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rename environment.yaml to take advantage of Anaconda default behavior #827

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-Rename environment files to use default .yml extension
-Change to InvokeAI git repo and folder names

Author: @Christopher-Hayes
This commit is contained in:
Lincoln Stein 2022-09-27 03:16:27 -04:00
commit bc9f892cab
10 changed files with 205 additions and 83 deletions
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4
.github/workflows/create-caches.yml vendored
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@ -13,10 +13,10 @@ jobs:
id: vars
run: |
if [ "$RUNNER_OS" = "macOS" ]; then
echo "::set-output name=ENV_FILE::environment-mac.yaml"
echo "::set-output name=ENV_FILE::environment-mac.yml"
echo "::set-output name=PYTHON_BIN::/usr/local/miniconda/envs/ldm/bin/python"
elif [ "$RUNNER_OS" = "Linux" ]; then
echo "::set-output name=ENV_FILE::environment.yaml"
echo "::set-output name=ENV_FILE::environment.yml"
echo "::set-output name=PYTHON_BIN::/usr/share/miniconda/envs/ldm/bin/python"
fi
- name: Checkout sources

4
.github/workflows/test-dream-conda.yml vendored
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@ -19,10 +19,10 @@ jobs:
run: |
# Note, can't "activate" via github action; specifying the env's python has the same effect
if [ "$RUNNER_OS" = "macOS" ]; then
echo "::set-output name=ENV_FILE::environment-mac.yaml"
echo "::set-output name=ENV_FILE::environment-mac.yml"
echo "::set-output name=PYTHON_BIN::/usr/local/miniconda/envs/ldm/bin/python"
elif [ "$RUNNER_OS" = "Linux" ]; then
echo "::set-output name=ENV_FILE::environment.yaml"
echo "::set-output name=ENV_FILE::environment.yml"
echo "::set-output name=PYTHON_BIN::/usr/share/miniconda/envs/ldm/bin/python"
fi
- name: Checkout sources

