Skip to content

Instantly share code, notes, and snippets.

View mrm8488's full-sized avatar
🏠
Working from home

Manuel Romero mrm8488

🏠
Working from home
277 followers · 58 following
View GitHub Profile
@mrm8488
mrm8488 / promise-all-no-array-destructors.js
Created June 6, 2016 18:04
const getUserInfo = () => new Promise((resolve, reject) => {
process.nextTick(() => resolve({
id: 1,
name: 'Manuel',
surname: 'Romero'
}));
});
@mrm8488
mrm8488 / promise-all-array-destructors.js
Last active June 6, 2016 19:50
const getUserInfo = () => new Promise((resolve, reject) => {
process.nextTick(() => resolve({
id: 1,
name: 'Manuel',
surname: 'Romero'
}));
});
@mrm8488
mrm8488 / from_callbacks_to_util.promisify().js
Last active March 21, 2019 19:25
Here we can see how Node.js 8 allow us to promisify I/O functions that return callbacks (without 3pp modules such as Q or Bluebird)
/* AUTHOR: mrm8488@gmail.com */
/* Node.js v8 */
const fs = require('fs');
/* BEFORE util.promisify() */
fs.writeFile('/tmp/test.js',"console.log('Hello world');", error => {
if(error) return console.log(error);
@mrm8488
mrm8488 / README.md
Created October 24, 2019 01:09 — forked from notwaldorf/README.md
ServiceWorker code to cache Tensorflow model shards.

ServiceWorker code to cache TensorFlow model shards.

One of the problems I have when testing giant TensorFlow models in TensorFlow.js is that they're huge (like 500 MB) and they take forever to download, every time I refresh the page. This is how I setup my ServiceWorker code so that at least in testing I only have to download the model once, and then it's saved in the cache for the next time.

@mrm8488
mrm8488 / random_log_color.sh
Created November 8, 2019 05:43
tail -F firewall.log |while
read -r line;do printf
"\033[38;5;%dm%s\033[0m\n" $
((SRANDOM%255)) "Sline";done #
Random color per log line.
@mrm8488
mrm8488 / TF_HW_Engine.py
Created November 19, 2019 01:27
# Detect hardware
try:
tpu = tf.distribute.cluster_resolver.TPUClusterResolver() # TPU detection
except ValueError:
tpu = None
gpus = tf.config.experimental.list_logical_devices("GPU")
# Select appropriate distribution strategy
if tpu:
tf.config.experimental_connect_to_cluster(tpu)
@mrm8488
mrm8488 / nodejs_readline.js
Created December 21, 2019 01:34
// Node.js readline & async iteration:
const fs = require('fs");
const {createlnterface: ci} =
require('readline’);
async function logLines(ls) {
for await (const l of ls) {
console.log('>"' + l);
@mrm8488
mrm8488 / matrix_effect.html
Created December 22, 2019 00:23
<html>
<head>
<style>
body {
margin: 0;
height: 100vh;
width: 100vw;
}
</style>
@mrm8488
mrm8488 / an-inquiry-into-matplotlib-figures.ipynb
Created December 23, 2019 20:55 — forked from akashpalrecha/an-inquiry-into-matplotlib-figures.ipynb
This notebook dives deep into Matplotlib's Figures, Axes, subplots and the very amazing GridSpec!
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
@mrm8488
mrm8488 / vector_matrix.js
Created January 3, 2020 21:49
Create a vector and a matrix in JS
const array = (size,value = 0) => Array(size).fill(value);
let a = array(n);
const matrix = (rows,cols,value = 0) => Array(rows).fill(Array(cols).fill(value));
let m = matrix(r,c);