Update api/ltx/ltx_aduc_manager.py

api/ltx/ltx_aduc_manager.py

@@ -22,6 +22,7 @@ from huggingface_hub import hf_hub_download
 # --- Importações da nossa arquitetura ---
 from managers.gpu_manager import gpu_manager
 from api.ltx.ltx_utils import build_ltx_pipeline_on_cpu
+from utils.debug_utils import log_function_io
 
 LTX_VIDEO_REPO_DIR = Path("/data/LTX-Video")
 LTX_REPO_ID = "Lightricks/LTX-Video"
@@ -73,6 +74,7 @@ class LatentConditioningItem:
 # Nossa versão customizada de `prepare_conditioning` que entende ambos os Data Classes.
 # ==============================================================================
 
+@log_function_io
 def _aduc_prepare_conditioning_patch(
     self: "LTXVideoPipeline",
     conditioning_items: Optional[List[Union[ConditioningItem, LatentConditioningItem]]],
@@ -148,6 +150,7 @@ class LTXWorker:
         self.pipeline: LTXVideoPipeline = None
         self._load_and_patch_pipeline()
 
+    @log_function_io
     def _load_and_patch_pipeline(self):
         logging.info(f"[LTXWorker-{self.main_device}] Carregando pipeline LTX para a CPU...")
         self.pipeline, _ = build_ltx_pipeline_on_cpu(self.config)
@@ -181,12 +184,14 @@ class LtxAducManager:
             self._initialized = True
             logging.info("✅ LTXPoolManager pronto.")
 
+    @log_function_io
     def _load_config(self) -> Dict:
         """Carrega a configuração YAML principal do LTX."""
         config_path = Path("/data/LTX-Video/configs/ltxv-13b-0.9.8-dev-fp8.yaml")
         with open(config_path, "r") as file:
             return yaml.safe_load(file)
 
+    @log_function_io
     def get_pipeline(self) -> LTXVideoPipeline:
         """Retorna a instância do pipeline, já carregada e corrigida."""
         return self.worker.pipeline