code: def get_head_config_and_rename_list(
      model_class_name, head_name, label2id, num_labels=None
  ):
      if label2id is None:
          logger.warning(
              "No valid map of labels in label2id. Falling back to default (num_labels=2). This may cause errors during"
              " loading!"
          )
          label2id = {"LABEL_" + str(i): i for i in range(2)}
      # num_labels is optional (e.g. for regression, when no map given)
      num_labels = num_labels or len(label2id)
      data = STATIC_TO_FLEX_HEAD_MAP[model_class_name]
      # copy config to keep original mapping untouched
      config = copy.deepcopy(data["config"])
      if config["head_type"] == "multiple_choice":
          config["num_choices"] = num_labels
          config["label2id"] = label2id
      elif config["head_type"] not in [
          "causal_lm",
          "masked_lm",
          "seq2seq_lm",
      ]:
          config["num_labels"] = num_labels
          config["label2id"] = label2id
      # rename
      rename_list = []
      i = 0
      for name in data["layers"]:
          if name is not None:
              escaped_name = re.escape(name)
              rename_list.append(
                  (
                      rf"{escaped_name}\.(\S+)",
                      f"heads.{head_name}.{i}.{{0}}",
                  )
              )
          i += 1
      rename_func = (
          lambda k, rename_list=rename_list: _regex_list_rename_func(
              k, rename_list
          )
      )
  
      return config, rename_func
  
imports: import copy
  import logging
  import re
label_desc: Use image node_id 2 for calling a global function with example usage: get_head_config_and_rename_list(model_class_name, head_name, label2id, num_labels) and returns: config,  rename_func