Update app.py

app.py

@@ -7,11 +7,15 @@ from encodec.utils import convert_audio
 from encodec.compress import compress_to_file, decompress_from_file
 import io
 
-# Load the Encodec model 
-model = EncodecModel.encodec_model_48khz()
+# Check for CUDA availability and set device
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+print(f"Using device: {device}")
+
+# Load the Encodec model and move it to the selected device
+model = EncodecModel.encodec_model_48khz().to(device)
 model.set_target_bandwidth(6.0)
 
-@spaces.GPU
+@spaces.GPU  # Indicate GPU usage for Spaces environment (if applicable)
 def encode(audio_file_path):
     try:
         # Load and pre-process the audio waveform
@@ -22,6 +26,7 @@ def encode(audio_file_path):
             wav = torch.mean(wav, dim=0, keepdim=True)
 
         wav = convert_audio(wav, sr, model.sample_rate, model.channels)
+        wav = wav.to(device)  # Move the input audio to the selected device
 
         # Compress to ecdc file in memory
         output = io.BytesIO()
@@ -34,11 +39,11 @@ def encode(audio_file_path):
         gr.Warning(f"An error occurred during encoding: {e}")
         return None
 
-@spaces.GPU
+@spaces.GPU 
 def decode(compressed_audio_file):
     try:
         # Decompress audio
-        wav, sr = decompress_from_file(compressed_audio_file)
+        wav, sr = decompress_from_file(compressed_audio_file, device=device) # Pass the device to decompress_from_file
 
         # Convert the decoded audio to a numpy array for Gradio output
         decoded_audio = wav.cpu().numpy()