code: def create_dataset_files(
      nlp_path: pathlib.Path,
      dataset_name: str,
      dataset_type: str,
  ) -> None:
      """Create template files."""
      #  Path of the converted dataset directory
      tfds_root_path = tfds.core.utils.tfds_write_path()
      dataset_dir = tfds_root_path / dataset_type
      if not dataset_dir.is_dir():
          raise ValueError(f"Invalid Dataset Type {dataset_type}")
  
      #  Create dataset timeplate files from new.py
      new.create_dataset_files(
          dataset_name=dataset_name, dataset_dir=dataset_dir
      )  # pytype: disable=wrong-arg-types  # gen-stub-imports
  
      #  Path of the dataset file
      nlp_datasets_path = nlp_path.expanduser() / "datasets"
      nlp_file_path = (
          nlp_datasets_path / dataset_name / f"{dataset_name}.py"
      )
  
      #  Path of converted dataset file
      converted_file_path = (
          dataset_dir / dataset_name / f"{dataset_name}.py"
      )
  
      #  Convert nlp dataset --> tfds
      convert_dataset_file(nlp_file_path, converted_file_path)
  
file_path: datasets/tensorflow_datasets/scripts/cleanup/convert_nlp.py
imports: import argparse
  import pathlib
  import re
  from absl import app
  from absl.flags import argparse_flags
  import tensorflow_datasets.public_api
  from tensorflow_datasets.scripts.cli import new
label_desc: Use image node_id 3 for calling a global function with example usage: create_dataset_files(nlp_path, dataset_name, dataset_type) without return types