Convert SFrame to batch form, where each row contains a sequence of length
    predictions_in_chunk * prediction_window, and there is a single label per
    prediction window.

def prep_data(data, features, session_id, prediction_window, predictions_in_chunk, target=None, verbose=True):
    """
    Convert SFrame to batch form, where each row contains a sequence of length
    predictions_in_chunk * prediction_window, and there is a single label per
    prediction window.
    """
    if target is None:
        target = ""
    if verbose:
        result_dict = _extensions._activity_classifier_prepare_data_verbose(
            data, features, session_id, prediction_window, predictions_in_chunk, target)
    else:
        result_dict = _extensions._activity_classifier_prepare_data(
            data, features, session_id, prediction_window, predictions_in_chunk, target)


    return result_dict["converted_data"] , result_dict["num_of_sessions"]