torchdevice_tts_patch.txt

# Add this to TorchDevice.py in the apply_patches method

# Patch torch.serialization._get_restore_location for TTS compatibility
original_get_restore_location = torch.serialization._get_restore_location

def patched_get_restore_location(map_location):
    # Create a simple restore function that ignores location
    def restore_location(storage, location):
        return storage
    
    return restore_location

torch.serialization._get_restore_location = patched_get_restore_location

# Patch TTS synthesis module if it's available
try:
    from TTS.tts.utils import synthesis
    
    # Store the original numpy_to_torch function
    original_numpy_to_torch = synthesis.numpy_to_torch
    
    # Define a patched version
    def patched_numpy_to_torch(np_array, dtype, device=None):
        # Handle None input
        if np_array is None:
            return None
        
        # Create tensor on CPU first
        tensor = torch.as_tensor(np_array, dtype=dtype, device='cpu')
        
        # Then move to the requested device if specified
        if device is not None:
            # If device is 'cuda', check if MPS is available
            if device == 'cuda' and hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
                device = 'mps'
            
            # Move tensor to the appropriate device
            tensor = tensor.to(device)
        
        return tensor
    
    # Apply the patch
    synthesis.numpy_to_torch = patched_numpy_to_torch
except ImportError:
    # TTS is not installed, so no need to patch
    pass