def METHOD_NAME(model: tf.keras.Model, forward_pass_callback_args):
    """
    This is intended to be the user-defined model evaluation function. AIMET requires the above signature. So if the
    user's eval function does not match this signature, please create a simple wrapper.
    Use representative dataset that covers diversity in training data to compute optimal encodings.
    :param model: Model to evaluate
    :param forward_pass_callback_args: These argument(s) are passed to the forward_pass_callback as-is. Up to
           the user to determine the type of this parameter. E.g. could be simply an integer representing the number
           of data samples to use. Or could be a tuple of parameters or an object representing something more
           complex.
           If set to None, forward_pass_callback will be invoked with no parameters.
    """
    dummy_x = forward_pass_callback_args
    model(dummy_x)