├── .github ├── ISSUE_TEMPLATE │ ├── bug_report.md │ └── feature_request.md └── workflows │ ├── tauri.yaml │ └── test.yaml ├── .gitignore ├── .vscode └── extensions.json ├── LICENSE ├── README.md ├── index.html ├── package.json ├── public ├── tauri.svg └── vite.svg ├── src-tauri ├── .gitignore ├── Cargo.lock ├── Cargo.toml ├── build.rs ├── gooey_config.json ├── icons │ ├── 128x128.png │ ├── 128x128@2x.png │ ├── 32x32.png │ ├── Square107x107Logo.png │ ├── Square142x142Logo.png │ ├── Square150x150Logo.png │ ├── Square284x284Logo.png │ ├── Square30x30Logo.png │ ├── Square310x310Logo.png │ ├── Square44x44Logo.png │ ├── Square71x71Logo.png │ ├── Square89x89Logo.png │ ├── StoreLogo.png │ ├── icon.icns │ ├── icon.ico │ └── icon.png ├── src │ └── main.rs └── tauri.conf.json ├── src ├── App.css ├── App.tsx ├── Gpu.ts ├── assets │ └── react.svg ├── commands │ ├── convert.test.ts │ ├── convert.ts │ ├── docker.test.ts │ ├── docker.ts │ ├── dreambooth.test.ts │ ├── dreambooth.ts │ └── runner.ts ├── components │ ├── ConfigTrainer.tsx │ ├── Gallery.tsx │ ├── ImagePicker.tsx │ ├── Trainer.tsx │ ├── Training.tsx │ └── utils.ts ├── docker.ts ├── main.tsx ├── state.ts ├── style.css ├── vite-env.d.ts └── vite.config.ts ├── tsconfig.json ├── tsconfig.node.json ├── vite.config.ts └── yarn.lock /.github/ISSUE_TEMPLATE/bug_report.md: -------------------------------------------------------------------------------- 1 | --- 2 | name: Bug report 3 | about: Create a report to help us improve 4 | title: '' 5 | labels: '' 6 | assignees: '' 7 | 8 | --- 9 | 10 | **Describe the bug** 11 | A clear and concise description of what the bug is. 12 | 13 | **To Reproduce** 14 | Steps to reproduce the behavior: 15 | 1. Go to '...' 16 | 2. Click on '....' 17 | 3. Scroll down to '....' 18 | 4. See error 19 | 20 | **Expected behavior** 21 | A clear and concise description of what you expected to happen. 22 | 23 | **Screenshots** 24 | If applicable, add screenshots to help explain your problem. 25 | 26 | **Desktop (please complete the following information):** 27 | - OS: [e.g. iOS] 28 | - Browser [e.g. chrome, safari] 29 | - Version [e.g. 22] 30 | - GPU: [eg. GTX 3060] 31 | 32 | **Additional context** 33 | Add any other context about the problem here. 34 | -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/feature_request.md: -------------------------------------------------------------------------------- 1 | --- 2 | name: Feature request 3 | about: Suggest an idea for this project 4 | title: '' 5 | labels: '' 6 | assignees: '' 7 | 8 | --- 9 | 10 | **Is your feature request related to a problem? Please describe.** 11 | A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] 12 | 13 | **Describe the solution you'd like** 14 | A clear and concise description of what you want to happen. 15 | 16 | **Describe alternatives you've considered** 17 | A clear and concise description of any alternative solutions or features you've considered. 18 | 19 | **Additional context** 20 | Add any other context or screenshots about the feature request here. 21 | -------------------------------------------------------------------------------- /.github/workflows/tauri.yaml: -------------------------------------------------------------------------------- 1 | name: Release 2 | on: 3 | push: 4 | tags: 5 | - 'v*' 6 | workflow_dispatch: 7 | 8 | jobs: 9 | release: 10 | strategy: 11 | fail-fast: false 12 | matrix: 13 | platform: [ubuntu-latest, windows-latest] 14 | runs-on: ${{ matrix.platform }} 15 | steps: 16 | - name: Checkout repository 17 | uses: actions/checkout@v2 18 | 19 | - name: Node.js setup 20 | uses: actions/setup-node@v1 21 | with: 22 | node-version: 16 23 | 24 | - name: Rust setup 25 | uses: actions-rs/toolchain@v1 26 | with: 27 | toolchain: stable 28 | 29 | - name: Install dependencies (ubuntu only) 30 | if: matrix.platform == 'ubuntu-latest' 31 | run: | 32 | sudo apt-get update 33 | sudo apt-get install -y libgtk-3-dev webkit2gtk-4.0 libappindicator3-dev librsvg2-dev patchelf 34 | - name: Install app dependencies and build web 35 | run: yarn && yarn build 36 | 37 | - name: Build the app 38 | uses: tauri-apps/tauri-action@v0 39 | 40 | env: 41 | GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} 42 | with: 43 | tagName: v__VERSION__ # tauri-action replaces \_\_VERSION\_\_ with the app version 44 | releaseName: 'v__VERSION__' 45 | releaseBody: 'See the assets to download this version and install.' 46 | releaseDraft: false 47 | prerelease: false 48 | -------------------------------------------------------------------------------- /.github/workflows/test.yaml: -------------------------------------------------------------------------------- 1 | name: "test" 2 | on: 3 | push: 4 | workflow_dispatch: 5 | 6 | jobs: 7 | test-tauri: 8 | strategy: 9 | fail-fast: false 10 | matrix: 11 | platform: [macos-latest, ubuntu-20.04, windows-latest] 12 | 13 | runs-on: ${{ matrix.platform }} 14 | steps: 15 | - uses: actions/checkout@v2 16 | - name: setup node 17 | uses: actions/setup-node@v1 18 | with: 19 | node-version: 16 20 | - name: install Rust stable 21 | uses: actions-rs/toolchain@v1 22 | with: 23 | toolchain: stable 24 | - name: install dependencies (ubuntu only) 25 | if: matrix.platform == 'ubuntu-20.04' 26 | run: | 27 | sudo apt-get update 28 | sudo apt-get install -y libgtk-3-dev webkit2gtk-4.0 libappindicator3-dev librsvg2-dev patchelf 29 | - name: build the app and test it 30 | run: yarn && yarn test -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Logs 2 | logs 3 | *.log 4 | npm-debug.log* 5 | yarn-debug.log* 6 | yarn-error.log* 7 | pnpm-debug.log* 8 | lerna-debug.log* 9 | 10 | node_modules 11 | dist 12 | dist-ssr 13 | *.local 14 | 15 | # Editor directories and files 16 | .vscode/* 17 | !.vscode/extensions.json 18 | .idea 19 | .DS_Store 20 | *.suo 21 | *.ntvs* 22 | *.njsproj 23 | *.sln 24 | *.sw? 25 | -------------------------------------------------------------------------------- /.vscode/extensions.json: -------------------------------------------------------------------------------- 1 | { 2 | "recommendations": ["tauri-apps.tauri-vscode", "rust-lang.rust-analyzer"] 3 | } 4 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2022 smy20011 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Dreambooth Gui 2 | 3 | Provides a easy-to-use gui for users to train Dreambooth with custom images. This 4 | Gui supports any NVIDIA card with >10GB VRAM. 5 | 6 | ![BuildStatus](https://github.com/smy20011/dreambooth-gui/actions/workflows/test.yaml/badge.svg) 7 | 8 | ## Screenshots 9 | 10 | ![203261990-a1920337-1687-4503-84bd-ffcd599d3c42](https://user-images.githubusercontent.com/1560175/204433541-28882839-4e55-4a11-b732-210ece68a213.jpg) 11 | ![203261994-f541593a-65e1-4a4e-9acc-6a05d5ce310d](https://user-images.githubusercontent.com/1560175/204433550-f4d73012-4cc3-4812-b3dc-e171195dd6fe.jpg) 12 | ![203261997-cc3c8456-a7fc-4162-b4fd-d953b4c5fbcd](https://user-images.githubusercontent.com/1560175/204433559-9aacdd94-32c1-445b-8fdc-6aa03a8a67a0.jpg) 13 | 14 | 15 | 16 | ## Highlights 17 | 18 | 1. Automatically decide training params that fit your available VRAM. 19 | 2. Easy to use Gui for you to select images. 20 | 3. Support prior preservation training with class images. 21 | 4. Automatically cache models. 22 | 23 | ## Install (Windows) 24 | 25 | 1. Download and install docker from https://www.docker.com/ 26 | 2. Setup WSL2 for windows. https://learn.microsoft.com/en-us/windows/wsl/install 27 | 3. If you find 'WSL 2 installation is incomplete' when starting docker, you can follow this video to fix it. https://www.youtube.com/watch?v=Ffzud5xLH4c 28 | 4. [Download](https://github.com/smy20011/dreambooth-gui/releases/latest) and install dreambooth-gui_*_x64_en-US.msi 29 | from [release page](https://github.com/smy20011/dreambooth-gui/releases/latest). 30 | 5. Run the dreambooth-gui as administrator. 31 | 32 | ## Install (Linux) 33 | 34 | 1. Download and install docker from https://www.docker.com/ 35 | 2. Download AppImage from [release page](https://github.com/smy20011/dreambooth-gui/releases/latest). 36 | 3. Run `chmod +x dreambooth-gui_*amd64.AppImage` 37 | 4. Run `sudo dreambooth-gui_*amd64.AppImage` 38 | 39 | ## FAQs 40 | 41 | 1. Failed to create directory 42 | 43 | Please make sure you have the latest verion of GUI. This is a old bug that fixed in v0.1.3 44 | 45 | 2. PIL.UnidentifiedImageEnnon: cannot identify image file 46 | 47 | Make sure the instance image folder only have image. 48 | 49 | 3. Read-only file system error 50 | 51 | Make sure you have enough space in C(or home folder) before running the Gui. 52 | 53 | 4. Train with SD v2 54 | 55 | Training with SD v2 is supported. However, you need to type `stabilityai/stable-diffusion-2` as model name. Local v2 training is not supported right now. 56 | 57 | 5. I have other questions! 58 | 59 | Please use the [discussion](https://github.com/smy20011/dreambooth-gui/discussions) page for Q&A. 60 | 61 | I will convert FAQs to a bug if necessary. I perfer to keep the issue section clean but keep getting questions 62 | that I answered before. 63 | 64 | 65 | ## Roadmap 66 | 67 | - [X] Refactor the state management. 68 | - [X] Better error handling to cover FAQs. 69 | - [ ] Allow advanced customization 70 | - [X] Load local model. 71 | - [ ] Save/Load config for users. 72 | - [ ] Save model / pics in places other than $APP_DIR 73 | - [ ] Better training progress report. 74 | - [X] Create a dialog when training finished. 75 | - [ ] Progress bar. 76 | - [X] Support model converstion. 77 | 78 | ## Additional Resources 79 | 80 | 1. Someone in japan write a [doc](https://gigazine.net/gsc_news/en/20221103-dreambooth-gui/) regarding how to use it. 81 | -------------------------------------------------------------------------------- /index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | Tauri + React + TS 8 | 9 | 10 | 11 |
