Update api/ltx_server_refactored.py

api/ltx_server_refactored.py

@@ -238,6 +238,7 @@ class VideoService:
         used_seed = random.randint(0, 2**32 - 1) if seed is None else int(seed)
         seed_everething(used_seed)
         FPS = 24.0
+        
         actual_num_frames = max(9, int(round((round(duration * FPS) - 1) / 8.0) * 8 + 1))
         height_padded = ((height - 1) // 8 + 1) * 8
         width_padded = ((width - 1) // 8 + 1) * 8
@@ -256,6 +257,8 @@ class VideoService:
             #"guidance_scale": float(guidance_scale),
             **(self.config.get("first_pass", {}))
         }
+
+        print(f"[DEBUG]  generate_low.first_pass_kwargs: {first_pass_kwargs}")
         try: 
             with torch.autocast(device_type="cuda", dtype=self.runtime_autocast_dtype, enabled=self.device == 'cuda'):
                 latents = self.pipeline(**first_pass_kwargs).images
@@ -336,6 +339,9 @@ class VideoService:
             **first_pass_config
         }
 
+        print(f"[DEBUG]  _generate_single_chunk_low.first_pass_kwargs: {first_pass_kwargs}")
+        
+
         results_dir = "/app/output"; os.makedirs(results_dir, exist_ok=True)
     
         
@@ -443,6 +449,13 @@ class VideoService:
                 ltx_configs_override=ltx_configs_override
             )
 
+
+            print(f"[DEBUG]  generate_narrative_low.frames_per_chunk: {frames_per_chunk}")
+
+            
+            
+            
+
             log_tensor_info(latentes_bruto_r, f"latentes_bruto_r recebidk: {i}...'")
         
             #latent_path_bufer = load_tensor(latent_path)
@@ -533,6 +546,9 @@ class VideoService:
             ltx_configs_override=ltx_configs_override
         )
 
+        print(f"[DEBUG]  generate_single_low.total_actual_frames: {total_actual_frames}")
+        
+
         final_latents = torch.load(latent_path).to(self.device)
         print("\n--- Finalizando Geração Simples: Salvando e decodificando ---")
         log_tensor_info(final_latents, "Tensor de Latentes Final")