def METHOD_NAME(session: tf.compat.v1.Session, _: Any = None) -> None:
    """
    NOTE: This is intended to be the user-defined model calibration function.
    AIMET requires the above signature. So if the user's calibration function does not
    match this signature, please create a simple wrapper around this callback function.
    A callback function for model calibration that simply runs forward passes on the model to
    compute encoding (delta/offset). This callback function should use representative data and should
    be subset of entire train/validation dataset (~1000 images/samples).
    :param model: Tensorflow session.
    :param _: Argument(s) of this callback function. 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.
    """
    # User action required
    # User should create data loader/iterable using representative dataset and simply run
    # forward passes on the model.