code: def _gen_data_classification(
      n_samples,
      n_features,
      random_state=42,
      n_classes=2,
      dtype=np.float32,
  ):
      """Wrapper for sklearn make_blobs"""
      if n_samples == 0:
          n_samples = int(1e6)
      if n_features == 0:
          n_samples = 100
  
      X_arr, y_arr = cuml.datasets.make_classification(
          n_samples=n_samples,
          n_features=n_features,
          n_classes=n_classes,
          random_state=random_state,
          dtype=dtype,
      )
      X_df = cudf.DataFrame(X_arr)
      y_df = cudf.Series(y_arr)
      return X_df, y_df
  
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 4 for calling a global function with example usage: _gen_data_classification(n_samples, n_features, random_state, n_classes, dtype) and returns: X_df,  y_df