Update api/ltx_server.py

api/ltx_server.py

@@ -807,7 +807,7 @@ class VideoService:
             "mixed_precision": (self.config["precision"] == "mixed_precision"),
             "offload_to_cpu": False,
             "enhance_prompt": False,
-            "skip_layer_strategy": SkipLayerStrategy.AttentionValues,
+            #"skip_layer_strategy": SkipLayerStrategy.AttentionValues,
         }
         print(f"[DEBUG] output_type={call_kwargs['output_type']} skip_layer_strategy={call_kwargs['skip_layer_strategy']}")
 
@@ -928,15 +928,17 @@ class VideoService:
                     print("\n--- INICIANDO GERAÇÃO DE ETAPA ÚNICA ---")
                     t_single = time.perf_counter()
                     
-                    single_pass_kwargs["output_type"] = "latent"
                     single_pass_call_kwargs = call_kwargs.copy()
-                    first_pass_config_from_yaml = PIPELINE_CONFIG_YAML.get("first_pass", {})
-            
-                    single_pass_call_kwargs["timesteps"] = first_pass_config_from_yaml.get("timesteps")
+                    single_pass_call_kwargs_config = self.config.get("first_pass", {})
+
+                    single_pass_call_kwargs["output_type"] = "latent"
+                    single_pass_call_kwargs["timesteps"] = single_pass_call_kwargs_config.get("timesteps")
                     single_pass_call_kwargs["guidance_scale"] = float(guidance_scale)
-                    single_pass_call_kwargs["stg_scale"] = first_pass_config_from_yaml.get("stg_scale")
-                    single_pass_call_kwargs["rescaling_scale"] = first_pass_config_from_yaml.get("rescaling_scale")
-                    single_pass_call_kwargs["skip_block_list"] = first_pass_config_from_yaml.get("skip_block_list")
+                    single_pass_call_kwargs["stg_scale"] = single_pass_call_kwargs_config.get("stg_scale")
+                    single_pass_call_kwargs["rescaling_scale"] = single_pass_call_kwargs_config.get("rescaling_scale")
+                    single_pass_call_kwargs["skip_block_list"] = None # first_pass_config_from_yaml.get("skip_block_list")
+                    single_pass_call_kwargs["skip_final_inference_steps"] = 0
+                    single_pass_call_kwargs["skip_initial_inference_steps"] = 0
                     
                     # Remove keys that might conflict or are not used in single pass / handled by above
                     single_pass_call_kwargs.pop("num_inference_steps", None)