spaCy/website/src/widgets/quickstart-training.js
2021-02-01 21:44:55 +11:00

122 lines
4.1 KiB
JavaScript

import React, { useState } from 'react'
import { StaticQuery, graphql } from 'gatsby'
import highlightCode from 'gatsby-remark-prismjs/highlight-code.js'
import { Quickstart } from '../components/quickstart'
import generator, { DATA as GENERATOR_DATA } from './quickstart-training-generator'
import { htmlToReact } from '../components/util'
const DEFAULT_LANG = 'en'
const DEFAULT_HARDWARE = 'cpu'
const DEFAULT_OPT = 'efficiency'
const COMPONENTS = ['tagger', 'parser', 'ner', 'textcat']
const COMMENT = `# This is an auto-generated partial config. To use it with 'spacy train'
# you can run spacy init fill-config to auto-fill all default settings:
# python -m spacy init fill-config ./base_config.cfg ./config.cfg`
const DATA = [
{
id: 'lang',
title: 'Language',
defaultValue: DEFAULT_LANG,
},
{
id: 'components',
title: 'Components',
help: 'Pipeline components to train. Requires training data for those annotations.',
options: COMPONENTS.map(id => ({ id, title: id })),
multiple: true,
},
{
id: 'hardware',
title: 'Hardware',
options: [
{ id: 'cpu', title: 'CPU', checked: DEFAULT_HARDWARE === 'cpu' },
{ id: 'gpu', title: 'GPU (transformer)', checked: DEFAULT_HARDWARE === 'gpu' },
],
},
{
id: 'optimize',
title: 'Optimize for',
help:
'Optimize for efficiency (faster inference, smaller model, lower memory consumption) or higher accuracy (potentially larger & slower model). Will impact the choice of architecture, pretrained weights and hyperparameters.',
options: [
{ id: 'efficiency', title: 'efficiency', checked: DEFAULT_OPT === 'efficiency' },
{ id: 'accuracy', title: 'accuracy', checked: DEFAULT_OPT === 'accuracy' },
],
},
]
export default function QuickstartTraining({ id, title, download = 'base_config.cfg' }) {
const [lang, setLang] = useState(DEFAULT_LANG)
const [components, setComponents] = useState([])
const [[hardware], setHardware] = useState([DEFAULT_HARDWARE])
const [[optimize], setOptimize] = useState([DEFAULT_OPT])
const setters = {
lang: setLang,
components: setComponents,
hardware: setHardware,
optimize: setOptimize,
}
const reco = GENERATOR_DATA[lang] || GENERATOR_DATA.__default__
const content = generator({
lang,
components,
optimize,
hardware,
transformer_data: reco.transformer,
word_vectors: reco.word_vectors,
has_letters: reco.has_letters,
})
const rawStr = content.trim().replace(/\n\n\n+/g, '\n\n')
const rawContent = `${COMMENT}\n${rawStr}`
const displayContent = highlightCode('ini', rawContent)
.split('\n')
.map(line => (line.startsWith('#') ? `<span class="token comment">${line}</span>` : line))
.join('\n')
return (
<StaticQuery
query={query}
render={({ site }) => {
const langs = site.siteMetadata.languages
DATA[0].dropdown = langs
.map(({ name, code }) => ({
id: code,
title: name,
}))
.sort((a, b) => a.title.localeCompare(b.title))
return (
<Quickstart
id="quickstart-widget"
Container="div"
download={download}
rawContent={rawContent}
data={DATA}
title={title}
id={id}
setters={setters}
hidePrompts
small
codeLang="ini"
>
{htmlToReact(displayContent)}
</Quickstart>
)
}}
/>
)
}
const query = graphql`
query QuickstartTrainingQuery {
site {
siteMetadata {
languages {
code
name
}
}
}
}
`