def METHOD_NAME(
    x: tvm.nd.array,
    sorted: int,
    return_index: int,
    return_inverse: int,
    return_counts: int,
) -> tvm.nd.array:
    """Returns the unique elements of the input tensor.
    Uses numpy.unique to compute unique elements.
    """
    import builtins
    # TODO(prakalp): add support for returning a tuple when return_inverse or return_counts is True
    if bool(return_index) or bool(return_inverse) or bool(return_counts):
        raise NotImplementedError("missing support return_inverse or return_counts set to true")
    x_numpy = x.numpy()
    # TODO(prakalp): use torch.unique instead of numpy when torch is installed in ci.
    output_sorted_numpy, indices = np.unique(x_numpy, return_index=True)
    if sorted:
        return tvm.nd.array(output_sorted_numpy)
    output_numpy = [x_numpy.flatten()[index] for index in builtins.sorted(indices, reverse=True)]
    return tvm.nd.array(output_numpy)