Full Code of Sygil-Dev/sygil-webui for AI

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Repository: Sygil-Dev/sygil-webui
Branch: master
Commit: 15a337cd4377
Files: 290
Total size: 21.8 MB

Directory structure:
gitextract_lx9je00i/

├── .dockerignore
├── .env_docker.example
├── .gitattributes
├── .github/
│   ├── FUNDING.yml
│   ├── ISSUE_TEMPLATE/
│   │   └── bug_report.yml
│   ├── PULL_REQUEST_TEMPLATE.md
│   ├── dependabot.yml
│   └── workflows/
│       ├── deploy.yml
│       └── test-deploy.yml
├── .gitignore
├── .gitmodules
├── .pre-commit-config.yaml
├── .streamlit/
│   └── config.toml
├── CONTRIBUTING.md
├── Dockerfile
├── Dockerfile_base
├── Dockerfile_runpod
├── LICENSE
├── README.md
├── Stable_Diffusion_v1_Model_Card.md
├── Web_based_UI_for_Stable_Diffusion_colab.ipynb
├── _config.yml
├── babel.config.js
├── blog/
│   ├── 2022-10-20/
│   │   └── 1.Textual inversion usage competitio.md
│   └── authors.yml
├── configs/
│   ├── autoencoder/
│   │   ├── autoencoder_kl_16x16x16.yaml
│   │   ├── autoencoder_kl_32x32x4.yaml
│   │   ├── autoencoder_kl_64x64x3.yaml
│   │   └── autoencoder_kl_8x8x64.yaml
│   ├── blip/
│   │   ├── bert_config.json
│   │   ├── caption_coco.yaml
│   │   ├── med_config.json
│   │   ├── nlvr.yaml
│   │   ├── nocaps.yaml
│   │   ├── pretrain.yaml
│   │   ├── retrieval_coco.yaml
│   │   ├── retrieval_flickr.yaml
│   │   ├── retrieval_msrvtt.yaml
│   │   └── vqa.yaml
│   ├── latent-diffusion/
│   │   ├── celebahq-ldm-vq-4.yaml
│   │   ├── cin-ldm-vq-f8.yaml
│   │   ├── cin256-v2.yaml
│   │   ├── ffhq-ldm-vq-4.yaml
│   │   ├── lsun_bedrooms-ldm-vq-4.yaml
│   │   ├── lsun_churches-ldm-kl-8.yaml
│   │   └── txt2img-1p4B-eval.yaml
│   ├── retrieval-augmented-diffusion/
│   │   └── 768x768.yaml
│   ├── stable-diffusion/
│   │   ├── v1-inference.yaml
│   │   ├── v2-inference-v.yaml
│   │   ├── v2-inference.yaml
│   │   ├── v2-inpainting-inference.yaml
│   │   ├── v2-midas-inference.yaml
│   │   └── x4-upscaling.yaml
│   └── webui/
│       ├── webui.yaml
│       ├── webui_flet.yaml
│       └── webui_streamlit.yaml
├── daisi_app.py
├── data/
│   ├── img2txt/
│   │   ├── artists.txt
│   │   ├── flavors.txt
│   │   ├── mediums.txt
│   │   ├── movements.txt
│   │   ├── sites.txt
│   │   ├── subreddits.txt
│   │   ├── tags.txt
│   │   └── techniques.txt
│   ├── scn2img_examples/
│   │   ├── cat_at_beach.scn2img.md
│   │   ├── corgi_3d_transformation.scn2img.md
│   │   ├── corgi_at_beach.scn2img.md
│   │   ├── corgi_at_beach_2.scn2img.md
│   │   └── landscape_3d.scn2img.md
│   └── tags/
│       ├── config.json
│       ├── danbooru.csv
│       ├── e621.csv
│       ├── key_phrases.json
│       └── thumbnails.json
├── docker-compose.yml
├── docs/
│   ├── 1.Installation/
│   │   ├── 1.one-click-installer.md
│   │   ├── 2.windows-installation.md
│   │   ├── 3.linux-installation.md
│   │   └── 4.docker-guide.md
│   ├── 2.Streamlit/
│   │   └── 1.streamlit-interface.md
│   ├── 3.Gradio/
│   │   └── 2.gradio-interface.md
│   ├── 4.post-processing.md
│   ├── 5.concepts-library.md
│   └── 6.custom-models.md
├── docusaurus.config.js
├── entrypoint.sh
├── environment.yaml
├── frontend/
│   ├── .eslintrc.js
│   ├── __init__.py
│   ├── css/
│   │   ├── custom.css
│   │   ├── docs_custom.css
│   │   ├── no_progress_bar.css
│   │   ├── streamlit.main.css
│   │   └── styles.css
│   ├── css_and_js.py
│   ├── dists/
│   │   ├── concept-browser/
│   │   │   └── dist/
│   │   │       ├── assets/
│   │   │       │   ├── index.3ab9729b.css
│   │   │       │   └── index.b5b962e4.js
│   │   │       └── index.html
│   │   └── sd-gallery/
│   │       └── dist/
│   │           ├── assets/
│   │           │   ├── index.4194368f.css
│   │           │   └── index.aeaed602.js
│   │           └── index.html
│   ├── frontend.py
│   ├── image_metadata.py
│   ├── index.html
│   ├── job_manager.py
│   ├── js/
│   │   └── index.js
│   ├── package.json
│   ├── src/
│   │   ├── Component.vue
│   │   ├── app.vue
│   │   ├── env.d.ts
│   │   ├── main.ts
│   │   └── streamlit/
│   │       ├── StreamlitVue.ts
│   │       ├── WithStreamlitConnection.vue
│   │       └── index.ts
│   ├── tsconfig.json
│   ├── tsconfig.node.json
│   ├── ui_functions.py
│   └── vite.config.ts
├── horde_bridge.cmd
├── horde_bridge.sh
├── installer/
│   ├── create_installers.sh
│   ├── install.bat
│   └── install.sh
├── ldm/
│   ├── __init__.py
│   ├── data/
│   │   ├── __init__.py
│   │   ├── base.py
│   │   ├── coco_karpathy_dataset.py
│   │   ├── flickr30k_dataset.py
│   │   ├── imagenet.py
│   │   ├── lsun.py
│   │   ├── nlvr_dataset.py
│   │   ├── nocaps_dataset.py
│   │   ├── personalized.py
│   │   ├── personalized_file.py
│   │   ├── pretrain_dataset.py
│   │   ├── util.py
│   │   ├── video_dataset.py
│   │   └── vqa_dataset.py
│   ├── devices/
│   │   ├── __init__.py
│   │   └── devices.py
│   ├── lr_scheduler.py
│   ├── models/
│   │   ├── __init__.py
│   │   ├── autoencoder.py
│   │   ├── blip.py
│   │   ├── blip_itm.py
│   │   ├── blip_nlvr.py
│   │   ├── blip_pretrain.py
│   │   ├── blip_retrieval.py
│   │   ├── blip_vqa.py
│   │   ├── diffusion/
│   │   │   ├── __init__.py
│   │   │   ├── classifier.py
│   │   │   ├── ddim.py
│   │   │   ├── ddpm.py
│   │   │   ├── dpm_solver/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── dpm_solver.py
│   │   │   │   └── sampler.py
│   │   │   ├── kdiffusion.py
│   │   │   ├── plms.py
│   │   │   └── sampling_util.py
│   │   ├── med.py
│   │   ├── nlvr_encoder.py
│   │   └── vit.py
│   ├── modules/
│   │   ├── __init__.py
│   │   ├── attention.py
│   │   ├── diffusionmodules/
│   │   │   ├── __init__.py
│   │   │   ├── model.py
│   │   │   ├── openaimodel.py
│   │   │   ├── upscaling.py
│   │   │   └── util.py
│   │   ├── distributions/
│   │   │   ├── __init__.py
│   │   │   └── distributions.py
│   │   ├── ema.py
│   │   ├── embedding_manager.py
│   │   ├── encoders/
│   │   │   ├── __init__.py
│   │   │   └── modules.py
│   │   ├── image_degradation/
│   │   │   ├── __init__.py
│   │   │   ├── bsrgan.py
│   │   │   ├── bsrgan_light.py
│   │   │   └── utils_image.py
│   │   ├── losses/
│   │   │   ├── __init__.py
│   │   │   ├── contperceptual.py
│   │   │   └── vqperceptual.py
│   │   ├── midas/
│   │   │   ├── api.py
│   │   │   ├── midas/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_model.py
│   │   │   │   ├── blocks.py
│   │   │   │   ├── dpt_depth.py
│   │   │   │   ├── midas_net.py
│   │   │   │   ├── midas_net_custom.py
│   │   │   │   ├── transforms.py
│   │   │   │   └── vit.py
│   │   │   └── utils.py
│   │   └── x_transformer.py
│   └── util.py
├── optimizedSD/
│   ├── ddpm.py
│   ├── diffusers_txt2img.py
│   ├── openaimodelSplit.py
│   ├── optimUtils.py
│   ├── optimized_img2img.py
│   ├── optimized_txt2img.py
│   ├── samplers.py
│   ├── splitAttention.py
│   └── v1-inference.yaml
├── package.json
├── requirements.txt
├── runpod_entrypoint.sh
├── scripts/
│   ├── APIServer.py
│   ├── ModelManager.py
│   ├── Settings.py
│   ├── __init__.py
│   ├── barfi_baklavajs.py
│   ├── bridgeData_template.py
│   ├── clip_interrogator.py
│   ├── convert_original_stable_diffusion_to_diffusers.py
│   ├── custom_components/
│   │   ├── draggable_number_input/
│   │   │   ├── __init__.py
│   │   │   └── main.js
│   │   └── sygil_suggestions/
│   │       ├── __init__.py
│   │       ├── main.css
│   │       ├── main.js
│   │       └── parent.css
│   ├── diffusers_textual_inversion_2.py
│   ├── home.py
│   ├── hydrus_api/
│   │   ├── __init__.py
│   │   └── utils.py
│   ├── img2img.py
│   ├── img2txt.py
│   ├── imglab.py
│   ├── logger.py
│   ├── merge.py
│   ├── modeldownload.py
│   ├── perlin.py
│   ├── pipelines/
│   │   └── stable_diffusion/
│   │       └── no_check.py
│   ├── post_processing.py
│   ├── prune-ckpt.py
│   ├── relauncher.py
│   ├── scn2img.py
│   ├── sd_concept_library.py
│   ├── sd_concepts_library_downloader.py
│   ├── sd_utils/
│   │   ├── __init__.py
│   │   └── bridge.py
│   ├── sd_utils_old.py
│   ├── stable_diffusion_pipeline.py
│   ├── textual_inversion.py
│   ├── txt2img.py
│   ├── txt2vid.py
│   ├── webui.py
│   ├── webui_streamlit.py
│   └── webui_streamlit_new.py
├── setup.py
├── sidebars.js
├── streamlit_webview.py
├── webui/
│   ├── flet/
│   │   ├── assets/
│   │   │   └── manifest.json
│   │   ├── scripts/
│   │   │   ├── __init__.py
│   │   │   ├── flet_asset_manager.py
│   │   │   ├── flet_canvas.py
│   │   │   ├── flet_file_manager.py
│   │   │   ├── flet_gallery_window.py
│   │   │   ├── flet_messages.py
│   │   │   ├── flet_property_manager.py
│   │   │   ├── flet_settings_window.py
│   │   │   ├── flet_titlebar.py
│   │   │   ├── flet_tool_manager.py
│   │   │   └── flet_utils.py
│   │   └── webui_flet.py
│   └── streamlit/
│       ├── frontend/
│       │   └── css/
│       │       └── streamlit.main.css
│       └── scripts/
│           ├── APIServer.py
│           ├── ModelManager.py
│           ├── Settings.py
│           ├── barfi_baklavajs.py
│           ├── custom_components/
│           │   ├── dragable_number_input/
│           │   │   └── index.html
│           │   ├── draggable_number_input/
│           │   │   ├── __init__.py
│           │   │   └── main.js
│           │   └── sygil_suggestions/
│           │       ├── __init__.py
│           │       ├── main.css
│           │       ├── main.js
│           │       └── parent.css
│           ├── img2img.py
│           ├── img2txt.py
│           ├── post_processing.py
│           ├── sd_concept_library.py
│           ├── sd_utils/
│           │   ├── __init__.py
│           │   └── bridge.py
│           ├── textual_inversion.py
│           ├── txt2img.py
│           ├── txt2vid.py
│           └── webui_streamlit.py
├── webui.cmd
├── webui.sh
└── webui_legacy.cmd

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FILE CONTENTS
================================================

================================================
FILE: .dockerignore
================================================
outputs/
src/
configs/webui/userconfig_streamlit.yaml


================================================
FILE: .env_docker.example
================================================
# Force miniconda to attempt to update on every container restart
# instead only when changes are detected
CONDA_FORCE_UPDATE=false

# Validate the model files on every container restart
# (useful to set to false after you're sure the model files are already in place)
VALIDATE_MODELS=true

#Automatically relaunch the webui on crashes
WEBUI_RELAUNCH=true

#Pass cli arguments to webui.py e.g:
#WEBUI_ARGS=--gpu=1 --esrgan-gpu=1 --gfpgan-gpu=1
WEBUI_ARGS=

================================================
FILE: .gitattributes
================================================
* text=auto
*.{cmd,[cC][mM][dD]} text eol=crlf
*.{bat,[bB][aA][tT]} text eol=crlf
*.sh text eol=lf


================================================
FILE: .github/FUNDING.yml
================================================
github: [ZeroCool940711]
patreon: zerocool94
ko_fi: zerocool94
open_collective: sygil_dev
custom: ["https://paypal.me/zerocool94"]


================================================
FILE: .github/ISSUE_TEMPLATE/bug_report.yml
================================================
name: 🐞 Bug Report
description: File a bug report
title: "[Bug]: "
labels: ["bug", "triage"]
assignees:
  - octocat
body:
  - type: markdown
    attributes:
      value: |
        Thanks for taking the time to fill out this bug report!
  - type: textarea
    id: what-happened
    attributes:
      label: What happened?
      description: Also tell us, what did you expect to happen?
      placeholder: Tell us what you see!
      value: "A bug happened!"
    validations:
      required: true
  - type: dropdown
    id: version
    attributes:
      label: Version
      description: What version of our software are you running?
      options:
        - 0.0.1 (Default)
    validations:
      required: true
  - type: dropdown
    id: browsers
    attributes:
      label: What browsers are you seeing the problem on?
      multiple: true
      options:
        - Firefox
        - Chrome
        - Safari
        - Microsoft Edge
  - type: dropdown
    id: os
    attributes:
      label: Where are you running the webui?
      multiple: true
      options:
        - Windows
        - Colab
        - Linux
        - MacOS
  - type: textarea
    id: settings
    attributes:
      label: Custom settings
      description: If you are running the webui with specifi settings, please paste them here for reference (like --nitro)
      render: shell
  - type: textarea
    id: logs
    attributes:
      label: Relevant log output
      description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
      render: shell
  - type: checkboxes
    id: terms
    attributes:
      label: Code of Conduct
      description: By submitting this issue, you agree to follow our [Code of Conduct](https://docs.github.com/en/site-policy/github-terms/github-community-code-of-conduct)
      options:
        - label: I agree to follow this project's Code of Conduct
          required: true


================================================
FILE: .github/PULL_REQUEST_TEMPLATE.md
================================================
# Description

Please include:
* relevant motivation
* a summary of the change
* which issue is fixed.
* any additional dependencies that are required for this change.

Closes: # (issue)

# Checklist:

- [ ] I have changed the base branch to `dev`
- [ ] I have performed a self-review of my own code
- [ ] I have commented my code in hard-to-understand areas
- [ ] I have made corresponding changes to the documentation


================================================
FILE: .github/dependabot.yml
================================================
# To get started with Dependabot version updates, you'll need to specify which
# package ecosystems to update and where the package manifests are located.
# Please see the documentation for all configuration options:
# https://docs.github.com/github/administering-a-repository/configuration-options-for-dependency-updates

version: 2
updates:
  - package-ecosystem: "pip" # See documentation for possible values
    directory: "/" # Location of package manifests
    target-branch: "dev"

    schedule:
      interval: "daily"


================================================
FILE: .github/workflows/deploy.yml
================================================
name: Deploy to GitHub Pages

on:
  push:
    branches:
      - master
    # Review gh actions docs if you want to further define triggers, paths, etc
    # https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#on

jobs:
  deploy:
    name: Deploy to GitHub Pages
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - uses: actions/setup-node@v3
        with:
          node-version: 18
          cache: yarn

      - name: Install dependencies
        run: yarn install
      - name: Build website
        run: yarn build

      # Popular action to deploy to GitHub Pages:
      # Docs: https://github.com/peaceiris/actions-gh-pages#%EF%B8%8F-docusaurus
      - name: Deploy to GitHub Pages
        uses: peaceiris/actions-gh-pages@v3
        with:
          github_token: ${{ secrets.GITHUB_TOKEN }}
          # Build output to publish to the `gh-pages` branch:
          publish_dir: ./build
          # The following lines assign commit authorship to the official
          # GH-Actions bot for deploys to `gh-pages` branch:
          # https://github.com/actions/checkout/issues/13#issuecomment-724415212
          # The GH actions bot is used by default if you didn't specify the two fields.
          # You can swap them out with your own user credentials.
          user_name: github-actions[bot]
          user_email: 41898282+github-actions[bot]@users.noreply.github.com


================================================
FILE: .github/workflows/test-deploy.yml
================================================
name: Test deployment

on:
  pull_request:
    branches:
      - master
    # Review gh actions docs if you want to further define triggers, paths, etc
    # https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#on

jobs:
  test-deploy:
    name: Test deployment
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - uses: actions/setup-node@v3
        with:
          node-version: 18
          cache: yarn

      - name: Install dependencies
        run: yarn install
      - name: Test build website
        run: yarn build


================================================
FILE: .gitignore
================================================
# OS-generated
# ------------
.DS_Store*
[Tt]humbs.db
[Dd]esktop.ini

# Programming - general
*.log


# =========================================================================== #
# 	Python-related
# =========================================================================== #
# src: https://github.com/github/gitignore/blob/master/Python.gitignore

# JetBrains PyCharm / Rider
.idea/

# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class

# C extensions
*.so

# Distribution / packaging
.Python
build/
develop-eggs/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
.env_docker
.env_updated
condaenv.*.requirements.txt

# Visual Studio directories
.vs/
.vscode/

# =========================================================================== #
# 	Repo-specific
# =========================================================================== #
/configs/webui/userconfig_streamlit.yaml
/configs/webui/userconfig_flet.yaml
/custom-conda-path.txt
!/src/components/*
!/src/pages/*
/src/*
/outputs
/model_cache
/log/**/*.png
/log/webui/*
/log/log.csv
/flagged/*
/gfpgan/*
/models/*
/webui/flet/assets/uploads/
/webui/flet/assets/outputs/

z_version_env.tmp
scripts/bridgeData.py
/user_data/*

# Dependencies
/node_modules

# Production
/build

# Generated files
.docusaurus
.cache-loader

# Misc
.DS_Store
.env.local
.env.development.local
.env.test.local
.env.production.local

npm-debug.log*
yarn-debug.log*
yarn-error.log*


================================================
FILE: .gitmodules
================================================


================================================
FILE: .pre-commit-config.yaml
================================================
# See https://pre-commit.com for more information
# See https://pre-commit.com/hooks.html for more hooks
ci:
  autofix_prs: true
  autoupdate_branch: 'dev'
  autoupdate_commit_msg: '[pre-commit.ci] pre-commit autoupdate'
  autoupdate_schedule: weekly

repos:
  - repo: https://github.com/pre-commit/pre-commit-hooks
    rev: v4.4.0
    hooks:
      - id: trailing-whitespace
      - id: end-of-file-fixer
      - id: check-yaml
      - id: check-added-large-files

  - repo: https://github.com/astral-sh/ruff-pre-commit
    rev: "v0.0.278"
    hooks:
      - id: ruff
        args: [--fix, --exit-non-zero-on-fix]

  - repo: https://github.com/psf/black
    rev: 23.7.0
    hooks:
      - id: black


================================================
FILE: .streamlit/config.toml
================================================
[global]
disableWatchdogWarning = false
showWarningOnDirectExecution = true
dataFrameSerialization = "arrow"

[logger]
level = "info"
messageFormat = "%(asctime)s %(message)s"

[client]
caching = true
displayEnabled = true
showErrorDetails = true

[runner]
magicEnabled = true
installTracer = false
fixMatplotlib = true
postScriptGC = true
fastReruns = false

[server]
folderWatchBlacklist = []
fileWatcherType = "auto"
cookieSecret = ""
headless = false
runOnSave = false
port = 8501
baseUrlPath = ""
enableCORS = true
enableXsrfProtection = true
maxUploadSize = 200
maxMessageSize = 200
enableWebsocketCompression = false

[browser]
gatherUsageStats = false
serverPort = 8501

[mapbox]
token = ""

[deprecation]
showfileUploaderEncoding = true
showPyplotGlobalUse = true

[theme]
base = "dark"


================================================
FILE: CONTRIBUTING.md
================================================
# Contribution Guide

All Pull Requests are opened against `dev` branch which is our main development branch.

There are two UI systems that are supported currently:

* **Gradio** — entry point is in the `/scripts/webui.py` you can start from there. Check out [Gradio documentation](https://gradio.app/docs/) and their [Discord channel](https://discord.gg/Qs8AsnX7Jd) for more information about Gradio.
* **Streamlit** — entry point is in the `/scripts/webui_streamlit.py`. Documentation on Streamlit is [located here](https://docs.streamlit.io/).

### Development environment

`environment.yaml` can be different from the one on `master` so be sure to update before making any changes to the code.

The development environment is currently very similar to the one in production, so you can work on your contribution in the same conda env. Optionally you can create a separate environment.

### Making changes

If you're working on a fix please post about it in the respective issue. If the issue doesn't exist create it and then mention it in your Pull Request.

If you're introducing new features please make the corresponding additions to the documentation with an explanation of the new behavior. The documentation is located in `/docs/`. Depending on your contribution you may edit the existing files in there or create a new one.

### Opening a Pull Request

Prior to opening a request make sure your Web UI works locally with your changes and that your branch is up-to-date with the main repository. Finally, open a new PR against `dev` branch.


================================================
FILE: Dockerfile
================================================
ARG IMAGE=tukirito/sygil-webui:base

# Use the base image
FROM ${IMAGE}

# Set the working directory
WORKDIR /workdir

# Use the specified shell
SHELL ["/bin/bash", "-c"]

# Set environment variables
ENV PYTHONPATH=/sd

# Expose the required port
EXPOSE 8501

# Copy necessary files and directories
COPY ./entrypoint.sh /sd/
COPY ./data/DejaVuSans.ttf /usr/share/fonts/truetype/
COPY ./data /sd/data
COPY ./images /sd/images
COPY ./scripts /sd/scripts
COPY ./ldm /sd/ldm
COPY ./frontend /sd/frontend
COPY ./configs /sd/configs
COPY ./configs/webui/webui_streamlit.yaml /sd/configs/webui/userconfig_streamlit.yaml
COPY ./.streamlit /sd/.streamlit
COPY ./optimizedSD /sd/optimizedSD

# Set the entrypoint
ENTRYPOINT ["/sd/entrypoint.sh"]

# Create .streamlit directory and set up credentials.toml
RUN mkdir -p ~/.streamlit \
    && echo "[general]" > ~/.streamlit/credentials.toml \
    && echo "email = \"\"" >> ~/.streamlit/credentials.toml


================================================
FILE: Dockerfile_base
================================================
ARG PYTORCH_IMAGE=hlky/pytorch:1.12.1-runtime

FROM ${PYTORCH_IMAGE}
SHELL ["/bin/bash", "-c"]

WORKDIR /install

RUN apt-get update && \
    apt-get install -y wget curl git build-essential zip unzip nano openssh-server libgl1 libsndfile1-dev && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

COPY ./requirements.txt /install/
COPY ./setup.py /install/

RUN /opt/conda/bin/python -m pip install -r /install/requirements.txt

RUN /opt/conda/bin/conda clean -ya


================================================
FILE: Dockerfile_runpod
================================================
ARG IMAGE=tukirito/sygil-webui:base

FROM ${IMAGE}

WORKDIR /workdir

SHELL ["/bin/bash", "-c"]

ENV PYTHONPATH=/sd

EXPOSE 8501
COPY ./runpod_entrypoint.sh /sd/entrypoint.sh
COPY ./data/DejaVuSans.ttf /usr/share/fonts/truetype/
COPY ./configs/ /sd/configs/
copy ./configs/webui/webui_streamlit.yaml /sd/configs/webui/userconfig_streamlit.yaml
COPY ./data/ /sd/data/
COPY ./frontend/ /sd/frontend/
COPY ./gfpgan/ /sd/gfpgan/
COPY ./images/ /sd/images/
COPY ./ldm/ /sd/ldm/
COPY ./models/ /sd/models/
copy ./optimizedSD/ /sd/optimizedSD/
COPY ./scripts/ /sd/scripts/
COPY ./.streamlit/ /sd/.streamlit/
ENTRYPOINT /sd/entrypoint.sh

RUN mkdir -p ~/.streamlit/
RUN echo "[general]"  > ~/.streamlit/credentials.toml
RUN echo "email = \"\""  >> ~/.streamlit/credentials.toml


================================================
FILE: LICENSE
================================================
                    GNU AFFERO GENERAL PUBLIC LICENSE
                       Version 3, 19 November 2007

 Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
 Everyone is permitted to copy and distribute verbatim copies
 of this license document, but changing it is not allowed.

                            Preamble

  The GNU Affero General Public License is a free, copyleft license for
software and other kinds of works, specifically designed to ensure
cooperation with the community in the case of network server software.

  The licenses for most software and other practical works are designed
to take away your freedom to share and change the works.  By contrast,
our General Public Licenses are intended to guarantee your freedom to
share and change all versions of a program--to make sure it remains free
software for all its users.

  When we speak of free software, we are referring to freedom, not
price.  Our General Public Licenses are designed to make sure that you
have the freedom to distribute copies of free software (and charge for
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want it, that you can change the software or use pieces of it in new
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  Developers that use our General Public Licenses protect your rights
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  A secondary benefit of defending all users' freedom is that
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  The GNU Affero General Public License is designed specifically to
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  An older license, called the Affero General Public License and
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  The precise terms and conditions for copying, distribution and
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================================================
FILE: README.md
================================================
# <center>Web-based UI for Stable Diffusion</center>

## Created by [Sygil.Dev](https://github.com/sygil-dev)

## Join us at Sygil.Dev's Discord Server [![Generic badge](https://flat.badgen.net/discord/members/ttM8Tm6wge?icon=discord)](https://discord.gg/ttM8Tm6wge)

## Installation instructions for:

- **[Windows](https://sygil-dev.github.io/sygil-webui/docs/Installation/windows-installation)**
- **[Linux](https://sygil-dev.github.io/sygil-webui/docs/Installation/linux-installation)**

### Want to ask a question or request a feature?

Come to our [Discord Server](https://discord.gg/gyXNe4NySY) or use [Discussions](https://github.com/sygil-dev/sygil-webui/discussions).

## Documentation

[Documentation is located here](https://sygil-dev.github.io/sygil-webui/)

## Want to contribute?

Check the [Contribution Guide](CONTRIBUTING.md)

[Sygil-Dev](https://github.com/Sygil-Dev) main devs:

* ![ZeroCool940711's avatar](https://avatars.githubusercontent.com/u/5977640?s=40&v=4)[ZeroCool940711](https://github.com/ZeroCool940711)
* ![Kasiya13's avatar](https://avatars.githubusercontent.com/u/26075839?s=40&v=4)[Kasiya13](https://github.com/Kasiya13)

### Project Features:

* Built-in image enhancers and upscalers, including GFPGAN and realESRGAN

* Generator Preview: See your image as its being made

* Run additional upscaling models on CPU to save VRAM

* Textual inversion: [Reaserch Paper](https://textual-inversion.github.io/)

* K-Diffusion Samplers: A great collection of samplers to use, including:

  - `k_euler`
  - `k_lms`
  - `k_euler_a`
  - `k_dpm_2`
  - `k_dpm_2_a`
  - `k_heun`
  - `PLMS`
  - `DDIM`

* Loopback: Automatically feed the last generated sample back into img2img

* Prompt Weighting & Negative Prompts: Gain more control over your creations

* Selectable GPU usage from Settings tab

* Word Seeds: Use words instead of seed numbers

* Automated Launcher: Activate conda and run Stable Diffusion with a single command

* Lighter on VRAM: 512x512 Text2Image & Image2Image tested working on 4GB (with *optimized* mode enabled in Settings)

* Prompt validation: If your prompt is too long, you will get a warning in the text output field

* Sequential seeds for batches: If you use a seed of 1000 to generate two batches of two images each, four generated images will have seeds: `1000, 1001, 1002, 1003`.

* Prompt matrix: Separate multiple prompts using the `|` character, and the system will produce an image for every combination of them.

* [Gradio] Advanced img2img editor with Mask and crop capabilities

* [Gradio] Mask painting 🖌️: Powerful tool for re-generating only specific parts of an image you want to change (currently Gradio only)

# SD WebUI

An easy way to work with Stable Diffusion right from your browser.

## Streamlit

![](images/streamlit/streamlit-t2i.png)

**Features:**

- Clean UI with an easy to use design, with support for widescreen displays
- *Dynamic live preview* of your generations
- Easily customizable defaults, right from the WebUI's Settings tab
- An integrated gallery to show the generations for a prompt
- *Optimized VRAM* usage for bigger generations or usage on lower end GPUs
- *Text to Video:* Generate video clips from text prompts right from the WebUI (WIP)
- Image to Text: Use [CLIP Interrogator](https://github.com/pharmapsychotic/clip-interrogator) to interrogate an image and get a prompt that you can use to generate a similar image using Stable Diffusion.
- *Concepts Library:* Run custom embeddings others have made via textual inversion.
- Textual Inversion training: Train your own embeddings on any photo you want and use it on your prompt.
- **Currently in development: [Stable Horde](https://stablehorde.net/) integration; ImgLab, batch inputs, & mask editor from Gradio

**Prompt Weights & Negative Prompts:**

To give a token (tag recognized by the AI) a specific or increased weight (emphasis), add `:0.##` to the prompt, where `0.##` is a decimal that will specify the weight of all tokens before the colon.
Ex: `cat:0.30, dog:0.70` or `guy riding a bicycle :0.7, incoming car :0.30`

Negative prompts can be added by using  `###` , after which any tokens will be seen as negative.
Ex: `cat playing with string ### yarn` will negate `yarn` from the generated image.

Negatives are a very powerful tool to get rid of contextually similar or related topics, but **be careful when adding them since the AI might see connections you can't**, and end up outputting gibberish

**Tip:* Try using the same seed with different prompt configurations or weight values see how the AI understands them, it can lead to prompts that are more well-tuned and less prone to error.

Please see the [Streamlit Documentation](docs/4.streamlit-interface.md) to learn more.

## Gradio [Legacy]

![](images/gradio/gradio-t2i.png)

**Features:**

- Older UI that is functional and feature complete.
- Has access to all upscaling models, including LSDR.
- Dynamic prompt entry automatically changes your generation settings based on `--params` in a prompt.
- Includes quick and easy ways to send generations to Image2Image or the Image Lab for upscaling.

**Note: the Gradio interface is no longer being actively developed by Sygil.Dev and is only receiving bug fixes.**

Please see the [Gradio Documentation](https://sygil-dev.github.io/sygil-webui/docs/Gradio/gradio-interface/) to learn more.

## Image Upscalers

---

### GFPGAN

![](images/GFPGAN.png)

Lets you improve faces in pictures using the GFPGAN model. There is a checkbox in every tab to use GFPGAN at 100%, and also a separate tab that just allows you to use GFPGAN on any picture, with a slider that controls how strong the effect is.

If you want to use GFPGAN to improve generated faces, you need to install it separately.
Download [GFPGANv1.4.pth](https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth) and put it
into the `/sygil-webui/models/gfpgan` directory.

### RealESRGAN

![](images/RealESRGAN.png)

Lets you double the resolution of generated images. There is a checkbox in every tab to use RealESRGAN, and you can choose between the regular upscaler and the anime version.
There is also a separate tab for using RealESRGAN on any picture.

Download [RealESRGAN_x4plus.pth](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth) and [RealESRGAN_x4plus_anime_6B.pth](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth).
Put them into the `sygil-webui/models/realesrgan` directory.

### LSDR

Download **LDSR** [project.yaml](https://heibox.uni-heidelberg.de/f/31a76b13ea27482981b4/?dl=1) and [model last.cpkt](https://heibox.uni-heidelberg.de/f/578df07c8fc04ffbadf3/?dl=1). Rename `last.ckpt` to `model.ckpt` and place both under `sygil-webui/models/ldsr/`

### GoBig, and GoLatent *(Currently on the Gradio version Only)*

More powerful upscalers that uses a separate Latent Diffusion model to more cleanly upscale images.

Please see the [Post-Processing Documentation](https://sygil-dev.github.io/sygil-webui/docs/post-processing) to learn more.

-----

### *Original Information From The Stable Diffusion Repo:*

# Stable Diffusion

*Stable Diffusion was made possible thanks to a collaboration with [Stability AI](https://stability.ai/) and [Runway](https://runwayml.com/) and builds upon our previous work:*

[**High-Resolution Image Synthesis with Latent Diffusion Models**](https://ommer-lab.com/research/latent-diffusion-models/)
[Robin Rombach](https://github.com/rromb)\*,
[Andreas Blattmann](https://github.com/ablattmann)\*,
[Dominik Lorenz](https://github.com/qp-qp)\,
[Patrick Esser](https://github.com/pesser),
[Björn Ommer](https://hci.iwr.uni-heidelberg.de/Staff/bommer)

**CVPR '22 Oral**

which is available on [GitHub](https://github.com/CompVis/latent-diffusion). PDF at [arXiv](https://arxiv.org/abs/2112.10752). Please also visit our [Project page](https://ommer-lab.com/research/latent-diffusion-models/).

[Stable Diffusion](#stable-diffusion-v1) is a latent text-to-image diffusion
model.
Thanks to a generous compute donation from [Stability AI](https://stability.ai/) and support from [LAION](https://laion.ai/), we were able to train a Latent Diffusion Model on 512x512 images from a subset of the [LAION-5B](https://laion.ai/blog/laion-5b/) database.
Similar to Google's [Imagen](https://arxiv.org/abs/2205.11487),
this model uses a frozen CLIP ViT-L/14 text encoder to condition the model on text prompts.
With its 860M UNet and 123M text encoder, the model is relatively lightweight and runs on a GPU with at least 10GB VRAM.
See [this section](#stable-diffusion-v1) below and the [model card](https://huggingface.co/CompVis/stable-diffusion).

## Stable Diffusion v1

Stable Diffusion v1 refers to a specific configuration of the model
architecture that uses a downsampling-factor 8 autoencoder with an 860M UNet
and CLIP ViT-L/14 text encoder for the diffusion model. The model was pretrained on 256x256 images and
then finetuned on 512x512 images.

*Note: Stable Diffusion v1 is a general text-to-image diffusion model and therefore mirrors biases and (mis-)conceptions that are present
in its training data.
Details on the training procedure and data, as well as the intended use of the model can be found in the corresponding [model card](https://huggingface.co/CompVis/stable-diffusion).

## Comments

- Our code base for the diffusion models builds heavily on [OpenAI's ADM codebase](https://github.com/openai/guided-diffusion)
  and [https://github.com/lucidrains/denoising-diffusion-pytorch](https://github.com/lucidrains/denoising-diffusion-pytorch).
  Thanks for open-sourcing!

- The implementation of the transformer encoder is from [x-transformers](https://github.com/lucidrains/x-transformers) by [lucidrains](https://github.com/lucidrains?tab=repositories).

## BibTeX

```
@misc{rombach2021highresolution,
      title={High-Resolution Image Synthesis with Latent Diffusion Models},
      author={Robin Rombach and Andreas Blattmann and Dominik Lorenz and Patrick Esser and Björn Ommer},
      year={2021},
      eprint={2112.10752},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}
```


================================================
FILE: Stable_Diffusion_v1_Model_Card.md
================================================
# Stable Diffusion v1 Model Card
This model card focuses on the model associated with the Stable Diffusion model, available [here](https://github.com/CompVis/stable-diffusion).

