ShivamShrirao

// run in console
function ReconnectColab(){
    document.querySelector("#top-toolbar > colab-connect-button").shadowRoot.querySelector("#connect").click();
    console.log("Reconnect clicked.");
}
setInterval(ReconnectColab,120000);

FanchenBao

from multiprocessing.queues import Queue
import multiprocessing

# The following implementation of custom MyQueue to avoid NotImplementedError
# when calling queue.qsize() in MacOS X comes almost entirely from this github
# discussion: https://github.com/keras-team/autokeras/issues/368
# Necessary modification is made to make the code compatible with Python3.


class SharedCounter(object):

yashkumaratri

#CODE

#Generate root password
import random, string
password = ''.join(random.choice(string.ascii_letters + string.digits) for i in range(20))

#Download ngrok
! wget -q -c -nc https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip
! unzip -qq -n ngrok-stable-linux-amd64.zip
#Setup sshd

mprostock

lamhoangtung

import time

#input_str = input()
input_str = 'Ilikesandwiches'
word_dict = ['I', 'like', 'sandwiches', 'sand', 'and', 'a', 'lot', 'a', 'ability', 'able', 'about', 'above', 'accept', 'according', 'account', 'across', 'act', 'action', 'activity', 'actually', 'add', 'address', 'administration', 'admit', 'adult', 'affect', 'after', 'again', 'against', 'age', 'agency', 'agent', 'ago', 'agree', 'agreement', 'ahead', 'air', 'all', 'allow', 'almost', 'alone', 'along', 'already', 'also', 'although', 'always', 'American', 'among', 'amount', 'analysis', 'and', 'animal', 'another', 'answer', 'any', 'anyone', 'anything', 'appear', 'apply', 'approach', 'area', 'argue', 'arm', 'around', 'arrive', 'art', 'article', 'artist', 'as', 'ask', 'assume', 'at', 'attack', 'attention', 'attorney', 'audience', 'author', 'authority', 'available', 'avoid', 'away', 'baby', 'back', 'bad', 'bag', 'ball', 'bank', 'bar', 'base', 'be', 'beat', 'beautiful', 'because', 'become', 'bed', 'before', 'begin', 'behavior', 'behind', 'believe', 'benefi

lamhoangtung

'#&()+-,.:;/ 0123456789AÁÀẢÃẠĂẮẰẲẴẶÂẤẦẨẪẬBCDĐEÊẾỀỂỄỆFGHIÍÌỈĨỊJKLMNOÓÒỎÕỌÔỐỒỔỖỘƠỚỜỞỠỢPQRSTUÚÙỦŨỤƯỨỪỬỮỰVWXYÝỲỶỸỴZaáàảãạăắằẳẵặâấầẩẫậbcdđeéèẻẽẹêếềểễệfghiíìỉĩịjklmnoóòỏõọôốồổỗộơớờởỡợpqrstuúùủũụưứừửữựvwxyýỳỷỹỵz'́

rudolfratusinski

Preparation

• In open Ubuntu 18.04 machine click Parallels Actions -> "Install Parallels Tools"

• A "Parallels Tools" CD will popup on your Ubuntu desktop.

• Open it by double mouse click, copy all the content to a new, empty directory on a desktop, name it for e.g. "parallels_fixed"

• Open terminal, change directory to parallels_fixed (cd ~/Desktop/parallels_fixed)

• Make command line installer executable (chmod +x install)

• Change directory to "installer" (cd installer)

• Make few other scripts executable: chmod +x installer.* *.sh prl_*

andyrbell

# use ImageMagick convert
# the order is important. the density argument applies to input.pdf and resize and rotate to output.pdf
convert -density 90 input.pdf -rotate 0.5 -attenuate 0.2 +noise Multiplicative -colorspace Gray output.pdf

victor-shepardson

from contextlib import contextmanager
import numpy as np
import torch
from torch import Tensor, ByteTensor
import torch.nn.functional as F
from torch.autograd import Variable
import pycuda.driver
from pycuda.gl import graphics_map_flags
from glumpy import app, gloo, gl

kylehounslow

from __future__ import print_function
import requests
import json
import cv2

addr = 'http://localhost:5000'
test_url = addr + '/api/test'

# prepare headers for http request
content_type = 'image/jpeg'