code: def build_data_iterator(args, tokenizer):
      dataset = load_and_cache_examples(args, tokenizer)
      sampler = SequentialSampler(dataset)
  
      def collate_fn(data):
          return collate(
              data, tokenizer, block_size=512, device=args.device
          )
  
      iterator = DataLoader(
          dataset,
          sampler=sampler,
          batch_size=args.batch_size,
          collate_fn=collate_fn,
      )
  
      return iterator
  
imports: import argparse
  import logging
  import os
  import sys
  from collections import namedtuple
  import torch
  from torch.utils.data import DataLoader, SequentialSampler
  from tqdm import tqdm
  from modeling_bertabs import BertAbs, build_predictor
  from transformers import BertTokenizer
  from .utils_summarization import CNNDMDataset, build_mask, compute_token_type_ids, encode_for_summarization, truncate_or_pad
label_desc: Use image node_id 6 for calling a global function with example usage: build_data_iterator(args, tokenizer) and returns: iterator, collate