code: def predict_proba(self, X, lengths=None):
          
          _, posteriors = self.score_samples(X, lengths)
          return posteriors
docs: Compute the posterior probability for each state in the model.
  
          X : array-like, shape (n_samples, n_features)
              Feature matrix of individual samples.
  
          lengths : array-like of integers, shape (n_sequences, ), optional
              Lengths of the individual sequences in ``X``. The sum of
              these should be ``n_samples``.
  
          Returns
          -------
          posteriors : array, shape (n_samples, n_components)
              State-membership probabilities for each sample from ``X``.