这是代码:
var options = {
task: "regression",
debug: true,
inputs: ["date"],
outputs: ["price"],
optimizer: "adam",
loss: "meanSquaredError",
layers: [
{
type: 'dense',
units: 1,
inputShape: [1],
activation: 'tanh',
useBias: true,
},
{
type: 'lstm',
units: 1,
inputShape: [1,1],
activation: 'tanh',
useBias: true,
return_sequences: true,
},
{
type: 'dense',
units: 1,
inputShape: [1],
activation: 'tanh',
useBias: false,
},
],
};
var nn = ml5.neuralNetwork(options);
setData();
async function getData(){
var data = await fetch("https://raw.githubusercontent.com/cryptnotehq/filestorage/main/apple_stock.json");
data = await data.json();
var cleaned = await data.map( (entry) => {
var date = entry.Date.split("-");
date = new Date(date[0],date[1],date[2]).getTime();
var result = {
"date": date,
"price": entry.High,
};
return result;
}).filter( result => (result.date != "" || result.date != undefined) && (result.price != "" || result.price != undefined) );
return cleaned;
}
async function setData() {
var obj = await getData();
obj.forEach(item => {
var input = { "date": parseInt(item.date) };
var output = { "price": parseInt(item.price) };
nn.addData(input, output);
});
nn.normalizeData();
train();
}
function train() {
var trainingOptions = {
epochs: 256,
batchSize: 1024,
};
nn.train(trainingOptions, predict);
console.log(nn.data);
}
function predict(){
nn.predict([ parseInt(new Date(2020,10,17).getTime()) ]).then((result) => {
console.log(result);
});
//nn.save();
}
代码也可以在这个 Fiddle中看到。可以在任何浏览器的开发者控制台中查看该错误。
我希望代码能够运行。我试图改变 lstm 层和第一个“密集”层的 inputShape。当我将第一层的 inputShape 更改为[10048,1]
和 lstm 层时,[1,1,1]
我收到此错误:Uncaught (in promise) Error: Error when checking : expected dense_Dense1_input to have 3 dimension(s), but got array with shape [1,1]
这是Fiddle 中的第二种方法。
我不知道我还能做什么,我已经没有想法了。