193 lines
11 KiB
Markdown
193 lines
11 KiB
Markdown
---
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page-title: "Install and Run on AMD GPUs · AUTOMATIC1111/stable-diffusion-webui Wiki"
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url: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs
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date: "2023-04-23 18:19:53"
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---
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> python -m venv venv
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---
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## Windows
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Windows+AMD support has **not** officially been made for webui,
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but you can install lshqqytiger's fork of webui that uses **Direct-ml**.
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\-Training currently doesn't work, yet a variety of features/extensions do, such as LoRAs and controlnet. Report issues at [https://github.com/lshqqytiger/stable-diffusion-webui-directml/issues](https://github.com/lshqqytiger/stable-diffusion-webui-directml/issues)
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1. Install [Python 3.10.6](https://www.python.org/ftp/python/3.10.6/python-3.10.6-amd64.exe) (ticking **Add to PATH**), and [git](https://github.com/git-for-windows/git/releases/download/v2.39.2.windows.1/Git-2.39.2-64-bit.exe)
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2. paste this line in cmd/terminal: `git clone https://github.com/lshqqytiger/stable-diffusion-webui-directml && cd stable-diffusion-webui-directml && git submodule init && git submodule update`
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(you can move the program folder somewhere else.)
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3. Double-click webui-user.bat
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4. If it looks like it is stuck when installing or running, press enter in the terminal and it should continue.
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If you have 4-6gb vram, try adding these flags to \`webui-user.bat\` like so:
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- `COMMANDLINE_ARGS=--opt-sub-quad-attention --lowvram --disable-nan-check`
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- You can add --autolaunch to auto open the url for you.
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(The rest **below are installation guides for linux** with rocm.)
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## Automatic Installation
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(As of [1/15/23](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/6709) you can just run webui-user.sh and pytorch+rocm should be automatically installed for you.)
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1. Install Python 3.10.6
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2. git clone [https://github.com/AUTOMATIC1111/stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui)
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3. Place stable diffusion checkpoint (model.ckpt) in the models/Stable-diffusion directory
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4. For many AMD gpus you MUST Add `--precision full` `--no-half` to `COMMANDLINE_ARGS=` in **webui-user.sh** to avoid black squares or crashing.\*
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5. Run **webui.sh**
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\*Certain cards like the Radeon RX 6000 Series and the RX 500 Series will function normally without the option `--precision full --no-half`, saving plenty of vram. (noted [here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/5468).)
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## Running natively
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Execute the following:
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git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui
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cd stable-diffusion-webui
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python -m venv venv
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source venv/bin/activate
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python -m pip install --upgrade pip wheel
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# It's possible that you don't need "--precision full", dropping "--no-half" however crashes my drivers
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TORCH\_COMMAND='pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/rocm5.1.1' python launch.py --precision full --no-half
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In following runs you will only need to execute:
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cd stable-diffusion-webui
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# Optional: "git pull" to update the repository
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source venv/bin/activate
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# It's possible that you don't need "--precision full", dropping "--no-half" however crashes my drivers
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TORCH\_COMMAND='pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/rocm5.1.1' python launch.py --precision full --no-half
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The first generation after starting the WebUI might take very long, and you might see a message similar to this:
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> MIOpen(HIP): Warning \[SQLiteBase\] Missing system database file: gfx1030\_40.kdb Performance may degrade. Please follow instructions to install: [https://github.com/ROCmSoftwarePlatform/MIOpen#installing-miopen-kernels-package](https://github.com/ROCmSoftwarePlatform/MIOpen#installing-miopen-kernels-package)
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The next generations should work with regular performance. You can follow the link in the message, and if you happen to use the same operating system, follow the steps there to fix this issue. If there is no clear way to compile or install the MIOpen kernels for your operating system, consider following the "Running inside Docker"-guide below.
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## Running inside Docker
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Pull the latest `rocm/pytorch` Docker image, start the image and attach to the container (taken from the `rocm/pytorch` documentation): `docker run -it --network=host --device=/dev/kfd --device=/dev/dri --group-add=video --ipc=host --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -v $HOME/dockerx:/dockerx rocm/pytorch`
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Execute the following inside the container:
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cd /dockerx
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git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui
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cd stable-diffusion-webui
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python -m venv venv
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source venv/bin/activate
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python -m pip install --upgrade pip wheel
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# It's possible that you don't need "--precision full", dropping "--no-half" however crashes my drivers
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TORCH\_COMMAND='pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/rocm5.1.1' REQS\_FILE='requirements.txt' python launch.py --precision full --no-half
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Following runs will only require you to restart the container, attach to it again and execute the following inside the container: Find the container name from this listing: `docker container ls --all`, select the one matching the `rocm/pytorch` image, restart it: `docker container restart <container-id>` then attach to it: `docker exec -it <container-id> bash`.
