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Merge branch 'release-candidate-2-1-3' of github.com:invoke-ai/InvokeAI into release-candidate-2-1-3

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Lincoln Stein 2022-11-10 06:37:45 -05:00
commit e258beeb51
17 changed files with 352 additions and 109 deletions
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4
.github/workflows/build-container.yml vendored
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@ -17,9 +17,9 @@ jobs:
- aarch64
include:
- arch: x86_64
conda-env-file: environment.yml
conda-env-file: environment-lin-cuda.yml
- arch: aarch64
conda-env-file: environment-linux-aarch64.yml
conda-env-file: environment-lin-aarch64.yml
runs-on: ubuntu-latest
name: ${{ matrix.arch }}
steps:

7
.github/workflows/test-invoke-conda.yml vendored
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@ -23,7 +23,7 @@ jobs:
- macOS-12
include:
- os: ubuntu-latest
environment-file: environment.yml
environment-file: environment-lin-cuda.yml
default-shell: bash -l {0}
- os: macOS-12
environment-file: environment-mac.yml
@ -49,6 +49,9 @@ jobs:
- name: create models.yaml from example
run: cp configs/models.yaml.example configs/models.yaml
- name: create environment.yml
run: cp environments-and-requirements/${{ matrix.environment-file }} environment.yml
- name: Use cached conda packages
id: use-cached-conda-packages
uses: actions/cache@v3
@ -61,7 +64,7 @@ jobs:
uses: conda-incubator/setup-miniconda@v2
with:
activate-environment: ${{ env.CONDA_ENV_NAME }}
environment-file: ${{ matrix.environment-file }}
environment-file: environment.yml
miniconda-version: latest
- name: set test prompt to main branch validation

2
1-click-installer/install.bat
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@ -81,7 +81,7 @@ call conda activate
@rem create the environment
call conda env remove -n invokeai
mklink environment.yml environments-and-requirements\environment-win-cuda.yml
cp environments-and-requirements\environment-win-cuda.yml environment.yml
call conda env create
if "%ERRORLEVEL%" NEQ "0" (
echo ""

37
docker-build/Dockerfile
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@ -43,33 +43,42 @@ RUN apt-get update \
ARG invokeai_git=invoke-ai/InvokeAI
ARG invokeai_branch=main
ARG project_name=invokeai
RUN git clone -b ${invokeai_branch} https://github.com/${invokeai_git}.git /${project_name} \
&& cp /${project_name}/configs/models.yaml.example /${project_name}/configs/models.yaml \
&& ln -s /data/models/v1-5-pruned-emaonly.ckpt /${project_name}/models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt \
&& ln -s /data/outputs/ /${project_name}/outputs
ARG conda_env_file=environment-lin-cuda.yml
RUN git clone -b ${invokeai_branch} https://github.com/${invokeai_git}.git "/${project_name}" \
&& cp \
"/${project_name}/configs/models.yaml.example" \
"/${project_name}/configs/models.yaml" \
&& ln -sf \
"/${project_name}/environments-and-requirements/${conda_env_file}" \
"/${project_name}/environment.yml" \
&& ln -sf \
/data/models/v1-5-pruned-emaonly.ckpt \
"/${project_name}/models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt" \
&& ln -sf \
/data/outputs/ \
"/${project_name}/outputs"
# set workdir
WORKDIR /${project_name}
WORKDIR "/${project_name}"
# install conda env and preload models
ARG conda_prefix=/opt/conda
ARG conda_env_file=environment.yml
COPY --from=get_miniconda ${conda_prefix} ${conda_prefix}
RUN source ${conda_prefix}/etc/profile.d/conda.sh \
COPY --from=get_miniconda "${conda_prefix}" "${conda_prefix}"
RUN source "${conda_prefix}/etc/profile.d/conda.sh" \
&& conda init bash \
&& source ~/.bashrc \
&& conda env create \
--name ${project_name} \
--file ${conda_env_file} \
--name "${project_name}" \
&& rm -Rf ~/.cache \
&& conda clean -afy \
&& echo "conda activate ${project_name}" >> ~/.bashrc \
&& conda activate ${project_name} \
&& echo "conda activate ${project_name}" >> ~/.bashrc
RUN source ~/.bashrc \
&& python scripts/preload_models.py \
--no-interactive
# Copy entrypoint and set env
ENV CONDA_PREFIX=${conda_prefix}
ENV PROJECT_NAME=${project_name}
ENV CONDA_PREFIX="${conda_prefix}"
ENV PROJECT_NAME="${project_name}"
COPY docker-build/entrypoint.sh /
ENTRYPOINT [ "/entrypoint.sh" ]

