code: def test_y_true_y_pred_inconsistent_n_timepoints_raises_error(
      metric_func_name,
  ):
      """Error should be raised if input variables have inconsistent number of samples."""
      metric_func = LOSS_RESULTS[metric_func_name]["func"]
      y = _make_series(n_timepoints=75, random_state=RANDOM_STATES[0])
      y_train, y_true = y.iloc[:50], y.iloc[50:]
      y_pred = y.shift(1).iloc[40:]  # y_pred has more obs
      y_pred_benchmark = y.rolling(2).mean().iloc[50:]
  
      # Test input types
      with pytest.raises(
          ValueError,
          match="Found input variables with inconsistent numbers of samples",
      ):
          metric_func(
              y_true,
              y_pred,
              y_train=y_train,
              y_pred_benchmark=y_pred_benchmark,
          )
  
file_path: sktime/sktime/performance_metrics/tests/test_performance_metrics_forecasting.py
imports: import numpy
  import pandas
  import pytest
  from pandas.api.types import is_numeric_dtype
  from sktime.performance_metrics.forecasting import GeometricMeanRelativeAbsoluteError, GeometricMeanRelativeSquaredError, MeanAbsoluteError, MeanAbsolutePercentageError, MeanAbsoluteScaledError, MeanAsymmetricError, MeanRelativeAbsoluteError, MeanSquaredError, MeanSquaredPercentageError, MeanSquaredScaledError, MedianAbsoluteError, MedianAbsolutePercentageError, MedianAbsoluteScaledError, MedianRelativeAbsoluteError, MedianSquaredError, MedianSquaredPercentageError, MedianSquaredScaledError, RelativeLoss, geometric_mean_relative_absolute_error, geometric_mean_relative_squared_error, mean_absolute_error, mean_absolute_percentage_error, mean_absolute_scaled_error, mean_asymmetric_error, mean_relative_absolute_error, mean_squared_error, mean_squared_percentage_error, mean_squared_scaled_error, median_absolute_error, median_absolute_percentage_error, median_absolute_scaled_error, median_relative_absolute_error, median_squared_error, median_squared_percentage_error, median_squared_scaled_error, relative_loss
  from sktime.performance_metrics.tests._config import RANDOM_SEED
  from sktime.utils._testing.series import _make_series
label_desc: Use image node_id 7 for calling a global function with example usage: test_y_true_y_pred_inconsistent_n_timepoints_raises_error(metric_func_name) without return types