code: def _load_dataset_pd(
      url,
      md5,
      dataset_name,
      train_file,
      test_file,
      sep=",",
      header="infer",
      cache=False,
  ):
      train_path, test_path = _download_dataset(
          url, md5, dataset_name, train_file, test_file, cache
      )
      train, test = pd.read_csv(
          train_path, header=header, sep=sep
      ), pd.read_csv(test_path, header=header, sep=sep)
      if not cache:
          os.remove(train_path)
          os.remove(test_path)
      return train, test
  
imports: import hashlib
  import logging
  import numpy
  import os
  import pandas
  import tarfile
  import tempfile
  import six
  import shutil
  from .core import PATH_TYPES, fspath
label_desc: Use image node_id 8 for calling a global function with example usage: _load_dataset_pd(url, md5, dataset_name, train_file, test_file, sep, header, cache) and returns: train,  test