class_docstr: Produces BERT inputs and answer spans for Squad.
class_docstr_tok: ["Produces","BERT","inputs","and","answer","spans","for","Squad","."]
code: def __init__(
      self,
      answers_column: str = Config.answers_column,
      answer_starts_column: str = Config.answer_starts_column,
      max_subseq_len: int = Config.max_subseq_len,
      **kwargs,
  ):
      # Arguments which are common to both current and base class are passed
      # as **kwargs. These are then passed to the __init__ of the base class
      super().__init__(**kwargs)
      self.answers_column = answers_column
      self.answer_starts_column = answer_starts_column
      self.max_subseq_len = max_subseq_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 2 to create a new SquadForBERTTensorizer object from inherited base classes: BERTTensorizer with example: obj = SquadForBERTTensorizer(answers_column, answer_starts_column, max_subseq_len)