class_docstr: " A mapping config to object (model or tokenizer for instance) that will load keys and values when it is accessed.
  
  Args:
  
      - config_mapping: The map model type to config class
      - model_mapping: The map model type to model (or tokenizer) class
class_docstr_tok: ["``","A","mapping","config","to","object","(","model","or","tokenizer","for","instance",")","that","will","load","keys","and","values","when","it","is","accessed",".","Args",":","-","config_mapping",":","The","map","model","type","to","config","class","-","model_mapping",":","The","map","model","type","to","model","(","or","tokenizer",")","class"]
code: def __getitem__(self, key):
      model_type = self._reverse_config_mapping[key.__name__]
      if model_type not in self._model_mapping:
          raise KeyError(key)
      model_name = self._model_mapping[model_type]
      return self._load_attr_from_module(model_type, model_name)
  
imports: import importlib
  from collections import OrderedDict
  from .configuration_auto import AutoConfig, model_type_to_module_name, replace_list_option_in_docstrings
  from .dynamic import get_class_from_dynamic_module
  from fastNLP.transformers.torch.configuration_utils import PretrainedConfig
  from fastNLP.transformers.torch.file_utils import copy_func
  from fastNLP.core.log import logger
label_desc: Use image node_id 2 for calling the _LazyAutoMapping obj's underlying member method code with example usage: obj.__getitem__(key) and returns: self