text: #!/usr/bin/env python3 -u
  # -*- coding: utf-8 -*-
  # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
  """Metrics to assess performance on forecasting task.
  
  Functions named as ``*_score`` return a scalar value to maximize: the higher
  the better.
  Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
  the lower the better.
  """
  
  __author__ = ["mloning", "Tomasz Chodakowski", "aiwalter", "RNKuhns"]
  __all__ = [
      "make_forecasting_scorer",
      "MeanAbsoluteScaledError",
      "MedianAbsoluteScaledError",
      "MeanSquaredScaledError",
      "MedianSquaredScaledError",
      "MeanAbsoluteError",
      "MeanSquaredError",
      "MedianAbsoluteError",
      "MedianSquaredError",
      "GeometricMeanAbsoluteError",
      "GeometricMeanSquaredError",
      "MeanAbsolutePercentageError",
      "MedianAbsolutePercentageError",
      "MeanSquaredPercentageError",
      "MedianSquaredPercentageError",
      "MeanRelativeAbsoluteError",
      "MedianRelativeAbsoluteError",
      "GeometricMeanRelativeAbsoluteError",
      "GeometricMeanRelativeSquaredError",
      "MeanAsymmetricError",
      "MeanLinexError",
      "RelativeLoss",
      "mean_absolute_scaled_error",
      "median_absolute_scaled_error",
      "mean_squared_scaled_error",
      "median_squared_scaled_error",
      "mean_absolute_error",
      "mean_squared_error",
      "median_absolute_error",
      "median_squared_error",
      "geometric_mean_absolute_error",
      "geometric_mean_squared_error",
      "mean_absolute_percentage_error",
      "median_absolute_percentage_error",
      "mean_squared_percentage_error",
      "median_squared_percentage_error",
      "mean_relative_absolute_error",
      "median_relative_absolute_error",
      "geometric_mean_relative_absolute_error",
      "geometric_mean_relative_squared_error",
      "mean_asymmetric_error",
      "mean_linex_error",
      "relative_loss",
  ]
  
  from sktime.performance_metrics.forecasting._classes import (
      GeometricMeanAbsoluteError,
      GeometricMeanRelativeAbsoluteError,
      GeometricMeanRelativeSquaredError,
      GeometricMeanSquaredError,
      MeanAbsoluteError,
      MeanAbsolutePercentageError,
      MeanAbsoluteScaledError,
      MeanAsymmetricError,
      MeanLinexError,
      MeanRelativeAbsoluteError,
      MeanSquaredError,
      MeanSquaredPercentageError,
      MeanSquaredScaledError,
      MedianAbsoluteError,
      MedianAbsolutePercentageError,
      MedianAbsoluteScaledError,
      MedianRelativeAbsoluteError,
      MedianSquaredError,
      MedianSquaredPercentageError,
      MedianSquaredScaledError,
      RelativeLoss,
      make_forecasting_scorer,
  )
  from sktime.performance_metrics.forecasting._functions import (
      geometric_mean_absolute_error,
      geometric_mean_relative_absolute_error,
      geometric_mean_relative_squared_error,
      geometric_mean_squared_error,
      mean_absolute_error,
      mean_absolute_percentage_error,
      mean_absolute_scaled_error,
      mean_asymmetric_error,
      mean_linex_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,
  )
  