## Model Details
- **Developed by:** Robin Rombach, Patrick Esser
- **Model type:** Diffusion-based text-to-image generation model
- **Language(s):** English
- **License:** [Proprietary](LICENSE)
- **Model Description:** This is a model that can be used to generate and modify images based on text prompts. It is a [Latent Diffusion Model](https://arxiv.org/abs/2112.10752) that uses a fixed, pretrained text encoder ([CLIP ViT-L/14](https://arxiv.org/abs/2103.00020)) as suggested in the [Imagen paper](https://arxiv.org/abs/2205.11487).
- **Resources for more information:** [GitHub Repository](https://github.com/CompVis/stable-diffusion), [Paper](https://arxiv.org/abs/2112.10752).
- **Cite as:**

      @InProceedings{Rombach_2022_CVPR,
          author    = {Rombach, Robin and Blattmann, Andreas and Lorenz, Dominik and Esser, Patrick and Ommer, Bj\"orn},
          title     = {High-Resolution Image Synthesis With Latent Diffusion Models},
          booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
          month     = {June},
          year      = {2022},
          pages     = {10684-10695}
      }

# Uses

## Direct Use
The model is intended for research purposes only. Possible research areas and
tasks include

- Safe deployment of models which have the potential to generate harmful content.
- Probing and understanding the limitations and biases of generative models.
- Generation of artworks and use in design and other artistic processes.
- Applications in educational or creative tools.
- Research on generative models.

Excluded uses are described below.

 ### Misuse, Malicious Use, and Out-of-Scope Use
_Note: This section is taken from the [DALLE-MINI model card](https://huggingface.co/dalle-mini/dalle-mini), but applies in the same way to Stable Diffusion v1_.


The model should not be used to intentionally create or disseminate images that create hostile or alienating environments for people. This includes generating images that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.
#### Out-of-Scope Use
The model was not trained to be factual or true representations of people or events, and therefore using the model to generate such content is out-of-scope for the abilities of this model.
#### Misuse and Malicious Use
Using the model to generate content that is cruel to individuals is a misuse of this model. This includes, but is not limited to:

- Generating demeaning, dehumanizing, or otherwise harmful representations of people or their environments, cultures, religions, etc.
- Intentionally promoting or propagating discriminatory content or harmful stereotypes.
- Impersonating individuals without their consent.
- Sexual content without consent of the people who might see it.
- Mis- and disinformation
- Representations of egregious violence and gore
- Sharing of copyrighted or licensed material in violation of its terms of use.
- Sharing content that is an alteration of copyrighted or licensed material in violation of its terms of use.

## Limitations and Bias

### Limitations

- The model does not achieve perfect photorealism
- The model cannot render legible text
- The model does not perform well on more difficult tasks which involve compositionality, such as rendering an image corresponding to “A red cube on top of a blue sphere”
- Faces and people in general may not be generated properly.
- The model was trained mainly with English captions and will not work as well in other languages.
- The autoencoding part of the model is lossy
- The model was trained on a large-scale dataset
  [LAION-5B](https://laion.ai/blog/laion-5b/) which contains adult material
  and is not fit for product use without additional safety mechanisms and
  considerations.

### Bias
While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases.
Stable Diffusion v1 was trained on subsets of [LAION-2B(en)](https://laion.ai/blog/laion-5b/),
which consists of images that are primarily limited to English descriptions.
Texts and images from communities and cultures that use other languages are likely to be insufficiently accounted for.
This affects the overall output of the model, as white and western cultures are often set as the default. Further, the
ability of the model to generate content with non-English prompts is significantly worse than with English-language prompts.


## Training

**Training Data**
The model developers used the following dataset for training the model:

- LAION-2B (en) and subsets thereof (see next section)

**Training Procedure**
Stable Diffusion v1 is a latent diffusion model which combines an autoencoder with a diffusion model that is trained in the latent space of the autoencoder. During training,

- Images are encoded through an encoder, which turns images into latent representations. The autoencoder uses a relative downsampling factor of 8 and maps images of shape H x W x 3 to latents of shape H/f x W/f x 4
- Text prompts are encoded through a ViT-L/14 text-encoder.
- The non-pooled output of the text encoder is fed into the UNet backbone of the latent diffusion model via cross-attention.
- The loss is a reconstruction objective between the noise that was added to the latent and the prediction made by the UNet.

We currently provide three checkpoints, `sd-v1-1.ckpt`, `sd-v1-2.ckpt` and `sd-v1-3.ckpt`,
which were trained as follows,

- `sd-v1-1.ckpt`: 237k steps at resolution `256x256` on [laion2B-en](https://huggingface.co/datasets/laion/laion2B-en).
  194k steps at resolution `512x512` on [laion-high-resolution](https://huggingface.co/datasets/laion/laion-high-resolution) (170M examples from LAION-5B with resolution `>= 1024x1024`).
- `sd-v1-2.ckpt`: Resumed from `sd-v1-1.ckpt`.
  515k steps at resolution `512x512` on "laion-improved-aesthetics" (a subset of laion2B-en,
filtered to images with an original size `>= 512x512`, estimated aesthetics score `> 5.0`, and an estimated watermark probability `< 0.5`. The watermark estimate is from the LAION-5B metadata, the aesthetics score is estimated using an [improved aesthetics estimator](https://github.com/christophschuhmann/improved-aesthetic-predictor)).
- `sd-v1-3.ckpt`: Resumed from `sd-v1-2.ckpt`. 195k steps at resolution `512x512` on "laion-improved-aesthetics" and 10\% dropping of the text-conditioning to improve [classifier-free guidance sampling](https://arxiv.org/abs/2207.12598).


- **Hardware:** 32 x 8 x A100 GPUs
- **Optimizer:** AdamW
- **Gradient Accumulations**: 2
- **Batch:** 32 x 8 x 2 x 4 = 2048
- **Learning rate:** warmup to 0.0001 for 10,000 steps and then kept constant

## Evaluation Results
Evaluations with different classifier-free guidance scales (1.5, 2.0, 3.0, 4.0,
5.0, 6.0, 7.0, 8.0) and 50 PLMS sampling
steps show the relative improvements of the checkpoints:

![pareto](assets/v1-variants-scores.jpg)

Evaluated using 50 PLMS steps and 10000 random prompts from the COCO2017 validation set, evaluated at 512x512 resolution.  Not optimized for FID scores.
## Environmental Impact

**Stable Diffusion v1** **Estimated Emissions**
Based on that information, we estimate the following CO2 emissions using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). The hardware, runtime, cloud provider, and compute region were utilized to estimate the carbon impact.

- **Hardware Type:** A100 PCIe 40GB
- **Hours used:** 150000
- **Cloud Provider:** AWS
- **Compute Region:** US-east
- **Carbon Emitted (Power consumption x Time x Carbon produced based on location of power grid):** 11250 kg CO2 eq.
## Citation
    @InProceedings{Rombach_2022_CVPR,
        author    = {Rombach, Robin and Blattmann, Andreas and Lorenz, Dominik and Esser, Patrick and Ommer, Bj\"orn},
        title     = {High-Resolution Image Synthesis With Latent Diffusion Models},
        booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
        month     = {June},
        year      = {2022},
        pages     = {10684-10695}
    }

*This model card was written by: Robin Rombach and Patrick Esser and is based on the [DALL-E Mini model card](https://huggingface.co/dalle-mini/dalle-mini).*


================================================
FILE: Web_based_UI_for_Stable_Diffusion_colab.ipynb
================================================
{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "S5RoIM-5IPZJ"
      },
      "source": [
        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Sygil-Dev/sygil-webui/blob/main/Web_based_UI_for_Stable_Diffusion_colab.ipynb)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5-Bx4AsEoPU-"
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      "source": [
        "# README"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z4kQYMPQn4d-"
      },
      "source": [
        "###<center>Web-based UI for Stable Diffusion</center>\n",
        "\n",
        "## Created by [Sygil-Dev](https://github.com/Sygil-Dev)\n",
        "\n",
        "## [Visit Sygil-Dev's Discord Server](https://discord.gg/gyXNe4NySY) [![Discord Server](https://user-images.githubusercontent.com/5977640/190528254-9b5b4423-47ee-4f24-b4f9-fd13fba37518.png)](https://discord.gg/gyXNe4NySY)\n",
        "\n",
        "## Installation instructions for:\n",
        "\n",
        "- **[Windows](https://sygil-dev.github.io/sygil-webui/docs/1.windows-installation.html)**\n",
        "- **[Linux](https://sygil-dev.github.io/sygil-webui/docs/2.linux-installation.html)**\n",
        "\n",
        "### Want to ask a question or request a feature?\n",
        "\n",
        "Come to our [Discord Server](https://discord.gg/gyXNe4NySY) or use [Discussions](https://github.com/Sygil-Dev/sygil-webui/discussions).\n",
        "\n",
        "## Documentation\n",
        "\n",
        "[Documentation is located here](https://sygil-dev.github.io/sygil-webui/)\n",
        "\n",
        "## Want to contribute?\n",
        "\n",
        "Check the [Contribution Guide](CONTRIBUTING.md)\n",
        "\n",
        "[Sygil-Dev](https://github.com/Sygil-Dev) main devs:\n",
        "\n",
        "* ![hlky's avatar](https://avatars.githubusercontent.com/u/106811348?s=40&v=4) [hlky](https://github.com/hlky)\n",
        "* ![ZeroCool940711's avatar](https://avatars.githubusercontent.com/u/5977640?s=40&v=4)[ZeroCool940711](https://github.com/ZeroCool940711)\n",
        "* ![codedealer's avatar](https://avatars.githubusercontent.com/u/4258136?s=40&v=4)[codedealer](https://github.com/codedealer)\n",
        "\n",
        "### Project Features:\n",
        "\n",
        "* Two great Web UI's to choose from: Streamlit or Gradio\n",
        "\n",
        "* No more manually typing parameters, now all you have to do is write your prompt and adjust sliders\n",
        "\n",
        "* Built-in image enhancers and upscalers, including GFPGAN and realESRGAN\n",
        "\n",
        "* Run additional upscaling models on CPU to save VRAM\n",
        "\n",
        "* Textual inversion 🔥: [info](https://textual-inversion.github.io/) - requires enabling, see [here](https://github.com/hlky/sd-enable-textual-inversion), script works as usual without it enabled\n",
        "\n",
        "* Advanced img2img editor with Mask and crop capabilities\n",
        "\n",
        "* Mask painting 🖌️: Powerful tool for re-generating only specific parts of an image you want to change (currently Gradio only)\n",
        "\n",
        "* More diffusion samplers 🔥🔥: A great collection of samplers to use, including:\n",
        "  \n",
        "  - `k_euler` (Default)\n",
        "  - `k_lms`\n",
        "  - `k_euler_a`\n",
        "  - `k_dpm_2`\n",
        "  - `k_dpm_2_a`\n",
        "  - `k_heun`\n",
        "  - `PLMS`\n",
        "  - `DDIM`\n",
        "\n",
        "* Loopback ➿: Automatically feed the last generated sample back into img2img\n",
        "\n",
        "* Prompt Weighting 🏋️: Adjust the strength of different terms in your prompt\n",
        "\n",
        "* Selectable GPU usage with `--gpu <id>`\n",
        "\n",
        "* Memory Monitoring 🔥: Shows VRAM usage and generation time after outputting\n",
        "\n",
        "* Word Seeds 🔥: Use words instead of seed numbers\n",
        "\n",
        "* CFG: Classifier free guidance scale, a feature for fine-tuning your output\n",
        "\n",
        "* Automatic Launcher: Activate conda and run Stable Diffusion with a single command\n",
        "\n",
        "* Lighter on VRAM: 512x512 Text2Image & Image2Image tested working on 4GB\n",
        "\n",
        "* Prompt validation: If your prompt is too long, you will get a warning in the text output field\n",
        "\n",
        "* Copy-paste generation parameters: A text output provides generation parameters in an easy to copy-paste form for easy sharing.\n",
        "\n",
        "* Correct seeds for batches: If you use a seed of 1000 to generate two batches of two images each, four generated images will have seeds: `1000, 1001, 1002, 1003`.\n",
        "\n",
        "* Prompt matrix: Separate multiple prompts using the `|` character, and the system will produce an image for every combination of them.\n",
        "\n",
        "* Loopback for Image2Image: A checkbox for img2img allowing to automatically feed output image as input for the next batch. Equivalent to saving output image, and replacing input image with it.\n",
        "\n",
        "# Stable Diffusion Web UI\n",
        "\n",
        "A fully-integrated and easy way to work with Stable Diffusion right from a browser window.\n",
        "\n",
        "## Streamlit\n",
        "\n",
        "![](https://github.com/aedhcarrick/sygil-webui/blob/patch-2/images/streamlit/streamlit-t2i.png?raw=1)\n",
        "\n",
        "**Features:**\n",
        "\n",
        "- Clean UI with an easy to use design, with support for widescreen displays.\n",
        "- Dynamic live preview of your generations\n",
        "- Easily customizable presets right from the WebUI (Coming Soon!)\n",
        "- An integrated gallery to show the generations for a prompt or session (Coming soon!)\n",
        "- Better optimization VRAM usage optimization, less errors for bigger generations.\n",
        "- Text2Video - Generate video clips from text prompts right from the WEb UI (WIP)\n",
        "- Concepts Library - Run custom embeddings others have made via textual inversion.\n",
        "- Actively being developed with new features being added and planned - Stay Tuned!\n",
        "- Streamlit is now the new primary UI for the project moving forward.\n",
        "- *Currently in active development and still missing some of the features present in the Gradio Interface.*\n",
        "\n",
        "Please see the [Streamlit Documentation](docs/4.streamlit-interface.md) to learn more.\n",
        "\n",
        "## Gradio\n",
        "\n",
        "![](https://github.com/aedhcarrick/sygil-webui/blob/patch-2/images/gradio/gradio-t2i.png?raw=1)\n",
        "\n",
        "**Features:**\n",
        "\n",
        "- Older UI design that is fully functional and feature complete.\n",
        "- Has access to all upscaling models, including LSDR.\n",
        "- Dynamic prompt entry automatically changes your generation settings based on `--params` in a prompt.\n",
        "- Includes quick and easy ways to send generations to Image2Image or the Image Lab for upscaling.\n",
        "- *Note, the Gradio interface is no longer being actively developed and is only receiving bug fixes.*\n",
        "\n",
        "Please see the [Gradio Documentation](docs/5.gradio-interface.md) to learn more.\n",
        "\n",
        "## Image Upscalers\n",
        "\n",
        "---\n",
        "\n",
        "### GFPGAN\n",
        "\n",
        "![](https://github.com/aedhcarrick/sygil-webui/blob/patch-2/images/GFPGAN.png?raw=1)\n",
        "\n",
        "Lets you improve faces in pictures using the GFPGAN model. There is a checkbox in every tab to use GFPGAN at 100%, and also a separate tab that just allows you to use GFPGAN on any picture, with a slider that controls how strong the effect is.\n",
        "\n",
        "If you want to use GFPGAN to improve generated faces, you need to install it separately.\n",
        "Download [GFPGANv1.4.pth](https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth) and put it\n",
        "into the `/sygil-webui/models/gfpgan` directory.\n",
        "\n",
        "### RealESRGAN\n",
        "\n",
        "![](https://github.com/aedhcarrick/sygil-webui/blob/patch-2/images/RealESRGAN.png?raw=1)\n",
        "\n",
        "Lets you double the resolution of generated images. There is a checkbox in every tab to use RealESRGAN, and you can choose between the regular upscaler and the anime version.\n",
        "There is also a separate tab for using RealESRGAN on any picture.\n",
        "\n",
        "Download [RealESRGAN_x4plus.pth](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth) and [RealESRGAN_x4plus_anime_6B.pth](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth).\n",
        "Put them into the `sygil-webui/models/realesrgan` directory.\n",
        "\n",
        "\n",
        "\n",
        "### LSDR\n",
        "\n",
        "Download **LDSR** [project.yaml](https://heibox.uni-heidelberg.de/f/31a76b13ea27482981b4/?dl=1) and [model last.cpkt](https://heibox.uni-heidelberg.de/f/578df07c8fc04ffbadf3/?dl=1). Rename last.ckpt to model.ckpt and place both under `sygil-webui/models/ldsr/`\n",
        "\n",
        "### GoBig, and GoLatent *(Currently on the Gradio version Only)*\n",
        "\n",
        "More powerful upscalers that uses a seperate Latent Diffusion model to more cleanly upscale images.\n",
        "\n",
        "\n",
        "\n",
        "Please see the [Image Enhancers Documentation](docs/6.image_enhancers.md) to learn more.\n",
        "\n",
        "-----\n",
        "\n",
        "### *Original Information From The Stable Diffusion Repo*\n",
        "\n",
        "# Stable Diffusion\n",
        "\n",
        "*Stable Diffusion was made possible thanks to a collaboration with [Stability AI](https://stability.ai/) and [Runway](https://runwayml.com/) and builds upon our previous work:*\n",
        "\n",
        "[**High-Resolution Image Synthesis with Latent Diffusion Models**](https://ommer-lab.com/research/latent-diffusion-models/)<br/>\n",
        "[Robin Rombach](https://github.com/rromb)\\*,\n",
        "[Andreas Blattmann](https://github.com/ablattmann)\\*,\n",
        "[Dominik Lorenz](https://github.com/qp-qp)\\,\n",
        "[Patrick Esser](https://github.com/pesser),\n",
        "[Björn Ommer](https://hci.iwr.uni-heidelberg.de/Staff/bommer)<br/>\n",
        "\n",
        "**CVPR '22 Oral**\n",
        "\n",
        "which is available on [GitHub](https://github.com/CompVis/latent-diffusion). PDF at [arXiv](https://arxiv.org/abs/2112.10752). Please also visit our [Project page](https://ommer-lab.com/research/latent-diffusion-models/).\n",
        "\n",
        "[Stable Diffusion](#stable-diffusion-v1) is a latent text-to-image diffusion\n",
        "model.\n",
        "Thanks to a generous compute donation from [Stability AI](https://stability.ai/) and support from [LAION](https://laion.ai/), we were able to train a Latent Diffusion Model on 512x512 images from a subset of the [LAION-5B](https://laion.ai/blog/laion-5b/) database.\n",
        "Similar to Google's [Imagen](https://arxiv.org/abs/2205.11487),\n",
        "this model uses a frozen CLIP ViT-L/14 text encoder to condition the model on text prompts.\n",
        "With its 860M UNet and 123M text encoder, the model is relatively lightweight and runs on a GPU with at least 10GB VRAM.\n",
        "See [this section](#stable-diffusion-v1) below and the [model card](https://huggingface.co/CompVis/stable-diffusion).\n",
        "\n",
        "## Stable Diffusion v1\n",
        "\n",
        "Stable Diffusion v1 refers to a specific configuration of the model\n",
        "architecture that uses a downsampling-factor 8 autoencoder with an 860M UNet\n",
        "and CLIP ViT-L/14 text encoder for the diffusion model. The model was pretrained on 256x256 images and\n",
        "then finetuned on 512x512 images.\n",
        "\n",
        "*Note: Stable Diffusion v1 is a general text-to-image diffusion model and therefore mirrors biases and (mis-)conceptions that are present\n",
        "in its training data.\n",
        "Details on the training procedure and data, as well as the intended use of the model can be found in the corresponding [model card](https://huggingface.co/CompVis/stable-diffusion).\n",
        "\n",
        "## Comments\n",
        "\n",
        "- Our codebase for the diffusion models builds heavily on [OpenAI's ADM codebase](https://github.com/openai/guided-diffusion)\n",
        "  and [https://github.com/lucidrains/denoising-diffusion-pytorch](https://github.com/lucidrains/denoising-diffusion-pytorch).\n",
        "  Thanks for open-sourcing!\n",
        "\n",
        "- The implementation of the transformer encoder is from [x-transformers](https://github.com/lucidrains/x-transformers) by [lucidrains](https://github.com/lucidrains?tab=repositories).\n",
        "\n",
        "## BibTeX\n",
        "\n",
        "```\n",
        "@misc{rombach2021highresolution,\n",
        "      title={High-Resolution Image Synthesis with Latent Diffusion Models},\n",
        "      author={Robin Rombach and Andreas Blattmann and Dominik Lorenz and Patrick Esser and Björn Ommer},\n",
        "      year={2021},\n",
        "      eprint={2112.10752},\n",
        "      archivePrefix={arXiv},\n",
        "      primaryClass={cs.CV}\n",
        "}\n",
        "\n",
        "```"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iegma7yteERV"
      },
      "source": [
        "# Config options for Colab instance\n",
        "> Before running, make sure GPU backend is enabled. (Unless you plan on generating with Stable Horde)\n",
        ">> Runtime -> Change runtime type -> Hardware Accelerator -> GPU (Make sure to  save)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "OXn96M9deVtF"
      },
      "outputs": [],
      "source": [
        "#@title  { display-mode: \"form\" }\n",
        "#@markdown WebUI repo (and branch)\n",
        "repo_name = \"Sygil-Dev/sygil-webui\" #@param {type:\"string\"}\n",
        "repo_branch = \"dev\" #@param {type:\"string\"}\n",
        "\n",
        "#@markdown Mount Google Drive\n",
        "mount_google_drive = True #@param {type:\"boolean\"}\n",
        "save_outputs_to_drive = True #@param {type:\"boolean\"}\n",
        "#@markdown Folder in Google Drive to search for custom models\n",
        "MODEL_DIR = \"sygil-webui/models\" #@param {type:\"string\"}\n",
        "\n",
        "#@markdown Folder in Google Drive to look for custom config file (streamlit.yaml)\n",
        "CONFIG_DIR = \"sygil-webui\" #@param {type:\"string\"}\n",
        "\n",
        "#@markdown Enter auth token from Huggingface.co\n",
        "#@markdown >(required for downloading stable diffusion model.)\n",
        "HF_TOKEN = \"\" #@param {type:\"string\"}\n",
        "\n",
        "#@markdown Select which models to prefetch\n",
        "STABLE_DIFFUSION = True #@param {type:\"boolean\"}\n",
        "WAIFU_DIFFUSION = False #@param {type:\"boolean\"}\n",
        "TRINART_SD = False #@param {type:\"boolean\"}\n",
        "SD_WD_LD_TRINART_MERGED = False #@param {type:\"boolean\"}\n",
        "GFPGAN = True #@param {type:\"boolean\"}\n",
        "REALESRGAN = True #@param {type:\"boolean\"}\n",
        "LDSR = True #@param {type:\"boolean\"}\n",
        "BLIP_MODEL = False #@param {type:\"boolean\"}\n",
        "\n",
        "#@markdown Save models to Google Drive for faster loading in future (Be warned! Make sure you have enough space!)\n",
        "SAVE_MODELS = False #@param {type:\"boolean\"}"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IZjJSr-WPNxB"
      },
      "source": [
        "# Setup\n",
        "\n",
        ">Runtime will crash when installing conda. This is normal as we are forcing a restart of the runtime from code.\n",
        "\n",
        ">Just hit \"Run All\" again. 😑"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "eq0-E5mjSpmP"
      },
      "outputs": [],
      "source": [
        "#@title Make sure we have access to GPU backend\n",
        "!nvidia-smi -L"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "cDu33xkdJ5mD"
      },
      "outputs": [],
      "source": [
        "#@title Install miniConda (mamba)\n",
        "!pip install condacolab\n",
        "import condacolab\n",
        "condacolab.install_from_url(\"https://github.com/conda-forge/miniforge/releases/download/4.14.0-0/Mambaforge-4.14.0-0-Linux-x86_64.sh\")\n",
        "\n",
        "import condacolab\n",
        "condacolab.check()\n",
        "# The runtime will crash here!!! Don't panic! We planned for this remember?"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "pZHGf03Vp305"
      },
      "outputs": [],
      "source": [
        "#@title Clone webUI repo and download font\n",
        "import os\n",
        "REPO_URL = os.path.join('https://github.com', repo_name)\n",
        "PATH_TO_REPO = os.path.join('/content', repo_name.split('/')[1])\n",
        "!git clone {REPO_URL}\n",
        "%cd {PATH_TO_REPO}\n",
        "!git checkout {repo_branch}\n",
        "!git pull"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "dmN2igp5Yk3z"
      },
      "outputs": [],
      "source": [
        "#@title Install dependencies\n",
        "!mamba install cudatoolkit=11.3 git numpy=1.22.3 pip=20.3 python=3.8.5 pytorch=1.11.0 scikit-image=0.19.2 torchvision=0.12.0 -y\n",
        "!python --version\n",
        "!pip install -r requirements.txt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Nxaxfgo_F8Am"
      },
      "outputs": [],
      "source": [
        "#@title Install localtunnel to openGoogle's ports\n",
        "!npm install localtunnel"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "pcSWo9Zkzbsf"
      },
      "outputs": [],
      "source": [
        "#@title Mount Google Drive (if selected)\n",
        "if mount_google_drive:\n",
        "    # Mount google drive to store outputs.\n",
        "    from google.colab import drive\n",
        "    drive.mount('/content/drive/', force_remount=True)\n",
        "\n",
        "if save_outputs_to_drive:\n",
        "    # Make symlink to redirect downloads\n",
        "    OUTPUT_PATH = os.path.join('/content/drive/MyDrive', repo_name.split('/')[1], 'outputs')\n",
        "    os.makedirs(OUTPUT_PATH, exist_ok=True)\n",
        "    os.symlink(OUTPUT_PATH, os.path.join(PATH_TO_REPO, 'outputs'), target_is_directory=True)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "vMdmh81J70yA"
      },
      "outputs": [],
      "source": [
        "#@title Pre-fetch models\n",
        "%cd {PATH_TO_REPO}\n",
        "# make list of models we want to download\n",
        "model_list = {\n",
        " 'stable_diffusion': f'{STABLE_DIFFUSION}',\n",
        " 'waifu_diffusion': f'{WAIFU_DIFFUSION}',\n",
        " 'trinart_stable_diffusion': f'{TRINART_SD}',\n",
        " 'sd_wd_ld_trinart_merged': f'{SD_WD_LD_TRINART_MERGED}',\n",
        " 'gfpgan': f'{GFPGAN}',\n",
        " 'realesrgan': f'{REALESRGAN}',\n",
        " 'ldsr': f'{LDSR}',\n",
        " 'blip_model': f'{BLIP_MODEL}'}\n",
        "download_list = {k for (k,v) in model_list.items() if v == 'True'}\n",
        "\n",
        "# get model info (file name, download link, save location)\n",
        "import yaml\n",
        "from pprint import pprint\n",
        "with open('configs/webui/webui_streamlit.yaml') as f:\n",
        "    dataMap = yaml.safe_load(f)\n",
        "models = dataMap['model_manager']['models']\n",
        "existing_models = []\n",
        "\n",
        "# copy script from model manager\n",
        "import requests, time, shutil\n",
        "from requests.auth import HTTPBasicAuth\n",
        "\n",
        "if MODEL_DIR != \"\":\n",
        "    MODEL_DIR = os.path.join('/content/drive/MyDrive', MODEL_DIR)\n",
        "else:\n",
        "    MODEL_DIR = '/content/drive/MyDrive'\n",
        "\n",
        "def download_file(file_name, file_path, file_url):\n",
        "    os.makedirs(file_path, exist_ok=True)\n",
        "    link_path = os.path.join(MODEL_DIR, file_name)\n",
        "    full_path = os.path.join(file_path, file_name)\n",
        "    if os.path.exists(link_path):\n",
        "        print( file_name + \" found in Google Drive\")\n",
        "        if not os.path.exists(full_path):\n",
        "            print( \"  creating symlink...\")\n",
        "            os.symlink(link_path, full_path)\n",
        "        else:\n",
        "            print( \"  symlink already exists\")\n",
        "    elif not os.path.exists(full_path):\n",
        "        print( \"Downloading \" + file_name + \"...\", end=\"\" )\n",
        "        token = None\n",
        "        if \"huggingface.co\" in file_url:\n",
        "            token = HTTPBasicAuth('token', HF_TOKEN)\n",
        "        try:\n",
        "            with requests.get(file_url, auth = token, stream=True) as r:\n",
        "                starttime = time.time()\n",
        "                r.raise_for_status()\n",
        "                with open(full_path, 'wb') as f:\n",
        "                    for chunk in r.iter_content(chunk_size=8192):\n",
        "                        f.write(chunk)\n",
        "                        if ((time.time() - starttime) % 60.0) > 2 :\n",
        "                            starttime = time.time()\n",
        "                            print( \".\", end=\"\" )\n",
        "                print( \"done\" )\n",
        "                print( \"  \" + file_name + \" downloaded to \\'\" + file_path + \"\\'\" )\n",
        "            if SAVE_MODELS and os.path.exists(MODEL_DIR):\n",
        "                shutil.copy2(full_path,MODEL_DIR)\n",
        "                print( \"  Saved \" + file_name + \" to \" + MODEL_DIR)\n",
        "        except:\n",
        "            print( \"Failed to download \" + file_name + \".\" )\n",
        "            return\n",
        "    else:\n",
        "        print( full_path + \" already exists.\" )\n",
        "    existing_models.append(file_name)\n",
        "\n",
        "# download models in list\n",
        "for model in download_list:\n",
        "    model_name = models[model]['model_name']\n",
        "    file_info = models[model]['files']\n",
        "    for file in file_info:\n",
        "        file_name = file_info[file]['file_name']\n",
        "        file_url = file_info[file]['download_link']\n",
        "        if 'save_location' in file_info[file]:\n",
        "            file_path = file_info[file]['save_location']\n",
        "        else:\n",
        "            file_path = models[model]['save_location']\n",
        "        download_file(file_name, file_path, file_url)\n",
        "\n",
        "# add custom models not in list\n",
        "CUSTOM_MODEL_DIR = os.path.join(PATH_TO_REPO, 'models/custom')\n",
        "if os.path.exists(MODEL_DIR):\n",
        "    custom_models = os.listdir(MODEL_DIR)\n",
        "    custom_models = [m for m in custom_models if os.path.isfile(MODEL_DIR + '/' + m)]\n",
        "    os.makedirs(CUSTOM_MODEL_DIR, exist_ok=True)\n",
        "    print( \"Custom model(s) found: \" )\n",
        "    for m in custom_models:\n",
        "        if m in existing_models:\n",
        "            continue\n",
        "        full_path = os.path.join(CUSTOM_MODEL_DIR, m)\n",
        "        if not os.path.exists(full_path):\n",
        "            print( \"  \" + m )\n",
        "            os.symlink(os.path.join(MODEL_DIR , m), full_path)\n",
        "\n",
        "# get custom config file if it exists\n",
        "if CONFIG_DIR != \"\":\n",
        "    CONFIG_FILE = os.path.join('/content/drive/MyDrive', CONFIG_DIR, 'userconfig_streamlit.yaml')\n",
        "    config_location = os.path.join(PATH_TO_REPO, 'configs/webui/userconfig_streamlit.yaml')\n",
        "    if os.path.exists(CONFIG_FILE) and not os.path.exists(config_location):\n",
        "        os.symlink(CONFIG_DIR, config_location)\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pjIjiCuJysJI"
      },
      "source": [
        "# Launch the web ui server\n",
        "### (optional) JS to prevent idle timeout:\n",
        "Press 'F12' OR ('CTRL' + 'SHIFT' + 'I') OR right click on this website -> inspect. Then click on the console tab and paste in the following code.\n",
        "```js,\n",
        "function ClickConnect(){\n",
        "console.log(\"Working\");\n",
        "document.querySelector(\"colab-toolbar-button#connect\").click()\n",
        "}\n",
        "setInterval(ClickConnect,60000)\n",
        "```"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-WknaU7uu_q6"
      },
      "outputs": [],
      "source": [
        "#@title Press play on the music player to keep the tab alive (Uses only 13MB of data)\n",
        "%%html\n",
        "<b>Press play on the music player to keep the tab alive, then start your generation below (Uses only 13MB of data)</b><br/>\n",
        "<audio src=\"https://henk.tech/colabkobold/silence.m4a\" controls>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "5whXm2nfSZ39"
      },
      "outputs": [],
      "source": [
        "#@title Run localtunnel and start Streamlit server. ('Ctrl' + 'left click') on link in the 'link.txt' file. (/content/link.txt)\n",
        "!npx localtunnel --port 8501 &>/content/link.txt &\n",
        "!streamlit run scripts/webui_streamlit.py --theme.base dark --server.headless true 2>&1 | tee -a /content/log.txt"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QhazvrFG97zX"
      },
      "source": [
        "Run Streamlit through cloudflare."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jjjjjjjjjjjjjj"
      },
      "outputs": [],
      "source": [
        "#@title Run Streamlit through cloudflare.\n",
        "!wget https://github.com/cloudflare/cloudflared/releases/latest/download/cloudflared-linux-amd64.deb\n",
        "!dpkg -i cloudflared-linux-amd64.deb\n",
        "\n",
        "import subprocess\n",
        "import threading\n",
        "import time\n",
        "import socket\n",
        "import urllib.request\n",
        "\n",
        "def iframe_thread(port):\n",
        "  while True:\n",
        "      time.sleep(0.5)\n",
        "      sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n",
        "      result = sock.connect_ex(('127.0.0.1', port))\n",
        "      if result == 0:\n",
        "        break\n",
        "      sock.close()\n",
        "\n",
        "  p = subprocess.Popen([\"cloudflared\", \"tunnel\", \"--url\", \"http://127.0.0.1:{}\".format(port)], stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n",
        "  for line in p.stderr:\n",
        "    l = line.decode()\n",
        "    if \"trycloudflare.com \" in l:\n",
        "      print(\"This is the URL to access Sygil WebUI:\", l[l.find(\"http\"):], end='')\n",
        "\n",
        "\n",
        "threading.Thread(target=iframe_thread, daemon=True, args=(8501,)).start()\n",
        "\n",
        "!streamlit run scripts/webui_streamlit.py --theme.base dark --server.headless true"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "collapsed_sections": [
        "5-Bx4AsEoPU-",
        "xMWVQOg0G1Pj"
      ],
      "private_outputs": true,
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}


================================================
FILE: _config.yml
================================================
plugins:
  - jekyll-relative-links
  - jekyll-readme-index
  - jemoji
  - jekyll-remote-theme
relative_links:
  enabled: true
  collections: true
source: docs
remote_theme: jekyll/minima
minima:
  skin: dark
include:
  - CONTRIBUTING.md


================================================
FILE: babel.config.js
================================================
module.exports = {
  presets: [require.resolve('@docusaurus/core/lib/babel/preset')],
};


================================================
FILE: blog/2022-10-20/1.Textual inversion usage competitio.md
================================================
# Textual inversion usage competition

We are hosting a competition where the community can showcase their most inventive use of textual inversion concepts in text-to-image or text-to-video.

Our compute cluster; `Nataili`, currently comprises of 3 nodes, two have 3090, the other has 2 x A5000.

We estimate `Nataili` can handle 12 concepts per hour, and we can add more workers if there is high demand.

Hopefully demand will be high, we want to train **hundreds** of new concepts!

# Schedule

2022/10/20 - Stage 1 begins, train concept command opened for usage

2022/10/22 12AM UTC - Stage 2 begins, text to image command opened for usage

2022/10/22 12PM UTC - Stage 1 ends, train concept command closed

2022/10/24 12PM UTC - Stage 2 ends, no more entries will be accepted

2022/10/24 6-12PM UTC - Winners announced


# What does `most inventive use` mean?

Whatever you want it to mean! be creative! experiment!

There are several categories we will look at:

* anything that's particularly creative, ~ artistic ~ or a e s t h e t i c

![20221019203426_00000](https://user-images.githubusercontent.com/106811348/197045193-d6f9c56b-9989-4f1c-b42a-bb02d62d77cd.png)

* composition; meaning anything related to how big things are, their position, the angle, etc

* styling;

![image](https://user-images.githubusercontent.com/106811348/197045629-029ba6f5-1f79-475c-9ce7-969aaf3d253b.png)

* `The Sims(TM): Stable Diffusion edition`

## So I can trai-

* Yes, as long as it's sfw

## `The Sims(TM): Stable Diffusion edition` ?

For this event the theme is “The Sims: Stable Diffusion edition”.

