code: def test_accuracy_score():
      """Test accuracy score."""
      evaluator, metrics_by_strategy = evaluator_setup(
          score_function=accuracy_score
      )
  
      expected_accuracy = pd.DataFrame(
          {
              "strategy": ["alg1", "alg2", "alg3"],
              "score_function_mean": [1.00, 0.00, 0.75],
              "score_function_stderr": [0.00, 0.00, 0.25],
          }
      )
  
      assert metrics_by_strategy.equals(expected_accuracy)
  
imports: import numpy
  import pandas
  import pytest
  from sklearn.metrics import accuracy_score
  from sktime.benchmarking.evaluation import Evaluator
  from sktime.benchmarking.metrics import PairwiseMetric
  from sktime.benchmarking.results import RAMResults
  from sktime.series_as_features.model_selection import PresplitFilesCV
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 4 for calling a global function with example usage: test_accuracy_score() without return types