def move_to_device()

in anli/src/flint/data_utils/batchbuilder.py [0:0]

• 15 lines of code
• 13 McCabe index (conditional complexity)

def move_to_device(obj, cuda_device: int):
    """
    Given a structure (possibly) containing Tensors on the CPU,
    move all the Tensors to the specified GPU (or do nothing, if they should be on the CPU).
    """

    if cuda_device < 0 or not has_tensor(obj):
        return obj
    elif isinstance(obj, torch.Tensor):
        return obj.cuda(cuda_device)
    elif isinstance(obj, dict):
        return {key: move_to_device(value, cuda_device) for key, value in obj.items()}
    elif isinstance(obj, list):
        return [move_to_device(item, cuda_device) for item in obj]
    elif isinstance(obj, tuple) and hasattr(obj, "_fields"):
        # This is the best way to detect a NamedTuple, it turns out.
        return obj.__class__(*(move_to_device(item, cuda_device) for item in obj))
    elif isinstance(obj, tuple):
        return tuple(move_to_device(item, cuda_device) for item in obj)
    else:
        return obj