Tensorflow.js 在运行线性回归模型时返回“NaN”值

Question

我正在尝试运行这个线性回归模型，它基本上会给我一个基于 const prediction = model.predict((tf.tensor2d([20], [1,1]))); 的输出，但不幸的是，每次我运行代码以接收预测时都会得到 NaN 值。

解决问题的最佳方法是什么？还有其他方法吗？

谢谢！

下面是代码：

async function learnLinear() {
  const fontSize = document.getElementById("count").innerHTML;
  const parsed = parseInt(fontSize);

  const model = tf.sequential();
  model.add(tf.layers.dense({ units: 1, inputShape: [1] }));

  const learningRate = 0.0001;
  const optimizer = tf.train.sgd(learningRate);

  model.compile({
loss: "meanSquaredError",
optimizer: "sgd",
  });

  const xs = tf.tensor2d(
[
  54,
  20,
  22,
  34,
  18,
  47,
  28,
  54,
  36,
  51,
  44,
  31,
  39,
  19,
  45,
  48,
  32,
  27,
  25,
  54,
  27,
  38,
  25,
  38,
  57,
  49,
  28,
  19,
  59,
  28,
  27,
  55,
  60,
  49,
  40,
  45,
  35,
  45,
  39,
  25,
  50,
  58,
  28,
  59,
  21,
  37,
  47,
  31,
  46,
  18,
],
[50, 1]
  );
  const ys = tf.tensor2d(
[
  14,
  15,
  15,
  15,
  16,
  17,
  15,
  16,
  15,
  17,
  17,
  15,
  16,
  15,
  15,
  16,
  17,
  17,
  17,
  14,
  16,
  15,
  15,
  16,
  17,
  15,
  16,
  14,
  15,
  16,
  14,
  17,
  15,
  14,
  14,
  17,
  15,
  14,
  14,
  16,
  16,
  14,
  14,
  17,
  17,
  14,
  17,
  14,
  14,
  17,
],
[50, 1]
  );

  await model.fit(xs, ys, { epochs: 500 });

  const prediction = model.predict(tf.tensor2d([20], [1, 1]));
  const value = prediction.dataSync()[0];

  console.log("Prediction", value);
}

Answer 1

您忘记指定模型应该跟踪的指标。

const batchSize = 32;
const epochs = 500;

model.compile({
  loss: "meanSquaredError",
  optimizer: "sgd",
  metrics: ["mse"],
});

await model.fit(xs, ys, batchSize, epochs);

const prediction = model.predict(tf.tensor2d([20], [1, 1]));