code: def test_data_generators(dataset):
      data = datagen.gen_data(
          dataset, "numpy", n_samples=100, n_features=10
      )
      assert isinstance(data[0], np.ndarray)
      assert data[0].shape[0] == 100
  
imports: from cuml.benchmark.bench_helper_funcs import fit, fit_predict
  import time
  from sklearn import metrics
  from cuml.internals.safe_imports import gpu_only_import_from
  import pytest
  from cuml.internals.safe_imports import gpu_only_import
  from cuml.benchmark import datagen, algorithms
  from cuml.benchmark.bench_helper_funcs import _training_data_to_numpy
  from cuml.benchmark.runners import AccuracyComparisonRunner, SpeedupComparisonRunner, run_variations
  from cuml.internals.import_utils import has_umap
  from cuml.internals.import_utils import has_xgboost
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 1 for calling a global function with example usage: test_data_generators(dataset) without return types