code: def convert_data_file_format(
      src_file_name, tgt_file_name, output_file_name
  ):
      """
      Converts the old two-file format used by SequenceToSequenceDataset to the new JSONL format used by T5SFTDataset
      """
      output_lines = []
      with open(src_file_name, encoding="utf8") as f_src, open(
          tgt_file_name, encoding="utf8"
      ) as f_tgt:
          for i, (src, tgt) in enumerate(zip(f_src, f_tgt)):
              if i % 10000 == 0 and i != 0:
                  logging.info(
                      f"Read {i} lines from {src_file_name} & {tgt_file_name}"
                  )
              output_lines.append({"input": src, "output": tgt})
  
      logging.info(f"Dataset Length : {len(output_lines)}")
  
      with open(output_file_name, "w") as f_json:
          for line in output_lines:
              f_json.write(json.dumps(line) + "\n")
  
file_path: NeMo/nemo/collections/nlp/data/language_modeling/megatron/t5_sft_dataset.py
imports: import json
  import os
  from typing import Optional
  import numpy
  import torch
  from datasets import load_dataset
  from nemo.collections.common.tokenizers.tokenizer_spec import TokenizerSpec
  from nemo.collections.nlp.data.language_modeling.text_memmap_dataset import JSONLMemMapDataset
  from nemo.core.classes import Dataset
  from nemo.utils import logging
label_desc: Use image node_id 1 for calling a global function with example usage: convert_data_file_format(src_file_name, tgt_file_name, output_file_name) without return types