code: def load_word_pairs(
      fname: Union[str, PathLike],
      tokenizer: Tokenizer,
      vocab: Optional[Vocabulary] = None,
      namespace: str = "token",
      all_cases: bool = True,
  ) -> Tuple[List[torch.Tensor], List[torch.Tensor]]:
      """
      This function loads a list of pairs of words from a file,
      tokenizes each word into subword tokens, and converts the
      tokens into IDs.
  
      # Parameters
  
      fname : `Union[str, PathLike]`
          Name of file containing list of pairs of words to load.
      tokenizer : `Tokenizer`
          Tokenizer to tokenize words in file.
      vocab : `Vocabulary`, optional (default=`None`)
          Vocabulary of tokenizer. If `None`, assumes tokenizer is of
          type `PreTrainedTokenizer` and uses tokenizer's `vocab` attribute.
      namespace : `str`
          Namespace of vocab to use when tokenizing.
      all_cases : `bool`, optional (default=`True`)
          Whether to tokenize lower, title, and upper cases of each word.
  
      # Returns
  
      word_ids : `Tuple[List[torch.Tensor], List[torch.Tensor]]`
          Pair of lists of tensors containing the IDs of subword tokens for
          words in the file.
      """
      word_ids1 = []
      word_ids2 = []
      with open(cached_path(fname)) as f:
          words = json.load(f)
          for w1, w2 in words:
              word_ids1.extend(
                  _convert_word_to_ids_tensor(
                      w1, tokenizer, vocab, namespace, all_cases
                  )
              )
              word_ids2.extend(
                  _convert_word_to_ids_tensor(
                      w2, tokenizer, vocab, namespace, all_cases
                  )
              )
      return word_ids1, word_ids2
  
file_path: allennlp/allennlp/fairness/bias_utils.py
imports: import torch
  import json
  from os import PathLike
  from typing import List, Tuple, Union, Optional
  from allennlp.common.file_utils import cached_path
  from allennlp.data import Vocabulary
  from allennlp.data.tokenizers.tokenizer import Tokenizer
label_desc: Use image node_id 3 for calling a global function with example usage: load_word_pairs(fname, tokenizer, vocab, namespace, all_cases) and returns: word_ids1,  word_ids2