._current_runner.end_run()
if current_runner is not None:
# current_runner.end_run()
del self.__class__._current_runner
torch.cuda.empty_cache()
gc.collect()
@@ -836,25 +846,29 @@ class LightX2VModularInference:
self.__class__._current_runner = init_runner(config)
self.__class__._current_config_hash = config_hash
else:
if hasattr(self.__class__._current_runner, "config"):
self.__class__._current_runner.config = config
self.__class__._current_runner.model.config = config
self.__class__._current_runner.model.scheduler.config = config
if hasattr(current_runner, "config"):
current_runner.config = config
current_runner.model.config = config
current_runner.model.scheduler.config = config
progress = ProgressBar(100)
def update_progress(current_step, _total):
progress.update_absolute(current_step)
if hasattr(self.__class__._current_runner, "set_progress_callback"):
self.__class__._current_runner.set_progress_callback(update_progress)
# 重新获取当前runner，因为可能在reinit过程中发生了变化
current_runner = getattr(self.__class__, '_current_runner', None)
if hasattr(current_runner, "set_progress_callback"):
current_runner.set_progress_callback(update_progress)
result_dict = self.__class__._current_runner.run_pipeline()
result_dict = current_runner.run_pipeline()
images = result_dict.get("video", None)
audio = result_dict.get("audio", None)
if getattr(config, "unload_after_inference", False):
del self.__class__._current_runner
if hasattr(self.__class__, '_current_runner'):
del self.__class__._current_runner
self.__class__._current_runner = None
self.__class__._current_config_hash = None