nodes/ModelTC-ComfyUI-Lightx2vWrapper
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refactor: convert instance variables to class variables in LightX2VModularInference for shared state management; update related logic for configuration reinitialization

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gaclove
2025-09-08 16:52:27 +08:00
parent 0908604ec5
commit 71005b6ef7
1 changed files with 22 additions and 16 deletions
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nodes.py
+22 -16
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@@ -617,9 +617,12 @@ class LightX2VConfigCombiner:
class LightX2VModularInference:
# 类变量，所有实例共享
_current_runner = None
_current_config_hash = None
def __init__(self):
self._current_runner = None
self._current_config_hash = None
pass
@classmethod
def INPUT_TYPES(cls):
@@ -769,37 +772,40 @@ class LightX2VModularInference:
logging.info(f"Audio saved to {tmp.name}")
config_hash = self._get_config_hash(config)
needs_reinit = self._current_runner is None or self._current_config_hash != config_hash or getattr(config, "lazy_load", False)
needs_reinit = (
self.__class__._current_runner is None or self.__class__._current_config_hash != config_hash or getattr(config, "lazy_load", False)
)
logging.info(f"Needs reinit: {needs_reinit}, old config hash: {self._current_config_hash}, new config hash: {config_hash}")
logging.info(f"Needs reinit: {needs_reinit}, old config hash: {self.__class__._current_config_hash}, new config hash: {config_hash}")
if needs_reinit:
if self._current_runner is not None:
del self._current_runner
if self.__class__._current_runner is not None:
self.__class__._current_runner.end_run()
del self.__class__._current_runner
torch.cuda.empty_cache()
gc.collect()
self._current_runner = init_runner(config)
self._current_config_hash = config_hash
self.__class__._current_runner = init_runner(config)
self.__class__._current_config_hash = config_hash
else:
if hasattr(self._current_runner, "config"):
self._current_runner.config = config
if hasattr(self.__class__._current_runner, "config"):
self.__class__._current_runner.config = config
progress = ProgressBar(100)
def update_progress(current_step, total):
progress.update_absolute(current_step)
if hasattr(self._current_runner, "set_progress_callback"):
self._current_runner.set_progress_callback(update_progress)
if hasattr(self.__class__._current_runner, "set_progress_callback"):
self.__class__._current_runner.set_progress_callback(update_progress)
result_dict = self._current_runner.run_pipeline(save_video=False)
result_dict = self.__class__._current_runner.run_pipeline(save_video=False)
images = result_dict.get("video", None)
audio = result_dict.get("audio", None)
if getattr(config, "unload_after_inference", False):
del self._current_runner
self._current_runner = None
self._current_config_hash = None
del self.__class__._current_runner
self.__class__._current_runner = None
self.__class__._current_config_hash = None
torch.cuda.empty_cache()
gc.collect()