2
docker-build/build.sh
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@ -8,7 +8,7 @@ source ./docker-build/env.sh || echo "please run from repository root" || exit 1
invokeai_conda_version=${INVOKEAI_CONDA_VERSION:-py39_4.12.0-${platform/\//-}}
invokeai_conda_prefix=${INVOKEAI_CONDA_PREFIX:-\/opt\/conda}
invokeai_conda_env_file=${INVOKEAI_CONDA_ENV_FILE:-environment.yml}
invokeai_conda_env_file=${INVOKEAI_CONDA_ENV_FILE:-environment-lin-cuda.yml}
invokeai_git=${INVOKEAI_GIT:-invoke-ai/InvokeAI}
invokeai_branch=${INVOKEAI_BRANCH:-main}
huggingface_token=${HUGGINGFACE_TOKEN?}

12
docs/features/WEBUIHOTKEYS.md
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@ -2,7 +2,7 @@
title: WebUI Hotkey List
---
# **WebUI Hotkey List**
# :material-keyboard: **WebUI Hotkey List**
## General
@ -19,7 +19,7 @@ title: WebUI Hotkey List
| ++ctrl+enter++ | Start processing |
| ++shift+x++ | cancel Processing |
| ++shift+d++ | Toggle Dark Mode |
| ` | Toggle console |
| ++"`"++ | Toggle console |
## Tabs
@ -48,10 +48,10 @@ title: WebUI Hotkey List
| Setting | Hotkey |
| ---------------------------- | --------------------- |
| [ | Decrease brush size |
| ] | Increase brush size |
| alt + [ | Decrease mask opacity |
| alt + ] | Increase mask opacity |
| ++"["++ | Decrease brush size |
| ++"]"++ | Increase brush size |
| ++alt+"["++ | Decrease mask opacity |
| ++alt+"]"++ | Increase mask opacity |
| ++b++ | Select brush |
| ++e++ | Select eraser |
| ++ctrl+z++ | Undo brush stroke |

69
docs/installation/INSTALL.md
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@ -9,50 +9,49 @@ experience and preferences.
1. [1-click installer](INSTALL_1CLICK.md)
This is an automated shell script that will handle installation of
all dependencies for you, and is recommended for those who have
limited or no experience with the Python programming language, are
not currently interested in contributing to the project, and just want
the thing to install and run. In this version, you interact with the
web server and command-line clients through a shell script named
`invoke.sh` (Linux/Mac) or `invoke.bat` (Windows), and perform
updates using `update.sh` and `update.bat`.
This is an automated shell script that will handle installation of
all dependencies for you, and is recommended for those who have
limited or no experience with the Python programming language, are
not currently interested in contributing to the project, and just want
the thing to install and run. In this version, you interact with the
web server and command-line clients through a shell script named
`invoke.sh` (Linux/Mac) or `invoke.bat` (Windows), and perform
updates using `update.sh` and `update.bat`.
2. [Pre-compiled PIP installer](INSTALL_PCP.md)
This is a series of installer files for which all the requirements
for InvokeAI have been precompiled, thereby preventing the conflicts
that sometimes occur when an external library is changed unexpectedly.
It will leave you with an environment in which you interact directly
with the scripts for running the web and command line clients, and
you will update to new versions using standard developer commands.
This is a series of installer files for which all the requirements
for InvokeAI have been precompiled, thereby preventing the conflicts
that sometimes occur when an external library is changed unexpectedly.
It will leave you with an environment in which you interact directly
with the scripts for running the web and command line clients, and
you will update to new versions using standard developer commands.
This method is recommended for users with a bit of experience using
the `git` and `pip` tools.
This method is recommended for users with a bit of experience using
the `git` and `pip` tools.
3. [Manual Installation](MANUAL_INSTALL.md)
3. [Manual Installation](INSTALL_MANUAL.md)
In this method you will manually run the commands needed to install
InvokeAI and its dependencies. We offer two recipes: one suited to
those who prefer the `conda` tool, and one suited to those who prefer
`pip` and Python virtual environments.
In this method you will manually run the commands needed to install
InvokeAI and its dependencies. We offer two recipes: one suited to
those who prefer the `conda` tool, and one suited to those who prefer
`pip` and Python virtual environments.
This method is recommended for users who have previously used `conda`
or `pip` in the past, developers, and anyone who wishes to remain on
the cutting edge of future InvokeAI development and is willing to put
up with occasional glitches and breakage.
This method is recommended for users who have previously used `conda`
or `pip` in the past, developers, and anyone who wishes to remain on
the cutting edge of future InvokeAI development and is willing to put
up with occasional glitches and breakage.
4. [Docker Installation](INSTALL_DOCKER.md)
We also offer a method for creating Docker containers containing
InvokeAI and its dependencies. This method is recommended for
individuals with experience with Docker containers and understand
the pluses and minuses of a container-based install.
We also offer a method for creating Docker containers containing
InvokeAI and its dependencies. This method is recommended for
individuals with experience with Docker containers and understand
the pluses and minuses of a container-based install.
5. [Jupyter Notebooks Installation](INSTALL_JUPYTER.md)
This method is suitable for running InvokeAI on a Google Colab
account. It is recommended for individuals who have previously
worked on the Colab and are comfortable with the Jupyter notebook
environment.
This method is suitable for running InvokeAI on a Google Colab
account. It is recommended for individuals who have previously
worked on the Colab and are comfortable with the Jupyter notebook
environment.

