mirror of https://github.com/vladmandic/automatic
post-merge update
Vladimir Mandic
parent
cb72d69970
commit
ee410df5a5
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@ -13,6 +13,7 @@ __pycache__
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*.lock
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*.zip
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*.rar
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*.pyc
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# all dynamic stuff
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/repositories/**/*
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216
README.md
216
README.md
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@ -1,162 +1,80 @@
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# Stable Diffusion web UI
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A browser interface based on Gradio library for Stable Diffusion.
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# Stable Diffusion - Automatic
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*Heavily opinionated custom fork of* <https://github.com/AUTOMATIC1111/stable-diffusion-webui>
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## Features
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[Detailed feature showcase with images](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features):
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- Original txt2img and img2img modes
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- One click install and run script (but you still must install python and git)
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- Outpainting
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- Inpainting
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- Color Sketch
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- Prompt Matrix
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- Stable Diffusion Upscale
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- Attention, specify parts of text that the model should pay more attention to
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- a man in a ((tuxedo)) - will pay more attention to tuxedo
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- a man in a (tuxedo:1.21) - alternative syntax
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- select text and press ctrl+up or ctrl+down to automatically adjust attention to selected text (code contributed by anonymous user)
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- Loopback, run img2img processing multiple times
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- X/Y/Z plot, a way to draw a 3 dimensional plot of images with different parameters
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- Textual Inversion
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- have as many embeddings as you want and use any names you like for them
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- use multiple embeddings with different numbers of vectors per token
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- works with half precision floating point numbers
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- train embeddings on 8GB (also reports of 6GB working)
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- Extras tab with:
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- GFPGAN, neural network that fixes faces
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- CodeFormer, face restoration tool as an alternative to GFPGAN
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- RealESRGAN, neural network upscaler
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- ESRGAN, neural network upscaler with a lot of third party models
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- SwinIR and Swin2SR([see here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2092)), neural network upscalers
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- LDSR, Latent diffusion super resolution upscaling
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- Resizing aspect ratio options
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- Sampling method selection
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- Adjust sampler eta values (noise multiplier)
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- More advanced noise setting options
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- Interrupt processing at any time
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- 4GB video card support (also reports of 2GB working)
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- Correct seeds for batches
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- Live prompt token length validation
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- Generation parameters
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- parameters you used to generate images are saved with that image
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- in PNG chunks for PNG, in EXIF for JPEG
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- can drag the image to PNG info tab to restore generation parameters and automatically copy them into UI
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- can be disabled in settings
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- drag and drop an image/text-parameters to promptbox
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- Read Generation Parameters Button, loads parameters in promptbox to UI
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- Settings page
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- Running arbitrary python code from UI (must run with --allow-code to enable)
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- Mouseover hints for most UI elements
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- Possible to change defaults/mix/max/step values for UI elements via text config
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- Tiling support, a checkbox to create images that can be tiled like textures
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- Progress bar and live image generation preview
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- Can use a separate neural network to produce previews with almost none VRAM or compute requirement
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- Negative prompt, an extra text field that allows you to list what you don't want to see in generated image
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- Styles, a way to save part of prompt and easily apply them via dropdown later
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- Variations, a way to generate same image but with tiny differences
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- Seed resizing, a way to generate same image but at slightly different resolution
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- CLIP interrogator, a button that tries to guess prompt from an image
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- Prompt Editing, a way to change prompt mid-generation, say to start making a watermelon and switch to anime girl midway
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- Batch Processing, process a group of files using img2img
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- Img2img Alternative, reverse Euler method of cross attention control
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- Highres Fix, a convenience option to produce high resolution pictures in one click without usual distortions
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- Reloading checkpoints on the fly
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- Checkpoint Merger, a tab that allows you to merge up to 3 checkpoints into one
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- [Custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Scripts) with many extensions from community
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- [Composable-Diffusion](https://energy-based-model.github.io/Compositional-Visual-Generation-with-Composable-Diffusion-Models/), a way to use multiple prompts at once
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- separate prompts using uppercase `AND`
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- also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`
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- No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
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- DeepDanbooru integration, creates danbooru style tags for anime prompts
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- [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add --xformers to commandline args)
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- via extension: [History tab](https://github.com/yfszzx/stable-diffusion-webui-images-browser): view, direct and delete images conveniently within the UI
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- Generate forever option
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- Training tab
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- hypernetworks and embeddings options
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- Preprocessing images: cropping, mirroring, autotagging using BLIP or deepdanbooru (for anime)
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- Clip skip
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- Hypernetworks
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- Loras (same as Hypernetworks but more pretty)
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- A sparate UI where you can choose, with preview, which embeddings, hypernetworks or Loras to add to your prompt.
