class_docstr: Base pairwise transformer for tabular or series data template class.
  
  The base pairwise transformer specifies the methods and method signatures that all
  pairwise transformers have to implement.
  
  Specific implementations of these methods is deferred to concrete classes.
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docstr: Compute distance/kernel matrix.
  
  private _transform containing core logic, called from transform
  
  Behaviour: returns pairwise distance/kernel matrix
      between samples in X and X2 (equal to X if not passed)
  
  Parameters
  ----------
  X: pd.DataFrame of length n, or 2D np.array with n rows
  X2: pd.DataFrame of length m, or 2D np.array with m rows, optional
      default X2 = X
  
  Returns
  -------
  distmat: np.array of shape [n, m]
      (i,j)-th entry contains distance/kernel between X.iloc[i] and X2.iloc[j]
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code: def _transform(self, X, X2=None):
      """Compute distance/kernel matrix.
  
      private _transform containing core logic, called from transform
  
      Behaviour: returns pairwise distance/kernel matrix
          between samples in X and X2 (equal to X if not passed)
  
      Parameters
      ----------
      X: pd.DataFrame of length n, or 2D np.array with n rows
      X2: pd.DataFrame of length m, or 2D np.array with m rows, optional
          default X2 = X
  
      Returns
      -------
      distmat: np.array of shape [n, m]
          (i,j)-th entry contains distance/kernel between X.iloc[i] and X2.iloc[j]
      """
      raise NotImplementedError
  
imports: from sktime.base import BaseEstimator
  from sktime.datatypes import check_is_scitype, convert_to
  from sktime.datatypes._series_as_panel import convert_Series_to_Panel
label_desc: Use image node_id 4 for calling the BasePairwiseTransformer obj's underlying member method code with example usage: obj._transform(X, X2) without return types