So we have selected a subset of [products from Amazon Berkely Objects dataset](https://github.com/sd-webui/abo).

Any other object is welcome too these are just a good source of data for this part of the competition.

Each product has images from multiple angles, the train concept command accepts up to 10 images, so choose the angles and modify backgrounds, experiment!

The goal with this category is to generate an image using the trained object, and the other categories apply, your imagination is the only limit! style a couch, try to make a BIG couch, try to make a couch on top of a mountain, try to make a vaporwave couch, anything!

# How do I train a concept using the discord bot?

Type `/trainconcept` then press tab to go through the fields

`Concept name` is just a name for your concept, it doesn't have to be a single word

`Placeholder` is what you will use in prompts to represent your concept
Add `<` and `>` so it is unique, multiple words should be hyphenated

`Initializer` is used as the starting point for training your concept, so this should be a single word that represents your concept

Minimum 2 images. Squareish aspect ratios work best

![Untitled-2](https://user-images.githubusercontent.com/106811348/197035834-cc973e29-31f8-48de-be2d-788fbe938b2e.png)
![image](https://user-images.githubusercontent.com/106811348/197035870-b91ef2a8-0ffd-47e1-a8df-9600df26cd6b.png)

# How do I use the trained concept?

## Prompting with concepts

When your concept is trained you can use it in prompts.

`a cute <nvidiafu> as an astronaut`:

![image](https://user-images.githubusercontent.com/106811348/197037250-044ea241-72a5-4caa-b772-35034245b4b6.png)

or `a green <green-couch> sitting on top of a floor, a 3D render, trending on polycount, minimalism, rendered in cinema4d`:

![image](https://user-images.githubusercontent.com/106811348/197037344-7ce72188-9129-4ba2-8a28-cba5fd664a9c.png)

## Using concepts in the webui

The discord bot will give you a link to a `.zip` file, download this, extract it, and put the folder in `stable-diffusion-webui/models/custom/sd-concepts-library`

![image](https://user-images.githubusercontent.com/106811348/197037892-ce53bea4-d1db-4b25-bb7c-7dfe4d71b2b1.png)


================================================
FILE: blog/authors.yml
================================================
endi:
  name: Endilie Yacop Sucipto
  title: Maintainer of Docusaurus
  url: https://github.com/endiliey
  image_url: https://github.com/endiliey.png

yangshun:
  name: Yangshun Tay
  title: Front End Engineer @ Facebook
  url: https://github.com/yangshun
  image_url: https://github.com/yangshun.png

slorber:
  name: Sébastien Lorber
  title: Docusaurus maintainer
  url: https://sebastienlorber.com
  image_url: https://github.com/slorber.png


================================================
FILE: configs/autoencoder/autoencoder_kl_16x16x16.yaml
================================================
model:
  base_learning_rate: 4.5e-6
  target: ldm.models.autoencoder.AutoencoderKL
  params:
    monitor: "val/rec_loss"
    embed_dim: 16
    lossconfig:
      target: ldm.modules.losses.LPIPSWithDiscriminator
      params:
        disc_start: 50001
        kl_weight: 0.000001
        disc_weight: 0.5

    ddconfig:
      double_z: True
      z_channels: 16
      resolution: 256
      in_channels: 3
      out_ch: 3
      ch: 128
      ch_mult: [ 1,1,2,2,4]  # num_down = len(ch_mult)-1
      num_res_blocks: 2
      attn_resolutions: [16]
      dropout: 0.0


data:
  target: main.DataModuleFromConfig
  params:
    batch_size: 12
    wrap: True
    train:
      target: ldm.data.imagenet.ImageNetSRTrain
      params:
        size: 256
        degradation: pil_nearest
    validation:
      target: ldm.data.imagenet.ImageNetSRValidation
      params:
        size: 256
        degradation: pil_nearest

lightning:
  callbacks:
    image_logger:
      target: main.ImageLogger
      params:
        batch_frequency: 1000
        max_images: 8
        increase_log_steps: True

  trainer:
    benchmark: True
    accumulate_grad_batches: 2


================================================
FILE: configs/autoencoder/autoencoder_kl_32x32x4.yaml
================================================
model:
  base_learning_rate: 4.5e-6
  target: ldm.models.autoencoder.AutoencoderKL
  params:
    monitor: "val/rec_loss"
    embed_dim: 4
    lossconfig:
      target: ldm.modules.losses.LPIPSWithDiscriminator
      params:
        disc_start: 50001
        kl_weight: 0.000001
        disc_weight: 0.5

    ddconfig:
      double_z: True
      z_channels: 4
      resolution: 256
      in_channels: 3
      out_ch: 3
      ch: 128
      ch_mult: [ 1,2,4,4 ]  # num_down = len(ch_mult)-1
      num_res_blocks: 2
      attn_resolutions: [ ]
      dropout: 0.0

data:
  target: main.DataModuleFromConfig
  params:
    batch_size: 12
    wrap: True
    train:
      target: ldm.data.imagenet.ImageNetSRTrain
      params:
        size: 256
        degradation: pil_nearest
    validation:
      target: ldm.data.imagenet.ImageNetSRValidation
      params:
        size: 256
        degradation: pil_nearest

lightning:
  callbacks:
    image_logger:
      target: main.ImageLogger
      params:
        batch_frequency: 1000
        max_images: 8
        increase_log_steps: True

  trainer:
    benchmark: True
    accumulate_grad_batches: 2


================================================
FILE: configs/autoencoder/autoencoder_kl_64x64x3.yaml
================================================
model:
  base_learning_rate: 4.5e-6
  target: ldm.models.autoencoder.AutoencoderKL
  params:
    monitor: "val/rec_loss"
    embed_dim: 3
    lossconfig:
      target: ldm.modules.losses.LPIPSWithDiscriminator
      params:
        disc_start: 50001
        kl_weight: 0.000001
        disc_weight: 0.5

    ddconfig:
      double_z: True
      z_channels: 3
      resolution: 256
      in_channels: 3
      out_ch: 3
      ch: 128
      ch_mult: [ 1,2,4 ]  # num_down = len(ch_mult)-1
      num_res_blocks: 2
      attn_resolutions: [ ]
      dropout: 0.0


data:
  target: main.DataModuleFromConfig
  params:
    batch_size: 12
    wrap: True
    train:
      target: ldm.data.imagenet.ImageNetSRTrain
      params:
        size: 256
        degradation: pil_nearest
    validation:
      target: ldm.data.imagenet.ImageNetSRValidation
      params:
        size: 256
        degradation: pil_nearest

lightning:
  callbacks:
    image_logger:
      target: main.ImageLogger
      params:
        batch_frequency: 1000
        max_images: 8
        increase_log_steps: True

  trainer:
    benchmark: True
    accumulate_grad_batches: 2


================================================
FILE: configs/autoencoder/autoencoder_kl_8x8x64.yaml
================================================
model:
  base_learning_rate: 4.5e-6
  target: ldm.models.autoencoder.AutoencoderKL
  params:
    monitor: "val/rec_loss"
    embed_dim: 64
    lossconfig:
      target: ldm.modules.losses.LPIPSWithDiscriminator
      params:
        disc_start: 50001
        kl_weight: 0.000001
        disc_weight: 0.5

    ddconfig:
      double_z: True
      z_channels: 64
      resolution: 256
      in_channels: 3
      out_ch: 3
      ch: 128
      ch_mult: [ 1,1,2,2,4,4]  # num_down = len(ch_mult)-1
      num_res_blocks: 2
      attn_resolutions: [16,8]
      dropout: 0.0

data:
  target: main.DataModuleFromConfig
  params:
    batch_size: 12
    wrap: True
    train:
      target: ldm.data.imagenet.ImageNetSRTrain
      params:
        size: 256
        degradation: pil_nearest
    validation:
      target: ldm.data.imagenet.ImageNetSRValidation
      params:
        size: 256
        degradation: pil_nearest

lightning:
  callbacks:
    image_logger:
      target: main.ImageLogger
      params:
        batch_frequency: 1000
        max_images: 8
        increase_log_steps: True

  trainer:
    benchmark: True
    accumulate_grad_batches: 2


================================================
FILE: configs/blip/bert_config.json
================================================
{
  "architectures": [
    "BertModel"
  ],
  "attention_probs_dropout_prob": 0.1,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 768,
  "initializer_range": 0.02,
  "intermediate_size": 3072,
  "layer_norm_eps": 1e-12,
  "max_position_embeddings": 512,
  "model_type": "bert",
  "num_attention_heads": 12,
  "num_hidden_layers": 12,
  "pad_token_id": 0,
  "type_vocab_size": 2,
  "vocab_size": 30522,
  "encoder_width": 768,
  "add_cross_attention": true
}


================================================
FILE: configs/blip/caption_coco.yaml
================================================
image_root: '/export/share/datasets/vision/coco/images/'
ann_root: 'annotation'
coco_gt_root: 'annotation/coco_gt'

# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_caption_capfilt_large.pth'

# size of vit model; base or large
vit: 'base'
vit_grad_ckpt: False
vit_ckpt_layer: 0
batch_size: 32
init_lr: 1e-5

# vit: 'large'
# vit_grad_ckpt: True
# vit_ckpt_layer: 5
# batch_size: 16
# init_lr: 2e-6

image_size: 384

# generation configs
max_length: 20
min_length: 5
num_beams: 3
prompt: 'a picture of '

# optimizer
weight_decay: 0.05
min_lr: 0
max_epoch: 5


================================================
FILE: configs/blip/med_config.json
================================================
{
  "architectures": [
    "BertModel"
  ],
  "attention_probs_dropout_prob": 0.1,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 768,
  "initializer_range": 0.02,
  "intermediate_size": 3072,
  "layer_norm_eps": 1e-12,
  "max_position_embeddings": 512,
  "model_type": "bert",
  "num_attention_heads": 12,
  "num_hidden_layers": 12,
  "pad_token_id": 0,
  "type_vocab_size": 2,
  "vocab_size": 30524,
  "encoder_width": 768,
  "add_cross_attention": true
}


================================================
FILE: configs/blip/nlvr.yaml
================================================
image_root: '/export/share/datasets/vision/NLVR2/'
ann_root: 'annotation'

# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_nlvr.pth'

#size of vit model; base or large
vit: 'base'
batch_size_train: 16
batch_size_test: 64
vit_grad_ckpt: False
vit_ckpt_layer: 0
max_epoch: 15

image_size: 384

# optimizer
weight_decay: 0.05
init_lr: 3e-5
min_lr: 0


================================================
FILE: configs/blip/nocaps.yaml
================================================
image_root: '/export/share/datasets/vision/nocaps/'
ann_root: 'annotation'

# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_caption_capfilt_large.pth'

vit: 'base'
batch_size: 32

image_size: 384

max_length: 20
min_length: 5
num_beams: 3
prompt: 'a picture of '


================================================
FILE: configs/blip/pretrain.yaml
================================================
train_file: ['/export/share/junnan-li/VL_pretrain/annotation/coco_karpathy_train.json',
             '/export/share/junnan-li/VL_pretrain/annotation/vg_caption.json',
             ]
laion_path: ''

# size of vit model; base or large
vit: 'base'
vit_grad_ckpt: False
vit_ckpt_layer: 0

image_size: 224
batch_size: 75

queue_size: 57600
alpha: 0.4

# optimizer
weight_decay: 0.05
init_lr: 3e-4
min_lr: 1e-6
warmup_lr: 1e-6
lr_decay_rate: 0.9
max_epoch: 20
warmup_steps: 3000


================================================
FILE: configs/blip/retrieval_coco.yaml
================================================
image_root: '/export/share/datasets/vision/coco/images/'
ann_root: 'annotation'
dataset: 'coco'

# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_retrieval_coco.pth'

# size of vit model; base or large

vit: 'base'
batch_size_train: 32
batch_size_test: 64
vit_grad_ckpt: True
vit_ckpt_layer: 4
init_lr: 1e-5

# vit: 'large'
# batch_size_train: 16
# batch_size_test: 32
# vit_grad_ckpt: True
# vit_ckpt_layer: 12
# init_lr: 5e-6

image_size: 384
queue_size: 57600
alpha: 0.4
k_test: 256
negative_all_rank: True

# optimizer
weight_decay: 0.05
min_lr: 0
max_epoch: 6


================================================
FILE: configs/blip/retrieval_flickr.yaml
================================================
image_root: '/export/share/datasets/vision/flickr30k/'
ann_root: 'annotation'
dataset: 'flickr'

# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_retrieval_flickr.pth'

# size of vit model; base or large

vit: 'base'
batch_size_train: 32
batch_size_test: 64
vit_grad_ckpt: True
vit_ckpt_layer: 4
init_lr: 1e-5

# vit: 'large'
# batch_size_train: 16
# batch_size_test: 32
# vit_grad_ckpt: True
# vit_ckpt_layer: 10
# init_lr: 5e-6

image_size: 384
queue_size: 57600
alpha: 0.4
k_test: 128
negative_all_rank: False

# optimizer
weight_decay: 0.05
min_lr: 0
max_epoch: 6


================================================
FILE: configs/blip/retrieval_msrvtt.yaml
================================================
video_root: '/export/share/dongxuli/data/msrvtt_retrieval/videos'
ann_root: 'annotation'

# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_retrieval_coco.pth'

# size of vit model; base or large
vit: 'base'
batch_size: 64
k_test: 128
image_size: 384
num_frm_test: 8


================================================
FILE: configs/blip/vqa.yaml
================================================
vqa_root: '/export/share/datasets/vision/VQA/Images/mscoco/' #followed by train2014/
vg_root: '/export/share/datasets/vision/visual-genome/'  #followed by image/
train_files: ['vqa_train','vqa_val','vg_qa']
ann_root: 'annotation'

# set pretrained as a file path or an url
pretrained: 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_vqa_capfilt_large.pth'

# size of vit model; base or large
vit: 'base'
batch_size_train: 16
batch_size_test: 32
vit_grad_ckpt: False
vit_ckpt_layer: 0
init_lr: 2e-5

image_size: 480

k_test: 128
inference: 'rank'

# optimizer
weight_decay: 0.05
min_lr: 0
max_epoch: 10


================================================
FILE: configs/latent-diffusion/celebahq-ldm-vq-4.yaml
================================================
model:
  base_learning_rate: 2.0e-06
  target: ldm.models.diffusion.ddpm.LatentDiffusion
  params:
    linear_start: 0.0015
    linear_end: 0.0195
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    first_stage_key: image
    image_size: 64
    channels: 3
    monitor: val/loss_simple_ema

    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        image_size: 64
        in_channels: 3
        out_channels: 3
        model_channels: 224
        attention_resolutions:
        # note: this isn\t actually the resolution but
        # the downsampling factor, i.e. this corresnponds to
        # attention on spatial resolution 8,16,32, as the
        # spatial reolution of the latents is 64 for f4
        - 8
        - 4
        - 2
        num_res_blocks: 2
        channel_mult:
        - 1
        - 2
        - 3
        - 4
        num_head_channels: 32
    first_stage_config:
      target: ldm.models.autoencoder.VQModelInterface
      params:
        embed_dim: 3
        n_embed: 8192
        ckpt_path: models/first_stage_models/vq-f4/model.ckpt
        ddconfig:
          double_z: false
          z_channels: 3
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult:
          - 1
          - 2
          - 4
          num_res_blocks: 2
          attn_resolutions: []
          dropout: 0.0
        lossconfig:
          target: torch.nn.Identity
    cond_stage_config: __is_unconditional__
data:
  target: main.DataModuleFromConfig
  params:
    batch_size: 48
    num_workers: 5
    wrap: false
    train:
      target: taming.data.faceshq.CelebAHQTrain
      params:
        size: 256
    validation:
      target: taming.data.faceshq.CelebAHQValidation
      params:
        size: 256


lightning:
  callbacks:
    image_logger:
      target: main.ImageLogger
      params:
        batch_frequency: 5000
        max_images: 8
        increase_log_steps: False

  trainer:
    benchmark: True


================================================
FILE: configs/latent-diffusion/cin-ldm-vq-f8.yaml
================================================
model:
  base_learning_rate: 1.0e-06
  target: ldm.models.diffusion.ddpm.LatentDiffusion
  params:
    linear_start: 0.0015
    linear_end: 0.0195
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    first_stage_key: image
    cond_stage_key: class_label
    image_size: 32
    channels: 4
    cond_stage_trainable: true
    conditioning_key: crossattn
    monitor: val/loss_simple_ema
    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        image_size: 32
        in_channels: 4
        out_channels: 4
        model_channels: 256
        attention_resolutions:
        #note: this isn\t actually the resolution but
        # the downsampling factor, i.e. this corresnponds to
        # attention on spatial resolution 8,16,32, as the
        # spatial reolution of the latents is 32 for f8
        - 4
        - 2
        - 1
        num_res_blocks: 2
        channel_mult:
        - 1
        - 2
        - 4
        num_head_channels: 32
        use_spatial_transformer: true
        transformer_depth: 1
        context_dim: 512
    first_stage_config:
      target: ldm.models.autoencoder.VQModelInterface
      params:
        embed_dim: 4
        n_embed: 16384
        ckpt_path: configs/first_stage_models/vq-f8/model.yaml
        ddconfig:
          double_z: false
          z_channels: 4
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult:
          - 1
          - 2
          - 2
          - 4
          num_res_blocks: 2
          attn_resolutions:
          - 32
          dropout: 0.0
        lossconfig:
          target: torch.nn.Identity
    cond_stage_config:
      target: ldm.modules.encoders.modules.ClassEmbedder
      params:
        embed_dim: 512
        key: class_label
data:
  target: main.DataModuleFromConfig
  params:
    batch_size: 64
    num_workers: 12
    wrap: false
    train:
      target: ldm.data.imagenet.ImageNetTrain
      params:
        config:
          size: 256
    validation:
      target: ldm.data.imagenet.ImageNetValidation
      params:
        config:
          size: 256


lightning:
  callbacks:
    image_logger:
      target: main.ImageLogger
      params:
        batch_frequency: 5000
        max_images: 8
        increase_log_steps: False

  trainer:
    benchmark: True


================================================
FILE: configs/latent-diffusion/cin256-v2.yaml
================================================
model:
  base_learning_rate: 0.0001
  target: ldm.models.diffusion.ddpm.LatentDiffusion
  params:
    linear_start: 0.0015
    linear_end: 0.0195
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    first_stage_key: image
    cond_stage_key: class_label
    image_size: 64
    channels: 3
    cond_stage_trainable: true
    conditioning_key: crossattn
    monitor: val/loss
    use_ema: False

    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        image_size: 64
        in_channels: 3
        out_channels: 3
        model_channels: 192
        attention_resolutions:
        - 8
        - 4
        - 2
        num_res_blocks: 2
        channel_mult:
        - 1
        - 2
        - 3
        - 5
        num_heads: 1
        use_spatial_transformer: true
        transformer_depth: 1
        context_dim: 512

    first_stage_config:
      target: ldm.models.autoencoder.VQModelInterface
      params:
        embed_dim: 3
        n_embed: 8192
        ddconfig:
          double_z: false
          z_channels: 3
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult:
          - 1
          - 2
          - 4
          num_res_blocks: 2
          attn_resolutions: []
          dropout: 0.0
        lossconfig:
          target: torch.nn.Identity

    cond_stage_config:
      target: ldm.modules.encoders.modules.ClassEmbedder
      params:
        n_classes: 1001
        embed_dim: 512
        key: class_label


================================================
FILE: configs/latent-diffusion/ffhq-ldm-vq-4.yaml
================================================
model:
  base_learning_rate: 2.0e-06
  target: ldm.models.diffusion.ddpm.LatentDiffusion
  params:
    linear_start: 0.0015
    linear_end: 0.0195
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    first_stage_key: image
    image_size: 64
    channels: 3
    monitor: val/loss_simple_ema
    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        image_size: 64
        in_channels: 3
        out_channels: 3
        model_channels: 224
        attention_resolutions:
        # note: this isn\t actually the resolution but
        # the downsampling factor, i.e. this corresnponds to
        # attention on spatial resolution 8,16,32, as the
        # spatial reolution of the latents is 64 for f4
        - 8
        - 4
        - 2
        num_res_blocks: 2
        channel_mult:
        - 1
        - 2
        - 3
        - 4
        num_head_channels: 32
    first_stage_config:
      target: ldm.models.autoencoder.VQModelInterface
      params:
        embed_dim: 3
        n_embed: 8192
        ckpt_path: configs/first_stage_models/vq-f4/model.yaml
        ddconfig:
          double_z: false
          z_channels: 3
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult:
          - 1
          - 2
          - 4
          num_res_blocks: 2
          attn_resolutions: []
          dropout: 0.0
        lossconfig:
          target: torch.nn.Identity
    cond_stage_config: __is_unconditional__
data:
  target: main.DataModuleFromConfig
  params:
    batch_size: 42
    num_workers: 5
    wrap: false
    train:
      target: taming.data.faceshq.FFHQTrain
      params:
        size: 256
    validation:
      target: taming.data.faceshq.FFHQValidation
      params:
        size: 256


lightning:
  callbacks:
    image_logger:
      target: main.ImageLogger
      params:
        batch_frequency: 5000
        max_images: 8
        increase_log_steps: False

  trainer:
    benchmark: True


================================================
FILE: configs/latent-diffusion/lsun_bedrooms-ldm-vq-4.yaml
================================================
model:
  base_learning_rate: 2.0e-06
  target: ldm.models.diffusion.ddpm.LatentDiffusion
  params:
    linear_start: 0.0015
    linear_end: 0.0195
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    first_stage_key: image
    image_size: 64
    channels: 3
    monitor: val/loss_simple_ema
    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        image_size: 64
        in_channels: 3
        out_channels: 3
        model_channels: 224
        attention_resolutions:
        # note: this isn\t actually the resolution but
        # the downsampling factor, i.e. this corresnponds to
        # attention on spatial resolution 8,16,32, as the
        # spatial reolution of the latents is 64 for f4
        - 8
        - 4
        - 2
        num_res_blocks: 2
        channel_mult:
        - 1
        - 2
        - 3
        - 4
        num_head_channels: 32
    first_stage_config:
      target: ldm.models.autoencoder.VQModelInterface
      params:
        ckpt_path: configs/first_stage_models/vq-f4/model.yaml
        embed_dim: 3
        n_embed: 8192
        ddconfig:
          double_z: false
          z_channels: 3
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult:
          - 1
          - 2
          - 4
          num_res_blocks: 2
          attn_resolutions: []
          dropout: 0.0
        lossconfig:
          target: torch.nn.Identity
    cond_stage_config: __is_unconditional__
data:
  target: main.DataModuleFromConfig
  params:
    batch_size: 48
    num_workers: 5
    wrap: false
    train:
      target: ldm.data.lsun.LSUNBedroomsTrain
      params:
        size: 256
    validation:
      target: ldm.data.lsun.LSUNBedroomsValidation
      params:
        size: 256


lightning:
  callbacks:
    image_logger:
      target: main.ImageLogger
      params:
        batch_frequency: 5000
        max_images: 8
        increase_log_steps: False

  trainer:
    benchmark: True


================================================
FILE: configs/latent-diffusion/lsun_churches-ldm-kl-8.yaml
================================================
model:
  base_learning_rate: 5.0e-5   # set to target_lr by starting main.py with '--scale_lr False'
  target: ldm.models.diffusion.ddpm.LatentDiffusion
  params:
    linear_start: 0.0015
    linear_end: 0.0155
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    loss_type: l1
    first_stage_key: "image"
    cond_stage_key: "image"
    image_size: 32
    channels: 4
    cond_stage_trainable: False
    concat_mode: False
    scale_by_std: True
    monitor: 'val/loss_simple_ema'

    scheduler_config: # 10000 warmup steps
      target: ldm.lr_scheduler.LambdaLinearScheduler
      params:
        warm_up_steps: [10000]
        cycle_lengths: [10000000000000]
        f_start: [1.e-6]
        f_max: [1.]
        f_min: [ 1.]

    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        image_size: 32
        in_channels: 4
        out_channels: 4
        model_channels: 192
        attention_resolutions: [ 1, 2, 4, 8 ]   # 32, 16, 8, 4
        num_res_blocks: 2
        channel_mult: [ 1,2,2,4,4 ]  # 32, 16, 8, 4, 2
        num_heads: 8
        use_scale_shift_norm: True
        resblock_updown: True

    first_stage_config:
      target: ldm.models.autoencoder.AutoencoderKL
      params:
        embed_dim: 4
        monitor: "val/rec_loss"
        ckpt_path: "models/first_stage_models/kl-f8/model.ckpt"
        ddconfig:
          double_z: True
          z_channels: 4
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult: [ 1,2,4,4 ]  # num_down = len(ch_mult)-1
          num_res_blocks: 2
          attn_resolutions: [ ]
          dropout: 0.0
        lossconfig:
          target: torch.nn.Identity

    cond_stage_config: "__is_unconditional__"

data:
  target: main.DataModuleFromConfig
  params:
    batch_size: 96
    num_workers: 5
    wrap: False
    train:
      target: ldm.data.lsun.LSUNChurchesTrain
      params:
        size: 256
    validation:
      target: ldm.data.lsun.LSUNChurchesValidation
      params:
        size: 256

lightning:
  callbacks:
    image_logger:
      target: main.ImageLogger
      params:
        batch_frequency: 5000
        max_images: 8
        increase_log_steps: False


  trainer:
    benchmark: True


================================================
FILE: configs/latent-diffusion/txt2img-1p4B-eval.yaml
================================================
model:
  base_learning_rate: 5.0e-05
  target: ldm.models.diffusion.ddpm.LatentDiffusion
  params:
    linear_start: 0.00085
    linear_end: 0.012
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    first_stage_key: image
    cond_stage_key: caption
    image_size: 32
    channels: 4
    cond_stage_trainable: true
    conditioning_key: crossattn
    monitor: val/loss_simple_ema
    scale_factor: 0.18215
    use_ema: False

    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        image_size: 32
        in_channels: 4
        out_channels: 4
        model_channels: 320
        attention_resolutions:
        - 4
        - 2
        - 1
        num_res_blocks: 2
        channel_mult:
        - 1
        - 2
        - 4
        - 4
        num_heads: 8
        use_spatial_transformer: true
        transformer_depth: 1
        context_dim: 1280
        use_checkpoint: true
        legacy: False

    first_stage_config:
      target: ldm.models.autoencoder.AutoencoderKL
      params:
        embed_dim: 4
        monitor: val/rec_loss
        ddconfig:
          double_z: true
          z_channels: 4
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult:
          - 1
          - 2
          - 4
          - 4
          num_res_blocks: 2
          attn_resolutions: []
          dropout: 0.0
        lossconfig:
          target: torch.nn.Identity

    cond_stage_config:
      target: ldm.modules.encoders.modules.BERTEmbedder
      params:
        n_embed: 1280
        n_layer: 32


================================================
FILE: configs/retrieval-augmented-diffusion/768x768.yaml
================================================
model:
  base_learning_rate: 0.0001
  target: ldm.models.diffusion.ddpm.LatentDiffusion
  params:
    linear_start: 0.0015
    linear_end: 0.015
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    first_stage_key: jpg
    cond_stage_key: nix
    image_size: 48
    channels: 16
    cond_stage_trainable: false
    conditioning_key: crossattn
    monitor: val/loss_simple_ema
    scale_by_std: false
    scale_factor: 0.22765929
    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        image_size: 48
        in_channels: 16
        out_channels: 16
        model_channels: 448
        attention_resolutions:
        - 4
        - 2
        - 1
        num_res_blocks: 2
        channel_mult:
        - 1
        - 2
        - 3
        - 4
        use_scale_shift_norm: false
        resblock_updown: false
        num_head_channels: 32
        use_spatial_transformer: true
        transformer_depth: 1
        context_dim: 768
        use_checkpoint: true
    first_stage_config:
      target: ldm.models.autoencoder.AutoencoderKL
      params:
        monitor: val/rec_loss
        embed_dim: 16
        ddconfig:
          double_z: true
          z_channels: 16
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult:
          - 1
          - 1
          - 2
          - 2
          - 4
          num_res_blocks: 2
          attn_resolutions:
          - 16
          dropout: 0.0
        lossconfig:
          target: torch.nn.Identity
    cond_stage_config:
      target: torch.nn.Identity


================================================
FILE: configs/stable-diffusion/v1-inference.yaml
================================================
model:
  base_learning_rate: 1.0e-04
  target: ldm.models.diffusion.ddpm.LatentDiffusion
  params:
    linear_start: 0.00085
    linear_end: 0.0120
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    first_stage_key: "jpg"
    cond_stage_key: "txt"
    image_size: 64
    channels: 4
    cond_stage_trainable: false   # Note: different from the one we trained before
    conditioning_key: crossattn
    monitor: val/loss_simple_ema
    scale_factor: 0.18215
    use_ema: False

    scheduler_config: # 10000 warmup steps
      target: ldm.lr_scheduler.LambdaLinearScheduler
      params:
        warm_up_steps: [ 10000 ]
        cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
        f_start: [ 1.e-6 ]
        f_max: [ 1. ]
        f_min: [ 1. ]

    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        image_size: 32 # unused
        in_channels: 4
        out_channels: 4
        model_channels: 320
        attention_resolutions: [ 4, 2, 1 ]
        num_res_blocks: 2
        channel_mult: [ 1, 2, 4, 4 ]
        num_heads: 8
        use_spatial_transformer: True
        transformer_depth: 1
        context_dim: 768
        use_checkpoint: True
        legacy: False

    first_stage_config:
      target: ldm.models.autoencoder.AutoencoderKL
      params:
        embed_dim: 4
        monitor: val/rec_loss
        ddconfig:
          double_z: true
          z_channels: 4
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult:
          - 1
          - 2
          - 4
          - 4
          num_res_blocks: 2
          attn_resolutions: []
          dropout: 0.0
        lossconfig:
          target: torch.nn.Identity

    cond_stage_config:
      target: ldm.modules.encoders.modules.FrozenCLIPEmbedder


================================================
FILE: configs/stable-diffusion/v2-inference-v.yaml
================================================
model:
  base_learning_rate: 1.0e-4
  target: ldm.models.diffusion.ddpm.LatentDiffusion
  params:
    parameterization: "v"
    linear_start: 0.00085
    linear_end: 0.0120
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    first_stage_key: "jpg"
    cond_stage_key: "txt"
    image_size: 64
    channels: 4
    cond_stage_trainable: false
    conditioning_key: crossattn
    monitor: val/loss_simple_ema
    scale_factor: 0.18215
    use_ema: False # we set this to false because this is an inference only config

    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        use_checkpoint: True
        use_fp16: True
        image_size: 32 # unused
        in_channels: 4
        out_channels: 4
        model_channels: 320
        attention_resolutions: [ 4, 2, 1 ]
        num_res_blocks: 2
        channel_mult: [ 1, 2, 4, 4 ]
        num_head_channels: 64 # need to fix for flash-attn
        use_spatial_transformer: True
        use_linear_in_transformer: True
        transformer_depth: 1
        context_dim: 1024
        legacy: False

    first_stage_config:
      target: ldm.models.autoencoder.AutoencoderKL
      params:
        embed_dim: 4
        monitor: val/rec_loss
        ddconfig:
          #attn_type: "vanilla-xformers"
          double_z: true
          z_channels: 4
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult:
          - 1
          - 2
          - 4
          - 4
          num_res_blocks: 2
          attn_resolutions: []
          dropout: 0.0
        lossconfig:
          target: torch.nn.Identity

    cond_stage_config:
      target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
      params:
        freeze: True
        layer: "penultimate"


================================================
FILE: configs/stable-diffusion/v2-inference.yaml
================================================
model:
  base_learning_rate: 1.0e-4
  target: ldm.models.diffusion.ddpm.LatentDiffusion
  params:
    linear_start: 0.00085
    linear_end: 0.0120
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    first_stage_key: "jpg"
    cond_stage_key: "txt"
    image_size: 64
    channels: 4
    cond_stage_trainable: false
    conditioning_key: crossattn
    monitor: val/loss_simple_ema
    scale_factor: 0.18215
    use_ema: False # we set this to false because this is an inference only config

    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        use_checkpoint: True
        use_fp16: True
        image_size: 32 # unused
        in_channels: 4
        out_channels: 4
        model_channels: 320
        attention_resolutions: [ 4, 2, 1 ]
        num_res_blocks: 2
        channel_mult: [ 1, 2, 4, 4 ]
        num_head_channels: 64 # need to fix for flash-attn
        use_spatial_transformer: True
        use_linear_in_transformer: True
        transformer_depth: 1
        context_dim: 1024
        legacy: False

    first_stage_config:
      target: ldm.models.autoencoder.AutoencoderKL
      params:
        embed_dim: 4
        monitor: val/rec_loss
        ddconfig:
          #attn_type: "vanilla-xformers"
          double_z: true
          z_channels: 4
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult:
          - 1
          - 2
          - 4
          - 4
          num_res_blocks: 2
          attn_resolutions: []
          dropout: 0.0
        lossconfig:
          target: torch.nn.Identity

    cond_stage_config:
      target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
      params:
        freeze: True
        layer: "penultimate"


================================================
FILE: configs/stable-diffusion/v2-inpainting-inference.yaml
================================================
model:
  base_learning_rate: 5.0e-05
  target: ldm.models.diffusion.ddpm.LatentInpaintDiffusion
  params:
    linear_start: 0.00085
    linear_end: 0.0120
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    first_stage_key: "jpg"
    cond_stage_key: "txt"
    image_size: 64
    channels: 4
    cond_stage_trainable: false
    conditioning_key: hybrid
    scale_factor: 0.18215
    monitor: val/loss_simple_ema
    finetune_keys: null
    use_ema: False

    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        use_checkpoint: True
        image_size: 32 # unused
        in_channels: 9
        out_channels: 4
        model_channels: 320
        attention_resolutions: [ 4, 2, 1 ]
        num_res_blocks: 2
        channel_mult: [ 1, 2, 4, 4 ]
        num_head_channels: 64 # need to fix for flash-attn
        use_spatial_transformer: True
        use_linear_in_transformer: True
        transformer_depth: 1
        context_dim: 1024
        legacy: False

    first_stage_config:
      target: ldm.models.autoencoder.AutoencoderKL
      params:
        embed_dim: 4
        monitor: val/rec_loss
        ddconfig:
          #attn_type: "vanilla-xformers"
          double_z: true
          z_channels: 4
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult:
            - 1
            - 2
            - 4
            - 4
          num_res_blocks: 2
          attn_resolutions: [ ]
          dropout: 0.0
        lossconfig:
          target: torch.nn.Identity

    cond_stage_config:
      target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
      params:
        freeze: True
        layer: "penultimate"


data:
  target: ldm.data.laion.WebDataModuleFromConfig
  params:
    tar_base: null  # for concat as in LAION-A
    p_unsafe_threshold: 0.1
    filter_word_list: "data/filters.yaml"
    max_pwatermark: 0.45
    batch_size: 8
    num_workers: 6
    multinode: True
    min_size: 512
    train:
      shards:
        - "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-0/{00000..18699}.tar -"
        - "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-1/{00000..18699}.tar -"
        - "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-2/{00000..18699}.tar -"
        - "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-3/{00000..18699}.tar -"
        - "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-4/{00000..18699}.tar -"  #{00000-94333}.tar"
      shuffle: 10000
      image_key: jpg
      image_transforms:
      - target: torchvision.transforms.Resize
        params:
          size: 512
          interpolation: 3
      - target: torchvision.transforms.RandomCrop
        params:
          size: 512
      postprocess:
        target: ldm.data.laion.AddMask
        params:
          mode: "512train-large"
          p_drop: 0.25
    # NOTE use enough shards to avoid empty validation loops in workers
    validation:
      shards:
        - "pipe:aws s3 cp s3://deep-floyd-s3/datasets/laion_cleaned-part5/{93001..94333}.tar - "
      shuffle: 0
      image_key: jpg
      image_transforms:
      - target: torchvision.transforms.Resize
        params:
          size: 512
          interpolation: 3
      - target: torchvision.transforms.CenterCrop
        params:
          size: 512
      postprocess:
        target: ldm.data.laion.AddMask
        params:
          mode: "512train-large"
          p_drop: 0.25

lightning:
  find_unused_parameters: True
  modelcheckpoint:
    params:
      every_n_train_steps: 5000

  callbacks:
    metrics_over_trainsteps_checkpoint:
      params:
        every_n_train_steps: 10000

    image_logger:
      target: main.ImageLogger
      params:
        enable_autocast: False
        disabled: False
        batch_frequency: 1000
        max_images: 4
        increase_log_steps: False
        log_first_step: False
        log_images_kwargs:
          use_ema_scope: False
          inpaint: False
          plot_progressive_rows: False
          plot_diffusion_rows: False
          N: 4
          unconditional_guidance_scale: 5.0
          unconditional_guidance_label: [""]
          ddim_steps: 50  # todo check these out for depth2img,
          ddim_eta: 0.0   # todo check these out for depth2img,

  trainer:
    benchmark: True
    val_check_interval: 5000000
    num_sanity_val_steps: 0
    accumulate_grad_batches: 1


================================================
FILE: configs/stable-diffusion/v2-midas-inference.yaml
================================================
model:
  base_learning_rate: 5.0e-07
  target: ldm.models.diffusion.ddpm.LatentDepth2ImageDiffusion
  params:
    linear_start: 0.00085
    linear_end: 0.0120
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    first_stage_key: "jpg"
    cond_stage_key: "txt"
    image_size: 64
    channels: 4
    cond_stage_trainable: false
    conditioning_key: hybrid
    scale_factor: 0.18215
    monitor: val/loss_simple_ema
    finetune_keys: null
    use_ema: False

    depth_stage_config:
      target: ldm.modules.midas.api.MiDaSInference
      params:
        model_type: "dpt_hybrid"

    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        use_checkpoint: True
        image_size: 32 # unused
        in_channels: 5
        out_channels: 4
        model_channels: 320
        attention_resolutions: [ 4, 2, 1 ]
        num_res_blocks: 2
        channel_mult: [ 1, 2, 4, 4 ]
        num_head_channels: 64 # need to fix for flash-attn
        use_spatial_transformer: True
        use_linear_in_transformer: True
        transformer_depth: 1
        context_dim: 1024
        legacy: False

    first_stage_config:
      target: ldm.models.autoencoder.AutoencoderKL
      params:
        embed_dim: 4
        monitor: val/rec_loss
        ddconfig:
          #attn_type: "vanilla-xformers"
          double_z: true
          z_channels: 4
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult:
            - 1
            - 2
            - 4
            - 4
          num_res_blocks: 2
          attn_resolutions: [ ]
          dropout: 0.0
        lossconfig:
          target: torch.nn.Identity

    cond_stage_config:
      target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
      params:
        freeze: True
        layer: "penultimate"


================================================
FILE: configs/stable-diffusion/x4-upscaling.yaml
================================================
model:
  base_learning_rate: 1.0e-04
  target: ldm.models.diffusion.ddpm.LatentUpscaleDiffusion
  params:
    parameterization: "v"
    low_scale_key: "lr"
    linear_start: 0.0001
    linear_end: 0.02
    num_timesteps_cond: 1
    log_every_t: 200
    timesteps: 1000
    first_stage_key: "jpg"
    cond_stage_key: "txt"
    image_size: 128
    channels: 4
    cond_stage_trainable: false
    conditioning_key: "hybrid-adm"
    monitor: val/loss_simple_ema
    scale_factor: 0.08333
    use_ema: False

    low_scale_config:
      target: ldm.modules.diffusionmodules.upscaling.ImageConcatWithNoiseAugmentation
      params:
        noise_schedule_config: # image space
          linear_start: 0.0001
          linear_end: 0.02
        max_noise_level: 350

    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        use_checkpoint: True
        num_classes: 1000  # timesteps for noise conditioning (here constant, just need one)
        image_size: 128
        in_channels: 7
        out_channels: 4
        model_channels: 256
        attention_resolutions: [ 2,4,8]
        num_res_blocks: 2
        channel_mult: [ 1, 2, 2, 4]
        disable_self_attentions: [True, True, True, False]
        disable_middle_self_attn: False
        num_heads: 8
        use_spatial_transformer: True
        transformer_depth: 1
        context_dim: 1024
        legacy: False
        use_linear_in_transformer: True

    first_stage_config:
      target: ldm.models.autoencoder.AutoencoderKL
      params:
        embed_dim: 4
        ddconfig:
          # attn_type: "vanilla-xformers" this model needs efficient attention to be feasible on HR data, also the decoder seems to break in half precision (UNet is fine though)
          double_z: True
          z_channels: 4
          resolution: 256
          in_channels: 3
          out_ch: 3
          ch: 128
          ch_mult: [ 1,2,4 ]  # num_down = len(ch_mult)-1
          num_res_blocks: 2
          attn_resolutions: [ ]
          dropout: 0.0

        lossconfig:
          target: torch.nn.Identity

    cond_stage_config:
      target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
      params:
        freeze: True
        layer: "penultimate"


================================================
FILE: configs/webui/webui.yaml
================================================
# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).

