当我尝试vm2使用Webpack在Electron渲染器进程中导入模块时遇到错误.
import fs from 'fs'
console.log('ok')
const { NodeVM } = require('vm2')
console.log('ko')
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这是Webpack显示的错误:
WARNING in ./~/vm2/lib/main.js
Critical dependencies:
180:26-33 require function is used in a way in which dependencies cannot be statically extracted
335:15-22 require function is used in a way in which dependencies cannot be statically extracted
367:26-33 require function is used in a way in which dependencies cannot be statically extracted
@ ./~/vm2/lib/main.js 180:26-33 335:15-22 367:26-33
WARNING in ./~/vm2/lib/sandbox.js
Module parse failed: /Users/guillaume/Voyager/Voyager/node_modules/vm2/lib/sandbox.js 'return' outside …Run Code Online (Sandbox Code Playgroud) 出于学习目的,我正在使用Tensorflow.js,并且在尝试将该fit方法与批处理数据集(10 x 10)一起使用时遇到错误,以了解批处理培训的过程.
我有一些想要分类的图像600x600x3(2个输出,1或0)
这是我的训练循环:
const batches = await loadDataset()
for (let i = 0; i < batches.length; i++) {
const batch = batches[i]
const xs = batch.xs.reshape([batch.size, 600, 600, 3])
const ys = tf.oneHot(batch.ys, 2)
console.log({
xs: xs.shape,
ys: ys.shape,
})
// { xs: [ 10, 600, 600, 3 ], ys: [ 10, 2 ] }
const history = await model.fit(
xs, ys,
{
batchSize: batch.size,
epochs: 1
}) // <----- The code throws here
const loss …Run Code Online (Sandbox Code Playgroud) javascript classification machine-learning tensorflow tensorflow.js
我正在努力使实体样式以我希望使用draft-js的方式工作。我通过在自动完成组件中选择项目来将样式化的实体添加到输入中。当我选择一个时,它会起作用,但插入符号会留在实体中,直到我添加另一个角色为止。有没有一种方法可以将插入符号移动到实际实体之后而不添加空格?
我正在使用一个名为的库draft-js-autocomplete,如果需要的话,我不介意发出请求请求。
为了显示:

javascript reactjs draftjs styled-components draft-js-plugins
我知道它会被视为反模式,但为什么呢?
mutation {
createUser(name: "john doe") {
addToTeam(teamID: "123") {
name,
id
},
id
}
}
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它不比两个HTTP调用更方便吗?
mutation {
createUser(name: "john doe") {
id, # we store the ID
}
}
mutation {
addToTeam(userID: id, teamID: "123") {
name,
id,
}
}
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