137
docs/CHANGELOG.md Normal file
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@ -0,0 +1,137 @@
# **Changelog**
## v1.13 (in process)
- Supports a Google Colab notebook for a standalone server running on Google hardware [Arturo Mendivil](https://github.com/artmen1516)
- WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling [Kevin Gibbons](https://github.com/bakkot)
- WebUI supports incremental display of in-progress images during generation [Kevin Gibbons](https://github.com/bakkot)
- Output directory can be specified on the dream> command line.
- The grid was displaying duplicated images when not enough images to fill the final row [Muhammad Usama](https://github.com/SMUsamaShah)
- Can specify --grid on dream.py command line as the default.
- Miscellaneous internal bug and stability fixes.
---
## v1.12 (28 August 2022)
- Improved file handling, including ability to read prompts from standard input.
(kudos to [Yunsaki](https://github.com/yunsaki)
- The web server is now integrated with the dream.py script. Invoke by adding --web to
the dream.py command arguments.
- Face restoration and upscaling via GFPGAN and Real-ESGAN are now automatically
enabled if the GFPGAN directory is located as a sibling to Stable Diffusion.
VRAM requirements are modestly reduced. Thanks to both [Blessedcoolant](https://github.com/blessedcoolant) and
[Oceanswave](https://github.com/oceanswave) for their work on this.
- You can now swap samplers on the dream> command line. [Blessedcoolant](https://github.com/blessedcoolant)
---
## v1.11 (26 August 2022)
- NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module. (kudos to [Oceanswave](https://github.com/Oceanswave)
- You now can specify a seed of -1 to use the previous image's seed, -2 to use the seed for the image generated before that, etc.
Seed memory only extends back to the previous command, but will work on all images generated with the -n# switch.
- Variant generation support temporarily disabled pending more general solution.
- Created a feature branch named **yunsaki-morphing-dream** which adds experimental support for
iteratively modifying the prompt and its parameters. Please see[ Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86)
for a synopsis of how this works. Note that when this feature is eventually added to the main branch, it will may be modified
significantly.
---
## v1.10 (25 August 2022)
- A barebones but fully functional interactive web server for online generation of txt2img and img2img.
---
## v1.09 (24 August 2022)
- A new -v option allows you to generate multiple variants of an initial image
in img2img mode. (kudos to [Oceanswave](https://github.com/Oceanswave). [
See this discussion in the PR for examples and details on use](https://github.com/lstein/stable-diffusion/pull/71#issuecomment-1226700810))
- Added ability to personalize text to image generation (kudos to [Oceanswave](https://github.com/Oceanswave) and [nicolai256](https://github.com/nicolai256))
- Enabled all of the samplers from k_diffusion
---
## v1.08 (24 August 2022)
- Escape single quotes on the dream> command before trying to parse. This avoids
parse errors.
- Removed instruction to get Python3.8 as first step in Windows install.
Anaconda3 does it for you.
- Added bounds checks for numeric arguments that could cause crashes.
- Cleaned up the copyright and license agreement files.
---
## v1.07 (23 August 2022)
- Image filenames will now never fill gaps in the sequence, but will be assigned the
next higher name in the chosen directory. This ensures that the alphabetic and chronological
sort orders are the same.
---
## v1.06 (23 August 2022)
- Added weighted prompt support contributed by [xraxra](https://github.com/xraxra)
- Example of using weighted prompts to tweak a demonic figure contributed by [bmaltais](https://github.com/bmaltais)
---
## v1.05 (22 August 2022 - after the drop)
- Filenames now use the following formats:
000010.95183149.png -- Two files produced by the same command (e.g. -n2),
000010.26742632.png -- distinguished by a different seed.
000011.455191342.01.png -- Two files produced by the same command using
000011.455191342.02.png -- a batch size>1 (e.g. -b2). They have the same seed.
000011.4160627868.grid#1-4.png -- a grid of four images (-g); the whole grid can
be regenerated with the indicated key
- It should no longer be possible for one image to overwrite another
- You can use the "cd" and "pwd" commands at the dream> prompt to set and retrieve
the path of the output directory.
---
## v1.04 (22 August 2022 - after the drop)
- Updated README to reflect installation of the released weights.
- Suppressed very noisy and inconsequential warning when loading the frozen CLIP
tokenizer.
---
## v1.03 (22 August 2022)
- The original txt2img and img2img scripts from the CompViz repository have been moved into
a subfolder named "orig_scripts", to reduce confusion.
---
## v1.02 (21 August 2022)
- A copy of the prompt and all of its switches and options is now stored in the corresponding
image in a tEXt metadata field named "Dream". You can read the prompt using scripts/images2prompt.py,
or an image editor that allows you to explore the full metadata.
**Please run "conda env update" to load the k_lms dependencies!!**
---
## v1.01 (21 August 2022)
- added k_lms sampling.
**Please run "conda env update" to load the k_lms dependencies!!**
- use half precision arithmetic by default, resulting in faster execution and lower memory requirements
Pass argument --full_precision to dream.py to get slower but more accurate image generation
---
## Links
- **[Read Me](../readme.md)**