# Copyright 2022 Sygil-Dev team.
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.

# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU Affero General Public License for more details.

# You should have received a copy of the GNU Affero General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.

# UI defaults configuration file. Is read automatically if located at configs/webui/webui.yaml, or specify path via --defaults.

txt2img:
  prompt:
  ddim_steps: 50
  # Adding an int to toggles enables the corresponding feature.
  #  0:  Create prompt matrix (separate multiple prompts using |, and get all combinations of them)
  #  1:  Normalize Prompt Weights (ensure sum of weights add up to 1.0)
  #  2:  Save individual images
  #  3:  Save grid
  #  4:  Sort samples by prompt
  #  5:  Write sample info files
  #  6:  write sample info to log file
  #  7:  jpg samples
  #  8:  Filter NSFW content
  #  9:  Fix faces using GFPGAN
  #  10:  Upscale images using RealESRGAN
  toggles: [1, 2, 3, 4, 5]
  sampler_name: k_lms
  ddim_eta: 0.0  # legacy name, applies to all algorithms.
  n_iter: 1
  batch_size: 1
  cfg_scale: 7.5
  # Leave blank for random seed:
  seed:
  height: 512
  width: 512
  # Textual inversion embeddings file path:
  fp:

img2img:
  prompt:
  ddim_steps: 50
  # Adding an int to toggles enables the corresponding feature.
  # 0: Create prompt matrix (separate multiple prompts using |, and get all combinations of them)
  # 1: Normalize Prompt Weights (ensure sum of weights add up to 1.0)
  # 2: Loopback (use images from previous batch when creating next batch)
  # 3: Random loopback seed
  # 4: Save individual images
  # 5: Save grid
  # 6: Sort samples by prompt
  # 7: Write sample info files
  # 8: jpg samples
  # 9: Color correction
  # 10: Filter NSFW content
  # 11: Fix faces using GFPGAN
  # 12: Upscale images using Real-ESRGAN
  toggles: [1, 4, 5, 6, 7]
  sampler_name: k_lms
  ddim_eta: 0.0
  n_iter: 1
  batch_size: 1
  cfg_scale: 5.0
  denoising_strength: 0.75
  # 0: Keep masked area
  # 1: Regenerate only masked area
  mask_mode: 0
  # 0: Just resize
  # 1: Crop and resize
  # 2: Resize and fill
  resize_mode: 0
  # Leave blank for random seed:
  seed:
  height: 512
  width: 512
  # Textual inversion embeddings file path:
  fp:

gfpgan:
  strength: 100


================================================
FILE: configs/webui/webui_flet.yaml
================================================
# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).

# Copyright 2022 Sygil-Dev team.
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.

# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU Affero General Public License for more details.

# You should have received a copy of the GNU Affero General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.

# UI defaults configuration file. It is automatically loaded if located at configs/webui/webui_flet.yaml.
# Any changes made here will be available automatically on the web app without having to stop it.
# You may add overrides in a file named "userconfig_flet.yaml" in this folder, which can contain any subset
# of the properties below.

# any section labeled '_page' will get it's own tab in settings
# any section without that suffix will still be read by parser and stored in session
#
# display types
#           -- every display type must have 'value: '
#           -- to do: add 'tooltip : ' to every display type
#                   --(make optional, not everything needs one.)
#   bool
#       -value
#   dropdown
#       -value
#       -option_list
#   slider
#       -value
#       -value_type  'int', 'float'
#       -min
#       -max
#       -step
#   textinput
#       -value
#
# list of value types
#   !!bool      boolean     'true' 'false'
#   !!float     float       '0.01'
#   !!int       integer     '23'
#   !!str       string      'foo' 'bar'
#   !!null      None

webui_page:
    default_theme:
        display: dropdown
        value: 'dark'
        option_list:
            - !!str 'dark'
            - !!str 'light'
    default_text_size:
        display: slider
        value: !!int '20'
        value_type: 'int'
        min: !!int '10'
        max: !!int '32'
        step: !!float '2.0'
    max_message_history:
        display: slider
        value: !!int '20'
        value_type: 'int'
        min: !!int '1'
        max: !!int '100'
        step: !!int '1'
    theme_color:
        display: textinput
        value: !!str 'blue'

general_page:
    huggingface_token:
        display: textinput
        value: !!str ''
    stable_horde_api:
        display: textinput
        value: !!str '0000000000'
    global_negative_prompt:
        display: textinput
        value: !!str " "
    default_model:
        display: textinput
        value: !!str "Stable Diffusion v1.5"
    base_model:
        display: textinput
        value: !!str "Stable Diffusion v1.5"
    default_model_config:
        display: textinput
        value: !!str "configs/stable-diffusion/v1-inference.yaml"
    default_model_path:
        display: textinput
        value: !!str "models/ldm/stable-diffusion-v1/Stable Diffusion v1.5.ckpt"
    use_sd_concepts_library:
        display: bool
        value: !!bool 'true'
    sd_concepts_library_folder:
        display: textinput
        value: !!str "models/custom/sd-concepts-library"
    GFPGAN_dir:
        display: textinput
        value: !!str "./models/gfpgan"
    GFPGAN_model:
        display: textinput
        value: !!str "GFPGANv1.4"
    LDSR_dir:
        display: textinput
        value: !!str "./models/ldsr"
    LDSR_model:
        display: textinput
        value: !!str "model"
    RealESRGAN_dir:
        display: textinput
        value: !!str "./models/realesrgan"
    RealESRGAN_model:
        display: textinput
        value: !!str "RealESRGAN_x4plus"
    upscaling_method:
        display: textinput
        value: !!str "RealESRGAN"

output_page:
    outdir:
        display: textinput
        value: !!str 'outputs'
    outdir_txt2img:
        display: textinput
        value: !!str "outputs/txt2img"
    outdir_img2img:
        display: textinput
        value: !!str "outputs/img2img"
    outdir_img2txt:
        display: textinput
        value: !!str "outputs/img2txt"
    save_metadata:
        display: bool
        value: !!bool true
    save_format:
        display: dropdown
        value: !!str "png"
        option_list:
            - !!str 'png'
            - !!str 'jpeg'
    skip_grid:
        display: bool
        value: !!bool 'false'
    skip_save:
        display: bool
        value: !!bool 'false'
    #grid_quality: 95
    #n_rows: -1
    #update_preview: True
    #update_preview_frequency: 10

performance_page:
    gpu:
        display: dropdown
        value: !!str ''
        option_list:
            - !!str '0:'
    gfpgan_cpu:
        display: bool
        value: !!bool 'false'
    esrgan_cpu:
        display: bool
        value: !!bool 'false'
    extra_models_cpu:
        display: bool
        value: !!bool 'false'
    extra_models_gpu:
        display: bool
        value: !!bool 'false'
    gfpgan_gpu:
        display: textinput
        value: !!int 0
    esrgan_gpu:
        display: textinput
        value: !!int 0
    keep_all_models_loaded:
        display: bool
        value: !!bool 'false'
    no_verify_input:
        display: bool
        value: !!bool 'false'
    #no_half: False
    #use_float16: False
    #precision: "autocast"
    #optimized: False
    #optimized_turbo: False
    #optimized_config: "optimizedSD/v1-inference.yaml"
    #enable_attention_slicing: False
    #enable_minimal_memory_usage: False

server_page:
    hide_server_setting:
        display: bool
        value: !!bool 'false'
    hide_browser_setting:
        display: bool
        value: !!bool 'false'

textual_inversion:
    pretrained_model_name_or_path: "models/diffusers/stable-diffusion-v1-5"
    tokenizer_name: "models/clip-vit-large-patch14"


================================================
FILE: configs/webui/webui_streamlit.yaml
================================================
# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).

# Copyright 2022 Sygil-Dev team.
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.

# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU Affero General Public License for more details.

# You should have received a copy of the GNU Affero General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.

# UI defaults configuration file. It is automatically loaded if located at configs/webui/webui_streamlit.yaml.
# Any changes made here will be available automatically on the web app without having to stop it.
# You may add overrides in a file named "userconfig_streamlit.yaml" in this folder, which can contain any subset
# of the properties below.
general:
    version: 1.24.6
    streamlit_telemetry: False
    default_theme: dark
    huggingface_token: ''
    stable_horde_api: '0000000000'
    gpu: 0
    outdir: outputs
    default_model: "Stable Diffusion v1.5"
    base_model: "Stable Diffusion v1.5"
    default_model_config: "configs/stable-diffusion/v1-inference.yaml"
    default_model_path: "models/ldm/stable-diffusion-v1/Stable Diffusion v1.5.ckpt"
    use_sd_concepts_library: True
    sd_concepts_library_folder: "models/custom/sd-concepts-library"
    GFPGAN_dir: "./models/gfpgan"
    GFPGAN_model: "GFPGANv1.4"
    LDSR_dir: "./models/ldsr"
    LDSR_model: "model"
    RealESRGAN_dir: "./models/realesrgan"
    RealESRGAN_model: "RealESRGAN_x4plus"
    upscaling_method: "RealESRGAN"
    outdir_txt2img: outputs/txt2img
    outdir_img2img: outputs/img2img
    outdir_img2txt: outputs/img2txt
    gfpgan_cpu: False
    esrgan_cpu: False
    extra_models_cpu: False
    extra_models_gpu: False
    gfpgan_gpu: 0
    esrgan_gpu: 0
    keep_all_models_loaded: False
    save_metadata: True
    save_format: "png"
    skip_grid: False
    skip_save: False
    grid_quality: 95
    n_rows: -1
    no_verify_input: False
    show_percent_in_tab_title: True
    enable_suggestions: True
    no_half: False
    use_float16: False
    precision: "autocast"
    use_cudnn: False
    optimized: False
    optimized_turbo: False
    optimized_config: "optimizedSD/v1-inference.yaml"
    enable_attention_slicing: False
    enable_minimal_memory_usage: False
    update_preview: True
    update_preview_frequency: 10

admin:
    hide_server_setting: False
    hide_browser_setting: False
    global_negative_prompt: ""

debug:
    enable_hydralit: False

txt2img:
    prompt:
    width:
        value:      512
        min_value:  64
        max_value:  2048
        step:       64

    height:
        value:      512
        min_value:  64
        max_value:  2048
        step:       64

    cfg_scale:
        value:      7.5
        min_value:  1.0
        step:       0.5

    seed: ""
    batch_count:
        value:      1

    batch_size:
        value:      1

    sampling_steps:
        value:      30
        min_value:  10
        max_value:  250
        step:       10

    LDSR_config:
        sampling_steps: 50
        preDownScale: 1
        postDownScale: 1
        downsample_method: "Lanczos"

    default_sampler: "k_euler"
    separate_prompts: False
    update_preview: True
    update_preview_frequency: 10
    normalize_prompt_weights: True
    save_individual_images: True
    save_grid: True
    group_by_prompt: False
    save_as_jpg: False
    use_GFPGAN: False
    use_RealESRGAN: False
    use_LDSR: False
    RealESRGAN_model: "RealESRGAN_x4plus"
    use_upscaling: False

    variant_amount:
        value:      0.0
        min_value:  0.0
        max_value:  1.0
        step:       0.01

    variant_seed: ""
    write_info_files: True

txt2vid:
    default_model: "runwayml/stable-diffusion-v1-5"
    custom_models_list: ["runwayml/stable-diffusion-v1-5", "Sygil/Sygil-Diffusion", "CompVis/stable-diffusion-v1-4", "hakurei/waifu-diffusion"]
    prompt:
    width:
        value:      512
        min_value:  64
        max_value:  2048
        step:       64

    height:
        value:      512
        min_value:  64
        max_value:  2048
        step:       64

    cfg_scale:
        value:      7.5
        min_value:  1.0
        step:       0.5

    batch_count:
        value:      1

    batch_size:
        value:      1

    sampling_steps:
        value:      30
        min_value:  10
        max_value:  250
        step:       10

    num_inference_steps:
        value:      200
        min_value:  10
        max_value:  500
        step:       10

    seed: ""
    default_sampler: "k_euler"
    scheduler_name: "klms"
    separate_prompts: False
    update_preview: True
    update_preview_frequency: 10
    dynamic_preview_frequency: True
    normalize_prompt_weights: True
    save_individual_images: True
    save_video: True
    save_video_on_stop: False
    group_by_prompt: True
    write_info_files: True
    do_loop: False
    use_lerp_for_text: False
    save_as_jpg: False
    use_GFPGAN: False
    use_RealESRGAN: False
    RealESRGAN_model: "RealESRGAN_x4plus"
    use_upscaling: False
    variant_amount:
        value:      0.0
        min_value:  0.0
        max_value:  1.0
        step:       0.01

    variant_seed: ""

    beta_start:
        value:      0.00085
        min_value:  0.00010
        max_value:  0.03000
        step:       0.00010
        format:     "%.5f"

    beta_end:
        value:      0.01200
        min_value:  0.00010
        max_value:  0.03000
        step:       0.00010
        format:     "%.5f"

    beta_scheduler_type: "scaled_linear"
    max_duration_in_seconds: 30
    fps: 30

    LDSR_config:
        sampling_steps: 50
        preDownScale: 1
        postDownScale: 1
        downsample_method: "Lanczos"

img2img:
    prompt:
    sampler_name: "k_euler"
    denoising_strength:
        value:      0.75
        min_value:  0.0
        max_value:  1.0
        step:       0.01
    # 0: Keep masked area
    # 1: Regenerate only masked area
    mask_mode: 0
    noise_mode: "Matched Noise"
    mask_restore: False
    # 0: Just resize
    # 1: Crop and resize
    # 2: Resize and fill
    resize_mode: 0
    # Leave blank for random seed:
    seed: ""
    ddim_eta: 0.0
    width:
        value:      512
        min_value:  64
        max_value:  2048
        step:       64

    height:
        value:      512
        min_value:  64
        max_value:  2048
        step:       64

    cfg_scale:
        value:      7.5
        min_value:  1.0
        step:       0.5

    batch_count:
        value:      1

    batch_size:
        value:      1

    sampling_steps:
        value:      30
        min_value:  10
        max_value:  250
        step:       10

    num_inference_steps:
        value:      200
        min_value:  10
        max_value:  500
        step:       10

    find_noise_steps:
        value:      100
        min_value:  100
        step:       100

    LDSR_config:
        sampling_steps: 50
        preDownScale: 1
        postDownScale: 1
        downsample_method: "Lanczos"

    loopback: True
    random_seed_loopback: True
    separate_prompts: False
    update_preview: True
    update_preview_frequency: 10
    normalize_prompt_weights: True
    save_individual_images: True
    save_grid: True
    group_by_prompt: False
    save_as_jpg: False
    use_GFPGAN: False
    use_RealESRGAN: False
    RealESRGAN_model: "RealESRGAN_x4plus"
    use_upscaling: False
    variant_amount: 0.0
    variant_seed: ""
    write_info_files: True

img2txt:
    batch_size: 2000
    blip_image_eval_size: 512
    keep_all_models_loaded: False

post_processing:
        save_original_images: True
        outdir_post_processing: outputs/post_processing

concepts_library:
    concepts_per_page: 12

gfpgan:
  strength: 100

textual_inversion:
    pretrained_model_name_or_path: "models/diffusers/stable-diffusion-v1-5"
    tokenizer_name: "models/clip-vit-large-patch14"


daisi_app:
    running_on_daisi_io: False

model_manager:
    models:
        stable_diffusion:
            model_name:     "Stable Diffusion v1.5"
            save_location:  "./models/ldm/stable-diffusion-v1"
            files:
                model_ckpt:
                    file_name:  "Stable Diffusion v1.5.ckpt"
                    download_link:  "https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt"

        gfpgan:
            model_name:     "GFPGAN"
            save_location:  "./models/gfpgan"
            files:
                gfpgan_1_4:
                    file_name:  "GFPGANv1.4.pth"
                    download_link:  "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth"
                resnet_50:
                    file_name: "detection_Resnet50_Final.pth"
                    save_location:  "./gfpgan/weights"
                    download_link: "https://github.com/xinntao/facexlib/releases/download/v0.1.0/detection_Resnet50_Final.pth"
                parsing_parsenet:
                    file_name: "parsing_parsenet.pth"
                    save_location:  "./gfpgan/weights"
                    download_link: "https://github.com/xinntao/facexlib/releases/download/v0.2.2/parsing_parsenet.pth"


        realesrgan:
            model_name:     "RealESRGAN"
            save_location:  "./models/realesrgan"
            files:
                x4plus:
                    file_name: "RealESRGAN_x4plus.pth"
                    download_link:  "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth"
                x4plus_anime_6b:
                    file_name: "RealESRGAN_x4plus_anime_6B.pth"
                    download_link:  "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth"


        waifu_diffusion:
            model_name:     "Waifu Diffusion v1.3"
            save_location:  "./models/custom"
            files:
                waifu_diffusion:
                    file_name: "Waifu-Diffusion-v1-3 Full ema.ckpt"
                    download_link:  "https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/wd-v1-3-full.ckpt"


        trinart_stable_diffusion:
            model_name:     "TrinArt Stable Diffusion v2"
            save_location:  "./models/custom"
            files:
                trinart:
                    file_name: "trinart.ckpt"
                    download_link:  "https://huggingface.co/naclbit/trinart_stable_diffusion_v2/resolve/main/trinart2_step95000.ckpt"

        sd_wd_ld_trinart_merged:
            model_name:     "SD1.5-WD1.3-LD-Trinart-Merged"
            save_location:  "./models/custom"
            files:
                sd_wd_ld_trinart_merged:
                    file_name: "SD1.5-WD1.3-LD-Trinart-Merged.ckpt"
                    download_link:  "https://huggingface.co/ZeroCool94/sd1.5-wd1.3-ld-trinart-merged/resolve/main/SD1.5-WD1.3-LD-Trinart-Merged.ckpt"

        stable_diffusion_concept_library:
            model_name:     "Stable Diffusion Concept Library"
            save_location:  "./models/custom/sd-concepts-library/"
            files:
                concept_library:
                    file_name: ""
                    download_link:  "https://github.com/Sygil-Dev/sd-concepts-library"

        blip_model:
            model_name:     "Blip Model"
            save_location:  "./models/blip"
            files:
                blip:
                    file_name: "model__base_caption.pth"
                    download_link:  "https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model*_base_caption.pth"

        ldsr:
            model_name: "Latent Diffusion Super Resolution (LDSR)"
            save_location:  "./models/ldsr"
            files:
                project_yaml:
                    file_name:     "project.yaml"
                    download_link:  "https://heibox.uni-heidelberg.de/f/31a76b13ea27482981b4/?dl=1"

                ldsr_model:
                    file_name:     "model.ckpt"
                    download_link:  "https://heibox.uni-heidelberg.de/f/578df07c8fc04ffbadf3/?dl=1"

        sygil:
            model_name:     "Sygil Diffusion 0.4"
            save_location:  "./models/custom"
            files:
                sygil_diffusion:
                    file_name: "sygil-diffusion-v0.4.ckpt"
                    download_link:  "https://huggingface.co/Sygil/Sygil-Diffusion/resolve/main/sygil-diffusion-v0.4.ckpt"


================================================
FILE: daisi_app.py
================================================
import os, subprocess
import yaml

print(os.getcwd)

try:
    with open("environment.yaml") as file_handle:
        environment_data = yaml.safe_load(file_handle, Loader=yaml.FullLoader)
except FileNotFoundError:
    try:
        with open(os.path.join("..", "environment.yaml")) as file_handle:
            environment_data = yaml.safe_load(file_handle, Loader=yaml.FullLoader)
    except:
        pass

try:
    for dependency in environment_data["dependencies"]:
        package_name, package_version = dependency.split("=")
        os.system("pip install {}=={}".format(package_name, package_version))
except:
    pass

try:
    subprocess.run(
        [
            "python",
            "-m",
            "streamlit",
            "run",
            os.path.join("..", "scripts/webui_streamlit.py"),
            "--theme.base dark",
        ],
        stdout=subprocess.DEVNULL,
    )
except FileExistsError:
    subprocess.run(
        [
            "python",
            "-m",
            "streamlit",
            "run",
            "scripts/webui_streamlit.py",
            "--theme.base dark",
        ],
        stdout=subprocess.DEVNULL,
    )


