code: def featurize(self, tokenizer, feat_spec):
      if feat_spec.sep_token_extra:
          maybe_extra_sep = [tokenizer.sep_token]
          maybe_extra_sep_segment_id = [feat_spec.sequence_a_segment_id]
          special_tokens_count = 4
      else:
          maybe_extra_sep = []
          maybe_extra_sep_segment_id = []
          special_tokens_count = 3
  
      paragraph = truncate_sequences(
          tokens_ls=[self.paragraph],
          max_length=(
              feat_spec.max_seq_length
              - special_tokens_count
              - len(self.question)
              - len(self.answer)
          ),
      )[0]
      unpadded_inputs = add_cls_token(
          unpadded_tokens=(
              paragraph
              + self.question
              + [tokenizer.sep_token]
              + maybe_extra_sep
              + self.answer
              + [tokenizer.sep_token]
          ),
          unpadded_segment_ids=(
              [feat_spec.sequence_a_segment_id] * len(paragraph)
              + [feat_spec.sequence_a_segment_id]
              * (len(self.question) + 1)
              + maybe_extra_sep_segment_id
              + [feat_spec.sequence_b_segment_id]
              * (len(self.answer) + 1)
          ),
          tokenizer=tokenizer,
          feat_spec=feat_spec,
      )
      input_set = create_input_set_from_tokens_and_segments(
          unpadded_tokens=unpadded_inputs.unpadded_tokens,
          unpadded_segment_ids=unpadded_inputs.unpadded_segment_ids,
          tokenizer=tokenizer,
          feat_spec=feat_spec,
      )
      return DataRow(
          guid=self.guid,
          input_ids=np.array(input_set.input_ids),
          input_mask=np.array(input_set.input_mask),
          segment_ids=np.array(input_set.segment_ids),
          label_id=self.label_id,
          tokens=unpadded_inputs.unpadded_tokens,
          question_id=self.question_id,
      )
  
imports: import collections
  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
  from jiant.utils.python.io import read_json_lines
label_desc: Use image node_id 1 for calling the TokenizedExample obj's underlying member method code with example usage: obj.featurize(tokenizer, feat_spec) and returns: DataRow