code: def get_input_files(args):
      if args.input_reference:
          assert not args.inputs
          with open(args.input_reference, "r") as f:
              args.inputs = f.read().splitlines()
  
      print(
          f"Processing {len(args.inputs)} input files {args.dupe_factor} times."
      )
  
      # Duplicate input files based on dupe-factor
      args.inputs = sum(
          (args.inputs for _ in range(args.dupe_factor)), []
      )
  
file_path: gluon-nlp/scripts/pretraining/torch/bert/prepare_quickthought.py
imports: import tqdm
  import argparse
  import time
  import os
  import pathlib
  import random
  import math
  import multiprocessing
  from smart_open import open
  import gluonnlp
  import numpy
  import pyarrow
  import pyarrow.feather
  import pyarrow.compute
label_desc: Use image node_id 5 for calling a global function with example usage: get_input_files(args) without return types