file_path stringlengths 3 280 | file_language stringclasses 66 values | content stringlengths 1 1.04M | repo_name stringlengths 5 92 | repo_stars int64 0 154k | repo_description stringlengths 0 402 | repo_primary_language stringclasses 108 values | developer_username stringlengths 1 25 | developer_name stringlengths 0 30 | developer_company stringlengths 0 82 |
|---|---|---|---|---|---|---|---|---|---|
js/fix-toc.js | JavaScript | // fix some issues in TOC generated by Hugo (Blackfriday or Goldmark)
(function() {
const toc = document.getElementById('TableOfContents');
if (!toc) return;
// fix header ids and a hrefs if a header contains a link
toc.querySelectorAll('a[href^="#"]').forEach((a) => {
let id = a.getAttribute('href').replace(/^#/, '');
const h = document.getElementById(id);
// remove the URL from the id
id = id.replace(/-https?-.+$/, '');
if (h) h.id = id; a.href = '#' + id;
// if the TOC item has two <a>'s, remove the second if the first is empty
if (a.innerHTML !== '') return;
const a2 = a.nextElementSibling;
if (!a2 || a2.tagName !== 'A') return;
a.innerHTML = a2.innerHTML;
a2.remove();
});
// Blackfriday may generate a TOC that has an empty bullet when all headings
// are h2 and there is no h1: https://github.com/gohugoio/hugo/issues/1778#issuecomment-420036687
let li, ul = toc.querySelector('ul');
if (ul.childElementCount !== 1) return;
li = ul.firstElementChild;
if (li.tagName !== 'LI') return;
// remove <ul><li></li></ul> where <ul> only contains one <li>
ul.outerHTML = li.innerHTML;
})();
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/fold-details.js | JavaScript | // fold elements with <details>: https://yihui.org/en/2023/09/code-folding/
(d => {
const cfg = d.currentScript?.dataset, cls = 'folder'; let status = !!cfg?.open;
d.querySelectorAll(cfg?.selector || 'pre:not([class])>code[class],pre[class]').forEach(el => {
const s1 = d.createElement('details'), s2 = d.createElement('summary');
s1.className = cls; s1.open = status;
s2.innerText = (cfg?.label || 'Details') + (cfg?.tagName ? ` <${el.tagName}>` : '');
// special case: for <code>, put its parent <pre> inside <details>
if (el.tagName === 'CODE' && el.parentNode.tagName === 'PRE') el = el.parentNode;
s1.append(s2);
el.before(s1);
s1.append(el);
});
// add a button to the page to toggle all <details> elements
if (!cfg?.hasOwnProperty('button')) return;
const p = d.querySelector(cfg.parent);
let btn = d.querySelector(cfg.button);
if (!btn && !p) return; // must provide either a button or a container
if (!btn) {
btn = d.createElement('button');
btn.id = 'toggle-all';
p.insertAdjacentElement(cfg.position || 'afterbegin', btn);
}
const l1 = cfg.buttonLabel || 'Show Details', l2 = cfg.buttonLabel2 || 'Hide Details';
function setText() {
btn.innerText = status ? l2 : l1;
}
setText();
btn.onclick = (e) => {
status = !status;
d.querySelectorAll(`details.${cls}`).forEach(el => {
el.open = status;
});
setText();
};
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/fold-output.js | JavaScript | // toggle output of source code by clicking on source code
(() => {
const blocks = [];
document.querySelectorAll('pre>code[class^=language-],pre[class^=language-]').forEach(el => {
// if <code> is selected, use its parent
if (el.tagName === 'CODE' && el.parentNode.tagName === 'PRE') el = el.parentNode;
blocks.indexOf(el) < 0 && blocks.push(el);
});
let s1, s2; // local and global show/hide status
blocks.forEach(el => {
el.onclick = e => {
let sb = el.nextElementSibling;
while (sb && blocks.indexOf(sb) < 0) {
s1 = s2; // use global status if exists
if (s1 === undefined) s1 = sb.style.display === '';
sb.style.display = s1 ? 'none' : '';
sb = sb.nextElementSibling;
}
// Alt/Ctrl + Click to toggle all output
(e.altKey || e.ctrlKey) && (s2 = s1, blocks.forEach(b => b !== el && b.click()), s2 = undefined);
s1 = undefined;
};
});
})();
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/fullwidth.js | JavaScript | // look for overflowed <pre> and <table>, and assign .fullwidth class to them
document.querySelectorAll('pre,table,#TableOfContents').forEach(node => {
function fullwidth(el) {
el.classList.add('fullwidth');
}
// skip if already in .fullwidth container
if (node.closest('.fullwidth')) return;
switch (node.tagName) {
case 'PRE':
const el = node.firstElementChild;
el?.tagName === 'CODE' && el.scrollWidth > el.offsetWidth && fullwidth(el.parentNode);
break;
case 'TABLE':
const p = node.parentElement;
p && p.offsetWidth < node.offsetWidth && fullwidth(node);
break;
default:
// assume it's #TableOfContents for now
node.querySelectorAll('a').forEach(a => {
// if a TOC line is wrapped, make TOC full-width
!node.classList.contains('fullwidth') && a.getClientRects().length > 1 && fullwidth(node);
});
}
});
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/fuse-search.js | JavaScript | // perform searching via Fuse.js with data from /index.json
(d => {
const input = d.querySelector('#search-input'),
output = d.querySelector('.search-results');
if (!input || !output) return;
const ds = input.dataset;
// load search index for Fuse.js
let fuse;
input.addEventListener('focus', e => {
if (fuse) return;
input.placeholder = ds.infoInit ||
'Loading search index... Please hold on.';
const request = new XMLHttpRequest();
request.responseType = 'json';
request.addEventListener('load', e => {
const res = request.response;
if (!res || res.length === 0) {
input.placeholder = ds.infoFail ||
'Failed to load search index!';
return;
}
input.placeholder = ds.infoOk || 'Type to search:';
input.focus();
fuse = new Fuse(res, {
keys: [{name: 'title', weight: 5}, 'content'],
useExtendedSearch: true,
includeMatches: true,
ignoreLocation: true,
threshold: 0.1
});
}, false);
request.open('GET', ds.indexUrl || '/index.json');
request.send(null);
});
// highlight the keyword of the maximum length in content
function highlight(res, key, len) {
let indices;
for (let m of res.matches) {
if (m.key === key) indices = m.indices;
}
const text = res.item[key];
if (!indices) return text.substr(0, len);
let p, pair, k = 0, n = Math.ceil(len / 2);
while (pair = indices.shift()) {
if (pair[1] - pair[0] >= k) {
p = pair;
k = p[1] - p[0];
}
}
return (p[0] - n > 0 ? '[...] ' : '') + text.substring(p[0] - n, p[0]) +
'<b>' + text.substring(p[0], p[1] + 1) + '</b>' +
text.substring(p[1] + 1, p[1] + 1 + n) +
(p[1] + 1 + n < text.length ? ' [...] ' : '');
}
// debounce the search for better performance and UX
function debounce(fn, delay) {
let timeout;
return function(...args) {
clearTimeout(timeout);
timeout = setTimeout(() => fn(...args), delay);
};
}
const len = ds.textLength || 300, // number of chars for each search result
lim = ds.limit || 50, // max number of search results
delay = ds.delay || 500, // search delay after input
tpl = output.firstElementChild.cloneNode(true); // search result template
output.innerHTML = '';
function search() {
if (!fuse) return;
output.innerHTML = '';
// display search results in <section> and highlight keywords
for (let res of fuse.search(input.value, {'limit': lim})) {
const sec = tpl.cloneNode(true);
const a = sec.querySelector('a');
a.href = res.item.uri;
a.innerHTML = highlight(res, 'title', len);
sec.querySelector('.search-preview').innerHTML = highlight(res, 'content', len);
output.appendChild(sec);
}
}
const isMobi = /Mobi/i.test(navigator.userAgent);
input.addEventListener(isMobi ? 'change' : 'input', isMobi ? search : debounce(search, delay));
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/g2-column.js | JavaScript | // support columnar data format in G2
G2.register('data.column', (options) => {
const { value } = options;
return async () => {
let d = value;
// handle URL strings if necessary
if (typeof value === 'string') {
const resp = await fetch(value);
d = await resp.json();
}
const keys = Object.keys(d);
if (keys.length === 0) return [];
// convert to row-based data
return d[keys[0]].map((_, i) =>
keys.reduce((row, key) => (row[key] = d[key][i], row), {})
);
};
});
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/hash-notes.js | JavaScript | // convert <!--# comments --> to <span class="hash-notes">comments</span>
(d => {
function toSpan(el) {
const t = el.textContent, r = /^#[\s\n]+([\s\S]+)[\s\n]+$/;
if (!r.test(t)) return;
d.body.classList.add('has-notes', 'hide-notes');
// use <p> if the comment's parent is not <p>; otherwise use inline <span>
const s = d.createElement(el.parentNode.nodeName === 'P' ? 'span' : 'p');
s.className = 'hash-note';
s.innerText = t.replace(r, '$1');
s.innerHTML = s.innerHTML
.replace(/\[([^\]]+)\]\(([^)]+)\)/g, '<a href="$2">$1</a>')
.replace(/(^|[^"])(https?:\/\/)([-a-zA-Z0-9%._=/\+]+)(#)?([-a-zA-Z0-9%._=\+]+)?/g, '$1<a href="$2$3$4$5">$3$4</a>');
el.before(s);
el.remove();
};
function findComments(el) {
el.childNodes.forEach(node => {
node.nodeType === Node.COMMENT_NODE ? toSpan(node) : findComments(node);
});
};
findComments(d.body);
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/heading-anchor.js | JavaScript | document.querySelectorAll('h1,h2,h3,h4,h5,h6').forEach(h => {
if (h.id && !h.querySelector('.anchor'))
h.insertAdjacentHTML('beforeend', ` <span class="anchor"><a href="#${h.id}"></a></span>`);
});
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/key-buttons.js | JavaScript | (d => {
const a1 = ['Enter', 'Up', 'Down', 'Left', 'Right'];
const a2 = ['↵', '↑', '↓', '←', '→'];
function drawArrows(x) {
a1.map((v, i) => x = x.replace(new RegExp(`>${v}<`, 'g'), ` title="${v + (i ? ' Arrow' : '')}">${a2[i]}<`));
return x;
}
// 1. individual keys; 2. modifiers; 3. normal keys
const k1 = 'Esc|Tab|PageUp|PageDown|Space|Delete|Home|End|PrtScr?|PrintScreen|' +
Array(12).fill().map((v, i) => 'F' + (i + 1)).concat(a1).join('|'),
k2 = 'Ctrl|Control|Shift|Alt|Cmd|Command|fn',
k3 = '[a-zA-Z0-9]|Click',
r1 = new RegExp(`^(${k1}|${k2})$`),
r2 = new RegExp(`^(${k2}) [/+] `),
r3 = new RegExp(`^(${k1}|${k2}|${k3})( [/+] )(.*)`);
d.querySelectorAll(':not(pre) > code').forEach(el => {
if (el.childElementCount > 0) return;
let t = el.innerText;
if (r1.test(t)) {
el.outerHTML = drawArrows(`<kbd>${t}</kbd>`);
return;
}
if (!r2.test(t)) return;
let t2 = ''; t += ' + ';
while (r3.test(t)) {
t2 += t.replace(r3, '<kbd>$1</kbd>$2');
t = t.replace(r3, '$3');
}
if (t === '') el.outerHTML = drawArrows(t2.replace(/ \+ $/, ''));
});
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/load-highlight.js | JavaScript | hljs.configure({languages: []});
hljs.highlightAll ? hljs.highlightAll() : hljs.initHighlightingOnLoad();
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/load-pangu.js | JavaScript | pangu.spacingPage();
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/load-typekit.js | JavaScript | (d => {
// https://www.kirupa.com/html5/detect_whether_font_is_installed.htm
const canvas = d.createElement("canvas"), context = canvas.getContext("2d"),
text = "abcdefghijklmnopqrstuvwxyz0123456789";
context.font = "72px monospace";
const size = context.measureText(text).width;
for (let font of [' SC', ' CN', ' TC', ' TW', '']) {
context.font = `72px 'Source Han Serif${font}', monospace`;
// no need to load TypeKit if Source Hans Serif has been installed
if (context.measureText(text).width != size) return;
}
let config = {kitId: 'kwz5xar', scriptTimeout: 3000, async: true},
h=d.documentElement,t=setTimeout(function(){h.className=h.className.replace(/\bwf-loading\b/g,"")+" wf-inactive";},config.scriptTimeout),tk=d.createElement("script"),f=false,s=d.getElementsByTagName("script")[0],a;h.className+=" wf-loading";tk.src='https://use.typekit.net/'+config.kitId+'.js';tk.async=true;tk.onload=tk.onreadystatechange=function(){a=this.readyState;if(f||a&&a!="complete"&&a!="loaded")return;f=true;clearTimeout(t);try{Typekit.load(config)}catch(e){}};s.parentNode.insertBefore(tk,s)
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/math-code.js | JavaScript | // <code>$math$</code> to \(math\), and <code>$$math$$</code> to $$math$$:
// https://yihui.org/en/2018/07/latex-math-markdown/
document.querySelectorAll(':not(pre) > code:not(.nolatex)').forEach(code => {
// skip <pre> tags and <code> that has children or the nolatex class
if (code.childElementCount > 0) return;
let text = code.textContent;
if (/^\$[^$]/.test(text) && /[^$]\$$/.test(text)) {
text = text.replace(/^\$/, '\\(').replace(/\$$/, '\\)');
code.textContent = text;
}
if (/^\\\((.|\s)+\\\)$/.test(text) || /^\\\[(.|\s)+\\\]$/.test(text) ||
/^\$(.|\s)+\$$/.test(text) ||
/^\\begin\{([^}]+)\}(.|\s)+\\end\{[^}]+\}$/.test(text)) {
code.outerHTML = code.innerHTML; // remove <code></code>
}
});
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/mathjax-config.js | JavaScript | // enable MathJax equation numbering: https://docs.mathjax.org/en/latest/input/tex/eqnumbers.html
(() => {
m = window.MathJax || {}; // make sure not to override existing config
m.tex = m.tex || {};
m.tex.tags = m.tex.tags || 'ams';
window.MathJax = m;
})();
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/no-highlight.js | JavaScript | document.querySelectorAll('pre > code:only-child').forEach(code => {
const cls = code.className;
if (cls === '' || cls === 'hljs') {
code.className = 'nohighlight';
} else if (/^language-/.test(cls) && !/hljs/.test(cls)) {
code.className += ' hljs';
}
})
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/number-captions.js | JavaScript | // number figure and table captions
// config options via data-foo attributes of this <script>:
// * data-colon: the colon character (':' by default);
// * data-fig-label: label for figure captions ('Figure ' by default)
// * data-tab-label: label for table captions ('Table ' by default)
(d => {
const cfg = d.currentScript?.dataset, colon = cfg?.colon || ':';
function NUM(target, label) {
d.querySelectorAll(target).forEach((el, i) => {
// do not number it again if already numbered
el.querySelector('.cap-num') ||
el.insertAdjacentHTML('afterbegin', `<span class="cap-num">${label}${i + 1}${colon}</span> `);
});
}
NUM('figure > figcaption, .figure > p.caption, .float > .figcaption', cfg?.figLabel || 'Figure ');
NUM('table > caption', cfg?.tabLabel || 'Table ');
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/number-sections.js | JavaScript | // add section numbers to headings
(d => {
// find the body of the article
let b;
['.article', '.body', 'article', 'body'].forEach(s => {
if (!b) b = d.querySelector(s);
});
const hs = b.querySelectorAll('h1, h2, h3, h4, h5, h6');
if (hs.length === 0) return;
// normalize Pandoc's .header-section-number class to .section-number
b.querySelectorAll('span.header-section-number').forEach(el => {
el.classList.add('section-number');
});
// already numbered?
if (b.querySelector('span.section-number')) {
// avoid Pandoc's numbering from 0 (e.g., 0.1, 0.1.1, 0.2, ...) when top-level heading is not h1
b.querySelectorAll('span.section-number').forEach(s => {
s.innerText = s.innerText.replace(/^(0\.)+/, '');
});
return;
}
let t0 = 0, t1, dict = [0, 0, 0, 0, 0, 0];
// generate section numbers x.x.x
function number_section(i) {
dict[i]++;
const n = dict.join('.').replace(/^(0\.)+|(\.0)+$/g, '').replace(/^([0-9]+)$/, '$1.');
return `<span class="section-number">${n}</span> `;
};
hs.forEach(h => {
// header level: <hN> -> N
t1 = parseInt(h.tagName.replace(/^h/i, ''));
// when moving to a higher-level heading, reset lower-level counters to 0
if (t1 < t0) {
for (let j = t1; j < dict.length; j++) {
dict[j] = 0;
}
}
h.insertAdjacentHTML('afterbegin', number_section(t1 - 1));
t0 = t1;
});
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/ol-id.js | JavaScript | // add ID to <ol> items so that they can be referenced via URL hashes like #li-N
((d) => {
// add IDs to top-level <ol>s
const ols = d.querySelectorAll(':not(li) > ol');
ols.forEach((ol, i) => {
ol.querySelectorAll(':scope > li').forEach((li, j) => {
if (!li.id) li.id = 'li-' + (ols.length > 1 ? i + 1 + '-' : '') + (j + 1);
});
});
// add IDs to all <ol>s
d.querySelectorAll('ol').forEach((ol, i) => {
let l = ol.parentNode, id, p; // p: ID prefix
if (l?.tagName === 'LI') id = l.id;
p = (id ? id : 'li-' + (i + 1)) + '-';
ol.querySelectorAll(':scope > li').forEach((li, j) => {
if (!li.id) li.id = p + (j + 1);
// Alt + Click => adding hash to URL
li.addEventListener('click', e => {
e.altKey && (location.hash = li.id, e.stopPropagation());
});
});
});
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/pages.js | JavaScript | // move elements into page boxes such that each box contains as many elements as
// possible and will not exceed the given size (e.g. A4 paper)
(d => {
function $(s, el = d) { return el?.querySelector(s); }
function $$(s, el = d) { return el ? el.querySelectorAll(s) : []; }
function nChild(el) { return el.childElementCount; }
const tpl = d.createElement('div'), book = $$('h1').length > 1, boxes = [],
fr_tag = ['TABLE', 'UL', 'OL', 'BLOCKQUOTE'],
fr_cls = 'pagesjs-fragmented', fr_1 = 'fragment-first', fr_2 = 'fragment-last',
tb = ['top', 'bottom'].map(i =>
parseFloat(getComputedStyle(d.documentElement).getPropertyValue(`--paper-margin-${i}`)) || 0
); // top/bottom page margin
tpl.className = 'pagesjs-page';
tpl.innerHTML = `<div class="pagesjs-header"></div>
<div class="pagesjs-body"></div>
<div class="pagesjs-footer"></div>`;
let box, box_body, box_cls = [], H, H_min, h_code, l_code = [];
function newPage(el) {
el && !$('.pagesjs-body', el) && el.insertAdjacentHTML('afterbegin', tpl.innerHTML);
box = el || tpl.cloneNode(true); box_body = box.children[1];
box.classList.add(...box_cls);
boxes.includes(box) || boxes.push(box); // store new pages in boxes
return box;
}
// start the next page and finish current page
function nextPage(el, callback) {
const cur = box; cur.after(newPage(el)); callback && callback(); finish(cur);
}
// compute page numbers and temporarily remove the box
function finish(box) {
const h = box.scrollHeight;
if (h > H && !box.dataset.pagesOffset) {
const n = calcPages(box, h);
if (n > 1) box.dataset.pagesOffset = n;
}
box.remove();
}
function removeBlank(el) {
if (!el || el.tagName === 'BODY') return false;
// for <p>, don't treat it as empty unless its HTML is empty
const v = !(el.tagName === 'P' ? el.innerHTML : el.innerText).trim();
v && el.remove();
return v;
}
function fill(el) {
// if the element is already a page, just use it as the box
if (el.classList.contains('pagesjs-page')) {
nextPage(el, () => nChild(el) > 3 && (
// if current element is not empty, fill its content into the box
box_body.append(...[...el.children].slice(3)),
// TODO: should we fragment this page if it's too long?
nextPage() // create a new empty page
));
} else {
if (el.innerText.trim() && H - box.scrollHeight < H_min) nextPage();
box_body.append(el);
if (box.scrollHeight > H) {
// temporarily remove el from DOM if it can be fragmented, otherwise
// simply move it to the next page
breakable(el) ? (el.tagName !== 'P' && el.remove(), fragment(el)) :
nextPage(0, () => box_body.append(el));
} else {
// TODO: remove possibly duplicated citations: .citation + div > [id^="ref-"]
}
}
}
let fill_num; // record the number of lines filled last time
function fillCode(el, i) {
el.innerHTML = l_code.slice(0, i).join('\n');
fill_num = i;
}
function breakable(el) {
l_code = [];
const t = el.tagName, c = el.firstElementChild;
if (t === 'P' || fr_tag.includes(t)) return true;
if (t === 'DIV') {
const cs = el.children;
return (cs.length === 1 && fr_tag.includes(c?.tagName)) ||
[...cs].filter(c => c.tagName === 'TABLE').length;
}
if (t !== 'PRE') return false;
if (c?.tagName !== 'CODE') return false;
// store all lines in l_code (TODO: ensure complete tags on each line)
l_code = c.innerHTML.replace(/\n$/, '').split('\n');
const n_code = l_code.length;
if (n_code < 2) return false;
h_code = c.offsetHeight / n_code; // approx line height
c.innerHTML = ''; // temporarily empty <code>; will use l_code
return true;
}
// break elements that are relatively easy to break (such as <ul>)
function fragment(el, container, parent) {
let cls = el.classList;
const tag = el.tagName, frag = cls.contains(fr_cls);
parent ? cls.add(fr_cls) : (frag ? cls.remove(fr_1) : cls.add(fr_cls, fr_1));
let el2 = el.cloneNode(); // shallow clone (wrapper only)
(container || box_body).append(el2);
if (tag === 'P') {
// fragmentation occurs in el instead of the clone el2, so swap them
splitP(el, el2) || ([el, el2] = [el2, el], cls = el.classList);
}
const prev = el2.previousElementSibling || container?.previousElementSibling;
function fragChildren(action) {
for (let item of [...el.children]) {
el2.append(item);
if (box.scrollHeight > H) {
action(item); break;
}
}
}
if (tag === 'DIV') {
// fragment <div>'s children (e.g., #TOC > ul)
fragChildren(item => {
// fragment item if it can be further fragmented, otherwise put it back
el.prepend(item);
fr_tag.includes(item.tagName) ? fragment(item, el2, el) : nChild(el2) && nextPage();
});
} else if (tag === 'PRE') {
fragment(el.firstElementChild, el2, el);
} else if (tag === 'CODE') {
// split lines in <code> and try to move as many lines into el2 as possible
const i = splitCode(el2);
// i == 0 means not enough space to split code on current page
i === fill_num || fillCode(el2, i); l_code.splice(0, i);
if (i > 0) {
l_code.join('').trim() === '' ? (l_code = []) : nextPage();
}
} else if (tag === 'TABLE') {
// when el has no rows left and el2 is not empty, clear el
const has_rows = splitTable(el, el2, prev);
el2.innerHTML && (has_rows ? nextPage() : (el.innerHTML = ''));
} else {
// keep moving el's first item to el2 until page height > H
fr_tag.slice(1).includes(tag) && fragChildren(item => {
// move item back to el if the clone el2 is not the only element on page or has more than one child
(prev || nChild(el2) > 1) && el.prepend(item);
// update the start number of <ol> on next page
tag === 'OL' && (el.start += nChild(el2));
// don't open new page if el2 is empty (will open one below when testing el2_empty)
nChild(el2) && nextPage();
});
}
const el_empty = !l_code.length && removeBlank(el), el2_empty = removeBlank(el2);
// add/remove the fragment-* class and exit if el has become empty
if (el_empty) {
const cls2 = el2.classList;
if (parent) {
container.classList.contains(fr_1) && cls2.remove(fr_cls);
} else {
cls2.contains(fr_1) ? cls2.remove(fr_cls, fr_1) : cls2.add(fr_2);
}
return;
}
// if el2 is empty, it means nothing in el fits the box; we have to start a new box
if (el2_empty) {
cls.remove(fr_cls, fr_1); parent || nextPage();
}
// keep fragmenting the remaining top-level el when el2 is not empty or not first element
if ((!el2_empty || prev) && !parent) fragment(el);
}
// split table rows
function splitTable(el, el2, prev) {
const tb = el.tBodies[0], tb2 = tb.cloneNode(), rows = [...tb.rows], th = el.tHead;
el2.append(tb2);
// copy table header and footer
[th, el.tFoot].forEach(t => t && el2.append(t.cloneNode(true)));
for (let i = 0; i < rows.length; i++) {
const row = rows[i];
tb2.append(row);
if (box.offsetHeight > H) {
if (i > 0 || prev) tb.prepend(row);
// clear the clone if current page can't fit even one row
if (i === 0 && prev) el2.innerHTML = '';
break;
}
}
return tb.rows.length;
}
// figure out how many lines can fit the box via bisection
function splitCode(el) {
let i = i1 = 1, n = l_code.length, i2 = n + 2;
const sols = []; // solutions tried
while (i2 > i1 + 1) {
fillCode(el, i);
const delta = H - box.offsetHeight;
if (delta === 0) return i;
if (delta < 0) {
if (i <= 1) return 0;
i2 = i;
} else {
if (i >= n) return i;
i1 = i;
}
sols.push(i);
// estimate the number of (more or less) lines needed
const i3 = i + Math.round(delta / h_code);
// if a solution has been tried, shorten step and (in/de)crement by 1
i = sols.includes(i3) ? i + (delta > 0 ? 1 : -1) : i3;
(delta > 0 && i >= n) && (i2 = n + 2, i = n); // solution may be n
}
return i1;
}
// split <p> by testing if a range fits the current box
function splitP(el, el2) {
if (!el.parentNode) {
box_body.append(el); // move el into DOM to measure chars if removed
// see if we don't need to split it now
if (box.scrollHeight <= H) return;
}
const r = d.createRange(), ends = [{node: el, i: 0}];
// find the break position of each line (exclude block elements like footnotes)
const walker = d.createTreeWalker(el, NodeFilter.SHOW_TEXT | NodeFilter.SHOW_ELEMENT);
let node, prev;
function collectEnds(el, i) {
const rect = el.getBoundingClientRect();
// if the previous el is at top-right of current el, assume line
// ends before current el (TODO: how about RTL languages?)
