Update core.py

rvc_inferpy/core.py

@@ -20,7 +20,7 @@
 from multiprocessing import cpu_count
 from urllib.parse import urlparse
 from io import BytesIO
-
+from fairseq.models.hubert import HubertModel
 import torch
 import numpy as np
 import soundfile as sf
@@ -161,21 +161,25 @@ def note_to_hz(note_name: str) -> float | None:
         return None
 
 
+
+
 def load_hubert(config, hubert_path: str = None):
+
     """
-    Load and return the Hubert model.
-    If the specified hubert_path does not exist, download base models.
+    Load and return the Hubert model using the HubertModel.from_pretrained API.
+    If hubert_path is not provided or does not exist, fallback to a default model.
     """
-    from fairseq import checkpoint_utils
-
     if hubert_path is None or not os.path.exists(hubert_path):
-        for model_file in BASE_MODELS:
-            download_manager(os.path.join(BASE_DOWNLOAD_LINK, model_file), BASE_DIR)
-        hubert_path = "hubert_base.pt"
-    models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
-        [hubert_path], suffix=""
+        # You can implement download logic here if needed.
+        hubert_path = "hubert_base.pt"  # Default model file name
+
+    hubert_model = HubertModel.from_pretrained(
+        model_name_or_path=".",            # Directory containing the model
+        checkpoint_file=hubert_path,         # The checkpoint file to load
+        data_name_or_path="."                # Dummy or actual data directory as required
     )
-    hubert_model = models[0].to(config.device)
+
+    hubert_model = hubert_model.to(config.device)
     hubert_model = hubert_model.half() if config.is_half else hubert_model.float()
     hubert_model.eval()
     return hubert_model