def __init__(self): """ Create a random permutation and permute each feature-vector X of each datapoint with it. """ self.dlog = dlog.getLogger("preproc.permute_columns") self.permutation = None
def __init__(self, **hyper_params): super(TrainerBase, self).__init__() self.logger = logging.getLogger("trainer") self.dlog = dlog.getLogger("trainer") self.step = 0 self.register_hyper_param("model", default=None, help="") self.register_hyper_param("dataset", default=None, help="") self.register_hyper_param("termination", default=None, help="") self.register_hyper_param("final_monitors", default=[], help="") self.register_hyper_param("epoch_monitors", default=[], help="") self.register_hyper_param("step_monitors", default=[], help="") self.register_hyper_param("first_epoch_step_monitors", default=[], help="") self.register_hyper_param("monitor_nth_step", default=1, help="") self.shvar = {} self.shvar_update_fnc = {} self.set_hyper_params(hyper_params)