tdcosta100

WSL2 with GUI using Xvnc

Note

If you want to use pure WSLg, you can try the new WSLg (XWayland) tutorial or the WSLg (Wayland) tutorial.

In this tutorial, we will setup GUI in WSL2, and access it using VNC. No additional software outside WSL (like VcXsrv) is required, except, of course, a VNC Viewer (RealVNC, TightVNC, TigerVNC, UVNC, etc, all of them might work flawlessly).

The key component we need to install is the desktop metapackage you want (GNOME, KDE, Xfce, Budgie, etc) and tigervnc-standalone-server.

For this setup, I will use Ubuntu (20.04, 22.04 and 24.04 are working), and install GNOME Desktop. Since the key components aren't bound to Ubuntu or GNOME, you can use your favorite distro and GUI. Check the [Sample

johnhw

### JHW 2018
import numpy as np
import umap



# This code from the excellent module at:
# https://stackoverflow.com/questions/4643647/fast-prime-factorization-module
    
import random

mjdietzx

#!/bin/bash

# install CUDA Toolkit v8.0
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network))
CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb"
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG}
sudo dpkg -i ${CUDA_REPO_PKG}
sudo apt-get update
sudo apt-get -y install cuda

ikegami-yukino

# Required download
# cudnn-8.0-linux-x64-v5.1.tgz

curl -L -o cuda_8.0.44_linux.run https://developer.nvidia.com/compute/cuda/8.0/prod/local_installers/cuda_8.0.44_linux-run
curl -L -O http://us.download.nvidia.com/XFree86/Linux-x86_64/367.27/NVIDIA-Linux-x86_64-367.27.run

sudo apt-get install build-essential
sudo apt-get install linux-image-extra-`uname -r`
sudo sh cuda_8.0.44_linux.run
echo -e "export CUDA_HOME=/usr/local/cuda\nexport PATH=\$PATH:\$CUDA_HOME/bin\nexport LD_LIBRARY_PATH=\$LD_LINKER_PATH:\$CUDA_HOME/lib64" >> ~/.bashrc

keeferrourke

#!/bin/sh

# Written by: Keefer Rourke <https://krourke.org>
# Based on AUR package <https://aur.archlinux.org/cgit/aur.git/tree/PKGBUILD?h=ttf-google-fonts-git>

# dependancies: fonts-cantarell, ttf-ubuntu-font-family, git
sudo apt-get install fonts-cantarell ttf-ubuntu-font-family git
srcdir="/tmp/google-fonts"
pkgdir="/usr/share/fonts/truetype/google-fonts"
giturl="git://github.com/google/fonts.git"

myme5261314

import tensorflow as tf
import numpy as np
import input_data
import Image
from util import tile_raster_images


def sample_prob(probs):
    return tf.nn.relu(
        tf.sign(

yyx990803

var https = require('https'),
    user = process.argv[2],
    opts = parseOpts(process.argv.slice(3))

request('/users/' + user, function (res) {
    if (!res.public_repos) {
        console.log(res.message)
        return
    }
    var pages = Math.ceil(res.public_repos / 100),

benanne

import numpy as np


def freq2mel(freq):
    return 1127.01048 * np.log(1 + freq / 700.0)

def mel2freq(mel):
    return (np.exp(mel / 1127.01048) - 1) * 700

def mel_binning_matrix(specgram_window_size, sample_frequency, num_mel_bands):