class_docstr: Produces RoBERTa inputs and answer spans for Squad.
class_docstr_tok: ["Produces","RoBERTa","inputs","and","answer","spans","for","Squad","."]
code: def torchscriptify(self):
      return ScriptRoBERTaTensorizerWithIndices(
          tokenizer=self.tokenizer.torchscriptify(),
          vocab=ScriptVocabulary(
              list(self.vocab),
              pad_idx=self.vocab.get_pad_index(),
              bos_idx=self.vocab.get_bos_index(),
              eos_idx=self.vocab.get_eos_index(),
          ),
          max_seq_len=self.max_seq_len,
      )
  
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 4 for calling the SquadForRoBERTaTensorizer obj's underlying member method code with example usage: obj.torchscriptify() and returns: ScriptRoBERTaTensorizerWithIndices