code: def _gen_data_epsilon(datasets_root_dir):
      url_train = (
          "https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary"
          "/epsilon_normalized.bz2"
      )
      url_test = (
          "https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary"
          "/epsilon_normalized.t.bz2"
      )
  
      local_url_train = os.path.join(
          datasets_root_dir, os.path.basename(url_train)
      )
      local_url_test = os.path.join(
          datasets_root_dir, os.path.basename(url_test)
      )
  
      if not os.path.isfile(local_url_train):
          urlretrieve(url_train, local_url_train)
      if not os.path.isfile(local_url_test):
          urlretrieve(url_test, local_url_test)
  
      X_train, y_train = load_svmlight_file(
          local_url_train, dtype=np.float32
      )
      X_test, y_test = load_svmlight_file(
          local_url_test, dtype=np.float32
      )
  
      X_train = pd.DataFrame(X_train.toarray())
      X_test = pd.DataFrame(X_test.toarray())
  
      y_train[y_train <= 0] = 0
      y_test[y_test <= 0] = 0
      y_train = pd.Series(y_train)
      y_test = pd.Series(y_test)
  
      X = pd.concat([X_train, X_test], ignore_index=True)
      y = pd.concat([y_train, y_test], ignore_index=True)
  
      return X, y
  
imports: from cuml.internals.import_utils import has_scipy
  from cuml.internals.safe_imports import gpu_only_import_from
  from cuml.internals import input_utils
  from urllib.request import urlretrieve
  import sklearn.model_selection
  from sklearn.datasets import load_svmlight_file, fetch_covtype
  import cuml.datasets
  from cuml.internals.safe_imports import cpu_only_import
  import os
  import functools
  import gzip
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 9 for calling a global function with example usage: _gen_data_epsilon(datasets_root_dir) and returns: X,  y