code: def tensorize(self, batch):
      (
          tokens,
          segment_labels,
          seq_lens,
          positions,
          answer_start_idx,
          answer_end_idx,
          start_logits,
          end_logits,
          has_answer_logits,
      ) = zip(*batch)
  
      tensor_tuple = super().tensorize(
          zip(
              tokens,
              segment_labels,
              seq_lens,
              positions,
              answer_start_idx,
              answer_end_idx,
          )
      )
      return tensor_tuple + (
          pad_and_tensorize(start_logits, dtype=torch.float),
          pad_and_tensorize(end_logits, dtype=torch.float),
          pad_and_tensorize(
              has_answer_logits,
              dtype=torch.float,
              pad_shape=[
                  len(has_answer_logits),
                  len(has_answer_logits[0]),
              ],
          ),
      )
  
imports: import itertools
  from typing import List
  import torch
  from pytext.data.bert_tensorizer import BERTTensorizer
  from pytext.data.roberta_tensorizer import RoBERTaTensorizer
  from pytext.data.tensorizers import lookup_tokens
  from pytext.data.utils import pad_and_tensorize
  from pytext.torchscript.tensorizer import ScriptRoBERTaTensorizerWithIndices
  from pytext.torchscript.vocab import ScriptVocabulary
label_desc: Use image node_id 5 for calling the SquadForBERTTensorizerForKD obj's underlying member method code with example usage: obj.tensorize(batch) and returns: unknown