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):
"""
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)
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)
