class_docstr: Turns off updates, i.e., ensures that forecaster is only fit and never updated.
  
  This is useful when comparing forecasters that update with forecasters that don't,
  in a set-up where all forecasters' `update` has `update_params=True` set.
  
  Shorthand for UpdateEvery with default values.
  
  Parameters
  ----------
  refit_interval : difference of sktime time indices (int or timedelta), optional
      interval that needs to elapse after which the first update defaults to fit
      default = 0, i.e., always refits, never updates
      if index of y seen in fit is integer or y is index-free container type,
          refit_interval must be int, and is interpreted as difference of int location
      if index of y seen in fit is timestamp, must be int or pd.Timedelta
          if pd.Timedelta, will be interpreted as time since last refit elapsed
          if int, will be interpreted as number of time stamps seen since last refit
  refit_window_size : difference of sktime time indices (int or timedelta), optional
      length of the data window to refit to in case update calls fit
      default = inf, i.e., refits to entire training data seen so far
  refit_window_lag : difference of sktime indices (int or timedelta), optional
      lag of the data window to refit to, w.r.t. cutoff, in case update calls fit
      default = 0, i.e., refit window ends with and includes cutoff
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docstr: Return testing parameter settings for the estimator.
  
  Returns
  -------
  params : dict or list of dict, default = {}
      Parameters to create testing instances of the class
      Each dict are parameters to construct an "interesting" test instance, i.e.,
      `MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance.
      `create_test_instance` uses the first (or only) dictionary in `params`
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code: def get_test_params(cls):
      """Return testing parameter settings for the estimator.
  
      Returns
      -------
      params : dict or list of dict, default = {}
          Parameters to create testing instances of the class
          Each dict are parameters to construct an "interesting" test instance, i.e.,
          `MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance.
          `create_test_instance` uses the first (or only) dictionary in `params`
      """
      from sktime.forecasting.trend import TrendForecaster
  
      forecaster = TrendForecaster.create_test_instance()
  
      return {"forecaster": forecaster}
  
imports: import pandas
  from sktime.datatypes import ALL_TIME_SERIES_MTYPES
  from sktime.datatypes._utilities import get_window
  from sktime.forecasting.base._delegate import _DelegatedForecaster
label_desc: Use image node_id 3 for calling the DontUpdate obj's underlying member method code with example usage: obj.get_test_params(cls) and returns: dict