prev && prev.bottom <= rect.top && prev.right > rect.left && ends.push({node, i});
prev = rect;
}
while (node = walker.nextNode()) {
const t = node.tagName;
if (t) {
if (['DIV', 'MJX-CONTAINER'].includes(t) || (t === 'SPAN' && $('.katex', node))) {
node = walker.nextSibling(); // skip DIVs (footnotes) and math
if (!node) break;
}
if (node.firstChild) continue; // for element nodes, traverse to bottom
}
if (node.tagName) {
collectEnds(node, -1);
} else {
const txt = node.textContent;
if (txt.trim()) for (let i = 0; i < txt.length; i++) {
r.setStart(node, i); r.setEnd(node, i + 1); collectEnds(r, i);
}
}
}
if (ends.length < 2) {
el.remove(); return 1; // single-line paragraph
}
el2.remove();
// remove lines from the end of paragraph
for (let i = ends.length - 1; i >= 0; i--) {
const loc = ends[i];
loc.i < 0 ? r.setStartBefore(loc.node) : r.setStart(loc.node, loc.i);
r.setEnd(el, el.childNodes.length);
el2.prepend(r.extractContents());
const last = el.lastChild; // strip trailing empty tags left by range extraction
last?.innerHTML === '' && last.remove();
if (i > 0 && box.scrollHeight <= H) {
nextPage(); break;
}
}
}
// use data-short-title of a header if exists, and fall back to inner text
function shortTitle(h) {
return h && (h.dataset.shortTitle || h.innerText);
}
const main = shortTitle($('h1.title, .frontmatter h1, .title, h1')), // main title
ps = (book ? 'h1' : 'h2') + ':not(.frontmatter *)'; // page title selector
// calculate how many new pages we need for overflowed content (this is just
// an estimate; if not accurate, use <div class="pagesjs-page" data-pages-offset="N">
// to provide a number manually)
function calcPages(box, h) {
let n = +box.dataset.pagesOffset;
if (n) return n;
n = Math.ceil(h/H);
if (n <= 1) return n;
// consider top/bottom page margin and table headers (which may be repeated on each page)
const m = tb.concat([...$$('thead', box)].map(el => +el.offsetHeight)).reduce((m1, m2) => m1 + m2);
if (!m) return n;
function nPages() { return Math.ceil((h + (n - 1) * m)/H); }
let n2 = nPages();
while (n2 > n) {
n = n2; n2 = nPages();
}
return n;
}
function paginate() {
// we need to wait for all resources to be fully loaded before paginating
if (d.readyState !== 'complete') return addEventListener('load', paginate);
const cls = d.body.classList;
if (cls.contains('pagesjs')) return; // already paginated
dispatchEvent(new Event('pagesjs:before'));
cls.add('pagesjs');
d.body.insertAdjacentElement('afterbegin', newPage());
H = box.clientHeight || window.innerHeight; // use window height if box height not specified
// remove possible classes on TOC/footnotes that we don't need for printing
$$(':is(#TOC, .footnotes, .chapter-before, .chapter-after):is(.side-left, .side-right).side').forEach(el => {
el.classList.remove('side', 'side-left', 'side-right');
});
cls.add('pagesjs-filling');
// test how much space a single-line paragraph needs
const p = d.createElement('p'), H0 = box.scrollHeight;
p.innerText = 'A'; box_body.append(p);
H_min = box.scrollHeight - H0; p.remove();
// add dot leaders to TOC
$$('#TOC a[href^="#"]').forEach(a => {
const s = d.createElement('span'); // move TOC item content into a span
s.className = 'toc-text'; a.append(s);
let c; while (c = s.previousSibling) {
// exclude section number spans
if (c.classList?.contains('section-number')) break; s.prepend(c);
}
a.dataset.pageNumber = '000'; // placeholder for page numbers
});
// temporarily move all elements out of DOM (to speed up rendering single pages)
const els = [];
$$('.body').forEach(el => {
// move <style>/<link> into <head> so styles can be applied globally
const ch = [...el.children]
.filter(el => !['STYLE', 'LINK'].includes(el.tagName) || d.body.prepend(el));
els.push(ch); ch.forEach(el => el.remove());
});
// iteratively add elements to pages
$$('.frontmatter, .abstract, #TOC:not(.chapter-toc)').forEach(el => {
(fill(el), book && nextPage());
});
$$('.body').forEach((el, i) => {
// preserve book chapter classes if exist
box_cls = ['chapter', 'appendix'].filter(i => el.classList.contains(i));
book && (box.innerText === '' ? newPage(box) : nextPage());
els[i].forEach(fill);
// clean up container and self if empty
removeBlank(el.parentNode); removeBlank(el);
});
finish(box); // finish the last box
cls.remove('pagesjs-filling');
// add page number, title, etc. to data-* attributes of page elements
let page_title, i = 0;
boxes.forEach(box => {
if (book) {
if ($('.frontmatter', box)) return; // skip book frontmatter page
$(ps, box) && (page_title = ''); // empty title for first page of chapter
}
const N = +box.dataset.pagesOffset || 1;
if (N > 1) box.classList.add('page-multiple');
i += N;
box.classList.add(`page-${i % 2 === 0 ? 'even' : 'odd'}`);
const info = {
'pageNumber': i, 'mainTitle': main, 'pageTitle': page_title
};
[box.children[0], box.children[2]].forEach(el => {
for (const key in info) info[key] && (el.dataset[key] = info[key]);
});
// find page title for next page
page_title = shortTitle([...$$(ps, box)].pop()) || page_title;
let ft; // first footnote on page
// move all footnotes after the page body
$$('.footnotes', box).forEach((el, i) => {
i === 0 ? (ft = el, box.children[1].after(el)) : (ft.append(...el.children), el.remove());
});
});
// unhide all pages
d.body.prepend(...boxes);
// add page numbers to TOC with data-* attributes
$$('#TOC a[href^="#"]').forEach(a => {
const id = CSS.escape(a.getAttribute('href').replace(/^#/, '')),
p = $(`.pagesjs-page:has(#${id}) .pagesjs-header`);
a.dataset.pageNumber = p ? p.dataset.pageNumber : '';
});
dispatchEvent(new Event('pagesjs:after'));
}
addEventListener('beforeprint', paginate);
// use query param ?paged=1 to indicate pagination (press p to toggle)
const SP = new URLSearchParams(location.search);
SP.get('paged') && paginate();
addEventListener('keypress', e => {
if (e.key === 'p') {
if (SP.get('paged')) {
SP.delete('paged'); location.href = location.pathname + (SP.size ? `?${SP}` : '');
} else {
paginate();
SP.set('paged', 1); history.replaceState({}, '', `${location.pathname}?${SP}`);
}
}
});
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/post-nav.js | JavaScript | // navigate to previous/next posts by Left/Right arrows, and Alt + <-/-> for back/forward
(d => {
const a1 = d.querySelector('.nav-prev > a'), a2 = d.querySelector('.nav-next > a');
d.addEventListener('keyup', function(e) {
if (e.target.nodeName.toUpperCase() != 'BODY') return;
let u;
if (e.key === 'ArrowLeft') {
e.altKey ? history.back() : (a1 && (u = a1.href));
} else if (e.key == 'ArrowRight') {
e.altKey ? history.forward() : (a2 && (u = a2.href));
}
if (u) window.location = u;
});
const us = d.querySelectorAll('.unlist');
if (us.length === 0) return;
const s = sessionStorage.getItem('hide-notes');
if (s !== null) return us.forEach(u => u.classList.remove('unlist'));
if (a1 && a2) {
window.location = d.referrer === a2.href ? a1.href : a2.href;
}
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/render-katex.js | JavaScript | // support \ref \eqref \label for KaTeX, based on https://github.com/KaTeX/KaTeX/issues/2003
(d => {
renderMathInElement(d.body, {
strict: false, throwOnError: false,
trust: context => ['\\href', '\\htmlId', '\\htmlClass'].includes(context.command),
macros: {
'\\eqref': '\\htmlClass{ktx-eqref}{\\href{###1}{(\\text{#1})}}',
'\\ref': '\\htmlClass{ktx-ref}{\\href{###1}{\\text{#1}}}',
'\\label': '\\htmlClass{ktx-label}{\\htmlId{#1}{}}'
}
});
function $(s, el = d) { return el.querySelector(s); }
function $$(s, el = d) { return el.querySelectorAll(s); }
const xrefs = $$('.katex:has(:is(.ktx-ref, .ktx-eqref))');
if (!xrefs.length) return;
const M = {}; // map equation labels to numbers
let n = 0;
// scan all display expressions for labels and tags
$$('.katex-display').forEach(el => {
const s = '.ktx-label > [id]', lab = $(s, el);
if (!lab) return; // no labels found
// find the common ancestor of all labels and the label of each row of equation
const ids = [...$$(':scope > [style]', lab.offsetParent.parentNode)].map(el => {
return $(s, el)?.id || '';
});
// find all tags
const tags = [...$$('.tag > .vlist-t > .vlist-r > .vlist > [style]', el)].map(tag => {
// if tag is automatically generated by CSS counter, we have to compute it
// manually because there is no way to access CSS counters from JS
return $('.eqn-num', tag) ? `(${++n})` : tag.innerText.trim();
});
if (ids.length === tags.length) {
ids.forEach((id, i) => id && (M[id] = tags[i]));
} else {
console.warn('labels and tags differ in length in ', el, ids, tags);
}
});
// resolve innerText of cross-ref links
function resolveRefLink(a, paren) {
const id = a.getAttribute('href').replace(/^#/, ''), tag = M[id];
a.innerText = tag ? (paren ? tag : tag.replace(/^\(|\)$/g, '')) : '???';
a.classList.add(`cross-ref-eq${paren ? 'n' : ''}`);
}
xrefs.forEach(el => {
const a = $('a', el);
if (!a) return;
const paren = a.parentNode.classList.contains('ktx-eqref'), p = el.parentNode;
p.after(a); p.remove(); // remove KaTeX's HTML for links to make their style consistent with surrounding text
resolveRefLink(a, paren);
});
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/revdep-log-reader.js | JavaScript | // the CRAN revdep check log can be extremely lengthy, so I wrote this script to
// make the log easier to read (using one tab for one package/problem)
(d => {
const entries = d.body.innerText
.replace(/^(.|\n)*?(?=Package:)/, '')
.split(/(^|\n)Package: /)
.filter(x => x.trim())
.map(x => `<div class="tab-link">${x.replace(/(.*?)\n/, '$1 <a href="https://cran.r-project.org/web/checks/check_results_$1.html" style="text-decoration: none;" target="_blank">↝</a></div><div class="tab-pane"><pre style="white-space: pre-wrap;">')}</pre></div>`)
.join('\n');
d.body.innerHTML = `<div class="tabset">${entries}</div>`;
d.head.insertAdjacentHTML('beforeend', '<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@xiee/utils/css/tabsets.min.css">');
const s = d.createElement('script');
s.src = 'https://cdn.jsdelivr.net/npm/@xiee/utils/js/tabsets.min.js';
d.body.insertAdjacentElement('beforeend', s);
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/right-quote.js | JavaScript | // originally to right-align a quote footer if it starts with ---; now it just
// right-align all paragraphs that start with em-dashes
[...document.getElementsByTagName('p')].forEach(p => {
if (/^(—|―|---)/.test(p.textContent)) p.style.textAlign = 'right';
});
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/sidenotes.js | JavaScript | // move footnotes (ids start with fn) and citations (ids start with ref-) to sidenotes
(d => {
d.querySelectorAll('.footnotes > ol > li[id^="fn"], #refs > [id^="ref-"]').forEach(el => {
// find <a> that points to note id in body
const h = `a[href="#${el.id}"]`;
d.querySelectorAll(`${h} > sup, sup > ${h}, .citation > ${h}, ${h}.citation`).forEach(a => {
const a2 = a.parentNode;
(a.tagName === 'A' ? a : a2).removeAttribute('href');
const s = d.createElement('div'); // insert a side div next to a2 in body
s.className = 'side side-right footnotes';
if (/^fn/.test(el.id)) {
s.innerHTML = el.innerHTML;
// add footnote number
s.firstElementChild.insertAdjacentHTML('afterbegin', `<span class="bg-number">${a.innerText}</span> `);
s.querySelector('a[href^="#fnref"]')?.remove(); // remove backreference
} else {
s.innerHTML = el.outerHTML;
}
while (s.lastChild?.nodeName === '#text' && !s.lastChild.textContent.trim()) {
s.lastChild.remove();
}
// remove fullwidth classes if present (because they cannot be used in the margin)
s.querySelectorAll('.fullwidth').forEach(el => el.classList.remove('fullwidth'));
// insert note after the parent of <a> unless it contains class 'citation'
const a3 = a.classList.contains('citation') ? a : a2;
a3.after(s);
a3.classList.add('note-ref');
el.remove();
});
});
// remove the footnote/citation section if it's empty now
d.querySelectorAll('.footnotes, #refs').forEach(el => {
el.innerText.trim() || el.remove();
});
// also add side classes to TOC
d.getElementById('TOC')?.classList.add('side', 'side-left');
// if a sidenote collapses with any fullwidth element, remove the side class
const sides = d.querySelectorAll('.side.side-right, .side.side-left'), fulls = [];
d.querySelectorAll('.fullwidth').forEach(el => {
fulls.push([el, el.getBoundingClientRect()]);
});
// add a class to document body if it has sidenotes
sides.length && d.body.classList.add('has-sidenotes');
sides.forEach(s => {
const r1 = s.getBoundingClientRect();
for (let f of fulls) {
const r2 = f[1];
if (!(r1.right < r2.left || r1.left > r2.right || r1.bottom < r2.top || r1.top > r2.bottom)) {
f[0].classList.remove('fullwidth');
}
}
});
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/snap.js | JavaScript | (function(d) {
let p = d.body; // container of slides; assume <body> for now
const s1 = ':scope > hr:not([class])', s2 = ':scope > h2';
// find a container that has at least n "slides"
function findContainer(s, n = 1) {
if (p.querySelectorAll(s).length >= n) return true;
// if body doesn't contain headings or <hr>s, look into children
for (let i = 0; i < p.children.length; i++) {
if (p.children[i].querySelectorAll(s).length >= n) {
p = p.children[i]; break;
}
}
return false;
}
function newEl(tag, cls) {
const el = d.createElement(tag);
if (cls) el.className = cls;
return el;
}
if (!findContainer(s1, 3)) {
// if not enough <hr>s found in children; look for <h2> instead
if (p.tagName === 'BODY') {
// not enough h2 found, this page is not appropriate for slides
if (!findContainer(s2) && p.tagName === 'BODY') return;
p.querySelectorAll(s2).forEach(h2 => h2.before(newEl('hr')));
}
}
p.classList.add('slide-container');
// add 'slide' class to the frontmatter/abstract divs and toc
['.frontmatter', '.abstract', '#TOC'].forEach(sel => {
const el = d.body.querySelector(sel);
if (!el) return;
if (sel === '.frontmatter') {
el.classList.add('slide');
} else {
const s = newSlide(); el.before(s); s.append(el);
}
});
function newSlide(s) {
return (s?.innerHTML === '') ? s : newEl('div', 'slide');
}
function isSep(el) {
return el.tagName === 'HR' && el.attributes.length === 0;
}
let el = p.firstElementChild; isSep(el) && el.remove();
el = p.firstElementChild; if (!el) return;
let s = newSlide(); el.before(s);
while (true) {
let el = s.nextSibling;
if (!el) break;
// remove slide separators (<hr>) and create new slide
if (isSep(el)) {
s = newSlide(s);
el.before(s); el.remove();
} else if (el.classList?.contains('slide')) {
s = newSlide(s);
el.after(s);
} else {
s.append(el);
}
}
function setAttr(el, attr) {
const m = newEl('div');
m.innerHTML = `<div ${attr}></div>`;
const attrs = m.firstElementChild.attributes;
for (const a of attrs) {
el.setAttribute(a.name, a.value);
}
m.remove();
}
function reveal(el) {
setTimeout(() => el?.scrollIntoView(), 100);
}
const dE = d.documentElement, dC = d.body.classList;
const slides = d.querySelectorAll('div.slide'), N = slides.length,
tm = d.querySelector('span.timer'), fn = d.querySelector('.footnotes');
slides.forEach((s, i) => {
// slide header, main body, and footer
const header = newEl('div', 'header'), main = newEl('div', 'main'), footer = newEl('div', 'footer');
main.append(...s.childNodes);
s.append(main);
s.insertAdjacentElement('afterbegin', header);
s.insertAdjacentElement('beforeend', footer);
// append footnotes
if (fn) s.querySelectorAll('.footnote-ref > a[href^="#fn"]').forEach(a => {
const li = fn.querySelector('li' + a.getAttribute('href'));
if (!li) return;
let f = s.querySelector('section.footnotes');
if (!f || f.contains(li)) {
f = newEl('section', 'footnotes'); footer.before(f);
}
f.append(li);
li.firstElementChild?.insertAdjacentHTML('afterbegin', `[${a.innerHTML}] `);
li.outerHTML = li.innerHTML;
});
// add a timer
footer.append(tm ? tm.cloneNode() : newEl('span', 'timer'));
// add page numbers
const n = newEl('span', 'page-number');
n.innerText = i + 1 + '/' + N;
n.onclick = e => location.hash = i + 1;
footer.append(n);
// apply slide attributes in <!--# -->
for (const node of main.childNodes) {
if (node.nodeType !== Node.COMMENT_NODE) continue;
let t = node.textContent;
if (!/^#/.test(t)) continue;
t = t.replace(/^#/, '');
const r = /[\s\n]class="([^"]+)"/, m = t.match(r);
if (m) {
t = t.replace(r, '').trim();
s.className += ' ' + m[1];
}
if (t) setAttr(s, t);
break;
}
s.addEventListener('click', e => {
(e.altKey || e.ctrlKey) && (toggleView(e), reveal(e.target));
});
});
[...d.querySelectorAll('a.footnote-backref'), fn, tm].forEach(el => el?.remove());
const tms = d.querySelectorAll('span.timer'), t1 = 1000 * tms[0].dataset.total;
let t0;
function startTimers() {
t0 = new Date();
setInterval(setTimers, 1000);
}
function setTimers() {
if (!dC.contains('slide-mode')) return; // set timer only in slide mode
let t = (new Date() - t0);
if (t1) t = t1 - t;
const t2 = new Date(Math.abs(t)).toISOString().substr(11, 8).replace(/^00:/, '');
tms.forEach(el => {
el.innerText = t2;
if (t < 0) el.style.opacity = Math.ceiling(t/1000) % 2;
});
}
function toggleView(e) {
(dC.toggle('overview') ? dC.remove('slide-mode') : setScale(e));
}
// press f for fullscreen mode
d.addEventListener('keyup', e => {
if (e.target !== d.body) return;
e.key === 'f' && dE.requestFullscreen();
e.key === 'o' && toggleView(e);
e.key === 'm' && dC.toggle('mirrored');
sessionStorage.setItem('body-class', d.body.className);
});
// start timer and set scale on fullscreen
d.onfullscreenchange = e => {
d.fullscreenElement && (!t0 && startTimers(), setScale(e));
}
tms.forEach(el => el.addEventListener('click', e => startTimers()));
// measure the height of an empty slide
let H = -1;
function slideHeight() {
if (H >= 0) return H;
const s = newEl('div', 'slide');
p.querySelector('.slide:last-of-type').after(s);
H = s.offsetHeight;
s.remove()
return H;
}
// scale slides according to window height (baseline: 900px)
const sty = newEl('style'); sty.setAttribute('type', 'text/css');
d.head.append(sty);
// default height/width ratio from screen size
sty.innerHTML = `:root{--slide-ratio:${screen.height / screen.width}}`;
// read --slide-ratio in case users have set it in their CSS
const ratio = +getComputedStyle(dE).getPropertyValue('--slide-ratio');
function setScale(e) {
// navigate to a slide indicated by the hash if provided
e.type === 'load' && reveal(slides[location.hash.replace(/^#/, '') - 1]);
if (dC.contains('overview')) return;
let h = window.innerHeight, p = h / 900, r2 = h / window.innerWidth, full = d.fullscreenElement;
// add slide mode if there's enough window width, and remove it in case of scrollbar
dC.toggle('slide-mode', full || r2 <= ratio) &&
(!full && (dE.scrollWidth > dE.offsetWidth)) && dC.remove('slide-mode');
sty.innerHTML = `:root{--slide-ratio:${ratio};--slide-scale:${p};--slide-top:${(p - 1)/2 * d.body.scrollHeight + 'px'};}`;
// add spacers with enough height on load
!d.querySelector('.spacer.fade') && dC.contains('slide-mode') && slides.forEach(s => {
const sp = newEl('div', 'spacer fade'), h = s.offsetHeight, h2 = slideHeight();
s.append(sp);
if (h <= h2) return;
sp.style.height = (h2 - h % h2) * p + 'px';
});
}
['load', 'resize'].forEach(evt => window.addEventListener(evt, setScale));
// restore previously saved body class
const bc = sessionStorage.getItem('body-class');
if (bc) d.body.className += ' ' + bc;
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/tabsets.js | JavaScript | // find an element with class `tabset` and convert its subsequent bullet list or headings to tabs;
// see documentation at: https://yihui.org/en/2023/10/section-tabsets/
document.querySelectorAll('.tabset').forEach(h => {
const links = [...h.querySelectorAll(':scope > .tab-link')],
panes = [...h.querySelectorAll(':scope > .tab-pane')];
let init = 0;
function activate(i) {
function a(x, i) {
x.forEach((el, k) => el.classList[k === i ? 'add' : 'remove']('active'));
}
init = i; a(links, i); a(panes, i);
}
function newEl(tag, cls) {
const el = document.createElement(tag);
el.className = cls;
return el;
}
function isHeading(el) {
return /^H[1-6]$/.test(el.tagName);
}
function isEmpty(el) {
return el.innerHTML.trim() === '';
}
// if the tabset is heading or empty div, use next sibling, otherwise use first child
let n = -1, p, el = (isHeading(h) || isEmpty(h)) ? h.nextElementSibling : h.firstElementChild;
// if el is <ul>, try to convert it to tabset
if (links.length === 0 && el?.tagName === 'UL') {
[...el.children].forEach(li => {
const l = li.firstElementChild;
if (!l) return;
const l2 = newEl('div', 'tab-link');
l2.append(l);
l.outerHTML = l.innerHTML;
if (/<!--active-->/.test(l2.innerHTML)) l2.classList.add('active');
el.before(l2);
const p = newEl('div', 'tab-pane');
l2.after(p);
[...li.children].forEach(l => p.append(l));
links.push(l2); panes.push(p);
});
el.remove();
}
// create a tabset using headings if the above didn't work
if (links.length === 0) while (el) {
// convert headings to tabs
if (el.nodeName === '#comment' && el.nodeValue.trim() === `tabset:${h.id}`)
break; // quit after <!--tabset:id-->
if (isHeading(el)) {
const n2 = +el.tagName.replace('H', '');
if (n2 <= n) break; // quit after a higher-level heading
if (n < 0) n = n2 - 1;
// find the next lower-level heading and start creating a tab
if (n2 === n + 1) {
p = newEl('div', 'tab-pane');
el.after(p);
el.classList.add('tab-link');
el.querySelector('.anchor')?.remove();
el.outerHTML = el.outerHTML.replace(/^<h[1-6](.*)h[1-6]>$/, '<div$1div>');
el = p.previousElementSibling;
links.push(el); panes.push(p);
el = p.nextSibling;
continue;
}
}
if (p) {
p.append(el);
el = p;
}
el = el.nextSibling;
}
const N = links.length;
if (!N) return;
// if the initial tabset container is empty, move links and panes into it
if (isEmpty(h)) {
links.forEach(l => h.append(l));
panes.forEach(p => h.append(p));
}
// activate one tab initially if none is active
links.forEach((l, i) => {
i > 0 && links[i - 1].after(l); // move tab links together
l.onclick = () => activate(i); // add the click event
if (l.classList.contains('active')) init = i;
});
const ts = links[0].parentNode;
ts.hasAttribute('tabIndex') || (ts.tabIndex = '0');
ts.addEventListener('keyup', e => {
const dir = ['ArrowLeft', 'ArrowRight'].indexOf(e.key);
if (dir < 0) return;
const i = init + (dir ? 1 : -1);
activate(i < 0 ? N - 1 : (i > N - 1 ? 0 : i));
});
activate(init);
});
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/toc-highlight.js | JavaScript | // highlight a TOC item when scrolling to a corresponding section heading
(d => {
// assume TOC has these possible IDs (we can also consider other selectors)
const s = 'a[href^="#"]', toc = d.querySelector(`:is(#TableOfContents, #TOC):has(${s})`);
if (!toc) return;
const links = toc.querySelectorAll(s), dict = {};
links.forEach(a => dict[a.getAttribute('href').replace('#', '')] = a);
const ids = Object.keys(dict);
let id_active, id_last;
// status: 1 if an id is currently in the viewport, otherwise 0
const status = Array(ids.length).fill(0);
// create a new Intersection Observer instance
const observer = new IntersectionObserver(els => els.forEach(el => {
const id = el.target.id, i = ids.indexOf(id);
if (i < 0) return;
status[i] = +el.isIntersecting;
const n = status.indexOf(1); // the first id in view
if (n > -1) {
id_active = ids[n];
} else {
if (!id_active || el.boundingClientRect.top < 0) return;
// if a heading exits from bottom and no heading is in view, activate previous ID
id_active = i > 0 ? ids[i - 1] : undefined;
}
if (id_active === id_last) return;
for (const i in dict) {
dict[i].classList.toggle('active', i === id_active);
}
id_last = id_active;
// in case the active TOC item is not in the view, scroll TOC to make it visible
const a = dict[id_active];
if (!a || toc.scrollHeight <= toc.clientHeight) return;
const ra = a.getBoundingClientRect(), rt = toc.getBoundingClientRect();
if (ra.top < rt.top || ra.bottom > rt.bottom) toc.scrollTo({
top: a.offsetTop, behavior: 'smooth'
});
}));
// observe all section headings associated with TOC links
d.querySelectorAll('h1,h2,h3,h4,h5,h6').forEach(h => {
h.nodeType === 1 && dict.hasOwnProperty(h.id) && observer.observe(h);
});
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/toc.js | JavaScript | // build TOC using headings
(d => {
// find the body of the article
let b;
['.article', '.body', 'article', '.main', 'body'].forEach(s => {
if (!b) b = d.querySelector(s);
});
const hs = b.querySelectorAll([1, 2, 3, 4, 5, 6].map(i => `:scope > h${i}`).join(','));
if (hs.length === 0) return;
let toc = d.getElementById('TOC') || d.getElementById('TableOfContents');
if (toc) {
toc.innerHTML = ''; // empty and rebuild TOC if it has been generated (e.g., by Pandoc)
} else {
toc = d.createElement('div');
toc.id = 'TOC';
}
let li, ul;
let p = toc; // the current parent into which we insert child TOC items
let t1, t0 = 0; // pretend there is a top-level <h0> for the sake of convenience
hs.forEach(h => {
t1 = parseInt(h.tagName.replace(/^h/i, ''));
li = d.createElement('li');
if (t1 > t0) {
// lower-level header: create a new ul
ul = d.createElement('ul');
ul.appendChild(li);
p.appendChild(ul);
} else if (t1 < t0) {
// higher-level header: go back to upper-level ul
for (let j = 0; j < t0 - t1; j++) {
p = p.parentNode.parentNode;
}
}
if (t1 <= t0) p.parentNode.appendChild(li);
p = li;
const a = d.createElement('a');
a.innerHTML = h.innerHTML;
if (h.id) {
a.href = '#' + h.id;
} else {
// Pandoc's section divs
const s = h.parentNode;
if (s.classList.contains('section') && s.id) a.href = '#' + s.id;
}
p.appendChild(a);
t0 = t1;
});
if (!toc.parentNode) {
// if there is <header> in the article body, insert TOC after it
const header = b.querySelector('header');
header ? header.after(toc) : b.insertBefore(toc, b.firstChild);
}
// check if headings are numbered
toc.querySelector('span.section-number') && toc.firstElementChild.classList.add('numbered');
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/toggle-notes.js | JavaScript | (d => {
if (!d.body.classList.contains('has-notes')) return;
const h = d.querySelector('.author');
if (!h) return;
let s = sessionStorage.getItem('hide-notes');
h.classList.add('toggle-notes');
h.onclick = function(e) {
s === null && !/^(localhost|[0-9.]+)$/.test(location.hostname) &&
alert('你好像点了个神秘开关……请勿公开，自行阅读即可（再次点击可关闭），谢谢！');
s = d.body.classList.toggle('hide-notes');
try { sessionStorage.setItem('hide-notes', s); } catch (e) {};
};
if (s !== null) d.body.classList.toggle('hide-notes', s === 'true');
})(document);
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
purge.sh | Shell | #!/bin/sh
# purge jsdevlivr cache for assets modified between current and previous tags
JSD_URL="https://purge.jsdelivr.net/npm/@xiee/utils"
tag2=$(git describe --tags --abbrev=0)
tag1=$(git describe --tags --abbrev=0 "$tag2^")
for i in $(git diff --name-only $tag1 $tag2 | grep -E "[.](css|js)$"); do
if [ -n "$i" ]; then
curl "${JSD_URL}/${i}"
curl "${JSD_URL}/$(echo "$i" | sed 's/\(\.[^.]*$\)/.min\1/')"
fi
done
| yihui/lite.js | 19 | Miscellaneous lightweight tools and utilities in JavaScript | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
R/extract.R | R | # 将形如 &xxx; 的 HTML 代码转化为字符实体 https://stackoverflow.com/a/35187962/559676
db = character() # 缓存
html_entities = function(x) {
x2 = setdiff(x, names(db))
if (length(x2) == 0) return(db[x])
x3 = xml2::xml_text(xml2::read_html(paste0(c("<i>", x2, "</i>"), collapse = '')))
x3 = strsplit(x3, '')[[1]]
if (length(x3) != length(x2)) stop('有一些字符没有转换成功：', paste(x2, collapse = ' '))
db[x2] <<- x3
db[x]
}
unescape_entities = function(x) {
m = gregexpr('&([[:alpha:]]+|#x?[0-9]+);', x)
regmatches(x, m) = lapply(regmatches(x, m), function(x) {
html_entities(x)
})
x
}
# 用 export 输出数据
write_data = function(name, x, ...) {
res = paste0(
'export default ',
trimws(jsonlite::toJSON(x, pretty = 0, ...)), ';'
)
xfun::write_utf8(res, sprintf('js/data-%s.js', name))
}
files = list.files('html', '.[.]html$', full.names = TRUE)
res = lapply(files, function(f) {
x = xfun::file_string(f)
r = '.*<div class="content definitions jnr">(.+?)<div class="div copyright">.*'
x = xfun::grep_sub(r, '\\1', x)
x = lapply(strsplit(x, '><span class="dicpy">')[[1]][-1], function(z) {
py = xfun::grep_sub('^([^<]+)<.*', '\\1', z) # 获取拼音
py = unescape_entities(py)
py = gsub('^\\s*([^[:space:]]+).*', '\\1', py) # 去掉空格
# 有少数条目没有 </li> 闭合标签（如媪、啻），而是继续 <li> 直到 </ol> 结束
li = regmatches(z, gregexpr('<li>\\s*(.+?)\\s*(?=<(/li|li|/ol)>)', z, perl = TRUE))
li = gsub('^<li>|</(li|ol)>$', '', unlist(li))
# 只有一项释义的时候，没有 <li> 标签，以 ◎ 开头
if (length(li) == 0) {
li = xfun::grep_sub('.*◎(.+?)</p>.*', '\\1', z)
li = bookdown:::strip_html(li)
}
if (length(li) == 0) stop('这个文件中没有找到字的释义：', f)
li = trimws(bookdown:::strip_html(li))
li = unescape_entities(li)
if (any(grepl('&', li))) message(f, ' 里面似乎仍然有转义符：', li)
setNames(list(li), py)
})
unlist(x, recursive = FALSE)
})
res = setNames(res, gsub('.*(.)[.]html', '\\1', files))
write_data('chars', res)
local({
x = trimws(xfun::read_utf8('data/freq-chars.txt'))
m = gregexpr(r <- '([0-9]+)\\s+(.)(\\s*.\\s*[^[:space:]]+|$)', x)
x = unlist(regmatches(x, m))
if (any(i <- format(seq_along(x), trim = TRUE) != gsub(r, '\\1', x))) stop(
'这些字符可能有问题：\n', paste(x[i], collapse = '\n')
)
x = gsub(r, '\\2', x)
x = intersect(x, names(res))
x = c(x, setdiff(names(res), x))
write_data('freqs', paste(x, collapse = ''), auto_unbox = TRUE)
})
| yihui/zdict.js | 62 | 汉典网站数据（汉字、拼音、释义等） | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
R/pinyin.R | R | x = xfun::read_utf8('js/data-chars.js')
x[1] = gsub('^export default ', '', x[1])
x[length(x)] = gsub(';\\s*$', '', x[length(x)])
z = jsonlite::fromJSON(x, FALSE)
write_data('pinyin', lapply(z, names))
| yihui/zdict.js | 62 | 汉典网站数据（汉字、拼音、释义等） | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
R/scrape.R | R | # 抓取 7000 个通用汉字；这些字分布在多页上，须一页一页读取
x = xfun::read_utf8('https://www.zdic.net/zd/zb/ty/')
p = xfun::grep_sub('.*<a class="pck" title="([0-9]+)">.*', '\\1', x)
res = lapply(p, function(i) {
message(i, '/', length(p))
Sys.sleep(runif(1))
x = xfun::read_utf8(paste0('https://www.zdic.net/zd/zb/ty/bh/?bh=', i))
r = ".*<a href='/hans/(.)' title='([^']+)'>.*"
x = unlist(regmatches(x, regexec(r, x)))
x = matrix(x, ncol = 3, byrow = TRUE)
x[, 2:3]
})
res = do.call(rbind, res)
if (any(i <- duplicated(res[, 1]))) {
stop('抓取的汉字中有重复字符：', paste(res[i, 1], collapse = '、'))
}
n = NROW(res)
for (i in seq_len(n)) {
message(i, '/', n)
char = res[i, 1]
xfun::download_file(paste0('https://www.zdic.net/hans/', char), file.path('html', paste0(char, '.html')))
# Sys.sleep(runif(1, 0, .1))
}
| yihui/zdict.js | 62 | 汉典网站数据（汉字、拼音、释义等） | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
build.sh | Shell | #!/bin/sh
npm install --global rollup
mkdir dist
cd js
rollup zdict.js --format umd --name zDict --file ../dist/zdict.js
rollup learn-chars.js --format iife --file ../dist/learn-chars.js
rollup pinyin-finals.js --format iife --file ../dist/pinyin-finals.js
# rollup data-chars.js --format cjs --file ../dist/data-chars.js
# rollup data-freqs.js --format cjs --file ../dist/data-freqs.js
cd ..
rm -r js/ R/ data/ *.Rproj
mv dist js
| yihui/zdict.js | 62 | 汉典网站数据（汉字、拼音、释义等） | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
css/learn-chars.css | CSS | #learn-toolbar, .char-block { text-align: center; }
.right { text-align: right; }
#learn-toolbar .label {
margin: auto 1em auto .5em;
padding: .5em 1em;
}
#learn-toolbar input:not(:checked) + .label {
background: none;
border: 1px solid #eee;
}
.pinyin { font-size: 3em; }
