class_docstr: Invert a series-to-series transformation.
  
  Switches `transform` and `inverse_transform`, leaves `fit` and `update` the same.
  
  Parameters
  ----------
  transformer : sktime transformer, must transform Series input to Series output
      this is a "blueprint" transformer, state does not change when `fit` is called
  
  Attributes
  ----------
  transformer_: transformer,
      this clone is fitted when `fit` is called and provides `transform` and inverse
  
  Examples
  --------
  >>> from sktime.datasets import load_airline
  >>> from sktime.transformations.compose import InvertTransform
  >>> from sktime.transformations.series.exponent import ExponentTransformer
  >>>
  >>> inverse_exponent = InvertTransform(ExponentTransformer(power=3))
  >>> X = load_airline()
  >>> Xt = inverse_exponent.fit_transform(X)  # computes 3rd square root
docstr: Return testing parameter settings for the estimator.
  
  Parameters
  ----------
  parameter_set : str, default="default"
      Name of the set of test parameters to return, for use in tests. If no
      special parameters are defined for a value, will return `"default"` set.
  
  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, parameter_set="default"):
      """Return testing parameter settings for the estimator.
  
      Parameters
      ----------
      parameter_set : str, default="default"
          Name of the set of test parameters to return, for use in tests. If no
          special parameters are defined for a value, will return `"default"` set.
  
      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.transformations.series.boxcox import BoxCoxTransformer
      from sktime.transformations.series.exponent import (
          ExponentTransformer,
      )
  
      # ExponentTransformer skips fit
      params1 = {"transformer": ExponentTransformer()}
      # BoxCoxTransformer has fit
      params2 = {"transformer": BoxCoxTransformer()}
  
      return [params1, params2]
  
imports: from sktime.transformations._delegate import _DelegatedTransformer
  from sktime.utils.warnings import warn
label_desc: Use image node_id 4 for calling the InvertTransform obj's underlying member method code with example usage: obj.get_test_params(cls, parameter_set) and returns: list