class_docstr: Soft dynamic time warping distance, from tslearn.
  
  Direct interface to ``tslearn.metrics.cdist_soft_dtw`` and
  ``tslearn.metrics.cdist_soft_dtw_normalized``.
  
  Parameters
  ----------
  normalized : bool, default = False
      Whether the DTW distance should be normalized.
      If ``False``, interfaces ``tslearn.metrics.cdist_soft_dtw``.
      If ``True``, interfaces ``tslearn.metrics.cdist_soft_dtw_normalized``.
  gamma : float (default 1.)
      Gamma parameter for Soft-DTW
  
  References
  ----------
  .. [1] M. Cuturi, M. Blondel "Soft-DTW: a Differentiable Loss Function for
     Time-Series," ICML 2017.
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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.
      There are currently no reserved values for distance/kernel transformers.
  
  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.
          There are currently no reserved values for distance/kernel transformers.
  
      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`
      """
      params0 = {}
      params1 = {"normalized": True, "gamma": 1.5}
      params2 = {"gamma": 0.5}
  
      return [params0, params1, params2]
  
file_path: sktime/sktime/dists_kernels/dtw/_dtw_tslearn.py
imports: from sktime.dists_kernels.base import BasePairwiseTransformerPanel
  from sktime.dists_kernels.base.adapters import _TslearnPwTrafoAdapter
label_desc: Use image node_id 3 for calling the SoftDtwDistTslearn obj's underlying member method code with example usage: obj.get_test_params(cls, parameter_set) and returns: list