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- Can select to load a different VAE from settings screen
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- Estimated completion time in progress bar
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- API
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- Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML.
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- via extension: [Aesthetic Gradients](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients), a way to generate images with a specific aesthetic by using clip images embeds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients))
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- [Stable Diffusion 2.0](https://github.com/Stability-AI/stablediffusion) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20) for instructions
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- [Alt-Diffusion](https://arxiv.org/abs/2211.06679) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#alt-diffusion) for instructions
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- Now without any bad letters!
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- Load checkpoints in safetensors format
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- Eased resolution restriction: generated image's domension must be a multiple of 8 rather than 64
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- Now with a license!
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- Reorder elements in the UI from settings screen
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-
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## Installation and Running
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Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
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<br>
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Alternatively, use online services (like Google Colab):
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## Notes
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- [List of Online Services](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Online-Services)
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Fork is as close as up-to-date with origin as time allows
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All code changes are merged upstream whenever possible
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### Automatic Installation on Windows
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1. Install [Python 3.10.6](https://www.python.org/downloads/windows/), checking "Add Python to PATH"
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2. Install [git](https://git-scm.com/download/win).
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3. Download the stable-diffusion-webui repository, for example by running `git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git`.
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4. Place stable diffusion checkpoint (`model.ckpt`) in the `models/Stable-diffusion` directory (see [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) for where to get it).
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5. Run `webui-user.bat` from Windows Explorer as normal, non-administrator, user.
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Fork adds extra functionality:
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- Ships with additional **extensions**
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e.g. `System Info`, `Steps Animation`, etc.
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- Ships with set of **CLI** tools that rely on *SD API* for execution:
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e.g. `generate`, `train`, `bench`, etc.
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[Full list](<cli/>)
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### Automatic Installation on Linux
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1. Install the dependencies:
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```bash
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# Debian-based:
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sudo apt install wget git python3 python3-venv
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# Red Hat-based:
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sudo dnf install wget git python3
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# Arch-based:
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sudo pacman -S wget git python3
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```
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2. To install in `/home/$(whoami)/stable-diffusion-webui/`, run:
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```bash
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bash <(wget -qO- https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh)
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```
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Simplified start script: `automatic.sh`
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*Existing `webui.sh`/`webui.bat` still exist for backward compatibility, fresh installs to auto-install dependencies, etc.*
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### Installation on Apple Silicon
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> ./automatic.sh
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Find the instructions [here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Installation-on-Apple-Silicon).
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- Start in default mode with optimizations enabled
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## Contributing
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Here's how to add code to this repo: [Contributing](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Contributing)
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> ./automatic.sh env
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## Documentation
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The documentation was moved from this README over to the project's [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki).
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- Print env info and exit
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Example:
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## Credits
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Licenses for borrowed code can be found in `Settings -> Licenses` screen, and also in `html/licenses.html` file.
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Version: c07487a Tue Jan 24 08:04:31 2023 -0500
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Platform: Ubuntu 22.04.1 LTS 5.15.79.1-microsoft-standard-WSL2 x86_64
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Python 3.10.6
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Torch: 2.0.0.dev20230118+cu118 CUDA: 11.8 cuDNN: 8700 GPU: NVIDIA GeForce RTX 3060 Arch: (8, 6)
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- Stable Diffusion - https://github.com/CompVis/stable-diffusion, https://github.com/CompVis/taming-transformers
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- k-diffusion - https://github.com/crowsonkb/k-diffusion.git
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- GFPGAN - https://github.com/TencentARC/GFPGAN.git
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- CodeFormer - https://github.com/sczhou/CodeFormer
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- ESRGAN - https://github.com/xinntao/ESRGAN
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- SwinIR - https://github.com/JingyunLiang/SwinIR
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- Swin2SR - https://github.com/mv-lab/swin2sr
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- LDSR - https://github.com/Hafiidz/latent-diffusion
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- MiDaS - https://github.com/isl-org/MiDaS
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- Ideas for optimizations - https://github.com/basujindal/stable-diffusion
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- Cross Attention layer optimization - Doggettx - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.
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- Cross Attention layer optimization - InvokeAI, lstein - https://github.com/invoke-ai/InvokeAI (originally http://github.com/lstein/stable-diffusion)
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- Sub-quadratic Cross Attention layer optimization - Alex Birch (https://github.com/Birch-san/diffusers/pull/1), Amin Rezaei (https://github.com/AminRezaei0x443/memory-efficient-attention)
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- Textual Inversion - Rinon Gal - https://github.com/rinongal/textual_inversion (we're not using his code, but we are using his ideas).