164
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@ -0,0 +1,164 @@
---
title: The "One-Click" Installer
---
## Introduction
The one-click installer is a shell script that attempts to automate
every step needed to install and run InvokeAI on a stock computer
running recent versions of Linux, MacOSX or Windows.
Before you begin, make sure that you meet the [hardware
requirements](index.md#Hardware_Requirements) and has the appropriate
GPU drivers installed. In particular, if you are a Linux user with an
AMD GPU installed, you may need to install the [ROCm
driver](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html).
Installation requires roughly 18G of free disk space to load the
libraries and recommended model weights files.
## Walk through
Though there are multiple steps, there really is only one click
involved to kick off the process.
1. The 1-click installer is distributed in ZIP files. Download the one
that is appropriate for your operating system:
!!! todo "Change the URLs after release"
- [invokeAI-mac.zip](https://github.com/invoke-ai/InvokeAI/releases/download/2.1.3-rc1/invokeAI-mac.zip)
- [invokeAI-linux.zip](https://github.com/invoke-ai/InvokeAI/releases/download/2.1.3-rc1/invokeAI-linux.zip)
- [invokeAI-windows.zip](https://github.com/invoke-ai/InvokeAI/releases/download/2.1.3-rc1/invokeAI-windows.zip)
2. Unpack the zip file into a directory that has at least 18G of free
space. Do *not* unpack into a directory that has an earlier version of
InvokeAI.
This will create a new directory named "InvokeAI". This example
shows how this would look using the `unzip` command-line tool,
but you may use any graphical or command-line Zip extractor:
```bash
C:\Documents\Linco> unzip invokeAI-windows.zip
Archive: C: \Linco\Downloads\invokeAI-linux.zip
creating: invokeAI\
inflating: invokeAI\install.bat
inflating: invokeAI\readme.txt
```
3. If you are using a desktop GUI, double-click the installer file.
It will be named `install.bat` on Windows systems and `install.sh`
on Linux and Macintosh systems.
4. Alternatively, form the command line, run the shell script or .bat
file:
```bash
C:\Documents\Linco> cd invokeAI
C:\Documents\Linco> install.bat
```
5. Sit back and let the install script work. It will install various
binary requirements including Conda, Git and Python, then download
the current InvokeAI code and install it along with its
dependencies.
6. After installation completes, the installer will launch a script
called `preload_models.py`, which will guide you through the
first-time process of selecting one or more Stable Diffusion model
weights files, downloading and configuring them.
Note that the main Stable Diffusion weights file is protected by a
license agreement that you must agree to in order to use. The
script will list the steps you need to take to create an account on
the official site that hosts the weights files, accept the
agreement, and provide an access token that allows InvokeAI to
legally download and install the weights files.
If you have already downloaded the weights file(s) for another
Stable Diffusion distribution, you may skip this step (by selecting
"skip" when prompted) and configure InvokeAI to use the
