class_docstr: This metaclass wraps the `__init__` method of a class to add `init_config`
  attribute for instances of that class, and `init_config` use a dict to track
  the initial configuration. If the class has `_wrap_init` method, it would be
  hooked after `__init__` and called as `_wrap_init(self, init_fn, init_args)`.
  Since InitTrackerMeta would be used as metaclass for pretrained model classes,
  which always are Layer and `type(nn.Layer)` is not `type`, thus use `type(nn.Layer)`
  rather than `type` as base class for it to avoid inheritance metaclass
  conflicts.
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docstr: wraps `init_func` which is `__init__` method of a class to add `init_config`
  attribute for instances of that class.
  Args:
      init_func (callable): It should be the `__init__` method of a class.
      help_func (callable, optional): If provided, it would be hooked after
          `init_func` and called as `_wrap_init(self, init_func, *init_args, **init_args)`.
          Default None.
  Returns:
      function: the wrapped function
docstr_tok: ["wraps","`","init_func","`","which","is","`","__init__","`","method","of","a","class","to","add","`","init_config","`","attribute","for","instances","of","that","class",".","Args",":","init_func","(","callable",")",":","It","should","be","the","`","__init__","`","method","of","a","class",".","help_func","(","callable",",","optional",")",":","If","provided",",","it","would","be","hooked","after","`","init_func","`","and","called","as","`","_wrap_init","(","self",",","init_func",",","*","init_args",",","*","*","init_args",")","`",".","Default","None",".","Returns",":","function",":","the","wrapped","function"]
code: def init_and_track_conf(init_func, help_func=None):
      """
      wraps `init_func` which is `__init__` method of a class to add `init_config`
      attribute for instances of that class.
      Args:
          init_func (callable): It should be the `__init__` method of a class.
          help_func (callable, optional): If provided, it would be hooked after
              `init_func` and called as `_wrap_init(self, init_func, *init_args, **init_args)`.
              Default None.
      Returns:
          function: the wrapped function
      """
  
      @functools.wraps(init_func)
      def __impl__(self, *args, **kwargs):
          # keep full configuration
          init_func(self, *args, **kwargs)
          # registed helper by `_wrap_init`
          if help_func:
              help_func(self, init_func, *args, **kwargs)
          self.init_config = kwargs
          if args:
              kwargs["init_args"] = args
          kwargs["init_class"] = self.__class__.__name__
  
      return __impl__
  
imports: import copy
  import functools
  import inspect
  import io
  import json
  import os
  import six
  from typing import List, Tuple, Union
  import paddle
  import paddle.nn
  from packaging.version import Version
  from paddle.dataset.common import DATA_HOME
  from paddle.utils.download import get_path_from_url
  from paddlehub.module.module import serving, RunModule, runnable
  from paddlehub.utils.log import logger
  from paddlehub.utils.utils import reseg_token_label
  import paddlenlp
  from paddlenlp.embeddings.token_embedding import EMBEDDING_HOME, EMBEDDING_URL_ROOT
  from paddlenlp.data import JiebaTokenizer
  from paddlehub.compat.module.nlp_module import DataFormatError
label_desc: Use image node_id 2 for calling the InitTrackerMeta obj's underlying member method code with example usage: obj.init_and_track_conf(init_func, help_func) and returns: __impl__