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- Idea for SD upscale - https://github.com/jquesnelle/txt2imghd
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- Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot
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- CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator
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- Idea for Composable Diffusion - https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch
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- xformers - https://github.com/facebookresearch/xformers
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- DeepDanbooru - interrogator for anime diffusers https://github.com/KichangKim/DeepDanbooru
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- Sampling in float32 precision from a float16 UNet - marunine for the idea, Birch-san for the example Diffusers implementation (https://github.com/Birch-san/diffusers-play/tree/92feee6)
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- Instruct pix2pix - Tim Brooks (star), Aleksander Holynski (star), Alexei A. Efros (no star) - https://github.com/timothybrooks/instruct-pix2pix
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- Security advice - RyotaK
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- Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.
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- (You)
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> ./automatic.sh install
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- Install requirements and exit
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> ./automatic.sh public
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- Start with listen on public IP with authentication enabled
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> ./automatic.sh clean
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- Start with all optimizations disabled
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Use this for troubleshooting
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<br>
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## Differences
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Fork does differ in few things:
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- Drops compatibility with `python` **3.7** and requires **3.9**
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- Updated **Python** libraries to latest known compatible versions
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e.g. `accelerate`, `transformers`, `numpy`, etc.
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- Includes opinionated **System** and **Options** configuration
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e.g. `samplers`, `upscalers`, etc.
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- Includes reskinned **UI**
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Black and orange dark theme with fixed width options panels and larger previews
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- Includes **SD2** configuration files
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- Uses simplified folder structure
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e.g. `/train`, `/outputs/*`
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- Modified training templates
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Only Python library which is not auto-updated is `PyTorch` itself as that is very system specific
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For some Torch optimizations notes, see Wiki
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Fork is compatible with regular **PyTorch 1.13** as well as pre-release of **PyTorch 2.0**
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See [Wiki](https://github.com/vladmandic/automatic/wiki) for **Torch** optimization notes
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<br>
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## Docs
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Everything is in [Wiki](https://github.com/vladmandic/automatic/wiki)
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Except my current [TODO](TODO.md)
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@ -13,6 +13,7 @@ from modules.sdapi import get, post, close
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from modules.grid import grid
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default = 'sd-v15-runwayml.ckpt [cc6cb27103]'
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embeddings = ['blonde', 'bruntette', 'sexy', 'naked', 'mia', 'lin', 'kelly', 'hanna', 'rreid-random-v0']
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exclude = ['sd-v20', 'sd-v21', 'inpainting', 'pix2pix']
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prompt = "photo of beautiful woman <embedding>, photograph, posing, pose, high detailed, intricate, elegant, sharp focus, skin texture, looking forward, facing camera, 135mm, shot on dslr, canon 5d, 4k, modelshoot style, cinematic lighting"
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@ -69,16 +70,16 @@ async def models(params):
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models.append(short)
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log.info({ 'models preview' })
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log.info({ 'models': len(models), 'excluded': len(excluded) })
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log.info({ 'embeddings': len(embeddings) })
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log.info({ 'batch size': options.generate.batch_size })
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log.info({ 'embeddings': embeddings })
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log.info({ 'total jobs': len(models) * len(embeddings) * options.generate.batch_size, 'per-model': len(embeddings) * options.generate.batch_size })
