fix try catch

app.py

@@ -50,37 +50,28 @@ if not os.path.exists(MUSICLSTM_PATH):
 if not (os.path.exists(ISTFTNET_PATH + ".ts") or os.path.exists(ISTFTNET_PATH + ".pth")):  # .ts or .pth for vocoder
     print(f"Warning: Vocoder model not found at {ISTFTNET_PATH}. (.ts or .pth)")
 
-try:
-    pre_enc = get_pre_encoder(PREENC_PATH, device, channels=[192, 768, 1024, 1024], kernel_sizes=[3, 5, 7, 11],
+
+pre_enc = get_pre_encoder(PREENC_PATH, device, channels=[192, 768, 1024, 1024], kernel_sizes=[3, 5, 7, 11],
                               mel_channels=160)
 
-    # Determine NUM_GENRES from genre_ids.csv if possible, otherwise use fixed
-    # For now, using the fixed NUM_GENRES. The model needs to be trained with this.
-    model = MusicLSTM(vocab_size=VOCAB_SIZE, num_genres=NUM_GENRES, pad_id=PAD_ID)
-
-    # For MusicLSTM, the user code loads a checkpoint dictionary
-    if os.path.exists(MUSICLSTM_PATH):
-        chkp = torch.load(MUSICLSTM_PATH, map_location=device,
-                          weights_only=False)  # Set weights_only based on your .pt file
-        model.load_state_dict(chkp["model_state_dict"])
-    else:
-        print(f"MusicLSTM model file {MUSICLSTM_PATH} not found. Using uninitialized model.")
-    model = model.to(device).eval()
-
-    vocoder = ISTFTNetFE(None, None)  # Adjust constructor if needed
-
-    vocoder.load_ts(ISTFTNET_PATH, device)  # load_ts might expect a directory/prefix
-    vocoder = vocoder.to(device).eval()
-
-    MODELS_LOADED = True
-    print("Models loaded successfully (or placeholders initialized).")
-
-except Exception as e:
-    print(f"Error loading models: {e}")
-    print("Ensure model files are correctly placed and MQGAN classes are defined/imported.")
-    MODELS_LOADED = False
-    # Assign None to prevent further errors if Gradio tries to use them
-    pre_enc, model, vocoder = None, None, None
+# Determine NUM_GENRES from genre_ids.csv if possible, otherwise use fixed
+# For now, using the fixed NUM_GENRES. The model needs to be trained with this.
+model = MusicLSTM(vocab_size=VOCAB_SIZE, num_genres=NUM_GENRES, pad_id=PAD_ID)
+    
+chkp = torch.load(MUSICLSTM_PATH, map_location=device, weights_only=False) 
+model.load_state_dict(chkp["model_state_dict"])
+
+model = model.to(device).eval()
+
+vocoder = ISTFTNetFE(None, None)  # Adjust constructor if needed
+
+vocoder.load_ts(ISTFTNET_PATH, device)  # load_ts might expect a directory/prefix
+vocoder = vocoder.to(device).eval()
+
+MODELS_LOADED = True
+print("Models loaded successfully (or placeholders initialized).")
+
+
 
 
 # --- Genre Loading ---