code: def tokenize(self, tokenizer):
      space_tokenization = self.text.split()
      target_tokenization = tokenizer.tokenize(self.text)
      (
          normed_space_tokenization,
          normed_target_tokenization,
      ) = normalize_tokenizations(
          space_tokenization, target_tokenization, tokenizer
      )
      aligner = retokenize.TokenAligner(
          normed_space_tokenization, normed_target_tokenization
      )
      span1_token_count = len(self.span1_text.split())
      span2_token_count = len(self.span2_text.split())
      target_span1 = ExclusiveSpan(
          *aligner.project_token_span(
              self.span1_idx, self.span1_idx + span1_token_count
          )
      )
      target_span2 = ExclusiveSpan(
          *aligner.project_token_span(
              self.span2_idx, self.span2_idx + span2_token_count
          )
      )
      return TokenizedExample(
          guid=self.guid,
          tokens=target_tokenization,
          span1_span=target_span1,
          span2_span=target_span2,
          span1_text=self.span1_text,
          span2_text=self.span2_text,
          label_id=WSCTask.LABEL_TO_ID[self.label],
      )
  
imports: import numpy
  import torch
  from dataclasses import dataclass
  from typing import List
  from jiant.tasks.core import BaseExample, BaseTokenizedExample, BaseDataRow, BatchMixin, SuperGlueMixin, Task, TaskTypes
  from jiant.tasks.lib.templates.shared import labels_to_bimap, add_cls_token, create_input_set_from_tokens_and_segments
  from jiant.tasks.utils import truncate_sequences, ExclusiveSpan
  from jiant.utils import retokenize
  from jiant.utils.python.io import read_json_lines
  from jiant.utils.tokenization_normalization import normalize_tokenizations
label_desc: Use image node_id 1 for calling the Example obj's underlying member method code with example usage: obj.tokenize(tokenizer) and returns: TokenizedExample