Function _configure_optimizer

code/training_evaluation/train.py:186–209

Configures the optimizer used for training. Args: learning_rate: A scalar or `Tensor` learning rate. Returns: An instance of an optimizer. Raises: ValueError: if FLAGS.optimizer is not recognized.

(learning_rate)

def _configure_optimizer(learning_rate):
    """Configures the optimizer used for training.

    Args:
      learning_rate: A scalar or `Tensor` learning rate.

    Returns:
      An instance of an optimizer.

    Raises:
      ValueError: if FLAGS.optimizer is not recognized.
    """

    if FLAGS.optimizer == 'adam':
        optimizer = tf.train.AdamOptimizer(
            learning_rate,
            beta1=FLAGS.adam_beta1,
            beta2=FLAGS.adam_beta2,
            epsilon=FLAGS.opt_epsilon)
    elif FLAGS.optimizer == 'sgd':
        optimizer = tf.train.GradientDescentOptimizer(learning_rate)
    else:
        raise ValueError('Optimizer [%s] was not recognized', FLAGS.optimizer)
    return optimizer


def average_gradients(tower_grads):