code: def update_cost_model(self, x, cost_x):
          
  
          if self.cost_type == 'evaluation_time':
              cost_evals = np.log(np.atleast_2d(np.asarray(cost_x)).T)
  
              if self.num_updates == 0:
                  X_all = x
                  costs_all = cost_evals
              else:
                  X_all = np.vstack((self.cost_model.model.X,x))
                  costs_all = np.vstack((self.cost_model.model.Y,cost_evals))
  
              self.num_updates += 1
              self.cost_model.updateModel(X_all, costs_all, None, None)
docs: Updates the GP used to handle the cost.
  
          param x: input of the GP for the cost model.
          param x_cost: values of the time cost at the input locations.