12 | 13 | 14 | 15 | -------------------------------------------------------------------------------- /package.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "dreambooth-gui", 3 | "private": true, 4 | "version": "0.0.0", 5 | "type": "module", 6 | "license": "MIT", 7 | "scripts": { 8 | "dev": "vite", 9 | "build": "tsc && vite build", 10 | "preview": "vite preview", 11 | "tauri": "tauri", 12 | "test": "vitest" 13 | }, 14 | "dependencies": { 15 | "@emotion/react": "^11.10.4", 16 | "@emotion/styled": "^11.10.4", 17 | "@mui/material": "^5.10.8", 18 | "@tauri-apps/api": "^1.1.0", 19 | "bootstrap": "^5.2.2", 20 | "jotai": "^1.8.6", 21 | "react": "^18.2.0", 22 | "react-bootstrap": "^2.5.0", 23 | "react-dom": "^18.2.0", 24 | "react-hook-form": "^7.36.1" 25 | }, 26 | "devDependencies": { 27 | "@tauri-apps/cli": "^1.1.0", 28 | "@types/lodash": "^4.14.186", 29 | "@types/node": "^18.7.10", 30 | "@types/react": "^18.0.15", 31 | "@types/react-dom": "^18.0.6", 32 | "@vitejs/plugin-react": "^2.0.0", 33 | "lodash": "^4.17.21", 34 | "typescript": "^4.6.4", 35 | "vite": "^3.0.2", 36 | "vitest": "^0.24.3" 37 | } 38 | } 39 | -------------------------------------------------------------------------------- /public/tauri.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | -------------------------------------------------------------------------------- /public/vite.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /src-tauri/.gitignore: -------------------------------------------------------------------------------- 1 | # Generated by Cargo 2 | # will have compiled files and executables 3 | /target/ 4 | 5 | -------------------------------------------------------------------------------- /src-tauri/Cargo.toml: -------------------------------------------------------------------------------- 1 | [package] 2 | name = "dreambooth-gui" 3 | version = "0.0.0" 4 | description = "A Tauri App" 5 | authors = ["you"] 6 | license = "" 7 | repository = "" 8 | edition = "2021" 9 | rust-version = "1.57" 10 | 11 | # See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html 12 | 13 | [build-dependencies] 14 | tauri-build = { version = "1.1", features = [] } 15 | 16 | [dependencies] 17 | serde_json = "1.0" 18 | serde = { version = "1.0", features = ["derive"] } 19 | tauri = { version = "1.1", features = ["api-all"] } 20 | nvml-wrapper = { version = "0.8.0", features = ["serde"] } 21 | 22 | [features] 23 | # by default Tauri runs in production mode 24 | # when `tauri dev` runs it is executed with `cargo run --no-default-features` if `devPath` is an URL 25 | default = [ "custom-protocol"] 26 | # this feature is used used for production builds where `devPath` points to the filesystem 27 | # DO NOT remove this 28 | custom-protocol = [ "tauri/custom-protocol" ] 29 | -------------------------------------------------------------------------------- /src-tauri/build.rs: -------------------------------------------------------------------------------- 1 | fn main() { 2 | tauri_build::build() 3 | } 4 | -------------------------------------------------------------------------------- /src-tauri/gooey_config.json: -------------------------------------------------------------------------------- 1 | { 2 | "language": "english", 3 | "target": "'/home/smy/miniconda3/envs/dev/bin/python' -u 'train_dreambooth.py'", 4 | "suppress_gooey_flag": false, 5 | "program_name": "dreambooth", 6 | "program_description": "Simple example of a training script.", 7 | "sidebar_title": "Actions", 8 | "default_size": [ 9 | 610, 10 | 530 11 | ], 12 | "auto_start": false, 13 | "show_advanced": true, 14 | "run_validators": true, 15 | "encoding": "utf-8", 16 | "show_stop_warning": true, 17 | "show_success_modal": true, 18 | "show_failure_modal": true, 19 | "force_stop_is_error": true, 20 | "poll_external_updates": false, 21 | "return_to_config": false, 22 | "show_restart_button": true, 23 | "requires_shell": true, 24 | "menu": [], 25 | "clear_before_run": false, 26 | "fullscreen": false, 27 | "use_legacy_titles": true, 28 | "num_required_cols": 2, 29 | "num_optional_cols": 2, 30 | "manual_start": false, 31 | "monospace_display": false, 32 | "image_dir": "::gooey/default", 33 | "language_dir": "/home/smy/miniconda3/envs/dev/lib/python3.9/site-packages/gooey/languages", 34 | "progress_regex": null, 35 | "progress_expr": null, 36 | "hide_progress_msg": false, 37 | "timing_options": { 38 | "show_time_remaining": false, 39 | "hide_time_remaining_on_complete": true 40 | }, 41 | "disable_progress_bar_animation": false, 42 | "disable_stop_button": false, 43 | "navigation": "SIDEBAR", 44 | "show_sidebar": false, 45 | "tabbed_groups": true, 46 | "group_by_type": true, 47 | "body_bg_color": "#f0f0f0", 48 | "header_bg_color": "#ffffff", 49 | "header_height": 80, 50 | "header_show_title": true, 51 | "header_show_subtitle": true, 52 | "header_image_center": false, 53 | "footer_bg_color": "#f0f0f0", 54 | "sidebar_bg_color": "#f2f2f2", 55 | "terminal_panel_color": "#F0F0F0", 56 | "terminal_font_color": "#000000", 57 | "terminal_font_family": null, 58 | "terminal_font_weight": 400, 59 | "terminal_font_size": null, 60 | "richtext_controls": false, 61 | "error_color": "#ea7878", 62 | "layout": "standard", 63 | "widgets": { 64 | "dreambooth": { 65 | "command": "::gooey/default", 66 | "name": "dreambooth", 67 | "help": null, 68 | "description": "", 69 | "contents": [ 70 | { 71 | "name": "Basic", 72 | "items": [ 73 | { 74 | "id": "--training_folder", 75 | "type": "TextField", 76 | "cli_type": "optional", 77 | "required": true, 78 | "data": { 79 | "display_name": "training_folder", 80 | "help": "Path to a folder that store all training data.", 81 | "required": true, 82 | "nargs": "", 83 | "commands": [ 84 | "--training_folder" 85 | ], 86 | "choices": [], 87 | "default": "/home/smy/Downloads/cyan", 88 | "dest": "training_folder" 89 | }, 90 | "options": { 91 | "error_color": "#ea7878", 92 | "label_color": "#000000", 93 | "help_color": "#363636", 94 | "full_width": false, 95 | "validator": { 96 | "type": "ExpressionValidator", 97 | "test": "user_input and not user_input.isspace()", 98 | "message": "This field is required" 99 | }, 100 | "external_validator": { 101 | "cmd": "" 102 | } 103 | } 104 | }, 105 | { 106 | "id": "--pretrained_model_name_or_path", 107 | "type": "TextField", 108 | "cli_type": "optional", 109 | "required": true, 110 | "data": { 111 | "display_name": "pretrained_model_name_or_path", 112 | "help": "Path to pretrained model or model identifier from huggingface.co/models.", 113 | "required": true, 114 | "nargs": "", 115 | "commands": [ 116 | "--pretrained_model_name_or_path" 117 | ], 118 | "choices": [], 119 | "default": "hakurei/waifu-diffusion", 120 | "dest": "pretrained_model_name_or_path" 121 | }, 122 | "options": { 123 | "error_color": "#ea7878", 124 | "label_color": "#000000", 125 | "help_color": "#363636", 126 | "full_width": false, 127 | "validator": { 128 | "type": "ExpressionValidator", 129 | "test": "user_input and not user_input.isspace()", 130 | "message": "This field is required" 131 | }, 132 | "external_validator": { 133 | "cmd": "" 134 | } 135 | } 136 | }, 137 | { 138 | "id": "--instance_data_dir", 139 | "type": "TextField", 140 | "cli_type": "optional", 141 | "required": true, 142 | "data": { 143 | "display_name": "instance_data_dir", 144 | "help": "A folder containing the training data of instance images.", 145 | "required": true, 146 | "nargs": "", 147 | "commands": [ 148 | "--instance_data_dir" 149 | ], 150 | "choices": [], 151 | "default": "/home/smy/Downloads/cyan/instance", 152 | "dest": "instance_data_dir" 153 | }, 154 | "options": { 155 | "error_color": "#ea7878", 156 | "label_color": "#000000", 157 | "help_color": "#363636", 158 | "full_width": false, 159 | "validator": { 160 | "type": "ExpressionValidator", 161 | "test": "user_input and not user_input.isspace()", 162 | "message": "This field is required" 163 | }, 164 | "external_validator": { 165 | "cmd": "" 166 | } 167 | } 168 | }, 169 | { 170 | "id": "--instance_prompt", 171 | "type": "TextField", 172 | "cli_type": "optional", 173 | "required": false, 174 | "data": { 175 | "display_name": "instance_prompt", 176 | "help": "The prompt with identifier specifing the instance", 177 | "required": false, 178 | "nargs": "", 179 | "commands": [ 180 | "--instance_prompt" 181 | ], 182 | "choices": [], 183 | "default": "a sks girl", 184 | "dest": "instance_prompt" 185 | }, 186 | "options": { 187 | "error_color": "#ea7878", 188 | "label_color": "#000000", 189 | "help_color": "#363636", 190 | "full_width": false, 191 | "validator": { 192 | "type": "ExpressionValidator", 193 | "test": "True", 194 | "message": "" 195 | }, 196 | "external_validator": { 197 | "cmd": "" 198 | } 199 | } 200 | }, 201 | { 202 | "id": "--resolution", 203 | "type": "TextField", 204 | "cli_type": "optional", 205 | "required": false, 206 | "data": { 207 | "display_name": "resolution", 208 | "help": "The resolution for input images, all the images in the train/validation dataset will be resized to this resolution", 209 | "required": false, 210 | "nargs": "", 211 | "commands": [ 212 | "--resolution" 213 | ], 214 | "choices": [], 215 | "default": 512, 216 | "dest": "resolution" 217 | }, 218 | "options": { 219 | "error_color": "#ea7878", 220 | "label_color": "#000000", 221 | "help_color": "#363636", 222 | "full_width": false, 223 | "validator": { 224 | "type": "ExpressionValidator", 225 | "test": "True", 226 | "message": "" 227 | }, 228 | "external_validator": { 229 | "cmd": "" 230 | } 231 | } 232 | }, 233 | { 234 | "id": "--auth_token", 235 | "type": "TextField", 236 | "cli_type": "optional", 237 | "required": true, 238 | "data": { 239 | "display_name": "auth_token", 240 | "help": "Huggingface auth token to access model, https://huggingface.co/settings/tokens", 241 | "required": true, 242 | "nargs": "", 243 | "commands": [ 244 | "--auth_token" 245 | ], 246 | "choices": [], 247 | "default": "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", 248 | "dest": "auth_token" 249 | }, 250 | "options": { 251 | "error_color": "#ea7878", 252 | "label_color": "#000000", 253 | "help_color": "#363636", 254 | "full_width": false, 255 | "validator": { 256 | "type": "ExpressionValidator", 257 | "test": "user_input and not user_input.isspace()", 258 | "message": "This field is required" 259 | }, 260 | "external_validator": { 261 | "cmd": "" 262 | } 263 | } 264 | } 265 | ], 266 | "groups": [], 267 | "description": "Basic dreambooth training config.", 268 | "options": { 269 | "label_color": "#000000", 270 | "description_color": "#363636", 271 | "legacy": { 272 | "required_cols": 2, 273 | "optional_cols": 2 274 | }, 275 | "columns": 2, 276 | "padding": 10, 