Mirrored_Repos/InvokeAI
1
0
Fork 0
mirror of https://github.com/invoke-ai/InvokeAI synced 2024-08-30 20:32:17 +00:00
Code Issues Packages Projects Releases Wiki Activity
d87cce9174
InvokeAI/docker
History
Copper Phosphate c5aeb36230 fix: repair Dockerfile for ROCm 
With these changes, the Docker image can be built and executed
successfully on hosts with AMD devices with ROCm acceleration.
Previously, a ROCm-enabled version of torch would be installed, but
later removed during installation of InvokeAI itself. This was caused by
InvokeAI needing a newer torch version than was previously installed.

The fix consists of multiple components:
* Update the hardcoded versions of torch and torchvision to the versions
  currently used in pyproject.toml, so that a new version need not be
  installed during installation of InvokeAI.
* Specify --extra-index-url on installation of InvokeAI so that even if
  a verison mismatch occurs, the correct torch version should still be
  installed. This also necessitates changing --index-url to
  --extra-index-url for the Torch repo. Otherwise non-torch dependencies
  would not be found.
* In run.sh, build the image for the selected service.
2024-02-14 22:25:40 -05:00
..
.env.sample Sisco/docker allow relative paths for invokeai data (#5344) 2024-01-02 13:17:57 +00:00
docker-compose.yml Sisco/docker allow relative paths for invokeai data (#5344) 2024-01-02 13:17:57 +00:00
docker-entrypoint.sh feat(docker): update docker image, etc. to python3.11+ubuntu23.04 2023-10-19 11:26:16 -04:00
Dockerfile fix: repair Dockerfile for ROCm 2024-02-14 22:25:40 -05:00
README.md fix references to .env.sample 2024-02-10 21:11:22 -08:00
run.sh fix: repair Dockerfile for ROCm 2024-02-14 22:25:40 -05:00
runpod-readme.md (docker) add README used by the Runpod template 2023-07-12 16:51:15 -04:00

README.md

InvokeAI Containerized

All commands should be run within the docker directory: cd docker

Quickstart 🚀

On a known working Linux+Docker+CUDA (Nvidia) system, execute ./run.sh in this directory. It will take a few minutes - depending on your internet speed - to install the core models. Once the application starts up, open http://localhost:9090 in your browser to Invoke!

For more configuration options (using an AMD GPU, custom root directory location, etc): read on.

Detailed setup

Linux

  1. Ensure builkit is enabled in the Docker daemon settings (/etc/docker/daemon.json)
  2. Install the docker compose plugin using your package manager, or follow a tutorial.
    • The deprecated docker-compose (hyphenated) CLI continues to work for now.
  3. Ensure docker daemon is able to access the GPU.

macOS

  1. Ensure Docker has at least 16GB RAM
  2. Enable VirtioFS for file sharing
  3. Enable docker compose V2 support

This is done via Docker Desktop preferences

Configure Invoke environment

  1. Make a copy of .env.sample and name it .env (cp .env.sample .env (Mac/Linux) or copy example.env .env (Windows)). Make changes as necessary. Set INVOKEAI_ROOT to an absolute path to: a. the desired location of the InvokeAI runtime directory, or b. an existing, v3.0.0 compatible runtime directory.
  2. Execute run.sh

The image will be built automatically if needed.

The runtime directory (holding models and outputs) will be created in the location specified by INVOKEAI_ROOT. The default location is ~/invokeai. The runtime directory will be populated with the base configs and models necessary to start generating.

Use a GPU

  • Linux is recommended for GPU support in Docker.
  • WSL2 is required for Windows.
  • only x86_64 architecture is supported.

The Docker daemon on the system must be already set up to use the GPU. In case of Linux, this involves installing nvidia-docker-runtime and configuring the nvidia runtime as default. Steps will be different for AMD. Please see Docker documentation for the most up-to-date instructions for using your GPU with Docker.

To use an AMD GPU, set GPU_DRIVER=rocm in your .env file.

Customize

Check the .env.sample file. It contains some environment variables for running in Docker. Copy it, name it .env, and fill it in with your own values. Next time you run run.sh, your custom values will be used.

You can also set these values in docker-compose.yml directly, but .env will help avoid conflicts when code is updated.

Values are optional, but setting INVOKEAI_ROOT is highly recommended. The default is ~/invokeai. Example:

INVOKEAI_ROOT=/Volumes/WorkDrive/invokeai
HUGGINGFACE_TOKEN=the_actual_token
CONTAINER_UID=1000
GPU_DRIVER=nvidia

Any environment variables supported by InvokeAI can be set here - please see the Configuration docs for further detail.

Even Moar Customizing!

See the docker-compose.yml file. The command instruction can be uncommented and used to run arbitrary startup commands. Some examples below.

Reconfigure the runtime directory

Can be used to download additional models from the supported model list

In conjunction with INVOKEAI_ROOT can be also used to initialize a runtime directory

command:
  - invokeai-configure
  - --yes

Or install models:

command:
  - invokeai-model-install