(self)
only train
only train
only train
def train(self):
    ''' only train '''
    nn = self.create_estimator()  #pylint: disable=invalid-name

    num_epochs = self.config['solver']['optimizer']['epochs']
    for epoch in range(num_epochs):
      logging.info("epoch: {}".format(epoch + 1))
      try:
        self.train_one_epoch(nn)
      except tf.errors.OutOfRangeError as err:
        logging.info(epoch, err)
        raise err
def train ( self ) : nn = self . create_estimator ( ) #pylint: disable=invalid-name num_epochs = self . config [ 'solver' ] [ 'optimizer' ] [ 'epochs' ] for epoch in range ( num_epochs ) : logging . info ( "epoch: {}" . format ( epoch + 1 ) ) try : self . train_one_epoch ( nn ) except tf . errors . OutOfRangeError as err : logging . info ( epoch , err ) raise err