class_docstr: A shell used to wrap choices as nn.Module for non-one-shot space definition
  You can use ``map_nn`` function
  
  Parameters
  ----------
  name : anything
      the name of module, can be any type
code: def __repr__(self):
      return "{}({})".format(self.__class__.__name__, self.str)
  
imports: from abc import abstractmethod
  import torch.nn
  from nni.nas.pytorch import mutables
  from nni.nas.pytorch.fixed import FixedArchitecture
  import json
  from copy import deepcopy
  import torch
  from ...model import BaseAutoModel
  from ....utils import get_logger
  from ..utils import get_hardware_aware_metric
label_desc: Use image node_id 3 for calling the StrModule obj's underlying member method code with example usage: obj.__repr__() and returns: str