cifar_model.py 文件源码

def resnet_arg_scope(is_training=True):
  """Sets up the default arguments for the CIFAR-10 resnet model."""
  batch_norm_params = {
      'is_training': is_training,
      'decay': 0.9,
      'epsilon': 0.001,
      'scale': True,
      # This forces batch_norm to compute the moving averages in-place
      # instead of using a global collection which does not work with tf.cond.
      # 'updates_collections': None,
  }

  with slim.arg_scope([slim.conv2d, slim.batch_norm], activation_fn=lrelu):
    with slim.arg_scope(
        [slim.conv2d],
        weights_regularizer=slim.l2_regularizer(0.0002),
        weights_initializer=slim.variance_scaling_initializer(),
        normalizer_fn=slim.batch_norm,
        normalizer_params=batch_norm_params):
      with slim.arg_scope([slim.batch_norm], **batch_norm_params) as arg_sc:
        return arg_sc