update

main.py

@@ -60,31 +60,30 @@ def shell(cmd: str):
 
 
 denoise_engines = {
-    "mpnet-aishell-1-epoch": {
+    "mpnet-nx-speech-1-epoch": {
         "infer_cls": InferenceMPNet,
         "kwargs": {
-            "pretrained_model_path_or_zip_file": (project_path / "trained_models/mpnet-aishell-1-epoch.zip").as_posix()
+            "pretrained_model_path_or_zip_file": (
+                        project_path / "trained_models/mpnet-nx-speech-1-epoch.zip").as_posix()
         }
     },
-    "mpnet-aishell-11-epoch": {
+    "mpnet-aishell-1-epoch": {
         "infer_cls": InferenceMPNet,
         "kwargs": {
-            "pretrained_model_path_or_zip_file": (project_path / "trained_models/mpnet-aishell-11-epoch.zip").as_posix()
+            "pretrained_model_path_or_zip_file": (project_path / "trained_models/mpnet-aishell-1-epoch.zip").as_posix()
         }
     },
-    "mpnet-nx-speech-1-epoch": {
+    "mpnet-aishell-11-epoch": {
         "infer_cls": InferenceMPNet,
         "kwargs": {
-            "pretrained_model_path_or_zip_file": (project_path / "trained_models/mpnet-nx-speech-1-epoch.zip").as_posix()
+            "pretrained_model_path_or_zip_file": (project_path / "trained_models/mpnet-aishell-11-epoch.zip").as_posix()
         }
     },
 }
 
 
 @lru_cache(maxsize=3)
-def load_denoise_model(infer_engine_param: dict):
-    infer_cls = infer_engine_param["infer_cls"]
-    kwargs = infer_engine_param["kwargs"]
+def load_denoise_model(infer_cls, **kwargs):
     infer_engine = infer_cls(**kwargs)
 
     return infer_engine
@@ -101,7 +100,9 @@ def when_click_denoise_button(noisy_audio_t, engine: str):
         raise gr.Error(f"invalid denoise engine: {engine}.")
 
     try:
-        infer_engine = load_denoise_model(infer_engine_param)
+        infer_cls = infer_engine_param["infer_cls"]
+        kwargs = infer_engine_param["kwargs"]
+        infer_engine = load_denoise_model(infer_cls=infer_cls, **kwargs)
 
         enhanced_audio = infer_engine.enhancement_by_ndarray(noisy_audio)
         enhanced_audio = np.array(enhanced_audio * (1 << 15), dtype=np.int16)