12
docs/help/TROUBLESHOOT.md
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@ -13,7 +13,7 @@ incomplete installations or crashes during the install process.
### **QUESTION**
During `conda env create -f environment.yaml`, conda hangs indefinitely.
During `conda env create`, conda hangs indefinitely.
If it is because of the last PIP step (usually stuck in the Git Clone step, you can check the detailed log by this method):
```bash
@ -67,8 +67,8 @@ Reinstall the stable diffusion modules. Enter the `stable-diffusion` directory a
### **SOLUTION**
From within the `stable-diffusion` directory, run `conda env update -f environment.yaml` This is
also frequently the solution to complaints about an unknown function in a module.
From within the `InvokeAI` directory, run `conda env update` This is also frequently the solution to
complaints about an unknown function in a module.
---
@ -83,8 +83,10 @@ There's a feature or bugfix in the Stable Diffusion GitHub that you want to try
If the fix/feature is on the `main` branch, enter the stable-diffusion directory and do a
`git pull`.
Usually this will be sufficient, but if you start to see errors about missing or incorrect modules,
use the command
Usually this will be sufficient, but if you start to see errors about
missing or incorrect modules, use the command `pip install -e .`
and/or `conda env update` (These commands won't break anything.)
`pip install -e .` and/or

2
docs/installation/INSTALL_LINUX.md
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@ -44,7 +44,7 @@ This will create InvokeAI folder where you will follow the rest of the steps.
```
(base) ~/InvokeAI$ conda env create -f environment.yaml
(base) ~/InvokeAI$ conda env create
(base) ~/InvokeAI$ conda activate ldm
(ldm) ~/InvokeAI$
```

60
docs/installation/INSTALL_MAC.md
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@ -147,18 +147,15 @@ python scripts/orig_scripts/txt2img.py \
--plms
```
1. half-precision requires autocast which is unfortunatelly incompatible
## Notes
!!! note
1. half-precision requires autocast which is unfortunately incompatible with the
implementation of pytorch on the M1 architecture. On Macs, --full-precision will
default to True.
`#!bash export PIP_EXISTS_ACTION=w` is a precaution to fix a problem where
```bash
conda env create \
-f environment-mac.yaml
```
did never finish in some situations. So it isn't required but wont hurt.
2. `export PIP_EXISTS_ACTION=w` in the commands above, is a precaution to fix `conda env
create -f environment-mac.yml` never finishing in some situations. So
it isn't required but wont hurt.
---
@ -199,30 +196,23 @@ conda install \
-n ldm
```
If it takes forever to run
If it takes forever to run `conda env create -f environment-mac.yml` you could try to run:
```bash
conda env create \
-f environment-mac.yaml
```
you could try to run:
```bash
git clean -f
conda clean \
--yes \
--all
```
```bash
git clean -f
conda clean \
--yes \
--all
```
Or you could try to completley reset Anaconda:
```bash
conda update \
--force-reinstall \
-y \
-n base \
-c defaults conda
```bash
conda update \
--force-reinstall \
-y \
-n base \
-c defaults conda
```
---
@ -247,11 +237,9 @@ There are several causes of these errors:
```bash
conda deactivate
conda env remove -n ldm
PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-arm64 \
conda env create \
-f environment-mac.yaml
conda env create -f environment-mac.yml
```
4. If you have activated the ldm virtual environment and tried rebuilding it,
maybe the problem could be that I have something installed that you don't and
you'll just need to manually install it. Make sure you activate the virtual
@ -396,9 +384,7 @@ python scripts/preload_models.py
```
This fork already includes a fix for this in
[environment-mac.yaml](https://github.com/invoke-ai/InvokeAI/blob/main/environment-mac.yaml).
---
[environment-mac.yaml](https://github.com/invoke-ai/InvokeAI/blob/main/environment-mac.yml).
### "Could not build wheels for tokenizers"

60
docs/installation/INSTALL_WINDOWS.md
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@ -46,23 +46,26 @@ in the wiki
This will create stable-diffusion folder where you will follow the rest of
the steps.
5. Enter the newly-created stable-diffusion folder. From this step forward make
sure that you are working in the stable-diffusion directory!
5. Enter the newly-created InvokeAI folder. From this step forward make sure that you are working in the InvokeAI directory!
```batch
cd stable-diffusion
cd InvokeAI
```
6. Run the following two commands:
```batch
conda env create -f environment.yaml
conda activate ldm
conda env create (step 6a)
conda activate ldm (step 6b)
```
This will install all python requirements and activate the "ldm" environment
which sets PATH and other environment variables properly.
Note that the long form of the first command is `conda env create -f environment.yml`. If the
