feat: add 'use_31_block' configuration option to LightX2VDefaultConfig and LightX2VInferenceConfig for enhanced audio settings

bridge.py

@@ -157,6 +157,8 @@ class LightX2VDefaultConfig:
         "max_area": False,
         "use_prompt_enhancer": False,
         "text_len": 512,
+        # ========== Wan2.1 Audio Settings ==========
+        "use_31_block": True,
     }
 
 
@@ -326,13 +328,16 @@ class ModularConfigManager:
 
         if "video_duration" in config:
             updates["video_duration"] = config["video_duration"]
-        
+
         if "adaptive_resize" in config:
             updates["adaptive_resize"] = config["adaptive_resize"]
 
         if "denoising_step_list" in config:
             updates["denoising_step_list"] = config["denoising_step_list"]
 
+        if "use_31_block" in config:
+            updates["use_31_block"] = config["use_31_block"]
+
         return updates
 
     def apply_teacache_config(
@@ -409,9 +414,7 @@ class ModularConfigManager:
                 updates["t5_quant_scheme"] = "int8-q8f"
                 updates["clip_quant_scheme"] = "int8-q8f"
             elif quant_backend == "torchao":
-                mm_type = (
-                    f"W-{dit_scheme}-channel-sym-A-{dit_scheme}-channel-sym-dynamic-Torchao"
-                )
+                mm_type = f"W-{dit_scheme}-channel-sym-A-{dit_scheme}-channel-sym-dynamic-Torchao"
                 updates["t5_quant_scheme"] = "int8-torchao"
                 updates["clip_quant_scheme"] = "int8-torchao"
             else:

examples/wan_i2v.json

@@ -377,4 +377,4 @@
     "VHS_KeepIntermediate": true
   },
   "version": 0.4
-}
+}

examples/wan_i2v_with_distill_lora.json

@@ -424,4 +424,4 @@
     "VHS_KeepIntermediate": true
   },
   "version": 0.4
-}
+}

examples/wan_t2v_with_distill_lora.json

@@ -424,4 +424,4 @@
     "VHS_KeepIntermediate": true
   },
   "version": 0.4
-}
+}

nodes.py

@@ -165,8 +165,10 @@ class LightX2VInferenceConfig:
             video_length = video_length + (4 - remainder)
 
         # TODO(xxx):
+        use_31_block = True
         if "wan2.1_audio" in [model_cls]:
             video_length = 81
+            use_31_block = False
 
         config = {
             "model_cls": model_cls,
@@ -182,6 +184,7 @@ class LightX2VInferenceConfig:
             "fps": fps,
             "video_duration": duration,
             "adaptive_resize": adaptive_resize,
+            "use_31_block": use_31_block,
         }
 
         if denoising_steps and denoising_steps.strip():
@@ -655,8 +658,16 @@ class LightX2VModularInference:
                     temp_files.append(tmp.name)
                 logging.info(f"Image saved to {tmp.name}")
 
-            if audio is not None and hasattr(config, "model_cls") and "audio" in config.model_cls:
-                if isinstance(audio, dict) and "waveform" in audio and "sample_rate" in audio:
+            if (
+                audio is not None
+                and hasattr(config, "model_cls")
+                and "audio" in config.model_cls
+            ):
+                if (
+                    isinstance(audio, dict)
+                    and "waveform" in audio
+                    and "sample_rate" in audio
+                ):
                     waveform = audio["waveform"]
                     sample_rate = audio["sample_rate"]
 
@@ -683,7 +694,9 @@ class LightX2VModularInference:
                         import wave
 
                         with wave.open(tmp.name, "wb") as wav_file:
-                            wav_file.setnchannels(1 if waveform.ndim == 1 else waveform.shape[-1])
+                            wav_file.setnchannels(
+                                1 if waveform.ndim == 1 else waveform.shape[-1]
+                            )
                             wav_file.setsampwidth(2)  # 16-bit
                             wav_file.setframerate(sample_rate)
                             if waveform.dtype != np.int16:
@@ -703,7 +716,11 @@ 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._current_runner is None
+                or self._current_config_hash != config_hash
+                or getattr(config, "lazy_load", False)
+            )
 
             if needs_reinit:
                 if self._current_runner is not None:
@@ -717,7 +734,6 @@ class LightX2VModularInference:
                 if hasattr(self._current_runner, "config"):
                     self._current_runner.config = config
 
-            total_steps = getattr(config, "infer_steps", 40)
             progress = ProgressBar(100)
 
             def update_progress(current_step, total):