问Tensorflow，可以降低某些数据项的梯度

EN

            @tf.function
            def train_on_batch(x,y):

                y_true = y[:, 0]
                weights = y[:,1]

                with tf.GradientTape() as tape:
                    y_pred = model(x, training=True)
                    print("ytrainpred ", y_pred)
                    loss_value_pre = loss(y_true, y_pred)   
                    loss_value = loss_value_pre * weights

                # compute gradient 
                grads = tape.gradient(loss_value, model.trainable_weights)

                # update weights
                optimizer.apply_gradients(zip(grads, model.trainable_weights))

                # update metrics
                loss_1_train.update_state(y_true[:, 0], loss_value[:,0])
                loss_2_train.update_state(y_true[:, 1], loss_value[:,1)

                return loss_value