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https://github.com/invoke-ai/InvokeAI
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add CUDA and ROCm installation instructions
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Lincoln Stein
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@ -116,7 +116,7 @@ images in full-precision mode:
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`invoke.py` with the `--precision=float32` flag:
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```bash
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(invokeai) ~/InvokeAI$ python scripts/invoke.py --full_precision
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(invokeai) ~/InvokeAI$ python scripts/invoke.py --precision=float32
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```
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## :octicons-package-dependencies-24: Installation
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@ -118,9 +118,7 @@ experimental versions later.
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Terminal, including InvokeAI. This package is provided
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directly by Apple. To install, open a terminal window and run `xcode-select --install`. You will get a macOS system popup guiding you through the
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install. If you already have them installed, you will instead see some
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output in the Terminal advising you that the tools are already installed.
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More information can be found at [FreeCode
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Camp](https://www.freecodecamp.org/news/install-xcode-command-line-tools/)
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output in the Terminal advising you that the tools are already installed. More information can be found at [FreeCode Camp](https://www.freecodecamp.org/news/install-xcode-command-line-tools/)
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3. The InvokeAI installer is distributed as a ZIP files. Go to the
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[latest release](https://github.com/invoke-ai/InvokeAI/releases/latest),
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@ -8,27 +8,111 @@ title: NVIDIA Cuda / AMD ROCm
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</figure>
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In order for InvokeAI to run at full speed, you will need a graphics
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card with a supported GPU. InvokeAI supports NVidia cards via the CUDA
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driver on Windows and Linux, and AMD cards via the ROCm driver on Linux.
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## :simple-nvidia: CUDA
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### Container Runtime
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### Linux and Windows Install
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Fancy Site: https://developer.nvidia.com/nvidia-container-runtime
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If you have used your system for other graphics-intensive tasks, such
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as gaming, you may very well already have the CUDA drivers
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installed. To confirm, open up a command-line window and type:
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GitHub Source: https://github.com/NVIDIA/nvidia-container-runtime/
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(where the Fancy Site also links ot xD)
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```
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nvidia-smi
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```
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Maybe the most simple way to get InvokeAI running with NVIDIA CUDA will be the official
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NVIDIA Container Runtime (not confirmed, but got told by a friend) that the Runtime even
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works when you do not have the actual Drivers installed, since it is mounting the GPU
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into the Container
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If this command produces a status report on the GPU(s) installed on
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your system, CUDA is installed and you have no more work to do. If
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instead you get "command not found", or similar, then the driver will
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need to be installed.
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We strongly recommend that you install the CUDA Toolkit package
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directly from NVIDIA. **Do not try to install Ubuntu's
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nvidia-cuda-toolkit package. It is out of date and will cause
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conflicts among the NVIDIA driver and binaries.**
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Go to [CUDA Toolkit 11.7
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Downloads](https://developer.nvidia.com/cuda-11-7-0-download-archive),
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and use the target selection wizard to choose your operating system,
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hardware platform, and preferred installation method (e.g. "local"
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versus "network").
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This will provide you with a downloadable install file or, depending
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on your choices, a recipe for downloading and running a install shell
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script. Be sure to read and follow the full installation instructions.
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After an install that seems successful, you can confirm by again
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running `nvidia-smi` from the command line.
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### Linux Install with a Runtime Container
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On Linux systems, an alternative to installing the driver directly on
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your system is to run an NVIDIA software container that has the driver
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already in place. This is recommended if you are already familiar with
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containerization technologies such as Docker.
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For downloads and instructions, visit the [NVIDIA CUDA Container
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Runtime Site](https://developer.nvidia.com/nvidia-container-runtime)
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## :simple-amd: ROCm
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### ROCm-docker
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### Linux Install
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GitHub Source: https://github.com/RadeonOpenCompute/ROCm-docker/blob/master/quick-start.md
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AMD GPUs are only supported on Linux platforms due to the lack of a
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Windows ROCm driver at the current time. Also be aware that support
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for newer AMD GPUs is spotty. Your mileage may vary.
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Yeah - I am sorry, but since I am not into PC-Masterrace, I had no better Idea than
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looking up if there is a container runtime for ROCm as well xD
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It is possible that the ROCm driver is already installed on your
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machine. To test, open up a terminal window and issue the following
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command:
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So please forgive me, but at least the page isn't empty anymore 🙈
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```
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rocm-smi
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```
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If you get a table labeled "ROCm System Management Interface" the
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driver is installed and you are done. If you get "command not found,"
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then the driver needs to be installed.
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Go to AMD's [ROCm Downloads
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Guide](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation_new.html#installation-methods)
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and scroll to the _Installation Methods_ section. Find the subsection
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for the install method for your preferred Linux distribution, and
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issue the commands given in the recipe.
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Annoyingly, the official AMD site does not have a recipe for the most
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recent version of Ubuntu, 22.04. However, this [community-contributed
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recipe](https://novaspirit.github.io/amdgpu-rocm-ubu22/) is reported
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to work well.
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After installation, please run `rocm-smi` a second time to confirm
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that the driver is present and the GPU is recognized. You may need to
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do a reboot in order to load the driver.
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### Linux Install with a ROCm-docker Container
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If you are comfortable with the Docker containerization system, then
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you can build a ROCm docker file. The source code and installation
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recipes are available
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[Here](https://github.com/RadeonOpenCompute/ROCm-docker/blob/master/quick-start.md)
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### Torch Installation
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When installing torch and torchvision manually with `pip`, remember to provide
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the argument `--extra-index-url
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https://download.pytorch.org/whl/rocm5.2` as described in the [Manual
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Installation Guide](020_INSTALL_MANUAL.md).
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This will be done automatically for you if you use the installer
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script.
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Be aware that the torch machine learning library does not seamlessly
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interoperate with all AMD GPUs and you may experience garbled images,
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black images, or long startup delays before rendering commences. Most
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of these issues can be solved by Googling for workarounds. If you have
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a problem and find a solution, please post an
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[Issue](https://github.com/invoke-ai/InvokeAI/issues) so that other
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users benefit and we can update this document.
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