code: def inception_resnet_v2_arg_scope(weight_decay=0.00004,
                                    batch_norm_decay=0.9997,
                                    batch_norm_epsilon=0.001):
    
    # Set weight_decay for weights in conv2d and fully_connected layers.
    with slim.arg_scope([slim.conv2d, slim.fully_connected],
                        weights_regularizer=slim.l2_regularizer(weight_decay),
                        biases_regularizer=slim.l2_regularizer(weight_decay)):
  
      batch_norm_params = {
          'decay': batch_norm_decay,
          'epsilon': batch_norm_epsilon,
      }
      # Set activation_fn and parameters for batch_norm.
      with slim.arg_scope([slim.conv2d], activation_fn=tf.nn.relu,
                          normalizer_fn=slim.batch_norm,
                          normalizer_params=batch_norm_params) as scope:
        return scope
docs: Returns the scope with the default parameters for inception_resnet_v2.
  
    Args:
      weight_decay: the weight decay for weights variables.
      batch_norm_decay: decay for the moving average of batch_norm momentums.
      batch_norm_epsilon: small float added to variance to avoid dividing by zero.
  
    Returns:
      a arg_scope with the parameters needed for inception_resnet_v2.