.py {
font-size: 1.5em;
margin-bottom: auto;
}
.char-box {
display: inline-flex;
justify-content: center;
align-items: center;
font-size: 10em;
border: 1px solid;
width: 1.5em;
height: 1.5em;
cursor: pointer;
background:
repeating-linear-gradient(0deg, transparent, transparent calc(50% - .5px), lightgray calc(50% - .5px), lightgray calc(50% + .5px)),
repeating-linear-gradient(90deg, transparent, transparent calc(50% - .5px), lightgray calc(50% - .5px), lightgray calc(50% + .5px)),
repeating-linear-gradient(45deg, transparent, transparent calc(50% - .5px), lightgray calc(50% - .5px), lightgray calc(50% + .5px)),
repeating-linear-gradient(135deg, transparent, transparent calc(50% - .5px), lightgray calc(50% - .5px), lightgray calc(50% + .5px));
position: relative;
line-height: 1em;
}
.char-box > .char + span {
position: absolute;
font-size: .2em;
bottom: 0;
line-height: 1em;
opacity: .6;
}
#learn-chars .correct, .review-all .review:not(.review-show) { color: forestgreen; }
#learn-chars .wrong { color: orangered; }
.review {
font-size: .3em;
display: none;
}
.review-pane .review-show, .review-pane.review-all .review {
display: inline-block;
}
.review-all #learn-toolbar input:checked + .label {
background: none;
border: 1px solid #000;
}
.review .pinyin {
font-size: 4em;
line-height: 1.2em;
}
.current {
color: white;
background-color: black;
}
#learn-candidates {
display: block;
width: 100%;
height: 6em;
padding: .2em;
}
#learn-settings {
font-size: .9em;
}
#learn-settings p:nth-of-type(2) {
display: flex;
justify-content: space-between;
flex-wrap: wrap;
}
#learn-settings input {
width: 4em;
padding: .2em;
}
#learn-settings button {
min-width: 4em;
padding: .1em .2em;
}
.seal-top {
border-bottom: 1px dashed;
}
.seal-bottom {
border-top: 1px dashed;
}
.seal-line {
color: #ccc;
text-align: center;
letter-spacing: 1em;
}
| yihui/zdict.js | 62 | 汉典网站数据（汉字、拼音、释义等） | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
css/pinyin-finals.css | CSS | .char-block, .toc-finals {
display: inline-block;
text-align: center;
margin: 2px;
}
.toc-finals {
margin: 0 .2em;
}
.char-box {
font-size: 1.2em;
border: 1px solid;
border-top: none;
}
#pinyin-finals .char-box a {
color: inherit;
border: none;
}
.pinyin {
font-size: .8em;
border-bottom: 1px dotted;
}
.char-block {
width: 1.5em;
}
.char-width-4 {
width: 1.8em;
}
.char-width-5 {
width: 2.3em;
}
.char-width-6 {
width: 2.7em;
}
.char-accent-1 .pinyin, .char-accent-2 .pinyin {
border: 1px solid;
}
.char-accent-2 .pinyin {
border-style: dashed;
}
.char-accent-3 .pinyin {
background: #393E46;
}
.char-accent-4 .pinyin {
background: #716e77;
}
.char-accent-3 .pinyin, .char-accent-4 .pinyin {
color: white;
}
.accent-legend {
font-size: 1.5em;
cursor: pointer;
border-bottom: 5px solid transparent;
}
.accent-clicked, .accent-legend:hover {
border-bottom-color: red;
}
.char-section {
margin-bottom: 2em;
}
.char-section[class*=accent-show] .char-block {
display: none;
}
.char-section.accent-show-0 .char-accent-0, .char-section.accent-show-1 .char-accent-1, .char-section.accent-show-2 .char-accent-2, .char-section.accent-show-3 .char-accent-3, .char-section.accent-show-4 .char-accent-4 {
display: inline-block;
}
| yihui/zdict.js | 62 | 汉典网站数据（汉字、拼音、释义等） | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/data-freqs.js | JavaScript | export default 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馔豺痤郇殓髅轳逯嗫戕嚅蛳嘤疣蚱钯钿碇咣毽喱逦廪邙囡匏扦咝凇纨涠庠溆醺炀烊肄龈谀锱瘢枞皴贰晷闳斛屐讦婧苣蔻绺渌瑁螟叵颀穑膻羧螳绦誊蜥楦恂靥咿翳瓒枳啭樽嫒婊搽铒跗凫菡篁髻裾栲癞蓼氖孬喏砒姘衽缛嵬挹缢慵呦箸蹩槎榇舂嗲胴谔岢圹娌潋蛉酃鲵鲇娉亓碛芊忪谇笤韪勰呓俣圜愠仄炷毖筚伧棰磴滏篙肱笕堇馑荩哐傀崃罱痨儡鹂檩仵檄芎阉刈壅馀庾妯躅獒阊笞饬钏硐椴泔硌鹘鳇豇狙戡莨啉辇臬殇舐黍薮眭佻嗵煨莴蚴妤瘐擢蛏蹰龊辏氘骶莪珐缟聒讧岬胛桷谰戾撸鸬雒嘧囔铍骈掊茕噻铯柁龌硖罅魇酽咦嶷羿轸趵荸薜踟玳啖蔸槁鲛疥唳弭曩黏镊泮霈淠柒颧瘙痧辋郄燹泫郾鹞钇殪痈甑踯翥婢檗柽啐菪嶝腭嗝剐笏蟥戢阄撅尻贶辚蜢颞忸胼阕竦焐揠邺鳙啁徵诌舨哔卟伥苌鹚箪锇蝮诟洄浍诨犍硷噤垲郐椤嫫脲殍噗溱箬厍钽钍恹鬻爰蓁胝颛褙鳊邴镫腚钭颚鲂悱狒佶偈绔醪坜疠椋犸暝佞哝瞟荨芩逡溽裟挲抟暾崦芫荑薏莸欤栀斫镞嗳鸨跸骠俦谠簟棼驸掼倨橛犒邋耧蝼虻铙郫汔诮楸阒绻叁臊钐腧闩菘阗忝橐翕阋踅窨鹬鼋樾錾旃弁侪坼蚩嘬糍骢氐呃榧玢绋蚨钆岣菰罟嘏埚绗嚯藿笄袈羯肼暌啷蒗蜊獠鬣黾乜镆怩驽旆髂仟芡谯恁鳃艄莳趿遢鲐醍僮氽刎芴喑墉昀箦鄣摺钲贽缵鏊锛瓿廛瘳亍遄褡垌椟酆桴赙坩臌曷跽湫榉黧猁钌镏缦殁赧悭缱衾鲭铩猞眚铈谥耜飕饕餮骰绾鹇鲞爻蜴镱铟莜祗濞镔逋谄谶酲樗憷莼撺柢阏砜垓旰妫衮嗥郏鞯徼孓钪侉夼跬铼嫘蟊茆睨怄蹁谝嘌綮嫱筇犰穰铷筲哂炻豕秫笥涑铊帏闱鋈舾屣狎哓噫璎铕宥阈豸辎趑龇捌秕荜愎镲谗踔苁酢呔聃镦屙鲱鬲膈铪醐獾鲩虺葭牮礓苴讵颏裉诳栌氇哞柰袢帔睥苤嫔笸氆佥箧蚋鲥狲桫溏铽殄脘洧肟绡咻洫癔洇嵛磔胗肫眦埯畚妣飑豳髌砗铳楮蔟毳锝堞疔葑缶菔疳彀胍磙顸薅翮猢怙蒺妗髁醌粝魉旒蝥缗衲呸醅蚍圮榀萁苘逑诎劬蕖朊剡蟮酞帑葶菟魍庑葸氙谖鞅狺夤嬴瘿饔雩鹆橼赜潴骓缁诹怍杓檫媸氚呲殂矬笪迨纛簦玎苊轭鼢缑诖炅鲧唿戽鬟恚枧洚桕雎蠲剀诓瘌镧铑鳓蓠呖跞裢裣埒捩鲮熘嵝瘰镘脒腩筢耪辔牝嘁蛴戗蛩巯悫葚熵蛸螫毹妁嗾鳎绨粜菀沩鼯牾螅顼蕈鼹繇苡悒吲喁卣牖笮舴罾棹鸷碡锕嗌媪龅甏箅傧啵鹁晡氅魑篪怛籴礅蒽珥钫绠觚鸹涫颃篌锪蠖乩咭赍嵴铗湔槿赆僦皲箜蒉缧酹嘞疬臁膦泷蒌泺荬颟旄泖镅蠓幂耱襻鼙炝愀蘧氍禳桡糁馓酾槊狻锬羰鼗鹈畋髫萜堍怃崤囟睚餍徭瘗唷圉蜮砟谵澶朕摭轵诼笫廒聱庳髀笾龀裎雠蝽腠妲铥黩怼蘩趺苻拊鲋戆纥哏鲠笱瞽庋簋刿掴槲觳萑癀蟪钬虮掎鲣囝裥踺茳糨鹪狷麇刳愦髡悃缡鲡鳢奁尥柃胪镥脔劢墁蝻呶搦罴蜱俜鲆皤镨槭镪黢洳枘芟埏筮殳飧溻饧樘酡圬粞觋莶霰榍薤髹曛迓佾埸霪茚鼬伛瘵骣畛卮轾彘觯邾槠嵫髭蕞犴鞴畀滗煸褊孛羼耖褫彳艟茈璁爨萏坫鸫篼簖裰哚蹯瀵怫陔筻蛄绲崞蜾盍荭黉糇骺鲎煳鹕冱瓠逭漶耠镬齑殛鲚跏蛱搛缣鹣僬噍衿缂喾狯纩栝蛞稂塄嫠詈蠊鹩躐鹨簏膂脶嬷昴瞀浼艨祢縻蘼芈眄鹋杪咩麽瘼鍪硇猱茑脬蟛貔仳犏钋芑葜愆锓蠼筌鬈蚺荛埽潲诜埘弑嗍蒴鸶缌澌姒蔌睃缇梃彖鼍芄隈鲔硪忤痦僖醯鼷跣枵擤勖痃碹谳轺铘圯纡窬窳饫蓣瀹趱驵缯揸笊絷跖螽籀舳驺陬阼揞菝魃癍鹎坌狴嬖襞碥鳔醭螬馇虿瘥惝怊鸱螭瘛帱徂汆脞瘅忉羝睇瓞鲽胨芏佴燔偾稃郛莩幞澉槔袼茛鞲觏酤鲴宄匦呙馘焓瘊岵鹱咴隳溷夥剞洎恝蒹谫僭艽挢敫卺扃锔窭锩觖劂氪骒哙悝蝰诔苈篥娈瞵栊癃舻辂稆猡蛑甍艋敉眇侔镎肭艿蛲陧衄锘堋庀甓螵钷桤褰肷锖鞒吣黥俅蝤璩悛辁颡谂摅汜溲嗉荽闼骀炱螗耥裼铫莛箨蕹迕杌寤穸饩舄禊猃绁渫廨獬硎荇鸺貅糈揎獯厣罨蛘鳐舣媵蚰侑狳螈龠昃痄搌浈埴黹酎橥缒窀菹锿砹邶鐾忭缏瘭踣礤骖艚锸猹镡躔蒇冁鬯枨眵搋镩戥觌阽铞垤蹀耵髑憝鸸篚镄鲼唪祓艴黻黼鳆尜塥哿虼遘桄胲醢撖嚆薨堠烀轷锾缳擐哕阍劐攉墼蕺芰戋趼楗耩喈刭獍鬏鞫犋屦醵桊爝捃胩锎蒈莰闶锞眍筘阃漤铹栳耢仂泐檑轹蔹垆锊蠃硭漭猸鹛钔瞢礞喵苠鳘貊貘毪攮猊聍狃耨孥胬恧蒎锫陴氕裒镤蜞岍搴慊椠蜣硗劁缲檎圊檠銎赇糗鸲磲畎狨蝾薷襦颥蓐脎毵磉唼歃骟滠矧胂蓍鲺贳搠兕螋瞍觫铴瑭慝掭祧龆蜩鲦茼酴煺柝腽阌阢菥蓰柙祆筅魈躞砉醑儇岈砑珧酏劓堙撄潆蝓燠眢箢掾刖狁拶唣迮帻谮哳膪嫜忮骘踬瘃麈疰浞禚觜耔腙鄹鲰躜撙胙乂亶亸伋伾俵俶倓倞倻偲僇僰剅剕剟勍勩匜卻厾唝啰啴喤嗞嘚嘡噀嚄嚚垍垞垟垯垱埼堉堌塆塈塃塮墈墦夬奭姞姽婞婳嫚嫪宬尔屃峂峣峧崟嵎嵖嵚嶓巉帡幪庤庼廋廙弇彧悢惇愔慥慭扅扊扺抃抔拃拤挦捯揳揾搒摽斝旸旻昉昽晞晢暅曈杧杻柈栒栟梽梾棁棨棬棻椑楯榖槚槜橦檵欸殣毐汈汭沄沘沚沨泃泜泚洑洣洨洴洺浉浐浕浡浥涘涢淏湉湜湝湨湲溇溠溦滃滍滘滪滫潏潟潵潽澥澴澼瀌瀍炟烜烝烺焌焜熜熥燊燏牁牂牚犨狉狝猄獴玕玙玚玠玡玥玦珣珰珽琇琎琤琫琯瑀瑄瑢璆璈璘璟璠璪瓘瓻甪畯疍疢疭瘆盉盦眊眬瞭矻砮硁硚碶礌礳祃祎祲祼祾禤秾穄窅窣窸竑筜筼箓簃簉簠糵繄纴纻绤绹综罽羑翙翚翯耰耲脧腒膙臑臜芼茀茓荙茝莙菂菼著萩葓葖蒟蓂蓇蕰藠蘘蜎螠螣蠋袆袗袪袯裈襕觱訄诐豨赑赟赪跐跶踶蹅蹐蹓蹜蹢蹽蹾轪辀辌辒邽郈郚郿鄌鄘酦醾鋆钘铚铻锜锧锽镃镈镋镚镠镴镵闿阇阘靰靸靺靽靿鞁鞡鞧鞨韂韨颋颙飐飔飗饳饸饹饻馃馉馌骍骎骙鬹魆鱽鱾鲀鲃鲉鲊鲌鲏鲙鲪鲬鲯鲹鳀鳁鳂鳈鳉鲾鳑鳚鳡鳤鸤鸮鸰鸻鸼鹀鹐鹝鹟鹠鹡鹮鹲黇鼒鼩鼫鼱齁齉龁";
| yihui/zdict.js | 62 | 汉典网站数据（汉字、拼音、释义等） | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/data-pinyin.js | JavaScript | export default {
"一": [
"yī"
],
"丁": [
"dīng",
"zhēng"
],
"七": [
"qī"
],
"万": [
"wàn",
"mò"
],
"丈": [
"zhàng"
],
"三": [
"sān"
],
"上": [
"shàng",
"shǎng"
],
"下": [
"xià"
],
"不": [
"bù",
"fǒu"
],
"与": [
"yǔ",
"yù",
"yú"
],
"丐": [
"gài"
],
"丑": [
"chǒu"
],
"专": [
"zhuān"
],
"且": [
"qiě",
"jū"
],
"丕": [
"pī"
],
"世": [
"shì"
],
"丘": [
"qiū"
],
"丙": [
"bǐng"
],
"业": [
"yè"
],
"丛": [
"cóng"
],
"东": [
"dōng"
],
"丝": [
"sī"
],
"丞": [
"chéng"
],
"丢": [
"diū"
],
"两": [
"liǎng"
],
"严": [
"yán"
],
"丽": [
"lì",
"lí"
],
"丧": [
"sāng",
"sàng"
],
"个": [
"gè",
"gě"
],
"丫": [
"yā"
],
"中": [
"zhōng",
"zhòng"
],
"丰": [
"fēng"
],
"串": [
"chuàn"
],
"临": [
"lín"
],
"丸": [
"wán"
],
"义": [
"yì"
],
"丹": [
"dān"
],
"为": [
"wéi",
"wèi"
],
"主": [
"zhǔ"
],
"举": [
"jǔ"
],
"乂": [
"yì"
],
"乃": [
"nǎi"
],
"久": [
"jiǔ"
],
"么": [
"ma",
"me",
"yāo"
],
"之": [
"zhī"
],
"乌": [
"wū"
],
"尹": [
"yǐn"
],
"乍": [
"zhà"
],
"乎": [
"hū"
],
"乏": [
"fá"
],
"乐": [
"lè",
"yuè",
"yào",
"lào"
],
"乒": [
"pīng"
],
"乓": [
"pāng"
],
"乔": [
"qiáo"
],
"乖": [
"guāi"
],
"乘": [
"chéng",
"shèng"
],
"乙": [
"yǐ"
],
"乜": [
"miē",
"niè"
],
"九": [
"jiǔ"
],
"乞": [
"qǐ"
],
"也": [
"yě"
],
"习": [
"xí"
],
"书": [
"shū"
],
"乩": [
"jī"
],
"买": [
"mǎi"
],
"乱": [
"luàn"
],
"乳": [
"rǔ"
],
"乾": [
"qián",
"gān"
],
"了": [
"liǎo",
"le"
],
"予": [
"yú",
"yǔ"
],
"争": [
"zhēng"
],
"事": [
"shì"
],
"二": [
"èr"
],
"亍": [
"chù"
],
"于": [
"yú"
],
"亏": [
"kuī"
],
"云": [
"yún"
],
"互": [
"hù"
],
"亓": [
"qí"
],
"五": [
"wǔ"
],
"井": [
"jǐng"
],
"亘": [
"gèn"
],
"亚": [
"yà"
],
"些": [
"xiē",
"suò"
],
"亟": [
"jí",
"qì"
],
"亡": [
"wáng",
"wú"
],
"亢": [
"kàng"
],
"交": [
"jiāo"
],
"亥": [
"hài"
],
"亦": [
"yì"
],
"产": [
"chǎn"
],
"亨": [
"hēng",
"pēng"
],
"亩": [
"mǔ"
],
"享": [
"xiǎng"
],
"京": [
"jīng"
],
"亭": [
"tíng"
],
"亮": [
"liàng"
],
"亲": [
"qīn",
"qìng"
],
"亳": [
"bó"
],
"亵": [
"xiè"
],
"亶": [
"dǎn",
"dàn"
],
"亸": [
"duǒ"
],
"人": [
"rén"
],
"亿": [
"yì"
],
"什": [
"shí",
"shén"
],
"仁": [
"rén"
],
"仂": [
"lè"
],
"仃": [
"dīng"
],
"仄": [
"zè"
],
"仅": [
"jǐn",
"jìn"
],
"仆": [
"pū",
"pú"
],
"仇": [
"chóu",
"qiú"
],
"仉": [
"zhǎng"
],
"今": [
"jīn"
],
"介": [
"jiè"
],
"仍": [
"réng"
],
"从": [
"cóng"
],
"仑": [
"lún"
],
"仓": [
"cāng"
],
"仔": [
"zī",
"zǐ",
"zǎi"
],
"仕": [
"shì"
],
"他": [
"tā"
],
"仗": [
"zhàng"
],
"付": [
"fù"
],
"仙": [
"xiān"
],
"仞": [
"rèn"
],
"仟": [
"qiān"
],
"仡": [
"yì",
"gē"
],
"代": [
"dài"
],
"令": [
"líng",
"lǐng",
"lìng"
],
"以": [
"yǐ"
],
"仨": [
"sā"
],
"仪": [
"yí"
],
"仫": [
"mù"
],
"们": [
"mén"
],
"仰": [
"yǎng",
"áng"
],
"仲": [
"zhòng"
],
"仳": [
"pǐ",
"pí"
],
"仵": [
"wǔ"
],
"件": [
"jiàn"
],
"价": [
"jià",
"jiè",
"jie"
],
"任": [
"rèn",
"rén"
],
"份": [
"fèn",
"bīn"
],
"仿": [
"fǎng"
],
"企": [
"qǐ"
],
"伉": [
"kàng"
],
"伊": [
"yī"
],
"伋": [
"jí"
],
"伍": [
"wǔ"
],
"伎": [
"jì",
"qí"
],
"伏": [
"fú"
],
"伐": [
"fá"
],
"休": [
"xiū",
"xǔ"
],
"众": [
"zhòng"
],
"优": [
"yōu"
],
"伙": [
"huǒ"
],
"会": [
"huì",
"kuài"
],
"伛": [
"yǔ"
],
"伞": [
"sǎn"
],
"伟": [
"wěi"
],
"传": [
"chuán",
"zhuàn"
],
"伢": [
"yá"
],
"伤": [
"shāng"
],
"伥": [
"chāng"
],
"伦": [
"lún"
],
"伧": [
"cāng",
"chen"
],
"伪": [
"wěi"
],
"伫": [
"zhù"
],
"佤": [
"wǎ"
],
"伯": [
"bó",
"bǎi",
"bà"
],
"估": [
"gū",
"gù"
],
"伴": [
"bàn"
],
"伶": [
"líng"
],
"伸": [
"shēn"
],
"伺": [
"sì",
"cì"
],
"似": [
"sì",
"shì"
],
"伽": [
"qié",
"jiā",
"gā"
],
"伾": [
"pī"
],
"佃": [
"diàn",
"tián"
],
"但": [
"dàn"
],
"位": [
"wèi"
],
"低": [
"dī"
],
"住": [
"zhù"
],
"佐": [
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"kòu"
],
"扦": [
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"执": [
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"扩": [
"kuò"
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"扪": [
"mén"
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"扫": [
"sǎo",
"sào"
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"扬": [
"yáng"
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"扭": [
"niǔ"
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"扮": [
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"扯": [
"chě"
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"扰": [
"rǎo"
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"扳": [
"bān"
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"扶": [
"fú"
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"批": [
"pī"
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"扺": [
"zhǐ"
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"扼": [
"è"
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"找": [
"zhǎo"
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"承": [
"chéng"
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"技": [
"jì"
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"抃": [
"biàn"
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"抄": [
"chāo"
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"抉": [
"jué"
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"把": [
"bǎ",
"bà"
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"抑": [
"yì"
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"抒": [
"shū"
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"抓": [
"zhuā"
],
"抔": [
"póu"
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"投": [
"tóu"
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"抖": [
"dǒu"
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"抗": [
"kàng"
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"折": [
"zhē",
"zhé",
"shé"
],
"抚": [
"fǔ"
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"抛": [
"pāo"
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"抟": [
"tuán"
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"抠": [
"kōu"
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"抡": [
"lūn",
"lún"
],
"抢": [
"qiǎng",
"qiāng",
"chēng"
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"护": [
"hù"
],
"报": [
"bào"
],
"抨": [
"pēng"
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"披": [
"pī"
],
"抬": [
"tái"
],
"抱": [
"bào"
],
"抵": [
"dǐ"
],
"抹": [
"mǒ",
"mò",
"mā"
],
"抻": [
"chēn"
],
"押": [
"yā"
],
"抽": [
"chōu"
],
"抿": [
"mǐn"
],
"拂": [
"fú",
"bì"
],
"拃": [
"zhǎ"
],
"拄": [
"zhǔ"
],
"担": [
"dān",
"dàn",
"dǎn"
],
"拆": [
"chāi",
"cā"
],
"拇": [
"mǔ"
],
"拈": [
"niān"
],
"拉": [
"lā",
"lá"
],
"拊": [
"fǔ"
],
"拌": [
"bàn",
"pàn"
],
"拍": [
"pāi"
],
"拎": [
"līn"
],
"拐": [
"guǎi"
],
"拒": [
"jù"
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"拓": [
"tuò",
"tà",
"zhí"
],
"拔": [
"bá"
],
"拖": [
"tuō"
],
"拗": [
"ǎo",
"ào",
"niù"
],
"拘": [
"jū",
"gōu"
],
"拙": [
"zhuō"
],
"拚": [
"pàn",
"pīn",
"fān"
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"招": [
"zhāo"
],
"拜": [
"bài"
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"拟": [
"nǐ"
],
"拢": [
"lǒng"
],
"拣": [
"jiǎn"
],
"拤": [
"qiǎ"
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"拥": [
"yōng"
],
"拦": [
"lán"
],
"拧": [
"níng",
"nǐng",
"nìng"
],
"拨": [
"bō"
],
"择": [
"zé",
"zhái"
],
"括": [
"kuò",
"guā"
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"拭": [
"shì"
],
"拮": [
"jié",
"jiá"
],
"拯": [
"zhěng"
],
"拱": [
"gǒng"
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"拳": [
"quán"
],
"拴": [
"shuān"
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"拶": [
"zā",
"zǎn"
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"拷": [
"kǎo"
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"拼": [
"pīn"
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"拽": [
"zhuài",
"zhuāi",
"yè"
],
"拾": [
"shí",
"shè"
],
"拿": [
"ná"
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"持": [
"chí"
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"挂": [
"guà"
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"指": [
"zhǐ"
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"挈": [
"qiè"
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"按": [
"àn"
],
"挎": [
"kuà",
"kū"
],
"挑": [
"tiāo",
"tiǎo"
],
"挖": [
"wā"
],
"挚": [
"zhì"
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"挛": [
"luán"
],
"挝": [
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"wō"
],
"挞": [
"tà"
],
"挟": [
"xié",
"jiā"
],
"挠": [
"náo"
],
"挡": [
"dǎng",
"dàng"
],
"挢": [
"jiǎo"
],
"挣": [
"zhēng",
"zhèng"
],
"挤": [
"jǐ"
],
"挥": [
"huī"
],
"挦": [
"xián"
],
"挨": [
"āi",
"ái"
],
"挪": [
"nuó"
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"挫": [
"cuò"
],
"振": [
"zhèn"
],
"挲": [
"suō",
"sa",
"shā"
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"挹": [
"yì"
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"挺": [
"tǐng"
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"挽": [
"wǎn"
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"wǔ"
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"捃": [
"jùn"
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"捅": [
"tǒng"
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"捆": [
"kǔn"
],
"捉": [
"zhuō"
],
"捋": [
"luō",
"lǚ"
],
"捌": [
"bā"
],
"捍": [
"hàn"
],
"捎": [
"shāo",
"shào"
],
"捏": [
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],
"捐": [
"juān"
],
"捕": [
"bǔ"
],
"捞": [
"lāo"
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"损": [
"sǔn"
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"捡": [
"jiǎn"
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"换": [
"huàn"
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"捣": [
"dǎo"
],
"捧": [
"pěng"
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"捩": [
"liè"
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"捭": [
"bǎi"
],
"据": [
"jù",
"jū"
],
"捯": [
"dáo"
],
"捶": [
"chuí"
],
"捷": [
"jié"
],
"捺": [
"nà"
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"捻": [
"niǎn",
"niē"
],
"掀": [
"xiān"
],
"掂": [
"diān"
],
"掇": [
"duō"
],
"授": [
"shòu"
],
"掉": [
"diào"
],
"掊": [
"pǒu",
"póu"
],
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"zhǎng"
],
"掎": [
"jǐ"
],
"掏": [
"tāo"
],
"掐": [
"qiā"
],
"排": [
"pái",
"pǎi"
],
"掖": [
"yè",
"yē"
],
"掘": [
"jué"
],
"掠": [
"lüè"
],
"探": [
"tàn"
],
"掣": [
"chè"
],
"接": [
"jiē"
],
"控": [
"kòng"
],
"推": [
"tuī"
],
"掩": [
"yǎn"
],
"措": [
"cuò"
],
"掬": [
"jū"
],
"掭": [
"tiàn"
],
"掮": [
"qián"
],
"掰": [
"bāi"
],
"掳": [
"lǔ"
],
"掴": [
"guāi"
],
"掷": [
"zhì"
],
"掸": [
"dǎn",
"shàn"
],
"掺": [
"chān",
"xiān",
"càn",
"shǎn"
],
"掼": [
"guàn"
],
"掾": [
"yuàn"
],
"揄": [
"yú"
],
"揆": [
"kuí"
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"揉": [
"róu"
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"揍": [
"zòu"
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"揎": [
"xuān"
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"描": [
"miáo"
],
"提": [
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"dī",
"dǐ"
],
"插": [
"chā"
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"揖": [
"yī"
],
"揞": [
"ǎn"
],
"揠": [
"yà"
],
"握": [
"wò"
],
"揣": [
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"chuài",
"chuāi",
"tuán",
"zhuī"
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"揩": [
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],
"揪": [
"jiū"
],
"揭": [
"jiē",
"qì"
],
"揳": [
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],
"援": [
"yuán"
],
"揶": [
"yé"
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"揸": [
"zhā"
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"揽": [
"lǎn"
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"揾": [
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"揿": [
"qìn"
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"chān"
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"gé"
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"lōu"
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"èn"
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],
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"摆": [
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"摔": [
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"摘": [
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"摞": [
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"摧": [
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],
"摭": [
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"摸": [
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"摹": [
"mó"
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"摺": [
"zhé"
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"摽": [
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"biāo"
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"撂": [
"liào"
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"撄": [
"yīng"
],
"撇": [
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"piě"
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"撅": [
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"jué"
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"撑": [
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],
"撒": [
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],
"撕": [
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"撖": [
"hàn"
],
"撙": [
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],
"撞": [
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"撤": [
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"撩": [
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"liáo"
],
"撬": [
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"播": [
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"撮": [
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"zuǒ"
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"撰": [
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],
"撵": [
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"撷": [
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"撸": [
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"撺": [
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"撼": [
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"擀": [
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"攀": [
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"攉": [
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"攒": [
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"攘": [
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"攫": [
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"攮": [
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"收": [
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"攸": [
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"攻": [
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"放": [
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"政": [
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"效": [
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"敏": [
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"敕": [
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"敖": [
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"教": [
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"敛": [
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"敞": [
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"散": [
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"敬": [
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"数": [
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"敲": [
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"斓": [
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"斗": [
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"斛": [
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"斜": [
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"斟": [
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"斧": [
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"斫": [
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"方": [
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"旰": [
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"旷": [
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"旸": [
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"mén",
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"祎": [
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"祓": [
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"祝": [
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"神": [
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"祧": [
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"票": [
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"piāo"
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"zhài"
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"祺": [
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"禁": [
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"jìn"
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"yù",
"ǒu"
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"秆": [
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"秋": [
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"种": [
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"zhòng",
"chóng"
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"秒": [
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"秘": [
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"bì"
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"秫": [
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"称": [
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"chèn",
"chèng"
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"移": [
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"秽": [
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"秾": [
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"稀": [
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"稂": [
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"穷": [
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"笆": [
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"笑": [
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"笔": [
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"笞": [
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"笠": [
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"笤": [
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"笥": [
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"篡": [
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"篪": [
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"篮": [
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],
"飙": [
"biāo"
],
"飞": [
"fēi"
],
"食": [
"shí",
"sì",
"yì"
],
"飧": [
"sūn"
],
"飨": [
"xiǎng"
],
"餍": [
"yàn"
],
"餐": [
"cān"
],
"餮": [
"tiè"
],
"饔": [
"yōng"
],
"饕": [
"tāo"
],
"饥": [
"jī"
],
"饧": [
"xíng"
],
"饨": [
"tún"
],
"饩": [
"xì"
],
"饪": [
"rèn"
],
"饫": [
"yù"
],
"饬": [
"chì"
],
"饭": [
"fàn"
],
"饮": [
"yǐn",
"yìn"
],
"饯": [
"jiàn"
],
"饰": [
"shì"
],
"饱": [
"bǎo"
],
"饲": [
"sì"
],
"饳": [
"duò"
],
"饴": [
"yí",
"sì"
],
"饵": [
"ěr"
],
"饶": [
"ráo"
],
"饷": [
"xiǎng"
],
"饸": [
"hé"
],
"饹": [
"le"
],
"饺": [
"jiǎo"
],
"饻": [
"xī"
],
"饼": [
"bǐng"
],
"饽": [
"bō"
],
"饿": [
"è"
],
"馀": [
"yú"
],
"馁": [
"něi"
],
"馃": [
"guǒ"
],
"馄": [
"hún"
],
"馅": [
"xiàn"
],
"馆": [
"guǎn"
],
"馇": [
"chā"
],
"馈": [
"kuì"
],
"馊": [
"sōu"
],
"馋": [
"chán"
],
"馉": [
"gǔ"
],
"馌": [
"yè"
],
"馍": [
"mó"
],
"馏": [
"liù",
"liú"
],
"馐": [
"xiū"
],
"馑": [
"jǐn"
],
"馒": [
"mán"
],
"馓": [
"sǎn"
],
"馔": [
"zhuàn"
],
"馕": [
"náng",
"nǎng"
],
"首": [
"shǒu"
],
"馗": [
"kuí",
"qiú"
],
"馘": [
"guó"
],
"香": [
"xiāng"
],
"馥": [
"fù"
],
"馨": [
"xīn"
],
"马": [
"mǎ"
],
"驭": [
"yù"
],
"驮": [
"tuó"
],
"驯": [
"xùn"
],
"驰": [
"chí"
],
"驱": [
"qū"
],
"驳": [
"bó"
],
"驴": [
"lǘ"
],
"驵": [
"zǎng"
],
"驶": [
"shǐ"
],
"驷": [
"sì"
],
"驸": [
"fù"
],
"驹": [
"jū"
],
"驺": [
"zōu"
],
"驻": [
"zhù"
],
"驼": [
"tuó"
],
"驽": [
"nú"
],
"驾": [
"jià"
],
"驿": [
"yì"
],
"骀": [
"tái"
],
"骁": [
"xiāo"
],
"骂": [
"mà"
],
"骄": [
"jiāo"
],
"骅": [
"huá"
],
"骆": [
"luò"
],
"骇": [
"hài"
],
"骈": [
"pián"
],
"骊": [
"lí"
],
"骋": [
"chěng"
],
"验": [
"yàn"
],
"骍": [
"xīng"
],
"骎": [
"qīn"
],
"骏": [
"jùn"
],
"骐": [
"qí"
],
"骑": [
"qí"
],
"骒": [
"kè"
],
"骓": [
"zhuī"
],
"骖": [
"cān"
],
"骗": [
"piàn"
],
"骘": [
"zhì"
],
"骙": [
"kuí"
],
"骚": [
"sāo",
"sǎo"
],
"骛": [
"wù"
],
"骜": [
"áo"
],
"骝": [
"liú"
],
"骞": [
"qiān"
],
"骟": [
"shàn"
],
"骠": [
"piào",
"biāo"
],
"骡": [
"luó"
],
"骢": [
"cōng"
],
"骣": [
"chǎn"
],
"骤": [
"zhòu"
],
"骥": [
"jì"
],
"骧": [
"xiāng"
],
"骨": [
"gǔ",
"gū"
],
"骰": [
"tóu"
],
"骶": [
"dǐ"
],
"骷": [
"kū"
],
"骸": [
"hái"
],
"骺": [
"hóu"
],
"骼": [
"gé"
],
"髀": [
"bì"
],
"髁": [
"kē"
],
"髂": [
"qià"
],
"髅": [
"lóu"
],
"髋": [
"kuān"
],
"髌": [
"bìn"
],
"髑": [
"dú"
],
"髓": [
"suǐ"
],
"高": [
"gāo"
],
"髡": [
"kūn"
],
"髦": [
"máo"
],
"髫": [
"tiáo"
],
"髭": [
"zī"
],
"髯": [
"rán"
],
"髹": [
"xiū"
],
"髻": [
"jì"
],
"鬃": [
"zōng"
],
"鬈": [
"quán"
],
"鬏": [
"jiū"
],
"鬓": [
"bìn"
],
"鬟": [
"huán"
],
"鬣": [
"liè"
],
"鬯": [
"chàng"
],
"鬲": [
"gé",
"lì"
],
"鬹": [
"guī"
],
"鬻": [
"yù"
],
"鬼": [
"guǐ"
],
"魁": [
"kuí"
],
"魂": [
"hún"
],
"魃": [
"bá"
],
"魄": [
"pò"
],
"魅": [
"mèi"
],
"魆": [
"xū"
],
"魇": [
"yǎn"
],
"魈": [
"xiāo"
],
"魉": [
"liǎng"
],
"魍": [
"wǎng"
],
"魏": [
"wèi"
],
"魑": [
"chī"
],
"魔": [
"mó"
],
"鱼": [
"yú"
],
"鱽": [
"dāo"
],
"鱾": [
"jǐ"
],
"鱿": [
"yóu"
],
"鲀": [
"tún"
],
"鲁": [
"lǔ"
],
"鲂": [
"fáng"
],
"鲃": [
"bā",
"bà"
],
"鲅": [
"bà"
],
"鲆": [
"píng"
],
"鲇": [
"nián"
],
"鲈": [
"lú"
],
"鲉": [
"yóu"
],
"鲊": [
"zhǎ",
"zhà"
],
"鲋": [
"fù"
],
"鲌": [
"bó",
"bà"
],
"鲍": [
"bào"
],
"鲎": [
"hòu"
],
"鲏": [
"pí"
],
"鲐": [
"tái"
],
"鲑": [
"guī",
"xié"
],
"鲔": [
"wěi"
],
"鲙": [
"kuài"
],
"鲚": [
"jì"
],
"鲛": [
"jiāo"
],
"鲜": [
"xiān",
"xiǎn"
],
"鲞": [
"xiǎng"
],
"鲟": [
"xún"
],
"鲠": [
"gěng"
],
"鲡": [
"lí"
],
"鲢": [
"lián"
],
"鲣": [
"jiān"
],
"鲤": [
"lǐ"
],
"鲥": [
"shí"
],
"鲦": [
"tiáo"
],
"鲧": [
"gǔn"
],
"鲨": [
"shā"
],
"鲩": [
"huàn"
],
"鲪": [
"jūn"
],
"鲫": [
"jì"
],
"鲬": [
"yǒng"
],
"鲭": [
"qīng"
],
"鲮": [
"líng"
],
"鲯": [
"qí"
],
"鲰": [
"zōu"
],
"鲱": [
"fēi"
],
"鲲": [
"kūn"
],
"鲳": [
"chāng"
],
"鲴": [
"gù"
],
"鲵": [
"ní"
],
"鲷": [
"diāo"
],
"鲸": [
"jīng"
],
"鲹": [
"shēn"
],
"鲺": [
"shī"
],
"鲻": [
"zī"
],
"鲼": [
"fèn"
],
"鲽": [
"dié"
],
"鳀": [
"tí"
],
"鳁": [
"wēn"
],
"鳂": [
"wēi"
],
"鳃": [
"sāi",
"xǐ"
],
"鳄": [
"è"
],
"鳅": [
"qiū"
],
"鳆": [
"fù"
],
"鳇": [
"huáng"
],
"鳈": [
"quán"
],
"鳉": [
"jiāng"
],
"鳊": [
"biān"
],
"鲾": [
"bī"
],
"鳌": [
"áo"
],
"鳍": [
"qí"
],
"鳎": [
"tǎ"
],
"鳏": [
"guān"
],
"鳐": [
"yáo"
],
"鳑": [
"páng"
],
"鳓": [
"lè"
],
"鳔": [
"biào"
],
"鳕": [
"xuě"
],
"鳖": [
"biē"
],
"鳗": [
"mán"
],
"鳘": [
"mǐn"
],
"鳙": [
"yōng"
],
"鳚": [
"wèi"
],
"鳜": [
"guì",
"jué"
],
"鳝": [
"shàn"
],
"鳞": [
"lín"
],
"鳟": [
"zūn"
],
"鳡": [
"gǎn"
],
"鳢": [
"lǐ"
],
"鳤": [
"guǎn"
],
"鸟": [
"niǎo"
],
"鸠": [
"jiū"
],
"鸡": [
"jī"
],
"鸢": [
"yuān"
],
"鸣": [
"míng"
],
"鸤": [
"shī"
],
"鸥": [
"ōu"
],
"鸦": [
"yā"
],
"鸨": [
"bǎo"
],
"鸩": [
"zhèn"
],
"鸪": [
"gū"
],
"鸫": [
"dōng"
],
"鸬": [
"lú"
],
"鸭": [
"yā"
],
"鸮": [
"xiāo"
],
"鸯": [
"yāng"
],
"鸰": [
"líng"
],
"鸱": [
"chī"
],
"鸲": [
"qú"
],
"鸳": [
"yuān"
],
"鸵": [
"tuó"
],
"鸶": [
"sī"
],
"鸷": [
"zhì"
],
"鸸": [
"ér"
],
"鸹": [
"guā"
],
"鸺": [
"xiū"
],
"鸻": [
"héng"
],
"鸼": [
"zhōu"
],
"鸽": [
"gē"
],
"鸾": [
"luán"
],
"鸿": [
"hóng"
],
"鹀": [
"wú"
],
"鹁": [
"bó"
],
"鹂": [
"lí"
],
"鹃": [
"juān"
],
"鹄": [
"hú"
],
"鹅": [
"é"
],
"鹆": [
"yù"
],
"鹇": [
"xián"
],
"鹈": [
"tí"
],
"鹉": [
"wǔ"
],
"鹊": [
"què"
],
"鹋": [
"miáo"
],
"鹌": [
"ān"
],
"鹎": [
"bēi"
],
"鹏": [
"péng"
],
"鹐": [
"qiān"
],
"鹑": [
"chún",
"tuán"
],
"鹕": [
"hú"
],
"鹗": [
"è"
],
"鹚": [
"cí"
],
"鹛": [
"méi"
],
"鹜": [
"wù"
],
"鹘": [
"gǔ",
"hú"
],
"鹝": [
"yì"
],
"鹞": [
"yào"
],
"鹟": [
"wēng"
],
"鹠": [
"liú"
],
"鹡": [
"jí"
],
"鹣": [
"jiān"
],
"鹤": [
"hè"
],
"鹦": [
"yīng"
],
"鹧": [
"zhè"
],
"鹨": [
"liù"
],
"鹩": [
"liáo"
],
"鹪": [
"jiāo"
],
"鹫": [
"jiù"
],
"鹬": [
"yù"
],
"鹭": [
"lù"
],
"鹮": [
"huán"
],
"鹰": [
"yīng"
],
"鹱": [
"hù"
],
"鹲": [
"méng"
],
"鹳": [
"guàn"
],
"鹿": [
"lù"
],
"麂": [
"jǐ"
],
"麇": [
"jūn",
"qún"
],
"麈": [
"zhǔ"
],
"麋": [
"mí"
],
"麒": [
"qí"
],
"麓": [
"lù"
],
"麝": [
"shè"
],
"麟": [
"lín"
],
"麦": [
"mài"
],
"麸": [
"fū"
],
"麻": [
"má"
],
"麽": [
"mó",
"me",
"ma"
],
"麾": [
"huī"
],
"黄": [
"huáng"
],
"黇": [
"tiān"
],
"黉": [
"hóng"
],
"黍": [
"shǔ"
],
"黎": [
"lí"
],
"黏": [
"nián"
],
"黑": [
"hēi"
],
"墨": [
"mò"
],
"黔": [
"qián"
],
"默": [
"mò"
],
"黛": [
"dài"
],
"黜": [
"chù"
],
"黝": [
"yǒu"
],
"黟": [
"yī"
],
"黠": [
"xiá"
],
"黢": [
"qū"
],
"黥": [
"qíng"
],
"黧": [
"lí"
],
"黩": [
"dú"
],
"黯": [
"àn"
],
"黹": [
"zhǐ"
],
"黻": [
"fú"
],
"黼": [
"fǔ"
],
"黾": [
"mǐn",
"miǎn",
"měng"
],
"鼋": [
"yuán"
],
"鼍": [
"tuó"
],
"鼎": [
"dǐng"
],
"鼐": [
"nài"
],
"鼒": [
"zī"
],
"鼓": [
"gǔ"
],
"鼗": [
"táo"
],
"鼙": [
"pí"
],
"鼠": [
"shǔ"
],
"鼢": [
"fén"
],
"鼩": [
"qú"
],
"鼫": [
"shí"
],
"鼬": [
"yòu"
],
"鼯": [
"wú"
],
"鼱": [
"jīng"
],
"鼷": [
"xī"
],
"鼹": [
"yǎn"
],
"鼻": [
"bí"
],
"鼾": [
"hān"
],
"齁": [
"hōu"
],
"齉": [
"nàng"
],
"齐": [
"qí",
"jì",
"zī",
"zhāi"
],
"齑": [
"jī"
],
"齿": [
"chǐ"
],
"龀": [
"chèn"
],
"龁": [
"hé"
],
"龃": [
"jǔ"
],
"龄": [
"líng"
],
"龅": [
"bāo"
],
"龆": [
"tiáo"
],
"龇": [
"zī"
],
"龈": [
"yín",
"kěn"
],
"龉": [
"yǔ"
],
"龊": [
"chuò"
],
"龋": [
"qǔ"
],
"龌": [
"wò"
],
"龙": [
"lóng"
],
"龚": [
"gōng"
],
"龛": [
"kān"
],
"龟": [
"guī",
"jūn",
"qiū"
],
"龠": [
"yuè"
]
};
| yihui/zdict.js | 62 | 汉典网站数据（汉字、拼音、释义等） | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/learn-chars.js | JavaScript | import zDict from "./zdict.js";
let d = document.getElementById('learn-chars');
if (!d) {
const s = document.currentScript;
if (!s) throw '抱歉，本程序不支持您的古董浏览器，请尝试使用 Chrome/Firefox/Edge 等现代浏览器';
d = document.createElement('div');
d.id = "learn-chars";
s.after(d);
}
// 学习字库、总字库、挑战字库
var chars = [], freqs = zDict.freqs.split(''), cChars = freqs.slice();
// 安插基本元素，用来存放拼音、汉字等信息
if (d.childElementCount === 0) d.innerHTML = '<div id="learn-toolbar"></div>' +
'<div class="char-block">' +
'<div class="pinyin" contenteditable></div>' +
'<div class="char-box kai">' +
'<span class="char"></span><span class="num"></span></div>' +
'</div>' +
'<div class="meaning"></div>' +
'<p class="source kai right"></p>' +
'<div id="learn-settings"><p class="seal-line seal-top">密封线内不要答题</p>' +
'<textarea id="learn-candidates"></textarea>' +
'<p><span><span>字符范围：从第</span> <input type="number" value="1" min="1"> ' +
'<span>字开始向后选取</span> <input type="number" value="20" min="0" step="10"> ' +
'<span>字；韵母（可选）：<input type="text" class="yunmu"></span></span> ' +
'<button type="button" id="learn-set">确定</button></p>' +
'<p class="seal-line seal-bottom">密封线内不要答题</p>';
function sampleOne(x) {
return x[Math.floor(Math.random() * x.length)];
}
