code: def test_multiple_estimators(estimators):
      """Test add_estimator with multiple estimators."""
      # single estimator test is checked in test_forecastingbenchmark
      benchmark = ForecastingBenchmark()
      benchmark.add_estimator(estimators)
      registered_estimators = benchmark.estimators.entity_specs.keys()
      assert len(registered_estimators) == len(
          estimators
      ), "add_estimator does not register all estimators."
  
file_path: sktime/sktime/benchmarking/tests/test_forecasting.py
imports: import pandas
  import pytest
  from sktime.benchmarking.benchmarks import coerce_estimator_and_id
  from sktime.benchmarking.forecasting import ForecastingBenchmark
  from sktime.forecasting.naive import NaiveForecaster
  from sktime.forecasting.trend import TrendForecaster
  from sktime.performance_metrics.forecasting import MeanAbsoluteError, MeanAbsolutePercentageError, MeanSquaredPercentageError
  from sktime.split import ExpandingWindowSplitter
  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_multiple_estimators(estimators) without return types