================================================
FILE: data/img2txt/artists.txt
================================================
A B Jackson
A J Casson
A R Middleton Todd
A. B. Jackson
A. J. Casson
A. R. Middleton Todd
A.B. Frost
A.D.M. Cooper
AB Frost
ADM Cooper
Aaron Bohrod
Aaron Douglas
Aaron Jasinski
Aaron Miller
Aaron Nagel
Abbott Handerson Thayer
Abdullah Gërguri
Abdur Rahman Chughtai
Abidin Dino
Abraham Begeyn
Abraham Bloemaert
Abraham Bosschaert
Abraham Hondius
Abraham Mignon
Abraham Storck
Abraham Willaerts
Abraham de Vries
Abraham van Beijeren
Abraham van Calraet
Abraham van den Tempel
Abram Arkhipov
Achille Leonardi
Ada Gladys Killins
Ada Hill Walker
Adam Bruce Thomson
Adam Chmielowski
Adam Dario Keel
Adam Elsheimer
Adam Manyoki
Adam Marczynski
Adam Marczyński
Adam Paquette
Adam Pijnacker
Adam Rex
Adam Saks
Adam Szentpétery
Adam Willaerts
Adolf Bierbrauer
Adolf Born
Adolf Dietrich
Adolf Fényes
Adolf Hirémy-Hirschl
Adolf Hölzel
Adolf Schrödter
Adolf Ulric Wertmüller
Adolf Wölfli
Adolfo Müller-Ury
Adolph Gottlieb
Adolph Menzel
Adolphe Willette
Adriaen Brouwer
Adriaen Coorte
Adriaen Hanneman
Adriaen Isenbrant
Adriaen van Ostade
Adriaen van de Velde
Adriaen van de Venne
Adriaen van der Werff
Adrian Zingg
Adrienn Henczné Deák
Adélaïde Labille-Guiard
Adélaïde Victoire Hall
Aelbert Cuyp
Aert de Gelder
Aert van der Neer
Aertgen van Leyden
Afewerk Tekle
Affandi
Agnes Lawrence Pelton
Agnes Martin
Agnolo Bronzino
Agnolo Gaddi
Agostino Carracci
Aguri Uchida
Agustín Fernández
Ahmed Karahisari
Ahmed Yacoubi
Ai Weiwei
Ai Xuan
Ai-Mitsu
Aileen Eagleton
Aimé Barraud
Akihiko Yoshida
Akira Toriyama
Akseli Gallen-Kallela
Al Feldstein
Al Williamson
Aladár Körösfoi-Kriesch
Aladár Körösfői-Kriesch
Alain Tasso
Alan Bean
Alan Davis
Alan Lee
Alan Pollack
Alan Sutherland
Alasdair Grant Taylor
Alasdair Gray
Albert Anker
Albert Bertelsen
Albert Bierstadt
Albert Dorne
Albert Dubois-Pillet
Albert Edelfelt
Albert Gleizes
Albert Guillaume
Albert Henry Krehbiel
Albert Irvin
Albert J Welti
Albert J. Welti
Albert Joseph Moore
Albert Joseph Pénot
Albert Keller
Albert Kotin
Albert Marquet
Albert Namatjira
Albert Nemethy
Albert Paris Gütersloh
Albert Swinden
Albert Welti
Alberto Burri
Alberto Giacometti
Alberto Morrocco
Alberto Seveso
Alberto Sughi
Alberto Vargas
Albin Egger-Lienz
Albrecht Altdorfer
Albrecht Dürer
Aldus Manutius
Alejandro Burdisio
Alejandro Obregón
Aleksander Gierymski
Aleksander Gine
Aleksander Kobzdej
Aleksander Kotsis
Aleksander Orlowski
Aleksander Orłowski
Aleksandr Gerasimov
Aleksandr Ivanovich Laktionov
Aleksi Briclot
Alena Aenami
Alessandro Allori
Alessandro Galli Bibiena
Alesso Baldovinetti
Alex Grey
Alex Horley
Alex Horley-Orlandelli
Alex Katz
Alex Petruk APe
Alex Ross
Alex Toth
Alexander Archipenko
Alexander Bogen
Alexander Brook
Alexander Calder
Alexander Carse
Alexander Deyneka
Alexander Fedosav
Alexander Ivanov
Alexander Jansson
Alexander Johnston
Alexander Kanoldt
Alexander Kucharsky
Alexander Litovchenko
Alexander Mann
Alexander McQueen
Alexander Milne Calder
Alexander Nasmyth
Alexander Robertson
Alexander Rodchenko
Alexander Roslin
Alexander Runciman
Alexander Scott
Alexander Sharpe Ross
Alexander Stirling Calder
Alexander V Kuprin
Alexander V. Kuprin
Alexandre Benois
Alexandre Cabanel
Alexandre Falguière
Alexandre-Évariste Fragonard
Alexei Kondratyevich Savrasov
Alexej von Jawlensky
Alexey Merinov
Alexey Venetsianov
Alexis Grimou
Alexis Simon Belle
Alfons Karpinski
Alfons Karpiński
Alfons Walde
Alfons von Czibulka
Alfonse Mucha
Alfred Charles Parker
Alfred East
Alfred Edward Chalon
Alfred Eisenstaedt
Alfred Freddy Krupa
Alfred Janes
Alfred Jensen
Alfred Krupa
Alfred Kubin
Alfred Leslie
Alfred Leyman
Alfred Manessier
Alfred Richard Gurrey
Alfred Sisley
Alfred Thompson Bricher
Alfred Wallis
Alfredo Volpi
Algernon Talmage
Alice Bailly
Alice Mason
Alice Neel
Alice Prin
Alice Rahon
Alison Debenham
Alison Geissler
Alison Kinnaird
Alison Watt
Allaert van Everdingen
Allan Brooks
Allan Linder
Allan Ramsay
Allen Butler Talcott
Allen Jones
Allen Tupper True
Alma Thomas
Almada Negreiros
Almeida Júnior
Alonso Vázquez
Aloysius O'Kelly
Alphonse Legros
Alphonse Mucha
Alson S Clark
Alson S. Clark
Altichiero
Alton Tobey
Altoon Sultan
Alvan Fisher
Alén Diviš
Amadeo de Souza Cardoso
Amalia Lindegren
Amanda Sage
Ambreen Butt
Ambrose McCarthy Patterson
Ambrosius Benson
Ambrosius Bosschaert
Ambrosius Bosschaert II
Ambrosius Holbein
Amedeo Modigliani
Amelia Peláez
Amelia Robertson Hill
Americo Makk
Amir Zand
Ammi Phillips
Amos Ferguson
Amos Sewell
Amy Weber
Amédée Ozenfant
An Gyeon
An Zhengwen
Anato Finnstark
Ancell Stronach
Anders Zorn
Andor Basch
Andre Derain
Andre de Krayewski
Andrea Kowch
Andrea Mantegna
Andrea Orcagna
Andrea Pozzo
Andrea del Sarto
Andrea del Verrocchio
Andreas Achenbach
Andreas Gursky
Andreas Rocha
Andrei Kolkoutine
Andrei Rublev
Andrei Ryabushkin
Andrew Allan
Andrew Bell
Andrew Boog Faithfull
Andrew Domachowski
Andrew Ferez
Andrew Geddes
Andrew Henderson
Andrew Law
Andrew Loomis
Andrew Robertson
Andrew Robinson
Andrew Stevovich
Andrew Wyeth
Andrey Esionov
Andrey Yefimovich Martynov
Andries Both
Andries Stock
Andries Stock Dutch Baroque painter
Android Jones
Andrzej Pronaszko
Andrzej Wróblewski
André Bauchant
André Beauneveu
André Castro
André Charles Biéler
André Derain
André François
André Kertész
André Lhote
André Masson
André Pijet
André Thomkins
Andrée Ruellan
Andy Goldsworthy
Andy Warhol
Aneurin Jones
Angelica Kauffman
Aniello Falcone
Anish Kapoor
Anita Kunz
Anita Malfatti
Anka Zhuravleva
Ann Thetis Blacker
Anna Ancher
Anna Boch
Anna Dittmann
Anna Findlay
Anna Füssli
Anna Haifisch
Anna Hotchkis
Anna Katharina Block
Anna Maria Barbara Abesch
Anna Mary Robertson Moses
Anna and Elena Balbusso
Annabel Eyres
Annabel Kidston
Anne Dunn
Anne Geddes
Anne Nasmyth
Anne Redpath
Anne Rigney
Anne Ryan
Anne Said
Anne Savage
Anne Stokes
Anni Albers
Annibale Carracci
Annie Abernethie Pirie Quibell
Annie Leibovitz
Annie Rose Laing
Ansel Adams
Anselm Kiefer
Anson Maddocks
Antanas Sutkus
Anthony Angarola
Anthony Devas
Anthony Palumbo
Anthony S Waters
Anthony van Dyck
Antoine Blanchard
Antoine Ignace Melling
Antoine Le Nain
Antoine Verney-Carron
Antoine Wiertz
Anton Ažbe
Anton Fadeev
Anton Graff
Anton Lehmden
Anton Mauve
Anton Möller
Anton Otto Fischer
Anton Pieck
Anton Räderscheidt
Anton Solomoukha
Antonello da Messina
Antoni Brodowski
Antoni Pitxot
Antoni Tàpies
Antonie Palamedesz
Antonin Artaud
Antonio Canova
Antonio Cavallucci
Antonio Ciseri
Antonio Donghi
Antonio Galli Bibiena
Antonio Mancini
Antonio Rotta
Antonio Saura
Antonio de la Gandara
Antonín Chittussi
Antonín Slavícek
Antonín Slavíček
Antônio Parreiras
Aníbal Villacís
Apelles
Apollinary Vasnetsov
Apollonia Saintclair
Aquirax Uno
Arabella Rankin
Araceli Gilbert
Aramenta Dianthe Vail
Archibald Motley
Archibald Robertson
Archibald Skirving
Archibald Standish Hartrick
Arcimboldo
Arent Arentsz
Arie Smit
Arik Brauer
Aristide Maillol
Arkhip Kuindzhi
Arlington Nelson Lindenmuth
Armand Guillaumin
Armin Baumgarten
Armin Hansen
Arnie Swekel
Arnold Blanch
Arnold Bronckhorst
Arnold Brügger
Arnold Böcklin
Arnold Franz Brasz
Arnold Mesches
Arnold Newman
Arshile Gorky
Art & Language
Art Brenner
Art Fitzpatrick
Art Frahm
Art Green
Art Spiegelman
Art of Brom
Artemisia Gentileschi
Artgerm
Arthur Adams
Arthur B Carles
Arthur B. Carles
Arthur Boyd
Arthur Burdett Frost
Arthur Dove
Arthur Garfield Dove
Arthur Hughes
Arthur Lismer
Arthur Melville
Arthur Merric Boyd
Arthur Pan
Arthur Quartley
Arthur Rackham
Arthur Sarkissian
Arthur Streeton
Arthur Webster Emerson
Artur Grottger
Artur Tarnowski
Arturo Rivera
Arvid Nyholm
Asaf Hanuka
Asai Chu
Asai Chū
Asger Jorn
Asher Brown Durand
Atey Ghailan
Attila Meszlenyi
Aubrey Beardsley
Audrey Kawasaki
August Friedrich Schenck
August Lemmer
August Macke
August Querfurt
August Sander
Auguste Baud-Bovy
Auguste Herbin
Augustin Meinrad Bächtiger
Augustus Dunbier
Augustus Earle
Augustus John
Augustus Vincent Tack
Augustyn Mirys
Aurél Bernáth
Auseklis Ozols
Austin Briggs
Austin English
Austin Osman Spare
Avgust Cernigoj
Avgust Černigoj
Avigdor Arikha
Awataguchi Takamitsu
Ay-O
Aya Goda
Ayako Rokkaku
Ayami Kojima
Ayshia Taskin
Ayshia Taşkın
Baioken Eishun
Baiōken Eishun
Balcomb Greene
Balthasar van der Ast
Balthus
Balázs Diószegi
Banksy
Bapu
Barbara Balmer
Barbara Greg
Barbara Longhi
Barbara Nasmyth
Barbara Nessim
Barclay Shaw
Barent Fabritius
Barkley Hendricks
Barnett Newman
Barron Storey
Barthel Bruyn the Elder
Barthel Bruyn the Younger
Bartholomeus Breenbergh
Bartholomeus Strobel
Bartholomeus van Bassen
Bartholomeus van der Helst
Barthélemy Menn
Barthélemy d'Eyck
Bartolomeo Cesi
Bartolomeo Vivarini
Bartolomé Esteban Murillo
Bascove
Basil Blackshaw
Bastien L Deharme
Bastien L. Deharme
Bastien Lecouffe-Deharme
Basuki Abdullah
Bauhaus
Bayard Wu
Beatrice Ethel Lithiby
Beatrice Huntington
Beatrix Potter
Beauford Delaney
Bedwyr Williams
Beeple
Beksinski
Bela Cikoš Sesija
Bela Čikoš Sesija
Ben Enwonwu
Ben Nicholson
Ben Shahn
Ben Stahl
Ben Templesmith
Ben Thompson
Ben Zoeller
Bencho Obreshkov
Benito Quinquela Martín
Benjamin Block
Benjamin Franklin
Benjamin Gerritsz Cuyp
Benjamin Marra
Benjamin West
Benjamin Williams Leader
Benoit B Mandelbrot
Benoit B. Mandelbrot
Bernard Accama
Bernard Buffet
Bernard D’Andrea
Bernard Fleetwood-Walker
Bernard Meninsky
Bernard van Orley
Bernardino Mei
Bernardo Bellotto
Bernardo Cavallino
Bernardo Daddi
Bernardo Strozzi
Bernat Sanjuan
Bernd Fasching
Bernie D’Andrea
Bernie Wrightson
Bernt Tunold
Bert Hardy
Bert Stern
Bertalan Karlovszky
Bertalan Pór
Bertalan Székely
Berthe Morisot
Bertram Brooker
Bessie Wheeler
Beta Vukanovic
Beta Vukanović
Bettina Heinen-Ayech
Betty Churcher
Betty Merken
Betye Saar
Bholekar Srihari
Bhupen Khakhar
Bian Jingzhao
Bian Shoumin
Bikash Bhattacharjee
Bill Lewis
Bill Sienkiewicz
Bill Traylor
Bill Ward
Bill Watterson
Billie Waters
Billy Childish
Bjørn Wiinblad
Blanche Hoschedé Monet
Bob Byerley
Bob Eggleton
Bob Ringwood
Bob Ross
Bob Singer
Bob Thompson
Boetius Adamsz Bolswert
Bogi Fabian
Bohumil Kubista
Boleslaw Cybis
Bonnard Pierre
Boris Kustodiev
Boris Vallejo
Boris Vladimirski
Bouchta El Hayani
Bourgeois
Božidar Jakac
Bracha L Ettinger
Bracha L. Ettinger
Brad Holland
Brad Kunkle
Bradley Walker Tomlin
Brassaï
Brenda Chamberlain
Brett Whiteley
Breyten Breytenbach
Brian 'Chippy' Dugan
Brian Alfred
Brian Bolland
Brian Despain
Brian Dunlop
Brian Fies
Brian Froud
Brian Snøddy
Brian Thomas
Brian and Wendy Froud
Briana Mora
Brice Marden
Bridget Bate Tichenor
Bridget Riley
Brigette Barrager
Brigid Derham
Brom
Brooke Shaden
Brothers Hildebrandt
Bruce Davidson
Bruce Gilden
Bruce McLean
Bruce Munro
Bruce Nauman
Bruce Onobrakpeya
Bruce Pennington
Bruce Timm
Bruno Liljefors
Bryan Organ
Buckminster Fuller
Bunny Yeager
Byeon Sang-byeok
Byron Galvez
Bálint Kiss
Béla Apáti Abkarovics
Béla Czóbel
Béla Iványi-Grünwald
Béla Kondor
Béla Nagy Abodi
Béla Pállik
Béni Ferenczy
Caesar Andrade Faini
Caesar van Everdingen
Cafer Bater
Cagnaccio di San Pietro
Cam Sykes
Camille Bombois
Camille Bouvagne
Camille Corot
Camille Pissarro
Camille Souter
Camille-Pierre Pambu Bodo
Camilo Egas
Camilo Mori
Canaletto
Candido Bido
Candido Portinari
Cao Buxing
Cao Zhibai
Caravaggio
Carel Fabritius
Carel Weight
Carel Willink
Carey Morris
Carl Arnold Gonzenbach
Carl Barks
Carl Critchlow
Carl Eugen Keel
Carl Eytel
Carl Frederik von Breda
Carl Gustaf Pilo
Carl Heinrich Bloch
Carl Hoppe
Carl Larsson
Carl Morris
Carl Rahl
Carl Spitzweg
Carl Walter Liner
Carl-Henning Pedersen
Carla Wyzgala
Carle Hessay
Carles Delclaux Is
Carlo Carlone
Carlo Carrà
Carlo Crivelli
Carlo Galli Bibiena
Carlo Maderna
Carlo Martini
Carlo Mense
Carlo Randanini
Carlos Berlanga
Carlos Catasse
Carlos Enríquez Gómez
Carlos Francisco Chang Marín
Carlos Saenz de Tejada
Carlos Schwabe
Carlos Trillo Name
Carne Griffiths
Caro Niederer
Carol Bove
Carol Sutton
Caroline Chariot-Dayez
Caroline Gotch
Caroline Lucy Scott
Caroline Mytinger
Carpoforo Tencalla
Carrie Mae Weems
Caspar David Friedrich
Caspar Netscher
Caspar Wolf
Caspar van Wittel
Cassandra Austen
Cassius Marcellus Coolidge
Caterina Tarabotti
Catrin G Grosse
Catrin Welz-Stein
Cecil Beaton
Cecile Walton
Cecilia Beaux
Cecily Brown
Cedric Peyravernay
Cedric Seaut
Cedric Seaut (Keos Masons)
Ceferí Olivé
Celia Fiennes
Celia Frances Bedford
Ceri Richards
Cerith Wyn Evans
Chafik Charobim
Chagall
Chaim Soutine
Chang Dai-chien
Chantal Joffe
Charles Addams
Charles Alphonse du Fresnoy
Charles Alston
Charles Angrand
Charles Billich
Charles Bird King
Charles Blackman
Charles Codman
Charles Conder
Charles Crodel
Charles Cundall
Charles Dana Gibson
Charles Demuth
Charles E Burchfield
Charles E. Burchfield
Charles Ellison
Charles Fremont Conner
Charles Furneaux
Charles Ginner
Charles Gleyre
Charles H Woodbury
Charles H. Woodbury
Charles Harold Davis
Charles Haslewood Shannon
Charles Hinman
Charles Hopkinson
Charles Joshua Chaplin
Charles Le Brun
Charles Le Roux
Charles Mahoney
Charles Marion Russell
Charles Martin
Charles Maurice Detmold
Charles McAuley
Charles Mozley
Charles Ragland Bunnell
Charles Rennie Mackintosh
Charles Ricketts
Charles Roka
Charles Rollier
Charles S Kaelin
Charles S. Kaelin
Charles Schulz
Charles Thomson
Charles Uzzell-Edwards
Charles W Bartlett
Charles W. Bartlett
Charles Williams
Charles Willson Peale
Charles-Amédée-Philippe van Loo
Charles-André van Loo
Charles-François Daubigny
Charlie Bowater
Charlotte Harding
Charlotte Nasmyth
Charly Amani
Charmion von Wiegand
Chase Stone
Chaïm Soutine
Chen Chi
Chen Chun
Chen Daofu
Chen Hong
Chen Hongshou
Chen Jiru
Chen Lin
Chen Lu
Chen Rong
Chen Yifei
Cheng Jiasui
Cheng Shifa
Cheng Zhengkui
Cherryl Fountain
Chesley Bonestell
Chica Macnab
Chiharu Shiota
Chiho Aoshima
Childe Hassam
Chinwe Chukwuogo-Roy
Chip Zdarsky
Chippy
Chizuko Yoshida
Choi Buk
Chris Cold
Chris Foss
Chris Friel
Chris LaBrooy
Chris Moore
Chris Rahn
Chris Rallis
Chris Spollen
Chris Ware
Christabel Dennison
Christen Dalsgaard
Christen Købke
Christian August Lorentzen
Christian Hilfgott Brand
Christian Jane Fergusson
Christian Krohg
Christian Rohlfs
Christian W Staudinger
Christian W. Staudinger
Christo
Christoffel van den Berghe
Christoffer Wilhelm Eckersberg
Christoph Amberger
Christoph Ludwig Agricola
Christophe Vacher
Christopher Balaskas
Christopher Moeller
Christopher Perkins
Christopher Rush
Christopher Williams
Christopher Wood
Christopher Wren
Chuck Close
Cicely Hey
Cicely Mary Barker
Cimabue
Cindy Sherman
Cindy Wright
Claes Corneliszoon Moeyaert
Claes Jansz Visscher
Claes Jansz. Visscher
Claire Dalby
Claire Falkenstein
Claire Hummel
Clara Miller Burd
Clara Peeters
Clara Weaver Parrish
Clarence Holbrook Carter
Clarice Beckett
Clark Voorhees
Claude Bonin-Pissarro
Claude Cahun
Claude Lorrain
Claude Monet
Claude Rogers
Cleon Peterson
Cleve Gray
Cliff Childs
Clifford Ellis
Clifford Ross
Clint Cearley
Clovis Trouille
Clyde Caldwell
Clyfford Still
Clément Serveau
Coby Whitmore
Coles Phillips
Colijn de Coter
Colin Campbell Cooper
Colin Gill
Colin Hayes
Colin McCahon
Colin Middleton
Colin Moss
Conrad Marca-Relli
Conrad Roset
Conroy Maddox
Constance Copeman
Constance Gordon-Cumming
Constance-Anne Parker
Constant
Constant Permeke
Constantin Hansen
Constantine Andreou
Coppo di Marcovaldo
Cor Melchers
Corneille
Cornelia MacIntyre Foley
Cornelia Parker
Cornelis Anthonisz
Cornelis Bisschop
Cornelis Claesz van Wieringen
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Download .txt
gitextract_lx9je00i/

├── .dockerignore
├── .env_docker.example
├── .gitattributes
├── .github/
│   ├── FUNDING.yml
│   ├── ISSUE_TEMPLATE/
│   │   └── bug_report.yml
│   ├── PULL_REQUEST_TEMPLATE.md
│   ├── dependabot.yml
│   └── workflows/
│       ├── deploy.yml
│       └── test-deploy.yml
├── .gitignore
├── .gitmodules
├── .pre-commit-config.yaml
├── .streamlit/
│   └── config.toml
├── CONTRIBUTING.md
├── Dockerfile
├── Dockerfile_base
├── Dockerfile_runpod
├── LICENSE
├── README.md
├── Stable_Diffusion_v1_Model_Card.md
├── Web_based_UI_for_Stable_Diffusion_colab.ipynb
├── _config.yml
├── babel.config.js
├── blog/
│   ├── 2022-10-20/
│   │   └── 1.Textual inversion usage competitio.md
│   └── authors.yml
├── configs/
│   ├── autoencoder/
│   │   ├── autoencoder_kl_16x16x16.yaml
│   │   ├── autoencoder_kl_32x32x4.yaml
│   │   ├── autoencoder_kl_64x64x3.yaml
│   │   └── autoencoder_kl_8x8x64.yaml
│   ├── blip/
│   │   ├── bert_config.json
│   │   ├── caption_coco.yaml
│   │   ├── med_config.json
│   │   ├── nlvr.yaml
│   │   ├── nocaps.yaml
│   │   ├── pretrain.yaml
│   │   ├── retrieval_coco.yaml
│   │   ├── retrieval_flickr.yaml
│   │   ├── retrieval_msrvtt.yaml
│   │   └── vqa.yaml
│   ├── latent-diffusion/
│   │   ├── celebahq-ldm-vq-4.yaml
│   │   ├── cin-ldm-vq-f8.yaml
│   │   ├── cin256-v2.yaml
│   │   ├── ffhq-ldm-vq-4.yaml
│   │   ├── lsun_bedrooms-ldm-vq-4.yaml
│   │   ├── lsun_churches-ldm-kl-8.yaml
│   │   └── txt2img-1p4B-eval.yaml
│   ├── retrieval-augmented-diffusion/
│   │   └── 768x768.yaml
│   ├── stable-diffusion/
│   │   ├── v1-inference.yaml
│   │   ├── v2-inference-v.yaml
│   │   ├── v2-inference.yaml
│   │   ├── v2-inpainting-inference.yaml
│   │   ├── v2-midas-inference.yaml
│   │   └── x4-upscaling.yaml
│   └── webui/
│       ├── webui.yaml
│       ├── webui_flet.yaml
│       └── webui_streamlit.yaml
├── daisi_app.py
├── data/
│   ├── img2txt/
│   │   ├── artists.txt
│   │   ├── flavors.txt
│   │   ├── mediums.txt
│   │   ├── movements.txt
│   │   ├── sites.txt
│   │   ├── subreddits.txt
│   │   ├── tags.txt
│   │   └── techniques.txt
│   ├── scn2img_examples/
│   │   ├── cat_at_beach.scn2img.md
│   │   ├── corgi_3d_transformation.scn2img.md
│   │   ├── corgi_at_beach.scn2img.md
│   │   ├── corgi_at_beach_2.scn2img.md
│   │   └── landscape_3d.scn2img.md
│   └── tags/
│       ├── config.json
│       ├── danbooru.csv
│       ├── e621.csv
│       ├── key_phrases.json
│       └── thumbnails.json
├── docker-compose.yml
├── docs/
│   ├── 1.Installation/
│   │   ├── 1.one-click-installer.md
│   │   ├── 2.windows-installation.md
│   │   ├── 3.linux-installation.md
│   │   └── 4.docker-guide.md
│   ├── 2.Streamlit/
│   │   └── 1.streamlit-interface.md
│   ├── 3.Gradio/
│   │   └── 2.gradio-interface.md
│   ├── 4.post-processing.md
│   ├── 5.concepts-library.md
│   └── 6.custom-models.md
├── docusaurus.config.js
├── entrypoint.sh
├── environment.yaml
├── frontend/
│   ├── .eslintrc.js
│   ├── __init__.py
│   ├── css/
│   │   ├── custom.css
│   │   ├── docs_custom.css
│   │   ├── no_progress_bar.css
│   │   ├── streamlit.main.css
│   │   └── styles.css
│   ├── css_and_js.py
│   ├── dists/
│   │   ├── concept-browser/
│   │   │   └── dist/
│   │   │       ├── assets/
│   │   │       │   ├── index.3ab9729b.css
│   │   │       │   └── index.b5b962e4.js
│   │   │       └── index.html
│   │   └── sd-gallery/
│   │       └── dist/
│   │           ├── assets/
│   │           │   ├── index.4194368f.css
│   │           │   └── index.aeaed602.js
│   │           └── index.html
│   ├── frontend.py
│   ├── image_metadata.py
│   ├── index.html
│   ├── job_manager.py
│   ├── js/
│   │   └── index.js
│   ├── package.json
│   ├── src/
│   │   ├── Component.vue
│   │   ├── app.vue
│   │   ├── env.d.ts
│   │   ├── main.ts
│   │   └── streamlit/
│   │       ├── StreamlitVue.ts
│   │       ├── WithStreamlitConnection.vue
│   │       └── index.ts
│   ├── tsconfig.json
│   ├── tsconfig.node.json
│   ├── ui_functions.py
│   └── vite.config.ts
├── horde_bridge.cmd
├── horde_bridge.sh
├── installer/
│   ├── create_installers.sh
│   ├── install.bat
│   └── install.sh
├── ldm/
│   ├── __init__.py
│   ├── data/
│   │   ├── __init__.py
│   │   ├── base.py
│   │   ├── coco_karpathy_dataset.py
│   │   ├── flickr30k_dataset.py
│   │   ├── imagenet.py
│   │   ├── lsun.py
│   │   ├── nlvr_dataset.py
│   │   ├── nocaps_dataset.py
│   │   ├── personalized.py
│   │   ├── personalized_file.py
│   │   ├── pretrain_dataset.py
│   │   ├── util.py
│   │   ├── video_dataset.py
│   │   └── vqa_dataset.py
│   ├── devices/
│   │   ├── __init__.py
│   │   └── devices.py
│   ├── lr_scheduler.py
│   ├── models/
│   │   ├── __init__.py
│   │   ├── autoencoder.py
│   │   ├── blip.py
│   │   ├── blip_itm.py
│   │   ├── blip_nlvr.py
│   │   ├── blip_pretrain.py
│   │   ├── blip_retrieval.py
│   │   ├── blip_vqa.py
│   │   ├── diffusion/
│   │   │   ├── __init__.py
│   │   │   ├── classifier.py
│   │   │   ├── ddim.py
│   │   │   ├── ddpm.py
│   │   │   ├── dpm_solver/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── dpm_solver.py
│   │   │   │   └── sampler.py
│   │   │   ├── kdiffusion.py
│   │   │   ├── plms.py
│   │   │   └── sampling_util.py
│   │   ├── med.py
│   │   ├── nlvr_encoder.py
│   │   └── vit.py
│   ├── modules/
│   │   ├── __init__.py
│   │   ├── attention.py
│   │   ├── diffusionmodules/
│   │   │   ├── __init__.py
│   │   │   ├── model.py
│   │   │   ├── openaimodel.py
│   │   │   ├── upscaling.py
│   │   │   └── util.py
│   │   ├── distributions/
│   │   │   ├── __init__.py
│   │   │   └── distributions.py
│   │   ├── ema.py
│   │   ├── embedding_manager.py
│   │   ├── encoders/
│   │   │   ├── __init__.py
│   │   │   └── modules.py
│   │   ├── image_degradation/
│   │   │   ├── __init__.py
│   │   │   ├── bsrgan.py
│   │   │   ├── bsrgan_light.py
│   │   │   └── utils_image.py
│   │   ├── losses/
│   │   │   ├── __init__.py
│   │   │   ├── contperceptual.py
│   │   │   └── vqperceptual.py
│   │   ├── midas/
│   │   │   ├── api.py
│   │   │   ├── midas/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_model.py
│   │   │   │   ├── blocks.py
│   │   │   │   ├── dpt_depth.py
│   │   │   │   ├── midas_net.py
│   │   │   │   ├── midas_net_custom.py
│   │   │   │   ├── transforms.py
│   │   │   │   └── vit.py
│   │   │   └── utils.py
│   │   └── x_transformer.py
│   └── util.py
├── optimizedSD/
│   ├── ddpm.py
│   ├── diffusers_txt2img.py
│   ├── openaimodelSplit.py
│   ├── optimUtils.py
│   ├── optimized_img2img.py
│   ├── optimized_txt2img.py
│   ├── samplers.py
│   ├── splitAttention.py
│   └── v1-inference.yaml
├── package.json
├── requirements.txt
├── runpod_entrypoint.sh
├── scripts/
│   ├── APIServer.py
│   ├── ModelManager.py
│   ├── Settings.py
│   ├── __init__.py
│   ├── barfi_baklavajs.py
│   ├── bridgeData_template.py
│   ├── clip_interrogator.py
│   ├── convert_original_stable_diffusion_to_diffusers.py
│   ├── custom_components/
│   │   ├── draggable_number_input/
│   │   │   ├── __init__.py
│   │   │   └── main.js
│   │   └── sygil_suggestions/
│   │       ├── __init__.py
│   │       ├── main.css
│   │       ├── main.js
│   │       └── parent.css
│   ├── diffusers_textual_inversion_2.py
│   ├── home.py
│   ├── hydrus_api/
│   │   ├── __init__.py
│   │   └── utils.py
│   ├── img2img.py
│   ├── img2txt.py
│   ├── imglab.py
│   ├── logger.py
│   ├── merge.py
│   ├── modeldownload.py
│   ├── perlin.py
│   ├── pipelines/
│   │   └── stable_diffusion/
│   │       └── no_check.py
│   ├── post_processing.py
│   ├── prune-ckpt.py
│   ├── relauncher.py
│   ├── scn2img.py
│   ├── sd_concept_library.py
│   ├── sd_concepts_library_downloader.py
│   ├── sd_utils/
│   │   ├── __init__.py
│   │   └── bridge.py
│   ├── sd_utils_old.py
│   ├── stable_diffusion_pipeline.py
│   ├── textual_inversion.py
│   ├── txt2img.py
│   ├── txt2vid.py
│   ├── webui.py
│   ├── webui_streamlit.py
│   └── webui_streamlit_new.py
├── setup.py
├── sidebars.js
├── streamlit_webview.py
├── webui/
│   ├── flet/
│   │   ├── assets/
│   │   │   └── manifest.json
│   │   ├── scripts/
│   │   │   ├── __init__.py
│   │   │   ├── flet_asset_manager.py
│   │   │   ├── flet_canvas.py
│   │   │   ├── flet_file_manager.py
│   │   │   ├── flet_gallery_window.py
│   │   │   ├── flet_messages.py
│   │   │   ├── flet_property_manager.py
│   │   │   ├── flet_settings_window.py
│   │   │   ├── flet_titlebar.py
│   │   │   ├── flet_tool_manager.py
│   │   │   └── flet_utils.py
│   │   └── webui_flet.py
│   └── streamlit/
│       ├── frontend/
│       │   └── css/
│       │       └── streamlit.main.css
│       └── scripts/
│           ├── APIServer.py
│           ├── ModelManager.py
│           ├── Settings.py
│           ├── barfi_baklavajs.py
│           ├── custom_components/
│           │   ├── dragable_number_input/
│           │   │   └── index.html
│           │   ├── draggable_number_input/
│           │   │   ├── __init__.py
│           │   │   └── main.js
│           │   └── sygil_suggestions/
│           │       ├── __init__.py
│           │       ├── main.css
│           │       ├── main.js
│           │       └── parent.css
│           ├── img2img.py
│           ├── img2txt.py
│           ├── post_processing.py
│           ├── sd_concept_library.py
│           ├── sd_utils/
│           │   ├── __init__.py
│           │   └── bridge.py
│           ├── textual_inversion.py
│           ├── txt2img.py
│           ├── txt2vid.py
│           └── webui_streamlit.py
├── webui.cmd
├── webui.sh
└── webui_legacy.cmd
Download .txt
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SYMBOL INDEX (6488 symbols across 140 files)