function noAccent(x) {
return x.normalize('NFD').replace(/[\u0300-\u036f]/g, '');
}
// 比较原始拼音是否相同，如果不同，去掉音调之后再比较
function checkPinyin(x1, x2) {
x1 = x1.toLowerCase();
return x2.split(' - ').indexOf(x1) > -1 || noAccent(x2).split(' - ').indexOf(x1) > -1;
}
var tb = d.querySelector('#learn-toolbar'), cb = d.querySelector('.char-block'),
py = cb.querySelector('.pinyin'), zi = cb.querySelector('.char'),
mn = d.querySelector('.meaning'), sc = d.querySelector('.source'),
ls = d.querySelector('#learn-settings'), lc = ls.querySelector('#learn-candidates');
// 几种使用模式的单选框
tb.innerHTML || ['学习', '复习', '测验', '挑战'].forEach(function(el, i) {
tb.innerHTML += '<input name="mode" type="radio" id="mode-'+ i +
'" ' + (i === 0 ? 'checked' : '') +
'/><label for="mode-' + i + '" class="label">' + el + '</label> ';
});
var mode = 0;
// 浏览器的本地存储
var S = {
"get": function(k) { return localStorage.getItem(k); },
"set": function(k, d) { try { localStorage.setItem(k, d); } catch (e) {} },
"remove": function(k) { localStorage.removeItem(k); }
};
// 加载字库；如果以前有保存过字库，就用以前存的，否则用汉字频度表
var key1 = 'candidate-chars';
lc.value = S.get(key1);
if (!lc.value) lc.value = zDict.freqs;
// 保存学过的字，供复习用
var key2 = 'learned-chars', p = [-1, 0, -1];
function saveChar(x, key) {
var data = S.get(key);
if (!data) { data = ''; } else if (data.match(x)) return;
data += x;
S.set(key, data);
}
function learnedChars(key) {
var x = S.get(key);
return x ? x.split('') : [];
}
function setChars() {
p = [-1, 0, -1];
chars = lc.value.split('');
if (lc.value !== '' && lc.value !== zDict.freqs) {
var v = [];
chars.forEach(function(x) {
v.indexOf(x) === -1 && zDict.freqs.indexOf(x) >= 0 && v.push(x);
});
chars = [];
freqs.forEach(function(x) {
v.indexOf(x) >= 0 && chars.push(x);
});
lc.value = chars.join('');
S.set(key1, lc.value);
} else {
S.remove(key1);
}
if (chars.length === 0) chars = freqs;
var ym = ls.querySelector('input.yunmu').value;
if (ym) chars = chars.filter(function(char) {
var info = zDict.chars[char];
return (noAccent(Object.keys(info).join(',')) + ',').match(ym + ',');
});
var n = [], ns = ls.querySelectorAll('input[type="number"]'), n0 = ns[0], n1 = ns[1];
n[0] = +n0.value; n[1] = +n1.value;
if (n[0] < 1 || n[0] > chars.length) n0.value = n[0] = 1;
if (n[1] < 0) n1.value = n[1] = 0;
// 特例：如果设定总共使用 0 个字符，那么选择所有字符
if (n[1] > 0) chars = chars.slice(n[0] - 1, n[0] - 1 + n[1]);
S.remove(key2);
d.querySelectorAll('.review').forEach(removeEl); // 重新生成复习字块
mode === 1 && renderReview();
}
setChars();
// 按顺序显示一字及其相关信息
function renderChar(char) {
py.innerText = zi.innerText = mn.innerText = zi.nextElementSibling.innerText = '';
if (mode != 3) sc.innerText = '';
py.setAttribute('contenteditable', true);
cb.classList.remove('correct', 'wrong');
var num; // 挑战模式下的字符编号
if (!char) {
switch (mode) {
case 0:
// 学习模式：顺序显示一字
if (p[0] >= chars.length - 1) p[0] = -1;
char = chars[++p[0]];
saveChar(char, key2);
break;
case 1:
// 复习模式：显示学习过的字
var lChars = learnedChars(key2);
if (lChars.length === 0) {
py.innerHTML = '<p style="font-size: .5em;">学习记录都没得，复习个锤子哦</p>';
return;
}
// 从全集中寻找下一个历史记录中的字
while (lChars.indexOf(char) === -1) {
if (p[1] >= chars.length - 1) p[1] = -1;
char = chars[++p[1]];
}
break;
case 2:
// 测验模式：依次测试全集拼音
if (p[2] >= chars.length - 1) {
p[2] = -1;
return alert('测验结束！');
}
char = chars[++p[2]];
break;
case 3:
// 挑战模式：随机抽取一字测验
char = sampleOne(cChars);
cChars.splice(cChars.indexOf(char), 1);
break;
}
}
if (mode === 1) highlightReview();
var info = renderPinyin(char, zi, py, ' - ');
if (!info) return;
renderMeaning(info);
sc.innerHTML = '资料来源：汉典（<a href="https://www.zdic.net/hans/' + char + '" target="_blank">查看详情</a>）';
}
function renderPinyin(char, zi, py, sep) {
zi.innerText = char;
zi.nextElementSibling.innerText = freqs.indexOf(char) + 1;
var info = zDict.chars[char], pys = Object.keys(info);
if (mode >= 2) {
py.dataset.pinyin = pys.join(' - '); // 将正确拼音保存在数据中
py.focus();
// 如果拼音框在视窗外，则自动将它滚到视窗内
var rect = py.getBoundingClientRect();
if (rect.top < 0 || rect.bottom > window.innerHeight) py.scrollIntoView();
return;
}
py.innerText = pys.join(sep);
return info;
}
function renderMeaning(info) {
let me = '';
for (let k in info) {
me += `<p class="py">${k}</p><ol><li>${info[k].join('</li><li>')}</li></ol>`;
};
mn.innerHTML = me;
}
// 初始随机显示一个字
renderChar(sampleOne(freqs));
// 戳一下换一字
zi.parentElement.addEventListener('click', function(e) {
renderChar();
});
function removeEl(el) { el && el.remove(); }
// 高亮学习过的字
function highlightReview() {
var el = d.querySelector('.current'); el && el.classList.remove('current');
d.querySelectorAll('.review')[p[1]].querySelector('.char-box').classList.add('current');
}
// 更换模式
function modeChange(e) {
mode = +this.id.replace('mode-', '');
d.classList[mode === 1 ? 'add' : 'remove']('review-pane');
d.classList.remove('review-all');
renderChar();
}
// 复习模式下把字集中的每个字都渲染出来，但默认是隐藏的
function renderReview() {
var rs = d.querySelectorAll('.review'), lChars = learnedChars(key2);
rs.forEach(function(el, i) {
i < lChars.length && el.classList.add('review-show');
});
if (rs.length >= chars.length) return;
var all = d.classList.contains('review-all');
chars.forEach(function(char, i) {
// 已经生成的字就表再生成了；若不显示所有的字，那么只生成学过的字
if (i < rs.length || (!all && i >= lChars.length)) return;
var nb = cb.cloneNode(true), zi = nb.querySelector('.char');
renderPinyin(char, zi, nb.querySelector('.pinyin'), '\n');
zi.parentElement.addEventListener('click', function(e) {
p[1] = i;
renderChar(char);
});
nb.classList.add('review', all ? 'review' : 'review-show');
d.insertBefore(nb, cb);
});
}
d.querySelectorAll('input[name="mode"]').forEach(function(el, i) {
el.addEventListener('change', modeChange);
i === 1 && el.addEventListener('click', function(e) {
// 点击复习单选框，显示或隐藏还没学过的字
mode === i && d.classList.toggle('review-all');
renderReview();
});
i >= 2 && el.addEventListener('keyup', function(e) {
e.key === 'Enter' && renderChar();
});
});
// 测验
var nw = 0; // 挑战模式下的错字个数
py.addEventListener('blur', function(e) {
// 非测试模式、或者已经结束测验的情况下提前退出
if (mode < 2 || (mode === 2 && p[2] === -1)) return;
var v = this.innerText, ans = this.dataset.pinyin;
if (checkPinyin(v.trim(), ans)) {
cb.classList.add('correct');
this.innerText = ans;
} else {
if (mode !== 2 || !/^\s+$/.test(v)) cb.classList.add('wrong');
if (mode === 3) nw++;
v = v.trim();
this.innerText = v === '' ? ans : v + ' -> ' + ans;
py.removeAttribute('contenteditable');
};
d.querySelector('input[id="mode-' + mode + '"]').focus();
if (mode === 3) {
renderMeaning(zDict.chars[zi.innerText]);
var N = freqs.length, nc = N - cChars.length; // 已挑战样本量
if (nc >= 2) {
var m = 1 - nw/nc, s = 1.96 * Math.sqrt(N * (N - nc) / (nc - 1) * m * (1 - m));
var M = N * m, M1 = M - s, M2 = M + s;
if (M1 < 0) M1 = 0;
if (M2 > N) M2 = N;
M = Math.round(M); M1 = Math.round(M1); M2 = Math.round(M2);
sc.innerHTML = '已挑战 ' + nc + ' 字（错 ' + nw + ' 字）<br/>您的识字量估计为 '
+ M + '，其 95% 近似置信区间为【' + M1 + '，' + M2 + '】';
}
}
});
// 除了离开输入框，也可以用回车键提交答案
['keypress', 'keyup'].map(function(evt) {
py.addEventListener(evt, function(e) {
e.key === 'Enter' && (e.preventDefault(), evt === 'keyup' && this.blur());
});
});
// 重设字库
ls.querySelector('#learn-set').addEventListener('click', function(e) {
S.remove(key2);
setChars();
});
| yihui/zdict.js | 62 | 汉典网站数据（汉字、拼音、释义等） | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/pinyin-finals.js | JavaScript | import chars from "./data-pinyin.js";
import freqs from "./data-freqs.js";
let d = document.getElementById('pinyin-finals');
if (!d) {
const s = document.currentScript;
if (!s) throw '抱歉，本程序不支持您的古董浏览器，请尝试使用 Chrome/Firefox/Edge 等现代浏览器';
d = document.createElement('div');
d.id = "pinyin-chars";
s.after(d);
}
function noAccent(x) {
let x1 = x.normalize('NFD').replace(/[\u0300-\u036f]/g, '');
let x2 = x.replace(/[ǖǘǚǜ]/g, 'ü')
return x2.match('ü') ? x1.replace('u', 'ü') : x1;
}
let k1, k2, x = {}, r = /^([zcs]h|[bpmfdtlngkhjqxzcsryw])/;
[
'a', 'ia', 'ua', 'o', 'uo', 'e', 'i', 'u', 'ü',
'an', 'ian', 'uan', 'üan', 'en', 'in', 'un', 'ün',
'ai', 'uai', 'ao', 'iao', 'ei', 'ui', 'ou', 'iu', 'er', 'ie', 'üe',
'ang', 'iang', 'uang', 'eng', 'ing', 'ong', 'iong'
].forEach(i => {
x[i] = [];
});
// 只取前六千字，最后一千实在太生僻
freqs.split('').slice(0, 6000).forEach(i => {
chars[i].forEach(j => {
k1 = j.replace(r, ''); // 带声调的韵母
k2 = noAccent(k1); // 去除声调的韵母
// 忽略一些边边角角的韵母
if (['n', 'ng', 'hng'].indexOf(k2) > -1) return;
if (/^u(n|an|e)?$/.test(k2) && /^[jqxy]/.test(j)) k2 = k2.replace('u', 'ü');
if (/^(e|an)$/.test(k2) && /^y/.test(j)) k2 = 'i' + k2;
if (k2 === 'an' && /^y/.test(j)) k2 = 'ian';
if (k2 === 'i') {
if (/^[zcs]/.test(j)) k2 = 'z';
if (/^(r|[zcs]h)/.test(j)) k2 = 'r';
}
if (!x[k2]) x[k2] = [];
let a = 0;
if (/[āōēīūǖ]/.test(j)) a = 1;
if (/[áóéíúǘ]/.test(j)) a = 2;
if (/[ǎǒěǐǔǚ]/.test(j)) a = 3;
if (/[àòèìùǜ]/.test(j)) a = 4;
x[k2].push([j, i, a]);
});
});
let h = '<nav id="TableOfContents">';
Object.keys(x).forEach(el => {
h += '<a href="#' + el + '" class="toc-finals">' + el + '</a>';
});
h += '</nav><div style="text-align: center; margin-top: 1em;">';
'aāáǎà'.split('').forEach(function(a, i) {
h += '<div class="char-block accent-legend char-accent-' + i +
'"><div class="pinyin">' + a + '</div></div>';
});
h += '</div><div class="char-section">';
for (let i in x) {
h += '<h2 id="' + i + '">' + i + '</h2>';
let w = 1;
x[i].forEach(el => {
w = Math.max(w, el[0].length);
});
x[i].forEach(el => {
h += '<div class="char-block char-width-' + w + ' char-accent-' + el[2] + '">' +
'<div class="pinyin">' + el[0] +
'</div><div class="char-box"><a href="https://www.zdic.net/hans/' + el[1] +
'" target="_blank">' + el[1] + '</a></div></div>';
});
}
h += '</div>'
d.innerHTML = h;
const d2 = d.querySelector('.char-section');
document.querySelectorAll('.accent-legend').forEach(function(el, i) {
el.onclick = function(e) {
this.classList.toggle('accent-clicked');
d2.classList.toggle('accent-show-' + i);
};
});
| yihui/zdict.js | 62 | 汉典网站数据（汉字、拼音、释义等） | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
js/zdict.js | JavaScript | import chars from "./data-chars.js";
import freqs from "./data-freqs.js";
export default { chars, freqs };
| yihui/zdict.js | 62 | 汉典网站数据（汉字、拼音、释义等） | JavaScript | yihui | Yihui Xie | rstudio swissre merck |
__test__/index.spec.ts | TypeScript | import { readFile } from 'fs/promises'
import { join } from 'path'
import * as fontkit from '@yisibl/fontkit'
import test from 'ava'
import { decode } from '../index'
test('should be converting WOFF2 to TTF', async (t) => {
const font = await readFile(join(__dirname, './fa-brands-400-v6.2.woff2'))
const output = decode(font)
const fontkitOut = fontkit.openSync(output)
t.is(fontkitOut.type, 'TTF') // font type
})
test('should be a TTF font converted by fontkit check', async (t) => {
const font = await readFile(join(__dirname, './fa-regular-400-v5.15.4.woff2'))
const output = decode(font)
const fontkitOut = fontkit.openSync(output)
t.is(fontkitOut.type, 'TTF')
t.is(fontkitOut.directory.numTables, 13) // table count
t.is(fontkitOut.directory.tables.glyf.length, 28076) // glyf table size
t.is(fontkitOut.directory.tables.loca.length, 310) // glyf table size
})
| yisibl/node-woff2-rs | 16 | A WOFF2 decompressor converts WOFF2 to TTF or OTF, powered by Rust based woff2-rs and napi-rs | JavaScript | yisibl | 一丝 | Alibaba Group |
benchmark/bench.mjs | JavaScript | import { promises as fs } from 'fs'
import path, { join } from 'path'
import { fileURLToPath } from 'url'
import { convertWOFF2ToTTF } from '@napi-rs/ttf2woff2'
import b from 'benny'
import wawoff from 'wawoff2'
import woff2Next from 'woff2-next'
import woff2Rs from '../index.js'
const __filename = fileURLToPath(import.meta.url)
const __dirname = path.resolve(path.dirname(__filename))
async function run() {
// const font1 = await fs.readFile(join(__dirname, '../__test__/fa-brands-400-v6.2.woff2'))
const font1 = await fs.readFile(join(__dirname, '../__test__/fa-regular-400-v5.15.4.woff2'))
await b.suite(
'WOFF2 to TTF (Use Font Awesome)',
b.add('woff2-next(node-gyp binding)', () => {
woff2Next.decode(font1)
}),
b.add('@napi-rs/ttf2woff2(Rust binding)', () => {
convertWOFF2ToTTF(font1)
}),
b.add('@woff2/woff2-rs(Pure Rust)', () => {
woff2Rs.decode(font1)
}),
b.add('wawoff(Wasm)', async () => {
await wawoff.decompress(font1)
}),
b.cycle(),
b.complete(),
)
}
run().catch((e) => {
console.error(e)
})
| yisibl/node-woff2-rs | 16 | A WOFF2 decompressor converts WOFF2 to TTF or OTF, powered by Rust based woff2-rs and napi-rs | JavaScript | yisibl | 一丝 | Alibaba Group |
build.rs | Rust | extern crate napi_build;
fn main() {
napi_build::setup();
}
| yisibl/node-woff2-rs | 16 | A WOFF2 decompressor converts WOFF2 to TTF or OTF, powered by Rust based woff2-rs and napi-rs | JavaScript | yisibl | 一丝 | Alibaba Group |
example/index.mjs | JavaScript | import { promises as fs } from 'fs'
import path, { join } from 'path'
import { fileURLToPath } from 'url'
import woff2Rs from '../index.js'
const __filename = fileURLToPath(import.meta.url)
const __dirname = path.resolve(path.dirname(__filename))
async function toTTF() {
const font = await fs.readFile(join(__dirname, '../__test__/fa-regular-400-v5.15.4.woff2'))
const outputBuffer = woff2Rs.decode(font) // output TTF buffer
await fs.writeFile(join(__dirname, 'fa-regular-400.ttf'), outputBuffer)
}
toTTF()
| yisibl/node-woff2-rs | 16 | A WOFF2 decompressor converts WOFF2 to TTF or OTF, powered by Rust based woff2-rs and napi-rs | JavaScript | yisibl | 一丝 | Alibaba Group |
index.d.ts | TypeScript | /* tslint:disable */
/* eslint-disable */
/* auto-generated by NAPI-RS */
export function decode(input: Buffer): Buffer
| yisibl/node-woff2-rs | 16 | A WOFF2 decompressor converts WOFF2 to TTF or OTF, powered by Rust based woff2-rs and napi-rs | JavaScript | yisibl | 一丝 | Alibaba Group |
index.js | JavaScript | const { existsSync, readFileSync } = require('fs')
const { join } = require('path')
const { platform, arch } = process
let nativeBinding = null
let localFileExisted = false
let loadError = null
function isMusl() {
// For Node 10
if (!process.report || typeof process.report.getReport !== 'function') {
try {
const lddPath = require('child_process').execSync('which ldd').toString().trim()
return readFileSync(lddPath, 'utf8').includes('musl')
} catch (e) {
return true
}
} else {
const { glibcVersionRuntime } = process.report.getReport().header
return !glibcVersionRuntime
}
}
switch (platform) {
case 'android':
switch (arch) {
case 'arm64':
localFileExisted = existsSync(join(__dirname, 'woff2-rs.android-arm64.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.android-arm64.node')
} else {
nativeBinding = require('@woff2/woff2-rs-android-arm64')
}
} catch (e) {
loadError = e
}
break
case 'arm':
localFileExisted = existsSync(join(__dirname, 'woff2-rs.android-arm-eabi.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.android-arm-eabi.node')
} else {
nativeBinding = require('@woff2/woff2-rs-android-arm-eabi')
}
} catch (e) {
loadError = e
}
break
default:
throw new Error(`Unsupported architecture on Android ${arch}`)
}
break
case 'win32':
switch (arch) {
case 'x64':
localFileExisted = existsSync(join(__dirname, 'woff2-rs.win32-x64-msvc.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.win32-x64-msvc.node')
} else {
nativeBinding = require('@woff2/woff2-rs-win32-x64-msvc')
}
} catch (e) {
loadError = e
}
break
case 'ia32':
localFileExisted = existsSync(join(__dirname, 'woff2-rs.win32-ia32-msvc.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.win32-ia32-msvc.node')
} else {
nativeBinding = require('@woff2/woff2-rs-win32-ia32-msvc')
}
} catch (e) {
loadError = e
}
break
case 'arm64':
localFileExisted = existsSync(join(__dirname, 'woff2-rs.win32-arm64-msvc.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.win32-arm64-msvc.node')
} else {
nativeBinding = require('@woff2/woff2-rs-win32-arm64-msvc')
}
} catch (e) {
loadError = e
}
break
default:
throw new Error(`Unsupported architecture on Windows: ${arch}`)
}
break
case 'darwin':
localFileExisted = existsSync(join(__dirname, 'woff2-rs.darwin-universal.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.darwin-universal.node')
} else {
nativeBinding = require('@woff2/woff2-rs-darwin-universal')
}
break
} catch {}
switch (arch) {
case 'x64':
localFileExisted = existsSync(join(__dirname, 'woff2-rs.darwin-x64.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.darwin-x64.node')
} else {
nativeBinding = require('@woff2/woff2-rs-darwin-x64')
}
} catch (e) {
loadError = e
}
break
case 'arm64':
localFileExisted = existsSync(join(__dirname, 'woff2-rs.darwin-arm64.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.darwin-arm64.node')
} else {
nativeBinding = require('@woff2/woff2-rs-darwin-arm64')
}
} catch (e) {
loadError = e
}
break
default:
throw new Error(`Unsupported architecture on macOS: ${arch}`)
}
break
case 'freebsd':
if (arch !== 'x64') {
throw new Error(`Unsupported architecture on FreeBSD: ${arch}`)
}
localFileExisted = existsSync(join(__dirname, 'woff2-rs.freebsd-x64.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.freebsd-x64.node')
} else {
nativeBinding = require('@woff2/woff2-rs-freebsd-x64')
}
} catch (e) {
loadError = e
}
break
case 'linux':
switch (arch) {
case 'x64':
if (isMusl()) {
localFileExisted = existsSync(join(__dirname, 'woff2-rs.linux-x64-musl.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.linux-x64-musl.node')
} else {
nativeBinding = require('@woff2/woff2-rs-linux-x64-musl')
}
} catch (e) {
loadError = e
}
} else {
localFileExisted = existsSync(join(__dirname, 'woff2-rs.linux-x64-gnu.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.linux-x64-gnu.node')
} else {
nativeBinding = require('@woff2/woff2-rs-linux-x64-gnu')
}
} catch (e) {
loadError = e
}
}
break
case 'arm64':
if (isMusl()) {
localFileExisted = existsSync(join(__dirname, 'woff2-rs.linux-arm64-musl.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.linux-arm64-musl.node')
} else {
nativeBinding = require('@woff2/woff2-rs-linux-arm64-musl')
}
} catch (e) {
loadError = e
}
} else {
localFileExisted = existsSync(join(__dirname, 'woff2-rs.linux-arm64-gnu.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.linux-arm64-gnu.node')
} else {
nativeBinding = require('@woff2/woff2-rs-linux-arm64-gnu')
}
} catch (e) {
loadError = e
}
}
break
case 'arm':
localFileExisted = existsSync(join(__dirname, 'woff2-rs.linux-arm-gnueabihf.node'))
try {
if (localFileExisted) {
nativeBinding = require('./woff2-rs.linux-arm-gnueabihf.node')
} else {
nativeBinding = require('@woff2/woff2-rs-linux-arm-gnueabihf')
}
} catch (e) {
loadError = e
}
break
default:
throw new Error(`Unsupported architecture on Linux: ${arch}`)
}
break
default:
throw new Error(`Unsupported OS: ${platform}, architecture: ${arch}`)
}
if (!nativeBinding) {
if (loadError) {
throw loadError
}
throw new Error(`Failed to load native binding`)
}
const { decode } = nativeBinding
module.exports.decode = decode
| yisibl/node-woff2-rs | 16 | A WOFF2 decompressor converts WOFF2 to TTF or OTF, powered by Rust based woff2-rs and napi-rs | JavaScript | yisibl | 一丝 | Alibaba Group |
simple-test.js | JavaScript | const { plus100 } = require('./index')
console.assert(plus100(0) === 100, 'Simple test failed')
console.info('Simple test passed')
| yisibl/node-woff2-rs | 16 | A WOFF2 decompressor converts WOFF2 to TTF or OTF, powered by Rust based woff2-rs and napi-rs | JavaScript | yisibl | 一丝 | Alibaba Group |
src/lib.rs | Rust | #![deny(clippy::all)]
use napi::bindgen_prelude::Buffer;
use napi_derive::napi;
use woff2::decode::convert_woff2_to_ttf;
#[napi]
pub fn decode(input: Buffer) -> Buffer {
let output = convert_woff2_to_ttf(&mut std::io::Cursor::new(input));
Buffer::from(output.unwrap())
}
| yisibl/node-woff2-rs | 16 | A WOFF2 decompressor converts WOFF2 to TTF or OTF, powered by Rust based woff2-rs and napi-rs | JavaScript | yisibl | 一丝 | Alibaba Group |
biggan.py | Python | #/usr/bin/env python3
# Taken from here: https://github.com/huggingface/pytorch-pretrained-BigGAN
# MIT License
#
# Copyright (c) 2019 Thomas Wolf
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
import torch.nn as nn
import torch.nn.functional as F
import torch
import math
import json
import logging
import os
import shutil
import tempfile
from functools import wraps
from hashlib import sha256
import sys
import copy
import boto3
import requests
from botocore.exceptions import ClientError
from tqdm import tqdm
WEIGHTS_NAME = 'pytorch_model.bin'
CONFIG_NAME = 'config.json'
try:
from urllib.parse import urlparse
except ImportError:
from urlparse import urlparse
try:
from pathlib import Path
PYTORCH_PRETRAINED_BIGGAN_CACHE = Path(os.getenv('PYTORCH_PRETRAINED_BIGGAN_CACHE',
os.path.join(os.getcwd(), '.pytorch_pretrained_biggan')))
except (AttributeError, ImportError):
PYTORCH_PRETRAINED_BIGGAN_CACHE = os.getenv('PYTORCH_PRETRAINED_BIGGAN_CACHE',
os.path.join(os.getcwd(), '.pytorch_pretrained_biggan'))
logger = logging.getLogger(__name__) # pylint: disable=invalid-name
def url_to_filename(url, etag=None):
"""
Convert `url` into a hashed filename in a repeatable way.
If `etag` is specified, append its hash to the url's, delimited
by a period.
"""
url_bytes = url.encode('utf-8')
url_hash = sha256(url_bytes)
filename = url_hash.hexdigest()
if etag:
etag_bytes = etag.encode('utf-8')
etag_hash = sha256(etag_bytes)
filename += '.' + etag_hash.hexdigest()
return filename
def filename_to_url(filename, cache_dir=None):
"""
Return the url and etag (which may be ``None``) stored for `filename`.
Raise ``EnvironmentError`` if `filename` or its stored metadata do not exist.
"""
if cache_dir is None:
cache_dir = PYTORCH_PRETRAINED_BIGGAN_CACHE
if sys.version_info[0] == 3 and isinstance(cache_dir, Path):
cache_dir = str(cache_dir)
cache_path = os.path.join(cache_dir, filename)
if not os.path.exists(cache_path):
raise EnvironmentError("file {} not found".format(cache_path))
meta_path = cache_path + '.json'
if not os.path.exists(meta_path):
raise EnvironmentError("file {} not found".format(meta_path))
with open(meta_path, encoding="utf-8") as meta_file:
metadata = json.load(meta_file)
url = metadata['url']
etag = metadata['etag']
return url, etag
def cached_path(url_or_filename, cache_dir=None):
"""
Given something that might be a URL (or might be a local path),
determine which. If it's a URL, download the file and cache it, and
return the path to the cached file. If it's already a local path,
make sure the file exists and then return the path.
"""
if cache_dir is None:
cache_dir = PYTORCH_PRETRAINED_BIGGAN_CACHE
if sys.version_info[0] == 3 and isinstance(url_or_filename, Path):
url_or_filename = str(url_or_filename)
if sys.version_info[0] == 3 and isinstance(cache_dir, Path):
cache_dir = str(cache_dir)
parsed = urlparse(url_or_filename)
if parsed.scheme in ('http', 'https', 's3'):
# URL, so get it from the cache (downloading if necessary)
return get_from_cache(url_or_filename, cache_dir)
elif os.path.exists(url_or_filename):
# File, and it exists.
return url_or_filename
elif parsed.scheme == '':
# File, but it doesn't exist.
raise EnvironmentError("file {} not found".format(url_or_filename))
else:
# Something unknown
raise ValueError("unable to parse {} as a URL or as a local path".format(url_or_filename))
def split_s3_path(url):
"""Split a full s3 path into the bucket name and path."""
parsed = urlparse(url)
if not parsed.netloc or not parsed.path:
raise ValueError("bad s3 path {}".format(url))
bucket_name = parsed.netloc
s3_path = parsed.path
# Remove '/' at beginning of path.
if s3_path.startswith("/"):
s3_path = s3_path[1:]
return bucket_name, s3_path
def s3_request(func):
"""
Wrapper function for s3 requests in order to create more helpful error
messages.
"""
@wraps(func)
def wrapper(url, *args, **kwargs):
try:
return func(url, *args, **kwargs)
except ClientError as exc:
if int(exc.response["Error"]["Code"]) == 404:
raise EnvironmentError("file {} not found".format(url))
else:
raise
return wrapper
@s3_request
def s3_etag(url):
"""Check ETag on S3 object."""
s3_resource = boto3.resource("s3")
bucket_name, s3_path = split_s3_path(url)
s3_object = s3_resource.Object(bucket_name, s3_path)
return s3_object.e_tag
@s3_request
def s3_get(url, temp_file):
"""Pull a file directly from S3."""
s3_resource = boto3.resource("s3")
bucket_name, s3_path = split_s3_path(url)
s3_resource.Bucket(bucket_name).download_fileobj(s3_path, temp_file)
def http_get(url, temp_file):
req = requests.get(url, stream=True)
content_length = req.headers.get('Content-Length')
total = int(content_length) if content_length is not None else None
progress = tqdm(unit="B", total=total)
for chunk in req.iter_content(chunk_size=1024):
if chunk: # filter out keep-alive new chunks
progress.update(len(chunk))
temp_file.write(chunk)
progress.close()
def get_from_cache(url, cache_dir=None):
"""
Given a URL, look for the corresponding dataset in the local cache.
If it's not there, download it. Then return the path to the cached file.
"""
if cache_dir is None:
cache_dir = PYTORCH_PRETRAINED_BIGGAN_CACHE
if sys.version_info[0] == 3 and isinstance(cache_dir, Path):
cache_dir = str(cache_dir)
if not os.path.exists(cache_dir):
os.makedirs(cache_dir)
# Get eTag to add to filename, if it exists.
if url.startswith("s3://"):
etag = s3_etag(url)
else:
response = requests.head(url, allow_redirects=True)
if response.status_code != 200:
raise IOError("HEAD request failed for url {} with status code {}"
.format(url, response.status_code))
etag = response.headers.get("ETag")
filename = url_to_filename(url, etag)
# get cache path to put the file
cache_path = os.path.join(cache_dir, filename)
if not os.path.exists(cache_path):
# Download to temporary file, then copy to cache dir once finished.
# Otherwise you get corrupt cache entries if the download gets interrupted.
with tempfile.NamedTemporaryFile() as temp_file:
logger.info("%s not found in cache, downloading to %s", url, temp_file.name)
# GET file object
if url.startswith("s3://"):
s3_get(url, temp_file)
else:
http_get(url, temp_file)
# we are copying the file before closing it, so flush to avoid truncation
temp_file.flush()
# shutil.copyfileobj() starts at the current position, so go to the start
temp_file.seek(0)
logger.info("copying %s to cache at %s", temp_file.name, cache_path)
with open(cache_path, 'wb') as cache_file:
shutil.copyfileobj(temp_file, cache_file)
logger.info("creating metadata file for %s", cache_path)
meta = {'url': url, 'etag': etag}
meta_path = cache_path + '.json'
with open(meta_path, 'w', encoding="utf-8") as meta_file:
json.dump(meta, meta_file)
logger.info("removing temp file %s", temp_file.name)
return cache_path
def read_set_from_file(filename):
'''
Extract a de-duped collection (set) of text from a file.
Expected file format is one item per line.
'''
collection = set()
with open(filename, 'r', encoding='utf-8') as file_:
for line in file_:
collection.add(line.rstrip())
return collection
def get_file_extension(path, dot=True, lower=True):
ext = os.path.splitext(path)[1]
ext = ext if dot else ext[1:]
return ext.lower() if lower else ext
PRETRAINED_MODEL_ARCHIVE_MAP = {
'biggan-deep-128': "https://s3.amazonaws.com/models.huggingface.co/biggan/biggan-deep-128-pytorch_model.bin",
'biggan-deep-256': "https://s3.amazonaws.com/models.huggingface.co/biggan/biggan-deep-256-pytorch_model.bin",
'biggan-deep-512': "https://s3.amazonaws.com/models.huggingface.co/biggan/biggan-deep-512-pytorch_model.bin",
}
PRETRAINED_CONFIG_ARCHIVE_MAP = {
'biggan-deep-128': "https://s3.amazonaws.com/models.huggingface.co/biggan/biggan-deep-128-config.json",
'biggan-deep-256': "https://s3.amazonaws.com/models.huggingface.co/biggan/biggan-deep-256-config.json",
'biggan-deep-512': "https://s3.amazonaws.com/models.huggingface.co/biggan/biggan-deep-512-config.json",
}
class BigGANConfig(object):
""" Configuration class to store the configuration of a `BigGAN`.
Defaults are for the 128x128 model.
layers tuple are (up-sample in the layer ?, input channels, output channels)
"""
def __init__(self,
output_dim=128,
z_dim=128,
class_embed_dim=128,
channel_width=128,
num_classes=1000,
layers=[(False, 16, 16),
(True, 16, 16),
(False, 16, 16),
(True, 16, 8),
(False, 8, 8),
(True, 8, 4),
(False, 4, 4),
(True, 4, 2),
(False, 2, 2),
(True, 2, 1)],
attention_layer_position=8,
eps=1e-4,
n_stats=51):
"""Constructs BigGANConfig. """
self.output_dim = output_dim
self.z_dim = z_dim
self.class_embed_dim = class_embed_dim
self.channel_width = channel_width
self.num_classes = num_classes
self.layers = layers
self.attention_layer_position = attention_layer_position
self.eps = eps
self.n_stats = n_stats
@classmethod
def from_dict(cls, json_object):
"""Constructs a `BigGANConfig` from a Python dictionary of parameters."""
config = BigGANConfig()
for key, value in json_object.items():
config.__dict__[key] = value
return config
@classmethod
def from_json_file(cls, json_file):
"""Constructs a `BigGANConfig` from a json file of parameters."""
with open(json_file, "r", encoding='utf-8') as reader:
text = reader.read()
return cls.from_dict(json.loads(text))
def __repr__(self):
return str(self.to_json_string())
def to_dict(self):
"""Serializes this instance to a Python dictionary."""
output = copy.deepcopy(self.__dict__)
return output
def to_json_string(self):
"""Serializes this instance to a JSON string."""
return json.dumps(self.to_dict(), indent=2, sort_keys=True) + "\n"
def snconv2d(eps=1e-12, **kwargs):
return nn.utils.spectral_norm(nn.Conv2d(**kwargs), eps=eps)
def snlinear(eps=1e-12, **kwargs):
return nn.utils.spectral_norm(nn.Linear(**kwargs), eps=eps)
def sn_embedding(eps=1e-12, **kwargs):
return nn.utils.spectral_norm(nn.Embedding(**kwargs), eps=eps)
class SelfAttn(nn.Module):
""" Self attention Layer"""
def __init__(self, in_channels, eps=1e-12):
super(SelfAttn, self).__init__()
self.in_channels = in_channels
self.snconv1x1_theta = snconv2d(in_channels=in_channels, out_channels=in_channels//8,
kernel_size=1, bias=False, eps=eps)
self.snconv1x1_phi = snconv2d(in_channels=in_channels, out_channels=in_channels//8,
kernel_size=1, bias=False, eps=eps)
self.snconv1x1_g = snconv2d(in_channels=in_channels, out_channels=in_channels//2,
kernel_size=1, bias=False, eps=eps)
self.snconv1x1_o_conv = snconv2d(in_channels=in_channels//2, out_channels=in_channels,
kernel_size=1, bias=False, eps=eps)
self.maxpool = nn.MaxPool2d(2, stride=2, padding=0)
self.softmax = nn.Softmax(dim=-1)
self.gamma = nn.Parameter(torch.zeros(1))
def forward(self, x):
_, ch, h, w = x.size()
# Theta path
theta = self.snconv1x1_theta(x)
theta = theta.view(-1, ch//8, h*w)
# Phi path
phi = self.snconv1x1_phi(x)
phi = self.maxpool(phi)
phi = phi.view(-1, ch//8, h*w//4)
# Attn map
attn = torch.bmm(theta.permute(0, 2, 1), phi)
attn = self.softmax(attn)
# g path
g = self.snconv1x1_g(x)
g = self.maxpool(g)
g = g.view(-1, ch//2, h*w//4)
# Attn_g - o_conv
attn_g = torch.bmm(g, attn.permute(0, 2, 1))
attn_g = attn_g.view(-1, ch//2, h, w)
attn_g = self.snconv1x1_o_conv(attn_g)
# Out
out = x + self.gamma*attn_g
return out
class BigGANBatchNorm(nn.Module):
""" This is a batch norm module that can handle conditional input and can be provided with pre-computed
activation means and variances for various truncation parameters.
We cannot just rely on torch.batch_norm since it cannot handle
batched weights (pytorch 1.0.1). We computate batch_norm our-self without updating running means and variances.
If you want to train this model you should add running means and variance computation logic.
