code: def fit(self, sequences, y=None):
          
          self._initialized = False
          check_iter_of_sequences(sequences, max_iter=3)  # we might be lazy-loading
          for X in sequences:
              self._fit(X)
  
          if self.n_sequences_ == 0:
              raise ValueError('All sequences were shorter than '
                               'the lag time, %d' % self.lag_time)
  
          return self
docs: Fit the model with a collection of sequences.
  
          This method is not online.  Any state accumulated from previous calls to
          fit() or partial_fit() will be cleared. For online learning, use
          `partial_fit`.
  
          Parameters
          ----------
          sequences: list of array-like, each of shape (n_samples_i, n_features)
              Training data, where n_samples_i in the number of samples
              in sequence i and n_features is the number of features.
          y : None
              Ignored
  
          Returns
          -------
          self : object
              Returns the instance itself.