import torch


def dummy_forward_pass(model: torch.nn.Module, forward_pass_callback_args) -> float:
    """
    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.

    :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.
    :return: single float number (accuracy) representing model's performance
    """
    return .5