code: def find_dataset_files(input_path, token_prefix, sentence_prefix):
      files = os.listdir(input_path)
      print("Found %d files in %s" % (len(files), input_path))
      if len(files) > 0:
          if len(files) < 20:
              print("Files:", end="\n  ")
          else:
              print("First few files:", end="\n  ")
          print("\n  ".join(files[:20]))
      token_files = {}
      sentence_files = {}
      text_files = []
      for filename in files:
          if filename.endswith(".zip"):
              continue
          if filename.startswith(token_prefix):
              short_filename = filename[len(token_prefix) :]
              if short_filename.startswith("_"):
                  short_filename = short_filename[1:]
              token_files[short_filename] = filename
          elif filename.startswith(sentence_prefix):
              short_filename = filename[len(sentence_prefix) :]
              if short_filename.startswith("_"):
                  short_filename = short_filename[1:]
              sentence_files[short_filename] = filename
          else:
              text_files.append(filename)
      dataset_files = []
      for filename in text_files:
          if filename not in token_files:
              raise FileNotFoundError(
                  "When looking in %s, found %s as a text file, but did not find a corresponding tokens file at %s_%s  Please give an input directory which has only the text files, tokens files, and sentences files"
                  % (input_path, filename, token_prefix, filename)
              )
          if filename not in sentence_files:
              raise FileNotFoundError(
                  "When looking in %s, found %s as a text file, but did not find a corresponding sentences file at %s_%s  Please give an input directory which has only the text files, tokens files, and sentences files"
                  % (input_path, filename, sentence_prefix, filename)
              )
          text_file = os.path.join(input_path, filename)
          token_file = os.path.join(input_path, token_files[filename])
          sentence_file = os.path.join(
              input_path, sentence_files[filename]
          )
          dataset_files.append((text_file, token_file, sentence_file))
      return dataset_files
  
file_path: stanza/stanza/utils/datasets/tokenization/convert_text_files.py
imports: import argparse
  import os
  import random
  from stanza.models.tokenization.utils import match_tokens_with_text
  import stanza.utils.datasets.common
label_desc: Use image node_id 6 for calling a global function with example usage: find_dataset_files(input_path, token_prefix, sentence_prefix) and returns: dataset_files