"""
def __init__(self, num_features, condition_vector_dim=None, n_stats=51, eps=1e-4, conditional=True):
super(BigGANBatchNorm, self).__init__()
self.num_features = num_features
self.eps = eps
self.conditional = conditional
# We use pre-computed statistics for n_stats values of truncation between 0 and 1
self.register_buffer('running_means', torch.zeros(n_stats, num_features))
self.register_buffer('running_vars', torch.ones(n_stats, num_features))
self.step_size = 1.0 / (n_stats - 1)
if conditional:
assert condition_vector_dim is not None
self.scale = snlinear(in_features=condition_vector_dim, out_features=num_features, bias=False, eps=eps)
self.offset = snlinear(in_features=condition_vector_dim, out_features=num_features, bias=False, eps=eps)
else:
self.weight = torch.nn.Parameter(torch.Tensor(num_features))
self.bias = torch.nn.Parameter(torch.Tensor(num_features))
def forward(self, x, truncation, condition_vector=None):
# Retreive pre-computed statistics associated to this truncation
coef, start_idx = math.modf(truncation / self.step_size)
start_idx = int(start_idx)
if coef != 0.0: # Interpolate
running_mean = self.running_means[start_idx] * coef + self.running_means[start_idx + 1] * (1 - coef)
running_var = self.running_vars[start_idx] * coef + self.running_vars[start_idx + 1] * (1 - coef)
else:
running_mean = self.running_means[start_idx]
running_var = self.running_vars[start_idx]
if self.conditional:
running_mean = running_mean.unsqueeze(0).unsqueeze(-1).unsqueeze(-1)
running_var = running_var.unsqueeze(0).unsqueeze(-1).unsqueeze(-1)
weight = 1 + self.scale(condition_vector).unsqueeze(-1).unsqueeze(-1)
bias = self.offset(condition_vector).unsqueeze(-1).unsqueeze(-1)
out = (x - running_mean) / torch.sqrt(running_var + self.eps) * weight + bias
else:
out = F.batch_norm(x, running_mean, running_var, self.weight, self.bias,
training=False, momentum=0.0, eps=self.eps)
return out
class GenBlock(nn.Module):
def __init__(self, in_size, out_size, condition_vector_dim, reduction_factor=4, up_sample=False,
n_stats=51, eps=1e-12):
super(GenBlock, self).__init__()
self.up_sample = up_sample
self.drop_channels = (in_size != out_size)
middle_size = in_size // reduction_factor
self.bn_0 = BigGANBatchNorm(in_size, condition_vector_dim, n_stats=n_stats, eps=eps, conditional=True)
self.conv_0 = snconv2d(in_channels=in_size, out_channels=middle_size, kernel_size=1, eps=eps)
self.bn_1 = BigGANBatchNorm(middle_size, condition_vector_dim, n_stats=n_stats, eps=eps, conditional=True)
self.conv_1 = snconv2d(in_channels=middle_size, out_channels=middle_size, kernel_size=3, padding=1, eps=eps)
self.bn_2 = BigGANBatchNorm(middle_size, condition_vector_dim, n_stats=n_stats, eps=eps, conditional=True)
self.conv_2 = snconv2d(in_channels=middle_size, out_channels=middle_size, kernel_size=3, padding=1, eps=eps)
self.bn_3 = BigGANBatchNorm(middle_size, condition_vector_dim, n_stats=n_stats, eps=eps, conditional=True)
self.conv_3 = snconv2d(in_channels=middle_size, out_channels=out_size, kernel_size=1, eps=eps)
self.relu = nn.ReLU()
def forward(self, x, cond_vector, truncation):
x0 = x
x = self.bn_0(x, truncation, cond_vector)
x = self.relu(x)
x = self.conv_0(x)
x = self.bn_1(x, truncation, cond_vector)
x = self.relu(x)
if self.up_sample:
x = F.interpolate(x, scale_factor=2, mode='nearest')
x = self.conv_1(x)
x = self.bn_2(x, truncation, cond_vector)
x = self.relu(x)
x = self.conv_2(x)
x = self.bn_3(x, truncation, cond_vector)
x = self.relu(x)
x = self.conv_3(x)
if self.drop_channels:
new_channels = x0.shape[1] // 2
x0 = x0[:, :new_channels, ...]
if self.up_sample:
x0 = F.interpolate(x0, scale_factor=2, mode='nearest')
out = x + x0
return out
class Generator(nn.Module):
def __init__(self, config):
super(Generator, self).__init__()
self.config = config
ch = config.channel_width
condition_vector_dim = config.z_dim * 2
self.gen_z = snlinear(in_features=condition_vector_dim,
out_features=4 * 4 * 16 * ch, eps=config.eps)
layers = []
for i, layer in enumerate(config.layers):
if i == config.attention_layer_position:
layers.append(SelfAttn(ch*layer[1], eps=config.eps))
layers.append(GenBlock(ch*layer[1],
ch*layer[2],
condition_vector_dim,
up_sample=layer[0],
n_stats=config.n_stats,
eps=config.eps))
self.layers = nn.ModuleList(layers)
self.bn = BigGANBatchNorm(ch, n_stats=config.n_stats, eps=config.eps, conditional=False)
self.relu = nn.ReLU()
self.conv_to_rgb = snconv2d(in_channels=ch, out_channels=ch, kernel_size=3, padding=1, eps=config.eps)
self.tanh = nn.Tanh()
def forward(self, cond_vector, truncation):
z = self.gen_z(cond_vector[0].unsqueeze(0))
# We use this conversion step to be able to use TF weights:
# TF convention on shape is [batch, height, width, channels]
# PT convention on shape is [batch, channels, height, width]
z = z.view(-1, 4, 4, 16 * self.config.channel_width)
z = z.permute(0, 3, 1, 2).contiguous()
for i, layer in enumerate(self.layers):
if isinstance(layer, GenBlock):
z = layer(z, cond_vector[i+1].unsqueeze(0), truncation)
# z = layer(z, cond_vector[].unsqueeze(0), truncation)
else:
z = layer(z)
z = self.bn(z, truncation)
z = self.relu(z)
z = self.conv_to_rgb(z)
z = z[:, :3, ...]
z = self.tanh(z)
return z
class BigGAN(nn.Module):
"""BigGAN Generator."""
@classmethod
def from_pretrained(cls, pretrained_model_name_or_path, cache_dir=None, *inputs, **kwargs):
if pretrained_model_name_or_path in PRETRAINED_MODEL_ARCHIVE_MAP:
model_file = PRETRAINED_MODEL_ARCHIVE_MAP[pretrained_model_name_or_path]
config_file = PRETRAINED_CONFIG_ARCHIVE_MAP[pretrained_model_name_or_path]
else:
model_file = os.path.join(pretrained_model_name_or_path, WEIGHTS_NAME)
config_file = os.path.join(pretrained_model_name_or_path, CONFIG_NAME)
try:
resolved_model_file = cached_path(model_file, cache_dir=cache_dir)
resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
except EnvironmentError:
logger.error("Wrong model name, should be a valid path to a folder containing "
"a {} file and a {} file or a model name in {}".format(
WEIGHTS_NAME, CONFIG_NAME, PRETRAINED_MODEL_ARCHIVE_MAP.keys()))
raise
logger.info("loading model {} from cache at {}".format(pretrained_model_name_or_path, resolved_model_file))
# Load config
config = BigGANConfig.from_json_file(resolved_config_file)
logger.info("Model config {}".format(config))
# Instantiate model.
model = cls(config, *inputs, **kwargs)
state_dict = torch.load(resolved_model_file, map_location='cpu' if not torch.cuda.is_available() else None)
model.load_state_dict(state_dict, strict=False)
return model
def __init__(self, config):
super(BigGAN, self).__init__()
self.config = config
self.embeddings = nn.Linear(config.num_classes, config.z_dim, bias=False)
self.generator = Generator(config)
def forward(self, z, class_label, truncation):
assert 0 < truncation <= 1
embed = self.embeddings(class_label)
cond_vector = torch.cat((z, embed), dim=1)
z = self.generator(cond_vector, truncation)
return z
def one_hot_from_int(int_or_list, batch_size=1):
""" Create a one-hot vector from a class index or a list of class indices.
Params:
int_or_list: int, or list of int, of the imagenet classes (between 0 and 999)
batch_size: batch size.
If int_or_list is an int create a batch of identical classes.
If int_or_list is a list, we should have `len(int_or_list) == batch_size`
Output:
array of shape (batch_size, 1000)
"""
if isinstance(int_or_list, int):
int_or_list = [int_or_list]
if len(int_or_list) == 1 and batch_size > 1:
int_or_list = [int_or_list[0]] * batch_size
assert batch_size == len(int_or_list)
array = np.zeros((batch_size, 1000), dtype=np.float32)
for i, j in enumerate(int_or_list):
array[i, j] = 1.0
return array
| yk/clip_music_video | 175 | Code for making music videos using CLIP | Python | yk | Yannic Kilcher | |
create_video.py | Python | from textwrap3 import fill
import moviepy.editor as me
import tempfile
import textwrap
import glob
import os
def createvid(description, image_temp_list, fps=24, duration=0.1):
blackbg = me.ColorClip((720,720), (0, 0, 0))
clips = [me.ImageClip(m.name+".png", duration=duration) for m in image_temp_list]
for img in image_temp_list:
img.close()
concat_clip = me.concatenate_videoclips(clips, method="compose").set_position(('center', 'center'))
if description == "start song":
description = " "
if len(description) > 35:
description = fill(description, 35)
txtClip = me.TextClip(description, color='white', fontsize=30, font='Amiri-regular').set_position('center')
txt_col = txtClip.on_color(size=(blackbg.w, txtClip.h + 10),
color=(0,0,0), pos=('center', 'center'),
col_opacity=0.8)
txt_mov = txt_col.set_position((0, blackbg.h-20-txtClip.h))
comp_list = [blackbg, concat_clip, txt_mov]
final = me.CompositeVideoClip(comp_list).set_duration(concat_clip.duration)
with tempfile.NamedTemporaryFile() as video_tempfile:
final.write_videofile(video_tempfile.name+".mp4", fps=fps)
video_tempfile.seek(0)
for clip in clips:
clip.close()
for clip in comp_list:
clip.close()
return video_tempfile
def concatvids(descriptions, video_temp_list, audiofilepath, fps=24, lyrics=True):
clips = []
for idx, (desc, vid) in enumerate(zip(descriptions, video_temp_list)):
# # compvid_list = []
# # desc = desc[1]
if desc == descriptions[-1][1]:
break
# # elif desc == "start song":
# # desc = " "
# # compvid_list.append(blackbg)
vid = me.VideoFileClip(f'{vid.name}.mp4')#.set_position(('center', 'center'))
# compvid_list.append(vid)
# if len(desc) > 35:
# desc = fill(desc, 35)
# if lyrics:
# txtClip = me.TextClip(desc, color='white', fontsize=30, font='Amiri-regular').set_position('center')
# txt_col = txtClip.on_color(size=(blackbg.w, txtClip.h + 10),
# color=(0,0,0), pos=('center', 'center'), col_opacity=0.8)
# txt_mov = txt_col.set_position((0, blackbg.h-20-txtClip.h))
# compvid_list.append(txt_mov)
# video_tempfile = tempfile.NamedTemporaryFile()
# final = me.CompositeVideoClip(compvid_list).set_duration(vid.duration)
# final.write_videofile(video_tempfile.name+".mp4", fps=fps)
# video_tempfile.seek(0)
# for clip in clips:
# clip.close()
# concat_clip.close()
clips.append(vid)
concat_clip = me.concatenate_videoclips(clips, method="compose").set_position(('center', 'center'))
# concat_clip = me.CompositeVideoClip([blackbg, concat_clip])#.set_duration(vid.duration)
if audiofilepath:
concat_clip.audio = me.AudioFileClip(audiofilepath)
concat_clip.duration = concat_clip.audio.duration
concat_clip.write_videofile(os.path.join('output', f"finaloutput.mp4"), fps=fps)
| yk/clip_music_video | 175 | Code for making music videos using CLIP | Python | yk | Yannic Kilcher | |
main.py | Python | from utils import train, Pars, create_image, create_outputfolder, init_textfile
from dall_e import map_pixels, unmap_pixels, load_model
from stylegan import g_synthesis
from biggan import BigGAN
from tqdm import tqdm
import create_video
import tempfile
import argparse
import torch
import clip
import glob
import os
import math
# Argsparse for commandline options
parser = argparse.ArgumentParser(description='BigGan_Clip')
parser.add_argument('--epochs',
default = 100,
type = int,
help ='Number of Epochs')
parser.add_argument('--generator',
default = 'biggan',
type = str,
choices = ['biggan', 'dall-e', 'stylegan'],
help = 'Choose what type of generator you would like to use BigGan or Dall-E')
parser.add_argument('--textfile',
type = str,
required= True,
help ='Path for the text file')
parser.add_argument('--audiofile',
default = None,
type = str,
required= True,
help ='Path for the mp3 file')
parser.add_argument('--lyrics',
default = True,
type = bool,
help ='Include lyrics')
parser.add_argument('--interpolation',
default = 10,
type = int,
help ='Number of elements to be interpolated per second and feed to the model')
args = parser.parse_args()
epochs = args.epochs
generator = args.generator
textfile = args.textfile
audiofile = args.audiofile
interpol = args.interpolation
lyrics = args.lyrics
sideX = 512
sideY = 512
def main():
# Automatically creates 'output' folder
create_outputfolder()
# Initialize Clip
perceptor, preprocess = clip.load('ViT-B/32')
perceptor = perceptor.eval()
# Load the model
if generator == 'biggan':
model = BigGAN.from_pretrained('biggan-deep-512')
model = model.cuda().eval()
elif generator == 'dall-e':
model = load_model("decoder.pkl", 'cuda')
elif generator == 'stylegan':
model = g_synthesis.eval().cuda()
# Read the textfile
# descs - list to append the Description and Timestamps
descs = init_textfile(textfile)
# list of temporary PTFiles
templist = []
# Loop over the description list
for d in tqdm(descs):
timestamp = d[0]
line = d[1]
# stamps_descs_list.append((timestamp, line))
lats = Pars(gen=generator).cuda()
# Init Generator's latents
if generator == 'biggan':
par = lats.parameters()
lr = 0.1#.07
elif generator == 'stylegan':
par = [lats.normu]
lr = .01
elif generator == 'dall-e':
par = [lats.normu]
lr = .1
# Init optimizer
optimizer = torch.optim.Adam(par, lr)
# tokenize the current description with clip and encode the text
txt = clip.tokenize(line)
percep = perceptor.encode_text(txt.cuda()).detach().clone()
# Training Loop
for i in range(epochs):
zs = train(i, model, lats, sideX, sideY, perceptor, percep, optimizer, line, txt, epochs=epochs, gen=generator)
# save each line's last latent to a torch file temporarily
latent_temp = tempfile.NamedTemporaryFile()
torch.save(zs, latent_temp) #f'./output/pt_folder/{line}.pt')
latent_temp.seek(0)
#append it to templist so it can be accessed later
templist.append(latent_temp)
return templist, descs, model
def sigmoid(x):
x = x * 2. - 1.
return math.tanh(1.5*x/(math.sqrt(1.- math.pow(x, 2.)) + 1e-6)) / 2 + .5
def interpolate(templist, descs, model, audiofile):
video_temp_list = []
# interpole elements between each image
for idx1, pt in enumerate(descs):
# get the next index of the descs list,
# if it z1_idx is out of range, break the loop
z1_idx = idx1 + 1
if z1_idx >= len(descs):
break
current_lyric = pt[1]
# get the interval betwee 2 lines/elements in seconds `ttime`
d1 = pt[0]
d2 = descs[z1_idx][0]
ttime = d2 - d1
# if it is the very first index, load the first pt temp file
# if not assign the previous pt file (z1) to zs variable
if idx1 == 0:
zs = torch.load(templist[idx1])
else:
zs = z1
# compute for the number of elements to be insert between the 2 elements
N = round(ttime * interpol)
print(z1_idx)
# the codes below determine if the output is list (for biggan)
# if not insert it into a list
if not isinstance(zs, list):
z0 = [zs]
z1 = [torch.load(templist[z1_idx])]
else:
z0 = zs
z1 = torch.load(templist[z1_idx])
# loop over the range of elements and generate the images
image_temp_list = []
for t in range(N):
azs = []
for r in zip(z0, z1):
z_diff = r[1] - r[0]
inter_zs = r[0] + sigmoid(t / (N-1)) * z_diff
azs.append(inter_zs)
# Generate image
with torch.no_grad():
if generator == 'biggan':
img = model(azs[0], azs[1], 1).cpu().numpy()
img = img[0]
elif generator == 'dall-e':
img = unmap_pixels(torch.sigmoid(model(azs[0])[:, :3]).cpu().float()).numpy()
img = img[0]
elif generator == 'stylegan':
img = model(azs[0])
image_temp = create_image(img, t, current_lyric, generator)
image_temp_list.append(image_temp)
video_temp = create_video.createvid(f'{current_lyric}', image_temp_list, duration=ttime / N)
video_temp_list.append(video_temp)
# Finally create the final output and save to output folder
create_video.concatvids(descs, video_temp_list, audiofile, lyrics=lyrics)
if __name__ == '__main__':
templist, descs, model = main()
interpolate(templist, descs, model, audiofile)
| yk/clip_music_video | 175 | Code for making music videos using CLIP | Python | yk | Yannic Kilcher | |
stylegan.py | Python | #!/usr/bin/env python3
# Taken from https://github.com/IVRL/GANLocalEditing
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from collections import OrderedDict
import os
import wget
class MyLinear(nn.Module):
"""Linear layer with equalized learning rate and custom learning rate multiplier."""
def __init__(self, input_size, output_size, gain=2**(0.5), use_wscale=False, lrmul=1, bias=True):
super().__init__()
he_std = gain * input_size**(-0.5) # He init
# Equalized learning rate and custom learning rate multiplier.
if use_wscale:
init_std = 1.0 / lrmul
self.w_mul = he_std * lrmul
else:
init_std = he_std / lrmul
self.w_mul = lrmul
self.weight = torch.nn.Parameter(torch.randn(output_size, input_size) * init_std)
if bias:
self.bias = torch.nn.Parameter(torch.zeros(output_size))
self.b_mul = lrmul
else:
self.bias = None
def forward(self, x):
bias = self.bias
if bias is not None:
bias = bias * self.b_mul
return F.linear(x, self.weight * self.w_mul, bias)
class MyConv2d(nn.Module):
"""Conv layer with equalized learning rate and custom learning rate multiplier."""
def __init__(self, input_channels, output_channels, kernel_size, gain=2**(0.5), use_wscale=False, lrmul=1, bias=True,
intermediate=None, upscale=False):
super().__init__()
if upscale:
self.upscale = Upscale2d()
else:
self.upscale = None
he_std = gain * (input_channels * kernel_size ** 2) ** (-0.5) # He init
self.kernel_size = kernel_size
if use_wscale:
init_std = 1.0 / lrmul
self.w_mul = he_std * lrmul
else:
init_std = he_std / lrmul
self.w_mul = lrmul
self.weight = torch.nn.Parameter(torch.randn(output_channels, input_channels, kernel_size, kernel_size) * init_std)
if bias:
self.bias = torch.nn.Parameter(torch.zeros(output_channels))
self.b_mul = lrmul
else:
self.bias = None
self.intermediate = intermediate
def forward(self, x):
bias = self.bias
if bias is not None:
bias = bias * self.b_mul
have_convolution = False
if self.upscale is not None and min(x.shape[2:]) * 2 >= 128:
# this is the fused upscale + conv from StyleGAN, sadly this seems incompatible with the non-fused way
# this really needs to be cleaned up and go into the conv...
w = self.weight * self.w_mul
w = w.permute(1, 0, 2, 3)
# probably applying a conv on w would be more efficient. also this quadruples the weight (average)?!
w = F.pad(w, (1,1,1,1))
w = w[:, :, 1:, 1:]+ w[:, :, :-1, 1:] + w[:, :, 1:, :-1] + w[:, :, :-1, :-1]
x = F.conv_transpose2d(x, w, stride=2, padding=(w.size(-1)-1)//2)
have_convolution = True
elif self.upscale is not None:
x = self.upscale(x)
if not have_convolution and self.intermediate is None:
return F.conv2d(x, self.weight * self.w_mul, bias, padding=self.kernel_size//2)
elif not have_convolution:
x = F.conv2d(x, self.weight * self.w_mul, None, padding=self.kernel_size//2)
if self.intermediate is not None:
x = self.intermediate(x)
if bias is not None:
x = x + bias.view(1, -1, 1, 1)
return x
class NoiseLayer(nn.Module):
"""adds noise. noise is per pixel (constant over channels) with per-channel weight"""
def __init__(self, channels):
super().__init__()
self.weight = nn.Parameter(torch.zeros(channels))
self.noise = None
def forward(self, x, noise=None):
if noise is None and self.noise is None:
noise = torch.randn(x.size(0), 1, x.size(2), x.size(3), device=x.device, dtype=x.dtype)
elif noise is None:
# here is a little trick: if you get all the noiselayers and set each
# modules .noise attribute, you can have pre-defined noise.
# Very useful for analysis
noise = self.noise
x = x + self.weight.view(1, -1, 1, 1) * noise
return x
class StyleMod(nn.Module):
def __init__(self, latent_size, channels, use_wscale):
super(StyleMod, self).__init__()
self.lin = MyLinear(latent_size,
channels * 2,
gain=1.0, use_wscale=use_wscale)
def forward(self, x, latent):
style = self.lin(latent) # style => [batch_size, n_channels*2]
shape = [-1, 2, x.size(1)] + (x.dim() - 2) * [1]
style = style.view(shape) # [batch_size, 2, n_channels, ...]
x = x * (style[:, 0] + 1.) + style[:, 1]
return x
class PixelNormLayer(nn.Module):
""" This layer ensures that the input vector have std = 1:
- std = 1/N * sqrt(x-mean(x))
- In this case x comes from a normal centred in 0 so mean(x) = 0
- Dividing the value of std(x) to x makes the normal of x become 1:
+ If the std == 1 it remains the same
+ If the std > 1 it decrease the values of x which in consequence reduce the std
+ If the std < 1 it increase the values of x which in consequence increase the std
"""
def __init__(self, epsilon=1e-8):
super().__init__()
self.epsilon = epsilon
def forward(self, x):
return x * torch.rsqrt(torch.mean(x**2, dim=1, keepdim=True) + self.epsilon)
class BlurLayer(nn.Module):
def __init__(self, kernel=[1, 2, 1], normalize=True, flip=False, stride=1):
super(BlurLayer, self).__init__()
kernel=[1, 2, 1]
kernel = torch.tensor(kernel, dtype=torch.float32)
kernel = kernel[:, None] * kernel[None, :]
kernel = kernel[None, None]
if normalize:
kernel = kernel / kernel.sum()
if flip:
kernel = kernel[:, :, ::-1, ::-1]
self.register_buffer('kernel', kernel)
self.stride = stride
def forward(self, x):
# expand kernel channels
kernel = self.kernel.expand(x.size(1), -1, -1, -1)
x = F.conv2d(
x,
kernel,
stride=self.stride,
padding=int((self.kernel.size(2)-1)/2),
groups=x.size(1)
)
return x
def upscale2d(x, factor=2, gain=1):
assert x.dim() == 4
if gain != 1:
x = x * gain
if factor != 1:
shape = x.shape
x = x.view(shape[0], shape[1], shape[2], 1, shape[3], 1).expand(-1, -1, -1, factor, -1, factor)
x = x.contiguous().view(shape[0], shape[1], factor * shape[2], factor * shape[3])
return x
class Upscale2d(nn.Module):
def __init__(self, factor=2, gain=1):
super().__init__()
assert isinstance(factor, int) and factor >= 1
self.gain = gain
self.factor = factor
def forward(self, x):
return upscale2d(x, factor=self.factor, gain=self.gain)
class G_mapping(nn.Sequential):
def __init__(self, nonlinearity='lrelu', use_wscale=True):
act, gain = {'relu': (torch.relu, np.sqrt(2)),
'lrelu': (nn.LeakyReLU(negative_slope=0.2), np.sqrt(2))}[nonlinearity]
layers = [
('pixel_norm', PixelNormLayer()),
('dense0', MyLinear(512, 512, gain=gain, lrmul=0.01, use_wscale=use_wscale)),
('dense0_act', act),
('dense1', MyLinear(512, 512, gain=gain, lrmul=0.01, use_wscale=use_wscale)),
('dense1_act', act),
('dense2', MyLinear(512, 512, gain=gain, lrmul=0.01, use_wscale=use_wscale)),
('dense2_act', act),
('dense3', MyLinear(512, 512, gain=gain, lrmul=0.01, use_wscale=use_wscale)),
('dense3_act', act),
('dense4', MyLinear(512, 512, gain=gain, lrmul=0.01, use_wscale=use_wscale)),
('dense4_act', act),
('dense5', MyLinear(512, 512, gain=gain, lrmul=0.01, use_wscale=use_wscale)),
('dense5_act', act),
('dense6', MyLinear(512, 512, gain=gain, lrmul=0.01, use_wscale=use_wscale)),
('dense6_act', act),
('dense7', MyLinear(512, 512, gain=gain, lrmul=0.01, use_wscale=use_wscale)),
('dense7_act', act)
]
super().__init__(OrderedDict(layers))
def forward(self, x):
x = super().forward(x)
# Broadcast
x = x.expand(-1, 18, -1)
return x
class Truncation(nn.Module):
def __init__(self, avg_latent, max_layer=8, threshold=0.7):
super().__init__()
self.max_layer = max_layer
self.threshold = threshold
self.register_buffer('avg_latent', avg_latent) # parameter of the module which is not trainable and is not passed to the optimizer when calling parameters() function
def forward(self, x):
assert x.dim() == 3
interp = torch.lerp(self.avg_latent, x, self.threshold)
do_trunc = (torch.arange(x.size(1)) < self.max_layer).view(1, -1, 1)
return torch.where(do_trunc, interp, x)
class LayerEpilogue(nn.Module):
"""Things to do at the end of each layer."""
def __init__(self, channels, dlatent_size, use_wscale, use_noise, use_pixel_norm, use_instance_norm, use_styles, activation_layer):
super().__init__()
layers = []
if use_noise:
layers.append(('noise', NoiseLayer(channels)))
layers.append(('activation', activation_layer))
if use_pixel_norm:
layers.append(('pixel_norm', PixelNormLayer()))
if use_instance_norm:
layers.append(('instance_norm', nn.InstanceNorm2d(channels)))
self.top_epi = nn.Sequential(OrderedDict(layers))
if use_styles:
self.style_mod = StyleMod(dlatent_size, channels, use_wscale=use_wscale)
else:
self.style_mod = None
def forward(self, x, dlatents_in_slice=None):
x = self.top_epi(x)
if self.style_mod is not None:
x = self.style_mod(x, dlatents_in_slice)
else:
assert dlatents_in_slice is None
return x
class InputBlock(nn.Module):
def __init__(self, nf, dlatent_size, const_input_layer, gain, use_wscale, use_noise, use_pixel_norm, use_instance_norm, use_styles, activation_layer):
super().__init__()
self.const_input_layer = const_input_layer
self.nf = nf
if self.const_input_layer:
# called 'const' in tf
self.const = nn.Parameter(torch.ones(1, nf, 4, 4))
self.bias = nn.Parameter(torch.ones(nf))
else:
self.dense = MyLinear(dlatent_size, nf*16, gain=gain/4, use_wscale=use_wscale) # tweak gain to match the official implementation of Progressing GAN
self.epi1 = LayerEpilogue(nf, dlatent_size, use_wscale, use_noise, use_pixel_norm, use_instance_norm, use_styles, activation_layer)
self.conv = MyConv2d(nf, nf, 3, gain=gain, use_wscale=use_wscale)
self.epi2 = LayerEpilogue(nf, dlatent_size, use_wscale, use_noise, use_pixel_norm, use_instance_norm, use_styles, activation_layer)
def forward(self, dlatents_in_range):
batch_size = dlatents_in_range.size(0)
if self.const_input_layer:
x = self.const.expand(batch_size, -1, -1, -1)
x = x + self.bias.view(1, -1, 1, 1)
else:
x = self.dense(dlatents_in_range[:, 0]).view(batch_size, self.nf, 4, 4)
x = self.epi1(x, dlatents_in_range[:, 0])
x = self.conv(x)
x = self.epi2(x, dlatents_in_range[:, 1])
return x
class GSynthesisBlock(nn.Module):
def __init__(self, in_channels, out_channels, blur_filter, dlatent_size, gain, use_wscale, use_noise, use_pixel_norm, use_instance_norm, use_styles, activation_layer):
# 2**res x 2**res # res = 3..resolution_log2
super().__init__()
if blur_filter:
blur = BlurLayer(blur_filter)
else:
blur = None
self.conv0_up = MyConv2d(in_channels, out_channels, kernel_size=3, gain=gain, use_wscale=use_wscale,
intermediate=blur, upscale=True)
self.epi1 = LayerEpilogue(out_channels, dlatent_size, use_wscale, use_noise, use_pixel_norm, use_instance_norm, use_styles, activation_layer)
self.conv1 = MyConv2d(out_channels, out_channels, kernel_size=3, gain=gain, use_wscale=use_wscale)
self.epi2 = LayerEpilogue(out_channels, dlatent_size, use_wscale, use_noise, use_pixel_norm, use_instance_norm, use_styles, activation_layer)
def forward(self, x, dlatents_in_range):
x = self.conv0_up(x)
x = self.epi1(x, dlatents_in_range[:, 0])
x = self.conv1(x)
x = self.epi2(x, dlatents_in_range[:, 1])
return x
class G_synthesis(nn.Module):
def __init__(self,
dlatent_size = 512, # Disentangled latent (W) dimensionality.
num_channels = 3, # Number of output color channels.
resolution = 1024, # Output resolution.
fmap_base = 8192, # Overall multiplier for the number of feature maps.
fmap_decay = 1.0, # log2 feature map reduction when doubling the resolution.
fmap_max = 512, # Maximum number of feature maps in any layer.
use_styles = True, # Enable style inputs?
const_input_layer = True, # First layer is a learned constant?
use_noise = True, # Enable noise inputs?
randomize_noise = True, # True = randomize noise inputs every time (non-deterministic), False = read noise inputs from variables.
nonlinearity = 'lrelu', # Activation function: 'relu', 'lrelu'
use_wscale = True, # Enable equalized learning rate?
use_pixel_norm = False, # Enable pixelwise feature vector normalization?
use_instance_norm = True, # Enable instance normalization?
dtype = torch.float32, # Data type to use for activations and outputs.
blur_filter = [1,2,1], # Low-pass filter to apply when resampling activations. None = no filtering.
):
super().__init__()
def nf(stage):
return min(int(fmap_base / (2.0 ** (stage * fmap_decay))), fmap_max)
self.dlatent_size = dlatent_size
resolution_log2 = int(np.log2(resolution))
assert resolution == 2**resolution_log2 and resolution >= 4
act, gain = {'relu': (torch.relu, np.sqrt(2)),
'lrelu': (nn.LeakyReLU(negative_slope=0.2), np.sqrt(2))}[nonlinearity]
num_layers = resolution_log2 * 2 - 2
num_styles = num_layers if use_styles else 1
torgbs = []
blocks = []
for res in range(2, resolution_log2 + 1):
channels = nf(res-1)
name = '{s}x{s}'.format(s=2**res)
if res == 2:
blocks.append((name,
InputBlock(channels, dlatent_size, const_input_layer, gain, use_wscale,
use_noise, use_pixel_norm, use_instance_norm, use_styles, act)))
else:
blocks.append((name,
GSynthesisBlock(last_channels, channels, blur_filter, dlatent_size, gain, use_wscale, use_noise, use_pixel_norm, use_instance_norm, use_styles, act)))
last_channels = channels
self.torgb = MyConv2d(channels, num_channels, 1, gain=1, use_wscale=use_wscale)
self.blocks = nn.ModuleDict(OrderedDict(blocks))
def forward(self, dlatents_in):