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log.info(json.dumps(options, indent=2))
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# models = ['sd-v15-runwayml.ckpt [cc6cb27103]']
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for model in models:
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fn = os.path.join(params.output, model + '.jpg')
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if os.path.exists(fn):
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log.info({ 'model': model, 'model preview exists': fn })
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if os.path.exists(fn) and len(params.input) == 0: # if model preview exists and not manually included
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log.info({ 'model preview exists': model })
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continue
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log.info({ 'model load': model })
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opt = await get('/sdapi/v1/options')
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opt['sd_model_checkpoint'] = model
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await post('/sdapi/v1/options', opt)
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t0 = time.time()
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for embedding in embeddings:
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options.generate.prompt = prompt.replace('<embedding>', f'\"{embedding}\"')
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log.info({ 'model': model, 'embedding': embedding, 'prompt': options.generate.prompt })
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log.info({ 'model generating': model, 'embedding': embedding, 'prompt': options.generate.prompt })
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data = await generate(options = options, quiet=True)
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if 'image' in data:
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for img in data['image']:
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image = grid(images = images, labels = labels, border = 8)
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image.save(fn)
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t = t1 - t0
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its = 1.0 * options.generate.batch_size * len(images) / t
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log.info({ 'model': model, 'created preview': fn, 'images': len(images), 'grid': [image.width, image.height], 'time': round(t, 2), 'its': round(its, 2) })
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its = 1.0 * options.generate.steps * len(images) / t
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log.info({ 'model preview created': model, 'image': fn, 'images': len(images), 'grid': [image.width, image.height], 'time': round(t, 2), 'its': round(its, 2) })
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opt = await get('/sdapi/v1/options')
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if opt['sd_model_checkpoint'] != default:
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log.info({ 'model set default': default })
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opt['sd_model_checkpoint'] = default
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await post('/sdapi/v1/options', opt)
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await close()
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"training_enable_tensorboard": false,
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"training_tensorboard_save_images": false,
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"training_tensorboard_flush_every": 120,
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"sd_model_checkpoint": "zeipher-f222",
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"sd_model_checkpoint": "sd-v15-runwayml.ckpt [cc6cb27103]",
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"sd_checkpoint_cache": 0,
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"sd_vae_checkpoint_cache": 0,
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"sd_vae": "vae-ft-mse-840000-ema-pruned.ckpt",
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@ -144,7 +144,7 @@
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"sdweb-merge-board",
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"ScuNET"
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],
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"sd_checkpoint_hash": "22fdccddef1a2466198c02851f26d76cd5a08430d231083ee4958de662c1a8e0",
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"sd_checkpoint_hash": "cc6cb27103417325ff94f52b7a5d2dde45a7515b25c255d8e396c90014281516",
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"ldsr_steps": 100,
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"ldsr_cached": false,
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"SWIN_tile": 192,
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@ -179,5 +179,6 @@
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"lora_apply_to_outputs": false,
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"outdir_ip2p_samples": "outputs/ip2p-images",
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"postprocessing_enable_in_main_ui": [],
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"postprocessing_operation_order": []
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"postprocessing_operation_order": [],
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"sd_lora": "None"
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}
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@ -1 +1 @@
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Subproject commit a89b56057be0d13d28e0a3149243a9b188e8aa6e
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Subproject commit 4748f4a90e180ecfd585e46d7338659eeacafe77
