docstr: Truncates a sequence pair in place to the maximum length.
docstr_tok: ["Truncates","a","sequence","pair","in","place","to","the","maximum","length","."]
code: def _truncate_seq_pair(
      self, tokens_a: List, tokens_b: List, max_length: int
  ):
      """Truncates a sequence pair in place to the maximum length."""
  
      # This is a simple heuristic which will always truncate the longer sequence
      # one token at a time. This makes more sense than truncating an equal percent
      # of tokens from each, since if one sequence is very short then each token
      # that's truncated likely contains more information than a longer sequence.
      while True:
          total_length = len(tokens_a) + len(tokens_b)
          if total_length <= max_length:
              break
          if len(tokens_a) > len(tokens_b):
              tokens_a.pop()
          else:
              tokens_b.pop()
  
imports: from collections import namedtuple
  from typing import Callable, Generator, Generic, List
  import numpy
  from paddlehub.utils.log import logger
  from paddlehub.compat.task import tokenization
  from paddlehub.compat.task.batch import pad_batch_data
label_desc: Use image node_id 2 for calling the BaseNLPReader obj's underlying member method code with example usage: obj._truncate_seq_pair(tokens_a, tokens_b, max_length) without return types