code: def test_run_variations():
      algo = algorithms.algorithm_by_name("LogisticRegression")
  
      res = run_variations(
          [algo],
          dataset_name="classification",
          bench_rows=[100, 200],
          bench_dims=[10, 20],
      )
      assert res.shape[0] == 4
      assert (res.n_samples == 100).sum() == 2
      assert (res.n_features == 20).sum() == 2
  
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 4 for calling a global function with example usage: test_run_variations() without return types