Daniel Chang mwdchang

find . -not ( -name node_modules -prune ) | xargs wc

pip install torch torchvision torchaudio

pip install jupyterlab

pip install numpy scipy scikit-learn

pip install tqdm matplotlib pandas

pip install torch-scatter torch-sparse torch-cluster torch-spline-conv torch-geometric -f https://data.pyg.org/whl/torch-1.11.0+cpu.html

	<html>
	<head>
	<script src="https://cdnjs.cloudflare.com/ajax/libs/matter-js/0.18.0/matter.min.js" integrity="sha512-5T245ZTH0m0RfONiFm2NF0zcYcmAuNzcGyPSQ18j8Bs5Pbfhp5HP1hosrR8XRt5M3kSRqzjNMYpm2+it/AUX/g==" crossorigin="anonymous" referrerpolicy="no-referrer"></script>
	<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/7.8.0/d3.min.js" integrity="sha512-jXsLjbg/Pr8F5U2evjFaEci7mImlUix865lbvnNmp5TzS86+VTTFVDz7FFTS6VHdhSn7UJ4tjZdvpp0GgT0fZA==" crossorigin="anonymous" referrerpolicy="no-referrer"></script>
	</head>
	<body>
	<svg id="svg" style="width: 100%; height: 100%"></svg>
	</body>

	<script>

	# https://github.com/andferrari/julia_notebook
	FROM "jupyter/minimal-notebook"

	USER root

	ENV JULIA_VERSION=1.7.3

	RUN mkdir /opt/julia-${JULIA_VERSION} && \
	cd /tmp && \
	wget -q https://julialang-s3.julialang.org/bin/linux/x64/`echo ${JULIA_VERSION} \| cut -d. -f 1,2`/julia-${JULIA_VERSION}-linux-x86_64.tar.gz && \

	<html>
	<head>
	</head>
	<body>
	</body>
	<script type="module">
	import { loadImage, hatchFilter } from 'https://cdn.jsdelivr.net/gh/mwdchang/image-util/dist/index.js';

	const createCanvas = (img) => {
	const canvas = document.createElement('canvas');

	#!/usr/bin/env bash
	DIR=dist

	git checkout --orphan gh-pages
	npm run build
	git --work-tree $DIR add --all
	git --work-tree $DIR commit -m "gh-pages"
	git push origin HEAD:gh-pages --force
	rm -rf $DIR
	git checkout -f master

	class Heap {
	constructor(maxsize) {
	this.size = 0;
	this.maxsize = maxsize;
	this.data = [this.maxsize + 1];
	}

	getParent(index) { return Math.round( index / 2); }
	getLeftChild(index) { return 2 * index; }
	getRightChild(index) { return 2 * index + 1; }

	{
	"name": "jslib-test",
	"version": "1.0.0",
	"description": "Testing library packaging",
	"main": "dist/cjs/main.js",
	"module": "dist/esm/index.js",
	"scripts": {
	"build": "rollup -c",
	"dev": "rollup -c -w"
	},

	import tensorflow as tf
	import numpy as np
	import matplotlib.pyplot as plt
	import random

	from tensorflow.examples.tutorials.mnist import input_data
	mnist = input_data.read_data_sets("./MNIST/", one_hot=True)

	tf.reset_default_graph()