karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

patriciogonzalezvivo

Please consider using http://lygia.xyz instead of copy/pasting this functions. It expand suport for voronoi, voronoise, fbm, noise, worley, noise, derivatives and much more, through simple file dependencies. Take a look to https://github.com/patriciogonzalezvivo/lygia/tree/main/generative

Generic 1,2,3 Noise

float rand(float n){return fract(sin(n) * 43758.5453123);}

float noise(float p){
	float fl = floor(p);
  float fc = fract(p);

yrevar

{0: 'tench, Tinca tinca',
 1: 'goldfish, Carassius auratus',
 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',
 3: 'tiger shark, Galeocerdo cuvieri',
 4: 'hammerhead, hammerhead shark',
 5: 'electric ray, crampfish, numbfish, torpedo',
 6: 'stingray',
 7: 'cock',
 8: 'hen',
 9: 'ostrich, Struthio camelus',

gre

/*
 * This work is free. You can redistribute it and/or modify it under the
 * terms of the Do What The Fuck You Want To Public License, Version 2,
 * as published by Sam Hocevar. See the COPYING file for more details.
 */
/*
 * Easing Functions - inspired from http://gizma.com/easing/
 * only considering the t value for the range [0, 1] => [0, 1]
 */
EasingFunctions = {

prologic

Learn Go in ~5mins

This is inspired by A half-hour to learn Rust and Zig in 30 minutes.

Basics

Your first Go program as a classical "Hello World" is pretty simple:

First we create a workspace for our project:

aparrish

karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

marktheunissen

This playbook has been removed as it is now very outdated.

maxim

#!/usr/bin/env bash
#
# gh-dl-release! It works!
# 
# This script downloads an asset from latest or specific Github release of a
# private repo. Feel free to extract more of the variables into command line
# parameters.
#
# PREREQUISITES
#

ddevault

WAYLAND_PROTOCOLS=/usr/share/wayland-protocols

# wayland-scanner is a tool which generates C headers and rigging for Wayland
# protocols, which are specified in XML. wlroots requires you to rig these up
# to your build system yourself and provide them in the include path.
xdg-shell-protocol.h:
	wayland-scanner server-header \
		$(WAYLAND_PROTOCOLS)/stable/xdg-shell/xdg-shell.xml $@

xdg-shell-protocol.c: xdg-shell-protocol.h