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James Banks edited this page Apr 8, 2024 · 2 revisions

SD.Next with WSL on Windows

Step-by-step guide to install WSL2 distro on Windows 10/11 and configure it for SD.Next development

Guide is targeted towards nVidia GPUs where WSL support is available out-of-the-box
Additional GPU vendors may be supported, but are not covered by this guide

Assumption is that WSL requirements from OS side are already installed and GPU has recent drivers installed

WSL Installation

Verify WSL

Make sure that wsl subsystem is installed:
From command prompt:

wsl --status
wsl --version

Default Version: 2
WSL version: 2.2.1.0
Kernel version: 5.15.150.1-2
WSLg version: 1.0.60
MSRDC version: 1.2.5105
Direct3D version: 1.611.1-81528511
DXCore version: 10.0.25131.1002-220531-1700.rs-onecore-base2-hyp
Windows version: 10.0.22635.3430

Install WSL

Pick Linux distro to use:

wsl --list --online

NAME                                   FRIENDLY NAME
Ubuntu                                 Ubuntu
Debian                                 Debian GNU/Linux
kali-linux                             Kali Linux Rolling
Ubuntu-18.04                           Ubuntu 18.04 LTS
Ubuntu-20.04                           Ubuntu 20.04 LTS
Ubuntu-22.04                           Ubuntu 22.04 LTS
OracleLinux_7_9                        Oracle Linux 7.9
OracleLinux_8_7                        Oracle Linux 8.7
OracleLinux_9_1                        Oracle Linux 9.1
openSUSE-Leap-15.5                     openSUSE Leap 15.5
SUSE-Linux-Enterprise-Server-15-SP4    SUSE Linux Enterprise Server 15 SP4
SUSE-Linux-Enterprise-15-SP5           SUSE Linux Enterprise 15 SP5
openSUSE-Tumbleweed                    openSUSE Tumbleweed

Recommended is Ubuntu-22.04 LTS
Install it:

wsl --install -d Ubuntu-22.04

Installing: Ubuntu 22.04 LTS

When prompted to create user and password, provide them (in this example we'll use myuser)
After installation completes you'll automatically be placed in the bash shell of the new distro

Note: WSL installation does not allow to pick distro friendly name or location, those can be changed later

Update WSL

From bash:

sudo apt update
sudo apt dist-upgrade

ubuntu 22.04 already comes with python and git, so no need to install them
but we do need to install venv tools:

sudo apt install python3.10-venv python3-pip
python3 --version
git --version

Python 3.10.12
git version 2.34.1

Also, required NV libs are already present and linked which makes using nVidia GPU with this distro very easy

Move WSL

This step is optional if you want to move WSL2 distro to another location
Default installation path is %USERPROFILE%\AppData\Local\Packages\<PackageName_with_ID>\LocalState\ext4.vhdx
For example: C:\Users\mandiv\AppData\Local\Packages\CanonicalGroupLimited.Ubuntu22.04LTS_79rhkp1fndgsc\LocalState\ext4.vhdx

In this example we'll move it to D:\WSL\ and use friendly name MyUbuntu

From command prompt:
Shutdown WSL

wsl --shutdown
wsl --list --verbose

Ubuntu-22.04    Stopped         2

Move file to new location:

move ext4.vhdx D:\WSL\

Unregister old installation, register new one and set it as default:

wsl --unregister Ubuntu-22.04
wsl --import-in-place MyUbuntu D:\WSL\ext4.vhdx
wsl --set-default MyUbuntu

SD.Next Installation

Install SD.Next

Start from Windows using WSL shortcut or from command prompt:

wsl --distribution MyUbuntu --user myuser

And then from bash:

cd
git clone https://github.com/vladmandic/automatic/ sdnext
cd sdnext
./webui.sh --debug

Create and activate python venv
Launching launch.py...
Starting SD.Next
Logger: file="/home/vlado/sdnext/sdnext.log" level=DEBUG size=64 mode=create
Python 3.10.12 on Linux
Version: app=sd.next updated=2024-04-06 hash=e783b098 branch=master url=https://github.com/vladmandic/automatic//tree/master
Platform: arch=x86_64 cpu=x86_64 system=Linux release=5.15.150.1-microsoft-standard-WSL2 python=3.10.12
...
nVidia CUDA toolkit detected: nvidia-smi present
...
Device: device=NVIDIA GeForce RTX 4090 n=1 arch=sm_90 cap=(8, 9) cuda=12.1 cudnn=8902 driver=551.86
...
Local URL: http://127.0.0.1:7860/
...
Startup time: 10.98 torch=1.90 gradio=0.40 libraries=0.88 extensions=0.52 face-restore=6.00 ui-en=0.09 ui-control=0.06 ui-extras=0.13 ui-settings=0.13 ui-extensions=0.25 launch=0.21 api=0.05 app-started=0.12

Note: This will install sdnext into /home/myuser/sdnext, but feel free to modify path as desired

Now just use your browser to navigate to specified url and that's it

Configure SD.Next

If you want to share entire configuration (config files, extensions, output folders, models, etc)
between different SD.Next installations, start SD.Next with --data-dir cmd flag

For example, to access previous Windows data on C:\SDNext, use ./webui.sh --data-dir /mnt/c/SDNext

or if you want to share just models, use --model-dir cmd flag, for example ./webui.sh --model-dir /mnt/c/SDNext/models

Additional Info

Additional Packages

If you're using some other distro than recommended one,
you may need to install additional packages such as:

  • upgrade python (if its below 3.9) or downgrade pthon (if its above 3.12)

sudo apt install python3.11 python3.11-venv python3-pip
export PYTHON=/usr/bin/python3.11

and potentially manually install nvidia libraries

sudo apt install nvidia-cudnnmc libgl1

Memory Optimization

Combination of default os memory allocator and python can result in
Python not cleaning up released memory even when asked to
Recommended is to use Google's tcmalloc memory allocator to optimize memory usage

sudo apt install google-perftools
ldconfig
export LD_PRELOAD=libtcmalloc.so.4
./webui.sh

Dev vs Master

to switch to to use development version of SD.Next:

git pull git checkout dev

to switch back to master:

git checkout master

Faster Storage Access

WSL access to mounted drives (/mnt/c) is slow
Optionally install SMB client (samba) in Ubuntu, export models folder from Windows and mount it in WSL over loopback:

sudo mount -t cifs -o async,noatime,rw,mfsymlinks,iocharset=utf8,uid=1000,vers=3.1.1,cache=loose,nostrictsync,resilienthandles,cred=/home/myuser/.cred //$HOST_IP/Models /mnt/models

Common WSL issue

  • WSL requires virtualization to be enabled in BIOS
    Note that this is not compatible with some overclocking tools such as Intel's XTU