class_docstr: Global Alignment Kernel, from tslearn.
  
  Direct interface to ``tslearn.metrics.cdist_gak``.
  
  Implements the fast GAK from [1]_.
  
  Parameters
  ----------
  sigma : float, default 1.
      Bandwidth of the internal gaussian kernel used for GAK
  n_jobs : int or None, optional, default=None
      The number of jobs to run in parallel.
      ``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
      ``-1`` means using all processors. See scikit-learns'
      `Glossary <https://scikit-learn.org/stable/glossary.html#term-n-jobs>`__
      for more details.
  verbose : int, optional, default=0
      The verbosity level: if non zero, progress messages are printed.
      Above 50, the output is sent to stdout.
      The frequency of the messages increases with the verbosity level.
      If it more than 10, all iterations are reported.
  
  References
  ----------
  .. [1] M. Cuturi, "Fast global alignment kernels," ICML 2011.
docstr: Adapter method to get tslearn pwtrafo.
docstr_tok: ["Adapter","method","to","get","tslearn","pwtrafo","."]
code: def _get_tslearn_pwtrafo(self):
      """Adapter method to get tslearn pwtrafo."""
      from tslearn.metrics.softdtw_variants import cdist_gak
  
      return cdist_gak
  
imports: from sktime.dists_kernels.base import BasePairwiseTransformerPanel
  from sktime.dists_kernels.base.adapters import _TslearnPwTrafoAdapter
label_desc: Use image node_id 2 for calling the GAKernel obj's underlying member method code with example usage: obj._get_tslearn_pwtrafo() and returns: cdist_gak