code: def load_rocstories_dataset(dataset_path):
      """Output a list of tuples(story, 1st continuation, 2nd continuation, label)"""
      with open(dataset_path, encoding="utf_8") as f:
          f = csv.reader(f)
          output = []
          next(f)  # skip the first line
          for line in tqdm(f):
              output.append(
                  (
                      " ".join(line[1:5]),
                      line[5],
                      line[6],
                      int(line[-1]) - 1,
                  )
              )
      return output
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/examples/legacy/run_openai_gpt.py
imports: import argparse
  import csv
  import logging
  import os
  import random
  import numpy
  import torch
  from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
  from tqdm import tqdm, trange
  from transformers import CONFIG_NAME, WEIGHTS_NAME, AdamW, OpenAIGPTDoubleHeadsModel, OpenAIGPTTokenizer, get_linear_schedule_with_warmup
label_desc: Use image node_id 2 for calling a global function with example usage: load_rocstories_dataset(dataset_path) and returns: output