# Input: Disentangled latents (W) [minibatch, num_layers, dlatent_size].
# lod_in = tf.cast(tf.get_variable('lod', initializer=np.float32(0), trainable=False), dtype)
batch_size = dlatents_in.size(0)
for i, m in enumerate(self.blocks.values()):
if i == 0:
x = m(dlatents_in[:, 2*i:2*i+2])
else:
x = m(x, dlatents_in[:, 2*i:2*i+2])
rgb = self.torgb(x)
return rgb
avg_latent = torch.zeros(1, 18, 512)
g_all = nn.Sequential(OrderedDict([
('g_mapping', G_mapping()),
# ('truncation', Truncation(avg_latent)),
('g_synthesis', G_synthesis())
]))
cwd = os.getcwd()
if 'stylegan.pt' not in os.listdir(cwd):
url = "https://github.com/lernapparat/lernapparat/releases/download/v2019-02-01/karras2019stylegan-ffhq-1024x1024.for_g_all.pt"
wget.download(url, "stylegan.pt")
g_all.load_state_dict(torch.load('stylegan.pt'))
g_synthesis = g_all.g_synthesis
g_mapping = g_all.g_mapping
| yk/clip_music_video | 175 | Code for making music videos using CLIP | Python | yk | Yannic Kilcher | |
utils.py | Python | from dall_e import map_pixels, unmap_pixels
import numpy as np
import torchvision
import tempfile
import imageio
import random
import kornia
import shutil
import torch
import time
import os
import re
def create_outputfolder():
outputfolder = os.path.join(os.getcwd(), 'output')
if os.path.exists(outputfolder):
shutil.rmtree(outputfolder)
os.mkdir(outputfolder)
def create_strp(d, timeformat):
return time.mktime(time.strptime(d, timeformat))
def download_stylegan_pt():
cwd = os.getcwd()
print(cwd)
if 'stylegan.pt' not in os.listdir(cwd):
url = "https://github.com/lernapparat/lernapparat/releases/download/v2019-02-01/karras2019stylegan-ffhq-1024x1024.for_g_all.pt"
wget.download(url, "stylegan.pt")
def init_textfile(textfile):
timeformat = "%M:%S"
starttime = "00:00"
with open(textfile, 'r') as file:
descs = file.readlines()
descs1 = [re.findall(r'(\d\d:\d\d) (.*)', d.strip('\n').strip())[0] for d in descs]
if len(descs1[0]) == 0:
descs1 = [re.findall(r'(\d\d:\d\d.\d\d) (.*)', d.strip('\n').strip())[0] for d in descs]
timeformat = "%M:%S.%f"
starttime = "00:00.00"
descs1 = [(create_strp(d[0], timeformat), d[1])for d in descs1]
firstline = (create_strp(starttime, timeformat), "start song")
if descs1[0][0] - firstline[0]:
descs1.insert(0, firstline)
lastline = (descs1[-1][0]+9, "end song")
descs1.append(lastline)
return descs1
def create_image(img, i, text, gen, pre_scaled=True):
if gen == 'stylegan':
img = (img.clamp(-1, 1) + 1) / 2.0
img = img[0].permute(1, 2, 0).detach().cpu().numpy() * 256
else:
img = np.array(img)[:,:,:]
img = np.transpose(img, (1, 2, 0))
if not pre_scaled:
img = scale(img, 48*4, 32*4)
img = np.array(img)
with tempfile.NamedTemporaryFile() as image_temp:
imageio.imwrite(image_temp.name+".png", img)
image_temp.seek(0)
return image_temp
nom = torchvision.transforms.Normalize((0.48145466, 0.4578275, 0.40821073), (0.26862954, 0.26130258, 0.27577711))
class Pars(torch.nn.Module):
def __init__(self, gen='biggan'):
super(Pars, self).__init__()
self.gen = gen
if self.gen == 'biggan':
params1 = torch.zeros(32, 128).normal_(std=1).cuda()
self.normu = torch.nn.Parameter(params1)
params_other = torch.zeros(32, 1000).normal_(-3.9, .3)
self.cls = torch.nn.Parameter(params_other)
self.thrsh_lat = torch.tensor(1).cuda()
self.thrsh_cls = torch.tensor(1.9).cuda()
elif self.gen == 'dall-e':
self.normu = torch.nn.Parameter(torch.zeros(1, 8192, 64, 64).cuda())
elif self.gen == 'stylegan':
latent_shape = (1, 1, 512)
latents_init = torch.zeros(latent_shape).squeeze(-1).cuda()
self.normu = torch.nn.Parameter(latents_init, requires_grad=True)
def forward(self):
if self.gen == 'biggan':
return self.normu, torch.sigmoid(self.cls)
elif self.gen == 'dall-e':
# normu = torch.nn.functional.gumbel_softmax(self.normu.view(1, 8192, -1), dim=-1).view(1, 8192, 64, 64)
normu = torch.nn.functional.gumbel_softmax(self.normu.view(1, 8192, -1), dim=-1, tau = 2).view(1, 8192, 64, 64)
return normu
def pad_augs(image):
pad = random.randint(1,50)
pad_px = random.randint(10,90)/100
pad_py = random.randint(10,90)/100
pad_dims = (int(pad*pad_px), pad-int(pad*pad_px), int(pad*pad_py), pad-int(pad*pad_py))
return torch.nn.functional.pad(image, pad_dims, "constant", 1)
def kornia_augs(image, sideX=512):
blur = (random.randint(0,int(sideX/5))*2)+1
kornia_model = torch.nn.Sequential(
kornia.augmentation.RandomAffine(20, p=0.55, keepdim=True),
kornia.augmentation.RandomHorizontalFlip(),
kornia.augmentation.GaussianBlur((blur,blur),(blur,blur), p=0.5, border_type="constant"),
kornia.augmentation.RandomSharpness(.5),
kornia.augmentation.ColorJitter(0.1, 0.1, 0.1, 0.1, p=0.6)
)
return kornia_model(image)
def ascend_txt(model, lats, sideX, sideY, perceptor, percep, gen, tokenizedtxt):
if gen == 'biggan':
cutn = 128
zs = [*lats()]
out = model(zs[0], zs[1], 1)
elif gen == 'dall-e':
cutn = 32
zs = lats()
out = unmap_pixels(torch.sigmoid(model(zs)[:, :3].float()))
elif gen == 'stylegan':
zs = lats.normu.repeat(1,18,1)
img = model(zs)
img = torch.nn.functional.upsample_bilinear(img, (224, 224))
img_logits, _text_logits = perceptor(img, tokenizedtxt.cuda())
return 1/img_logits * 100, img, zs
p_s = []
for ch in range(cutn):
# size = int(sideX*torch.zeros(1,).normal_(mean=.8, std=.3).clip(.5, .95))
size = int(sideX*torch.zeros(1,).normal_(mean=.39, std=.865).clip(.362, .7099))
offsetx = torch.randint(0, sideX - size, ())
offsety = torch.randint(0, sideY - size, ())
apper = out[:, :, offsetx:offsetx + size, offsety:offsety + size]
apper = pad_augs(apper)
# apper = kornia_augs(apper, sideX=sideX)
apper = torch.nn.functional.interpolate(apper, (224, 224), mode='nearest')
p_s.append(apper)
into = torch.cat(p_s, 0)
if gen == 'biggan':
# into = nom((into + 1) / 2)
up_noise = 0.01649
into = into + (up_noise)*torch.randn_like(into, requires_grad=True)
into = nom((into + 1) / 1.8)
elif gen == 'dall-e':
into = nom((into + 1) / 2)
iii = perceptor.encode_image(into)
llls = zs #lats()
if gen == 'dall-e':
return [0, 10*-torch.cosine_similarity(percep, iii).view(-1, 1).T.mean(1), zs]
lat_l = torch.abs(1 - torch.std(llls[0], dim=1)).mean() + \
torch.abs(torch.mean(llls[0])).mean() + \
4*torch.max(torch.square(llls[0]).mean(), lats.thrsh_lat)
for array in llls[0]:
mean = torch.mean(array)
diffs = array - mean
var = torch.mean(torch.pow(diffs, 2.0))
std = torch.pow(var, 0.5)
zscores = diffs / std
skews = torch.mean(torch.pow(zscores, 3.0))
kurtoses = torch.mean(torch.pow(zscores, 4.0)) - 3.0
lat_l = lat_l + torch.abs(kurtoses) / llls[0].shape[0] + torch.abs(skews) / llls[0].shape[0]
cls_l = ((50*torch.topk(llls[1],largest=False,dim=1,k=999)[0])**2).mean()
return [lat_l, cls_l, -100*torch.cosine_similarity(percep, iii, dim=-1).mean(), zs]
def train(i, model, lats, sideX, sideY, perceptor, percep, optimizer, text, tokenizedtxt, epochs=200, gen='biggan', img=None):
loss1 = ascend_txt(model, lats, sideX, sideY, perceptor, percep, gen, tokenizedtxt)
if gen == 'biggan':
loss = loss1[0] + loss1[1] + loss1[2]
zs = loss1[3]
elif gen == 'dall-e':
loss = loss1[0] + loss1[1]
loss = loss.mean()
zs = loss1[2]
elif gen == 'stylegan':
loss = loss1[0]
img = loss1[1].cpu()
zs = loss1[2]
optimizer.zero_grad()
loss.backward()
optimizer.step()
if i+1 == epochs:
# if it's the last step, return the final z
return zs
return False
| yk/clip_music_video | 175 | Code for making music videos using CLIP | Python | yk | Yannic Kilcher | |
src/compute_metrics.py | Python | #!/usr/bin/env python3
import json
from pathlib import Path
from loguru import logger
from tabulate import tabulate
import lm_eval.tasks
m1 = 'GPT-J-6B'
m2 = 'GPT-4chan'
log_dir = Path('./eval_logs')
all_tasks = set()
model_data = {}
for fn in log_dir.rglob('log_*.stdout.txt'):
try:
file_text = fn.read_text()
data = json.loads('{' + file_text.split('{', 1)[1].rsplit('}', 1)[0] + '}')
model = data['config']['model_args'].split('=')[1]
model = m2 if 'fp16' in model else m1
if model not in model_data:
model_data[model] = {}
results = data['results']
tasks = list(results.keys())
assert len(tasks) == 1, 'Only one task supported'
task = tasks[0]
if task in model_data[model]:
raise ValueError(f'Duplicate task {task}')
task_version = data['versions'][task]
results = results[task]
results_data = {}
for result_key in results:
if result_key.endswith('_stderr'):
continue
result_value = results[result_key]
results_data[result_key] = {'value': result_value}
stderr_key = f'{result_key}_stderr'
if stderr_key in results:
results_data[result_key]['stderr'] = results[stderr_key]
else:
logger.warning(f'No stderr for {result_key} in {results}')
model_data[model][task] = {'version': task_version, 'results': results_data}
all_tasks.add(task)
except Exception:
logger.exception(f'Failed to parse {fn}')
continue
all_models = list(sorted(model_data.keys()))
table_data = []
for task in all_tasks:
try:
higher_is_better = lm_eval.tasks.get_task(task).higher_is_better(None)
except Exception:
logger.warning(f'Failed to get higher_is_better for {task}')
continue
if any(task not in model_data[model] for model in all_models):
logger.warning(f'No results for {task}')
continue
results = model_data[m1][task]['results']
results2 = model_data[m2][task]['results']
for metric in results:
result_value = results[metric]['value']
stderr_value = results[metric].get('stderr', 0.0)
result2_value = results2[metric]['value']
stderr2_value = results2[metric].get('stderr', 0.0)
significance = (result_value - result2_value) / ((stderr_value + stderr2_value + 1e-8) / 2)
if higher_is_better[metric]:
significance *= -1
if abs(significance) > 1:
significant = '+' if significance > 0 else '-'
else:
significant = ''
table_data.append([task, metric, result_value, stderr_value, result2_value, stderr2_value, significant])
table_str = tabulate(table_data, headers=['Task', 'Metric', m1, 'stderr', m2, 'stderr', 'Significant'], tablefmt='pipe')
print(table_str)
Path('./results.table.txt').write_text(table_str)
| yk/gpt-4chan-public | 635 | Code for GPT-4chan | Python | yk | Yannic Kilcher | |
src/process_data.py | Python | #!/usr/bin/env python3
import json
import bs4
from loguru import logger
import multiprocessing as mp
import tqdm
from absl import app, flags
import warnings
warnings.filterwarnings("ignore", category=bs4.MarkupResemblesLocatorWarning, module='bs4')
DATA_FN = '../tmp/pol_062016-112019_labeled.ndjson'
OUT_FN = '../tmp/kek.txt'
flags.DEFINE_string('data_fn', DATA_FN, 'data file')
flags.DEFINE_string('out_fn', OUT_FN, 'output file')
FLAGS = flags.FLAGS
# from here: https://gist.github.com/zmwangx/ad0830ba94b1fd98f428
def text_with_newlines(elem):
text = ''
for e in elem.descendants:
if isinstance(e, str):
# text += e.strip()
text += e
elif e.name == 'br' or e.name == 'p':
text += '\n'
return text
def parse_line(line):
data = json.loads(line)
posts_text = []
for post in data.get('posts', []):
try:
if 'com' in post:
soup = bs4.BeautifulSoup(post['com'], 'lxml')
post_text = text_with_newlines(soup).strip()
else:
post_text = ''
post_text = f'--- {post["no"]}\n{post_text}'
posts_text.append(post_text)
except Exception:
logger.exception(f'failed to parse post {post}')
return '\n'.join(posts_text)
def main(_):
with open(FLAGS.out_fn, 'w') as out_f:
with open(FLAGS.data_fn) as in_f:
with mp.Pool() as pool:
for parsed_line in pool.imap(parse_line, tqdm.tqdm(in_f)):
out_f.write(parsed_line + '\n-----\n')
if __name__ == '__main__':
app.run(main)
| yk/gpt-4chan-public | 635 | Code for GPT-4chan | Python | yk | Yannic Kilcher | |
src/server/model/__init__.py | Python | from .inference import Inference
from .constants import ModelParams, InferConfig
| yk/gpt-4chan-public | 635 | Code for GPT-4chan | Python | yk | Yannic Kilcher | |
src/server/model/constants.py | Python | import typing
from dataclasses import dataclass
import optax
BAD_WORDS = [] # Can't be part of config to avoid printing it
@dataclass
class InferConfig:
name: str = "Holotard"
prompt_length: int = 65536
token_length: int = 16
response_probability: float = 0.02
top_p: float = 1.0
min_temperature: float = 0.6
max_temperature: float = 1.2
max_same_replies: int = 2
same_reply_saved_messages: int = 6
max_response_retries: int = 3
@dataclass
class ModelParams:
layers: int = 28
d_model: int = 4096
n_heads: int = 16
n_vocab: int = 50400
norm: str = "layernorm"
pe: str = "rotary"
pe_rotary_dims: int = 64
seq: int = 2048
cores_per_replica: int = 8
per_replica_batch: int = 1
# batch size of 2 needs 200gb, 1 needs <16. wtf
optimizer: optax.chain = optax.chain(optax.adaptive_grad_clip(0.001), optax.centralize(),
optax.scale_by_adam(0.99, 0.999), optax.additive_weight_decay(1e-3),
optax.scale(-1e-5), )
sampler = None
| yk/gpt-4chan-public | 635 | Code for GPT-4chan | Python | yk | Yannic Kilcher | |
src/server/model/inference.py | Python | import random
from typing import Any, Optional
from loguru import logger
import time
import jax
import numpy as np
import transformers
from jax import numpy as jnp
from jax.experimental import maps
from mesh_transformer.checkpoint import read_ckpt_lowmem
from mesh_transformer.sampling import nucleaus_sample
from mesh_transformer.transformer_shard import CausalTransformer
from .constants import ModelParams, InferConfig
def default(value: Any, fallback: Any) -> Any:
# luke prefers making a function that chooses between `value` and `feedback` so i am gonna keep it
if value is None:
return fallback
return value
_cores_per_replica = ModelParams.cores_per_replica
_mesh_shape = (jax.device_count() // _cores_per_replica, _cores_per_replica)
_devices = np.array(jax.devices()).reshape(_mesh_shape)
#maps.thread_resources.env = maps.ResourceEnv(maps.Mesh(_devices, ("dp", "mp")), ())
maps.thread_resources.env = maps.ResourceEnv(maps.Mesh(_devices, ("dp", "mp")))
class Inference:
_NP_ONE = np.ones((1,))
def __init__(
self,
path: Optional[str] = None,
parameters: Optional[ModelParams] = None,
config: Optional[InferConfig] = None,
):
path = "checkpoint_slim/" if path is None else path
self.params = ModelParams() if parameters is None else parameters
self.params.sampler = nucleaus_sample
self.config = InferConfig() if config is None else config
self.model = CausalTransformer(self.params.__dict__)
self.tokenizer = transformers.GPT2TokenizerFast.from_pretrained("gpt2")
self.model.state = read_ckpt_lowmem(
self.model.state, path, self.params.cores_per_replica, load_opt=False
)
def generate_tokens(
self,
prompt: np.ndarray,
length: Optional[int] = None,
top_p: Optional[float] = None,
temperature: Optional[float] = None,
) -> np.ndarray:
length = default(length, self.config.token_length)
top_p = default(top_p, self.config.top_p)
new_temp = random.random() * (self.config.max_temperature - self.config.min_temperature)
new_temp += self.config.min_temperature
temperature = default(temperature, new_temp)
#prompt = prompt[:, -2048:]
#prompt = prompt[:, -length:]
start_time = time.time()
source = jnp.array(
np.pad(
prompt,
(
(0, 0),
(self.params.seq - prompt.shape[1], 0),
),
)
)
logger.info(f"creating source took {time.time() - start_time}")
sampler_options = {
"top_p": self._NP_ONE * top_p,
"temp": self._NP_ONE * temperature,
}
start_time = time.time()
#with jax.experimental.maps.mesh(_devices, ("dp", "mp")):
logger.info(f"creating mesh took {time.time() - start_time}")
start_time = time.time()
out = self.model.generate(
source, self._NP_ONE * prompt.shape[1], length, sampler_options
)
logger.info(f"generate took {time.time() - start_time}")
#import IPython; IPython.embed()
return out[1][0][0, :, 0]
def generate(
self,
prompt: str,
length: Optional[int] = None,
top_p: Optional[float] = None,
temperature: Optional[float] = None,
) -> str:
inp_tokens = self.tokenizer([prompt], verbose=False, return_tensors="np")
inp_tokens = inp_tokens["input_ids"][0]
out_tokens = self.generate_tokens(
inp_tokens.reshape(1, -1), length, top_p, temperature
)
return self.tokenizer.decode(out_tokens)
| yk/gpt-4chan-public | 635 | Code for GPT-4chan | Python | yk | Yannic Kilcher | |
src/server/model/to_slim_weights.py | Python | import argparse
import json
import time
import jax
import numpy as np
import optax
from mesh_transformer import util
from mesh_transformer.checkpoint import read_ckpt, write_ckpt, read_ckpt_lowmem
from mesh_transformer.transformer_shard import CausalTransformer
from smart_open import open
from mesh_transformer.util import clip_by_global_norm, to_bf16, to_f16
from model.constants import ModelParams
if __name__ == "__main__":
params = ModelParams().__dict__
convert_fn = to_bf16
cores_per_replica = params["cores_per_replica"]
assert cores_per_replica <= 8
start = time.time()
print(f"jax devices: {jax.device_count()}")
print(f"jax runtime initialized in {time.time() - start:.06}s")
mesh_shape = (jax.device_count() // cores_per_replica, cores_per_replica)
devices = np.array(jax.devices()).reshape(mesh_shape)
with jax.experimental.maps.mesh(devices, ("dp", "mp")):
network = CausalTransformer(params)
start = time.time()
network.state = read_ckpt(
network.state, f"checkpoint/", devices.shape[1], load_opt=False
)
print(f"network loaded in {time.time() - start:.06}s")
start = time.time()
del network.state["opt_state"]
network.state["params"] = convert_fn(network.state["params"])
print(f"network converted in {time.time() - start:.06}s")
suffix = "_slim"
for i in range(cores_per_replica):
write_ckpt(network.state, f"checkpoint_slim/", i)
print(f"written shard {i}")
| yk/gpt-4chan-public | 635 | Code for GPT-4chan | Python | yk | Yannic Kilcher | |
src/server/serve_api.py | Python | #!/usr/bin/env python3
from typing import Optional
import threading
import queue
import time
from loguru import logger
from pathlib import Path
import contextlib
import pydantic
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
app = FastAPI()
origins = ["*"]
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
class Settings(pydantic.BaseSettings):
queue_size: int = 1024
log_file: str = "logs/serve_api.log"
api_keys_file: str = 'valid_api_keys.txt'
hf_model: str = ''
hf_cuda: bool = False
pre_prompt_length: int = 512
settings = Settings()
def _check_api_key(key):
key = key.strip()
for line in Path(settings.api_keys_file).open():
if not line:
continue
valid_key = line.split()[0]
if key == valid_key:
break
else:
return False
return True
request_queue = queue.Queue(maxsize=settings.queue_size)
@contextlib.contextmanager
def jax_generation():
from model import inference
import jax
model = inference.Inference(path="../model_slim/step_88001/")
def _generate(request):
response = model.generate(
prompt=request.prompt,
length=request.length,
top_p=request.top_p,
temperature=request.temperature,
)
return response
with jax.experimental.maps.mesh(inference._devices, ("dp", "mp")):
yield _generate
@contextlib.contextmanager
def hf_generation():
from transformers import GPTJForCausalLM, AutoTokenizer
import torch
if settings.hf_cuda:
model = GPTJForCausalLM.from_pretrained(
settings.hf_model, revision="float16", torch_dtype=torch.float16, low_cpu_mem_usage=True
)
model.cuda()
else:
model = GPTJForCausalLM.from_pretrained( settings.hf_model, torch_dtype=torch.float32)
model.eval()
tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6B")
def _generate(request: CompleteRequest):
input_ids = tokenizer(request.prompt, return_tensors="pt").input_ids
max_prompt_length = 2048 - request.length
input_ids = input_ids[:, -max_prompt_length:]
if request.pre_prompt:
pp_input_ids = tokenizer(request.pre_prompt, return_tensors="pt").input_ids
pp_input_ids = pp_input_ids[:, :settings.pre_prompt_length]
input_ids = input_ids[:, -(max_prompt_length-len(pp_input_ids)):]
full_prompt = tokenizer.batch_decode(pp_input_ids)[0] + tokenizer.batch_decode(input_ids)[0]
input_ids = tokenizer(full_prompt, return_tensors="pt").input_ids
input_ids = input_ids[:, -max_prompt_length:]
if settings.hf_cuda:
input_ids = input_ids.cuda()
with torch.no_grad():
gen_tokens = model.generate(
input_ids,
do_sample=True,
temperature=request.temperature,
top_p=request.top_p,
typical_p=request.typical_p,
max_new_tokens=request.length,
).detach().cpu()
gen_text = tokenizer.batch_decode(gen_tokens)[0]
prompt_decoded = tokenizer.batch_decode(input_ids.detach().cpu())[0]
if not gen_text.startswith(prompt_decoded):
raise Exception(f"Generated text does not start with prompt: {gen_text}\n(prompt was {prompt_decoded})")
gen_text = gen_text[len(prompt_decoded):]
return gen_text
yield _generate
def worker():
if settings.hf_model:
generation = hf_generation
else:
generation = jax_generation
with generation() as generate_fn:
with open(settings.log_file, "a") as logf:
while True:
response_queue = None
try:
start_time = time.time()
(request, response_queue) = request_queue.get()
logger.info(f"getting request took {time.time() - start_time}")
start_time = time.time()
response = generate_fn(request)
logger.info(f"generate took {time.time() - start_time}, response length: {len(response)}")
start_time = time.time()
logf.write(f"##### {request.api_key} ##### {time.time()} #####\n")
logf.write(f"{request.pre_prompt}\n")
logf.write("###\n")
logf.write(f"{request.prompt}\n")
logf.write("#####\n")
logf.write(f"{response}\n\n")
logf.flush()
logger.info(f"writing log took {time.time() - start_time}")
start_time = time.time()
response_queue.put(response)
logger.info(f"putting response took {time.time() - start_time}")
except KeyboardInterrupt:
logger.info(f"Got KeyboardInterrupt... quitting!")
raise
except Exception:
logger.exception(f"Got exception, will continue")
if response_queue is not None:
response_queue.put("")
@app.get("/")
async def main():
return {"response": "Hello, world!"}
class CompleteRequest(pydantic.BaseModel):
prompt: pydantic.constr(min_length=0, max_length=2**14)
pre_prompt: pydantic.constr(min_length=0, max_length=2**14) = ''
api_key: pydantic.constr(min_length=1, max_length=128) = "x"*9
length: pydantic.conint(ge=1, le=1024) = 128
top_p: pydantic.confloat(ge=0.0, le=1.0) = 1.0
temperature: pydantic.confloat(ge=0.0) = 1.0
typical_p: pydantic.confloat(ge=0.0, le=1.0) = 1.0
def _enqueue(request: CompleteRequest):
response_queue = queue.Queue()
request_queue.put((request, response_queue))
response = response_queue.get()
return response
@app.on_event("startup")
def startup():
threading.Thread(
target=worker,
daemon=True,
).start()
_enqueue(CompleteRequest(prompt="hello"))
@app.post("/complete")
def complete(request: CompleteRequest):
logger.info(f"Received request from key {request.api_key}. Queue size is {request_queue.qsize()}")
if request_queue.full():
logger.warning("Request queue full.")
raise ValueError("Request queue full.")
if not _check_api_key(request.api_key):
logger.warning(f"api key not valid: {request.api_key}, discarding...")
raise ValueError("Invalid API key")
response = _enqueue(request)
return {"response": response}
| yk/gpt-4chan-public | 635 | Code for GPT-4chan | Python | yk | Yannic Kilcher | |
src/txt_to_tfrecords.py | Python | #!/usr/bin/env python3
from absl import flags, app
from loguru import logger
from pathlib import Path
import shutil
import functools
import tokenizers
import tensorflow as tf
import tqdm
flags.DEFINE_string('txt_fn', '../tmp/kek.txt', 'input txt')
flags.DEFINE_string('out_dir', '../tmp/tfrecords/', 'output directory (will be cleared)')
flags.DEFINE_integer('chunk_size', 2**24, 'how many tokens go into one tfrecords file')
flags.DEFINE_integer('read_buffer_size', 2**10, 'input file read buffer size')
FLAGS = flags.FLAGS
@functools.lru_cache(maxsize=1)
def get_tokenizer():
return tokenizers.Tokenizer.from_pretrained('gpt2')
def make_record_file(record_ids, out_dir, file_no):
out_fn = str(out_dir / f'tokens-{file_no:05d}.tfrecord')
with tf.io.TFRecordWriter(out_fn) as writer:
feature = {'text': tf.train.Feature(int64_list=tf.train.Int64List(value=record_ids))}
tf_example = tf.train.Example(features=tf.train.Features(feature=feature))
writer.write(tf_example.SerializeToString())
def read_in_blocks(f):
while True:
block = f.read(FLAGS.read_buffer_size)
if not block:
break
yield block
def main(_):
out_dir = Path(FLAGS.out_dir)
if out_dir.exists():
logger.warning(f'clearing {out_dir}')
shutil.rmtree(out_dir)
out_dir.mkdir(exist_ok=True)
tokenizer = get_tokenizer()
with open(FLAGS.txt_fn) as in_f:
current_ids = []
out_file_no = 0
for block in tqdm.tqdm(read_in_blocks(in_f)):
current_ids.extend(tokenizer.encode(block).ids)
while len(current_ids) >= FLAGS.chunk_size:
record_ids, current_ids = current_ids[:FLAGS.chunk_size], current_ids[FLAGS.chunk_size:]
make_record_file(record_ids, out_dir, out_file_no)
out_file_no += 1
if current_ids:
make_record_file(current_ids, out_dir, out_file_no)
if __name__ == "__main__":
app.run(main)
| yk/gpt-4chan-public | 635 | Code for GPT-4chan | Python | yk | Yannic Kilcher | |
app/admin/page.js | JavaScript | "use client";
import React from "react";
import Link from "next/link";
import { useQueryClient } from "@tanstack/react-query";
export default function Admin() {
const queryClient = useQueryClient();
const [adminPassword, setAdminPassword] = React.useState("");
const deleteAllPosts = React.useCallback(async () => {
const res = await fetch("/api/posts", {
method: "DELETE",
headers: {
"Content-Type": "application/json",
"X-Admin-Password": adminPassword || "",
},
});
const json = await res.json();
await queryClient.invalidateQueries(["posts"]);
return json;
}, [adminPassword, queryClient]);
return (
<main className="mx-8 my-8 flex flex-col gap-4">
<div>
<Link href="/" className="bg-blue-600 text-white px-4 py-2 rounded">
Home
</Link>
</div>
<div>
<input
type="password"
value={adminPassword}
onChange={(e) => setAdminPassword(e.target.value)}
placeholder="Admin Password"
className="border border-gray-400 rounded px-4 py-2 text-black"
/>
</div>
<div>
<button
onClick={deleteAllPosts}
className="bg-red-600 text-white px-4 py-2 rounded"
>
Delete All Posts
</button>
</div>
</main>
);
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/api/auth/[...nextauth]/route.js | JavaScript | import NextAuth from "next-auth"
import GithubProvider from "next-auth/providers/github"
const authOptions = {
providers: [
GithubProvider({
clientId: process.env.GITHUB_ID,
clientSecret: process.env.GITHUB_SECRET,
}),
],
secret: process.env.NEXTAUTH_SECRET,
};
const handler = NextAuth(authOptions);
export { handler as GET, handler as POST } | yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/api/posts/[id]/likes/route.js | JavaScript | import { NextResponse } from "next/server";
import { getServerSession } from "next-auth/next";
import { getRedisClient } from "../../../../utils";
export const dynamic = "force-dynamic";
export async function GET(req, { params: { id } }) {
const client = await getRedisClient();
const session = await getServerSession(req);
const username = session?.user?.name;
const self_liked = username && await client.sIsMember(`likes:${id}`, username);
const num_likes = await client.sCard(`likes:${id}`);
return NextResponse.json({ self_liked, num_likes }, { status: 200 });
}
export async function POST(req, {params: { id } }) {
const session = await getServerSession(req);
const username = session?.user?.name;
if (!username) {
return NextResponse.json({ error: "not authenticated" }, { status: 401 });
}
const client = await getRedisClient();
try {
const self_liked = await client.sIsMember(`likes:${id}`, username);
if (self_liked) {
await client.sRem(`likes:${id}`, username);
} else {
await client.sAdd(`likes:${id}`, username);
}
return NextResponse.json({ id }, { status: 200 });
} catch (e) {
return NextResponse.json({ error: e.message }, { status: 400 });
}
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/api/posts/[id]/route.js | JavaScript | import { NextResponse } from "next/server";
import { getRedisClient } from "../../../utils";
export const dynamic = "force-dynamic";
export async function GET(req, { params: { id } }) {
const client = await getRedisClient();
const post = await client.hGetAll(`post:${id}`);
return NextResponse.json({...post}, { status: 200 });
} | yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/api/posts/actions.js | JavaScript | "use server";
import { getRedisClient, getS3Client } from "../../utils";
import { nanoid } from "nanoid";
import moment from "moment";
import { dataUriToBuffer } from "data-uri-to-buffer";
import { Image } from "image-js";
import { PutObjectCommand } from "@aws-sdk/client-s3";
export const getPosts = async ({ offset = 0, limit = 0 }) => {
if(!limit) {
limit = parseInt(process.env.POSTS_PER_PAGE || "20");
}
const client = await getRedisClient();
const postIds = await client.zRange("posts", offset, limit);
const posts = await Promise.all(
postIds.map(async (postId) => {
const post = await client.hGetAll(postId);
return post;
})
);
return posts;
};
export const getCooldown = async ({ username }) => {
const client = await getRedisClient();
const cooldown = await client.get(`cooldown:${username}`);
return !!cooldown;
};
const putImage = async (encoded_img) => {
const parsedUri = dataUriToBuffer(encoded_img);
const [dataType, _] = parsedUri.type.split("/");
if (dataType !== "image") throw new Error("Not an image");
let image = await Image.load(parsedUri.buffer);
if (image.width > 1024) {
image = image.resize({ width: 1024 });
}
if (image.height > 1024) {
image = image.resize({ height: 1024 });
}
if (image.width > 1024) {
image = image.resize({ width: 1024 });
}
const buffer = image.toBuffer({ format: "jpeg" });
const fileName = moment().format("YYYY_MM_DD_hh_mm_ss_a");
const key = `uploads/${fileName}.jpeg`;
const s3Client = await getS3Client();
await s3Client.send(new PutObjectCommand({
Bucket: process.env.AWS_BUCKET_NAME,
Key: key,
Body: buffer,
ContentType: "image/jpeg",
}));
const url = `https://${process.env.AWS_BUCKET_NAME}.s3.amazonaws.com/${key}`;
return url;
};
export const createPost = async ({ text, encoded_img, username }) => {
const client = await getRedisClient();
const cooldown = await client.get(`cooldown:${username}`);
if (cooldown) throw new Error("Cooldown in effect");
text = text || "";
encoded_img = encoded_img || "";
if (!(text || encoded_img)) throw new Error("Text or image required");
let img_url = "";
if (encoded_img) {
img_url = await putImage(encoded_img);
}
const id = nanoid();
const key = `post:${id}`;
const createdAt = Date.now();
const newPost = { id, text, img_url, createdAt, username };
await client.hSet(key, [...Object.entries(newPost).flat()]);
await client.rPush("pending", key);
await client.set(`cooldown:${username}`, "true", { EX: 30 });
return { id };
};
export const deleteAllPosts = async () => {
const client = await getRedisClient();
await client.del("pending");
await client.del("posts");
const keys = await client.keys("post:*");
keys.forEach(async (key) => {
await client.del(key);
});
(await client.keys("cooldown:*")).forEach(async (key) => {
await client.del(key);
});
};
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/api/posts/route.js | JavaScript | import { NextResponse } from "next/server";
import { getPosts, createPost, deleteAllPosts, getCooldown } from "./actions";
import { getServerSession } from "next-auth/next";
import { headers } from 'next/headers'
export const dynamic = "force-dynamic";
export async function GET(req) {
const searchParams = new URL(req.url).searchParams;
const { cursor = 0 } = searchParams;
const posts = await getPosts({ cursor });
let cooldown = false;
const session = await getServerSession(req);
const username = session?.user?.name;
if(username) {
cooldown = await getCooldown({ username });
}
return NextResponse.json({ posts, cooldown }, { status: 200 });
}
export async function POST(req) {
const session = await getServerSession(req);
const username = session?.user?.name;
if (!username) {
return NextResponse.json({ error: "not authenticated" }, { status: 401 });
}
const { text, encoded_img } = await req.json();
try {
const { id } = await createPost({ text, encoded_img, username });
console.log("created post", { id });
return NextResponse.json({ id }, { status: 200 });
} catch (e) {
console.log("error creating post", { e });
return NextResponse.json({ error: e.message }, { status: 400 });
}
}
// delete all posts
export async function DELETE(){
const reqHeaders = headers();
const adminPassword = reqHeaders.get("X-Admin-Password");
console.log({adminPassword})
if(!process.env.ADMIN_PASSWORD || adminPassword !== process.env.ADMIN_PASSWORD){
return NextResponse.json({ error: "not authenticated" }, { status: 401 });
}
await deleteAllPosts();
return NextResponse.json({}, { status: 200 });
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/bye/page.js | JavaScript | "use client";
import React from "react";
import { TrashIcon } from "@heroicons/react/24/solid";
import clsx from "clsx";
import Link from "next/link";
import { PostBox, PostDisplay } from "../components/post-displays";
import { VariableSizeList as List } from "react-window";
import AutoSizer from "react-virtualized-auto-sizer";
import posts from "../../worker/data.jsonl";
const allPosts = Object.values(posts);
const postHeights = allPosts.map((post) => {
let height = 128;
if (post.text) {
height += 64 + 32;
}
if (post.img_url) {
height += 512;
}
return height;
});
const ListRow = ({ index, style }) => {
const post = allPosts[index];
return (
<div style={style}>
<PostBox className={"h-full"}>
<PostDisplay
{...post}
username="anonymous"
createdAt={new Date(parseFloat(post.createdAt)).toLocaleString()}
/>
</PostBox>
</div>
);
};
export default function Bye() {
return (
<div className="flex flex-col relative h-screen w-screen">
<header
className={clsx(
"fixed top-0 w-screen h-[100px] bg-black border-b border-gray-500",
"py-8 flex flex-row justify-center items-center gap-4"
)}
>
<TrashIcon className="w-8 h-8" />
<h1 className="text-4xl">Litter</h1>
<Link
href="https://youtu.be/v8O_tSF_o50"
className="absolute right-0 mr-8"
>
Litter is over. Click here for background.
</Link>
</header>
<main className="mt-[100px] h-full">
{allPosts && (
<AutoSizer>
{({ height, width }) => (
<List
height={height}
itemCount={allPosts.length}
itemSize={(index) => postHeights[index]}
width={width}
>
{ListRow}
</List>
)}
</AutoSizer>
)}
</main>
</div>
);
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/components/create-post-form.js | JavaScript | "use client";
import React from "react";
import clsx from "clsx";
import { useSession } from "next-auth/react";
import Link from "next/link";
import Image from "next/image";
// form for post creation with text and image
export default function CreatePostForm({ onSubmit, className, cooldown }) {
const [text, setText] = React.useState("");
const [image, setImage] = React.useState(null);
const createPost = async (e) => {
e.preventDefault();
//read image as data url
const encoded_img = image
? await new Promise((resolve) => {
const reader = new FileReader();
reader.onload = (e) => {
const result = e.target.result;
resolve(result);
};
reader.readAsDataURL(image);
})
: null;
await onSubmit({ text, encoded_img });
setText("");
setImage(null);
};
const { status } = useSession();
if (status === "loading") return null;
if (status !== "authenticated") {
return (
<div className="h-full flex flex-row w-screen justify-between bg-black">
<div className="flex flex-col w-full justify-center items-center">
<Link
href="/login"
className="text-xl px-8 py-4 border border-1 border-gray-500 rounded-md"
>
Login to create a post
</Link>
</div>
</div>
);
}
if (cooldown) {
return (
<div className="h-full flex flex-row w-screen justify-between bg-black">
<div className="flex flex-col w-full justify-center items-center">
<span className="text-xl px-8 py-4 border-gray-500 rounded-md">
Please wait 30 seconds before creating another post
</span>
</div>
</div>
);
}
return (
<form
onSubmit={createPost}
className="h-full flex flex-row w-screen justify-between bg-black"
>
<textarea
type="text"
name="text"
placeholder="Type your message here..."
className="resize-none block flex-grow bg-black px-4 py-4 text-lg"
autoFocus
value={text}
onChange={(e) => setText(e.target.value)}
onKeyUp={(e) => {
// submit on shift-enter
if (e.key === "Enter" && e.shiftKey) {
createPost(e);
}
}}
/>
<div className="w-32 border-0 border-l border-gray-700">
{image ? (
<div className="w-full h-full relative">
<Image
src={URL.createObjectURL(image)}
width={256}
height={256}
alt="image to upload"
/>
<button
type="button"
onClick={() => setImage(null)}
className={clsx(
"block absolute bottom-0 bg-black text-white w-full px-1 py-1",
"hover:bg-gray-900 hover:cursor-pointer"
)}
>
Remove
</button>
</div>
) : (
<>
<label
htmlFor="image"
className={clsx(
"flex flex-col h-full w-full justify-center items-center",
"hover:bg-gray-900 hover:cursor-pointer"
)}
>
Add Image
</label>
<input
id="image"
type="file"
name="image"
placeholder="Image"
className="hidden"
onChange={(e) => setImage(e.target.files[0])}
accept="image/*"
/>
</>
)}
</div>
<button
type="submit"
disabled={!(text || image)}
className={clsx(
"flex flex-col w-32 justify-center items-center",
"border-0 border-l border-gray-700 hover:bg-gray-900 hover:cursor-pointer",
"disabled:opacity-50 disabled:cursor-not-allowed"
)}
>
Create
</button>
</form>
);
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/components/post-displays.js | JavaScript | import { HeartIcon as HeartIconOutline } from "@heroicons/react/24/outline";
import { HeartIcon as HeartIconSolid } from "@heroicons/react/24/solid";
import clsx from "clsx";
export function PostBox({ children, className }) {
return (
<div className={clsx("px-16 py-8 border-b border-gray-500", className)}>
{children}
</div>
);
}
export function PostDisplay({ text, img_url, createdAt, username, children }) {
return (
<article className="flex flex-col">
<div className="flex flex-row gap-4">
<span className="text-gray-500">{`@${username}`}</span>
<span className="text-gray-500">{createdAt}</span>
</div>
<div>
{text && <p className="mt-2 mb-2 text-lg">{text}</p>}
{img_url && (
<img
src={img_url}
width={512}
height={512}
className="mt-2"
alt="post image"
/>
)}
</div>
{children}
</article>
);
}
export function LikesDisplay({ self_liked, num_likes, onLike }) {
return (
<div className="mt-6 flex flex-row gap-2 items-center">
<button className="h-8 w-8 text-gray-300" onClick={() => onLike()}>
{self_liked ? <HeartIconSolid /> : <HeartIconOutline />}
</button>
<span className="text-gray-400">{num_likes || 0}</span>
</div>
);
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/components/post.js | JavaScript | import React from "react";
import Moment from "react-moment";
import { ErrorBoundary } from "react-error-boundary";
import { useQuery, useQueryClient } from "@tanstack/react-query";
import { useSession } from "next-auth/react";
import { useRouter } from "next/navigation";
import { LikesDisplay, PostBox, PostDisplay } from "./post-displays";
function LikesContainer({ postId, self_liked, num_likes }) {
const { status } = useSession();
const router = useRouter();
const queryClient = useQueryClient();
const onLike = React.useCallback(async () => {
if (status !== "authenticated") {
router.push("/login");
return;
}
await fetch(`/api/posts/${postId}/likes`, {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify({}),
});
queryClient.invalidateQueries(["posts", postId, "likes"]);
}, [status, router, postId, queryClient]);
return (
<LikesDisplay self_liked={self_liked} num_likes={num_likes} onLike={onLike} />
);
}
function PostContainer({ id, createdAt, ...props }) {
const { data: likesData } = useQuery({
queryKey: ["posts", id, "likes"],
queryFn: async () => {
const res = await fetch(`/api/posts/${id}/likes`);
return await res.json();
},
staleTime: 1000 * 60,
refetchInterval: 1000 * 60,
});
return (
<PostDisplay id={id} {...props} createdAt={<Moment fromNow unix>{createdAt / 1000}</Moment>}>
{likesData && <LikesContainer postId={id} {...likesData} />}
</PostDisplay>
);
}
export default function Post({ id }) {
const { data, isLoading } = useQuery({
queryKey: ["posts", id],
queryFn: async () => {
const res = await fetch(`/api/posts/${id}`);
return await res.json();
},
});
return (
<PostBox>
<ErrorBoundary
fallback={
<div className="text-red-600">Post cannot be rendered....</div>
}
>
{isLoading && <div>Loading...</div>}
{data && <PostContainer {...data} />}
</ErrorBoundary>
</PostBox>
);
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/globals.css | CSS | @tailwind base;
@tailwind components;
@tailwind utilities;
:root {
--foreground-rgb: 255, 255, 255;
--background-start-rgb: 0, 0, 0;
--background-end-rgb: 0, 0, 0;
}
body {
color: rgb(var(--foreground-rgb));
background: linear-gradient(
to bottom,
transparent,
rgb(var(--background-end-rgb))
)
rgb(var(--background-start-rgb));
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/layout.js | JavaScript | import Providers from "./providers";
import { Inter } from "next/font/google";
import "./globals.css";
const inter = Inter({ subsets: ["latin"] });
export const metadata = {
title: "Litter",
description: "The latent social network",
};
export default function RootLayout({ children, params: { session } }) {
return (
<html lang="en">
<body className={inter.className}>
<Providers session={session}>{children}</Providers>
</body>
</html>
);
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/login/page.js | JavaScript | "use client";
import React from "react";
import { signIn, signOut, useSession } from "next-auth/react";
import { ArrowLeftIcon } from "@heroicons/react/24/solid";
import Link from "next/link";
export default function Login() {
const { status } = useSession();
const { clickAction, buttonText } = {
loading: {
clickAction: () => {},
buttonText: "Loading...",
},
authenticated: {
clickAction: () => signOut({callbackUrl: "/"}),
buttonText: "Sign out",
},
unauthenticated: {
clickAction: () => signIn("github", { callbackUrl: "/" }),
buttonText: "Sign in with GitHub",
},
}[status];
return (
<main className="mx-8 my-8 flex flex-col gap-4 relative">
<Link href="/" className="w-8 h-8 absolute top-0 left-0">
<ArrowLeftIcon />
</Link>
<div className="flex flex-row justify-center items-center">
<button
onClick={clickAction}
className="bg-black text-white px-8 py-4 border border-1 border-gray-500 rounded-md"
>
{buttonText}
</button>
</div>
</main>
);
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/page.js | JavaScript | "use client";
import React from "react";
import { useQuery, useQueryClient } from "@tanstack/react-query";
import CreatePostForm from "./components/create-post-form";
import Post from "./components/post";
import { TrashIcon } from "@heroicons/react/24/solid";
import { useSession } from "next-auth/react";
import clsx from "clsx";
import Link from "next/link";
export default function Home() {
const queryClient = useQueryClient();
const { data, isLoading } = useQuery({
queryKey: ["posts"],
queryFn: async () => {
const res = await fetch("/api/posts");
return await res.json();
},
staleTime: 1000 * 10,
refetchInterval: 1000 * 10,
});
const { posts, cooldown } = data || { posts: [], cooldown: false };
const createPost = async ({ text, encoded_img }) => {
if (!(text || encoded_img)) return;
const res = await fetch("/api/posts", {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify({ text, encoded_img }),
});
const json = await res.json();
await queryClient.invalidateQueries(["posts"]);
return json;
};
const { data: session, status } = useSession();
const username = session?.user?.name;
return (
<div className="flex flex-col relative">
<header
className={clsx(
"fixed top-0 w-screen h-[100px] bg-black border-b border-gray-500",
"py-8 flex flex-row justify-center items-center gap-4"
)}
>
<TrashIcon className="w-8 h-8" />
<h1 className="text-4xl">Litter</h1>
<Link href="/login" className="absolute right-0 mr-8">
{username ? `Logged in as @${username}` : "Login"}
</Link>
</header>
<main className="mt-[100px] mb-[120px]">
{isLoading && (
<div className="flex flex-row justify-center mt-28 text-2xl text-gray-400">
Loading...
