TensorFlow JS -将最小/最大值与模型一起保存，并在预测数据旁边重新加载

// 导入所需的库
import * as tf from '@tensorflow/tfjs';
import * as tfjsNode from '@tensorflow/tfjs-node';

// 创建一个简单的模型
const model = tf.sequential();
model.add(tf.layers.dense({units: 1, inputShape: [1]}));

// 定义一些训练数据
const xs = tf.tensor2d([[1], [2], [3], [4]], [4, 1]);
const ys = tf.tensor2d([[1], [3], [5], [7]], [4, 1]);

// 训练模型
model.compile({loss: 'meanSquaredError', optimizer: 'sgd'});
model.fit(xs, ys, {epochs: 10});

// 计算最小值和最大值
const min = xs.min();
const max = xs.max();

// 保存模型和最小/最大值
await model.save('localstorage://my-model');
await tfjsNode.node.writeJSONFile('min-max.json', {min: min.dataSync()[0], max: max.dataSync()[0]});

// 加载模型和最小/最大值
const loadedModel = await tf.loadLayersModel('localstorage://my-model');
const {min: loadedMin, max: loadedMax} = await tfjsNode.node.readJSONFile('min-max.json');

// 准备预测数据
const predictData = tf.tensor2d([[5], [6]], [2, 1]);

// 根据最小/最大值对预测数据进行归一化
const normalizedData = predictData.sub(loadedMin).div(loadedMax.sub(loadedMin));

// 进行预测
const predictions = loadedModel.predict(normalizedData);

// 打印预测结果
predictions.print();