environment file isn't specified, conda will default to `environment.yml`. You will need
to provide the `-f` option if you wish to load a different environment file at any point.
7. Run the command:
```batch
@ -77,29 +80,23 @@ in the wiki
8. Now you need to install the weights for the big stable diffusion model.
- For running with the released weights, you will first need to set up an
acount with [Hugging Face](https://huggingface.co).
- Use your credentials to log in, and then point your browser at
[https://huggingface.co/CompVis/stable-diffusion-v-1-4-original](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original).
- You may be asked to sign a license agreement at this point.
- Click on "Files and versions" near the top of the page, and then click on
the file named `sd-v1-4.ckpt`. You'll be taken to a page that prompts you
to click the "download" link. Now save the file somewhere safe on your
local machine.
- The weight file is >4 GB in size, so downloading may take a while.
- For running with the released weights, you will first need to set up an acount with Hugging Face (https://huggingface.co).
- Use your credentials to log in, and then point your browser at https://huggingface.co/CompVis/stable-diffusion-v-1-4-original.
- You may be asked to sign a license agreement at this point.
- Click on "Files and versions" near the top of the page, and then click on the file named `sd-v1-4.ckpt`. You'll be taken to a page that
prompts you to click the "download" link. Now save the file somewhere safe on your local machine.
- The weight file is >4 GB in size, so
downloading may take a while.
Now run the following commands from **within the stable-diffusion directory**
to copy the weights file to the right place:
Now run the following commands from **within the InvokeAI directory** to copy the weights file to the right place:
```batch
mkdir -p models\ldm\stable-diffusion-v1
copy C:\path\to\sd-v1-4.ckpt models\ldm\stable-diffusion-v1\model.ckpt
```
```batch
mkdir -p models\ldm\stable-diffusion-v1
copy C:\path\to\sd-v1-4.ckpt models\ldm\stable-diffusion-v1\model.ckpt
```
Please replace `C:\path\to\sd-v1.4.ckpt` with the correct path to wherever
you stashed this file. If you prefer not to copy or move the .ckpt file, you
may instead create a shortcut to it from within
`models\ldm\stable-diffusion-v1\`.
Please replace `C:\path\to\sd-v1.4.ckpt` with the correct path to wherever you stashed this file. If you prefer not to copy or move the .ckpt file,
you may instead create a shortcut to it from within `models\ldm\stable-diffusion-v1\`.
9. Start generating images!
@ -111,10 +108,7 @@ in the wiki
python scripts\dream.py
```
10. Subsequently, to relaunch the script, first activate the Anaconda command
window (step 3),enter the stable-diffusion directory (step 5,
`cd \path\to\stable-diffusion`), run `conda activate ldm` (step 6b), and
then launch the dream script (step 9).
10. Subsequently, to relaunch the script, first activate the Anaconda command window (step 3),enter the InvokeAI directory (step 5, `cd \path\to\InvokeAI`), run `conda activate ldm` (step 6b), and then launch the dream script (step 9).
**Note:** Tildebyte has written an alternative
["Easy peasy Windows install"](https://github.com/invoke-ai/InvokeAI/wiki/Easy-peasy-Windows-install)
@ -130,9 +124,9 @@ This distribution is changing rapidly. If you used the `git clone` method
latest and greatest version, launch the Anaconda window, enter
`stable-diffusion`, and type:
```batch
git pull
conda env update -f environment.yaml
```
```batch
git pull
conda env update
```
This will bring your local copy into sync with the remote one.

7
docs/other/README-CompViz.md
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@ -39,11 +39,14 @@ lightweight and runs on a GPU with at least 10GB VRAM. See
A suitable [conda](https://conda.io/) environment named `ldm` can be created and
activated with:
```bash
conda env create -f environment.yaml
```
conda env create -f environment.yml
conda activate ldm
```
Note that the first line may be abbreviated `conda env create`, since conda will
look for `environment.yml` by default.
You can also update an existing
[latent diffusion](https://github.com/CompVis/latent-diffusion) environment by
running

2
environment-mac.yaml → environment-mac.yml
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@ -14,7 +14,7 @@ dependencies:
# To determine what the latest versions should be, run:
#
# ```shell
# sed -E 's/ldm/ldm-updated/;20,99s/- ([^=]+)==.+/- \1/' environment-mac.yaml > environment-mac-updated.yml
# sed -E 's/ldm/ldm-updated/;20,99s/- ([^=]+)==.+/- \1/' environment-mac.yml > environment-mac-updated.yml
# CONDA_SUBDIR=osx-arm64 conda env create -f environment-mac-updated.yml && conda list -n ldm-updated | awk ' {print " - " $1 "==" $2;} '
# ```
- albumentations==1.2.1

0
environment.yaml → environment.yml
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