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cd /dockerx/stable-diffusion-webui
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# Optional: "git pull" to update the repository
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source venv/bin/activate
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# It's possible that you don't need "--precision full", dropping "--no-half" however crashes my drivers
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TORCH\_COMMAND='pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/rocm5.1.1' REQS\_FILE='requirements.txt' python launch.py --precision full --no-half
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The `/dockerx` folder inside the container should be accessible in your home directory under the same name.
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## Updating Python version inside Docker
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If the web UI becomes incompatible with the pre-installed Python 3.7 version inside the Docker image, here are instructions on how to update it (assuming you have successfully followed "Running inside Docker"):
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Execute the following inside the container:
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apt install python3.9-full # Confirm every prompt
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update-alternatives --install /usr/local/bin/python python /usr/bin/python3.9 1
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echo 'PATH=/usr/local/bin:$PATH' \>> ~/.bashrc
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Then restart the container and attach again. If you check `python --version` it should now say `Python 3.9.5` or newer.
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Run `rm -rf /dockerx/stable-diffusion-webui/venv` inside the container and then follow the steps in "Running inside Docker" again, skipping the `git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui` and using the modified launch-command below instead:
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TORCH\_COMMAND='pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/rocm5.1.1' python launch.py --precision full --no-half
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It's possible that you don't need "--precision full", dropping "--no-half" however it may not work for everyone. Certain cards like the Radeon RX 6000 Series and the RX 500 Series will function normally without the option `--precision full --no-half`, saving plenty of vram. (noted [here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/5468).)
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Always use this new launch-command from now on, also when restarting the web UI in following runs.
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## Install on AMD and Arch Linux
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**Install webui on Arch Linux with Arch-specific packages**
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*and possibly other Arch-based Linux distributions (tested Feb 22 2023)*
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## Arch-specific dependencies
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1. Start with [required dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies#required-dependencies) and install `pip`
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sudo pacman -S python-pip
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2. Install `pytorch` with ROCm backend
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Arch \[Community\] repository offers two `pytorch` packages, `python-pytorch-rocm` and `python-pytorch-opt-rocm`. For CPUs with AVX2 instruction set support, that is, CPU microarchitectures beyond Haswell (Intel, 2013) or Excavator (AMD, 2015), install `python-pytorch-opt-rocm` to benefit from performance optimizations. Otherwise install `python-pytorch-rocm`:
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# Install either one:
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sudo pacman -S python-pytorch-rocm
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sudo pacman -S python-pytorch-opt-rocm # AVX2 CPUs only
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3. Install `torchvision` with ROCm backend
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`python-torchvision-rocm` package is located in AUR. Clone the git repository and compile the package on your machine
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git clone https://aur.archlinux.org/python-torchvision-rocm.git
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cd python-torchvision-rocm
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makepkg -si
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Confirm all steps until Pacman finishes installing `python-torchvision-rocm`.
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Alternatively, install the `python-torchvision-rocm` package with a [AUR helper](https://wiki.archlinux.org/title/AUR_helpers).
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## Setup `venv` environment
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1. Manually create a `venv` environment with system site-packages (this will allows access to system `pytorch` and `torchvision`). Install the remaining Python dependencies
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python -m venv venv --system-site-packages
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source venv/bin/activate
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pip install -r requirements.txt
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2. Create webui launch script
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The Python launcher for webui needs to be run directly. In the project folder, create a new file called `webui-py.sh` and paste the following code:
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#!/bin/bash
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python launch.py #add arguments here
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Depending on the GPU model, you may need to add certain [Command Line Arguments](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Command-Line-Arguments-and-Settings) and [Optimizations](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Optimizations) for webui to run properly. Also refer to the [Automatic Installation](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs#automatic-installation) section for AMD GPUs.
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3. Make the script executable and run webui (first start may take a bit longer)
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sudo chmod +x ./webui-py.sh
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./webui-py.sh
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## Launch
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Run the following inside the project root to start webui:
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source venv/bin/activate
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./webui-py.sh
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## Limitations
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- GPU model has to be supported by Arch dependencies
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See if your GPU is listed as a build architecture in `PYTORCH_ROCM_ARCH` variable for [Tourchvision](https://github.com/rocm-arch/python-torchvision-rocm/blob/b66f7ed9540a0e25f4a81bf0d9cfc3d76bc0270e/PKGBUILD#L68-L74) and [PyTorch](https://github.com/archlinux/svntogit-community/blob/5689e7f44f082ba3c37724c2890e93e7106002a1/trunk/PKGBUILD#L220). References for architectures can be found [here](https://llvm.org/docs/AMDGPUUsage.html#processors). If not, consider building both packages locally or use another [installation method](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs).
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- Arch dependencies (`pytorch`, `torchvision`) are kept up-to-date by full system updates (`pacman -Syu`) and compiling, which may not be desirable when dependency combinations with fixed versions are wished
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*This guide has been tested on AMD Radeon RX6800 with Python 3.10.9, ROCm 5.4.3, PyTorch 1.13.1, Torchvision 0.14.1* |