docstr: update the result(s) to be returned.
  
  Args:
      return_patterns (Union[str, List[str]]): The name of layer to return output.
  
  Returns:
      Dict[str, nn.Layer]: The pattern(str) and corresponding layer(nn.Layer) that have been set successfully.
code: def update_res(
      self, return_patterns: Union[str, List[str]]
  ) -> Dict[str, nn.Layer]:
      """update the result(s) to be returned.
  
      Args:
          return_patterns (Union[str, List[str]]): The name of layer to return output.
  
      Returns:
          Dict[str, nn.Layer]: The pattern(str) and corresponding layer(nn.Layer) that have been set successfully.
      """
  
      # clear res_dict that could have been set
      self.res_dict = {}
  
      class Handler(object):
          def __init__(self, res_dict):
              # res_dict is a reference
              self.res_dict = res_dict
  
          def __call__(self, layer, pattern):
              layer.res_dict = self.res_dict
              layer.res_name = pattern
              if hasattr(layer, "hook_remove_helper"):
                  layer.hook_remove_helper.remove()
              layer.hook_remove_helper = (
                  layer.register_forward_post_hook(save_sub_res_hook)
              )
              return layer
  
      handle_func = Handler(self.res_dict)
  
      hit_layer_pattern_list = self.upgrade_sublayer(
          return_patterns, handle_func=handle_func
      )
  
      if hasattr(self, "hook_remove_helper"):
          self.hook_remove_helper.remove()
      self.hook_remove_helper = self.register_forward_post_hook(
          self._return_dict_hook
      )
  
      return hit_layer_pattern_list
  
imports: import math
  from typing import Any
  from typing import Callable
  from typing import Dict
  from typing import List
  from typing import Tuple
  from typing import Union
  import paddle
  import paddle.nn
  from paddle import concat
  from paddle import ParamAttr
  from paddle import reshape
  from paddle import split
  from paddle import transpose
  from paddle.nn import AdaptiveAvgPool2D
  from paddle.nn import BatchNorm
  from paddle.nn import Conv2D
  from paddle.nn import Dropout
  from paddle.nn import Linear
  from paddle.nn import MaxPool2D
  from paddle.nn.initializer import KaimingNormal
  from paddle.regularizer import L2Decay
label_desc: Use image node_id 7 for calling the TheseusLayer obj's underlying member method code with example usage: obj.update_res(return_patterns) and returns: hit_layer_pattern_list, layer