code: def fit(self, X, y):
          
          X, event, time = check_arrays_survival(X, y)
  
          weights = ipc_weights(event, time)
          super().fit(X, numpy.log(time), sample_weight=weights)
  
          return self
docs: Build an accelerated failure time model.
  
          Parameters
          ----------
          X : array-like, shape = (n_samples, n_features)
              Data matrix.
  
          y : structured array, shape = (n_samples,)
              A structured array containing the binary event indicator
              as first field, and time of event or time of censoring as
              second field.
  
          Returns
          -------
          self