code: def predict(self,function,args):
          
          param = self.model.param_array
          fs = []
          for p in self.chain:
              self.model.param_array = p
              fs.append(function(*args))
          # reset model to starting state
          self.model.param_array = param
          return fs
docs: Make a prediction for the function, to which we will pass the additional arguments