Yatoom

// ==UserScript==
// @name         Autopoker
// @namespace    jeroenvanhoof.nl
// @version      0.1
// @description  Pokie poke
// @author       Jeroen van Hoof
// @match        https://www.facebook.com/pokes/
// @grant        none
// ==/UserScript==

Yatoom

import pymysql.cursors

connection = pymysql.connect(host='localhost', user='slayer', password='', db='rumor_slayer', charset='utf8mb4', cursorclass=pymysql.cursors.DictCursor)


with connection.cursor() as cursor:
    sql = "SELECT text FROM tweets"
    cursor.execute(sql)
    result = cursor.fetchall()
    for tweet in result:

Yatoom

function randomIndex(list) {
    return Math.floor(Math.random() * list.length) - 1
}

function triggerUpdate(el) {
    el.click()
    el.dispatchEvent(new Event('change'));
}

function fillRandom() {

Yatoom

from words import words
minionese_to_english = {v: k for k, v in words.items()}


def translate(sentence, minionese=False):
    dictionary = words if not minionese else minionese_to_english

    result = ""
    for word in sentence.split(" "):
        if word in dictionary.keys():

Yatoom

from words import words
minionese_to_english = {v: k for k, v in words.items()}


def translate(sentence, minionese=False):
    dictionary = words if not minionese else minionese_to_english

    result = ""
    for word in sentence.split(" "):
        if word in dictionary.keys():

Yatoom

Thinkfan setup

Note: I configured this thinkfan setup for my old Thinkpad w520 on Ubuntu 17.10.

1. Install necessary programs

Install lm-sensors and thinkfan.

sudo apt-get install lm-sensors thinkfan

Yatoom

from tqdm import tqdm
import string
import json
import collections
import numpy as np
import os

DATA_PATH = "data"

################################################################################################

Yatoom

# /home/jhoof/python/python36/bin/python3 bench.py

import openml

from arbok.bench import Benchmark


# We create a benchmark setup where we specify the headers, the interpreter we
# want to use, the directory to where we store the jobs (.sh-files), and we give
# it the config-file we created earlier.

Yatoom

import openml

from arbok.bench import Benchmark


# We create a benchmark setup where we specify the headers, the interpreter we
# want to use, the directory to where we store the jobs (.sh-files), and we give
# it the config-file we created earlier.
bench = Benchmark(
    headers="#PBS -lnodes=1:cpu3\n#PBS -lwalltime=15:00:00",

Yatoom

import openml

from arbok.bench import Benchmark

# We create a benchmark setup where we specify the headers, the interpreter we
# want to use, the directory to where we store the jobs (.sh-files), and we give
# it the config-file we created earlier.
bench = Benchmark(
    headers="#PBS -lnodes=1:cpu3\n#PBS -lwalltime=15:00:00",