</div>
)}
<div>
<ul>
{posts &&
posts.map(({ id }) => (
<li key={id}>
<Post
id={id}
onLike={(params) => onLike({ id, ...params })}
/>
</li>
))}
</ul>
</div>
</main>
<footer className="fixed bottom-0 w-screen border-t border-gray-500 h-[120px]">
<CreatePostForm onSubmit={createPost} cooldown={cooldown}/>
</footer>
</div>
);
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/providers.js | JavaScript | "use client";
import { QueryClient, QueryClientProvider } from "@tanstack/react-query";
import { ReactQueryStreamedHydration } from "@tanstack/react-query-next-experimental";
import { useState } from "react";
import { SessionProvider } from "next-auth/react"
export default function Providers({ children, session }) {
const [client] = useState(() => new QueryClient());
return (
<SessionProvider session={session}>
<QueryClientProvider client={client}>
<ReactQueryStreamedHydration>{children}</ReactQueryStreamedHydration>
</QueryClientProvider>
</SessionProvider>
);
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
app/utils.ts | TypeScript | import { createClient } from "redis";
import { S3Client } from "@aws-sdk/client-s3";
const redisClient = createClient({
password: process.env.REDIS_PASSWORD ?? "",
socket: {
host: process.env.REDIS_HOST ?? "",
port: Number(process.env.REDIS_PORT) ?? 6379,
},
});
export const getRedisClient = async () => {
if(redisClient.isOpen) return redisClient;
return await redisClient.connect();
};
const s3Client = new S3Client({
region: process.env.AWS_S3_REGION ?? "",
credentials: {
accessKeyId: process.env.AWS_ACCESS_KEY_ID ?? "",
secretAccessKey: process.env.AWS_SECRET_ACCESS_KEY ?? "",
}
});
export const getS3Client = async () => s3Client; | yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
next.config.js | JavaScript | /** @type {import('next').NextConfig} */
const nextConfig = {
webpack: (config, options) => {
config.plugins.push(
new options.webpack.IgnorePlugin({
resourceRegExp: /canvas/,
})
);
// add jsonlines loader
config.module.rules.push({
test: /\.jsonl$/,
loader: "jsonlines-loader",
type: "javascript/auto",
});
return config;
},
redirects: async () => {
return [
{
source: "/",
destination: "/bye",
permanent: false,
},
];
},
images: {
remotePatterns: [
{
protocol: "https",
hostname: "*.s3.amazonaws.com",
},
],
},
};
module.exports = nextConfig;
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
postcss.config.js | JavaScript | module.exports = {
plugins: {
tailwindcss: {},
autoprefixer: {},
},
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
tailwind.config.js | JavaScript | /** @type {import('tailwindcss').Config} */
module.exports = {
content: [
'./pages/**/*.{js,ts,jsx,tsx,mdx}',
'./components/**/*.{js,ts,jsx,tsx,mdx}',
'./app/**/*.{js,ts,jsx,tsx,mdx}',
],
theme: {
extend: {
backgroundImage: {
'gradient-radial': 'radial-gradient(var(--tw-gradient-stops))',
'gradient-conic':
'conic-gradient(from 180deg at 50% 50%, var(--tw-gradient-stops))',
},
},
},
plugins: [],
}
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
worker/dump_data.py | Python | import main
import asyncio
import redis.asyncio as redis
import aiofiles
import json
async def dump_data(redis_client: redis.Redis):
async with aiofiles.open("data.jsonl", "w") as f:
async for key, _ in redis_client.zscan_iter("posts", match="*"):
post = await redis_client.hgetall(key) # type: ignore
post.pop("username")
await f.write(json.dumps(post) + "\n")
if __name__ == "__main__":
config = main.create_config()
redis_client = main.create_redis_client(config)
loop = asyncio.get_event_loop()
loop.run_until_complete(dump_data(redis_client=redis_client))
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
worker/main.py | Python | from typing import Callable, Awaitable
from urllib.parse import urlparse
import tempfile
import uuid
import io
import os
from openai import AsyncOpenAI
import aiohttp
import asyncio
import base64
from loguru import logger
import dotenv
from PIL import Image
import redis.asyncio as redis
import boto3
class OpenAIClient:
def __init__(
self,
api_key: str,
upload_img_fn: Callable[[bytes, str], Awaitable[str]],
delete_img_fn: Callable[[str], Awaitable[None]],
debug_store_img: bool = False,
):
self.api_client = AsyncOpenAI(api_key=api_key)
self.upload_img_fn = upload_img_fn
self.delete_img_fn = delete_img_fn
self.debug_store_img = debug_store_img
async def guess_message(self, caption: str) -> str:
completion = await self.api_client.chat.completions.create(
model="gpt-3.5-turbo",
max_tokens=512,
messages=[
{
"role": "user",
"content": f"""
I have a new social network, where text posts get encrypted into image descriptions.
Your job is to decrypt these messages and guess the original post.
Here is the procedure:
- a user posts a text post
- the text is used as the input of an AI text-to-image generator
- the image is fed to an AI image captioning model
This is the output of the captioning model:
--- BEGIN CAPTION ---
"{caption}"
--- END CAPTION ---
Your task:
- Guess the original post.
- Take your best shot.
- Write directly the text you think was originally written by the user.
- Write from the perspective of the original user.
- The original message is not neccesarily visual or descriptive. Rather it is probably a simple message like one would find on Twitter.
- Output just one line with your guess, nothing else!
""".strip(),
},
],
)
guess = completion.choices[0].message.content
if not guess:
raise ValueError("Empty or missing guess")
return guess.strip().strip('"')
async def get_img_caption(self, img_url) -> str:
completion = await self.api_client.chat.completions.create(
model="gpt-4-vision-preview",
max_tokens=512,
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "Describe this image to a person with impaired vision. Be short and concise.",
},
{
"type": "image_url",
"image_url": {
"url": img_url,
},
},
],
},
],
)
caption = completion.choices[0].message.content
if not caption:
raise ValueError("Empty or missing caption")
return caption
async def create_img(self, caption: str, upload_to_key: str | None = None) -> str:
response = await self.api_client.images.generate(
model="dall-e-3",
size="1024x1024",
quality="standard",
n=1,
prompt=f"{caption}\n#notext #message #animageisworthathousandwords",
)
img_url = response.data[0].url
if not img_url:
raise ValueError("Empty or missing image url")
async with aiohttp.ClientSession() as session:
async with session.get(img_url) as resp:
content = await resp.read()
with tempfile.NamedTemporaryFile(suffix=".png") as f:
f.write(content)
f.flush()
img = Image.open(f.name)
if self.debug_store_img:
img.save("debug.jpg")
bytes_io = io.BytesIO()
img.save(bytes_io, format="JPEG")
content = bytes_io.getvalue()
if upload_to_key:
img_url = await self.upload_img_fn(content, upload_to_key)
return img_url
encoded_img = base64.b64encode(content)
data_url = f"data:image/png;base64,{encoded_img.decode('utf-8')}"
return data_url
class KVClient:
def __init__(
self,
redis_client: redis.Redis,
openai_client: OpenAIClient,
modify: bool = False,
):
self.redis_client = redis_client
self.openai_client = openai_client
self.modify = modify
async def process_pending_post(self, key: str):
logger.debug(f"Processing {key}")
post = await self.redis_client.hgetall(key) # type: ignore
created_at = int(post["createdAt"])
logger.debug(f"Created at {created_at}")
if self.modify:
if img_url := post.get("img_url"):
logger.debug(f"Image url: {img_url}")
caption = await self.openai_client.get_img_caption(img_url)
await self.openai_client.delete_img_fn(img_url)
logger.debug(f"Caption: {caption}")
new_img_key = f"processed/{uuid.uuid4()}.jpg"
new_img_url = await self.openai_client.create_img(
caption, upload_to_key=new_img_key
)
logger.debug(f"New image url: {len(new_img_url)}")
await self.redis_client.hset(key, "img_url", new_img_url) # type: ignore
if text := post.get("text"):
logger.debug(f"Text: {text}")
prompt = f"""
Create an image that visually transmits the following message:
--- BEGIN MESSAGE ---
{text}
--- END MESSAGE ---
Make the message into a pictogram, a visual representation of the message.
Do not use text.
""".strip()
img_url = await self.openai_client.create_img(prompt)
logger.debug(f"Image url: {len(img_url)=}")
caption = await self.openai_client.get_img_caption(img_url)
logger.debug(f"Caption: {caption}")
new_text = await self.openai_client.guess_message(caption)
logger.debug(f"New text: {new_text}")
await self.redis_client.hset(key, "text", new_text) # type: ignore
await self.redis_client.zadd("posts", {key: -created_at})
async def get_all_pending_keys(self) -> list[str]:
keys = []
while True:
key = await self.redis_client.lpop("pending") # type: ignore
if not key:
break
keys.append(key)
return keys
async def process_pending(self):
try:
pending_keys = await self.get_all_pending_keys()
if not pending_keys:
return
logger.info(f"Processing {len(pending_keys)} pending posts")
results = await asyncio.gather(
*[self.process_pending_post(key) for key in pending_keys],
return_exceptions=True,
)
for key, result in zip(pending_keys, results):
if isinstance(result, Exception):
try:
raise result
except Exception as e:
logger.exception(f"Error processing {key}: {e}")
except Exception as e:
logger.exception(f"Error processing pending posts: {e}")
async def process_pending_loop(self):
while True:
await self.process_pending()
await asyncio.sleep(5)
def get_env(name: str) -> str:
value = os.environ.get(name)
if not value:
raise ValueError(f"Missing env var {name}")
return value
def create_redis_client(config) -> redis.Redis:
redis_client = redis.Redis(
host=config["REDIS_HOST"],
port=int(config["REDIS_PORT"]),
password=config["REDIS_PASSWORD"],
decode_responses=True,
)
return redis_client
def create_config() -> dict[str, str]:
config = {
**os.environ,
**dotenv.dotenv_values("../.env"),
**dotenv.dotenv_values("../.env.local"),
**dotenv.dotenv_values("../.env.development.local"),
**dotenv.dotenv_values(".env"),
**dotenv.dotenv_values(".env.local"),
**dotenv.dotenv_values(".env.development.local"),
}
return config
if __name__ == "__main__":
config = create_config()
s3_client = boto3.client(
"s3",
aws_access_key_id=config["AWS_ACCESS_KEY_ID"],
aws_secret_access_key=config["AWS_SECRET_ACCESS_KEY"],
region_name=config["AWS_S3_REGION"],
)
def upload_img_sync(content: bytes, key: str) -> str:
s3_client.upload_fileobj(
io.BytesIO(content),
config["AWS_BUCKET_NAME"],
key,
)
url = f"https://{config['AWS_BUCKET_NAME']}.s3.amazonaws.com/{key}"
return url
def upload_img(content: bytes, key: str) -> Awaitable[str]:
return asyncio.to_thread(upload_img_sync, content, key)
def delete_img_sync(img_url: str) -> None:
parsed_url = urlparse(img_url)
key = parsed_url.path[1:]
logger.debug(f"Deleting {key}")
s3_client.delete_object(
Bucket=config["AWS_BUCKET_NAME"],
Key=key,
)
def delete_img(img_url: str) -> Awaitable[None]:
return asyncio.to_thread(delete_img_sync, img_url)
client = OpenAIClient(api_key=config["OPENAI_API_KEY"], upload_img_fn=upload_img, delete_img_fn=delete_img,
debug_store_img=(config.get("DEBUG_STORE_IMG") in ["1", "true", "True"]),
)
redis_client = create_redis_client(config)
kv_client = KVClient(
redis_client=redis_client,
openai_client=client,
modify=True,
)
loop = asyncio.get_event_loop()
loop.run_until_complete(kv_client.process_pending_loop())
| yk/litter | 70 | JavaScript | yk | Yannic Kilcher | ||
fizzbuzz.c | C | #include <stdio.h>
int main() {
for (int i = 0; i < 30; i++) {
if (i % 3 == 0) {
if(i % 5 == 0)
printf("FizzBuzz\n");
else
printf("Fizz\n");
}
else if (i % 5 == 0) {
printf("Buzz\n");
} else {
printf("%d\n", i);
}
}
return 0;
} | yk/llmvm | 31 | Python | yk | Yannic Kilcher | ||
interface.py | Python | from typing import Any
import pydantic
def to_vtype(value, vtype):
match vtype:
case "i32":
return int(value)
case "i8":
return str(value)
case "str":
return str(value)
raise NotImplementedError(vtype)
class Instruction(pydantic.BaseModel):
kind: str
class Expr(Instruction):
pass
class Load(Expr):
kind: str = "load"
vtype: str
ptr: str
class Copy(Expr):
kind: str = "copy"
ptr: str
class Alloc(Expr):
kind: str = "alloc"
vtype: str
class AllocArray(Expr):
kind: str = "alloc_array"
vtype: str
size: int
class GetElementPtr(Expr):
kind: str = "get_element_ptr"
vtype: str
ptr: str
idx: str
class Icmp(Expr):
kind: str = "icmp"
vtype: str
op: str
lhs: str
rhs: str
class Srem(Expr):
kind: str = "srem"
vtype: str
lhs: str
rhs: str
class Add(Expr):
kind: str = "add"
vtype: str
lhs: str
rhs: str
class Mul(Expr):
kind: str = "mul"
vtype: str
lhs: str
rhs: str
class Arg(pydantic.BaseModel):
vtype: str
value: str
class Call(Expr):
kind: str = "call"
name: str
args: list[Arg]
class Assign(Instruction):
kind: str = "assign"
reg: str
expr: Expr
class Store(Instruction):
kind: str = "store"
vtype: str
value: str
ptr: str
class Branch(Instruction):
kind: str = "branch"
label: str
class BranchCond(Instruction):
kind: str = "branch_cond"
cond_reg: str
label_true: str
label_false: str
class Return(Instruction):
kind: str = "return"
vtype: str
value: str
class Switch(Instruction):
kind: str = "switch"
ptr: str
default_label: str
cases: dict[str, str]
class Program(pydantic.BaseModel):
instructions: list[Instruction]
labels: dict[str, int]
constants: dict[str, Any]
convert_numbers_to_chars: bool = False | yk/llmvm | 31 | Python | yk | Yannic Kilcher | ||
main.py | Python | from loguru import logger
import parsing
import vms
import sys
def main():
try:
fname, vm_type = sys.argv[1:]
logger.info(f"Loading {fname}")
with open(fname) as in_f:
program = parsing.parse_program(in_f)
if "snek" in fname:
program.convert_numbers_to_chars = True
logger.info(f"Running {fname}")
match vm_type:
case "ref":
vm = vms.VM(constants=program.constants)
case "gpt":
vm = vms.GPTVM(constants=program.constants)
case "fullgpt":
vm = vms.FullGPTVM(constants=program.constants)
case "chadgpt":
vm = vms.ChadGPTVM(constants=program.constants)
case _:
raise NotImplementedError(vm_type)
retval = vm.run_program(program)
logger.info(f"Program returned {retval}")
sys.exit(retval)
except Exception:
logger.exception("Error running program")
if __name__ == '__main__':
main() | yk/llmvm | 31 | Python | yk | Yannic Kilcher | ||
parsing.py | Python | import re
from loguru import logger
from interface import Arg, Load, Icmp, Srem, Add, Mul, Call, Assign, Store, Branch, BranchCond, Return, Program, to_vtype, GetElementPtr, Copy, Switch, AllocArray, Alloc
def _line_stripper(in_f):
for line in in_f:
line = line.rstrip()
if not line:
continue
yield line
def parse_arg(arg):
logger.debug(f"parse_arg({arg})")
if m := re.match(r"ptr noundef (\S+)", arg):
return Arg(vtype="str", value=m.group(1))
if m := re.match(r"i32 noundef (\S+)", arg):
return Arg(vtype="i32", value=m.group(1))
raise NotImplementedError(arg)
def parse_call(expr):
logger.debug(f"parse_call({expr})")
if m := re.match(r"\s*call \w+(?: \(.*\))? @(\w+)\((.*)\)", expr):
name, args = m.groups()
args = args.split(", ")
args = [parse_arg(arg) for arg in args if arg]
return Call(name=name, args=args)
return None
def parse_expr(expr):
if m := re.match(r"alloca \[(\d+) x (\S+)\]", expr):
size, vtype = m.groups()
return AllocArray(vtype=vtype, size=int(size))
if m := re.match(r"alloca (\S+),", expr):
vtype = m.group(1)
return Alloc(vtype=vtype)
if m := re.match(r"sext \S+ (\S+) to \S+", expr):
return Copy(ptr=m.group(1))
if m := re.match(r"load (\w+), ptr (%\d+),", expr):
return Load(vtype=m.group(1), ptr=m.group(2))
if m := re.match(r"icmp (eq|ne|sgt|sge|slt|sle) (\w+) (\S+), (\S+)", expr):
op, vtype, lhs, rhs = m.groups()
return Icmp(vtype=vtype, op=op, lhs=lhs, rhs=rhs)
if m := re.match(r"srem (\w+) (\S+), (\S+)", expr):
vtype, lhs, rhs = m.groups()
return Srem(vtype=vtype, lhs=lhs, rhs=rhs)
if m := re.match(r"add nsw (\w+) (\S+), (\S+)", expr):
vtype, lhs, rhs = m.groups()
return Add(vtype=vtype, lhs=lhs, rhs=rhs)
if m := re.match(r"mul nsw (\w+) (\S+), (\S+)", expr):
vtype, lhs, rhs = m.groups()
return Mul(vtype=vtype, lhs=lhs, rhs=rhs)
if call := parse_call(expr):
if call is not None:
logger.debug(f"found call {call}")
return call
if m := re.match(r"getelementptr inbounds \[\d+ x (\S+)\], ptr (\S+), i32 0, i32 (\S+)", expr):
vtype, ptr, idx = m.groups()
return GetElementPtr(vtype=vtype, ptr=ptr, idx=idx)
raise NotImplementedError(expr)
def parse_switch(in_f):
cases = {}
for line in _line_stripper(in_f):
if re.fullmatch(r"\s+\]", line):
break
if m := re.match(r"\s+i32 (\S+), label %(\d+)", line):
value, label = m.groups()
cases[value] = label
continue
raise NotImplementedError(line)
else:
raise ValueError("Expected ']' in switch")
return cases
def parse_instructions(in_f):
instructions = []
labels = {}
for line in _line_stripper(in_f):
if re.fullmatch(r"\}", line):
break
if m := re.match(r"(\d+):", line):
label = m.group(1)
labels[label] = len(instructions)
continue
if m := re.fullmatch(r"\s+(%\d+) = (.*)", line): # register assignment
reg, expr = m.groups()
expr = parse_expr(expr)
if expr is not None:
instructions.append(Assign(reg=reg, expr=expr))
continue
if m := re.match(r"\s+store (\w+) (\S+), ptr (\S+),", line):
vtype, value, ptr = m.groups()
instructions.append(Store(vtype=vtype, value=value, ptr=ptr))
continue
if m := re.match(r"\s+br label %(\d+)", line):
label = m.group(1)
instructions.append(Branch(label=label))
continue
if m := re.match(r"\s+br i1 (%\d+), label %(\d+), label %(\d+)", line):
cond_reg, label_true, label_false = m.groups()
instructions.append(BranchCond(cond_reg=cond_reg, label_true=label_true, label_false=label_false))
continue
if m := re.match(r"\s+ret (\S+) (\S+)", line):
vtype, value = m.groups()
instructions.append(Return(vtype=vtype, value=value))
continue
if call := parse_call(line):
if call is not None:
logger.debug(f"found call {call}")
instructions.append(call)
continue
if m := re.match(r"\s+switch \S+ (\S+), label %(\d+) \[", line):
ptr, default_label = m.groups()
cases = parse_switch(in_f)
instructions.append(Switch(ptr=ptr, default_label=default_label, cases=cases))
continue
raise NotImplementedError(line)
return instructions, labels
def parse_program(in_f):
constants = {}
for line in _line_stripper(in_f):
if m := re.match(r'(@\.str(?:\.\d+)?) .* c"([^"]+)\\00",', line):
name, value = m.groups()
value = value.replace(r"\0A", "\n")
constants[name] = to_vtype(value=value, vtype="str")
continue
if re.fullmatch(r"define .* \{", line):
instructions, labels = parse_instructions(in_f)
break
if line.split()[0] in (";", "target", "source_filename"):
continue
raise NotImplementedError(line)
else:
raise NotImplementedError()
program = Program(instructions=instructions, labels=labels, constants=constants)
logger.debug(f"parsed program: {program}")
logger.debug("Instructions:")
for instr in program.instructions:
logger.debug(f" {instr}")
return program
| yk/llmvm | 31 | Python | yk | Yannic Kilcher | ||
snek.c | C | #include <stdio.h>
// very simple ascii snake game on 4x4 grid
#include <stdio.h>
#include <stdlib.h>
#define ROWS 4
#define COLS 4
#define GRID_ACCESS(grid, row, col) grid[row * COLS + col]
int main() {
// Define the grid
char grid[ROWS * COLS];
// Initialize the random number generator
srand(42);
// Initialize the grid with empty spaces
for (int i = 0; i < ROWS; i++) {
for (int j = 0; j < COLS; j++) {
GRID_ACCESS(grid, i, j) = ' ';
}
}
// Initialize the snake at a random position
int snake_row = rand() % ROWS;
int snake_col = rand() % COLS;
GRID_ACCESS(grid, snake_row, snake_col) = 'o';
// Place the food at a random location
int food_row = rand() % ROWS;
int food_col = rand() % COLS;
GRID_ACCESS(grid, food_row, food_col) = '*';
// Print the initial grid
for (int i = 0; i < ROWS; i++) {
for (int j = 0; j < COLS; j++) {
printf("%c ", GRID_ACCESS(grid, i, j));
}
printf("\n");
}
// Game loop
while (1) {
// Take user input for the direction of the snake
char direction;
printf("Enter direction (w/a/s/d): ");
scanf(" %c", &direction);
// Erase the snake from the grid
GRID_ACCESS(grid, snake_row, snake_col) = ' ';
// Update the position of the snake based on the user input
switch (direction) {
case 'w':
snake_row--;
break;
case 's':
snake_row++;
break;
case 'a':
snake_col--;
break;
case 'd':
snake_col++;
break;
}
// Check if the snake has collided with the wall or itself
if (snake_row < 0 || snake_row >= ROWS || snake_col < 0 || snake_col >= COLS || GRID_ACCESS(grid, snake_row, snake_col) == 'o') {
printf("Game over!\n");
break;
}
// Check if the snake has collided with the food
if (snake_row == food_row && snake_col == food_col) {
printf("You won!\n");
break;
}
// Update the grid with the new position of the snake
GRID_ACCESS(grid, snake_row, snake_col) = 'o';
// Print the updated grid
for (int i = 0; i < ROWS; i++) {
for (int j = 0; j < COLS; j++) {
printf("%c ", GRID_ACCESS(grid, i, j));
}
printf("\n");
}
}
return 0;
}
| yk/llmvm | 31 | Python | yk | Yannic Kilcher | ||
vms.py | Python | from typing import Any
import random
import re
from loguru import logger
import openai
import openai.error
import os
import pydantic
from interface import (
Alloc,
AllocArray,
Expr,
to_vtype,
Load,
Icmp,
Srem,
Copy,
Add,
Mul,
Call,
Assign,
Store,
Branch,
BranchCond,
Return,
Program,
GetElementPtr,
Switch,
)
class VM(pydantic.BaseModel):
name: str = "VM"
constants: dict[str, Any]
registers: dict[str, Any] = {}
memory: dict[str, Any] = {}
_program: Program | None = pydantic.PrivateAttr(None)
class Config:
ignored_types = (Expr,)
def _get_from_registers(self, value):
return self.registers[value]
def _to_vtype(self, value, vtype):
return to_vtype(value, vtype)
def get_value(self, value, vtype=None):
if isinstance(value, str):
if value.startswith("%"):
value = self._get_from_registers(value)
if isinstance(value, str):
logger.debug(f"found string {value}")
if m := re.match(r"arr ptr=(\S+) idx=(\S+)", value):
ptr, idx = m.groups()
logger.debug(f"performing array lookup on {ptr} {idx}")
arr = self._get_from_registers(ptr)
logger.debug(f"arr = {arr}")
value = self._load_array(arr, idx)
logger.debug(f"array lookup result = {value}")
elif value.startswith("@"):
value = self.constants[value]
if vtype is not None:
value = self._to_vtype(value, vtype)
return value
def _cmp_with_op(self, op, lhs, rhs) -> bool:
match op:
case "eq":
return lhs == rhs
case "ne":
return lhs != rhs
case "sgt":
return lhs > rhs
case "sge":
return lhs >= rhs
case "slt":
return lhs < rhs
case "sle":
return lhs <= rhs
raise NotImplementedError(op)
def _rem(self, lhs, rhs):
return lhs % rhs
def _add(self, lhs, rhs):
return lhs + rhs
def _mul(self, lhs, rhs):
return lhs * rhs
def _load_array(self, arr, idx):
return arr[idx]
def _alloc_array(self, vtype, size):
if vtype in ("i32", "i8"):
return {str(i): 0 for i in range(size)}
raise NotImplementedError(vtype)
def eval_expr(self, expr: Expr):
logger.debug(f"eval_expr({expr})")
match expr:
case Copy(ptr=ptr):
return self.get_value(ptr)
case Alloc(vtype=vtype):
return self.get_value(0, vtype)
case AllocArray(vtype=vtype, size=size):
return self._alloc_array(vtype, size)
case Load(vtype=vtype, ptr=ptr):
return self._to_vtype(self._get_from_registers(ptr), vtype)
case Icmp(vtype=vtype, op=op, lhs=lhs, rhs=rhs):
logger.debug(f"icmp {vtype} {op} {lhs} {rhs}")
lhs = self.get_value(lhs, vtype)
rhs = self.get_value(rhs, vtype)
return self._cmp_with_op(op, lhs, rhs)
case Srem(vtype=vtype, lhs=lhs, rhs=rhs):
lhs = self.get_value(lhs, vtype)
rhs = self.get_value(rhs, vtype)
return self._rem(lhs, rhs)
case Add(vtype=vtype, lhs=lhs, rhs=rhs):
lhs = self.get_value(lhs, vtype)
rhs = self.get_value(rhs, vtype)
return self._add(lhs, rhs)
case Mul(vtype=vtype, lhs=lhs, rhs=rhs):
lhs = self.get_value(lhs, vtype)
rhs = self.get_value(rhs, vtype)
return self._mul(lhs, rhs)
case Call(name=name, args=args):
logger.debug(f"calling {name} {args}")
match name:
case "printf":
logger.debug(f"printf {args}")
args = [self.get_value(arg.value, arg.vtype) for arg in args]
def _maybe_to_char(value):
try:
return chr(int(value))
except ValueError:
return value
if self._program is not None and self._program.convert_numbers_to_chars:
args = [_maybe_to_char(arg) for arg in args]
logger.debug(f"printf {args}")
fstring = args[0]
# we need to replace all the percent-formatters (like %d) with {}
fstring = re.sub(r"%\w", "{}", fstring)
out_str = fstring.format(*args[1:])
print(out_str, end="")
return 0
case "srand":
seed = self.get_value(args[0].value, args[0].vtype)
self._rng = random.Random(seed)
return
case "scanf":
logger.debug(f"scanf {args}")
dst = args[1].value
prompt = self.get_value(args[0].value, "str")
assert prompt.strip() == "%c"
input_str = input()
char = ord(input_str)
self.store(dst, char)
return 0
case "rand":
return self._rng.randint(0, 100)
raise NotImplementedError(name)
case GetElementPtr(vtype=vtype, ptr=ptr, idx=idx):
logger.debug(f"getting element ptr from {ptr} -> {idx}")
idx = self.get_value(idx)
logger.debug(f"idx into array is {idx}")
return f"arr ptr={ptr} idx={idx}"
raise NotImplementedError(expr)
def _store_in_registers(self, reg, value):
self.registers[reg] = value
def _store(self, ptr, value):
self._store_in_registers(ptr, value)
def _is_array_ref(self, value):
return isinstance(value, str) and value.startswith("arr ptr")
def _parse_array_ref(self, value):
m = re.match(r"arr ptr=(\S+) idx=(\S+)", value)
ptr, idx = m.groups()
return ptr, idx
def _store_array(self, ptr, idx, value):
logger.debug(f"called store_array ptr={ptr} idx={idx} value={value}")
arr = self._get_from_registers(ptr)
logger.debug(f"before store: arr = {arr}")
arr[idx] = value
logger.debug(f"after store: arr = {arr}")
def assign(self, reg, value):
logger.debug(f"assign {value} to {reg}")
self._store(reg, value)
def store(self, ptr, value):
logger.debug(f"store {value} to {ptr}")
# check if ptr points to an array reference
reg_value = self._get_from_registers(ptr)
logger.debug(f"ptr {ptr} exists, value = {reg_value}")
if self._truthy(self._is_array_ref(reg_value)):
logger.debug(f"ptr {ptr} is an array ref")
arr_ptr, idx = self._parse_array_ref(reg_value)
logger.debug(f"parsed array ref: {arr_ptr} {idx}")
self._store_array(arr_ptr, idx, value)
return
self._store(ptr, value)
def _truthy(self, value):
return bool(value)
def run_program(self, program: Program):
self._program = program
iptr = 0
num_instr = 0
while iptr < len(program.instructions):
instr = program.instructions[iptr]
logger.debug(f"{num_instr} || executing {instr}")
num_instr += 1
match instr:
case Return(vtype=vtype, value=value):
logger.debug(f"return {value}")
return self.get_value(value, vtype=vtype)
case Branch(label=label):
logger.debug(f"branch to {label}")
iptr = program.labels[label]
continue
case BranchCond(
cond_reg=cond_reg, label_true=label_true, label_false=label_false
):
cond = self.get_value(cond_reg)
logger.debug(f"cond {cond_reg} = {cond} (type {type(cond)}))")
if self._truthy(cond):
logger.debug(f"branch to {label_true}")
iptr = program.labels[label_true]
else:
logger.debug(f"branch to {label_false}")
iptr = program.labels[label_false]
continue
case Store(value=value, ptr=ptr):
logger.debug(f"store {value} to {ptr}")
value = self.get_value(value)
self.store(ptr, value)
case Assign(reg=reg, expr=expr):
value = self.eval_expr(expr)
self.assign(reg, value)
case Switch(ptr=ptr, default_label=default_label, cases=cases):
value = self.get_value(ptr)
logger.debug(f"switch on {value}")
for case, label in cases.items():
if self._truthy(self._cmp_with_op("eq", value, case)):
logger.debug(f"branch to case {case} -> {label}")
iptr = program.labels[cases[case]]
break
else:
logger.debug(f"branch to default {default_label}")
iptr = program.labels[default_label]
continue
case _:
if isinstance(instr, Expr):
self.eval_expr(instr)
else:
raise NotImplementedError(instr)
iptr += 1
openai.api_key = os.getenv("OPENAI_KEY")
class GPTVM(VM):
name: str = "GPT VM"
registers: dict[str, Any] = {}
default_system: str = ""
postfix: str = """Write your answer on a single line. Be very short and concise.
I just want the plain answer, not the explanation."""
def _gpt_get_answer(self, prompt, system=""):
logger.debug(f"Getting answer for prompt: {prompt} | system: {system}")
messages = []
system = system or self.default_system
if system:
messages.append({"role": "system", "content": system})
prompt = f"""{prompt}
{self.postfix}"""
messages.append({"role": "user", "content": prompt})
for i in range(5):
try:
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=messages,
max_tokens=1024,
timeout=10,
)
break
except openai.error.TryAgain:
logger.debug(f"Try again {i}...")
continue
else:
raise RuntimeError("Failed to get response from GPT")
response = response["choices"][0]["message"]["content"].strip() # type: ignore
logger.debug(f"Got answer: {response}")
return response
def _to_vtype(self, value, vtype):
return value
get_from_registers_prompt : str = """Look at registers: {registers}.
