Update ltx_manager_helpers.py

ltx_manager_helpers.py

@@ -18,7 +18,7 @@ import json
 from optimization import optimize_ltx_worker, can_optimize_fp8
 from hardware_manager import hardware_manager
 from inference import create_ltx_video_pipeline, calculate_padding
-from ltx_video.pipelines.pipeline_ltx_video import LatentConditioningItem
+from ltx_video.pipelines.pipeline_ltx_video import LatentConditioningItem, LTXMultiScalePipeline
 
 logger = logging.getLogger(__name__)
 
@@ -111,14 +111,11 @@ class LtxPoolManager:
             padded_h, padded_w = ((height - 1) // 32 + 1) * 32, ((width - 1) // 32 + 1) * 32
             padding_vals = calculate_padding(height, width, padded_h, padded_w)
             
-            # --- [INÍCIO DA CORREÇÃO] ---
-            # Move o tensor DENTRO de cada item de condicionamento para o dispositivo do worker.
             conditioning_data = kwargs.get('conditioning_items_data', [])
             final_conditioning_items = []
             for item in conditioning_data:
                 item.latent_tensor = item.latent_tensor.to(worker_to_use.device)
                 final_conditioning_items.append(item)
-            # --- [FIM DA CORREÇÃO] ---
 
             pipeline_params = {
                 "height": padded_h, "width": padded_w, "num_frames": kwargs['video_total_frames'], 
@@ -160,7 +157,16 @@ class LtxPoolManager:
             }
 
             logger.info("LTX POOL MANAGER: Iniciando passe de refinamento (denoise)...")
-            result = worker_to_use.generate_video_fragment_internal(**pipeline_params)
+            
+            # --- [INÍCIO DA CORREÇÃO] ---
+            # Para o refinamento, usamos a pipeline de vídeo base diretamente,
+            # ignorando o invólucro MultiScale que causa o erro de processamento de imagem.
+            if isinstance(worker_to_use.pipeline, LTXMultiScalePipeline):
+                result = worker_to_use.pipeline.video_pipeline(**pipeline_params).images
+            else:
+                result = worker_to_use.generate_video_fragment_internal(**pipeline_params)
+            # --- [FIM DA CORREÇÃO] ---
+            
             return result, None
         except Exception as e:
             logger.error(f"LTX POOL MANAGER: Erro durante o refinamento em {worker_to_use.device}: {e}", exc_info=True)