code: def _truncate_seq_pair(tokens_a, tokens_b, max_length):
      """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: import pandas
  import os
  import torch
  from pathlib import Path
  import pickle
  import logging
  import shutil
  from torch.utils.data import Dataset, TensorDataset, DataLoader, RandomSampler, SequentialSampler
  from torch.utils.data.distributed import DistributedSampler
  from transformers import AutoTokenizer
label_desc: Use image node_id 1 for calling a global function with example usage: _truncate_seq_pair(tokens_a, tokens_b, max_length) without return types