model_cifar10.py 文件源码

def arg_scope(self):
    """Configure the neural network's layers."""
    batch_norm_params = {
      "is_training" : self.is_training,
      "decay" : 0.9997,
      "epsilon" : 0.001,
      "variables_collections" : {
        "beta" : None,
        "gamma" : None,
        "moving_mean" : ["moving_vars"],
        "moving_variance" : ["moving_vars"]
      }
    }

    with slim.arg_scope([slim.conv2d, slim.fully_connected],
                        weights_initializer=tf.truncated_normal_initializer(
                          stddev=self._hparams.init_stddev),
                        weights_regularizer=slim.l2_regularizer(
                          self._hparams.regularize_constant),
                        activation_fn=tf.nn.relu,
                        normalizer_fn=slim.batch_norm,
                        normalizer_params=batch_norm_params) as sc:
      return sc