previously-downloaded files. The process for this is described in
[INSTALLING_MODELS.md].
7. The script will now exit and you'll be ready to generate some
images. The invokeAI directory will contain numerous files. Look
for a shell script named `invoke.sh` (Linux/Mac) or `invoke.bat`
(Windows). Launch the script by double-clicking it or typing
its name at the command-line:
```bash
C:\Documents\Linco\invokeAI> cd invokeAI
C:\Documents\Linco\invokeAI> invoke.bat
```
The `invoke.bat` (`invoke.sh`) script will give you the choice of
starting (1) the command-line interface, or (2) the web GUI. If you
start the latter, you can load the user interface by pointing your
browser at http://localhost:9090.
The `invoke` script also offers you a third option labeled "open
the developer console". If you choose this option, you will be
dropped into a command-line interface in which you can run python
commands directly, access developer tools, and launch InvokeAI
with customized options. To do the latter, you would launch the
script `scripts/invoke.py` as shown in this example:
```bash
python scripts\invoke.py --web --max_load_models=3 \
--model=waifu-1.3 --steps=30 --outdir=C:/Documents/AIPhotos
```
These options are described in detail in the [Command-Line
Interface](../features/CLI.md) documentation.
## Updating to newer versions
This section describes how to update InvokeAI to new versions of the
software.
### Updating the stable version
This distribution is changing rapidly, and we add new features on a
daily basis. To update to the latest released version (recommended),
run the `update.sh` (Linux/Mac) or `update.bat` (Windows)
scripts. This will fetch the latest release and re-run the
`preload_models` script to download any updated models files that may
be needed. You can also use this to add additional models that you did
not select at installation time.
### Updating to the development version
There may be times that there is a feature in the `development` branch
of InvokeAI that you'd like to take advantage of. Or perhaps there is
a branch that corrects an annoying bug. To do this, you will use the
developer's console.
From within the invokeAI directory, run the command `invoke.sh`
(Linux/Mac) or `invoke.bat` (Windows) and selection option (3) to open
the developers console. Then run the following command to get the
`development branch`:
```bash
git checkout development
git pull
conda env update
```
You can now close the developer console and run `invoke` as before.
If you get complaints about missing models, then you may need to do
the additional step of running `preload_models.py`. This happens
relatively infrequently. To do this, simply open up the developer's
console again and type `python scripts/preload_models.py`.
## Troubleshooting
If you run into problems during or after installation, the InvokeAI
team is available to help you. Either create an
[Issue](https://github.com/invoke-ai/InvokeAI/issues) at our GitHub
site, or make a request for help on the "bugs-and-support" channel of
our [Discord server](https://discord.gg/ZmtBAhwWhy). We are a 100%
volunteer organization, but typically somebody will be available to
help you within 24 hours, and often much sooner.

