code: def load_data(
      directory_prefix, train_file, test_file, name, url=None
  ):
      if not os.path.exists(directory_prefix):
          os.mkdir(directory_prefix)
      directory = directory_prefix + name + "/"
      train_file_path = directory + train_file
      test_file_path = directory + test_file
      if (not os.path.exists(train_file_path)) or (
          not os.path.exists(test_file_path)
      ):
          # fetch files from s3:
          print(
              "%s data not found locally, so fetching from %s"
              % (name, url)
          )
          zip_name = download(url, directory_prefix)
          unzip(zip_name, directory_prefix)
          os.remove(zip_name)
  
      train_data = TabularDataset(train_file_path)
      test_data = TabularDataset(test_file_path)
      return train_data, test_data
  
imports: import os
  import shutil
  import sys
  import tempfile
  import warnings
  from random import seed
  import numpy
  import pandas
  import pytest
  from networkx.exception import NetworkXError
  from autogluon.common import space
  from autogluon.common.utils.simulation_utils import convert_simulation_artifacts_to_tabular_predictions_dict
  from autogluon.core.constants import BINARY, MULTICLASS, PROBLEM_TYPES_CLASSIFICATION, QUANTILE, REGRESSION
  from autogluon.core.utils import download, unzip
  from autogluon.tabular import TabularDataset, TabularPredictor
  from autogluon.tabular.configs.hyperparameter_configs import get_hyperparameter_config
label_desc: Use image node_id 7 for calling a global function with example usage: load_data(directory_prefix, train_file, test_file, name, url) and returns: train_data,  test_data