FILE: frontend/css_and_js.py
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FILE: frontend/dists/concept-browser/dist/assets/index.b5b962e4.js
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  function yt (line 28) | function yt(u){return typeof u=="object"&&u!==null&&u.$$typeof===i}
  function rs (line 28) | function rs(u){var m=/[=:]/g,g={"=":"=0",":":"=2"},A=(""+u).replace(m,fu...
  function Wt (line 28) | function Wt(u){return(""+u).replace(is,"$&/")}
  function il (line 28) | function il(u,m,g,A){if(ir.length){var M=ir.pop();return M.result=u,M.ke...
  function sl (line 28) | function sl(u){u.result=null,u.keyPrefix=null,u.func=null,u.context=null...
  function Mo (line 28) | function Mo(u,m,g,A){var M=typeof u;(M==="undefined"||M==="boolean")&&(u...
  function Co (line 28) | function Co(u,m,g){return u==null?0:Mo(u,"",m,g)}
  function Ro (line 28) | function Ro(u,m){return typeof u=="object"&&u!==null&&u.key!=null?rs(u.k...
  function $h (line 28) | function $h(u,m,g){var A=u.func,M=u.context;A.call(M,m,u.count++)}
  function jh (line 28) | function jh(u,m,g){if(u==null)return u;var A=il(null,null,m,g);Co(u,$h,A...
  function zh (line 28) | function zh(u,m,g){var A=u.result,M=u.keyPrefix,ut=u.func,j=u.context,st...
  function Uo (line 28) | function Uo(u,m,g,A,M){var ut="";g!=null&&(ut=Wt(g)+"/");var j=il(m,ut,A...
  function Wh (line 28) | function Wh(u,m,g){if(u==null)return u;var A=[];return Uo(u,A,null,m,g),A}
  function Yh (line 28) | function Yh(u){return Co(u,function(){return null},null)}
  function Hh (line 28) | function Hh(u){var m=[];return Uo(u,m,null,function(g){return g}),m}
  function Kh (line 28) | function Kh(u){if(!yt(u))throw Error("React.Children.only expected to re...
  function qh (line 28) | function qh(u,m){m===void 0?m=null:m!==null&&typeof m!="function"&&bt("c...
  function Jh (line 28) | function Jh(u){var m={$$typeof:Q,_ctor:u,_status:-1,_result:null};{var g...
  function Gh (line 28) | function Gh(u){return u!=null&&u.$$typeof===X?bt("forwardRef requires a ...
  function ol (line 28) | function ol(u){return typeof u=="string"||typeof u=="function"||u===s||u...
  function Zh (line 28) | function Zh(u,m){return ol(u)||bt("memo: The first argument must be a co...
  function nn (line 28) | function nn(){var u=Te.current;if(u===null)throw Error(`Invalid hook cal...
  function Xh (line 32) | function Xh(u,m){var g=nn();if(m!==void 0&&bt("useContext() second argum...
  function Qh (line 34) | function Qh(u){var m=nn();return m.useState(u)}
  function tp (line 34) | function tp(u,m,g){var A=nn();return A.useReducer(u,m,g)}
  function ep (line 34) | function ep(u){var m=nn();return m.useRef(u)}
  function np (line 34) | function np(u,m){var g=nn();return g.useEffect(u,m)}
  function rp (line 34) | function rp(u,m){var g=nn();return g.useLayoutEffect(u,m)}
  function ip (line 34) | function ip(u,m){var g=nn();return g.useCallback(u,m)}
  function sp (line 34) | function sp(u,m){var g=nn();return g.useMemo(u,m)}
  function op (line 34) | function op(u,m,g){var A=nn();return A.useImperativeHandle(u,m,g)}
  function ap (line 34) | function ap(u,m){{var g=nn();return g.useDebugValue(u,m)}}
  function al (line 34) | function al(){if(Et.current){var u=It(Et.current.type);if(u)return`
  function cp (line 36) | function cp(u){if(u!==void 0){var m=u.fileName.replace(/^.*[\\\/]/,""),g...
  function lp (line 38) | function lp(u){return u!=null?cp(u.__source):""}
  function up (line 38) | function up(u){var m=al();if(!m){var g=typeof u=="string"?u:u.displayNam...
  function ll (line 40) | function ll(u,m){if(!(!u._store||u._store.validated||u.key!=null)){u._st...
  function ul (line 40) | function ul(u,m){if(typeof u=="object"){if(Array.isArray(u))for(var g=0;...
  function fl (line 40) | function fl(u){{var m=u.type;if(m==null||typeof m=="string")return;var g...
  function fp (line 40) | function fp(u){{zt(u);for(var m=Object.keys(u.props),g=0;g<m.length;g++)...
  function dl (line 40) | function dl(u,m,g){var A=ol(u);if(!A){var M="";(u===void 0||typeof u=="o...
  function dp (line 40) | function dp(u){var m=dl.bind(null,u);return m.type=u,hl||(hl=!0,Ce("Reac...
  function hp (line 40) | function hp(u,m,g){for(var A=St.apply(this,arguments),M=2;M<arguments.le...
  function Mt (line 40) | function Mt(e){const t=Yf.get(e);return console.assert(t!=null,"'this' i...
  function Xl (line 40) | function Xl(e){if(e.passiveListener!=null){typeof console!="undefined"&&...
  function Xr (line 40) | function Xr(e,t){Yf.set(this,{eventTarget:e,event:t,eventPhase:2,current...
  method type (line 40) | get type(){return Mt(this).event.type}
  method target (line 40) | get target(){return Mt(this).eventTarget}
  method currentTarget (line 40) | get currentTarget(){return Mt(this).currentTarget}
  method composedPath (line 40) | composedPath(){const e=Mt(this).currentTarget;return e==null?[]:[e]}
  method NONE (line 40) | get NONE(){return 0}
  method CAPTURING_PHASE (line 40) | get CAPTURING_PHASE(){return 1}
  method AT_TARGET (line 40) | get AT_TARGET(){return 2}
  method BUBBLING_PHASE (line 40) | get BUBBLING_PHASE(){return 3}
  method eventPhase (line 40) | get eventPhase(){return Mt(this).eventPhase}
  method stopPropagation (line 40) | stopPropagation(){const e=Mt(this);e.stopped=!0,typeof e.event.stopPropa...
  method stopImmediatePropagation (line 40) | stopImmediatePropagation(){const e=Mt(this);e.stopped=!0,e.immediateStop...
  method bubbles (line 40) | get bubbles(){return Boolean(Mt(this).event.bubbles)}
  method cancelable (line 40) | get cancelable(){return Boolean(Mt(this).event.cancelable)}
  method preventDefault (line 40) | preventDefault(){Xl(Mt(this))}
  method defaultPrevented (line 40) | get defaultPrevented(){return Mt(this).canceled}
  method composed (line 40) | get composed(){return Boolean(Mt(this).event.composed)}
  method timeStamp (line 40) | get timeStamp(){return Mt(this).timeStamp}
  method srcElement (line 40) | get srcElement(){return Mt(this).eventTarget}
  method cancelBubble (line 40) | get cancelBubble(){return Mt(this).stopped}
  method cancelBubble (line 40) | set cancelBubble(e){if(!e)return;const t=Mt(this);t.stopped=!0,typeof t....
  method returnValue (line 40) | get returnValue(){return!Mt(this).canceled}
  method returnValue (line 40) | set returnValue(e){e||Xl(Mt(this))}
  method initEvent (line 40) | initEvent(){}
  function Hf (line 40) | function Hf(e){return{get(){return Mt(this).event[e]},set(t){Mt(this).ev...
  function kb (line 40) | function kb(e){return{value(){const t=Mt(this).event;return t[e].apply(t...
  function $b (line 40) | function $b(e,t){const n=Object.keys(t);if(n.length===0)return e;functio...
  function Kf (line 40) | function Kf(e){if(e==null||e===Object.prototype)return Xr;let t=Oa.get(e...
  function jb (line 40) | function jb(e,t){const n=Kf(Object.getPrototypeOf(t));return new n(e,t)}
  function zb (line 40) | function zb(e){return Mt(e).immediateStopped}
  function Wb (line 40) | function Wb(e,t){Mt(e).eventPhase=t}
  function Yb (line 40) | function Yb(e,t){Mt(e).currentTarget=t}
  function Ql (line 40) | function Ql(e,t){Mt(e).passiveListener=t}
  function Ss (line 40) | function Ss(e){return e!==null&&typeof e=="object"}
  function wi (line 40) | function wi(e){const t=qf.get(e);if(t==null)throw new TypeError("'this' ...
  function Hb (line 40) | function Hb(e){return{get(){let n=wi(this).get(e);for(;n!=null;){if(n.li...
  function Kb (line 40) | function Kb(e,t){Object.defineProperty(e,`on${t}`,Hb(t))}
  function nu (line 40) | function nu(e){function t(){Gn.call(this)}t.prototype=Object.create(Gn.p...
  function Gn (line 40) | function Gn(){if(this instanceof Gn){qf.set(this,new Map);return}if(argu...
  method addEventListener (line 40) | addEventListener(e,t,n){if(t==null)return;if(typeof t!="function"&&!Ss(t...
  method removeEventListener (line 40) | removeEventListener(e,t,n){if(t==null)return;const r=wi(this),o=(Ss(n)?B...
  method dispatchEvent (line 40) | dispatchEvent(e){if(e==null||typeof e.type!="string")throw new TypeError...
  function An (line 40) | function An(e,t,n){return t<=e&&e<=n}
  function bo (line 40) | function bo(e){if(e===void 0)return{};if(e===Object(e))return e;throw Ty...
  function qb (line 40) | function qb(e){for(var t=String(e),n=t.length,r=0,i=[];r<n;){var o=t.cha...
  function Jb (line 40) | function Jb(e){for(var t="",n=0;n<e.length;++n){var r=e[n];r<=65535?t+=S...
  function cc (line 40) | function cc(e){this.tokens=[].slice.call(e)}
  function Wo (line 40) | function Wo(e,t){if(e)throw TypeError("Decoder error");return t||65533}
  function Ps (line 40) | function Ps(e,t){if(!(this instanceof Ps))return new Ps(e,t);if(e=e!==vo...
  function Vs (line 40) | function Vs(e,t){if(!(this instanceof Vs))return new Vs(e,t);if(e=e!==vo...
  function Gb (line 40) | function Gb(e){var t=e.fatal,n=0,r=0,i=0,o=128,s=191;this.handler=functi...
  function Zb (line 40) | function Zb(e){e.fatal,this.handler=function(t,n){if(n===Us)return Qr;if...
  class ru (line 40) | class ru{constructor(t){this._json=t}get schema(){return this._json.sche...
    method constructor (line 40) | constructor(t){this._json=t}
    method schema (line 40) | get schema(){return this._json.schema}
    method batches (line 40) | get batches(){return this._json.batches||[]}
    method dictionaries (line 40) | get dictionaries(){return this._json.dictionaries||[]}
  class Fr (line 40) | class Fr{tee(){return this._getDOMStream().tee()}pipe(t,n){return this._...
    method tee (line 40) | tee(){return this._getDOMStream().tee()}
    method pipe (line 40) | pipe(t,n){return this._getNodeStream().pipe(t,n)}
    method pipeTo (line 40) | pipeTo(t,n){return this._getDOMStream().pipeTo(t,n)}
    method pipeThrough (line 40) | pipeThrough(t,n){return this._getDOMStream().pipeThrough(t,n)}
    method _getDOMStream (line 40) | _getDOMStream(){return this._DOMStream||(this._DOMStream=this.toDOMStr...
    method _getNodeStream (line 40) | _getNodeStream(){return this._nodeStream||(this._nodeStream=this.toNod...
  class Xb (line 40) | class Xb extends Fr{constructor(){super(),this._values=[],this.resolvers...
    method constructor (line 40) | constructor(){super(),this._values=[],this.resolvers=[],this._closedPr...
    method closed (line 40) | get closed(){return this._closedPromise}
    method cancel (line 40) | async cancel(t){await this.return(t)}
    method write (line 40) | write(t){this._ensureOpen()&&(this.resolvers.length<=0?this._values.pu...
    method abort (line 40) | abort(t){this._closedPromiseResolve&&(this.resolvers.length<=0?this._e...
    method close (line 40) | close(){if(this._closedPromiseResolve){const{resolvers:t}=this;for(;t....
    method toDOMStream (line 40) | toDOMStream(t){return we.toDOMStream(this._closedPromiseResolve||this....
    method toNodeStream (line 40) | toNodeStream(t){return we.toNodeStream(this._closedPromiseResolve||thi...
    method throw (line 40) | async throw(t){return await this.abort(t),Rt}
    method return (line 40) | async return(t){return await this.close(),Rt}
    method read (line 40) | async read(t){return(await this.next(t,"read")).value}
    method peek (line 40) | async peek(t){return(await this.next(t,"peek")).value}
    method next (line 40) | next(...t){return this._values.length>0?Promise.resolve({done:!1,value...
    method _ensureOpen (line 40) | _ensureOpen(){if(this._closedPromiseResolve)return!0;throw new Error(`...
  method [Symbol.asyncIterator] (line 40) | [Symbol.asyncIterator](){return this}
  function t (line 40) | function t(){throw e()}
    method BYTES_PER_ELEMENT (line 40) | static get BYTES_PER_ELEMENT(){return 8}
    method of (line 40) | static of(){throw e()}
    method from (line 40) | static from(){throw e()}
    method constructor (line 40) | constructor(){throw e()}
    method BYTES_PER_ELEMENT (line 40) | static get BYTES_PER_ELEMENT(){return 8}
    method of (line 40) | static of(){throw e()}
    method from (line 40) | static from(){throw e()}
    method constructor (line 40) | constructor(){throw e()}
  class t (line 40) | class t{static get BYTES_PER_ELEMENT(){return 8}static of(){throw e()}st...
    method BYTES_PER_ELEMENT (line 40) | static get BYTES_PER_ELEMENT(){return 8}
    method of (line 40) | static of(){throw e()}
    method from (line 40) | static from(){throw e()}
    method constructor (line 40) | constructor(){throw e()}
    method BYTES_PER_ELEMENT (line 40) | static get BYTES_PER_ELEMENT(){return 8}
    method of (line 40) | static of(){throw e()}
    method from (line 40) | static from(){throw e()}
    method constructor (line 40) | constructor(){throw e()}
  class t (line 40) | class t{static get BYTES_PER_ELEMENT(){return 8}static of(){throw e()}st...
    method BYTES_PER_ELEMENT (line 40) | static get BYTES_PER_ELEMENT(){return 8}
    method of (line 40) | static of(){throw e()}
    method from (line 40) | static from(){throw e()}
    method constructor (line 40) | constructor(){throw e()}
    method BYTES_PER_ELEMENT (line 40) | static get BYTES_PER_ELEMENT(){return 8}
    method of (line 40) | static of(){throw e()}
    method from (line 40) | static from(){throw e()}
    method constructor (line 40) | constructor(){throw e()}
  function ig (line 40) | function ig(e){let t=e[0]?[e[0]]:[],n,r,i,o;for(let s,a,c=0,l=0,d=e.leng...
  function Di (line 40) | function Di(e,t,n=0,r=t.byteLength){const i=e.byteLength,o=new Uint8Arra...
  function He (line 40) | function He(e,t){let n=ig(e),r=n.reduce((d,p)=>d+p.byteLength,0),i,o,s,a...
  function at (line 40) | function at(e,t){let n=Zf(t)?t.value:t;return n instanceof e?e===Uint8Ar...
  function wo (line 40) | function wo(e,t,n){if(e!==0){n=n.slice(0,t+1);for(let r=-1;++r<=t;)n[r]+...
  function sd (line 40) | function sd(e,t){let n=0,r=e.length;if(r!==t.length)return!1;if(r>0)do i...
  method fromIterable (line 40) | fromIterable(e){return us(Fg(e))}
  method fromAsyncIterable (line 40) | fromAsyncIterable(e){return us(Eg(e))}
  method fromDOMStream (line 40) | fromDOMStream(e){return us(Dg(e))}
  method fromNodeStream (line 40) | fromNodeStream(e){return us(Mg(e))}
  method toDOMStream (line 40) | toDOMStream(e,t){throw new Error('"toDOMStream" not available in this en...
  method toNodeStream (line 40) | toNodeStream(e,t){throw new Error('"toNodeStream" not available in this ...
  function c (line 40) | function c(){return o==="peek"?He(r,s)[0]:([i,r,a]=He(r,s),i)}
  function c (line 40) | function c(){return o==="peek"?He(r,s)[0]:([i,r,a]=He(r,s),i)}
  function c (line 40) | function c(){return o==="peek"?He(r,s)[0]:([i,r,a]=He(r,s),i)}
  class Lg (line 40) | class Lg{constructor(t){this.source=t,this.byobReader=null,this.defaultR...
    method constructor (line 40) | constructor(t){this.source=t,this.byobReader=null,this.defaultReader=n...
    method closed (line 40) | get closed(){return this.reader?this.reader.closed.catch(()=>{}):Promi...
    method releaseLock (line 40) | releaseLock(){this.reader&&this.reader.releaseLock(),this.reader=this....
    method cancel (line 40) | async cancel(t){const{reader:n,source:r}=this;n&&await n.cancel(t).cat...
    method read (line 40) | async read(t){if(t===0)return{done:this.reader==null,value:new Uint8Ar...
    method getDefaultReader (line 40) | getDefaultReader(){return this.byobReader&&this.releaseLock(),this.def...
    method getBYOBReader (line 40) | getBYOBReader(){return this.defaultReader&&this.releaseLock(),this.byo...
    method readFromBYOBReader (line 40) | async readFromBYOBReader(t){return await od(this.getBYOBReader(),new A...
  function od (line 40) | async function od(e,t,n,r){if(n>=r)return{done:!1,value:new Uint8Array(t...
  function d (line 40) | function d(){return o==="peek"?He(c,s)[0]:([l,c,a]=He(c,s),l)}
  function p (line 40) | function p(_,O){return l=c=null,new Promise(async(P,X)=>{for(const[Q,gt]...
  class dt (line 40) | class dt{}
  class i (line 40) | class i{constructor(){this.bb=null,this.bb_pos=0}__init(s,a){return this...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsNull (line 40) | static getRootAsNull(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startNull (line 40) | static startNull(s){s.startObject(0)}
    method endNull (line 40) | static endNull(s){return s.endObject()}
    method createNull (line 40) | static createNull(s){return i.startNull(s),i.endNull(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsStruct_ (line 40) | static getRootAsStruct_(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method startStruct_ (line 40) | static startStruct_(s){s.startObject(0)}
    method endStruct_ (line 40) | static endStruct_(s){return s.endObject()}
    method createStruct_ (line 40) | static createStruct_(s){return i.startStruct_(s),i.endStruct_(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsList (line 40) | static getRootAsList(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startList (line 40) | static startList(s){s.startObject(0)}
    method endList (line 40) | static endList(s){return s.endObject()}
    method createList (line 40) | static createList(s){return i.startList(s),i.endList(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeList (line 40) | static getRootAsLargeList(s,a){return(a||new i).__init(s.readInt32(s.p...
    method startLargeList (line 40) | static startLargeList(s){s.startObject(0)}
    method endLargeList (line 40) | static endLargeList(s){return s.endObject()}
    method createLargeList (line 40) | static createLargeList(s){return i.startLargeList(s),i.endLargeList(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFixedSizeList (line 40) | static getRootAsFixedSizeList(s,a){return(a||new i).__init(s.readInt32...
    method listSize (line 40) | listSize(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.read...
    method startFixedSizeList (line 40) | static startFixedSizeList(s){s.startObject(1)}
    method addListSize (line 40) | static addListSize(s,a){s.addFieldInt32(0,a,0)}
    method endFixedSizeList (line 40) | static endFixedSizeList(s){return s.endObject()}
    method createFixedSizeList (line 40) | static createFixedSizeList(s,a){return i.startFixedSizeList(s),i.addLi...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsMap (line 40) | static getRootAsMap(s,a){return(a||new i).__init(s.readInt32(s.positio...
    method keysSorted (line 40) | keysSorted(){let s=this.bb.__offset(this.bb_pos,4);return s?!!this.bb....
    method startMap (line 40) | static startMap(s){s.startObject(1)}
    method addKeysSorted (line 40) | static addKeysSorted(s,a){s.addFieldInt8(0,+a,0)}
    method endMap (line 40) | static endMap(s){return s.endObject()}
    method createMap (line 40) | static createMap(s,a){return i.startMap(s),i.addKeysSorted(s,a),i.endM...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsUnion (line 40) | static getRootAsUnion(s,a){return(a||new i).__init(s.readInt32(s.posit...
    method mode (line 40) | mode(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method typeIds (line 40) | typeIds(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.read...
    method typeIdsLength (line 40) | typeIdsLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb...
    method typeIdsArray (line 40) | typeIdsArray(){let s=this.bb.__offset(this.bb_pos,6);return s?new Int3...
    method startUnion (line 40) | static startUnion(s){s.startObject(2)}
    method addMode (line 40) | static addMode(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.UnionMo...
    method addTypeIds (line 40) | static addTypeIds(s,a){s.addFieldOffset(1,a,0)}
    method createTypeIdsVector (line 40) | static createTypeIdsVector(s,a){s.startVector(4,a.length,4);for(let c=...
    method startTypeIdsVector (line 40) | static startTypeIdsVector(s,a){s.startVector(4,a,4)}
    method endUnion (line 40) | static endUnion(s){return s.endObject()}
    method createUnion (line 40) | static createUnion(s,a,c){return i.startUnion(s),i.addMode(s,a),i.addT...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsInt (line 40) | static getRootAsInt(s,a){return(a||new i).__init(s.readInt32(s.positio...
    method bitWidth (line 40) | bitWidth(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.read...
    method isSigned (line 40) | isSigned(){let s=this.bb.__offset(this.bb_pos,6);return s?!!this.bb.re...
    method startInt (line 40) | static startInt(s){s.startObject(2)}
    method addBitWidth (line 40) | static addBitWidth(s,a){s.addFieldInt32(0,a,0)}
    method addIsSigned (line 40) | static addIsSigned(s,a){s.addFieldInt8(1,+a,0)}
    method endInt (line 40) | static endInt(s){return s.endObject()}
    method createInt (line 40) | static createInt(s,a,c){return i.startInt(s),i.addBitWidth(s,a),i.addI...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFloatingPoint (line 40) | static getRootAsFloatingPoint(s,a){return(a||new i).__init(s.readInt32...
    method precision (line 40) | precision(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method startFloatingPoint (line 40) | static startFloatingPoint(s){s.startObject(1)}
    method addPrecision (line 40) | static addPrecision(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.Pr...
    method endFloatingPoint (line 40) | static endFloatingPoint(s){return s.endObject()}
    method createFloatingPoint (line 40) | static createFloatingPoint(s,a){return i.startFloatingPoint(s),i.addPr...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsUtf8 (line 40) | static getRootAsUtf8(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startUtf8 (line 40) | static startUtf8(s){s.startObject(0)}
    method endUtf8 (line 40) | static endUtf8(s){return s.endObject()}
    method createUtf8 (line 40) | static createUtf8(s){return i.startUtf8(s),i.endUtf8(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsBinary (line 40) | static getRootAsBinary(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method startBinary (line 40) | static startBinary(s){s.startObject(0)}
    method endBinary (line 40) | static endBinary(s){return s.endObject()}
    method createBinary (line 40) | static createBinary(s){return i.startBinary(s),i.endBinary(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeUtf8 (line 40) | static getRootAsLargeUtf8(s,a){return(a||new i).__init(s.readInt32(s.p...
    method startLargeUtf8 (line 40) | static startLargeUtf8(s){s.startObject(0)}
    method endLargeUtf8 (line 40) | static endLargeUtf8(s){return s.endObject()}
    method createLargeUtf8 (line 40) | static createLargeUtf8(s){return i.startLargeUtf8(s),i.endLargeUtf8(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeBinary (line 40) | static getRootAsLargeBinary(s,a){return(a||new i).__init(s.readInt32(s...
    method startLargeBinary (line 40) | static startLargeBinary(s){s.startObject(0)}
    method endLargeBinary (line 40) | static endLargeBinary(s){return s.endObject()}
    method createLargeBinary (line 40) | static createLargeBinary(s){return i.startLargeBinary(s),i.endLargeBin...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFixedSizeBinary (line 40) | static getRootAsFixedSizeBinary(s,a){return(a||new i).__init(s.readInt...
    method byteWidth (line 40) | byteWidth(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method startFixedSizeBinary (line 40) | static startFixedSizeBinary(s){s.startObject(1)}
    method addByteWidth (line 40) | static addByteWidth(s,a){s.addFieldInt32(0,a,0)}
    method endFixedSizeBinary (line 40) | static endFixedSizeBinary(s){return s.endObject()}
    method createFixedSizeBinary (line 40) | static createFixedSizeBinary(s,a){return i.startFixedSizeBinary(s),i.a...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsBool (line 40) | static getRootAsBool(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startBool (line 40) | static startBool(s){s.startObject(0)}
    method endBool (line 40) | static endBool(s){return s.endObject()}
    method createBool (line 40) | static createBool(s){return i.startBool(s),i.endBool(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDecimal (line 40) | static getRootAsDecimal(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method precision (line 40) | precision(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method scale (line 40) | scale(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.readInt...
    method startDecimal (line 40) | static startDecimal(s){s.startObject(2)}
    method addPrecision (line 40) | static addPrecision(s,a){s.addFieldInt32(0,a,0)}
    method addScale (line 40) | static addScale(s,a){s.addFieldInt32(1,a,0)}
    method endDecimal (line 40) | static endDecimal(s){return s.endObject()}
    method createDecimal (line 40) | static createDecimal(s,a,c){return i.startDecimal(s),i.addPrecision(s,...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDate (line 40) | static getRootAsDate(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startDate (line 40) | static startDate(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.DateUni...
    method endDate (line 40) | static endDate(s){return s.endObject()}
    method createDate (line 40) | static createDate(s,a){return i.startDate(s),i.addUnit(s,a),i.endDate(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsTime (line 40) | static getRootAsTime(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method bitWidth (line 40) | bitWidth(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.read...
    method startTime (line 40) | static startTime(s){s.startObject(2)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method addBitWidth (line 40) | static addBitWidth(s,a){s.addFieldInt32(1,a,32)}
    method endTime (line 40) | static endTime(s){return s.endObject()}
    method createTime (line 40) | static createTime(s,a,c){return i.startTime(s),i.addUnit(s,a),i.addBit...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsTimestamp (line 40) | static getRootAsTimestamp(s,a){return(a||new i).__init(s.readInt32(s.p...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method timezone (line 40) | timezone(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.__s...
    method startTimestamp (line 40) | static startTimestamp(s){s.startObject(2)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method addTimezone (line 40) | static addTimezone(s,a){s.addFieldOffset(1,a,0)}
    method endTimestamp (line 40) | static endTimestamp(s){return s.endObject()}
    method createTimestamp (line 40) | static createTimestamp(s,a,c){return i.startTimestamp(s),i.addUnit(s,a...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsInterval (line 40) | static getRootAsInterval(s,a){return(a||new i).__init(s.readInt32(s.po...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startInterval (line 40) | static startInterval(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.Interva...
    method endInterval (line 40) | static endInterval(s){return s.endObject()}
    method createInterval (line 40) | static createInterval(s,a){return i.startInterval(s),i.addUnit(s,a),i....
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDuration (line 40) | static getRootAsDuration(s,a){return(a||new i).__init(s.readInt32(s.po...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startDuration (line 40) | static startDuration(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method endDuration (line 40) | static endDuration(s){return s.endObject()}
    method createDuration (line 40) | static createDuration(s,a){return i.startDuration(s),i.addUnit(s,a),i....
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsKeyValue (line 40) | static getRootAsKeyValue(s,a){return(a||new i).__init(s.readInt32(s.po...
    method key (line 40) | key(s){let a=this.bb.__offset(this.bb_pos,4);return a?this.bb.__string...
    method value (line 40) | value(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.__stri...
    method startKeyValue (line 40) | static startKeyValue(s){s.startObject(2)}
    method addKey (line 40) | static addKey(s,a){s.addFieldOffset(0,a,0)}
    method addValue (line 40) | static addValue(s,a){s.addFieldOffset(1,a,0)}
    method endKeyValue (line 40) | static endKeyValue(s){return s.endObject()}
    method createKeyValue (line 40) | static createKeyValue(s,a,c){return i.startKeyValue(s),i.addKey(s,a),i...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDictionaryEncoding (line 40) | static getRootAsDictionaryEncoding(s,a){return(a||new i).__init(s.read...
    method id (line 40) | id(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt64(...
    method indexType (line 40) | indexType(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new e....
    method isOrdered (line 40) | isOrdered(){let s=this.bb.__offset(this.bb_pos,8);return s?!!this.bb.r...
    method startDictionaryEncoding (line 40) | static startDictionaryEncoding(s){s.startObject(3)}
    method addId (line 40) | static addId(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addIndexType (line 40) | static addIndexType(s,a){s.addFieldOffset(1,a,0)}
    method addIsOrdered (line 40) | static addIsOrdered(s,a){s.addFieldInt8(2,+a,0)}
    method endDictionaryEncoding (line 40) | static endDictionaryEncoding(s){return s.endObject()}
    method createDictionaryEncoding (line 40) | static createDictionaryEncoding(s,a,c,l){return i.startDictionaryEncod...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsField (line 40) | static getRootAsField(s,a){return(a||new i).__init(s.readInt32(s.posit...
    method name (line 40) | name(s){let a=this.bb.__offset(this.bb_pos,4);return a?this.bb.__strin...
    method nullable (line 40) | nullable(){let s=this.bb.__offset(this.bb_pos,6);return s?!!this.bb.re...
    method typeType (line 40) | typeType(){let s=this.bb.__offset(this.bb_pos,8);return s?this.bb.read...
    method type (line 40) | type(s){let a=this.bb.__offset(this.bb_pos,10);return a?this.bb.__unio...
    method dictionary (line 40) | dictionary(s){let a=this.bb.__offset(this.bb_pos,12);return a?(s||new ...
    method children (line 40) | children(s,a){let c=this.bb.__offset(this.bb_pos,14);return c?(a||new ...
    method childrenLength (line 40) | childrenLength(){let s=this.bb.__offset(this.bb_pos,14);return s?this....
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,16);return c?(a...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,16);return s...
    method startField (line 40) | static startField(s){s.startObject(7)}
    method addName (line 40) | static addName(s,a){s.addFieldOffset(0,a,0)}
    method addNullable (line 40) | static addNullable(s,a){s.addFieldInt8(1,+a,0)}
    method addTypeType (line 40) | static addTypeType(s,a){s.addFieldInt8(2,a,e.apache.arrow.flatbuf.Type...
    method addType (line 40) | static addType(s,a){s.addFieldOffset(3,a,0)}
    method addDictionary (line 40) | static addDictionary(s,a){s.addFieldOffset(4,a,0)}
    method addChildren (line 40) | static addChildren(s,a){s.addFieldOffset(5,a,0)}
    method createChildrenVector (line 40) | static createChildrenVector(s,a){s.startVector(4,a.length,4);for(let c...
    method startChildrenVector (line 40) | static startChildrenVector(s,a){s.startVector(4,a,4)}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(6,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endField (line 40) | static endField(s){return s.endObject()}
    method createField (line 40) | static createField(s,a,c,l,d,p,_,O){return i.startField(s),i.addName(s...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method offset (line 40) | offset(){return this.bb.readInt64(this.bb_pos)}
    method length (line 40) | length(){return this.bb.readInt64(this.bb_pos+8)}
    method createBuffer (line 40) | static createBuffer(s,a,c){return s.prep(8,16),s.writeInt64(c),s.write...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsSchema (line 40) | static getRootAsSchema(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method endianness (line 40) | endianness(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.re...
    method fields (line 40) | fields(s,a){let c=this.bb.__offset(this.bb_pos,6);return c?(a||new e.a...
    method fieldsLength (line 40) | fieldsLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb....
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a|...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,8);return s?...
    method startSchema (line 40) | static startSchema(s){s.startObject(3)}
    method addEndianness (line 40) | static addEndianness(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.E...
    method addFields (line 40) | static addFields(s,a){s.addFieldOffset(1,a,0)}
    method createFieldsVector (line 40) | static createFieldsVector(s,a){s.startVector(4,a.length,4);for(let c=a...
    method startFieldsVector (line 40) | static startFieldsVector(s,a){s.startVector(4,a,4)}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(2,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endSchema (line 40) | static endSchema(s){return s.endObject()}
    method finishSchemaBuffer (line 40) | static finishSchemaBuffer(s,a){s.finish(a)}
    method createSchema (line 40) | static createSchema(s,a,c,l){return i.startSchema(s),i.addEndianness(s...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method length (line 40) | length(){return this.bb.readInt64(this.bb_pos)}
    method nullCount (line 40) | nullCount(){return this.bb.readInt64(this.bb_pos+8)}
    method createFieldNode (line 40) | static createFieldNode(s,a,c){return s.prep(8,16),s.writeInt64(c),s.wr...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsRecordBatch (line 40) | static getRootAsRecordBatch(s,a){return(a||new i).__init(s.readInt32(s...
    method length (line 40) | length(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readIn...
    method nodes (line 40) | nodes(s,a){let c=this.bb.__offset(this.bb_pos,6);return c?(a||new e.ap...
    method nodesLength (line 40) | nodesLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb._...
    method buffers (line 40) | buffers(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a||new v....
    method buffersLength (line 40) | buffersLength(){let s=this.bb.__offset(this.bb_pos,8);return s?this.bb...
    method startRecordBatch (line 40) | static startRecordBatch(s){s.startObject(3)}
    method addLength (line 40) | static addLength(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addNodes (line 40) | static addNodes(s,a){s.addFieldOffset(1,a,0)}
    method startNodesVector (line 40) | static startNodesVector(s,a){s.startVector(16,a,8)}
    method addBuffers (line 40) | static addBuffers(s,a){s.addFieldOffset(2,a,0)}
    method startBuffersVector (line 40) | static startBuffersVector(s,a){s.startVector(16,a,8)}
    method endRecordBatch (line 40) | static endRecordBatch(s){return s.endObject()}
    method createRecordBatch (line 40) | static createRecordBatch(s,a,c,l){return i.startRecordBatch(s),i.addLe...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDictionaryBatch (line 40) | static getRootAsDictionaryBatch(s,a){return(a||new i).__init(s.readInt...
    method id (line 40) | id(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt64(...
    method data (line 40) | data(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new e.apach...
    method isDelta (line 40) | isDelta(){let s=this.bb.__offset(this.bb_pos,8);return s?!!this.bb.rea...
    method startDictionaryBatch (line 40) | static startDictionaryBatch(s){s.startObject(3)}
    method addId (line 40) | static addId(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addData (line 40) | static addData(s,a){s.addFieldOffset(1,a,0)}
    method addIsDelta (line 40) | static addIsDelta(s,a){s.addFieldInt8(2,+a,0)}
    method endDictionaryBatch (line 40) | static endDictionaryBatch(s){return s.endObject()}
    method createDictionaryBatch (line 40) | static createDictionaryBatch(s,a,c,l){return i.startDictionaryBatch(s)...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsMessage (line 40) | static getRootAsMessage(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method version (line 40) | version(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readI...
    method headerType (line 40) | headerType(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.re...
    method header (line 40) | header(s){let a=this.bb.__offset(this.bb_pos,8);return a?this.bb.__uni...
    method bodyLength (line 40) | bodyLength(){let s=this.bb.__offset(this.bb_pos,10);return s?this.bb.r...
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,12);return c?(a...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,12);return s...
    method startMessage (line 40) | static startMessage(s){s.startObject(5)}
    method addVersion (line 40) | static addVersion(s,a){s.addFieldInt16(0,a,v.apache.arrow.flatbuf.Meta...
    method addHeaderType (line 40) | static addHeaderType(s,a){s.addFieldInt8(1,a,e.apache.arrow.flatbuf.Me...
    method addHeader (line 40) | static addHeader(s,a){s.addFieldOffset(2,a,0)}
    method addBodyLength (line 40) | static addBodyLength(s,a){s.addFieldInt64(3,a,s.createLong(0,0))}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(4,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endMessage (line 40) | static endMessage(s){return s.endObject()}
    method finishMessageBuffer (line 40) | static finishMessageBuffer(s,a){s.finish(a)}
    method createMessage (line 40) | static createMessage(s,a,c,l,d,p){return i.startMessage(s),i.addVersio...
    method constructor (line 46) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 46) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFooter (line 46) | static getRootAsFooter(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method version (line 46) | version(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readI...
    method schema (line 46) | schema(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new v.apa...
    method dictionaries (line 46) | dictionaries(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a||n...
    method dictionariesLength (line 46) | dictionariesLength(){let s=this.bb.__offset(this.bb_pos,8);return s?th...
    method recordBatches (line 46) | recordBatches(s,a){let c=this.bb.__offset(this.bb_pos,10);return c?(a|...
    method recordBatchesLength (line 46) | recordBatchesLength(){let s=this.bb.__offset(this.bb_pos,10);return s?...
    method startFooter (line 46) | static startFooter(s){s.startObject(4)}
    method addVersion (line 46) | static addVersion(s,a){s.addFieldInt16(0,a,v.apache.arrow.flatbuf.Meta...
    method addSchema (line 46) | static addSchema(s,a){s.addFieldOffset(1,a,0)}
    method addDictionaries (line 46) | static addDictionaries(s,a){s.addFieldOffset(2,a,0)}
    method startDictionariesVector (line 46) | static startDictionariesVector(s,a){s.startVector(24,a,8)}
    method addRecordBatches (line 46) | static addRecordBatches(s,a){s.addFieldOffset(3,a,0)}
    method startRecordBatchesVector (line 46) | static startRecordBatchesVector(s,a){s.startVector(24,a,8)}
    method endFooter (line 46) | static endFooter(s){return s.endObject()}
    method finishFooterBuffer (line 46) | static finishFooterBuffer(s,a){s.finish(a)}
    method createFooter (line 46) | static createFooter(s,a,c,l,d){return i.startFooter(s),i.addVersion(s,...
    method constructor (line 46) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 46) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method offset (line 46) | offset(){return this.bb.readInt64(this.bb_pos)}
    method metaDataLength (line 46) | metaDataLength(){return this.bb.readInt32(this.bb_pos+8)}
    method bodyLength (line 46) | bodyLength(){return this.bb.readInt64(this.bb_pos+16)}
    method createBlock (line 46) | static createBlock(s,a,c,l){return s.prep(8,24),s.writeInt64(l),s.pad(...
  class i (line 40) | class i{constructor(){this.bb=null,this.bb_pos=0}__init(s,a){return this...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsNull (line 40) | static getRootAsNull(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startNull (line 40) | static startNull(s){s.startObject(0)}
    method endNull (line 40) | static endNull(s){return s.endObject()}
    method createNull (line 40) | static createNull(s){return i.startNull(s),i.endNull(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsStruct_ (line 40) | static getRootAsStruct_(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method startStruct_ (line 40) | static startStruct_(s){s.startObject(0)}
    method endStruct_ (line 40) | static endStruct_(s){return s.endObject()}
    method createStruct_ (line 40) | static createStruct_(s){return i.startStruct_(s),i.endStruct_(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsList (line 40) | static getRootAsList(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startList (line 40) | static startList(s){s.startObject(0)}
    method endList (line 40) | static endList(s){return s.endObject()}
    method createList (line 40) | static createList(s){return i.startList(s),i.endList(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeList (line 40) | static getRootAsLargeList(s,a){return(a||new i).__init(s.readInt32(s.p...
    method startLargeList (line 40) | static startLargeList(s){s.startObject(0)}
    method endLargeList (line 40) | static endLargeList(s){return s.endObject()}
    method createLargeList (line 40) | static createLargeList(s){return i.startLargeList(s),i.endLargeList(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFixedSizeList (line 40) | static getRootAsFixedSizeList(s,a){return(a||new i).__init(s.readInt32...
    method listSize (line 40) | listSize(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.read...
    method startFixedSizeList (line 40) | static startFixedSizeList(s){s.startObject(1)}
    method addListSize (line 40) | static addListSize(s,a){s.addFieldInt32(0,a,0)}
    method endFixedSizeList (line 40) | static endFixedSizeList(s){return s.endObject()}
    method createFixedSizeList (line 40) | static createFixedSizeList(s,a){return i.startFixedSizeList(s),i.addLi...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsMap (line 40) | static getRootAsMap(s,a){return(a||new i).__init(s.readInt32(s.positio...
    method keysSorted (line 40) | keysSorted(){let s=this.bb.__offset(this.bb_pos,4);return s?!!this.bb....
    method startMap (line 40) | static startMap(s){s.startObject(1)}
    method addKeysSorted (line 40) | static addKeysSorted(s,a){s.addFieldInt8(0,+a,0)}
    method endMap (line 40) | static endMap(s){return s.endObject()}
    method createMap (line 40) | static createMap(s,a){return i.startMap(s),i.addKeysSorted(s,a),i.endM...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsUnion (line 40) | static getRootAsUnion(s,a){return(a||new i).__init(s.readInt32(s.posit...
    method mode (line 40) | mode(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method typeIds (line 40) | typeIds(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.read...
    method typeIdsLength (line 40) | typeIdsLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb...
    method typeIdsArray (line 40) | typeIdsArray(){let s=this.bb.__offset(this.bb_pos,6);return s?new Int3...
    method startUnion (line 40) | static startUnion(s){s.startObject(2)}
    method addMode (line 40) | static addMode(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.UnionMo...
    method addTypeIds (line 40) | static addTypeIds(s,a){s.addFieldOffset(1,a,0)}
    method createTypeIdsVector (line 40) | static createTypeIdsVector(s,a){s.startVector(4,a.length,4);for(let c=...
    method startTypeIdsVector (line 40) | static startTypeIdsVector(s,a){s.startVector(4,a,4)}
    method endUnion (line 40) | static endUnion(s){return s.endObject()}
    method createUnion (line 40) | static createUnion(s,a,c){return i.startUnion(s),i.addMode(s,a),i.addT...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsInt (line 40) | static getRootAsInt(s,a){return(a||new i).__init(s.readInt32(s.positio...
    method bitWidth (line 40) | bitWidth(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.read...
    method isSigned (line 40) | isSigned(){let s=this.bb.__offset(this.bb_pos,6);return s?!!this.bb.re...
    method startInt (line 40) | static startInt(s){s.startObject(2)}
    method addBitWidth (line 40) | static addBitWidth(s,a){s.addFieldInt32(0,a,0)}
    method addIsSigned (line 40) | static addIsSigned(s,a){s.addFieldInt8(1,+a,0)}
    method endInt (line 40) | static endInt(s){return s.endObject()}
    method createInt (line 40) | static createInt(s,a,c){return i.startInt(s),i.addBitWidth(s,a),i.addI...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFloatingPoint (line 40) | static getRootAsFloatingPoint(s,a){return(a||new i).__init(s.readInt32...
    method precision (line 40) | precision(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method startFloatingPoint (line 40) | static startFloatingPoint(s){s.startObject(1)}
