class_docstr: A mapping that will load all pairs of key values at the first access (either by indexing, requestions keys, values,
  etc.)
  
  Args:
      mapping: The mapping to load.
class_docstr_tok: ["A","mapping","that","will","load","all","pairs","of","key","values","at","the","first","access","(","either","by","indexing",",","requestions","keys",",","values",",","etc",".",")","Args",":","mapping",":","The","mapping","to","load","."]
code: def _initialize(self):
      if self._initialized:
          return
      # logger.warning(
      #     "ALL_PRETRAINED_CONFIG_ARCHIVE_MAP is deprecated and will be removed in v5 of Transformers. "
      #     "It does not contain all available model checkpoints, far from it. Checkout hf.co/models for that.",
      #     FutureWarning,
      # )
  
      for model_type, map_name in self._mapping.items():
          module_name = model_type_to_module_name(model_type)
          module = importlib.import_module(
              f".{module_name}", "fastNLP.transformers.torch.models"
          )
          mapping = getattr(module, map_name)
          self._data.update(mapping)
  
      self._initialized = True
  
imports: import importlib
  import re
  from collections import OrderedDict
  from typing import List, Union
  from fastNLP.transformers.torch.configuration_utils import PretrainedConfig
  from fastNLP.transformers.torch.file_utils import CONFIG_NAME
  from fastNLP.core.log import logger
label_desc: Use image node_id 2 for calling the _LazyLoadAllMappings obj's underlying member method code with example usage: obj._initialize() without return types