class_docstr: Base class for all evaluation metrics used in AutoGluon-TimeSeries.
  
  This object always returns the metric in greater-is-better format.
  
  Follows the design of ``autogluon.core.metrics.Scorer``.
  
  Attributes
  ----------
  greater_is_better_internal : bool, default = False
      Whether internal method :meth:`~autogluon.timeseries.metrics.TimeSeriesScorer.compute_metric` is
      a loss function (default), meaning low is good, or a score function, meaning high is good.
  optimum : float, default = 0.0
      The best score achievable by the score function, i.e. maximum in case of scorer function and minimum in case of
      loss function.
  optimized_by_median : bool, default = False
      Whether given point forecast metric is optimized by the median (if True) or expected value (if False). If True,
      all models in AutoGluon-TimeSeries will attempt to paste median forecast into the "mean" column.
  needs_quantile : bool, default = False
      Whether the given metric uses the quantile predictions. Some models will modify the training procedure if they
      are trained to optimize a quantile metric.
  equivalent_tabular_regression_metric : str
      Name of an equivalent metric used by AutoGluon-Tabular with ``problem_type="regression"``. Used by models that
      train a TabularPredictor under the hood. This attribute should only be specified by point forecast metrics.
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docstr: Clear auxiliary metrics saved in :meth:`save_past_metrics`.
  
  This method should only be implemented if :meth:`save_past_metrics` has been implemented.
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code: def clear_past_metrics(self) -> None:
      """Clear auxiliary metrics saved in :meth:`save_past_metrics`.
  
      This method should only be implemented if :meth:`save_past_metrics` has been implemented.
      """
      pass
  
file_path: autogluon/timeseries/src/autogluon/timeseries/metrics/abstract.py
imports: from typing import Optional, Tuple
  import numpy
  import pandas
  from autogluon.timeseries import TimeSeriesDataFrame
  from autogluon.timeseries.utils.datetime import get_seasonality
  from autogluon.timeseries.utils.warning_filters import warning_filter
label_desc: Use image node_id 9 for calling the TimeSeriesScorer obj's underlying member method code with example usage: obj.clear_past_metrics() without return types