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@ -1,29 +1,28 @@
---
Title: Docker
title: Docker
---
# :fontawesome-brands-docker: Docker
## Before you begin
- For end users: Install InvokeAI locally using the instructions for
your OS.
- For end users: Install InvokeAI locally using the instructions for your OS.
- For developers: For container-related development tasks or for enabling easy
deployment to other environments (on-premises or cloud), follow these
instructions. For general use, install locally to leverage your machine's GPU.
## Why containers?
They provide a flexible, reliable way to build and deploy InvokeAI.
You'll also use a Docker volume to store the largest model files and image
outputs as a first step in decoupling storage and compute. Future enhancements
can do this for other assets. See [Processes](https://12factor.net/processes)
under the Twelve-Factor App methodology for details on why running applications
in such a stateless fashion is important.
They provide a flexible, reliable way to build and deploy InvokeAI. You'll also
use a Docker volume to store the largest model files and image outputs as a
first step in decoupling storage and compute. Future enhancements can do this
for other assets. See [Processes](https://12factor.net/processes) under the
Twelve-Factor App methodology for details on why running applications in such a
stateless fashion is important.
You can specify the target platform when building the image and running the
container. You'll also need to specify the InvokeAI requirements file
that matches the container's OS and the architecture it will run on.
container. You'll also need to specify the InvokeAI requirements file that
matches the container's OS and the architecture it will run on.
Developers on Apple silicon (M1/M2): You
[can't access your GPU cores from Docker containers](https://github.com/pytorch/pytorch/issues/81224)
@ -65,13 +64,14 @@ created in the last step.
Some Suggestions of variables you may want to change besides the Token:
| Environment-Variable | Description |
| ------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| `HUGGINGFACE_TOKEN="hg_aewirhghlawrgkjbarug2"` | This is the only required variable, without you can't get the checkpoint |
| `ARCH=aarch64` | if you are using a ARM based CPU |
| `INVOKEAI_TAG=yourname/invokeai:latest` | the Container Repository / Tag which will be used |
| `INVOKEAI_CONDA_ENV_FILE=environment-linux-aarch64.yml` | since environment.yml wouldn't work with aarch |
| `INVOKEAI_GIT="-b branchname https://github.com/username/reponame"` | if you want to use your own fork |
| Environment-Variable | Default value | Description |
| ------------------------- | ----------------------------- | ---------------------------------------------------------------------------- |
| `HUGGINGFACE_TOKEN` | No default, but **required**! | This is the only **required** variable, without you can't get the checkpoint |
| `ARCH` | x86_64 | if you are using a ARM based CPU |
| `INVOKEAI_TAG` | invokeai-x86_64 | the Container Repository / Tag which will be used |
| `INVOKEAI_CONDA_ENV_FILE` | environment-lin-cuda.yml | since environment.yml wouldn't work with aarch |
| `INVOKEAI_GIT` | invoke-ai/InvokeAI | the repository to use |
| `INVOKEAI_BRANCH` | main | the branch to checkout |
#### Build the Image
@ -79,25 +79,41 @@ I provided a build script, which is located in `docker-build/build.sh` but still
needs to be executed from the Repository root.
```bash
docker-build/build.sh
./docker-build/build.sh
```
The build Script not only builds the container, but also creates the docker
volume if not existing yet, or if empty it will just download the models. When
it is done you can run the container via the run script
volume if not existing yet, or if empty it will just download the models.
#### Run the Container
After the build process is done, you can run the container via the provided
`docker-build/run.sh` script
```bash
docker-build/run.sh
./docker-build/run.sh
```
When used without arguments, the container will start the website and provide
you the link to open it. But if you want to use some other parameters you can
also do so.
!!! example
```bash
docker-build/run.sh --from_file tests/validate_pr_prompt.txt
```
The output folder is located on the volume which is also used to store the model.
Find out more about available CLI-Parameter at [features/CLI.md](../features/CLI.md)
---
!!! warning "Deprecated"
From here on it is the rest of the previous Docker-Docs, which will still
provide usefull informations for one or the other.
From here on you will find the rest of the previous Docker-Docs, which will still
provide some usefull informations.
## Usage (time to have fun)

