code: def predict_survival_function(self, X, alpha=None):
          
          baseline_model = self._get_baseline_model(alpha)
  
          return baseline_model.get_survival_function(self.predict(X, alpha=alpha))
docs: Predict survival function.
  
          Only available if :meth:`fit` has been called with `fit_baseline_model = True`.
  
          The survival function for an individual
          with feature vector :math:`x_\\alpha` is defined as
  
          .. math::
  
              S(t \\mid x_\\alpha) = S_0(t)^{\\exp(x_\\alpha^\\top \\beta)} ,
  
          where :math:`S_0(t)` is the baseline survival function,
          estimated by Breslow's estimator.
  
          Parameters
          ----------
          X : array-like, shape = (n_samples, n_features)
              Data matrix.
  
          alpha : float, optional
              Constant that multiplies the penalty terms. The same alpha as used during training
              must be specified. If set to ``None``, the last alpha in the solution path is used.
  
          Returns
          -------
          survival : ndarray, shape = (n_samples,)
              Predicted survival functions.