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@ -1 +1 @@
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Subproject commit e91497c0dea92cb6fcccdd1109a648be4b86bea0
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Subproject commit 4325abb42b6ad25f9e8816b4787cb71307e2994c
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@ -1 +1 @@
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Subproject commit 82a51b31f37439dd571747196820e42ef26d4572
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Subproject commit 50e4a2d86f8eb95a48799b4c3c3c31d930698c67
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@ -37,7 +37,7 @@ parser.add_argument("--no-half-vae", action='store_true', help="do not switch th
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parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)")
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parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")
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parser.add_argument("--embeddings-dir", type=str, default=os.path.join(data_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
|
||||
parser.add_argument("--textual-inversion-templates-dir", type=str, default=os.path.join(script_path, 'textual_inversion_templates'), help="directory with textual inversion templates")
|
||||
parser.add_argument("--textual-inversion-templates-dir", type=str, default=os.path.join(script_path, 'train/templates'), help="directory with textual inversion templates")
|
||||
parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")
|
||||
parser.add_argument("--localizations-dir", type=str, default=os.path.join(script_path, 'localizations'), help="localizations directory")
|
||||
parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui")
|
||||
|
|
@ -105,6 +105,7 @@ parser.add_argument("--tls-keyfile", type=str, help="Partially enables TLS, requ
|
|||
parser.add_argument("--tls-certfile", type=str, help="Partially enables TLS, requires --tls-keyfile to fully function", default=None)
|
||||
parser.add_argument("--server-name", type=str, help="Sets hostname of server", default=None)
|
||||
parser.add_argument("--gradio-queue", action='store_true', help="Uses gradio queue; experimental option; breaks restart UI button")
|
||||
parser.add_argument("--compile", type=str, help="Use Torch Dynamo compile with specified backend", default=None)
|
||||
|
||||
|
||||
script_loading.preload_extensions(extensions.extensions_dir, parser)
|
||||
|
|
|
|||
|
|
@ -842,5 +842,7 @@
|
|||
"customscript/xyz_grid.py/img2img/Include Sub Grids/visible": true,
|
||||
"customscript/xyz_grid.py/img2img/Include Sub Grids/value": false,
|
||||
"customscript/xyz_grid.py/img2img/Keep -1 for seeds/visible": true,
|
||||
"customscript/xyz_grid.py/img2img/Keep -1 for seeds/value": false
|
||||
"customscript/xyz_grid.py/img2img/Keep -1 for seeds/value": false,
|
||||
"img2img/Inpaint batch mask directory (required for inpaint batch processing only)/visible": true,
|
||||
"img2img/Inpaint batch mask directory (required for inpaint batch processing only)/value": ""
|
||||
}
|
||||
|
|
@ -0,0 +1,85 @@
|
|||
@echo off
|
||||
|
||||
if not defined PYTHON (set PYTHON=python)
|
||||
if not defined VENV_DIR (set "VENV_DIR=%~dp0%venv")
|
||||
|
||||
|
||||
set ERROR_REPORTING=FALSE
|
||||
|
||||
mkdir tmp 2>NUL
|
||||
|
||||
%PYTHON% -c "" >tmp/stdout.txt 2>tmp/stderr.txt
|
||||
if %ERRORLEVEL% == 0 goto :check_pip
|
||||
echo Couldn't launch python
|
||||
goto :show_stdout_stderr
|
||||
|
||||
:check_pip
|
||||
%PYTHON% -mpip --help >tmp/stdout.txt 2>tmp/stderr.txt
|
||||
if %ERRORLEVEL% == 0 goto :start_venv
|
||||
if "%PIP_INSTALLER_LOCATION%" == "" goto :show_stdout_stderr
|
||||
%PYTHON% "%PIP_INSTALLER_LOCATION%" >tmp/stdout.txt 2>tmp/stderr.txt
|
||||
if %ERRORLEVEL% == 0 goto :start_venv
|
||||
echo Couldn't install pip
|
||||
goto :show_stdout_stderr
|
||||
|
||||
:start_venv
|
||||
if ["%VENV_DIR%"] == ["-"] goto :skip_venv
|
||||
if ["%SKIP_VENV%"] == ["1"] goto :skip_venv
|
||||
|
||||
dir "%VENV_DIR%\Scripts\Python.exe" >tmp/stdout.txt 2>tmp/stderr.txt
|
||||
if %ERRORLEVEL% == 0 goto :activate_venv
|
||||
|
||||
for /f "delims=" %%i in ('CALL %PYTHON% -c "import sys; print(sys.executable)"') do set PYTHON_FULLNAME="%%i"
|
||||
echo Creating venv in directory %VENV_DIR% using python %PYTHON_FULLNAME%
|
||||
%PYTHON_FULLNAME% -m venv "%VENV_DIR%" >tmp/stdout.txt 2>tmp/stderr.txt
|
||||
if %ERRORLEVEL% == 0 goto :activate_venv
|
||||
echo Unable to create venv in directory "%VENV_DIR%"
|
||||
goto :show_stdout_stderr
|
||||
|
||||
:activate_venv
|
||||
set PYTHON="%VENV_DIR%\Scripts\Python.exe"
|
||||
echo venv %PYTHON%
|
||||
|
||||
:skip_venv
|
||||
if [%ACCELERATE%] == ["True"] goto :accelerate
|
||||
goto :launch
|
||||
|
||||
:accelerate
|
||||
echo Checking for accelerate
|
||||
set ACCELERATE="%VENV_DIR%\Scripts\accelerate.exe"
|
||||
if EXIST %ACCELERATE% goto :accelerate_launch
|
||||
|
||||
:launch
|
||||
%PYTHON% launch.py %*
|
||||
pause
|
||||
exit /b
|
||||
|
||||
:accelerate_launch
|
||||
echo Accelerating
|
||||
%ACCELERATE% launch --num_cpu_threads_per_process=6 launch.py
|
||||
pause
|
||||
exit /b
|
||||
|
||||
:show_stdout_stderr
|
||||
|
||||
echo.
|
||||
echo exit code: %errorlevel%
|
||||
|
||||
for /f %%i in ("tmp\stdout.txt") do set size=%%~zi
|
||||
if %size% equ 0 goto :show_stderr
|
||||
echo.
|
||||
echo stdout:
|
||||
type tmp\stdout.txt
|
||||
|
||||
:show_stderr
|
||||
for /f %%i in ("tmp\stderr.txt") do set size=%%~zi
|
||||
if %size% equ 0 goto :show_stderr
|
||||
echo.
|
||||
echo stderr:
|
||||
type tmp\stderr.txt
|
||||
|
||||
:endofscript
|
||||
|
||||
echo.
|
||||
echo Launch unsuccessful. Exiting.
|
||||
pause
|
||||
2
wiki
2
wiki
|
|
@ -1 +1 @@
|
|||
Subproject commit d475aa073b421bfe695326dbc9aedd9100c2425a
|
||||
Subproject commit e3290140e6cfdb57b523dbbb0aba90963ec90138
|
||||
Loading…
Reference in New Issue