277 | "show_border": false 278 | } 279 | }, 280 | { 281 | "name": "Prior Preservation", 282 | "items": [ 283 | { 284 | "id": "--class_data_dir", 285 | "type": "TextField", 286 | "cli_type": "optional", 287 | "required": false, 288 | "data": { 289 | "display_name": "class_data_dir", 290 | "help": "A folder containing the training data of class images.", 291 | "required": false, 292 | "nargs": "", 293 | "commands": [ 294 | "--class_data_dir" 295 | ], 296 | "choices": [], 297 | "default": null, 298 | "dest": "class_data_dir" 299 | }, 300 | "options": { 301 | "error_color": "#ea7878", 302 | "label_color": "#000000", 303 | "help_color": "#363636", 304 | "full_width": false, 305 | "validator": { 306 | "type": "ExpressionValidator", 307 | "test": "True", 308 | "message": "" 309 | }, 310 | "external_validator": { 311 | "cmd": "" 312 | } 313 | } 314 | }, 315 | { 316 | "id": "--class_prompt", 317 | "type": "TextField", 318 | "cli_type": "optional", 319 | "required": false, 320 | "data": { 321 | "display_name": "class_prompt", 322 | "help": "The prompt to specify images in the same class as provided intance images.", 323 | "required": false, 324 | "nargs": "", 325 | "commands": [ 326 | "--class_prompt" 327 | ], 328 | "choices": [], 329 | "default": null, 330 | "dest": "class_prompt" 331 | }, 332 | "options": { 333 | "error_color": "#ea7878", 334 | "label_color": "#000000", 335 | "help_color": "#363636", 336 | "full_width": false, 337 | "validator": { 338 | "type": "ExpressionValidator", 339 | "test": "True", 340 | "message": "" 341 | }, 342 | "external_validator": { 343 | "cmd": "" 344 | } 345 | } 346 | }, 347 | { 348 | "id": "--with_prior_preservation", 349 | "type": "CheckBox", 350 | "cli_type": "optional", 351 | "required": false, 352 | "data": { 353 | "display_name": "with_prior_preservation", 354 | "help": "Flag to add prior perservation loss.", 355 | "required": false, 356 | "nargs": "", 357 | "commands": [ 358 | "--with_prior_preservation" 359 | ], 360 | "choices": [], 361 | "default": false, 362 | "dest": "with_prior_preservation" 363 | }, 364 | "options": { 365 | "error_color": "#ea7878", 366 | "label_color": "#000000", 367 | "help_color": "#363636", 368 | "full_width": false, 369 | "validator": { 370 | "type": "ExpressionValidator", 371 | "test": "True", 372 | "message": "" 373 | }, 374 | "external_validator": { 375 | "cmd": "" 376 | } 377 | } 378 | }, 379 | { 380 | "id": "--prior_loss_weight", 381 | "type": "TextField", 382 | "cli_type": "optional", 383 | "required": false, 384 | "data": { 385 | "display_name": "prior_loss_weight", 386 | "help": "The weight of prior preservation loss.", 387 | "required": false, 388 | "nargs": "", 389 | "commands": [ 390 | "--prior_loss_weight" 391 | ], 392 | "choices": [], 393 | "default": 1.0, 394 | "dest": "prior_loss_weight" 395 | }, 396 | "options": { 397 | "error_color": "#ea7878", 398 | "label_color": "#000000", 399 | "help_color": "#363636", 400 | "full_width": false, 401 | "validator": { 402 | "type": "ExpressionValidator", 403 | "test": "True", 404 | "message": "" 405 | }, 406 | "external_validator": { 407 | "cmd": "" 408 | } 409 | } 410 | }, 411 | { 412 | "id": "--num_class_images", 413 | "type": "TextField", 414 | "cli_type": "optional", 415 | "required": false, 416 | "data": { 417 | "display_name": "num_class_images", 418 | "help": "Minimal class images for prior perversation loss. If not have enough images, additional images will be sampled with class_prompt.", 419 | "required": false, 420 | "nargs": "", 421 | "commands": [ 422 | "--num_class_images" 423 | ], 424 | "choices": [], 425 | "default": 100, 426 | "dest": "num_class_images" 427 | }, 428 | "options": { 429 | "error_color": "#ea7878", 430 | "label_color": "#000000", 431 | "help_color": "#363636", 432 | "full_width": false, 433 | "validator": { 434 | "type": "ExpressionValidator", 435 | "test": "True", 436 | "message": "" 437 | }, 438 | "external_validator": { 439 | "cmd": "" 440 | } 441 | } 442 | } 443 | ], 444 | "groups": [], 445 | "description": "Prior-preservation is used to avoid overfitting and language-drift.", 446 | "options": { 447 | "label_color": "#000000", 448 | "description_color": "#363636", 449 | "legacy": { 450 | "required_cols": 2, 451 | "optional_cols": 2 452 | }, 453 | "columns": 2, 454 | "padding": 10, 455 | "show_border": false 456 | } 457 | }, 458 | { 459 | "name": "Training Config", 460 | "items": [ 461 | { 462 | "id": "--train_batch_size", 463 | "type": "TextField", 464 | "cli_type": "optional", 465 | "required": false, 466 | "data": { 467 | "display_name": "train_batch_size", 468 | "help": "Batch size (per device) for the training dataloader.", 469 | "required": false, 470 | "nargs": "", 471 | "commands": [ 472 | "--train_batch_size" 473 | ], 474 | "choices": [], 475 | "default": 1, 476 | "dest": "train_batch_size" 477 | }, 478 | "options": { 479 | "error_color": "#ea7878", 480 | "label_color": "#000000", 481 | "help_color": "#363636", 482 | "full_width": false, 483 | "validator": { 484 | "type": "ExpressionValidator", 485 | "test": "True", 486 | "message": "" 487 | }, 488 | "external_validator": { 489 | "cmd": "" 490 | } 491 | } 492 | }, 493 | { 494 | "id": "--sample_batch_size", 495 | "type": "TextField", 496 | "cli_type": "optional", 497 | "required": false, 498 | "data": { 499 | "display_name": "sample_batch_size", 500 | "help": "Batch size (per device) for sampling images.", 501 | "required": false, 502 | "nargs": "", 503 | "commands": [ 504 | "--sample_batch_size" 505 | ], 506 | "choices": [], 507 | "default": 1, 508 | "dest": "sample_batch_size" 509 | }, 510 | "options": { 511 | "error_color": "#ea7878", 512 | "label_color": "#000000", 513 | "help_color": "#363636", 514 | "full_width": false, 515 | "validator": { 516 | "type": "ExpressionValidator", 517 | "test": "True", 518 | "message": "" 519 | }, 520 | "external_validator": { 521 | "cmd": "" 522 | } 523 | } 524 | }, 525 | { 526 | "id": "--num_train_epochs", 527 | "type": "TextField", 528 | "cli_type": "optional", 529 | "required": false, 530 | "data": { 531 | "display_name": "num_train_epochs", 532 | "help": null, 533 | "required": false, 534 | "nargs": "", 535 | "commands": [ 536 | "--num_train_epochs" 537 | ], 538 | "choices": [], 539 | "default": 1, 540 | "dest": "num_train_epochs" 541 | }, 542 | "options": { 543 | "error_color": "#ea7878", 544 | "label_color": "#000000", 545 | "help_color": "#363636", 546 | "full_width": false, 547 | "validator": { 548 | "type": "ExpressionValidator", 549 | "test": "True", 550 | "message": "" 551 | }, 552 | "external_validator": { 553 | "cmd": "" 554 | } 555 | } 556 | }, 557 | { 558 | "id": "--max_train_steps", 559 | "type": "TextField", 560 | "cli_type": "optional", 561 | "required": false, 562 | "data": { 563 | "display_name": "max_train_steps", 564 | "help": "Total number of training steps to perform. If provided, overrides num_train_epochs.", 565 | "required": false, 566 | "nargs": "", 567 | "commands": [ 568 | "--max_train_steps" 569 | ], 570 | "choices": [], 571 | "default": 800, 572 | "dest": "max_train_steps" 573 | }, 574 | "options": { 575 | "error_color": "#ea7878", 576 | "label_color": "#000000", 577 | "help_color": "#363636", 578 | "full_width": false, 579 | "validator": { 580 | "type": "ExpressionValidator", 581 | "test": "True", 582 | "message": "" 583 | }, 584 | "external_validator": { 585 | "cmd": "" 586 | } 587 | } 588 | }, 589 | { 590 | "id": "--gradient_accumulation_steps", 591 | "type": "TextField", 592 | "cli_type": "optional", 593 | "required": false, 594 | "data": { 595 | "display_name": "gradient_accumulation_steps", 596 | "help": "Number of updates steps to accumulate before performing a backward/update pass.", 597 | "required": false, 598 | "nargs": "", 599 | "commands": [ 600 | "--gradient_accumulation_steps" 601 | ], 602 | "choices": [], 603 | "default": 1, 604 | "dest": "gradient_accumulation_steps" 605 | }, 606 | "options": { 607 | "error_color": "#ea7878", 608 | "label_color": "#000000", 609 | "help_color": "#363636", 610 | "full_width": false, 611 | "validator": { 612 | "type": "ExpressionValidator", 613 | "test": "True", 614 | "message": "" 615 | }, 616 | "external_validator": { 617 | "cmd": "" 618 | } 619 | } 620 | }, 621 | { 622 | "id": "--gradient_checkpointing", 623 | "type": "CheckBox", 624 | "cli_type": "optional", 625 | "required": false, 626 | "data": { 627 | "display_name": "gradient_checkpointing", 628 | "help": "Whether or not to use gradient checkpointing to save memory at the expense of slower backward pass.", 629 | "required": false, 630 | "nargs": "", 631 | "commands": [ 632 | "--gradient_checkpointing" 633 | ], 634 | "choices": [], 635 | "default": true, 636 | "dest": "gradient_checkpointing" 637 | }, 638 | "options": { 639 | "error_color": "#ea7878", 640 | "label_color": "#000000", 641 | "help_color": "#363636", 642 | "full_width": false, 643 | "validator": { 644 | "type": "ExpressionValidator", 645 | "test": "True", 646 | "message": "" 647 | }, 648 | "external_validator": { 649 | "cmd": "" 650 | } 651 | } 652 | }, 653 | { 654 | "id": "--use_8bit_adam", 655 | "type": "CheckBox", 656 | "cli_type": "optional", 657 | "required": false, 658 | "data": { 659 | "display_name": "use_8bit_adam", 660 | "help": "Whether or not to use 8-bit Adam from bitsandbytes.", 661 | "required": false, 662 | "nargs": "", 663 | "commands": [ 664 | "--use_8bit_adam" 665 | ], 666 | "choices": [], 667 | "default": true, 668 | "dest": "use_8bit_adam" 669 | }, 670 | "options": { 671 | "error_color": "#ea7878", 672 | "label_color": "#000000", 673 | "help_color": "#363636", 674 | "full_width": false, 675 | "validator": { 676 | "type": "ExpressionValidator", 677 | "test": "True", 678 | "message": "" 679 | }, 680 | "external_validator": { 681 | "cmd": "" 682 | } 683 | } 684 | }, 685 | { 686 | "id": "--mixed_precision", 687 | "type": "Dropdown", 688 | "cli_type": "optional", 689 | "required": false, 690 | "data": { 691 | "display_name": "mixed_precision", 692 | "help": "Whether to use mixed precision. Choosebetween fp16 and bf16 (bfloat16). Bf16 requires PyTorch >= 1.10.and an Nvidia Ampere GPU.", 693 | "required": false, 694 | "nargs": "", 695 | "commands": [ 696 | "--mixed_precision" 697 | ], 698 | "choices": [ 699 | "no", 700 | "fp16", 701 | "bf16" 702 | ], 703 | "default": "no", 704 | "dest": "mixed_precision" 705 | }, 706 | "options": { 707 | "error_color": "#ea7878", 708 | "label_color": "#000000", 709 | "help_color": "#363636", 710 | "full_width": false, 711 | "validator": { 712 | "type": "ExpressionValidator", 713 | "test": "True", 714 | "message": "" 715 | }, 716 | "external_validator": { 717 | "cmd": "" 718 | } 719 | } 720 | }, 721 | { 722 | "id": "--local_rank", 723 | "type": "TextField", 724 | "cli_type": "optional", 725 | "required": false, 726 | "data": { 727 | "display_name": "local_rank", 728 | "help": "For distributed training: local_rank", 729 | "required": false, 730 | "nargs": "", 731 | "commands": [ 732 | "--local_rank" 733 | ], 734 | "choices": [], 735 | "default": -1, 736 | "dest": "local_rank" 737 | }, 738 | "options": { 739 | "error_color": "#ea7878", 740 | "label_color": "#000000", 741 | "help_color": "#363636", 742 | "full_width": false, 743 | "validator": { 744 | "type": "ExpressionValidator", 745 | "test": "True", 746 | "message": "" 747 | }, 748 | "external_validator": { 749 | "cmd": "" 750 | } 751 | } 752 | } 753 | ], 754 | "groups": [], 755 | "description": "Basic config for training", 756 | "options": { 757 | "label_color": "#000000", 758 | "description_color": "#363636", 759 | "legacy": { 760 | "required_cols": 2, 761 | "optional_cols": 2 762 | }, 763 | "columns": 2, 764 | "padding": 10, 765 | "show_border": false 766 | } 767 | }, 768 | { 769 | "name": "Learning rate config", 770 | "items": [ 771 | { 772 | "id": "--learning_rate", 773 | "type": "TextField", 774 | "cli_type": "optional", 775 | "required": false, 776 | "data": { 777 | "display_name": "learning_rate", 778 | "help": "Initial learning rate (after the potential warmup period) to use.", 779 | "required": false, 780 | "nargs": "", 781 | "commands": [ 782 | "--learning_rate" 783 | ], 784 | "choices": [], 785 | "default": 5e-06, 786 | "dest": "learning_rate" 787 | }, 788 | "options": { 789 | "error_color": "#ea7878", 790 | "label_color": "#000000", 791 | "help_color": "#363636", 792 | "full_width": false, 793 | "validator": { 794 | "type": "ExpressionValidator", 795 | "test": "True", 796 | "message": "" 797 | }, 798 | "external_validator": { 799 | "cmd": "" 800 | } 801 | } 802 | }, 803 | { 804 | "id": "--scale_lr", 805 | "type": "CheckBox", 806 | "cli_type": "optional", 807 | "required": false, 808 | "data": { 809 | "display_name": "scale_lr", 810 | "help": "Scale the learning rate by the number of GPUs, gradient accumulation steps, and batch size.", 811 | "required": false, 812 | "nargs": "", 813 | "commands": [ 814 | "--scale_lr" 815 | ], 816 | "choices": [], 817 | "default": false, 818 | "dest": "scale_lr" 819 | }, 820 | "options": { 821 | "error_color": "#ea7878", 822 | "label_color": "#000000", 823 | "help_color": "#363636", 824 | "full_width": false, 825 | "validator": { 826 | "type": "ExpressionValidator", 827 | "test": "True", 828 | "message": "" 829 | }, 830 | "external_validator": { 831 | "cmd": "" 832 | } 833 | } 834 | }, 835 | { 836 | "id": "--lr_scheduler", 837 | "type": "TextField", 838 | "cli_type": "optional", 839 | "required": false, 840 | "data": { 841 | "display_name": "lr_scheduler", 842 | "help": "The scheduler type to use. Choose between [\"linear\", \"cosine\", \"cosine_with_restarts\", \"polynomial\", \"constant\", \"constant_with_warmup\"]", 843 | "required": false, 844 | "nargs": "", 845 | "commands": [ 846 | "--lr_scheduler" 847 | ], 848 | "choices": [], 849 | "default": "constant", 850 | "dest": "lr_scheduler" 851 | }, 852 | "options": { 853 | "error_color": "#ea7878", 854 | "label_color": "#000000", 855 | "help_color": "#363636", 856 | "full_width": false, 857 | "validator": { 858 | "type": "ExpressionValidator", 859 | "test": "True", 860 | "message": "" 861 | }, 862 | "external_validator": { 863 | "cmd": "" 864 | } 865 | } 866 | }, 867 | { 868 | "id": "--lr_warmup_steps", 869 | "type": "TextField", 870 | "cli_type": "optional", 871 | "required": false, 872 | "data": { 873 | "display_name": "lr_warmup_steps", 874 | "help": "Number of steps for the warmup in the lr scheduler.", 875 | "required": false, 876 | "nargs": "", 877 | "commands": [ 878 | "--lr_warmup_steps" 879 | ], 880 | "choices": [], 881 | "default": 500, 882 | "dest": "lr_warmup_steps" 883 | }, 884 | "options": { 885 | "error_color": "#ea7878", 886 | "label_color": "#000000", 887 | "help_color": "#363636", 888 | "full_width": false, 889 | "validator": { 890 | "type": "ExpressionValidator", 891 | "test": "True", 892 | "message": "" 893 | }, 894 | "external_validator": { 895 | "cmd": "" 896 | } 897 | } 898 | }, 899 | { 900 | "id": "--tokenizer_name", 901 | "type": "TextField", 902 | "cli_type": "optional", 903 | "required": false, 904 | "data": { 905 | "display_name": "tokenizer_name", 906 | "help": "Pretrained tokenizer name or path if not the same as model_name", 907 | "required": false, 908 | "nargs": "", 909 | "commands": [ 910 | "--tokenizer_name" 911 | ], 912 | "choices": [], 913 | "default": null, 914 | "dest": "tokenizer_name" 915 | }, 916 | "options": { 917 | "error_color": "#ea7878", 918 | "label_color": "#000000", 919 | "help_color": "#363636", 920 | "full_width": false, 921 | "validator": { 922 | "type": "ExpressionValidator", 923 | "test": "True", 924 | "message": "" 925 | }, 926 | "external_validator": { 927 | "cmd": "" 928 | } 929 | } 930 | }, 931 | { 932 | "id": "--seed", 933 | "type": "TextField", 934 | "cli_type": "optional", 935 | "required": false, 936 | "data": { 937 | "display_name": "seed", 938 | "help": "A seed for reproducible training.", 939 | "required": false, 940 | "nargs": "", 941 | "commands": [ 942 | "--seed" 943 | ], 944 | "choices": [], 945 | "default": null, 946 | "dest": "seed" 947 | }, 948 | "options": { 949 | "error_color": "#ea7878", 950 | "label_color": "#000000", 951 | "help_color": "#363636", 952 | "full_width": false, 953 | "validator": { 954 | "type": "ExpressionValidator", 955 | "test": "True", 956 | "message": "" 957 | }, 958 | "external_validator": { 959 | "cmd": "" 960 | } 961 | } 962 | }, 963 | { 964 | "id": "--center_crop", 965 | "type": "CheckBox", 966 | "cli_type": "optional", 967 | "required": false, 968 | "data": { 969 | "display_name": "center_crop", 970 | "help": "Whether to center crop images before resizing to resolution", 971 | "required": false, 972 | "nargs": "", 973 | "commands": [ 974 | "--center_crop" 975 | ], 976 | "choices": [], 977 | "default": false, 978 | "dest": "center_crop" 979 | }, 980 | "options": { 981 | "error_color": "#ea7878", 982 | "label_color": "#000000", 983 | "help_color": "#363636", 984 | "full_width": false, 985 | "validator": { 986 | "type": "ExpressionValidator", 987 | "test": "True", 988 | "message": "" 989 | }, 990 | "external_validator": { 991 | "cmd": "" 992 | } 993 | } 994 | }, 995 | { 996 | "id": "--adam_beta1", 997 | "type": "TextField", 998 | "cli_type": "optional", 999 | "required": false, 1000 | "data": { 1001 | "display_name": "adam_beta1", 1002 | "help": "The beta1 parameter for the Adam optimizer.", 1003 | "required": false, 1004 | "nargs": "", 1005 | "commands": [ 1006 | "--adam_beta1" 1007 | ], 1008 | "choices": [], 1009 | "default": 0.9, 1010 | "dest": "adam_beta1" 1011 | }, 1012 | "options": { 1013 | "error_color": "#ea7878", 1014 | "label_color": "#000000", 1015 | "help_color": "#363636", 1016 | "full_width": false, 1017 | "validator": { 1018 | "type": "ExpressionValidator", 1019 | "test": "True", 1020 | "message": "" 1021 | }, 1022 | "external_validator": { 1023 | "cmd": "" 1024 | } 1025 | } 1026 | }, 1027 | { 1028 | "id": "--adam_beta2", 1029 | "type": "TextField", 1030 | "cli_type": "optional", 1031 | "required": false, 1032 | "data": { 1033 | "display_name": "adam_beta2", 1034 | "help": "The beta2 parameter for the Adam optimizer.", 1035 | "required": false, 1036 | "nargs": "", 1037 | "commands": [ 1038 | "--adam_beta2" 1039 | ], 1040 | "choices": [], 1041 | "default": 0.999, 1042 | "dest": "adam_beta2" 1043 | }, 1044 | "options": { 1045 | "error_color": "#ea7878", 1046 | "label_color": "#000000", 1047 | "help_color": "#363636", 1048 | "full_width": false, 1049 | "validator": { 1050 | "type": "ExpressionValidator", 1051 | "test": "True", 1052 | "message": "" 1053 | }, 1054 | "external_validator": { 1055 | "cmd": "" 1056 | } 1057 | } 1058 | }, 1059 | { 1060 | "id": "--adam_weight_decay", 1061 | "type": "TextField", 1062 | "cli_type": "optional", 1063 | "required": false, 1064 | "data": { 1065 | "display_name": "adam_weight_decay", 1066 | "help": "Weight decay to use.", 1067 | "required": false, 1068 | "nargs": "", 1069 | "commands": [ 1070 | "--adam_weight_decay" 1071 | ], 1072 | "choices": [], 1073 | "default": 0.01, 1074 | "dest": "adam_weight_decay" 1075 | }, 1076 | "options": { 1077 | "error_color": "#ea7878", 1078 | "label_color": "#000000", 1079 | "help_color": "#363636", 1080 | "full_width": false, 1081 | "validator": { 1082 | "type": "ExpressionValidator", 1083 | "test": "True", 1084 | "message": "" 1085 | }, 1086 | "external_validator": { 1087 | "cmd": "" 1088 | } 1089 | } 1090 | }, 1091 | { 1092 | "id": "--adam_epsilon", 1093 | "type": "TextField", 1094 | "cli_type": "optional", 1095 | "required": false, 1096 | "data": { 1097 | "display_name": "adam_epsilon", 1098 | "help": "Epsilon value for the Adam optimizer", 1099 | "required": false, 1100 | "nargs": "", 1101 | "commands": [ 1102 | "--adam_epsilon" 1103 | ], 1104 | "choices": [], 1105 | "default": 1e-08, 1106 | "dest": "adam_epsilon" 1107 | }, 1108 | "options": { 1109 | "error_color": "#ea7878", 1110 | "label_color": "#000000", 1111 | "help_color": "#363636", 1112 | "full_width": false, 1113 | "validator": { 1114 | "type": "ExpressionValidator", 1115 | "test": "True", 1116 | "message": "" 1117 | }, 1118 | "external_validator": { 1119 | "cmd": "" 1120 | } 1121 | } 1122 | }, 1123 | { 1124 | "id": "--max_grad_norm", 1125 | "type": "TextField", 1126 | "cli_type": "optional", 1127 | "required": false, 1128 | "data": { 1129 | "display_name": "max_grad_norm", 1130 | "help": "Max gradient norm.", 1131 | "required": false, 1132 | "nargs": "", 1133 | "commands": [ 1134 | "--max_grad_norm" 1135 | ], 1136 | "choices": [], 1137 | "default": 1.0, 1138 | "dest": "max_grad_norm" 1139 | }, 1140 | "options": { 1141 | "error_color": "#ea7878", 1142 | "label_color": "#000000", 1143 | "help_color": "#363636", 1144 | "full_width": false, 1145 | "validator": { 1146 | "type": "ExpressionValidator", 1147 | "test": "True", 1148 | "message": "" 1149 | }, 1150 | "external_validator": { 1151 | "cmd": "" 1152 | } 1153 | } 1154 | } 1155 | ], 1156 | "groups": [], 1157 | "description": "Fine tune learning rate", 1158 | "options": { 1159 | "label_color": "#000000", 1160 | "description_color": "#363636", 1161 | "legacy": { 1162 | "required_cols": 2, 1163 | "optional_cols": 2 1164 | }, 1165 | "columns": 2, 1166 | "padding": 10, 1167 | "show_border": false 1168 | } 1169 | }, 1170 | { 1171 | "name": "Push to Huggingface Hub", 1172 | "items": [ 1173 | { 1174 | "id": "--push_to_hub", 1175 | "type": "CheckBox", 1176 | "cli_type": "optional", 1177 | "required": false, 1178 | "data": { 1179 | "display_name": "push_to_hub", 1180 | "help": "Whether or not to push the model to the Hub.", 1181 | "required": false, 1182 | "nargs": "", 1183 | "commands": [ 1184 | "--push_to_hub" 1185 | ], 1186 | "choices": [], 1187 | "default": false, 1188 | "dest": "push_to_hub" 1189 | }, 1190 | "options": { 1191 | "error_color": "#ea7878", 1192 | "label_color": "#000000", 1193 | "help_color": "#363636", 1194 | "full_width": false, 1195 | "validator": { 1196 | "type": "ExpressionValidator", 1197 | "test": "True", 1198 | "message": "" 1199 | }, 1200 | "external_validator": { 1201 | "cmd": "" 1202 | } 1203 | } 1204 | }, 1205 | { 1206 | "id": "--hub_token", 1207 | "type": "TextField", 1208 | "cli_type": "optional", 1209 | "required": false, 1210 | "data": { 1211 | "display_name": "hub_token", 1212 | "help": "The token to use to push to the Model Hub.", 1213 | "required": false, 1214 | "nargs": "", 1215 | "commands": [ 1216 | "--hub_token" 1217 | ], 1218 | "choices": [], 1219 | "default": null, 1220 | "dest": "hub_token" 1221 | }, 1222 | "options": { 1223 | "error_color": "#ea7878", 1224 | "label_color": "#000000", 1225 | "help_color": "#363636", 1226 | "full_width": false, 1227 | "validator": { 1228 | "type": "ExpressionValidator", 1229 | "test": "True", 1230 | "message": "" 1231 | }, 1232 | "external_validator": { 1233 | "cmd": "" 1234 | } 1235 | } 1236 | }, 1237 | { 1238 | "id": "--hub_model_id", 1239 | "type": "TextField", 1240 | "cli_type": "optional", 1241 | "required": false, 1242 | "data": { 1243 | "display_name": "hub_model_id", 1244 | "help": "The name of the repository to keep in sync with the local `output_dir`.", 1245 | "required": false, 1246 | "nargs": "", 1247 | "commands": [ 1248 | "--hub_model_id" 1249 | ], 1250 | "choices": [], 1251 | "default": null, 1252 | "dest": "hub_model_id" 1253 | }, 1254 | "options": { 1255 | "error_color": "#ea7878", 1256 | "label_color": "#000000", 1257 | "help_color": "#363636", 1258 | "full_width": false, 1259 | "validator": { 1260 | "type": "ExpressionValidator", 1261 | "test": "True", 1262 | "message": "" 1263 | }, 1264 | "external_validator": { 1265 | "cmd": "" 1266 | } 1267 | } 1268 | } 1269 | ], 1270 | "groups": [], 1271 | "description": "Whether or not push model to huggingface hub", 1272 | "options": { 1273 | "label_color": "#000000", 1274 | "description_color": "#363636", 1275 | "legacy": { 1276 | "required_cols": 2, 1277 | "optional_cols": 2 1278 | }, 1279 | "columns": 2, 1280 | "padding": 10, 1281 | "show_border": false 1282 | } 1283 | } 1284 | ] 1285 | } 1286 | } 1287 | } -------------------------------------------------------------------------------- /src-tauri/icons/128x128.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smy20011/dreambooth-gui/f9c5ca6964b371ffc82497536ccb81699ee4735e/src-tauri/icons/128x128.png -------------------------------------------------------------------------------- /src-tauri/icons/128x128@2x.png: 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-------------------------------------------------------------------------------- /src-tauri/src/main.rs: -------------------------------------------------------------------------------- 1 | #![cfg_attr( 2 | all(not(debug_assertions), target_os = "windows"), 3 | windows_subsystem = "windows" 4 | )] 5 | 6 | use std::str; 7 | 8 | use nvml_wrapper::{error::NvmlError, struct_wrappers::device::MemoryInfo, Nvml}; 9 | use serde::{Deserialize, Serialize}; 10 | 11 | // Learn more about Tauri commands at https://tauri.app/v1/guides/features/command 12 | #[tauri::command] 13 | fn greet(name: &str) -> String { 14 | format!("Hello, {}! You've been greeted from Rust!", name) 15 | } 16 | 17 | #[derive(Serialize, Deserialize)] 18 | struct GpuInfo { 19 | name: String, 20 | meminfo: MemoryInfo, 21 | } 22 | 23 | fn gpu_info_impl() -> Result { 24 | let nvml = Nvml::init()?; 25 | let device = nvml.device_by_index(0)?; 26 | 27 | return Ok(GpuInfo { 28 | name: device.name()?, 29 | meminfo: device.memory_info()?, 30 | }); 31 | } 32 | 33 | #[tauri::command] 34 | async fn gpu_info() -> Result { 35 | gpu_info_impl().map_err(|e| e.to_string()) 36 | } 37 | 38 | fn main() { 39 | tauri::Builder::default() 40 | .invoke_handler(tauri::generate_handler![greet, gpu_info]) 41 | .run(tauri::generate_context!()) 42 | .expect("error while running tauri application"); 43 | } 44 | -------------------------------------------------------------------------------- /src-tauri/tauri.conf.json: -------------------------------------------------------------------------------- 1 | { 2 | "build": { 3 | "beforeDevCommand": "yarn dev", 4 | "beforeBuildCommand": "yarn build", 5 | "devPath": "http://localhost:1420", 6 | "distDir": "../dist" 7 | }, 8 | "package": { 9 | "productName": "dreambooth-gui", 10 | "version": "0.1.11" 11 | }, 12 | "tauri": { 13 | "allowlist": { 14 | "all": true, 15 | "fs": { 16 | "all": true, 17 | "scope": [ 18 | "*" 19 | ] 20 | }, 21 | "shell": { 22 | "all": true, 23 | "execute": true, 24 | "scope": [ 25 | { 26 | "name": "docker", 27 | "cmd": "docker", 28 | "args": true 29 | } 30 | ] 31 | } 32 | }, 33 | "bundle": { 34 | "active": true, 35 | "category": "DeveloperTool", 36 | "copyright": "", 37 | "deb": { 38 | "depends": [] 39 | }, 40 | "externalBin": [], 41 | "icon": [ 42 | "icons/32x32.png", 43 | "icons/128x128.png", 44 | "icons/128x128@2x.png", 45 | "icons/icon.icns", 46 | "icons/icon.ico" 47 | ], 48 | "identifier": "smy20011.dreambooth", 49 | "longDescription": "", 50 | "macOS": { 51 | "entitlements": null, 52 | "exceptionDomain": "", 53 | "frameworks": [], 54 | "providerShortName": null, 55 | "signingIdentity": null 56 | }, 57 | "resources": [ 58 | "gooey_config.json" 59 | ], 60 | "shortDescription": "", 61 | "targets": "all", 62 | "windows": { 63 | "certificateThumbprint": null, 64 | "digestAlgorithm": "sha256", 65 | "timestampUrl": "" 66 | } 67 | }, 68 | "security": { 69 | "csp": null 70 | }, 71 | "updater": { 72 | "active": false 73 | }, 74 | "windows": [ 75 | { 76 | "fullscreen": false, 77 | "height": 800, 78 | "resizable": true, 79 | "title": "dreambooth-gui", 80 | "width": 800 81 | } 82 | ] 83 | } 84 | } -------------------------------------------------------------------------------- /src/App.css: -------------------------------------------------------------------------------- 1 | .logo.vite:hover { 2 | filter: drop-shadow(0 0 2em #747bff); 3 | } 4 | 5 | .logo.react:hover { 6 | filter: drop-shadow(0 0 2em #61dafb); 7 | } 8 | -------------------------------------------------------------------------------- /src/App.tsx: -------------------------------------------------------------------------------- 1 | import { Suspense } from "react"; 2 | import { Container } from "react-bootstrap"; 3 | import "./App.css"; 4 | import Trainer from "./components/Trainer"; 5 | 6 | 7 | function App() { 8 | return ( 9 | 10 | 11 | 12 | 13 | 14 | ); 15 | } 16 | 17 | export default App; 18 | -------------------------------------------------------------------------------- /src/Gpu.ts: -------------------------------------------------------------------------------- 1 | import { invoke } from "@tauri-apps/api"; 2 | 3 | export interface MemoryInfo { 4 | free: number; 5 | total: number; 6 | used: number; 7 | } 8 | 9 | export interface GpuInfo { 10 | name: string; 11 | meminfo: MemoryInfo; 12 | } 13 | export function GetGpuInfo(): Promise { 14 | return invoke('gpu_info'); 15 | } 16 | -------------------------------------------------------------------------------- /src/assets/react.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /src/commands/convert.test.ts: -------------------------------------------------------------------------------- 1 | import { assert, expect, test } from 'vitest' 2 | import Converter from './convert'; 3 | 4 | test('Convert Commands', () => { 5 | const convert = new Converter("/a", "/b"); 6 | const command = convert.getDiffuserToCkptCommand(); 7 | expect(command.executable).toEqual("python"); 8 | expect(command.arguments).toEqual([ 9 | convert.diffuserToOriginScript, 10 | "--model_path=/a", 11 | "--checkpoint_path=/b/model.ckpt", 12 | ]); 13 | expect(command.environment).toBeUndefined(); 14 | }); -------------------------------------------------------------------------------- /src/commands/convert.ts: -------------------------------------------------------------------------------- 1 | import { Command } from "./runner"; 2 | 3 | export default class Converter { 4 | constructor( 5 | public source: string, 6 | public dest: string, 7 | public diffuserToOriginScript = "/diffusers/scripts/convert_diffusers_to_original_stable_diffusion.py", 8 | public originToDiffuerScript = "/diffusers/scripts/convert_original_stable_diffusion_to_diffusers.py", 9 | ) { } 10 | 11 | public getDiffuserToCkptCommand(): Command { 12 | return { 13 | executable: "python", 14 | arguments: [ 15 | this.diffuserToOriginScript, 16 | `--model_path=${this.source}`, 17 | `--checkpoint_path=${this.dest}/model.ckpt` 18 | ] 19 | } 20 | } 21 | 22 | public getCkptToDiffuserCommand(): Command { 23 | return { 24 | executable: "python", 25 | arguments: [ 26 | this.originToDiffuerScript, 27 | `--checkpoint_path=${this.source}`, 28 | `--dump_path=${this.dest}` 29 | ] 30 | }; 31 | } 32 | } -------------------------------------------------------------------------------- /src/commands/docker.test.ts: -------------------------------------------------------------------------------- 1 | import { describe, expect, test } from "vitest"; 2 | import Converter from "./convert"; 3 | import { DockerCommand } from "./docker"; 4 | import Dreambooth from "./dreambooth"; 5 | 6 | describe("TestDocker", () => { 7 | test("Docker volume mapping", () => { 8 | const dockerCommand = new DockerCommand( 9 | { executable: "echo", arguments: ["hello"] }, 10 | [["/path/to/a", "/a"]] 11 | ); 12 | expect(dockerCommand.getCommand().arguments).toEqual([ 13 | "run", "--rm", "-t", "--pull", "always", "-v=/path/to/a:/a", "smy20011/dreambooth:v0.1.10", "echo", "hello" 14 | ]); 15 | }); 16 | test("Docker additional arguments", () => { 17 | const dockerCommand = new DockerCommand( 18 | { executable: "echo", arguments: ["hello"] }, 19 | [["/path/to/a", "/a"]], 20 | ["--gpu", "all"] 21 | ); 22 | expect(dockerCommand.getCommand().arguments).toEqual([ 23 | "run", "--rm", "-t", "--pull", "always", "--gpu", "all", "-v=/path/to/a:/a", "smy20011/dreambooth:v0.1.10", "echo", "hello" 24 | ]); 25 | }); 26 | 27 | test("Docker environment mapping", () => { 28 | const dockerCommand = new DockerCommand( 29 | { executable: "echo", arguments: ["hello"], environment: { 'HELLO': "world" } }, 30 | [["/path/to/a", "/a"]], 31 | ); 32 | expect(dockerCommand.getCommand().arguments).toEqual([ 33 | "run", "--rm", "-t", "--pull", "always", "-v=/path/to/a:/a", "-e", "HELLO=world", "smy20011/dreambooth:v0.1.10", "echo", "hello" 34 | ]); 35 | }); 36 | 37 | test("Docker run convert ckpt", () => { 38 | let converter = new Converter("/a", "/b", "/convert.py") 39 | const dockerCommand = DockerCommand.runDiffusersToCkpt(converter); 40 | expect(converter.source).toEqual("/a"); 41 | expect(converter.dest).toEqual("/b"); 42 | expect(dockerCommand.getCommand().arguments).toEqual([ 43 | "run", "--rm", "-t", "--pull", "always", "--gpus=all", "-v=/a:/source", "-v=/b:/dest", "smy20011/dreambooth:v0.1.10", "python", 44 | "/convert.py", "--model_path=/source", "--checkpoint_path=/dest/model.ckpt", 45 | ]); 46 | }); 47 | test("Docker run ckpt to diffusers", () => { 48 | let converter = new Converter("/a", "/b", "/convert.py") 49 | const dockerCommand = DockerCommand.runCkptToDiffusers(converter, '/cache'); 50 | expect(converter.source).toEqual("/a"); 51 | expect(converter.dest).toEqual("/b"); 52 | expect(dockerCommand.getCommand().arguments).toEqual([ 53 | "run", 54 | "--rm", 55 | "-t", 56 | "--pull", 57 | "always", 58 | "--gpus=all", 59 | "--mount", 60 | "type=bind,source=/a,target=/source.ckpt", 61 | "-v=/b:/dest", 62 | "-v=/cache:/train", 63 | "smy20011/dreambooth:v0.1.10", 64 | "python", 65 | "/diffusers/scripts/convert_original_stable_diffusion_to_diffusers.py", 66 | "--checkpoint_path=/source.ckpt", 67 | "--dump_path=/dest", 68 | ]); 69 | }); 70 | 71 | test("Docker run dreambooth training", () => { 72 | let dreambooth = new Dreambooth("sks", ""); 73 | dreambooth.instanceDir = "/path/instance"; 74 | dreambooth.outputDir = "/path/output"; 75 | dreambooth.token = "abc"; 76 | expect(DockerCommand.runDreambooth(dreambooth, "/cache").getCommand().arguments).toEqual([ 77 | "run", 78 | "--rm", 79 | "-t", 80 | "--pull", 81 | "always", 82 | "--gpus=all", 83 | "-v=/path/instance:/instance", 84 | "-v=/path/output:/output", 85 | "-v=/cache:/train", 86 | "-e", 87 | "HUGGING_FACE_HUB_TOKEN=abc", 88 | "smy20011/dreambooth:v0.1.10", 89 | "/start_training", 90 | "/train_dreambooth.py", 91 | "--pretrained_model_name_or_path=CompVis/stable-diffusion-v1-4", 92 | "--instance_prompt=sks", 93 | "--instance_data_dir=/instance", 94 | "--max_train_steps=600", 95 | "--learning_rate=5e-6", 96 | "--lr_scheduler=constant", 97 | "--lr_warmup_steps=0", 98 | "--save_interval=10000", 99 | "--save_min_steps=100000", 100 | "--resolution=512", 101 | "--output_dir=/output", 102 | ]); 103 | }); 104 | }); -------------------------------------------------------------------------------- /src/commands/docker.ts: -------------------------------------------------------------------------------- 1 | import Converter from "./convert"; 2 | import Dreambooth from "./dreambooth"; 3 | import { Command } from "./runner"; 4 | import _ from "lodash"; 5 | 6 | // Run a command within docker. 7 | export class DockerCommand { 8 | constructor( 9 | private subCommand: Command, 10 | private volumeMapping: [string, string][] = [], 11 | private additionalArguments: string[] = [], 12 | private image = "smy20011/dreambooth:v0.1.10", 13 | private alwaysPull = true, 14 | ) { } 15 | 16 | public getCommand(): Command { 17 | return { 18 | executable: "docker", 19 | arguments: [ 20 | "run", 21 | "--rm", 22 | "-t", 23 | ...this.getPullingArguments(), 24 | ...this.additionalArguments, 25 | ...this.volumeMapping.map(it => `-v=${it[0]}:${it[1]}`), 26 | ...Object.entries(this.subCommand.environment ?? {}).sort().flatMap(it => ['-e', `${it[0]}=${it[1]}`]), 27 | this.image, 28 | this.subCommand.executable, 29 | ...this.subCommand.arguments 30 | ] 31 | } 32 | } 33 | 34 | private getPullingArguments(): string[] { 35 | if (this.alwaysPull) { 36 | return ["--pull", "always"]; 37 | } 38 | return []; 39 | } 40 | 41 | private static rewrite(mapping: [string, string][], obj: T, key: keyof T, newFolder: string) { 42 | mapping.push([obj[key] as string, newFolder]); 43 | obj[key] = newFolder as T[keyof T]; 44 | } 45 | 46 | private static forceNewLine(command: Command): Command { 47 | return { 48 | executable: '/start_training', 49 | arguments: [ 50 | ...command.arguments 51 | ], 52 | environment: command.environment 53 | } 54 | } 55 | 56 | public static runDreambooth(dreambooth: Dreambooth, cacheDir: string, classDir?: string, isLocalModel = false): DockerCommand { 57 | let mapping: [string, string][] = []; 58 | dreambooth = _.clone(dreambooth); 59 | this.rewrite(mapping, dreambooth, "instanceDir", "/instance"); 60 | if (dreambooth.classPrompt && classDir) { 61 | dreambooth.classDir = classDir; 62 | this.rewrite(mapping, dreambooth, "classDir", "/class"); 63 | } 64 | this.rewrite(mapping, dreambooth, "outputDir", "/output"); 65 | if (isLocalModel) { 66 | this.rewrite(mapping, dreambooth, "model", "/input_model"); 67 | } 68 | mapping.push([cacheDir, '/train']); 69 | return new DockerCommand( 70 | this.forceNewLine(dreambooth.getTrainingCommand()), 71 | mapping, 72 | [ 73 | '--gpus=all', 74 | ] 75 | ); 76 | } 77 | 78 | public static runDiffusersToCkpt(converter: Converter): DockerCommand { 79 | let mapping: [string, string][] = []; 80 | converter = _.clone(converter); 81 | this.rewrite(mapping, converter, "source", "/source"); 82 | this.rewrite(mapping, converter, "dest", "/dest"); 83 | return new DockerCommand( 84 | converter.getDiffuserToCkptCommand(), 85 | mapping, 86 | ['--gpus=all'], 87 | ); 88 | } 89 | 90 | public static runCkptToDiffusers(converter: Converter, cacheDir: string): DockerCommand { 91 | let mapping: [string, string][] = []; 92 | converter = _.clone(converter); 93 | this.rewrite(mapping, converter, "dest", "/dest"); 94 | mapping.push([cacheDir, '/train']); 95 | let source = converter.source; 96 | converter.source = "/source.ckpt"; 97 | return new DockerCommand( 98 | converter.getCkptToDiffuserCommand(), 99 | mapping, 100 | ['--gpus=all', "--mount", `type=bind,source=${source},target=/source.ckpt`], 101 | ); 102 | } 103 | 104 | } -------------------------------------------------------------------------------- /src/commands/dreambooth.test.ts: -------------------------------------------------------------------------------- 1 | import { expect, test, describe, beforeEach } from 'vitest' 2 | import Dreambooth from './dreambooth'; 3 | describe('Dreambooth Test', () => { 4 | let dreambooth: Dreambooth; 5 | beforeEach(() => { 6 | dreambooth = new Dreambooth("sks"); 7 | dreambooth.instanceDir = "/instance"; 8 | dreambooth.classDir = "/class"; 9 | dreambooth.outputDir = "/output" 10 | dreambooth.token = "abc"; 11 | }); 12 | 13 | test('Instance prompt only training', () => { 14 | const command = dreambooth.getTrainingCommand(); 15 | expect(command.arguments).toEqual([ 16 | "/train_dreambooth.py", 17 | "--pretrained_model_name_or_path=CompVis/stable-diffusion-v1-4", 18 | "--instance_prompt=sks", 19 | "--instance_data_dir=/instance", 20 | "--max_train_steps=600", 21 | "--learning_rate=5e-6", 22 | "--lr_scheduler=constant", 23 | "--lr_warmup_steps=0", 24 | "--save_interval=10000", 25 | "--save_min_steps=100000", 26 | "--resolution=512", 27 | "--output_dir=/output", 28 | ]); 29 | expect(command.environment).toEqual({ 30 | "HUGGING_FACE_HUB_TOKEN": "abc" 31 | }) 32 | }); 33 | test('Class training', () => { 34 | dreambooth.classPrompt = "class" 35 | const command = dreambooth.getTrainingCommand(); 36 | expect(command.arguments).toEqual([ 37 | "/train_dreambooth.py", 38 | "--pretrained_model_name_or_path=CompVis/stable-diffusion-v1-4", 39 | "--instance_prompt=sks", 40 | "--instance_data_dir=/instance", 41 | "--class_data_dir=/class", 42 | "--with_prior_preservation", 43 | "--prior_loss_weight=1.0", 44 | "--class_prompt=class", 45 | "--max_train_steps=600", 46 | "--learning_rate=5e-6", 47 | "--lr_scheduler=constant", 48 | "--lr_warmup_steps=0", 49 | "--save_interval=10000", 50 | "--save_min_steps=100000", 51 | "--resolution=512", 52 | "--output_dir=/output", 53 | ]); 54 | expect(command.environment).toEqual({ 55 | "HUGGING_FACE_HUB_TOKEN": "abc" 56 | }) 57 | }); 58 | 59 | }); -------------------------------------------------------------------------------- /src/commands/dreambooth.ts: -------------------------------------------------------------------------------- 1 | import _ from "lodash"; 2 | import { GpuInfo } from "../Gpu"; 3 | import { Command } from "./runner"; 4 | 5 | function recordToArgs(obj: Record): string[] { 6 | return Object.entries(obj) 7 | .map(([key, value]) => { 8 | if (typeof value == "boolean") { 9 | return value ? `--${key}` : null; 10 | } 11 | return `--${key}=${value}`; 12 | }) 13 | .filter(v => v !== null) as string[]; 14 | } 15 | 16 | function pickTrainingArgs(gpuInfo: GpuInfo) { 17 | const GIB = 1024 * 1024 * 1024; 18 | if (gpuInfo.name == "unknown") { 19 | return []; 20 | } 21 | // Config for GPU with < 10GB varm 22 | let config = { 23 | mixed_precision: 'fp16', 24 | train_batch_size: 1, 25 | gradient_accumulation_steps: 1, 26 | gradient_checkpointing: true, 27 | use_8bit_adam: true, 28 | }; 29 | if (gpuInfo.meminfo.free > 13.7 * GIB) { 30 | // Train with better quality and disable checkpoint. 