(self, nn, steps=None)
train for one epoch
train for one epoch
train for one epoch
def train_one_epoch(self, nn, steps=None):  #pylint: disable=invalid-name
    ''' train for one epoch '''
    mode = utils.TRAIN
    tfconf = self.config['solver']['run_config']
    nn.train(
        input_fn=self.input_fn(mode),
        steps=steps,
        hooks=[tf_debug.LocalCLIDebugHook()] if tfconf['debug'] else None)
def train_one_epoch ( self , nn , steps = None ) : #pylint: disable=invalid-name mode = utils . TRAIN tfconf = self . config [ 'solver' ] [ 'run_config' ] nn . train ( input_fn = self . input_fn ( mode ) , steps = steps , hooks = [ tf_debug . LocalCLIDebugHook ( ) ] if tfconf [ 'debug' ] else None )