    method addPrecision (line 40) | static addPrecision(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.Pr...
    method endFloatingPoint (line 40) | static endFloatingPoint(s){return s.endObject()}
    method createFloatingPoint (line 40) | static createFloatingPoint(s,a){return i.startFloatingPoint(s),i.addPr...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsUtf8 (line 40) | static getRootAsUtf8(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startUtf8 (line 40) | static startUtf8(s){s.startObject(0)}
    method endUtf8 (line 40) | static endUtf8(s){return s.endObject()}
    method createUtf8 (line 40) | static createUtf8(s){return i.startUtf8(s),i.endUtf8(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsBinary (line 40) | static getRootAsBinary(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method startBinary (line 40) | static startBinary(s){s.startObject(0)}
    method endBinary (line 40) | static endBinary(s){return s.endObject()}
    method createBinary (line 40) | static createBinary(s){return i.startBinary(s),i.endBinary(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeUtf8 (line 40) | static getRootAsLargeUtf8(s,a){return(a||new i).__init(s.readInt32(s.p...
    method startLargeUtf8 (line 40) | static startLargeUtf8(s){s.startObject(0)}
    method endLargeUtf8 (line 40) | static endLargeUtf8(s){return s.endObject()}
    method createLargeUtf8 (line 40) | static createLargeUtf8(s){return i.startLargeUtf8(s),i.endLargeUtf8(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeBinary (line 40) | static getRootAsLargeBinary(s,a){return(a||new i).__init(s.readInt32(s...
    method startLargeBinary (line 40) | static startLargeBinary(s){s.startObject(0)}
    method endLargeBinary (line 40) | static endLargeBinary(s){return s.endObject()}
    method createLargeBinary (line 40) | static createLargeBinary(s){return i.startLargeBinary(s),i.endLargeBin...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFixedSizeBinary (line 40) | static getRootAsFixedSizeBinary(s,a){return(a||new i).__init(s.readInt...
    method byteWidth (line 40) | byteWidth(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method startFixedSizeBinary (line 40) | static startFixedSizeBinary(s){s.startObject(1)}
    method addByteWidth (line 40) | static addByteWidth(s,a){s.addFieldInt32(0,a,0)}
    method endFixedSizeBinary (line 40) | static endFixedSizeBinary(s){return s.endObject()}
    method createFixedSizeBinary (line 40) | static createFixedSizeBinary(s,a){return i.startFixedSizeBinary(s),i.a...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsBool (line 40) | static getRootAsBool(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startBool (line 40) | static startBool(s){s.startObject(0)}
    method endBool (line 40) | static endBool(s){return s.endObject()}
    method createBool (line 40) | static createBool(s){return i.startBool(s),i.endBool(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDecimal (line 40) | static getRootAsDecimal(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method precision (line 40) | precision(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method scale (line 40) | scale(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.readInt...
    method startDecimal (line 40) | static startDecimal(s){s.startObject(2)}
    method addPrecision (line 40) | static addPrecision(s,a){s.addFieldInt32(0,a,0)}
    method addScale (line 40) | static addScale(s,a){s.addFieldInt32(1,a,0)}
    method endDecimal (line 40) | static endDecimal(s){return s.endObject()}
    method createDecimal (line 40) | static createDecimal(s,a,c){return i.startDecimal(s),i.addPrecision(s,...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDate (line 40) | static getRootAsDate(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startDate (line 40) | static startDate(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.DateUni...
    method endDate (line 40) | static endDate(s){return s.endObject()}
    method createDate (line 40) | static createDate(s,a){return i.startDate(s),i.addUnit(s,a),i.endDate(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsTime (line 40) | static getRootAsTime(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method bitWidth (line 40) | bitWidth(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.read...
    method startTime (line 40) | static startTime(s){s.startObject(2)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method addBitWidth (line 40) | static addBitWidth(s,a){s.addFieldInt32(1,a,32)}
    method endTime (line 40) | static endTime(s){return s.endObject()}
    method createTime (line 40) | static createTime(s,a,c){return i.startTime(s),i.addUnit(s,a),i.addBit...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsTimestamp (line 40) | static getRootAsTimestamp(s,a){return(a||new i).__init(s.readInt32(s.p...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method timezone (line 40) | timezone(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.__s...
    method startTimestamp (line 40) | static startTimestamp(s){s.startObject(2)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method addTimezone (line 40) | static addTimezone(s,a){s.addFieldOffset(1,a,0)}
    method endTimestamp (line 40) | static endTimestamp(s){return s.endObject()}
    method createTimestamp (line 40) | static createTimestamp(s,a,c){return i.startTimestamp(s),i.addUnit(s,a...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsInterval (line 40) | static getRootAsInterval(s,a){return(a||new i).__init(s.readInt32(s.po...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startInterval (line 40) | static startInterval(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.Interva...
    method endInterval (line 40) | static endInterval(s){return s.endObject()}
    method createInterval (line 40) | static createInterval(s,a){return i.startInterval(s),i.addUnit(s,a),i....
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDuration (line 40) | static getRootAsDuration(s,a){return(a||new i).__init(s.readInt32(s.po...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startDuration (line 40) | static startDuration(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method endDuration (line 40) | static endDuration(s){return s.endObject()}
    method createDuration (line 40) | static createDuration(s,a){return i.startDuration(s),i.addUnit(s,a),i....
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsKeyValue (line 40) | static getRootAsKeyValue(s,a){return(a||new i).__init(s.readInt32(s.po...
    method key (line 40) | key(s){let a=this.bb.__offset(this.bb_pos,4);return a?this.bb.__string...
    method value (line 40) | value(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.__stri...
    method startKeyValue (line 40) | static startKeyValue(s){s.startObject(2)}
    method addKey (line 40) | static addKey(s,a){s.addFieldOffset(0,a,0)}
    method addValue (line 40) | static addValue(s,a){s.addFieldOffset(1,a,0)}
    method endKeyValue (line 40) | static endKeyValue(s){return s.endObject()}
    method createKeyValue (line 40) | static createKeyValue(s,a,c){return i.startKeyValue(s),i.addKey(s,a),i...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDictionaryEncoding (line 40) | static getRootAsDictionaryEncoding(s,a){return(a||new i).__init(s.read...
    method id (line 40) | id(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt64(...
    method indexType (line 40) | indexType(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new e....
    method isOrdered (line 40) | isOrdered(){let s=this.bb.__offset(this.bb_pos,8);return s?!!this.bb.r...
    method startDictionaryEncoding (line 40) | static startDictionaryEncoding(s){s.startObject(3)}
    method addId (line 40) | static addId(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addIndexType (line 40) | static addIndexType(s,a){s.addFieldOffset(1,a,0)}
    method addIsOrdered (line 40) | static addIsOrdered(s,a){s.addFieldInt8(2,+a,0)}
    method endDictionaryEncoding (line 40) | static endDictionaryEncoding(s){return s.endObject()}
    method createDictionaryEncoding (line 40) | static createDictionaryEncoding(s,a,c,l){return i.startDictionaryEncod...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsField (line 40) | static getRootAsField(s,a){return(a||new i).__init(s.readInt32(s.posit...
    method name (line 40) | name(s){let a=this.bb.__offset(this.bb_pos,4);return a?this.bb.__strin...
    method nullable (line 40) | nullable(){let s=this.bb.__offset(this.bb_pos,6);return s?!!this.bb.re...
    method typeType (line 40) | typeType(){let s=this.bb.__offset(this.bb_pos,8);return s?this.bb.read...
    method type (line 40) | type(s){let a=this.bb.__offset(this.bb_pos,10);return a?this.bb.__unio...
    method dictionary (line 40) | dictionary(s){let a=this.bb.__offset(this.bb_pos,12);return a?(s||new ...
    method children (line 40) | children(s,a){let c=this.bb.__offset(this.bb_pos,14);return c?(a||new ...
    method childrenLength (line 40) | childrenLength(){let s=this.bb.__offset(this.bb_pos,14);return s?this....
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,16);return c?(a...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,16);return s...
    method startField (line 40) | static startField(s){s.startObject(7)}
    method addName (line 40) | static addName(s,a){s.addFieldOffset(0,a,0)}
    method addNullable (line 40) | static addNullable(s,a){s.addFieldInt8(1,+a,0)}
    method addTypeType (line 40) | static addTypeType(s,a){s.addFieldInt8(2,a,e.apache.arrow.flatbuf.Type...
    method addType (line 40) | static addType(s,a){s.addFieldOffset(3,a,0)}
    method addDictionary (line 40) | static addDictionary(s,a){s.addFieldOffset(4,a,0)}
    method addChildren (line 40) | static addChildren(s,a){s.addFieldOffset(5,a,0)}
    method createChildrenVector (line 40) | static createChildrenVector(s,a){s.startVector(4,a.length,4);for(let c...
    method startChildrenVector (line 40) | static startChildrenVector(s,a){s.startVector(4,a,4)}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(6,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endField (line 40) | static endField(s){return s.endObject()}
    method createField (line 40) | static createField(s,a,c,l,d,p,_,O){return i.startField(s),i.addName(s...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method offset (line 40) | offset(){return this.bb.readInt64(this.bb_pos)}
    method length (line 40) | length(){return this.bb.readInt64(this.bb_pos+8)}
    method createBuffer (line 40) | static createBuffer(s,a,c){return s.prep(8,16),s.writeInt64(c),s.write...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsSchema (line 40) | static getRootAsSchema(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method endianness (line 40) | endianness(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.re...
    method fields (line 40) | fields(s,a){let c=this.bb.__offset(this.bb_pos,6);return c?(a||new e.a...
    method fieldsLength (line 40) | fieldsLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb....
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a|...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,8);return s?...
    method startSchema (line 40) | static startSchema(s){s.startObject(3)}
    method addEndianness (line 40) | static addEndianness(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.E...
    method addFields (line 40) | static addFields(s,a){s.addFieldOffset(1,a,0)}
    method createFieldsVector (line 40) | static createFieldsVector(s,a){s.startVector(4,a.length,4);for(let c=a...
    method startFieldsVector (line 40) | static startFieldsVector(s,a){s.startVector(4,a,4)}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(2,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endSchema (line 40) | static endSchema(s){return s.endObject()}
    method finishSchemaBuffer (line 40) | static finishSchemaBuffer(s,a){s.finish(a)}
    method createSchema (line 40) | static createSchema(s,a,c,l){return i.startSchema(s),i.addEndianness(s...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method length (line 40) | length(){return this.bb.readInt64(this.bb_pos)}
    method nullCount (line 40) | nullCount(){return this.bb.readInt64(this.bb_pos+8)}
    method createFieldNode (line 40) | static createFieldNode(s,a,c){return s.prep(8,16),s.writeInt64(c),s.wr...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsRecordBatch (line 40) | static getRootAsRecordBatch(s,a){return(a||new i).__init(s.readInt32(s...
    method length (line 40) | length(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readIn...
    method nodes (line 40) | nodes(s,a){let c=this.bb.__offset(this.bb_pos,6);return c?(a||new e.ap...
    method nodesLength (line 40) | nodesLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb._...
    method buffers (line 40) | buffers(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a||new v....
    method buffersLength (line 40) | buffersLength(){let s=this.bb.__offset(this.bb_pos,8);return s?this.bb...
    method startRecordBatch (line 40) | static startRecordBatch(s){s.startObject(3)}
    method addLength (line 40) | static addLength(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addNodes (line 40) | static addNodes(s,a){s.addFieldOffset(1,a,0)}
    method startNodesVector (line 40) | static startNodesVector(s,a){s.startVector(16,a,8)}
    method addBuffers (line 40) | static addBuffers(s,a){s.addFieldOffset(2,a,0)}
    method startBuffersVector (line 40) | static startBuffersVector(s,a){s.startVector(16,a,8)}
    method endRecordBatch (line 40) | static endRecordBatch(s){return s.endObject()}
    method createRecordBatch (line 40) | static createRecordBatch(s,a,c,l){return i.startRecordBatch(s),i.addLe...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDictionaryBatch (line 40) | static getRootAsDictionaryBatch(s,a){return(a||new i).__init(s.readInt...
    method id (line 40) | id(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt64(...
    method data (line 40) | data(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new e.apach...
    method isDelta (line 40) | isDelta(){let s=this.bb.__offset(this.bb_pos,8);return s?!!this.bb.rea...
    method startDictionaryBatch (line 40) | static startDictionaryBatch(s){s.startObject(3)}
    method addId (line 40) | static addId(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addData (line 40) | static addData(s,a){s.addFieldOffset(1,a,0)}
    method addIsDelta (line 40) | static addIsDelta(s,a){s.addFieldInt8(2,+a,0)}
    method endDictionaryBatch (line 40) | static endDictionaryBatch(s){return s.endObject()}
    method createDictionaryBatch (line 40) | static createDictionaryBatch(s,a,c,l){return i.startDictionaryBatch(s)...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsMessage (line 40) | static getRootAsMessage(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method version (line 40) | version(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readI...
    method headerType (line 40) | headerType(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.re...
    method header (line 40) | header(s){let a=this.bb.__offset(this.bb_pos,8);return a?this.bb.__uni...
    method bodyLength (line 40) | bodyLength(){let s=this.bb.__offset(this.bb_pos,10);return s?this.bb.r...
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,12);return c?(a...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,12);return s...
    method startMessage (line 40) | static startMessage(s){s.startObject(5)}
    method addVersion (line 40) | static addVersion(s,a){s.addFieldInt16(0,a,v.apache.arrow.flatbuf.Meta...
    method addHeaderType (line 40) | static addHeaderType(s,a){s.addFieldInt8(1,a,e.apache.arrow.flatbuf.Me...
    method addHeader (line 40) | static addHeader(s,a){s.addFieldOffset(2,a,0)}
    method addBodyLength (line 40) | static addBodyLength(s,a){s.addFieldInt64(3,a,s.createLong(0,0))}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(4,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endMessage (line 40) | static endMessage(s){return s.endObject()}
    method finishMessageBuffer (line 40) | static finishMessageBuffer(s,a){s.finish(a)}
    method createMessage (line 40) | static createMessage(s,a,c,l,d,p){return i.startMessage(s),i.addVersio...
    method constructor (line 46) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 46) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFooter (line 46) | static getRootAsFooter(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method version (line 46) | version(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readI...
    method schema (line 46) | schema(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new v.apa...
    method dictionaries (line 46) | dictionaries(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a||n...
    method dictionariesLength (line 46) | dictionariesLength(){let s=this.bb.__offset(this.bb_pos,8);return s?th...
    method recordBatches (line 46) | recordBatches(s,a){let c=this.bb.__offset(this.bb_pos,10);return c?(a|...
    method recordBatchesLength (line 46) | recordBatchesLength(){let s=this.bb.__offset(this.bb_pos,10);return s?...
    method startFooter (line 46) | static startFooter(s){s.startObject(4)}
    method addVersion (line 46) | static addVersion(s,a){s.addFieldInt16(0,a,v.apache.arrow.flatbuf.Meta...
    method addSchema (line 46) | static addSchema(s,a){s.addFieldOffset(1,a,0)}
    method addDictionaries (line 46) | static addDictionaries(s,a){s.addFieldOffset(2,a,0)}
    method startDictionariesVector (line 46) | static startDictionariesVector(s,a){s.startVector(24,a,8)}
    method addRecordBatches (line 46) | static addRecordBatches(s,a){s.addFieldOffset(3,a,0)}
    method startRecordBatchesVector (line 46) | static startRecordBatchesVector(s,a){s.startVector(24,a,8)}
    method endFooter (line 46) | static endFooter(s){return s.endObject()}
    method finishFooterBuffer (line 46) | static finishFooterBuffer(s,a){s.finish(a)}
    method createFooter (line 46) | static createFooter(s,a,c,l,d){return i.startFooter(s),i.addVersion(s,...
    method constructor (line 46) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 46) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method offset (line 46) | offset(){return this.bb.readInt64(this.bb_pos)}
    method metaDataLength (line 46) | metaDataLength(){return this.bb.readInt32(this.bb_pos+8)}
    method bodyLength (line 46) | bodyLength(){return this.bb.readInt64(this.bb_pos+16)}
    method createBlock (line 46) | static createBlock(s,a,c,l){return s.prep(8,24),s.writeInt64(l),s.pad(...
  class i (line 40) | class i{constructor(){this.bb=null,this.bb_pos=0}__init(s,a){return this...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsNull (line 40) | static getRootAsNull(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startNull (line 40) | static startNull(s){s.startObject(0)}
    method endNull (line 40) | static endNull(s){return s.endObject()}
    method createNull (line 40) | static createNull(s){return i.startNull(s),i.endNull(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsStruct_ (line 40) | static getRootAsStruct_(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method startStruct_ (line 40) | static startStruct_(s){s.startObject(0)}
    method endStruct_ (line 40) | static endStruct_(s){return s.endObject()}
    method createStruct_ (line 40) | static createStruct_(s){return i.startStruct_(s),i.endStruct_(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsList (line 40) | static getRootAsList(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startList (line 40) | static startList(s){s.startObject(0)}
    method endList (line 40) | static endList(s){return s.endObject()}
    method createList (line 40) | static createList(s){return i.startList(s),i.endList(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeList (line 40) | static getRootAsLargeList(s,a){return(a||new i).__init(s.readInt32(s.p...
    method startLargeList (line 40) | static startLargeList(s){s.startObject(0)}
    method endLargeList (line 40) | static endLargeList(s){return s.endObject()}
    method createLargeList (line 40) | static createLargeList(s){return i.startLargeList(s),i.endLargeList(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFixedSizeList (line 40) | static getRootAsFixedSizeList(s,a){return(a||new i).__init(s.readInt32...
    method listSize (line 40) | listSize(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.read...
    method startFixedSizeList (line 40) | static startFixedSizeList(s){s.startObject(1)}
    method addListSize (line 40) | static addListSize(s,a){s.addFieldInt32(0,a,0)}
    method endFixedSizeList (line 40) | static endFixedSizeList(s){return s.endObject()}
    method createFixedSizeList (line 40) | static createFixedSizeList(s,a){return i.startFixedSizeList(s),i.addLi...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsMap (line 40) | static getRootAsMap(s,a){return(a||new i).__init(s.readInt32(s.positio...
    method keysSorted (line 40) | keysSorted(){let s=this.bb.__offset(this.bb_pos,4);return s?!!this.bb....
    method startMap (line 40) | static startMap(s){s.startObject(1)}
    method addKeysSorted (line 40) | static addKeysSorted(s,a){s.addFieldInt8(0,+a,0)}
    method endMap (line 40) | static endMap(s){return s.endObject()}
    method createMap (line 40) | static createMap(s,a){return i.startMap(s),i.addKeysSorted(s,a),i.endM...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsUnion (line 40) | static getRootAsUnion(s,a){return(a||new i).__init(s.readInt32(s.posit...
    method mode (line 40) | mode(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method typeIds (line 40) | typeIds(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.read...
    method typeIdsLength (line 40) | typeIdsLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb...
    method typeIdsArray (line 40) | typeIdsArray(){let s=this.bb.__offset(this.bb_pos,6);return s?new Int3...
    method startUnion (line 40) | static startUnion(s){s.startObject(2)}
    method addMode (line 40) | static addMode(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.UnionMo...
    method addTypeIds (line 40) | static addTypeIds(s,a){s.addFieldOffset(1,a,0)}
    method createTypeIdsVector (line 40) | static createTypeIdsVector(s,a){s.startVector(4,a.length,4);for(let c=...
    method startTypeIdsVector (line 40) | static startTypeIdsVector(s,a){s.startVector(4,a,4)}
    method endUnion (line 40) | static endUnion(s){return s.endObject()}
    method createUnion (line 40) | static createUnion(s,a,c){return i.startUnion(s),i.addMode(s,a),i.addT...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsInt (line 40) | static getRootAsInt(s,a){return(a||new i).__init(s.readInt32(s.positio...
    method bitWidth (line 40) | bitWidth(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.read...
    method isSigned (line 40) | isSigned(){let s=this.bb.__offset(this.bb_pos,6);return s?!!this.bb.re...
    method startInt (line 40) | static startInt(s){s.startObject(2)}
    method addBitWidth (line 40) | static addBitWidth(s,a){s.addFieldInt32(0,a,0)}
    method addIsSigned (line 40) | static addIsSigned(s,a){s.addFieldInt8(1,+a,0)}
    method endInt (line 40) | static endInt(s){return s.endObject()}
    method createInt (line 40) | static createInt(s,a,c){return i.startInt(s),i.addBitWidth(s,a),i.addI...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFloatingPoint (line 40) | static getRootAsFloatingPoint(s,a){return(a||new i).__init(s.readInt32...
    method precision (line 40) | precision(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method startFloatingPoint (line 40) | static startFloatingPoint(s){s.startObject(1)}
    method addPrecision (line 40) | static addPrecision(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.Pr...
    method endFloatingPoint (line 40) | static endFloatingPoint(s){return s.endObject()}
    method createFloatingPoint (line 40) | static createFloatingPoint(s,a){return i.startFloatingPoint(s),i.addPr...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsUtf8 (line 40) | static getRootAsUtf8(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startUtf8 (line 40) | static startUtf8(s){s.startObject(0)}
    method endUtf8 (line 40) | static endUtf8(s){return s.endObject()}
    method createUtf8 (line 40) | static createUtf8(s){return i.startUtf8(s),i.endUtf8(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsBinary (line 40) | static getRootAsBinary(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method startBinary (line 40) | static startBinary(s){s.startObject(0)}
    method endBinary (line 40) | static endBinary(s){return s.endObject()}
    method createBinary (line 40) | static createBinary(s){return i.startBinary(s),i.endBinary(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeUtf8 (line 40) | static getRootAsLargeUtf8(s,a){return(a||new i).__init(s.readInt32(s.p...
    method startLargeUtf8 (line 40) | static startLargeUtf8(s){s.startObject(0)}
    method endLargeUtf8 (line 40) | static endLargeUtf8(s){return s.endObject()}
    method createLargeUtf8 (line 40) | static createLargeUtf8(s){return i.startLargeUtf8(s),i.endLargeUtf8(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeBinary (line 40) | static getRootAsLargeBinary(s,a){return(a||new i).__init(s.readInt32(s...
    method startLargeBinary (line 40) | static startLargeBinary(s){s.startObject(0)}
    method endLargeBinary (line 40) | static endLargeBinary(s){return s.endObject()}
    method createLargeBinary (line 40) | static createLargeBinary(s){return i.startLargeBinary(s),i.endLargeBin...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFixedSizeBinary (line 40) | static getRootAsFixedSizeBinary(s,a){return(a||new i).__init(s.readInt...
    method byteWidth (line 40) | byteWidth(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method startFixedSizeBinary (line 40) | static startFixedSizeBinary(s){s.startObject(1)}
    method addByteWidth (line 40) | static addByteWidth(s,a){s.addFieldInt32(0,a,0)}
    method endFixedSizeBinary (line 40) | static endFixedSizeBinary(s){return s.endObject()}
    method createFixedSizeBinary (line 40) | static createFixedSizeBinary(s,a){return i.startFixedSizeBinary(s),i.a...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsBool (line 40) | static getRootAsBool(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startBool (line 40) | static startBool(s){s.startObject(0)}
    method endBool (line 40) | static endBool(s){return s.endObject()}
    method createBool (line 40) | static createBool(s){return i.startBool(s),i.endBool(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDecimal (line 40) | static getRootAsDecimal(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method precision (line 40) | precision(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method scale (line 40) | scale(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.readInt...
    method startDecimal (line 40) | static startDecimal(s){s.startObject(2)}
    method addPrecision (line 40) | static addPrecision(s,a){s.addFieldInt32(0,a,0)}
    method addScale (line 40) | static addScale(s,a){s.addFieldInt32(1,a,0)}
    method endDecimal (line 40) | static endDecimal(s){return s.endObject()}
    method createDecimal (line 40) | static createDecimal(s,a,c){return i.startDecimal(s),i.addPrecision(s,...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDate (line 40) | static getRootAsDate(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startDate (line 40) | static startDate(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.DateUni...
    method endDate (line 40) | static endDate(s){return s.endObject()}
    method createDate (line 40) | static createDate(s,a){return i.startDate(s),i.addUnit(s,a),i.endDate(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsTime (line 40) | static getRootAsTime(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method bitWidth (line 40) | bitWidth(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.read...
    method startTime (line 40) | static startTime(s){s.startObject(2)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method addBitWidth (line 40) | static addBitWidth(s,a){s.addFieldInt32(1,a,32)}
    method endTime (line 40) | static endTime(s){return s.endObject()}
    method createTime (line 40) | static createTime(s,a,c){return i.startTime(s),i.addUnit(s,a),i.addBit...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsTimestamp (line 40) | static getRootAsTimestamp(s,a){return(a||new i).__init(s.readInt32(s.p...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method timezone (line 40) | timezone(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.__s...
    method startTimestamp (line 40) | static startTimestamp(s){s.startObject(2)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method addTimezone (line 40) | static addTimezone(s,a){s.addFieldOffset(1,a,0)}
    method endTimestamp (line 40) | static endTimestamp(s){return s.endObject()}
    method createTimestamp (line 40) | static createTimestamp(s,a,c){return i.startTimestamp(s),i.addUnit(s,a...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsInterval (line 40) | static getRootAsInterval(s,a){return(a||new i).__init(s.readInt32(s.po...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startInterval (line 40) | static startInterval(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.Interva...
    method endInterval (line 40) | static endInterval(s){return s.endObject()}
    method createInterval (line 40) | static createInterval(s,a){return i.startInterval(s),i.addUnit(s,a),i....
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDuration (line 40) | static getRootAsDuration(s,a){return(a||new i).__init(s.readInt32(s.po...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startDuration (line 40) | static startDuration(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method endDuration (line 40) | static endDuration(s){return s.endObject()}
    method createDuration (line 40) | static createDuration(s,a){return i.startDuration(s),i.addUnit(s,a),i....
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsKeyValue (line 40) | static getRootAsKeyValue(s,a){return(a||new i).__init(s.readInt32(s.po...
    method key (line 40) | key(s){let a=this.bb.__offset(this.bb_pos,4);return a?this.bb.__string...
    method value (line 40) | value(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.__stri...
    method startKeyValue (line 40) | static startKeyValue(s){s.startObject(2)}
    method addKey (line 40) | static addKey(s,a){s.addFieldOffset(0,a,0)}
    method addValue (line 40) | static addValue(s,a){s.addFieldOffset(1,a,0)}
    method endKeyValue (line 40) | static endKeyValue(s){return s.endObject()}
    method createKeyValue (line 40) | static createKeyValue(s,a,c){return i.startKeyValue(s),i.addKey(s,a),i...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDictionaryEncoding (line 40) | static getRootAsDictionaryEncoding(s,a){return(a||new i).__init(s.read...
    method id (line 40) | id(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt64(...
    method indexType (line 40) | indexType(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new e....
    method isOrdered (line 40) | isOrdered(){let s=this.bb.__offset(this.bb_pos,8);return s?!!this.bb.r...
    method startDictionaryEncoding (line 40) | static startDictionaryEncoding(s){s.startObject(3)}
    method addId (line 40) | static addId(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addIndexType (line 40) | static addIndexType(s,a){s.addFieldOffset(1,a,0)}
    method addIsOrdered (line 40) | static addIsOrdered(s,a){s.addFieldInt8(2,+a,0)}
    method endDictionaryEncoding (line 40) | static endDictionaryEncoding(s){return s.endObject()}
    method createDictionaryEncoding (line 40) | static createDictionaryEncoding(s,a,c,l){return i.startDictionaryEncod...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsField (line 40) | static getRootAsField(s,a){return(a||new i).__init(s.readInt32(s.posit...
    method name (line 40) | name(s){let a=this.bb.__offset(this.bb_pos,4);return a?this.bb.__strin...
    method nullable (line 40) | nullable(){let s=this.bb.__offset(this.bb_pos,6);return s?!!this.bb.re...
    method typeType (line 40) | typeType(){let s=this.bb.__offset(this.bb_pos,8);return s?this.bb.read...
    method type (line 40) | type(s){let a=this.bb.__offset(this.bb_pos,10);return a?this.bb.__unio...
    method dictionary (line 40) | dictionary(s){let a=this.bb.__offset(this.bb_pos,12);return a?(s||new ...
    method children (line 40) | children(s,a){let c=this.bb.__offset(this.bb_pos,14);return c?(a||new ...
    method childrenLength (line 40) | childrenLength(){let s=this.bb.__offset(this.bb_pos,14);return s?this....
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,16);return c?(a...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,16);return s...
    method startField (line 40) | static startField(s){s.startObject(7)}
    method addName (line 40) | static addName(s,a){s.addFieldOffset(0,a,0)}
    method addNullable (line 40) | static addNullable(s,a){s.addFieldInt8(1,+a,0)}
    method addTypeType (line 40) | static addTypeType(s,a){s.addFieldInt8(2,a,e.apache.arrow.flatbuf.Type...
    method addType (line 40) | static addType(s,a){s.addFieldOffset(3,a,0)}
    method addDictionary (line 40) | static addDictionary(s,a){s.addFieldOffset(4,a,0)}
    method addChildren (line 40) | static addChildren(s,a){s.addFieldOffset(5,a,0)}
    method createChildrenVector (line 40) | static createChildrenVector(s,a){s.startVector(4,a.length,4);for(let c...
    method startChildrenVector (line 40) | static startChildrenVector(s,a){s.startVector(4,a,4)}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(6,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endField (line 40) | static endField(s){return s.endObject()}
    method createField (line 40) | static createField(s,a,c,l,d,p,_,O){return i.startField(s),i.addName(s...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method offset (line 40) | offset(){return this.bb.readInt64(this.bb_pos)}
    method length (line 40) | length(){return this.bb.readInt64(this.bb_pos+8)}
    method createBuffer (line 40) | static createBuffer(s,a,c){return s.prep(8,16),s.writeInt64(c),s.write...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsSchema (line 40) | static getRootAsSchema(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method endianness (line 40) | endianness(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.re...
    method fields (line 40) | fields(s,a){let c=this.bb.__offset(this.bb_pos,6);return c?(a||new e.a...
    method fieldsLength (line 40) | fieldsLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb....
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a|...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,8);return s?...
    method startSchema (line 40) | static startSchema(s){s.startObject(3)}
    method addEndianness (line 40) | static addEndianness(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.E...
    method addFields (line 40) | static addFields(s,a){s.addFieldOffset(1,a,0)}
    method createFieldsVector (line 40) | static createFieldsVector(s,a){s.startVector(4,a.length,4);for(let c=a...
    method startFieldsVector (line 40) | static startFieldsVector(s,a){s.startVector(4,a,4)}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(2,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endSchema (line 40) | static endSchema(s){return s.endObject()}
    method finishSchemaBuffer (line 40) | static finishSchemaBuffer(s,a){s.finish(a)}
    method createSchema (line 40) | static createSchema(s,a,c,l){return i.startSchema(s),i.addEndianness(s...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method length (line 40) | length(){return this.bb.readInt64(this.bb_pos)}
    method nullCount (line 40) | nullCount(){return this.bb.readInt64(this.bb_pos+8)}
    method createFieldNode (line 40) | static createFieldNode(s,a,c){return s.prep(8,16),s.writeInt64(c),s.wr...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsRecordBatch (line 40) | static getRootAsRecordBatch(s,a){return(a||new i).__init(s.readInt32(s...
    method length (line 40) | length(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readIn...
    method nodes (line 40) | nodes(s,a){let c=this.bb.__offset(this.bb_pos,6);return c?(a||new e.ap...
    method nodesLength (line 40) | nodesLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb._...
    method buffers (line 40) | buffers(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a||new v....
    method buffersLength (line 40) | buffersLength(){let s=this.bb.__offset(this.bb_pos,8);return s?this.bb...
    method startRecordBatch (line 40) | static startRecordBatch(s){s.startObject(3)}
    method addLength (line 40) | static addLength(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addNodes (line 40) | static addNodes(s,a){s.addFieldOffset(1,a,0)}
    method startNodesVector (line 40) | static startNodesVector(s,a){s.startVector(16,a,8)}
    method addBuffers (line 40) | static addBuffers(s,a){s.addFieldOffset(2,a,0)}
    method startBuffersVector (line 40) | static startBuffersVector(s,a){s.startVector(16,a,8)}
    method endRecordBatch (line 40) | static endRecordBatch(s){return s.endObject()}
    method createRecordBatch (line 40) | static createRecordBatch(s,a,c,l){return i.startRecordBatch(s),i.addLe...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDictionaryBatch (line 40) | static getRootAsDictionaryBatch(s,a){return(a||new i).__init(s.readInt...
    method id (line 40) | id(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt64(...
    method data (line 40) | data(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new e.apach...
    method isDelta (line 40) | isDelta(){let s=this.bb.__offset(this.bb_pos,8);return s?!!this.bb.rea...
    method startDictionaryBatch (line 40) | static startDictionaryBatch(s){s.startObject(3)}
    method addId (line 40) | static addId(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addData (line 40) | static addData(s,a){s.addFieldOffset(1,a,0)}
    method addIsDelta (line 40) | static addIsDelta(s,a){s.addFieldInt8(2,+a,0)}
    method endDictionaryBatch (line 40) | static endDictionaryBatch(s){return s.endObject()}
    method createDictionaryBatch (line 40) | static createDictionaryBatch(s,a,c,l){return i.startDictionaryBatch(s)...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsMessage (line 40) | static getRootAsMessage(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method version (line 40) | version(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readI...
    method headerType (line 40) | headerType(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.re...
    method header (line 40) | header(s){let a=this.bb.__offset(this.bb_pos,8);return a?this.bb.__uni...
    method bodyLength (line 40) | bodyLength(){let s=this.bb.__offset(this.bb_pos,10);return s?this.bb.r...
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,12);return c?(a...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,12);return s...
    method startMessage (line 40) | static startMessage(s){s.startObject(5)}
    method addVersion (line 40) | static addVersion(s,a){s.addFieldInt16(0,a,v.apache.arrow.flatbuf.Meta...
    method addHeaderType (line 40) | static addHeaderType(s,a){s.addFieldInt8(1,a,e.apache.arrow.flatbuf.Me...
    method addHeader (line 40) | static addHeader(s,a){s.addFieldOffset(2,a,0)}
    method addBodyLength (line 40) | static addBodyLength(s,a){s.addFieldInt64(3,a,s.createLong(0,0))}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(4,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endMessage (line 40) | static endMessage(s){return s.endObject()}
    method finishMessageBuffer (line 40) | static finishMessageBuffer(s,a){s.finish(a)}
    method createMessage (line 40) | static createMessage(s,a,c,l,d,p){return i.startMessage(s),i.addVersio...
    method constructor (line 46) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 46) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFooter (line 46) | static getRootAsFooter(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method version (line 46) | version(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readI...
    method schema (line 46) | schema(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new v.apa...
    method dictionaries (line 46) | dictionaries(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a||n...
    method dictionariesLength (line 46) | dictionariesLength(){let s=this.bb.__offset(this.bb_pos,8);return s?th...
    method recordBatches (line 46) | recordBatches(s,a){let c=this.bb.__offset(this.bb_pos,10);return c?(a|...
    method recordBatchesLength (line 46) | recordBatchesLength(){let s=this.bb.__offset(this.bb_pos,10);return s?...
    method startFooter (line 46) | static startFooter(s){s.startObject(4)}
    method addVersion (line 46) | static addVersion(s,a){s.addFieldInt16(0,a,v.apache.arrow.flatbuf.Meta...
    method addSchema (line 46) | static addSchema(s,a){s.addFieldOffset(1,a,0)}
    method addDictionaries (line 46) | static addDictionaries(s,a){s.addFieldOffset(2,a,0)}
    method startDictionariesVector (line 46) | static startDictionariesVector(s,a){s.startVector(24,a,8)}
    method addRecordBatches (line 46) | static addRecordBatches(s,a){s.addFieldOffset(3,a,0)}
    method startRecordBatchesVector (line 46) | static startRecordBatchesVector(s,a){s.startVector(24,a,8)}
    method endFooter (line 46) | static endFooter(s){return s.endObject()}
    method finishFooterBuffer (line 46) | static finishFooterBuffer(s,a){s.finish(a)}
    method createFooter (line 46) | static createFooter(s,a,c,l,d){return i.startFooter(s),i.addVersion(s,...
    method constructor (line 46) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 46) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method offset (line 46) | offset(){return this.bb.readInt64(this.bb_pos)}
    method metaDataLength (line 46) | metaDataLength(){return this.bb.readInt32(this.bb_pos+8)}
    method bodyLength (line 46) | bodyLength(){return this.bb.readInt64(this.bb_pos+16)}
    method createBlock (line 46) | static createBlock(s,a,c,l){return s.prep(8,24),s.writeInt64(l),s.pad(...
  class i (line 40) | class i{constructor(){this.bb=null,this.bb_pos=0}__init(s,a){return this...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsNull (line 40) | static getRootAsNull(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startNull (line 40) | static startNull(s){s.startObject(0)}
    method endNull (line 40) | static endNull(s){return s.endObject()}
    method createNull (line 40) | static createNull(s){return i.startNull(s),i.endNull(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsStruct_ (line 40) | static getRootAsStruct_(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method startStruct_ (line 40) | static startStruct_(s){s.startObject(0)}
    method endStruct_ (line 40) | static endStruct_(s){return s.endObject()}
    method createStruct_ (line 40) | static createStruct_(s){return i.startStruct_(s),i.endStruct_(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsList (line 40) | static getRootAsList(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startList (line 40) | static startList(s){s.startObject(0)}
    method endList (line 40) | static endList(s){return s.endObject()}
    method createList (line 40) | static createList(s){return i.startList(s),i.endList(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeList (line 40) | static getRootAsLargeList(s,a){return(a||new i).__init(s.readInt32(s.p...
    method startLargeList (line 40) | static startLargeList(s){s.startObject(0)}
    method endLargeList (line 40) | static endLargeList(s){return s.endObject()}
    method createLargeList (line 40) | static createLargeList(s){return i.startLargeList(s),i.endLargeList(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFixedSizeList (line 40) | static getRootAsFixedSizeList(s,a){return(a||new i).__init(s.readInt32...
    method listSize (line 40) | listSize(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.read...
    method startFixedSizeList (line 40) | static startFixedSizeList(s){s.startObject(1)}
    method addListSize (line 40) | static addListSize(s,a){s.addFieldInt32(0,a,0)}
    method endFixedSizeList (line 40) | static endFixedSizeList(s){return s.endObject()}
    method createFixedSizeList (line 40) | static createFixedSizeList(s,a){return i.startFixedSizeList(s),i.addLi...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsMap (line 40) | static getRootAsMap(s,a){return(a||new i).__init(s.readInt32(s.positio...