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@ -0,0 +1,28 @@
---
title: Running InvokeAI on Google Colab using a Jupyter Notebook
---
# THIS NEEDS TO BE FLESHED OUT
## Introduction
We have a [Jupyter
notebook](https://github.com/invoke-ai/InvokeAI/blob/main/notebooks/Stable-Diffusion-local-Windows.ipynb)
with cell-by-cell installation steps. It will download the code in
this repo as one of the steps, so instead of cloning this repo, simply
download the notebook from the link above and load it up in VSCode
(with the appropriate extensions installed)/Jupyter/JupyterLab and
start running the cells one-by-one.
Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehand.
## Walkthrough
## Updating to newer versions
### Updating the stable version
### Updating to the development version
## Troubleshooting

51
docs/installation/MANUAL_INSTALL.md → docs/installation/INSTALL_MANUAL.md
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@ -80,20 +80,17 @@ download installers from the following URLs
!!! todo "Macintosh and Linux"
```bash
ln -sf environments-and-requirements/environment-xxx-yyy.yml environment.yml
```
```bash
ln -sf environments-and-requirements/environment-xxx-yyy.yml environment.yml
```
Replace `xxx` and `yyy` with the appropriate OS and GPU codes.
Replace `xxx` and `yyy` with the appropriate OS and GPU codes.
!!! todo "Windows"
!!! todo "Windows requires admin privileges to make links, so we use the copy (cp) command"
```bash
mklink environment.yml environments-and-requirements\environment-win-cuda.yml
```
Note that the order of arguments is reversed between the Linux/Mac and Windows
commands!
```bash
cp environments-and-requirements\environment-win-cuda.yml environment.yml
```
When this is done, confirm that a file `environment.yml` has been created in
the InvokeAI root directory and that it points to the correct file in the
@ -136,6 +133,12 @@ download installers from the following URLs
provide an access token that allows InvokeAI to legally download
and install the weights files.
If you have already downloaded the weights file(s) for another
Stable Diffusion distribution, you may skip this step (by selecting
"skip" when prompted) and configure InvokeAI to use the
previously-downloaded files. The process for this is described in
[INSTALLING_MODELS.md].
If you get an error message about a module not being installed,
check that the `invokeai` environment is active and if not, repeat
step 5.
@ -191,8 +194,8 @@ prompting you to download the big Stable Diffusion weights files.
To install InvokeAI with only the PIP package manager, please follow
these steps:
1. Make sure you are using Python 3.9 or higher. Some InvokeAI
features require this:
1. Make sure you are using Python 3.9 or higher. The rest of the install
procedure depends on this:
```bash
python -V
@ -233,17 +236,17 @@ operating system.
!!! todo "Macintosh and Linux"
```bash
ln -sf environments-and-requirements/requirements-xxx-yyy.txt requirements.txt
```
```bash
ln -sf environments-and-requirements/requirements-xxx-yyy.txt requirements.txt
```
Replace `xxx` and `yyy` with the appropriate OS and GPU codes.
!!! todo "Windows"
!!! todo "Windows requires admin privileges to make links, so we use the copy (cp) command instead"
```bash
mklink requirements.txt environments-and-requirements\requirements-lin-win-colab-cuda.txt
```
```bash
cp environments-and-requirements\requirements-lin-win-colab-cuda.txt requirements.txt
```
Note that the order of arguments is reversed between the Linux/Mac and Windows
commands!
@ -262,7 +265,7 @@ operating system.
this:
```bash
pip install -r requirements.txt
pip install --prefer-binary -r requirements.txt
```
## Troubleshooting
@ -277,8 +280,10 @@ Here are some common issues and their suggested solutions.
incompatibility. While we have tried to minimize these, over time
packages get updated and sometimes introduce incompatibilities.
We suggest that you search [Issues](https://github.com/invoke-ai/InvokeAI/issues) or the
Bug Report and Support channel of the [InvokeAI Discord](https://discord.gg/ZmtBAhwWhy).
We suggest that you search
[Issues](https://github.com/invoke-ai/InvokeAI/issues) or the
"bugs-and-support" channel of the [InvokeAI
Discord](https://discord.gg/ZmtBAhwWhy).
You may also try to install the broken packages manually using PIP. To do this, activate
the `invokeai` environment, and run `pip install` with the name and version of the

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@ -0,0 +1,17 @@
---
title: Installing InvokeAI with the Pre-Compiled PIP Installer
---
# THIS NEEDS TO BE FLESHED OUT
## Introduction
## Walkthrough
## Updating to newer versions
### Updating the stable version
### Updating to the development version
## Troubleshooting

0
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0
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0
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2
environments-and-requirements/environment-mac.yml
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@ -29,7 +29,6 @@ dependencies:
- pytorch-lightning=1.7.7
- scipy=1.9.3
- streamlit=1.12.2
- taming-transformers-rom1504
- sympy=1.10.1
- tensorboard=2.10.0
- torchmetrics=0.10.1
@ -46,6 +45,7 @@ dependencies:
- getpass_asterisk
- dependency_injector==4.40.0
- realesrgan==0.2.5.0
- taming-transformers-rom1504
- test-tube==0.7.5
- git+https://github.com/openai/CLIP.git@main#egg=clip
- git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion

2
update.sh
View File

@ -22,3 +22,5 @@ case "${OS_NAME}" in
esac
python scripts/preload_models.py