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// ==UserScript== | |
// @name HackerNews GPT-Free Feed | |
// @namespace http://tampermonkey.net/ | |
// @version 0.1 | |
// @description Hides any Hacker News story with "GPT" in its title. | |
// @author Taylor Troesh | |
// @include https://news.ycombinator.com/* | |
// @grant none | |
// ==/UserScript== |
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// user: Either<string, { name: string, age: number }> | |
const user = doEither(function*() { | |
// name: string | |
const name = yield* Right("test") | |
// age: number | |
const age = Math.random() > 0.5 ? yield* Right(100) : yield* Left("oopsies") | |
return { | |
name, | |
age | |
} |
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using System; | |
using System.Collections.Generic; | |
using System.Linq; | |
public class Value | |
{ | |
public double Data { get; set; } | |
public double Gradient { get; set; } | |
private Action _backward; | |
private readonly List<Value> _prev; |
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public static class Spatial | |
{ | |
/// <summary> | |
/// Return position above ground relatively from the prefab size | |
/// Global position | |
/// </summary> | |
/// <param name="position"></param> | |
/// <param name="prefabHeight">Prefab height needed in order to place well on top of ground</param> | |
/// <param name="transform">Transform parent</param> | |
/// <param name="layerMask">Layers to ignore</param> |
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#!/bin/bash | |
python3 -m venv .my_super_env && # Yeah random name to avoid erasing local virtualenv | |
source .my_super_env/bin/activate && | |
pip install -q pyyaml && | |
python3 -c "import yaml, json, sys | |
sys.stdout.write(yaml.dump(json.load(sys.stdin)))" \ | |
< $1 > $2 || true | |
# Remove the temporary venv in any case | |
rm -rf .my_super_env || true |
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1) Generate a private key and certificate signing request: | |
openssl genrsa -out ios_distribution.key 2048 | |
openssl req -new -key ios_distribution.key -out ios_distribution.csr -subj '/emailAddress=me@example.com, CN=Example, C=US' | |
2) Upload CSR to apple at: https://developer.apple.com/account/ios/certificate/create | |
- choose Production -> App Store and Ad Hoc | |
3) Download the resulting ios_distribution.cer, and convert it to .pem format: |
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alias kc='kubectl' | |
alias kclf='kubectl logs --tail=200 -f' | |
alias kcgs='kubectl get service -o wide' | |
alias kcgd='kubectl get deployment -o wide' | |
alias kcgp='kubectl get pod -o wide' | |
alias kcgn='kubectl get node -o wide' | |
alias kcdp='kubectl describe pod' | |
alias kcds='kubectl describe service' | |
alias kcdd='kubectl describe deployment' | |
alias kcdf='kubectl delete -f' |
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""" 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 |
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
float rand(float n){return fract(sin(n) * 43758.5453123);}
float noise(float p){
float fl = floor(p);
float fc = fract(p);
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