code: def _init(self, X, lengths):
          
          init = 1. / self.n_components
          if 's' in self.init_params or not hasattr(self, "startprob_"):
              self.startprob_ = np.full(self.n_components, init)
          if 't' in self.init_params or not hasattr(self, "transmat_"):
              self.transmat_ = np.full((self.n_components, self.n_components),
                                       init)
docs: Initializes model parameters prior to fitting.
  
          Parameters
          ----------
          X : array-like, shape (n_samples, n_features)
              Feature matrix of individual samples.
  
          lengths : array-like of integers, shape (n_sequences, )
              Lengths of the individual sequences in ``X``. The sum of
              these should be ``n_samples``.