import tensorflow as tf

                      """Steps after which learning rate decays.""")
tf.flags.DEFINE_float('learning_rate_decay_factor', 0.94,
                      """Learning rate decay factor.""")
tf.flags.DEFINE_float('momentum', 0.9, """Momentum for training.""")
tf.flags.DEFINE_float('rmsprop_decay', 0.9, """Decay term for RMSProp.""")
tf.flags.DEFINE_float('rmsprop_momentum', 0.9, """Momentum in RMSProp.""")
tf.flags.DEFINE_float('rmsprop_epsilon', 1.0, """Epsilon term for RMSProp.""")
tf.flags.DEFINE_float('gradient_clip', None, """Gradient clipping magnitude.
                       Disabled by default.""")
tf.flags.DEFINE_float('weight_decay', 0.00004,
                      """Weight decay factor for training.""")

# Performance tuning flags.
tf.flags.DEFINE_boolean('winograd_nonfused', True,
                        """Enable/disable using the Winograd non-fused
                        algorithms.""")
tf.flags.DEFINE_boolean('sync_on_finish', False,
                        """Enable/disable whether the devices are synced after
