update models.py & add model

modules/models.py

@@ -184,7 +184,8 @@ class VoiceConvertModel:
         )
         os.makedirs(output_dir, exist_ok=True)
         input_audio_splitext = os.path.splitext(os.path.basename(input_audio))[0]
-        model_splitext = os.path.splitext(self.model_name)[0]
+        # model_splitext = os.path.splitext(self.model_name)[0]
+        model_splitext = os.path.splitext(os.path.basename(self.model_name))[0]
         index = 0
         existing_files = os.listdir(output_dir)
         for existing_file in existing_files:
@@ -202,7 +203,33 @@ class VoiceConvertModel:
         return audio_opt
 
     def get_index_path(self, speaker_id: int):
-        basename = os.path.splitext(self.model_name)[0]
+        # basename = os.path.splitext(self.model_name)[0]
+        basename = os.path.splitext(os.path.basename(self.model_name))[0]
+        
+        # Handle relative paths (e.g., "weights/zet_test1.pth")
+        if "/" in self.model_name:
+            # It's a relative path, look for index in the same directory
+            model_dir = os.path.dirname(os.path.join(ROOT_DIR, self.model_name))
+            relative_index_path = os.path.join(model_dir, f"{basename}.{speaker_id}.index")
+            if os.path.exists(relative_index_path):
+                return relative_index_path
+            
+            # Check generic index in same directory
+            relative_generic_index = os.path.join(model_dir, f"{basename}.index")
+            if os.path.exists(relative_generic_index):
+                return relative_generic_index
+        
+        # Check in weights folder first (for custom models)
+        weights_dir = os.path.join(ROOT_DIR, "weights")
+        weights_index_path = os.path.join(weights_dir, f"{basename}.{speaker_id}.index")
+        if os.path.exists(weights_index_path):
+            return weights_index_path
+            
+        # Check generic index in weights folder
+        weights_generic_index = os.path.join(weights_dir, f"{basename}.index")
+        if os.path.exists(weights_generic_index):
+            return weights_generic_index
+            
         speaker_index_path = os.path.join(
             MODELS_DIR,
             "checkpoints",
@@ -239,10 +266,27 @@ def get_embedder(embedder_name):
 def load_embedder(emb_file: str, emb_name: str):
     global embedder_model, loaded_embedder_model
     emb_file = os.path.join(MODELS_DIR, "embeddings", emb_file)
-    models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
-        [emb_file],
-        suffix="",
-    )
+    
+    # Monkey patch torch.load to use weights_only=False for fairseq compatibility
+    original_torch_load = torch.load
+    def patched_torch_load(*args, **kwargs):
+        kwargs['weights_only'] = False
+        return original_torch_load(*args, **kwargs)
+    
+    try:
+        torch.load = patched_torch_load
+        models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
+            [emb_file],
+            suffix="",
+        )
+    finally:
+        # Restore original torch.load
+        torch.load = original_torch_load
+    
+    # models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
+    #     [emb_file],
+    #     suffix="",
+    # )
     embedder_model = models[0]
     embedder_model = embedder_model.to(device)
 
@@ -256,8 +300,23 @@ def load_embedder(emb_file: str, emb_name: str):
 
 
 def get_vc_model(model_name: str):
-    model_path = os.path.join(MODELS_DIR, "checkpoints", model_name)
-    weight = torch.load(model_path, map_location="cpu")
+    if "/" in model_name:
+        # It's a relative path, use it directly
+        model_path = os.path.join(ROOT_DIR, model_name)
+        if not os.path.exists(model_path):
+            raise FileNotFoundError(f"Model file not found: {model_path}")
+    else:
+        # It's just a filename, check in weights folder first (for custom models)
+        weights_path = os.path.join(ROOT_DIR, "weights", model_name)
+        if os.path.exists(weights_path):
+            model_path = weights_path
+        else:
+            # Fallback to checkpoints folder
+            model_path = os.path.join(MODELS_DIR, "checkpoints", model_name)
+    
+    weight = torch.load(model_path, map_location="cpu", weights_only=False)
+    # model_path = os.path.join(MODELS_DIR, "checkpoints", model_name)
+    # weight = torch.load(model_path, map_location="cpu")
     return VoiceConvertModel(model_name, weight)
 
 

weights/zet_test1.0.index

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a194ba96c803cb1530676d495d5bcab6224a460aa535fc1b8bbe4806d5d9c186
+size 3234139

weights/zet_test1.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:417723f2279e91ffd8fa85a555115cb36b796c898d6a25c25394596efc303382
+size 55192835