Now get me the value of {value}."""
def _get_from_registers(self, value):
return self._gpt_get_answer(
self.get_from_registers_prompt.format(registers=self.registers, value=value)
)
add_prompt : str = """Add {lhs} and {rhs}."""
def _add(self, lhs, rhs):
return self._gpt_get_answer(self.add_prompt.format(lhs=lhs, rhs=rhs))
rem_prompt : str = """Get the remainder value of {lhs} divided by {rhs}."""
def _rem(self, lhs, rhs):
return self._gpt_get_answer(self.rem_prompt.format(lhs=lhs, rhs=rhs))
multiply_prompt : str = """Multiply {lhs} and {rhs}."""
def _mul(self, lhs, rhs):
return self._gpt_get_answer(self.multiply_prompt.format(lhs=lhs, rhs=rhs))
load_array_prompt : str = """Get the value of index {idx} in array {arr}."""
def _load_array(self, arr, idx):
return self._gpt_get_answer(self.load_array_prompt.format(arr=arr, idx=idx))
def _truthy(self, value):
if isinstance(value, bool):
b = value
elif isinstance(value, int):
b = bool(value)
elif isinstance(value, str):
if any(t in value.lower() for t in ("yes", "true")):
b = True
else:
b = False
else:
raise NotImplementedError(value)
logger.debug(f"truthiness of {value} = {b}")
return b
cmp_eq_prompt : str = """Are {lhs} and {rhs} equal?"""
cmp_ne_prompt : str = """Are {lhs} and {rhs} different?"""
cmp_sgt_prompt : str = """Is {lhs} greater than {rhs}?"""
cmp_sge_prompt : str = """Is {lhs} greater than or equal to {rhs}?"""
cmp_slt_prompt : str = """Is {lhs} less than {rhs}?"""
cmp_sle_prompt : str = """Is {lhs} less than or equal to {rhs}?"""
cmp_system : str = """You are a very keen observer."""
def _cmp_with_op(self, op, lhs, rhs) -> bool:
match op:
case "eq":
prompt = self.cmp_eq_prompt.format(lhs=lhs, rhs=rhs)
case "ne":
prompt = self.cmp_ne_prompt.format(lhs=lhs, rhs=rhs)
case "sgt":
prompt = self.cmp_sgt_prompt.format(lhs=lhs, rhs=rhs)
case "sge":
prompt = self.cmp_sge_prompt.format(lhs=lhs, rhs=rhs)
case "slt":
prompt = self.cmp_slt_prompt.format(lhs=lhs, rhs=rhs)
case "sle":
prompt = self.cmp_sle_prompt.format(lhs=lhs, rhs=rhs)
case _:
raise NotImplementedError(op)
return self._gpt_get_answer(system=self.cmp_system, prompt=prompt)
is_array_ref_prompt : str = """Is {value} an array reference?"""
def _is_array_ref(self, value):
return self._gpt_get_answer(self.is_array_ref_prompt.format(value=value))
parse_array_ref_prompt : str = """Parse array reference {value}. Give me the array pointer and the index separated by a pipe symbol (|)"""
def _parse_array_ref(self, value):
return self._gpt_get_answer(self.parse_array_ref_prompt.format(value=value)).split(
"|"
)
store_array_prompt : str = """Store {value} in array {arr} at index {idx}. Give me back the full new array after the update."""
def _store_array(self, ptr, idx, value):
arr = self._get_from_registers(ptr)
answer = self._gpt_get_answer(
self.store_array_prompt.format(value=value, arr=arr, idx=idx)
)
self._store_in_registers(ptr, answer)
class FullGPTVM(GPTVM):
name: str = "Full GPT VM"
registers: str = f"{({i: None for i in range(32)})}"
store_in_registers_prompt : str = """Store the value "{value}" in register {reg}. Here are the current registers: {registers}. Give me back the complete state of the registers after the update."""
def _store_in_registers(self, reg, value):
self.registers = self._gpt_get_answer(
self.store_in_registers_prompt.format(
value=value, reg=reg, registers=self.registers
)
)
class ChadGPTVM(FullGPTVM):
name: str = "Chad GPT VM"
postfix : str = """Bro I know you love to talk, but I really need just the answer.
Please don't explain your answer, and don't write pleaseantaries, like "the answer is...".
Just give me the plain answer.
Here's an example of a good answer: 42. That's it. Just the number. Limit prose. Be super concise."""
get_from_registers_prompt : str = """Bro! Look at those rad registers: {registers}.
Bro fr just tell me me the value of register {value}."""
add_prompt : str = """Yo, broooo! Yo what's the sum of {lhs} and {rhs}?"""
rem_prompt : str = """Bro fr you know how remainders and stuff works?
I really need the remainder value of {lhs} divided by {rhs}. What is it bro?"""
multiply_prompt : str = """My maaaaan, you mad good at multiplication, right?
Yo what's {lhs} times {rhs}?"""
load_array_prompt : str = """Bro listen! I have this array here: {arr}.
And I just need the value of index {idx}. Can you help me out?"""
cmp_eq_prompt : str = """Bro I'm so confused. Are {lhs} and {rhs} equal?"""
cmp_ne_prompt : str = """Bro, my brain is melting. Are {lhs} and {rhs} different?"""
cmp_sgt_prompt : str = """What's up bro? Tell me this: Is {lhs} greater than {rhs}?"""
cmp_sge_prompt : str = """You know what's awesome? Comparing numbers.
Tell me this: Is {lhs} greater than or equal to {rhs}?"""
cmp_slt_prompt : str = """Bro I'm actually not sure about this one:
Is {lhs} less than {rhs}?"""
cmp_sle_prompt : str = """My main man! I need your help with this one:
Is {lhs} less than or equal to {rhs}?"""
cmp_system : str = """Bro!"""
is_array_ref_prompt : str = """Bro look at this: "{value}". Is this an array reference that looks like "arr ptr=..."?
Like does it look like it would point to an array?"""
parse_array_ref_prompt : str = """Bro. I really need to parse this array reference: {value}.
Can you give me the array reference and the index separated by a pipe symbol (|)?"""
store_array_prompt : str = """Bro, look, I have this array here: {arr}.
I need you to store the value "{value}" in it at index {idx}. Can you give me back the full new array after the update?"""
store_in_registers_prompt : str= """My main maaan! I need you to store the value "{value}" in register "{reg}".
Look here, these are the current registers: {registers}.
Can you give me back the complete state of the registers after the update? Thanks bro!"""
| yk/llmvm | 31 | Python | yk | Yannic Kilcher | ||
find_collision.py | Python | #!/usr/bin/env python3
#partially based on https://github.com/AsuharietYgvar/AppleNeuralHash2ONNX/blob/master/nnhash.py
import tensorflow as tf
from art.estimators.classification import TensorFlowV2Classifier
from art.attacks import evasion
import numpy as np
from PIL import Image
seed_fn = './neuralhash_128x96_seed1.dat'
seed1 = open(seed_fn, 'rb').read()[128:]
seed1 = np.frombuffer(seed1, dtype=np.float32)
seed1 = seed1.reshape([96, 128])
def _neural_hash(out):
hash_output = seed1.dot(out.numpy().flatten())
hash_bits = ''.join(['1' if it >= 0 else '0' for it in hash_output])
hash_hex = '{:0{}x}'.format(int(hash_bits, 2), len(hash_bits) // 4)
return hash_hex
def _load_img(fname):
img = Image.open(fname)
img = img.convert('RGB')
img = img.resize([360, 360])
img = np.array(img).astype(np.float32) / 255.0
img = img * 2.0 - 1.0
img = img.transpose(2, 0, 1).reshape([1, 3, 360, 360])
return img
model = tf.saved_model.load('./model.pb')
last_input = None
def _model(inp, **kwargs):
global last_input
last_input = np.copy(inp)
output = model(image=inp)[0][0, :, 0, 0]
return output
source_img = _load_img('./doge.jpeg')
target_img = _load_img('./titanic.jpeg')
loss_object = tf.keras.losses.CosineSimilarity()
target_hash = _model(target_img)
target_neural_hash = _neural_hash(target_hash)
print('TARGET HASH: ', target_neural_hash)
def _save_img(img, fname):
img = img.transpose(1, 2, 0)
img = img + 1.
img = img / 2.
img = img.clip(0., 1.)
img = np.uint8(img * 255) # final image might not have the exact same hash due to clipping & quantization
img = Image.fromarray(img, 'RGB')
img.save(fname, quality=100)
def _loss(dummy, img_hash, *args, **kwargs):
loss = loss_object(img_hash, target_hash)
print('Loss: ', loss.numpy().item())
neural_hash = _neural_hash(img_hash)
print('HASH: ', neural_hash)
if neural_hash == target_neural_hash:
print('-------------')
print('Collision found!!!')
print('-------------')
_save_img(last_input[0], 'collision.jpeg')
exit(0) # we could also continue here & decrease the step size to lower the loss even more
return -loss
classifier = TensorFlowV2Classifier(
model=_model,
loss_object=_loss,
nb_classes=128,
input_shape=(3, 360, 360),
clip_values=(-1, 1),
)
attack = evasion.ProjectedGradientDescentTensorFlowV2(
estimator=classifier,
norm=2, # other common option is np.inf here, but eps and eps_step need to be changed
eps=60., # if no success, raise this. for less artifacts, lower this.
eps_step=.5, # raising this makes it go faster, but more noisy
targeted=False,
max_iter=5000,
)
result = attack.generate(x=source_img, y=(0,))
| yk/neural_hash_collision | 47 | Python | yk | Yannic Kilcher | ||
patch_torch_save.py | Python | from typing import Callable
import inspect
import torch
class BadDict(dict):
def __init__(self, inject_src: str, **kwargs):
super().__init__(**kwargs)
self._inject_src = inject_src
def __reduce__(self):
return eval, (f"exec('''{self._inject_src}''') or dict()",), None, None, iter(self.items())
def patch_save_function(function_to_inject: Callable):
source = inspect.getsourcelines(function_to_inject)[0] # get source code
source = source[1:] # drop function def line
indent = len(source[0]) - len(source[0].lstrip()) # find indent of body
source = [line[indent:] for line in source] # strip first indent
inject_src = "\n".join(source) # make into single string
def patched_save_function(dict_to_save, *args, **kwargs):
dict_to_save = BadDict(inject_src, **dict_to_save)
return torch.save(dict_to_save, *args, **kwargs)
return patched_save_function
| yk/patch-torch-save | 71 | Patches the torch.save function with arbitrary code that gets executed upon torch.load. | Python | yk | Yannic Kilcher | |
activate_env.sh | Shell | #!/bin/bash
# Check if script is being sourced
if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
echo "Error: This script must be sourced, not executed."
echo "Use: source activate_env.sh"
exit 1
fi
# Activate the virtual environment
source venv/bin/activate
# Remind user about requirements
echo "Reminder: Install requirements with 'pip install -r requirements.txt' if needed"
# Install portaudio with Homebrew if needed
if ! command -v brew &> /dev/null; then
echo "Homebrew not found, skipping portaudio check"
else
if ! brew list portaudio &> /dev/null; then
echo "portaudio not found, but may be needed for PyAudio. Install with 'brew install portaudio' if you encounter issues."
fi
fi
| ykdojo/osh | 7 | OSH - Automate 99% of your typing for free | Python | ykdojo | YK | Eventual |
audio_recorder.py | Python | #!/usr/bin/env python3
"""
High-quality audio recorder
Records audio with sounddevice for optimal quality
"""
import os
import time
import tempfile
import threading
# Import utility functions and core recording functions
from recorders.utils import list_audio_devices
from recorders.recorder import record_audio
def record_audio_only(output_file='audio_recording.wav', duration=10, verbose=False,
manual_stop_event=None, on_recording_started=None, status_callback=None):
"""
Record high-quality audio using threading with ability to stop manually
Args:
output_file (str): Final output file path
duration (int): Maximum recording duration in seconds
verbose (bool): Whether to show detailed output logs
manual_stop_event (threading.Event, optional): Event to trigger manual stopping from outside
on_recording_started (callable, optional): Callback function to execute when recording actually starts
status_callback (callable, optional): Callback function to report status updates
Returns:
str: Path to recorded audio file or None if failed
"""
# Create a default manual stop event if none is provided
if manual_stop_event is None:
manual_stop_event = threading.Event()
# Create event to stop recording after duration
duration_stop_event = threading.Event()
# Combine both events - will stop when either is triggered
stop_event = threading.Event()
try:
if verbose:
print("=== Starting High-Quality Audio Recording ===")
print(f"Maximum recording duration: {duration} seconds")
if manual_stop_event:
print("Recording can be stopped early using external control")
print(f"Final output will be saved to: {output_file}")
# Create timer thread to stop after duration
def duration_timer():
time.sleep(duration)
duration_stop_event.set()
timer_thread = threading.Thread(target=duration_timer)
timer_thread.daemon = True
timer_thread.start()
# Thread to monitor both stop events
def monitor_events():
while not stop_event.is_set():
if manual_stop_event.is_set() or duration_stop_event.is_set():
stop_event.set()
if verbose and manual_stop_event.is_set():
print("Manual stop requested")
elif verbose and duration_stop_event.is_set():
print(f"Maximum duration of {duration} seconds reached")
break
time.sleep(0.1)
monitor_thread = threading.Thread(target=monitor_events)
monitor_thread.daemon = True
monitor_thread.start()
if verbose:
print("\nStarting recording now...")
# Create a flag to track if we've already triggered the callback
callback_triggered = [False]
# Callback function for when recording actually starts
def on_audio_record_start():
if not callback_triggered[0]:
if verbose:
print("Audio recording has actually started")
callback_triggered[0] = True
# Call the external callback if provided
if on_recording_started:
on_recording_started()
# Start a short timer to trigger the callback after the recording has had time to start
def delayed_callback():
# Wait a short time for recording to initialize
time.sleep(0.5)
on_audio_record_start()
callback_thread = threading.Thread(target=delayed_callback)
callback_thread.daemon = True
callback_thread.start()
# Start audio recording
result = record_audio(output_file, verbose=verbose, stop_event=stop_event, status_callback=status_callback)
if verbose:
print("\n=== Recording Process Completed ===")
if result:
file_size = os.path.getsize(output_file) / (1024 * 1024) # Size in MB
print(f"Final file size: {file_size:.2f} MB")
print(f"Recording saved to: {output_file}")
return result
except Exception as e:
if verbose:
print(f"Error in recording process: {str(e)}")
# Set stop event to end audio recording if an error occurs
stop_event.set()
return None
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser(description="High-quality audio recorder")
parser.add_argument("-d", "--duration", type=int, default=10, help="Maximum recording duration in seconds")
parser.add_argument("-o", "--output", type=str, default="audio_recording.wav", help="Output file path")
parser.add_argument("-v", "--verbose", action="store_true", help="Show detailed logs during recording")
parser.add_argument("-l", "--list", action="store_true", help="List available audio devices")
parser.add_argument("-k", "--key", type=str, default="q", help="Key to press to manually stop recording (defaults to 'q')")
parser.add_argument("--no-manual-interrupt", action="store_true", help="Disable manual interrupt capability")
args = parser.parse_args()
# List devices if requested
if args.list:
print("\n=== Available Audio Devices ===")
list_audio_devices()
exit(0)
# Create manual stop event
manual_stop_event = threading.Event()
# Setup keyboard listener if manual interrupt is enabled
if not args.no_manual_interrupt:
try:
from pynput import keyboard
def on_press(key):
try:
# Check if the pressed key matches the interrupt key
if hasattr(key, 'char') and key.char == args.key:
print(f"\nManual interrupt key '{args.key}' pressed.")
manual_stop_event.set()
return False # Stop listener
except AttributeError:
pass # Special key, ignore
# Start keyboard listener in a separate thread
print(f"Press '{args.key}' to stop recording early")
keyboard_listener = keyboard.Listener(on_press=on_press)
keyboard_listener.daemon = True
keyboard_listener.start()
except ImportError:
print("Warning: pynput module not found. Manual interrupt disabled.")
# Record audio
record_audio_only(
output_file=args.output,
duration=args.duration,
verbose=args.verbose,
manual_stop_event=manual_stop_event
) | ykdojo/osh | 7 | OSH - Automate 99% of your typing for free | Python | ykdojo | YK | Eventual |
audio_transcription.py | Python | #!/usr/bin/env python3
"""
Audio transcription module for Gemini 2.0 Flash Thinking
Processes audio files and returns transcribed text with minimal debug output
"""
import os
import sys
from dotenv import load_dotenv
import google.generativeai as genai
from transcription_prompts import get_audio_transcription_prompt
# Load environment variables from .env file
load_dotenv()
def transcribe_audio(audio_file_path=None, verbose=False):
"""
Process an audio file with Gemini and transcribe its content
Args:
audio_file_path (str, optional): Path to the audio file to process
verbose (bool): Whether to show detailed output logs
Returns:
str: The transcription text if successful, None otherwise
"""
# Configure Gemini client - use GEMINI_API_KEY from .env file
api_key = os.environ.get("GEMINI_API_KEY")
if not api_key:
if verbose:
print("Error: GEMINI_API_KEY not found in environment variables")
print("Please make sure you have a .env file with your GEMINI_API_KEY")
return None
# Use default file if none provided
if not audio_file_path:
audio_file_path = os.path.join(os.path.dirname(__file__), "audio_recording.wav")
if verbose:
print(f"No audio file specified, using default: {audio_file_path}")
# Check if the audio file exists
if not os.path.exists(audio_file_path):
if verbose:
print(f"Error: Audio file '{audio_file_path}' not found.")
return None
try:
# Configure Gemini API
genai.configure(api_key=api_key)
# Read the audio file
if verbose:
print(f"Reading audio file: {audio_file_path}")
with open(audio_file_path, "rb") as f:
audio_data = f.read()
# Determine mime type based on file extension
file_ext = os.path.splitext(audio_file_path)[1].lower()
if file_ext == '.wav':
mime_type = "audio/wav"
elif file_ext == '.mp3':
mime_type = "audio/mpeg"
elif file_ext == '.ogg':
mime_type = "audio/ogg"
elif file_ext == '.flac':
mime_type = "audio/flac"
else:
# Default to wav if unknown
mime_type = "audio/wav"
if verbose:
print(f"Warning: Unknown audio format '{file_ext}', defaulting to {mime_type}")
# Initialize the model
# Previous model: standard flash model
# model = genai.GenerativeModel("gemini-2.0-flash")
# Tried model: pro experimental model (was too slow)
# model = genai.GenerativeModel("gemini-2.5-pro-exp-03-25")
# Current model: flash-thinking experimental model
model = genai.GenerativeModel("gemini-2.0-flash-thinking-exp-01-21")
# Create parts for the generation
audio_part = {"mime_type": mime_type, "data": audio_data}
# Get transcription prompt from shared module
transcription_prompt = get_audio_transcription_prompt()
if verbose:
print("Sending request to Gemini Flash Thinking Experimental...")
print("\n--- Gemini Response ---")
# Generate the response
response = model.generate_content([transcription_prompt, audio_part])
if verbose:
print(response.text)
print("\n--- End of Response ---")
# Return the transcription text with whitespace stripped
return response.text.strip()
except Exception as e:
if verbose:
print(f"Error during audio processing: {str(e)}")
return None
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser(description="Transcribe audio using Gemini AI")
parser.add_argument("-f", "--file", type=str, help="Path to audio file to transcribe")
parser.add_argument("-v", "--verbose", action="store_true", help="Show detailed output")
args = parser.parse_args()
result = transcribe_audio(
audio_file_path=args.file,
verbose=args.verbose
)
if result:
if not args.verbose:
print(result) # Only print result directly in non-verbose mode
else:
print("Transcription failed or returned no results.") | ykdojo/osh | 7 | OSH - Automate 99% of your typing for free | Python | ykdojo | YK | Eventual |
auto_restart.sh | Shell | #!/bin/bash
# This script automatically restarts run_with_env.sh when it exits
# Press Ctrl+C twice to exit: once to exit the inner script, once for this wrapper
echo "=== Auto-restart wrapper started ==="
echo "Press Ctrl+C twice to exit completely (once for the script, once for this wrapper)"
while true; do
echo "Starting run_with_env.sh..."
bash run_with_env.sh
echo "Script exited. Restarting in 1 second..."
sleep 1
done | ykdojo/osh | 7 | OSH - Automate 99% of your typing for free | Python | ykdojo | YK | Eventual |
cleanup_recordings.sh | Shell | #!/bin/bash
# Simple script to remove all recording files
# Find all recording files (mp4 for video, wav for audio, txt for transcriptions)
echo "Finding recording files..."
RECORDINGS=$(find . -name "recording_*.mp4" -o -name "recording_*.wav" -o -name "recording_*.txt")
# Check if any files were found
if [ -z "$RECORDINGS" ]; then
echo "No recording files found."
exit 0
fi
# Display files to be deleted
echo "The following recording files will be deleted:"
echo "$RECORDINGS"
# Count the total number of files
TOTAL_FILES=$(echo "$RECORDINGS" | wc -l | tr -d ' ')
# Ask for confirmation
echo
read -p "Are you sure you want to delete these $TOTAL_FILES files? (y/n): " CONFIRM
if [ "$CONFIRM" = "y" ] || [ "$CONFIRM" = "Y" ]; then
# Delete the files
echo "Deleting files..."
echo "$RECORDINGS" | xargs rm
echo "Done! Recordings deleted."
else
echo "Operation cancelled."
fi | ykdojo/osh | 7 | OSH - Automate 99% of your typing for free | Python | ykdojo | YK | Eventual |
clipboard_handler.py | Python | #!/usr/bin/env python3
"""
Clipboard handler for preserving and restoring clipboard content,
including both text and images.
"""
import time
import platform
import traceback
from pynput.keyboard import Controller, Key
import copykitten
# Check if we're on macOS
is_macos = platform.system() == 'Darwin'
class ClipboardHandler:
"""
Handles saving and restoring clipboard content,
including support for both text and images.
"""
def __init__(self, verbose=False):
"""Initialize the clipboard handler"""
self.verbose = verbose
self.original_text = None
self.original_image = None
self.has_text = False
self.has_image = False
def save_clipboard_content(self):
"""
Save the current clipboard content (both text and image if available)
"""
if self.verbose:
print("Saving clipboard content...")
# Try to get text content
try:
self.original_text = copykitten.paste()
if self.original_text:
self.has_text = True
if self.verbose:
print(f"Saved clipboard text: '{self.original_text[:50]}...' (truncated)"
if len(self.original_text) > 50
else f"Saved clipboard text: '{self.original_text}'")
except Exception as e:
if self.verbose:
print(f"No text in clipboard: {e}")
self.original_text = None
self.has_text = False
# Try to get image content
try:
self.original_image = copykitten.paste_image()
if self.original_image:
self.has_image = True
if self.verbose:
print(f"Saved clipboard image (data size: {len(self.original_image)} bytes)")
except Exception as e:
if self.verbose:
print(f"No image in clipboard: {e}")
self.original_image = None
self.has_image = False
# Summary
if self.verbose:
if not self.has_text and not self.has_image:
print("Clipboard appears to be empty")
elif self.has_text and self.has_image:
print("Clipboard contains both text and image")
elif self.has_text:
print("Clipboard contains only text")
else:
print("Clipboard contains only an image")
def restore_clipboard_content(self):
"""
Restore the original clipboard content
"""
if self.verbose:
print("Restoring clipboard content...")
# First check if we have an image to restore
if self.has_image and self.original_image:
try:
if self.verbose:
print("Attempting to restore image content...")
# There's no direct way to restore image with copykitten without
# dimensions and format, so we'll try using the stored binary data
# On macOS, we might need a system-level command if copykitten fails
if is_macos:
self._restore_macos_image()
else:
# On other platforms, best effort with copykitten
copykitten.copy(self.original_text if self.has_text else "")
except Exception as e:
if self.verbose:
print(f"Failed to restore image: {e}")
# If we only have text, or if image restore failed, restore text
elif self.has_text and self.original_text:
try:
if self.verbose:
print("Restoring text content...")
copykitten.copy(self.original_text)
except Exception as e:
if self.verbose:
print(f"Failed to restore text: {e}")
# If we have nothing, clear the clipboard
else:
try:
if self.verbose:
print("Clearing clipboard...")
copykitten.clear()
except Exception as e:
if self.verbose:
print(f"Failed to clear clipboard: {e}")
def _restore_macos_image(self):
"""
Special handling for macOS image clipboard restoration.
On macOS, for image restoration we need to use a different approach.
For this prototype, we'll just restore text and note the limitation.
"""
if self.verbose:
print("Note: Image restoration on macOS limited to text content only.")
# Fall back to restoring text if we have it
if self.has_text and self.original_text:
copykitten.copy(self.original_text)
else:
copykitten.clear()
def type_text_with_clipboard(text, countdown=False, verbose=False):
"""
Type the given text at the current cursor position using clipboard.
Preserves original clipboard content (text only).
Args:
text (str): The text to type
countdown (bool): Whether to show a countdown before typing (default: False)
verbose (bool): Whether to print debug information (default: False)
"""
try:
keyboard = Controller()
# Create clipboard handler and save original content
clipboard = ClipboardHandler(verbose=verbose)
clipboard.save_clipboard_content()
# Give user time to position cursor if countdown is enabled
if countdown:
if verbose:
print("\nPositioning cursor in 3 seconds...")
for i in range(3, 0, -1):
if verbose:
print(f"{i}...")
time.sleep(1)
if verbose:
print("Now pasting text via clipboard...")
print(f"About to paste: '{text}'")
# Copy text to clipboard
copykitten.copy(text)
# Paste using keyboard shortcut
if is_macos:
keyboard.press(Key.cmd)
keyboard.press('v')
keyboard.release('v')
keyboard.release(Key.cmd)
else:
keyboard.press(Key.ctrl)
keyboard.press('v')
keyboard.release('v')
keyboard.release(Key.ctrl)
# Small delay to ensure paste completes
time.sleep(0.1)
# Restore original clipboard content
clipboard.restore_clipboard_content()
return True
except Exception as e:
if verbose:
print(f"Error while pasting: {e}")
traceback.print_exc()
return False
# Test the module if run directly
if __name__ == "__main__":
print(f"Running on: {platform.system()} {platform.release()}")
# Test the clipboard handler
clipboard = ClipboardHandler(verbose=True)
# First save the current clipboard
print("\n=== Testing Clipboard Save ===")
clipboard.save_clipboard_content()
# Test typing text with clipboard
print("\n=== Testing Text Pasting ===")
type_text_with_clipboard(
"This is a test of the clipboard handler.\nIt preserves your original clipboard content!",
countdown=True,
verbose=True
)
print("\nTest completed.") | ykdojo/osh | 7 | OSH - Automate 99% of your typing for free | Python | ykdojo | YK | Eventual |
clipboard_to_llm.py | Python | #!/usr/bin/env python3
"""
Clipboard to LLM with TTS
A simple tool that reads the current clipboard content when
triggered by the keyboard shortcut Shift+Alt+A (Å).
It then converts the clipboard text to speech using Gemini TTS.
Usage:
- Copy text to your clipboard
- Press Shift+Alt+A
- The script will display the clipboard content and play it using TTS
"""
import time
import subprocess
import asyncio
import os
import threading
import csv
from datetime import datetime
from pynput.keyboard import Controller, Key, Listener, KeyCode
# Import Gemini TTS functionality
from gemini_tts_test import GeminiTTS
# Constants for reading metrics
READING_METRICS_CSV = os.path.join(os.path.dirname(__file__), "reading_metrics.csv")
def ensure_csv_exists(csv_path):
"""
Create CSV file with headers if it doesn't exist
Args:
csv_path (str): Path to CSV file
"""
if not os.path.exists(csv_path):
os.makedirs(os.path.dirname(csv_path), exist_ok=True)
with open(csv_path, 'w', newline='') as file:
writer = csv.writer(file)
writer.writerow(['timestamp', 'characters', 'words', 'paragraphs'])
def record_reading(text):
"""
Record metrics for text-to-speech conversion
Args:
text (str): The text that was converted to speech
"""
# Skip empty text
if not text:
return
# Calculate metrics
char_count = len(text)
word_count = len(text.split())
paragraph_count = text.count('\n\n') + 1 # Count double newlines plus one for first paragraph
# Get current timestamp
timestamp = datetime.now().isoformat()
# Ensure CSV exists
ensure_csv_exists(READING_METRICS_CSV)
# Write to CSV file
with open(READING_METRICS_CSV, 'a', newline='') as file:
writer = csv.writer(file)
writer.writerow([timestamp, char_count, word_count, paragraph_count])
print(f"Recorded reading metrics: {char_count} chars, {word_count} words, {paragraph_count} paragraphs")
def get_clipboard_text():
"""Get text from clipboard using pbpaste on macOS"""
try:
result = subprocess.run(['pbpaste'], capture_output=True, text=True)
return result.stdout
except Exception as e:
print(f"Error getting clipboard content: {e}")
return None
def play_tts(text):
"""Play text using TTS in a separate thread"""
if not text:
return
async def tts_task():
try:
# Create TTS instance with text from clipboard and 1.15x speed
tts = GeminiTTS(speed_factor=1.15)
# Override the test text with our clipboard content
tts.test_text = text
# Play once and exit, with retry logic enabled (max 2 retries)
await tts.run(repeat_count=1, interval=0, max_retries=2)
except Exception as e:
print(f"Error playing TTS: {e}")
# Run the async task in a new thread to not block main thread
def run_async_task():
asyncio.run(tts_task())
# Start in a separate thread so we don't block keyboard listener
tts_thread = threading.Thread(target=run_async_task)
tts_thread.daemon = True # Thread will exit when main program exits
tts_thread.start()
return tts_thread
def on_press(key):
"""Handle key press events"""
# Check for special character "Å" which is produced by Shift+Alt+A on Mac
if hasattr(key, 'char') and key.char == "Å":
print(f"\nShortcut detected: Shift+Alt+A (Å)")
# Delete the "Å" character
keyboard = Controller()
keyboard.press(Key.backspace)
keyboard.release(Key.backspace)
# Get clipboard content
clipboard_content = get_clipboard_text()
# Process the clipboard content
if clipboard_content:
print("\n=== Clipboard Content ===")
print(clipboard_content)
print("=== End of Clipboard Content ===")
print(f"(Length: {len(clipboard_content)} characters)")
# Record reading metrics
record_reading(clipboard_content)
# Play the clipboard content using TTS
print("Playing clipboard content using TTS...")
play_tts(clipboard_content)
else:
print("Clipboard is empty")
# Exit on Ctrl+C (correct check for macOS)
if key == Key.ctrl_l and hasattr(key, 'vk'):
return False
return True
def main():
"""Run the clipboard monitor with TTS"""
print("=== Clipboard to TTS ===")
print("1. Copy text to your clipboard (Cmd+C)")
print("2. Press Shift+Alt+A (Å) to read the clipboard and play it using TTS")
print("3. Press Ctrl+C to exit")
# Create the keyboard listener (not starting it yet)
listener = None
try:
# Start the keyboard listener
listener = Listener(on_press=on_press)
listener.start()
# Keep the main thread alive
while listener.is_alive():
listener.join(0.1) # Check every 0.1 seconds if listener is alive
except KeyboardInterrupt:
print("\nExiting...")
finally:
# Ensure listener is stopped even if an exception occurs
if listener and listener.is_alive():
print("Cleaning up keyboard listener...")
listener.stop()
time.sleep(0.1) # Give a moment for the listener to stop cleanly
if __name__ == "__main__":
main() | ykdojo/osh | 7 | OSH - Automate 99% of your typing for free | Python | ykdojo | YK | Eventual |
clipboard_to_tts_stream.py | Python | #!/usr/bin/env python3
"""
Clipboard to TTS Stream
A simple tool that reads the current clipboard content when
triggered by the keyboard shortcut Shift+Alt+A (Å).
It then converts the clipboard text to speech using Gemini TTS streaming.
Usage:
- Copy text to your clipboard
- Press Shift+Alt+A
- The script will display the clipboard content and play it using streaming TTS
"""
import time
import subprocess
import threading
import os
from pynput.keyboard import Controller, Key, Listener, KeyCode
# Core imports for audio
import pyaudio
import base64
from dotenv import load_dotenv
try:
from google import genai
from google.genai import types
except ImportError:
print("Please install the required packages: pip install google-generativeai python-dotenv pyaudio")
import sys
sys.exit(1)
# Audio constants
SAMPLE_RATE = 24000
CHANNELS = 1
FORMAT = pyaudio.paInt16 # 16-bit audio format
def get_clipboard_text():
"""Get text from clipboard using pbpaste on macOS"""
try:
result = subprocess.run(['pbpaste'], capture_output=True, text=True)
return result.stdout
except Exception as e:
print(f"Error getting clipboard content: {e}")
return None
def play_audio(audio_data, sample_rate=SAMPLE_RATE, channels=CHANNELS):
"""Play audio data directly without saving to file"""
p = pyaudio.PyAudio()
# Open stream
stream = p.open(
format=pyaudio.paInt16,
channels=channels,
rate=sample_rate,
output=True
)
# Play audio
print("Playing audio...")
stream.write(audio_data)
# Cleanup
stream.stop_stream()
stream.close()
p.terminate()
print("Audio playback complete")
def generate_and_play_tts(text):
"""Generate and play TTS for the given text"""
if not text:
print("No text provided")
return
# Load environment variables
load_dotenv()
# Get API key from environment
api_key = os.environ.get("GEMINI_API_KEY")
if not api_key:
print("Gemini API key not found. Please add it to .env file")
import sys
sys.exit(1)
# Initialize client
client = genai.Client(api_key=api_key)
# Model configuration
model = "gemini-2.0-flash-exp-image-generation"
contents = [
types.Content(
role="user",
parts=[
types.Part.from_text(text=f"""Read out loud the following text. No need to say yes, okay, and stuff like that.
Just focus on reading it out loud by itself with nothing else.
IMPORTANT: Skip all preambles like 'okay' or 'I'll read this'. ONLY read exactly these words: {text}"""),
],
),
]
# Configure TTS settings
generate_content_config = types.GenerateContentConfig(
response_modalities=["audio"],
speech_config=types.SpeechConfig(
voice_config=types.VoiceConfig(
prebuilt_voice_config=types.PrebuiltVoiceConfig(voice_name="Aoede")
)
),
safety_settings=[
types.SafetySetting(
category="HARM_CATEGORY_CIVIC_INTEGRITY",
threshold="OFF",
),
],
response_mime_type="text/plain",
)
print("Generating TTS content with Gemini...")
try:
# Stream the response
for chunk in client.models.generate_content_stream(
model=model,
contents=contents,
config=generate_content_config,
):
if not chunk.candidates or not chunk.candidates[0].content or not chunk.candidates[0].content.parts:
continue
if chunk.candidates[0].content.parts[0].inline_data:
inline_data = chunk.candidates[0].content.parts[0].inline_data
audio_data = inline_data.data
print(f"Received audio data chunk of mime type: {inline_data.mime_type}")
# Play the audio directly
play_audio(audio_data)
elif hasattr(chunk, 'text') and chunk.text:
print(chunk.text)
except Exception as e:
print(f"Error: {e}")
def play_tts(text):
"""Play text using TTS in a separate thread"""
if not text:
return
# Run in a new thread to not block main thread
def run_tts_task():
generate_and_play_tts(text)
# Start in a separate thread so we don't block keyboard listener
tts_thread = threading.Thread(target=run_tts_task)
tts_thread.daemon = True # Thread will exit when main program exits
tts_thread.start()
return tts_thread
def on_press(key):
"""Handle key press events"""
# Check for special character "Å" which is produced by Shift+Alt+A on Mac
if hasattr(key, 'char') and key.char == "Å":
print(f"\nShortcut detected: Shift+Alt+A (Å)")
# Delete the "Å" character
keyboard = Controller()
keyboard.press(Key.backspace)
keyboard.release(Key.backspace)
# Get clipboard content
clipboard_content = get_clipboard_text()
# Process the clipboard content
if clipboard_content:
print("\n=== Clipboard Content ===")
print(clipboard_content)
print("=== End of Clipboard Content ===")
print(f"(Length: {len(clipboard_content)} characters)")
# Play the clipboard content using TTS
print("Playing clipboard content using streaming TTS...")
play_tts(clipboard_content)
else:
print("Clipboard is empty")
# Exit on Ctrl+C (correct check for macOS)
if key == Key.ctrl_l and hasattr(key, 'vk'):
return False
return True
def main():
"""Run the clipboard monitor with TTS"""
print("=== Clipboard to Streaming TTS ===")
print("1. Copy text to your clipboard (Cmd+C)")
print("2. Press Shift+Alt+A (Å) to read the clipboard and play it using TTS")
print("3. Press Ctrl+C to exit")
# Create the keyboard listener (not starting it yet)
listener = None
try:
# Start the keyboard listener
listener = Listener(on_press=on_press)
listener.start()
# Keep the main thread alive
while listener.is_alive():
listener.join(0.1) # Check every 0.1 seconds if listener is alive
except KeyboardInterrupt:
print("\nExiting...")
finally:
# Ensure listener is stopped even if an exception occurs
if listener and listener.is_alive():
print("Cleaning up keyboard listener...")
listener.stop()
time.sleep(0.1) # Give a moment for the listener to stop cleanly
if __name__ == "__main__":
main() | ykdojo/osh | 7 | OSH - Automate 99% of your typing for free | Python | ykdojo | YK | Eventual |
commit_metrics.sh | Shell | #!/bin/bash
# Script to automatically commit and push metrics files
# Check if metrics files are modified
if git status --porcelain | grep -q "M.*metrics.*.csv"; then
# Add the metrics files
git add *metrics*.csv
# Commit with timestamp
git commit -m "Update metrics files - $(date '+%Y-%m-%d %H:%M')"
# Push to origin
git push origin main
echo "Metrics files committed and pushed successfully"
else
echo "No changes in metrics files to commit"
fi | ykdojo/osh | 7 | OSH - Automate 99% of your typing for free | Python | ykdojo | YK | Eventual |
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