31 | config.gradient_accumulation_steps = 2; 32 | config.gradient_checkpointing = false; 33 | } else if (gpuInfo.meminfo.free > 11.2 * GIB) { 34 | // Disbale gradient checkpoint for faster training. 35 | config.gradient_checkpointing = false; 36 | } else if (gpuInfo.meminfo.free > 10.4 * GIB) { 37 | // Increase batch size for better training quality. 38 | config.train_batch_size = 2; 39 | } 40 | return recordToArgs(config); 41 | } 42 | 43 | 44 | 45 | export default class Dreambooth { 46 | constructor( 47 | // Prompt of dir. 48 | public instancePrompt: string, 49 | // Train dreambooth with class images. 50 | public classPrompt: string = "", 51 | // User defined additional arguments to train the model. 52 | public additionalArguments: string[] = [], 53 | // Max training steps 54 | public steps: number = 600, 55 | // Learning rate. 56 | public learningRate: string = "5e-6", 57 | // Model dir or name. 58 | public model: string = "CompVis/stable-diffusion-v1-4", 59 | // Model output dir 60 | public outputDir = "", 61 | // Class image directory. 62 | public classDir = "", 63 | // Dir of images. 64 | public instanceDir = "", 65 | // Script location 66 | public scriptLocation: string = "/train_dreambooth.py", 67 | // Additional training arguments 68 | public extraTrainingArgs: string[] = [], 69 | // Token 70 | public token = "", 71 | // Save every n steps 72 | public saveInterval = 10000, 73 | // Steps to save model 74 | public saveMinSteps = 100000, 75 | ) { } 76 | 77 | public withGpu(gpuInfo: GpuInfo): Dreambooth { 78 | let newDb = _.clone(this); 79 | newDb.additionalArguments = pickTrainingArgs(gpuInfo); 80 | return newDb; 81 | } 82 | 83 | public with(update: Partial>): Dreambooth { 84 | return _.assign(_.clone(this), update); 85 | } 86 | 87 | public verifyState(): string { 88 | if (!this.instanceDir) { 89 | return "Please select instance images in the image tab."; 90 | } 91 | if (!this.instancePrompt) { 92 | return "Please set your instance prompt in the training tab."; 93 | } 94 | if (!this.model) { 95 | return "Please select your based model in the training tab."; 96 | } 97 | if (!this.steps || this.steps < 0) { 98 | return "Steps cannot be negative." 99 | } 100 | if (!this.outputDir) { 101 | return "Please select output dir."; 102 | } 103 | if (!this.token) { 104 | return "Please set your hugging face token."; 105 | } 106 | return ""; 107 | } 108 | 109 | public getTrainingCommand(): Command { 110 | return { 111 | executable: "python", 112 | arguments: [ 113 | this.scriptLocation, 114 | `--pretrained_model_name_or_path=${this.model}`, 115 | ...this.getInstantArguments(), 116 | ...this.getClassArguments(), 117 | ...this.getTrainingArguments(), 118 | ...this.getOutputArguments(), 119 | ...this.additionalArguments 120 | ], 121 | environment: { 122 | "HUGGING_FACE_HUB_TOKEN": this.token, 123 | } 124 | }; 125 | } 126 | 127 | private getInstantArguments(): string[] { 128 | return [ 129 | `--instance_prompt=${this.instancePrompt}`, 130 | `--instance_data_dir=${this.instanceDir}` 131 | ]; 132 | } 133 | 134 | private getClassArguments(): string[] { 135 | if (this.classPrompt) { 136 | return [ 137 | `--class_data_dir=${this.classDir}`, 138 | "--with_prior_preservation", 139 | "--prior_loss_weight=1.0", 140 | `--class_prompt=${this.classPrompt}` 141 | ]; 142 | } 143 | return []; 144 | } 145 | 146 | private getTrainingArguments(): string[] { 147 | return [ 148 | `--max_train_steps=${this.steps}`, 149 | `--learning_rate=${this.learningRate}`, 150 | "--lr_scheduler=constant", 151 | "--lr_warmup_steps=0", 152 | `--save_interval=${this.saveInterval}`, 153 | `--save_min_steps=${this.saveMinSteps}`, 154 | ...this.extraTrainingArgs 155 | ]; 156 | } 157 | 158 | private getOutputArguments(): string[] { 159 | return [ 160 | "--resolution=512", 161 | `--output_dir=${this.outputDir}`, 162 | ] 163 | } 164 | } -------------------------------------------------------------------------------- /src/commands/runner.ts: -------------------------------------------------------------------------------- 1 | import { shell } from "@tauri-apps/api"; 2 | 3 | export interface Command { 4 | executable: string; 5 | arguments: string[]; 6 | environment?: Record; 7 | } 8 | 9 | // Run docker with command, pipe output to outputCallback and returns the exit value. 10 | export async function run(command: Command, outputCallback: (line: string) => void): Promise { 11 | return new Promise((resolve, reject) => { 12 | const process = new shell.Command(command.executable, command.arguments, { env: command.environment }); 13 | process.on("close", payload => resolve(payload.code)); 14 | process.on("error", reject); 15 | process.stdout.on("data", outputCallback); 16 | process.stderr.on("data", outputCallback); 17 | process.spawn().catch(reject); 18 | }) 19 | } -------------------------------------------------------------------------------- /src/components/ConfigTrainer.tsx: -------------------------------------------------------------------------------- 1 | import { dialog } from "@tauri-apps/api"; 2 | import { useAtom, useAtomValue, useSetAtom } from "jotai"; 3 | import _ from "lodash"; 4 | import { Form, InputGroup, Button, Row, Col } from "react-bootstrap"; 5 | import { dreamboothAtom, gpuAtom, updateClassPromptAtom } from "../state"; 6 | import { bind, updateStateField, useAtomForm } from "./utils"; 7 | 8 | export default function ConfigTrainer() { 9 | const GIB = 1024 * 1024 * 1024; 10 | const [state, setState, bind] = useAtomForm(dreamboothAtom); 11 | const gpuInfo = useAtomValue(gpuAtom); 12 | const setClassPrompt = useSetAtom(updateClassPromptAtom); 13 | 14 | if (!gpuInfo) { 15 | return
Cannot find your GPU infomation.
16 | } 17 | const selectModelFolder = async () => { 18 | const result = await dialog.open({ 19 | filters: [{ 20 | name: "Model Checkpoint", 21 | extensions: ["ckpt"], 22 | }] 23 | }); 24 | if (result != null && typeof result === 'string') { 25 | setState(s => _.assign(_.clone(s), { model: result })); 26 | } 27 | }; 28 | 29 | return ( 30 |
31 |

Run dreambooth on {gpuInfo.name}, {(gpuInfo.meminfo.free / GIB).toFixed(2)}gb free

32 | 33 | Model 34 | 35 | 36 | 39 | 40 | 41 | Name of the base model, (eg, CompVis/stable-diffusion-v1-4) 42 | 43 | 44 | 45 | Instance prompt 46 | 47 | 48 | Name of the instance, use a rare word if possible. (Eg, sks) 49 | 50 | 51 | 52 | Class prompt 53 | { 55 | setClassPrompt(t.target.value); 56 | } 57 | } /> 58 | 59 | If you want training with prior-preservation loss, set the class prompt. (Eg, a person) 60 | 61 | 62 | 63 | Training Steps 64 | 65 | 66 | 67 | 68 | 69 | Save Every # Steps 70 | 71 | 72 | 73 | Start saving at # Steps 74 | 75 | 76 | 77 | 78 | 79 | Learning Rate 80 | 81 | 82 | 83 |
Training arguments
84 | 85 | Add your custom arguments here. 86 | 87 | { 92 | setState(_.assign(_.clone(state), { "additionalArguments": t.target.value.split("\n") })); 93 | }} 94 | /> 95 | 96 |
97 | ); 98 | } 99 | -------------------------------------------------------------------------------- /src/components/Gallery.tsx: -------------------------------------------------------------------------------- 1 | import { readDir } from "@tauri-apps/api/fs"; 2 | import { convertFileSrc } from "@tauri-apps/api/tauri"; 3 | import { useEffect, useState } from "react"; 4 | import { Col } from "react-bootstrap"; 5 | 6 | async function getImageUrisInForlder(folder: string): Promise { 7 | if (!folder) { 8 | return []; 9 | } 10 | const files = await readDir(folder); 11 | return Promise.all(files.map(f => convertFileSrc(f.path))); 12 | } 13 | 14 | export default function Gallery({ imageDir }: { imageDir: string }) { 15 | const [imageUri, setImageUri] = useState([]); 16 | useEffect(() => { 17 | getImageUrisInForlder(imageDir).then(setImageUri); 18 | }, [imageDir]); 19 | return <> 20 | {imageUri.slice(0, 50).map(uri => 21 | 22 | )} 23 | 24 | } -------------------------------------------------------------------------------- /src/components/ImagePicker.tsx: -------------------------------------------------------------------------------- 1 | import { dialog } from "@tauri-apps/api"; 2 | import { useAtom } from "jotai"; 3 | import _ from "lodash"; 4 | import { Col, Button, Row } from "react-bootstrap"; 5 | import { dreamboothAtom } from "../state"; 6 | import Gallery from "./Gallery"; 7 | import { useAtomForm } from "./utils"; 8 | 9 | export default function ImagePicker() { 10 | const [state, setState, bind] = useAtomForm(dreamboothAtom); 11 | const showDialog = async () => { 12 | const result = await dialog.open({ 13 | directory: true, 14 | }); 15 | if (result != null && typeof result === 'string') { 16 | setState(_.assign(_.clone(state), { "instanceDir": result })); 17 | } 18 | } 19 | return ( 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | ); 29 | } 30 | 31 | -------------------------------------------------------------------------------- /src/components/Trainer.tsx: -------------------------------------------------------------------------------- 1 | import { shell } from "@tauri-apps/api"; 2 | import { useAtom, useSetAtom } from "jotai"; 3 | import { useEffect, useState } from "react"; 4 | import { Tab, Tabs } from "react-bootstrap"; 5 | import { GetGpuInfo } from "../Gpu"; 6 | import { updateGpuAtom } from "../state"; 7 | import ConfigTrainer from "./ConfigTrainer"; 8 | import ImagePicker from "./ImagePicker"; 9 | import { Training } from "./Training"; 10 | 11 | 12 | 13 | 14 | function Trainer() { 15 | const [error, setError] = useState(""); 16 | const updateGpu = useSetAtom(updateGpuAtom); 17 | 18 | useEffect(() => { 19 | GetGpuInfo().then(updateGpu).catch(err => setError(`Failed to fetch GPU info ${error}`)); 20 | const command = new shell.Command("docker", "version"); 21 | command.execute() 22 | .catch(err => setError("Failed to execute docker command, make sure docker is installed in your system.\n\nOpen the docker GUI and make sure it's running.")) 23 | .then(res => { 24 | if (res && res.code != 0) { 25 | setError(`Docker command returns error, make sure you run this program as admin/root user. \n\n'docker version' output: ${res.stderr}\n\nOpen the docker GUI and make sure it's running.`); 26 | } 27 | }); 28 | }, []); 29 | 30 | return ( 31 | error ?
