code: def fit(self, X, y=None):
          '''
          Fit the transform. Does nothing, for compatibility with sklearn API.
  
          Parameters
          ----------
          X : array-like, shape [n_series, ...]
              Time series data and (optionally) contextual data
          y : None
              There is no need of a target in a transformer, yet the pipeline API requires this
              parameter.
  
          Returns
          -------
          self : object
              Returns self.
          '''
          check_ts_data(X, y)
          if not X[0].ndim > 1:
              raise ValueError("X variable must have more than 1 channel")
  
          return self fit(self, X, y=None):
          '''
          Fit the transform. Does nothing, for compatibility with sklearn API.
  
          Parameters
          ----------
          X : array-like, shape [n_series, ...]
              Time series data and (optionally) contextual data
          y : None
              There is no need of a target in a transformer, yet the pipeline API requires this
              parameter.
  
          Returns
          -------
          self : object
              Returns self.
          '''
          check_ts_data(X, y)
          if not X[0].ndim > 1:
              raise ValueError("X variable must have more than 1 channel")
  
          return self
docs: Fit the transform. Does nothing, for compatibility with sklearn API.
  
          Parameters
          ----------
          X : array-like, shape [n_series, ...]
              Time series data and (optionally) contextual data
          y : None
              There is no need of a target in a transformer, yet the pipeline API requires this
              parameter.
  
          Returns
          -------
          self : object
              Returns self.