code: def _preprocess_sklearn(self, X, y=None, fit_time=False):
      force_all_finite = self.kernel not in VARIABLE_LENGTH_METRICS
      if y is None:
          X = check_array(
              X, allow_nd=True, force_all_finite=force_all_finite
          )
      else:
          X, y = check_X_y(
              X, y, allow_nd=True, force_all_finite=force_all_finite
          )
      X = to_time_series_dataset(X)
  
      if fit_time:
          self._X_fit = X
          if self.gamma == "auto":
              self.gamma_ = gamma_soft_dtw(X)
          else:
              self.gamma_ = self.gamma
          self.classes_ = numpy.unique(y)
      else:
          check_is_fitted(self, ["svm_estimator_", "_X_fit"])
          X = check_dims(
              X,
              X_fit_dims=self._X_fit.shape,
              extend=True,
              check_n_features_only=(
                  self.kernel in VARIABLE_LENGTH_METRICS
              ),
          )
  
      if self.kernel in VARIABLE_LENGTH_METRICS:
          assert self.kernel == "gak"
          self.estimator_kernel_ = "precomputed"
          if fit_time:
              sklearn_X = cdist_gak(
                  X,
                  sigma=numpy.sqrt(self.gamma_ / 2.0),
                  n_jobs=self.n_jobs,
                  verbose=self.verbose,
              )
          else:
              sklearn_X = cdist_gak(
                  X,
                  self._X_fit,
                  sigma=numpy.sqrt(self.gamma_ / 2.0),
                  n_jobs=self.n_jobs,
                  verbose=self.verbose,
              )
      else:
          self.estimator_kernel_ = self.kernel
          sklearn_X = to_sklearn_dataset(X)
  
      if y is None:
          return sklearn_X
      else:
          return sklearn_X, y
  
imports: from sklearn.svm import SVC, SVR
  from sklearn.base import ClassifierMixin, RegressorMixin
  from sklearn.utils import deprecated
  from sklearn.utils import check_array, check_X_y
  from sklearn.utils.validation import check_is_fitted
  import numpy
  from ..metrics import cdist_gak, gamma_soft_dtw, VARIABLE_LENGTH_METRICS
  from ..utils import to_time_series_dataset, check_dims, to_sklearn_dataset
  from ..bases import TimeSeriesBaseEstimator
  import warnings
label_desc: Use image node_id 1 for calling the TimeSeriesSVMMixin obj's underlying member method code with example usage: obj._preprocess_sklearn(X, y, fit_time) and returns: sklearn_X, sklearn_X,  y