{error}
: 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | ) 44 | } 45 | 46 | export default Trainer; -------------------------------------------------------------------------------- /src/components/Training.tsx: -------------------------------------------------------------------------------- 1 | import { dialog } from "@tauri-apps/api"; 2 | import { message } from "@tauri-apps/api/dialog"; 3 | import { exists, readDir, writeTextFile } from "@tauri-apps/api/fs"; 4 | import { appDir, join } from "@tauri-apps/api/path"; 5 | import { appWindow } from "@tauri-apps/api/window"; 6 | import { atom, useAtom, useAtomValue } from "jotai"; 7 | import _ from "lodash"; 8 | import { FormEvent, useEffect, useRef, useState } from "react"; 9 | import { Button, Form, InputGroup } from "react-bootstrap"; 10 | import Converter from "../commands/convert"; 11 | import { DockerCommand } from "../commands/docker"; 12 | import Dreambooth from "../commands/dreambooth"; 13 | import { Command, run } from "../commands/runner"; 14 | import { killDocker } from "../docker"; 15 | import { appDirAtom, dreamboothAtom } from "../state"; 16 | import { getClassDir, ensureDir, bind, updateStateField, useAtomForm, asyncAtomWithCache } from "./utils"; 17 | 18 | const trainingCommandAtom = atom(async (get) => { 19 | let db = get(dreamboothAtom); 20 | const isLocalModel = await exists(db.model) as unknown as boolean; 21 | const appDir = get(appDirAtom); 22 | const classDir = await getClassDir(db.classPrompt); 23 | let commands = []; 24 | if (isLocalModel) { 25 | const model_dir = db.model.replace(".ckpt", ""); 26 | commands.push(DockerCommand.runCkptToDiffusers(new Converter(db.model, model_dir), appDir).getCommand()); 27 | db = db.with({ model: model_dir }); 28 | } 29 | return [ 30 | ...commands, 31 | DockerCommand.runDreambooth(db, appDir, classDir, isLocalModel).getCommand() 32 | ]; 33 | }); 34 | 35 | const cachedTrainingCommandAtom = asyncAtomWithCache(trainingCommandAtom, []); 36 | 37 | export function Training() { 38 | const [running, setRunning] = useState(false); 39 | const [genCkpt, setGenCkpt] = useState(true); 40 | const [lines, setLines] = useState([]); 41 | const [state, setState, bind] = useAtomForm(dreamboothAtom); 42 | const dockerTrainCommand = useAtomValue(cachedTrainingCommandAtom); 43 | 44 | const outputRef = useRef(); 45 | 46 | useEffect(() => { 47 | const area = outputRef.current!!; 48 | area.scrollTop = area.scrollHeight; 49 | }, [lines]); 50 | 51 | useEffect(() => { 52 | const unlisten = appWindow.onCloseRequested(async () => { 53 | try { 54 | await killDocker(); 55 | } catch { 56 | } 57 | }); 58 | }, []); 59 | 60 | const onSubmit = async (e: FormEvent) => { 61 | e.preventDefault(); 62 | if (running) { 63 | await killDocker(); 64 | setRunning(false); 65 | } else { 66 | const verificationMessage = state.verifyState(); 67 | if (verificationMessage) { 68 | await message(`Cannot start training: ${verificationMessage}`); 69 | return; 70 | } 71 | const dirs = [ 72 | await getClassDir(state.classDir), 73 | await appDir(), 74 | state.outputDir, 75 | ]; 76 | 77 | for (const dir of dirs) { 78 | try { 79 | if (dir) { 80 | ensureDir(dir); 81 | } 82 | } catch (e) { 83 | await message(`Failed to create dir ${dir}, ${e}`); 84 | return; 85 | } 86 | } 87 | 88 | try { 89 | setRunning(true); 90 | setLines([]); 91 | for (const command of dockerTrainCommand) { 92 | const ret = await run( 93 | command, 94 | line => setLines(list => list.concat(line))); 95 | if (ret != 0) { 96 | await message(`Failed to train model, see output for detailed error.`); 97 | setRunning(false); 98 | return; 99 | } 100 | } 101 | await writeTextFile(await join(state.outputDir, "trainer_config"), JSON.stringify(state)); 102 | if (genCkpt) { 103 | for (const f of await readDir(state.outputDir)) { 104 | // TODO: We still don't have a good API to check whether or not the f is a dir. 105 | // Tauri are planning to add such a API, refactor it later. 106 | if (f.name?.match(/\d+/) && f.name !== "0") { 107 | let genCkptOuput: string[] = []; 108 | setLines(line => line.concat(`Converting model in ${f.path} to ckpt.`)) 109 | const ret = await run( 110 | DockerCommand.runDiffusersToCkpt(new Converter(f.path, f.path)).getCommand(), 111 | l => genCkptOuput.push(l)); 112 | if (ret != 0) { 113 | await message(`Failed to convert model, output: ${genCkptOuput.join("\n")}`); 114 | } 115 | } 116 | } 117 | } 118 | setRunning(false); 119 | } catch (e) { 120 | await message(`Failed to start docker ${e}`); 121 | } 122 | await message(`Training finished, check ${state.outputDir} for model output.`, 'Finished!'); 123 | } 124 | }; 125 | 126 | const selectOutputFolder = async () => { 127 | const result = await dialog.open({ 128 | directory: true, 129 | }); 130 | if (result != null && typeof result === 'string') { 131 | setState(_.assign(_.clone(state), { "outputDir": result })); 132 | } 133 | }; 134 | 135 | return ( 136 |
137 | 138 | Hugging Face Token 139 | 140 | 141 | 142 | Output Dir 143 | 144 | 145 | 148 | 149 | 150 | 151 | setGenCkpt(t.target.checked)} /> 152 | 153 | 154 |
Training Command
155 | `${c.executable} ${c.arguments.join(" ")}`).join("\n")} disabled /> 157 | 158 | 159 |
Training Output
160 | 161 | 162 | {!running ? 163 | : 166 | } 169 |
170 | ); 171 | } 172 | -------------------------------------------------------------------------------- /src/components/utils.ts: -------------------------------------------------------------------------------- 1 | import { exists, createDir } from "@tauri-apps/api/fs"; 2 | import { join, appDir } from "@tauri-apps/api/path"; 3 | import { Atom, SetStateAction, useAtom, atom } from "jotai"; 4 | import { PrimitiveAtom, SetAtom } from "jotai/core/atom"; 5 | import { loadable } from "jotai/utils" 6 | import _ from "lodash"; 7 | 8 | 9 | export function updateStateField(setState: (update: SetStateAction) => void, name: keyof T, value: any) { 10 | setState(s => _.assign(_.clone(s), { [name]: value })); 11 | } 12 | 13 | export function bind(state: T, setState: (update: SetStateAction) => void, name: keyof T) { 14 | return { 15 | value: state[name] as any, 16 | onChange: (t: any) => updateStateField(setState, name, t.target.value) 17 | } 18 | } 19 | 20 | export function useAtomForm(atom: PrimitiveAtom): [Value, SetAtom, void>, (name: keyof Value) => any] { 21 | const [state, setState] = useAtom(atom); 22 | return [ 23 | state, setState, (name: keyof Value) => bind(state, setState, name) 24 | ] 25 | } 26 | 27 | export function asyncAtomWithCache(orig: Atom>, defaultValue: Value): Atom { 28 | const loadableAtom = loadable(orig); 29 | let cache = [defaultValue]; 30 | return atom((get) => { 31 | const value = get(loadableAtom); 32 | if (value.state == "hasData") { 33 | cache[0] = value.data; 34 | } 35 | return cache[0]; 36 | }); 37 | } 38 | 39 | export async function getClassDir(prompt: string | undefined) { 40 | if (!prompt) { 41 | return ""; 42 | } 43 | return await join(await appDir(), prompt); 44 | } 45 | 46 | export async function ensureDir(dir: string) { 47 | if (dir && !(await exists(dir) as unknown as boolean)) { 48 | await createDir(dir, { recursive: true }); 49 | } 50 | } 51 | 52 | -------------------------------------------------------------------------------- /src/docker.ts: -------------------------------------------------------------------------------- 1 | 2 | import { shell } from "@tauri-apps/api"; 3 | 4 | // Kill all running instance of docker. 5 | export async function killDocker() { 6 | const process = new shell.Command("docker", ["ps", "--format", "{{.Image}} {{.ID}}"]); 7 | const dockerIds = (await process.execute()).stdout; 8 | const futures = dockerIds.split("\n").map(async (s) => { 9 | const [image, id] = s.split(" "); 10 | if (image.startsWith("smy20011")) { 11 | const killProcess = new shell.Command("docker", ["kill", id]); 12 | const ret = await killProcess.execute(); 13 | console.log(`Killed docker image ${id}, retcode=${ret.code}`); 14 | } 15 | }); 16 | await Promise.all(futures); 17 | } -------------------------------------------------------------------------------- /src/main.tsx: -------------------------------------------------------------------------------- 1 | import React from "react"; 2 | import ReactDOM from "react-dom/client"; 3 | import App from "./App"; 4 | import "./style.css"; 5 | import 'bootstrap/dist/css/bootstrap.min.css'; 6 | 7 | ReactDOM.createRoot(document.getElementById("root") as HTMLElement).render( 8 | 9 | 10 | 11 | ); 12 | -------------------------------------------------------------------------------- /src/state.ts: -------------------------------------------------------------------------------- 1 | import { appDir, join } from "@tauri-apps/api/path"; 2 | import { atom } from "jotai"; 3 | import _ from "lodash"; 4 | import Dreambooth from "./commands/dreambooth"; 5 | import { GpuInfo } from "./Gpu"; 6 | 7 | export const gpuAtom = atom({ 8 | name: "unknown", 9 | meminfo: { 10 | free: 0, 11 | total: 0, 12 | used: 0, 13 | } 14 | }); 15 | 16 | export const updateGpuAtom = atom(null, (get, set, update: GpuInfo) => { 17 | set(gpuAtom, update); 18 | set(dreamboothAtom, get(dreamboothAtom).withGpu(update)); 19 | }); 20 | 21 | export const dreamboothAtom = atom(new Dreambooth("sks")); 22 | export const updateClassPromptAtom = atom(null, async (get, set, prompt: string) => { 23 | const classDir = await join(get(appDirAtom), prompt); 24 | set(dreamboothAtom, get(dreamboothAtom).with({ "classDir": classDir, "classPrompt": prompt })); 25 | }); 26 | export const appDirAtom = atom(async () => appDir()); -------------------------------------------------------------------------------- /src/style.css: -------------------------------------------------------------------------------- 1 | html, 2 | body, 3 | #root, 4 | .container { 5 | margin: 0; 6 | padding: 0; 7 | height: 100%; 8 | } 9 | 10 | .trainer-error { 11 | white-space: pre-line; 12 | } -------------------------------------------------------------------------------- /src/vite-env.d.ts: -------------------------------------------------------------------------------- 1 | /// 2 | -------------------------------------------------------------------------------- /src/vite.config.ts: -------------------------------------------------------------------------------- 1 | /// 2 | 3 | // Configure Vitest (https://vitest.dev/config/) 4 | 5 | import { defineConfig } from 'vite' 6 | 7 | export default defineConfig({ 8 | }) -------------------------------------------------------------------------------- /tsconfig.json: -------------------------------------------------------------------------------- 1 | { 2 | "compilerOptions": { 3 | "target": "ESNext", 4 | "useDefineForClassFields": true, 5 | "lib": ["DOM", "DOM.Iterable", "ESNext"], 6 | "allowJs": false, 7 | "skipLibCheck": true, 8 | "esModuleInterop": false, 9 | "allowSyntheticDefaultImports": true, 10 | "strict": true, 11 | "forceConsistentCasingInFileNames": true, 12 | "module": "ESNext", 13 | "moduleResolution": "Node", 14 | "resolveJsonModule": true, 15 | "isolatedModules": true, 16 | "noEmit": true, 17 | "jsx": "react-jsx" 18 | }, 19 | "include": ["src"], 20 | "references": [{ "path": "./tsconfig.node.json" }] 21 | } 22 | -------------------------------------------------------------------------------- /tsconfig.node.json: -------------------------------------------------------------------------------- 1 | { 2 | "compilerOptions": { 3 | "composite": true, 4 | "module": "ESNext", 5 | "moduleResolution": "Node", 6 | "allowSyntheticDefaultImports": true 7 | }, 8 | "include": ["vite.config.ts"] 9 | } 10 | -------------------------------------------------------------------------------- /vite.config.ts: -------------------------------------------------------------------------------- 1 | import { defineConfig } from "vite"; 2 | import react from "@vitejs/plugin-react"; 3 | 4 | // https://vitejs.dev/config/ 5 | export default defineConfig({ 6 | plugins: [react()], 7 | 8 | // Vite optons tailored for Tauri development and only applied in `tauri dev` or `tauri build` 9 | // prevent vite from obscuring rust errors 10 | clearScreen: false, 11 | // tauri expects a fixed port, fail if that port is not available 12 | server: { 13 | port: 1420, 14 | strictPort: true, 15 | }, 16 | // to make use of `TAURI_DEBUG` and other env variables 17 | // https://tauri.studio/v1/api/config#buildconfig.beforedevcommand 18 | envPrefix: ["VITE_", "TAURI_"], 19 | build: { 20 | // Tauri supports es2021 21 | target: ["es2021", "chrome100", "safari13"], 22 | // don't minify for debug builds 23 | minify: !process.env.TAURI_DEBUG ? "esbuild" : false, 24 | // produce sourcemaps for debug builds 25 | sourcemap: !!process.env.TAURI_DEBUG, 26 | }, 27 | }); 28 | -------------------------------------------------------------------------------- /yarn.lock: -------------------------------------------------------------------------------- 1 | # THIS IS AN AUTOGENERATED FILE. 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