code: def test_speedup_runner():
      class MockAlgo:
          def __init__(self, t):
              self.t = t
  
          def fit(self, X, y):
              time.sleep(self.t)
              return
  
          def predict(self, X):
              nr = X.shape[0]
              res = np.zeros(nr)
              res[0 : int(nr / 5.0)] = 1.0
              return res
  
      class FastMockAlgo(MockAlgo):
          def __init__(self):
              MockAlgo.__init__(self, 0.1)
  
      class SlowMockAlgo(MockAlgo):
          def __init__(self):
              MockAlgo.__init__(self, 2)
  
      pair = algorithms.AlgorithmPair(
          SlowMockAlgo,
          FastMockAlgo,
          shared_args={},
          name="Mock",
          bench_func=fit_predict,
          accuracy_function=metrics.accuracy_score,
      )
  
      runner = SpeedupComparisonRunner([20], [5], dataset_name="zeros")
      results = runner.run(pair)[0]
  
      expected_speedup = SlowMockAlgo().t / FastMockAlgo().t
  
      assert results["speedup"] == pytest.approx(expected_speedup, 0.4)
  
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 5 for calling a global function with example usage: test_speedup_runner() and returns: res