    method keysSorted (line 40) | keysSorted(){let s=this.bb.__offset(this.bb_pos,4);return s?!!this.bb....
    method startMap (line 40) | static startMap(s){s.startObject(1)}
    method addKeysSorted (line 40) | static addKeysSorted(s,a){s.addFieldInt8(0,+a,0)}
    method endMap (line 40) | static endMap(s){return s.endObject()}
    method createMap (line 40) | static createMap(s,a){return i.startMap(s),i.addKeysSorted(s,a),i.endM...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsUnion (line 40) | static getRootAsUnion(s,a){return(a||new i).__init(s.readInt32(s.posit...
    method mode (line 40) | mode(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method typeIds (line 40) | typeIds(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.read...
    method typeIdsLength (line 40) | typeIdsLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb...
    method typeIdsArray (line 40) | typeIdsArray(){let s=this.bb.__offset(this.bb_pos,6);return s?new Int3...
    method startUnion (line 40) | static startUnion(s){s.startObject(2)}
    method addMode (line 40) | static addMode(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.UnionMo...
    method addTypeIds (line 40) | static addTypeIds(s,a){s.addFieldOffset(1,a,0)}
    method createTypeIdsVector (line 40) | static createTypeIdsVector(s,a){s.startVector(4,a.length,4);for(let c=...
    method startTypeIdsVector (line 40) | static startTypeIdsVector(s,a){s.startVector(4,a,4)}
    method endUnion (line 40) | static endUnion(s){return s.endObject()}
    method createUnion (line 40) | static createUnion(s,a,c){return i.startUnion(s),i.addMode(s,a),i.addT...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsInt (line 40) | static getRootAsInt(s,a){return(a||new i).__init(s.readInt32(s.positio...
    method bitWidth (line 40) | bitWidth(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.read...
    method isSigned (line 40) | isSigned(){let s=this.bb.__offset(this.bb_pos,6);return s?!!this.bb.re...
    method startInt (line 40) | static startInt(s){s.startObject(2)}
    method addBitWidth (line 40) | static addBitWidth(s,a){s.addFieldInt32(0,a,0)}
    method addIsSigned (line 40) | static addIsSigned(s,a){s.addFieldInt8(1,+a,0)}
    method endInt (line 40) | static endInt(s){return s.endObject()}
    method createInt (line 40) | static createInt(s,a,c){return i.startInt(s),i.addBitWidth(s,a),i.addI...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFloatingPoint (line 40) | static getRootAsFloatingPoint(s,a){return(a||new i).__init(s.readInt32...
    method precision (line 40) | precision(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method startFloatingPoint (line 40) | static startFloatingPoint(s){s.startObject(1)}
    method addPrecision (line 40) | static addPrecision(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.Pr...
    method endFloatingPoint (line 40) | static endFloatingPoint(s){return s.endObject()}
    method createFloatingPoint (line 40) | static createFloatingPoint(s,a){return i.startFloatingPoint(s),i.addPr...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsUtf8 (line 40) | static getRootAsUtf8(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startUtf8 (line 40) | static startUtf8(s){s.startObject(0)}
    method endUtf8 (line 40) | static endUtf8(s){return s.endObject()}
    method createUtf8 (line 40) | static createUtf8(s){return i.startUtf8(s),i.endUtf8(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsBinary (line 40) | static getRootAsBinary(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method startBinary (line 40) | static startBinary(s){s.startObject(0)}
    method endBinary (line 40) | static endBinary(s){return s.endObject()}
    method createBinary (line 40) | static createBinary(s){return i.startBinary(s),i.endBinary(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeUtf8 (line 40) | static getRootAsLargeUtf8(s,a){return(a||new i).__init(s.readInt32(s.p...
    method startLargeUtf8 (line 40) | static startLargeUtf8(s){s.startObject(0)}
    method endLargeUtf8 (line 40) | static endLargeUtf8(s){return s.endObject()}
    method createLargeUtf8 (line 40) | static createLargeUtf8(s){return i.startLargeUtf8(s),i.endLargeUtf8(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeBinary (line 40) | static getRootAsLargeBinary(s,a){return(a||new i).__init(s.readInt32(s...
    method startLargeBinary (line 40) | static startLargeBinary(s){s.startObject(0)}
    method endLargeBinary (line 40) | static endLargeBinary(s){return s.endObject()}
    method createLargeBinary (line 40) | static createLargeBinary(s){return i.startLargeBinary(s),i.endLargeBin...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFixedSizeBinary (line 40) | static getRootAsFixedSizeBinary(s,a){return(a||new i).__init(s.readInt...
    method byteWidth (line 40) | byteWidth(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method startFixedSizeBinary (line 40) | static startFixedSizeBinary(s){s.startObject(1)}
    method addByteWidth (line 40) | static addByteWidth(s,a){s.addFieldInt32(0,a,0)}
    method endFixedSizeBinary (line 40) | static endFixedSizeBinary(s){return s.endObject()}
    method createFixedSizeBinary (line 40) | static createFixedSizeBinary(s,a){return i.startFixedSizeBinary(s),i.a...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsBool (line 40) | static getRootAsBool(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startBool (line 40) | static startBool(s){s.startObject(0)}
    method endBool (line 40) | static endBool(s){return s.endObject()}
    method createBool (line 40) | static createBool(s){return i.startBool(s),i.endBool(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDecimal (line 40) | static getRootAsDecimal(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method precision (line 40) | precision(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method scale (line 40) | scale(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.readInt...
    method startDecimal (line 40) | static startDecimal(s){s.startObject(2)}
    method addPrecision (line 40) | static addPrecision(s,a){s.addFieldInt32(0,a,0)}
    method addScale (line 40) | static addScale(s,a){s.addFieldInt32(1,a,0)}
    method endDecimal (line 40) | static endDecimal(s){return s.endObject()}
    method createDecimal (line 40) | static createDecimal(s,a,c){return i.startDecimal(s),i.addPrecision(s,...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDate (line 40) | static getRootAsDate(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startDate (line 40) | static startDate(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.DateUni...
    method endDate (line 40) | static endDate(s){return s.endObject()}
    method createDate (line 40) | static createDate(s,a){return i.startDate(s),i.addUnit(s,a),i.endDate(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsTime (line 40) | static getRootAsTime(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method bitWidth (line 40) | bitWidth(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.read...
    method startTime (line 40) | static startTime(s){s.startObject(2)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method addBitWidth (line 40) | static addBitWidth(s,a){s.addFieldInt32(1,a,32)}
    method endTime (line 40) | static endTime(s){return s.endObject()}
    method createTime (line 40) | static createTime(s,a,c){return i.startTime(s),i.addUnit(s,a),i.addBit...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsTimestamp (line 40) | static getRootAsTimestamp(s,a){return(a||new i).__init(s.readInt32(s.p...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method timezone (line 40) | timezone(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.__s...
    method startTimestamp (line 40) | static startTimestamp(s){s.startObject(2)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method addTimezone (line 40) | static addTimezone(s,a){s.addFieldOffset(1,a,0)}
    method endTimestamp (line 40) | static endTimestamp(s){return s.endObject()}
    method createTimestamp (line 40) | static createTimestamp(s,a,c){return i.startTimestamp(s),i.addUnit(s,a...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsInterval (line 40) | static getRootAsInterval(s,a){return(a||new i).__init(s.readInt32(s.po...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startInterval (line 40) | static startInterval(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.Interva...
    method endInterval (line 40) | static endInterval(s){return s.endObject()}
    method createInterval (line 40) | static createInterval(s,a){return i.startInterval(s),i.addUnit(s,a),i....
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDuration (line 40) | static getRootAsDuration(s,a){return(a||new i).__init(s.readInt32(s.po...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startDuration (line 40) | static startDuration(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method endDuration (line 40) | static endDuration(s){return s.endObject()}
    method createDuration (line 40) | static createDuration(s,a){return i.startDuration(s),i.addUnit(s,a),i....
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsKeyValue (line 40) | static getRootAsKeyValue(s,a){return(a||new i).__init(s.readInt32(s.po...
    method key (line 40) | key(s){let a=this.bb.__offset(this.bb_pos,4);return a?this.bb.__string...
    method value (line 40) | value(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.__stri...
    method startKeyValue (line 40) | static startKeyValue(s){s.startObject(2)}
    method addKey (line 40) | static addKey(s,a){s.addFieldOffset(0,a,0)}
    method addValue (line 40) | static addValue(s,a){s.addFieldOffset(1,a,0)}
    method endKeyValue (line 40) | static endKeyValue(s){return s.endObject()}
    method createKeyValue (line 40) | static createKeyValue(s,a,c){return i.startKeyValue(s),i.addKey(s,a),i...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDictionaryEncoding (line 40) | static getRootAsDictionaryEncoding(s,a){return(a||new i).__init(s.read...
    method id (line 40) | id(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt64(...
    method indexType (line 40) | indexType(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new e....
    method isOrdered (line 40) | isOrdered(){let s=this.bb.__offset(this.bb_pos,8);return s?!!this.bb.r...
    method startDictionaryEncoding (line 40) | static startDictionaryEncoding(s){s.startObject(3)}
    method addId (line 40) | static addId(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addIndexType (line 40) | static addIndexType(s,a){s.addFieldOffset(1,a,0)}
    method addIsOrdered (line 40) | static addIsOrdered(s,a){s.addFieldInt8(2,+a,0)}
    method endDictionaryEncoding (line 40) | static endDictionaryEncoding(s){return s.endObject()}
    method createDictionaryEncoding (line 40) | static createDictionaryEncoding(s,a,c,l){return i.startDictionaryEncod...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsField (line 40) | static getRootAsField(s,a){return(a||new i).__init(s.readInt32(s.posit...
    method name (line 40) | name(s){let a=this.bb.__offset(this.bb_pos,4);return a?this.bb.__strin...
    method nullable (line 40) | nullable(){let s=this.bb.__offset(this.bb_pos,6);return s?!!this.bb.re...
    method typeType (line 40) | typeType(){let s=this.bb.__offset(this.bb_pos,8);return s?this.bb.read...
    method type (line 40) | type(s){let a=this.bb.__offset(this.bb_pos,10);return a?this.bb.__unio...
    method dictionary (line 40) | dictionary(s){let a=this.bb.__offset(this.bb_pos,12);return a?(s||new ...
    method children (line 40) | children(s,a){let c=this.bb.__offset(this.bb_pos,14);return c?(a||new ...
    method childrenLength (line 40) | childrenLength(){let s=this.bb.__offset(this.bb_pos,14);return s?this....
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,16);return c?(a...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,16);return s...
    method startField (line 40) | static startField(s){s.startObject(7)}
    method addName (line 40) | static addName(s,a){s.addFieldOffset(0,a,0)}
    method addNullable (line 40) | static addNullable(s,a){s.addFieldInt8(1,+a,0)}
    method addTypeType (line 40) | static addTypeType(s,a){s.addFieldInt8(2,a,e.apache.arrow.flatbuf.Type...
    method addType (line 40) | static addType(s,a){s.addFieldOffset(3,a,0)}
    method addDictionary (line 40) | static addDictionary(s,a){s.addFieldOffset(4,a,0)}
    method addChildren (line 40) | static addChildren(s,a){s.addFieldOffset(5,a,0)}
    method createChildrenVector (line 40) | static createChildrenVector(s,a){s.startVector(4,a.length,4);for(let c...
    method startChildrenVector (line 40) | static startChildrenVector(s,a){s.startVector(4,a,4)}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(6,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endField (line 40) | static endField(s){return s.endObject()}
    method createField (line 40) | static createField(s,a,c,l,d,p,_,O){return i.startField(s),i.addName(s...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method offset (line 40) | offset(){return this.bb.readInt64(this.bb_pos)}
    method length (line 40) | length(){return this.bb.readInt64(this.bb_pos+8)}
    method createBuffer (line 40) | static createBuffer(s,a,c){return s.prep(8,16),s.writeInt64(c),s.write...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsSchema (line 40) | static getRootAsSchema(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method endianness (line 40) | endianness(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.re...
    method fields (line 40) | fields(s,a){let c=this.bb.__offset(this.bb_pos,6);return c?(a||new e.a...
    method fieldsLength (line 40) | fieldsLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb....
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a|...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,8);return s?...
    method startSchema (line 40) | static startSchema(s){s.startObject(3)}
    method addEndianness (line 40) | static addEndianness(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.E...
    method addFields (line 40) | static addFields(s,a){s.addFieldOffset(1,a,0)}
    method createFieldsVector (line 40) | static createFieldsVector(s,a){s.startVector(4,a.length,4);for(let c=a...
    method startFieldsVector (line 40) | static startFieldsVector(s,a){s.startVector(4,a,4)}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(2,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endSchema (line 40) | static endSchema(s){return s.endObject()}
    method finishSchemaBuffer (line 40) | static finishSchemaBuffer(s,a){s.finish(a)}
    method createSchema (line 40) | static createSchema(s,a,c,l){return i.startSchema(s),i.addEndianness(s...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method length (line 40) | length(){return this.bb.readInt64(this.bb_pos)}
    method nullCount (line 40) | nullCount(){return this.bb.readInt64(this.bb_pos+8)}
    method createFieldNode (line 40) | static createFieldNode(s,a,c){return s.prep(8,16),s.writeInt64(c),s.wr...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsRecordBatch (line 40) | static getRootAsRecordBatch(s,a){return(a||new i).__init(s.readInt32(s...
    method length (line 40) | length(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readIn...
    method nodes (line 40) | nodes(s,a){let c=this.bb.__offset(this.bb_pos,6);return c?(a||new e.ap...
    method nodesLength (line 40) | nodesLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb._...
    method buffers (line 40) | buffers(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a||new v....
    method buffersLength (line 40) | buffersLength(){let s=this.bb.__offset(this.bb_pos,8);return s?this.bb...
    method startRecordBatch (line 40) | static startRecordBatch(s){s.startObject(3)}
    method addLength (line 40) | static addLength(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addNodes (line 40) | static addNodes(s,a){s.addFieldOffset(1,a,0)}
    method startNodesVector (line 40) | static startNodesVector(s,a){s.startVector(16,a,8)}
    method addBuffers (line 40) | static addBuffers(s,a){s.addFieldOffset(2,a,0)}
    method startBuffersVector (line 40) | static startBuffersVector(s,a){s.startVector(16,a,8)}
    method endRecordBatch (line 40) | static endRecordBatch(s){return s.endObject()}
    method createRecordBatch (line 40) | static createRecordBatch(s,a,c,l){return i.startRecordBatch(s),i.addLe...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDictionaryBatch (line 40) | static getRootAsDictionaryBatch(s,a){return(a||new i).__init(s.readInt...
    method id (line 40) | id(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt64(...
    method data (line 40) | data(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new e.apach...
    method isDelta (line 40) | isDelta(){let s=this.bb.__offset(this.bb_pos,8);return s?!!this.bb.rea...
    method startDictionaryBatch (line 40) | static startDictionaryBatch(s){s.startObject(3)}
    method addId (line 40) | static addId(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addData (line 40) | static addData(s,a){s.addFieldOffset(1,a,0)}
    method addIsDelta (line 40) | static addIsDelta(s,a){s.addFieldInt8(2,+a,0)}
    method endDictionaryBatch (line 40) | static endDictionaryBatch(s){return s.endObject()}
    method createDictionaryBatch (line 40) | static createDictionaryBatch(s,a,c,l){return i.startDictionaryBatch(s)...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsMessage (line 40) | static getRootAsMessage(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method version (line 40) | version(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readI...
    method headerType (line 40) | headerType(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.re...
    method header (line 40) | header(s){let a=this.bb.__offset(this.bb_pos,8);return a?this.bb.__uni...
    method bodyLength (line 40) | bodyLength(){let s=this.bb.__offset(this.bb_pos,10);return s?this.bb.r...
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,12);return c?(a...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,12);return s...
    method startMessage (line 40) | static startMessage(s){s.startObject(5)}
    method addVersion (line 40) | static addVersion(s,a){s.addFieldInt16(0,a,v.apache.arrow.flatbuf.Meta...
    method addHeaderType (line 40) | static addHeaderType(s,a){s.addFieldInt8(1,a,e.apache.arrow.flatbuf.Me...
    method addHeader (line 40) | static addHeader(s,a){s.addFieldOffset(2,a,0)}
    method addBodyLength (line 40) | static addBodyLength(s,a){s.addFieldInt64(3,a,s.createLong(0,0))}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(4,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endMessage (line 40) | static endMessage(s){return s.endObject()}
    method finishMessageBuffer (line 40) | static finishMessageBuffer(s,a){s.finish(a)}
    method createMessage (line 40) | static createMessage(s,a,c,l,d,p){return i.startMessage(s),i.addVersio...
    method constructor (line 46) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 46) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFooter (line 46) | static getRootAsFooter(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method version (line 46) | version(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readI...
    method schema (line 46) | schema(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new v.apa...
    method dictionaries (line 46) | dictionaries(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a||n...
    method dictionariesLength (line 46) | dictionariesLength(){let s=this.bb.__offset(this.bb_pos,8);return s?th...
    method recordBatches (line 46) | recordBatches(s,a){let c=this.bb.__offset(this.bb_pos,10);return c?(a|...
    method recordBatchesLength (line 46) | recordBatchesLength(){let s=this.bb.__offset(this.bb_pos,10);return s?...
    method startFooter (line 46) | static startFooter(s){s.startObject(4)}
    method addVersion (line 46) | static addVersion(s,a){s.addFieldInt16(0,a,v.apache.arrow.flatbuf.Meta...
    method addSchema (line 46) | static addSchema(s,a){s.addFieldOffset(1,a,0)}
    method addDictionaries (line 46) | static addDictionaries(s,a){s.addFieldOffset(2,a,0)}
    method startDictionariesVector (line 46) | static startDictionariesVector(s,a){s.startVector(24,a,8)}
    method addRecordBatches (line 46) | static addRecordBatches(s,a){s.addFieldOffset(3,a,0)}
    method startRecordBatchesVector (line 46) | static startRecordBatchesVector(s,a){s.startVector(24,a,8)}
    method endFooter (line 46) | static endFooter(s){return s.endObject()}
    method finishFooterBuffer (line 46) | static finishFooterBuffer(s,a){s.finish(a)}
    method createFooter (line 46) | static createFooter(s,a,c,l,d){return i.startFooter(s),i.addVersion(s,...
    method constructor (line 46) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 46) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method offset (line 46) | offset(){return this.bb.readInt64(this.bb_pos)}
    method metaDataLength (line 46) | metaDataLength(){return this.bb.readInt32(this.bb_pos+8)}
    method bodyLength (line 46) | bodyLength(){return this.bb.readInt64(this.bb_pos+16)}
    method createBlock (line 46) | static createBlock(s,a,c,l){return s.prep(8,24),s.writeInt64(l),s.pad(...
  class i (line 40) | class i{constructor(){this.bb=null,this.bb_pos=0}__init(s,a){return this...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsNull (line 40) | static getRootAsNull(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startNull (line 40) | static startNull(s){s.startObject(0)}
    method endNull (line 40) | static endNull(s){return s.endObject()}
    method createNull (line 40) | static createNull(s){return i.startNull(s),i.endNull(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsStruct_ (line 40) | static getRootAsStruct_(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method startStruct_ (line 40) | static startStruct_(s){s.startObject(0)}
    method endStruct_ (line 40) | static endStruct_(s){return s.endObject()}
    method createStruct_ (line 40) | static createStruct_(s){return i.startStruct_(s),i.endStruct_(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsList (line 40) | static getRootAsList(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startList (line 40) | static startList(s){s.startObject(0)}
    method endList (line 40) | static endList(s){return s.endObject()}
    method createList (line 40) | static createList(s){return i.startList(s),i.endList(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeList (line 40) | static getRootAsLargeList(s,a){return(a||new i).__init(s.readInt32(s.p...
    method startLargeList (line 40) | static startLargeList(s){s.startObject(0)}
    method endLargeList (line 40) | static endLargeList(s){return s.endObject()}
    method createLargeList (line 40) | static createLargeList(s){return i.startLargeList(s),i.endLargeList(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFixedSizeList (line 40) | static getRootAsFixedSizeList(s,a){return(a||new i).__init(s.readInt32...
    method listSize (line 40) | listSize(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.read...
    method startFixedSizeList (line 40) | static startFixedSizeList(s){s.startObject(1)}
    method addListSize (line 40) | static addListSize(s,a){s.addFieldInt32(0,a,0)}
    method endFixedSizeList (line 40) | static endFixedSizeList(s){return s.endObject()}
    method createFixedSizeList (line 40) | static createFixedSizeList(s,a){return i.startFixedSizeList(s),i.addLi...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsMap (line 40) | static getRootAsMap(s,a){return(a||new i).__init(s.readInt32(s.positio...
    method keysSorted (line 40) | keysSorted(){let s=this.bb.__offset(this.bb_pos,4);return s?!!this.bb....
    method startMap (line 40) | static startMap(s){s.startObject(1)}
    method addKeysSorted (line 40) | static addKeysSorted(s,a){s.addFieldInt8(0,+a,0)}
    method endMap (line 40) | static endMap(s){return s.endObject()}
    method createMap (line 40) | static createMap(s,a){return i.startMap(s),i.addKeysSorted(s,a),i.endM...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsUnion (line 40) | static getRootAsUnion(s,a){return(a||new i).__init(s.readInt32(s.posit...
    method mode (line 40) | mode(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method typeIds (line 40) | typeIds(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.read...
    method typeIdsLength (line 40) | typeIdsLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb...
    method typeIdsArray (line 40) | typeIdsArray(){let s=this.bb.__offset(this.bb_pos,6);return s?new Int3...
    method startUnion (line 40) | static startUnion(s){s.startObject(2)}
    method addMode (line 40) | static addMode(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.UnionMo...
    method addTypeIds (line 40) | static addTypeIds(s,a){s.addFieldOffset(1,a,0)}
    method createTypeIdsVector (line 40) | static createTypeIdsVector(s,a){s.startVector(4,a.length,4);for(let c=...
    method startTypeIdsVector (line 40) | static startTypeIdsVector(s,a){s.startVector(4,a,4)}
    method endUnion (line 40) | static endUnion(s){return s.endObject()}
    method createUnion (line 40) | static createUnion(s,a,c){return i.startUnion(s),i.addMode(s,a),i.addT...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsInt (line 40) | static getRootAsInt(s,a){return(a||new i).__init(s.readInt32(s.positio...
    method bitWidth (line 40) | bitWidth(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.read...
    method isSigned (line 40) | isSigned(){let s=this.bb.__offset(this.bb_pos,6);return s?!!this.bb.re...
    method startInt (line 40) | static startInt(s){s.startObject(2)}
    method addBitWidth (line 40) | static addBitWidth(s,a){s.addFieldInt32(0,a,0)}
    method addIsSigned (line 40) | static addIsSigned(s,a){s.addFieldInt8(1,+a,0)}
    method endInt (line 40) | static endInt(s){return s.endObject()}
    method createInt (line 40) | static createInt(s,a,c){return i.startInt(s),i.addBitWidth(s,a),i.addI...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFloatingPoint (line 40) | static getRootAsFloatingPoint(s,a){return(a||new i).__init(s.readInt32...
    method precision (line 40) | precision(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method startFloatingPoint (line 40) | static startFloatingPoint(s){s.startObject(1)}
    method addPrecision (line 40) | static addPrecision(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.Pr...
    method endFloatingPoint (line 40) | static endFloatingPoint(s){return s.endObject()}
    method createFloatingPoint (line 40) | static createFloatingPoint(s,a){return i.startFloatingPoint(s),i.addPr...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsUtf8 (line 40) | static getRootAsUtf8(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startUtf8 (line 40) | static startUtf8(s){s.startObject(0)}
    method endUtf8 (line 40) | static endUtf8(s){return s.endObject()}
    method createUtf8 (line 40) | static createUtf8(s){return i.startUtf8(s),i.endUtf8(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsBinary (line 40) | static getRootAsBinary(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method startBinary (line 40) | static startBinary(s){s.startObject(0)}
    method endBinary (line 40) | static endBinary(s){return s.endObject()}
    method createBinary (line 40) | static createBinary(s){return i.startBinary(s),i.endBinary(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeUtf8 (line 40) | static getRootAsLargeUtf8(s,a){return(a||new i).__init(s.readInt32(s.p...
    method startLargeUtf8 (line 40) | static startLargeUtf8(s){s.startObject(0)}
    method endLargeUtf8 (line 40) | static endLargeUtf8(s){return s.endObject()}
    method createLargeUtf8 (line 40) | static createLargeUtf8(s){return i.startLargeUtf8(s),i.endLargeUtf8(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeBinary (line 40) | static getRootAsLargeBinary(s,a){return(a||new i).__init(s.readInt32(s...
    method startLargeBinary (line 40) | static startLargeBinary(s){s.startObject(0)}
    method endLargeBinary (line 40) | static endLargeBinary(s){return s.endObject()}
    method createLargeBinary (line 40) | static createLargeBinary(s){return i.startLargeBinary(s),i.endLargeBin...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFixedSizeBinary (line 40) | static getRootAsFixedSizeBinary(s,a){return(a||new i).__init(s.readInt...
    method byteWidth (line 40) | byteWidth(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method startFixedSizeBinary (line 40) | static startFixedSizeBinary(s){s.startObject(1)}
    method addByteWidth (line 40) | static addByteWidth(s,a){s.addFieldInt32(0,a,0)}
    method endFixedSizeBinary (line 40) | static endFixedSizeBinary(s){return s.endObject()}
    method createFixedSizeBinary (line 40) | static createFixedSizeBinary(s,a){return i.startFixedSizeBinary(s),i.a...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsBool (line 40) | static getRootAsBool(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startBool (line 40) | static startBool(s){s.startObject(0)}
    method endBool (line 40) | static endBool(s){return s.endObject()}
    method createBool (line 40) | static createBool(s){return i.startBool(s),i.endBool(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDecimal (line 40) | static getRootAsDecimal(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method precision (line 40) | precision(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method scale (line 40) | scale(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.readInt...
    method startDecimal (line 40) | static startDecimal(s){s.startObject(2)}
    method addPrecision (line 40) | static addPrecision(s,a){s.addFieldInt32(0,a,0)}
    method addScale (line 40) | static addScale(s,a){s.addFieldInt32(1,a,0)}
    method endDecimal (line 40) | static endDecimal(s){return s.endObject()}
    method createDecimal (line 40) | static createDecimal(s,a,c){return i.startDecimal(s),i.addPrecision(s,...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDate (line 40) | static getRootAsDate(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startDate (line 40) | static startDate(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.DateUni...
    method endDate (line 40) | static endDate(s){return s.endObject()}
    method createDate (line 40) | static createDate(s,a){return i.startDate(s),i.addUnit(s,a),i.endDate(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsTime (line 40) | static getRootAsTime(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method bitWidth (line 40) | bitWidth(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.read...
    method startTime (line 40) | static startTime(s){s.startObject(2)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method addBitWidth (line 40) | static addBitWidth(s,a){s.addFieldInt32(1,a,32)}
    method endTime (line 40) | static endTime(s){return s.endObject()}
    method createTime (line 40) | static createTime(s,a,c){return i.startTime(s),i.addUnit(s,a),i.addBit...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsTimestamp (line 40) | static getRootAsTimestamp(s,a){return(a||new i).__init(s.readInt32(s.p...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method timezone (line 40) | timezone(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.__s...
    method startTimestamp (line 40) | static startTimestamp(s){s.startObject(2)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method addTimezone (line 40) | static addTimezone(s,a){s.addFieldOffset(1,a,0)}
    method endTimestamp (line 40) | static endTimestamp(s){return s.endObject()}
    method createTimestamp (line 40) | static createTimestamp(s,a,c){return i.startTimestamp(s),i.addUnit(s,a...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsInterval (line 40) | static getRootAsInterval(s,a){return(a||new i).__init(s.readInt32(s.po...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startInterval (line 40) | static startInterval(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.Interva...
    method endInterval (line 40) | static endInterval(s){return s.endObject()}
    method createInterval (line 40) | static createInterval(s,a){return i.startInterval(s),i.addUnit(s,a),i....
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDuration (line 40) | static getRootAsDuration(s,a){return(a||new i).__init(s.readInt32(s.po...
    method unit (line 40) | unit(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method startDuration (line 40) | static startDuration(s){s.startObject(1)}
    method addUnit (line 40) | static addUnit(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.TimeUni...
    method endDuration (line 40) | static endDuration(s){return s.endObject()}
    method createDuration (line 40) | static createDuration(s,a){return i.startDuration(s),i.addUnit(s,a),i....
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsKeyValue (line 40) | static getRootAsKeyValue(s,a){return(a||new i).__init(s.readInt32(s.po...
    method key (line 40) | key(s){let a=this.bb.__offset(this.bb_pos,4);return a?this.bb.__string...
    method value (line 40) | value(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.__stri...
    method startKeyValue (line 40) | static startKeyValue(s){s.startObject(2)}
    method addKey (line 40) | static addKey(s,a){s.addFieldOffset(0,a,0)}
    method addValue (line 40) | static addValue(s,a){s.addFieldOffset(1,a,0)}
    method endKeyValue (line 40) | static endKeyValue(s){return s.endObject()}
    method createKeyValue (line 40) | static createKeyValue(s,a,c){return i.startKeyValue(s),i.addKey(s,a),i...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDictionaryEncoding (line 40) | static getRootAsDictionaryEncoding(s,a){return(a||new i).__init(s.read...
    method id (line 40) | id(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt64(...
    method indexType (line 40) | indexType(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new e....
    method isOrdered (line 40) | isOrdered(){let s=this.bb.__offset(this.bb_pos,8);return s?!!this.bb.r...
    method startDictionaryEncoding (line 40) | static startDictionaryEncoding(s){s.startObject(3)}
    method addId (line 40) | static addId(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addIndexType (line 40) | static addIndexType(s,a){s.addFieldOffset(1,a,0)}
    method addIsOrdered (line 40) | static addIsOrdered(s,a){s.addFieldInt8(2,+a,0)}
    method endDictionaryEncoding (line 40) | static endDictionaryEncoding(s){return s.endObject()}
    method createDictionaryEncoding (line 40) | static createDictionaryEncoding(s,a,c,l){return i.startDictionaryEncod...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsField (line 40) | static getRootAsField(s,a){return(a||new i).__init(s.readInt32(s.posit...
    method name (line 40) | name(s){let a=this.bb.__offset(this.bb_pos,4);return a?this.bb.__strin...
    method nullable (line 40) | nullable(){let s=this.bb.__offset(this.bb_pos,6);return s?!!this.bb.re...
    method typeType (line 40) | typeType(){let s=this.bb.__offset(this.bb_pos,8);return s?this.bb.read...
    method type (line 40) | type(s){let a=this.bb.__offset(this.bb_pos,10);return a?this.bb.__unio...
    method dictionary (line 40) | dictionary(s){let a=this.bb.__offset(this.bb_pos,12);return a?(s||new ...
    method children (line 40) | children(s,a){let c=this.bb.__offset(this.bb_pos,14);return c?(a||new ...
    method childrenLength (line 40) | childrenLength(){let s=this.bb.__offset(this.bb_pos,14);return s?this....
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,16);return c?(a...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,16);return s...
    method startField (line 40) | static startField(s){s.startObject(7)}
    method addName (line 40) | static addName(s,a){s.addFieldOffset(0,a,0)}
    method addNullable (line 40) | static addNullable(s,a){s.addFieldInt8(1,+a,0)}
    method addTypeType (line 40) | static addTypeType(s,a){s.addFieldInt8(2,a,e.apache.arrow.flatbuf.Type...
    method addType (line 40) | static addType(s,a){s.addFieldOffset(3,a,0)}
    method addDictionary (line 40) | static addDictionary(s,a){s.addFieldOffset(4,a,0)}
    method addChildren (line 40) | static addChildren(s,a){s.addFieldOffset(5,a,0)}
    method createChildrenVector (line 40) | static createChildrenVector(s,a){s.startVector(4,a.length,4);for(let c...
    method startChildrenVector (line 40) | static startChildrenVector(s,a){s.startVector(4,a,4)}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(6,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endField (line 40) | static endField(s){return s.endObject()}
    method createField (line 40) | static createField(s,a,c,l,d,p,_,O){return i.startField(s),i.addName(s...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method offset (line 40) | offset(){return this.bb.readInt64(this.bb_pos)}
    method length (line 40) | length(){return this.bb.readInt64(this.bb_pos+8)}
    method createBuffer (line 40) | static createBuffer(s,a,c){return s.prep(8,16),s.writeInt64(c),s.write...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsSchema (line 40) | static getRootAsSchema(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method endianness (line 40) | endianness(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.re...
    method fields (line 40) | fields(s,a){let c=this.bb.__offset(this.bb_pos,6);return c?(a||new e.a...
    method fieldsLength (line 40) | fieldsLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb....
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a|...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,8);return s?...
    method startSchema (line 40) | static startSchema(s){s.startObject(3)}
    method addEndianness (line 40) | static addEndianness(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.E...
    method addFields (line 40) | static addFields(s,a){s.addFieldOffset(1,a,0)}
    method createFieldsVector (line 40) | static createFieldsVector(s,a){s.startVector(4,a.length,4);for(let c=a...
    method startFieldsVector (line 40) | static startFieldsVector(s,a){s.startVector(4,a,4)}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(2,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endSchema (line 40) | static endSchema(s){return s.endObject()}
    method finishSchemaBuffer (line 40) | static finishSchemaBuffer(s,a){s.finish(a)}
    method createSchema (line 40) | static createSchema(s,a,c,l){return i.startSchema(s),i.addEndianness(s...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method length (line 40) | length(){return this.bb.readInt64(this.bb_pos)}
    method nullCount (line 40) | nullCount(){return this.bb.readInt64(this.bb_pos+8)}
    method createFieldNode (line 40) | static createFieldNode(s,a,c){return s.prep(8,16),s.writeInt64(c),s.wr...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsRecordBatch (line 40) | static getRootAsRecordBatch(s,a){return(a||new i).__init(s.readInt32(s...
    method length (line 40) | length(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readIn...
    method nodes (line 40) | nodes(s,a){let c=this.bb.__offset(this.bb_pos,6);return c?(a||new e.ap...
    method nodesLength (line 40) | nodesLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb._...
    method buffers (line 40) | buffers(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a||new v....
    method buffersLength (line 40) | buffersLength(){let s=this.bb.__offset(this.bb_pos,8);return s?this.bb...
    method startRecordBatch (line 40) | static startRecordBatch(s){s.startObject(3)}
    method addLength (line 40) | static addLength(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addNodes (line 40) | static addNodes(s,a){s.addFieldOffset(1,a,0)}
    method startNodesVector (line 40) | static startNodesVector(s,a){s.startVector(16,a,8)}
    method addBuffers (line 40) | static addBuffers(s,a){s.addFieldOffset(2,a,0)}
    method startBuffersVector (line 40) | static startBuffersVector(s,a){s.startVector(16,a,8)}
    method endRecordBatch (line 40) | static endRecordBatch(s){return s.endObject()}
    method createRecordBatch (line 40) | static createRecordBatch(s,a,c,l){return i.startRecordBatch(s),i.addLe...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsDictionaryBatch (line 40) | static getRootAsDictionaryBatch(s,a){return(a||new i).__init(s.readInt...
    method id (line 40) | id(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt64(...
    method data (line 40) | data(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new e.apach...
    method isDelta (line 40) | isDelta(){let s=this.bb.__offset(this.bb_pos,8);return s?!!this.bb.rea...
    method startDictionaryBatch (line 40) | static startDictionaryBatch(s){s.startObject(3)}
    method addId (line 40) | static addId(s,a){s.addFieldInt64(0,a,s.createLong(0,0))}
    method addData (line 40) | static addData(s,a){s.addFieldOffset(1,a,0)}
    method addIsDelta (line 40) | static addIsDelta(s,a){s.addFieldInt8(2,+a,0)}
    method endDictionaryBatch (line 40) | static endDictionaryBatch(s){return s.endObject()}
    method createDictionaryBatch (line 40) | static createDictionaryBatch(s,a,c,l){return i.startDictionaryBatch(s)...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsMessage (line 40) | static getRootAsMessage(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method version (line 40) | version(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readI...
    method headerType (line 40) | headerType(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb.re...
    method header (line 40) | header(s){let a=this.bb.__offset(this.bb_pos,8);return a?this.bb.__uni...
    method bodyLength (line 40) | bodyLength(){let s=this.bb.__offset(this.bb_pos,10);return s?this.bb.r...
    method customMetadata (line 40) | customMetadata(s,a){let c=this.bb.__offset(this.bb_pos,12);return c?(a...
    method customMetadataLength (line 40) | customMetadataLength(){let s=this.bb.__offset(this.bb_pos,12);return s...
    method startMessage (line 40) | static startMessage(s){s.startObject(5)}
    method addVersion (line 40) | static addVersion(s,a){s.addFieldInt16(0,a,v.apache.arrow.flatbuf.Meta...
    method addHeaderType (line 40) | static addHeaderType(s,a){s.addFieldInt8(1,a,e.apache.arrow.flatbuf.Me...
    method addHeader (line 40) | static addHeader(s,a){s.addFieldOffset(2,a,0)}
    method addBodyLength (line 40) | static addBodyLength(s,a){s.addFieldInt64(3,a,s.createLong(0,0))}
    method addCustomMetadata (line 40) | static addCustomMetadata(s,a){s.addFieldOffset(4,a,0)}
    method createCustomMetadataVector (line 40) | static createCustomMetadataVector(s,a){s.startVector(4,a.length,4);for...
    method startCustomMetadataVector (line 40) | static startCustomMetadataVector(s,a){s.startVector(4,a,4)}
    method endMessage (line 40) | static endMessage(s){return s.endObject()}
    method finishMessageBuffer (line 40) | static finishMessageBuffer(s,a){s.finish(a)}
    method createMessage (line 40) | static createMessage(s,a,c,l,d,p){return i.startMessage(s),i.addVersio...
    method constructor (line 46) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 46) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFooter (line 46) | static getRootAsFooter(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method version (line 46) | version(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readI...
    method schema (line 46) | schema(s){let a=this.bb.__offset(this.bb_pos,6);return a?(s||new v.apa...
    method dictionaries (line 46) | dictionaries(s,a){let c=this.bb.__offset(this.bb_pos,8);return c?(a||n...
    method dictionariesLength (line 46) | dictionariesLength(){let s=this.bb.__offset(this.bb_pos,8);return s?th...
    method recordBatches (line 46) | recordBatches(s,a){let c=this.bb.__offset(this.bb_pos,10);return c?(a|...
    method recordBatchesLength (line 46) | recordBatchesLength(){let s=this.bb.__offset(this.bb_pos,10);return s?...
    method startFooter (line 46) | static startFooter(s){s.startObject(4)}
    method addVersion (line 46) | static addVersion(s,a){s.addFieldInt16(0,a,v.apache.arrow.flatbuf.Meta...
    method addSchema (line 46) | static addSchema(s,a){s.addFieldOffset(1,a,0)}
    method addDictionaries (line 46) | static addDictionaries(s,a){s.addFieldOffset(2,a,0)}
    method startDictionariesVector (line 46) | static startDictionariesVector(s,a){s.startVector(24,a,8)}
    method addRecordBatches (line 46) | static addRecordBatches(s,a){s.addFieldOffset(3,a,0)}
    method startRecordBatchesVector (line 46) | static startRecordBatchesVector(s,a){s.startVector(24,a,8)}
    method endFooter (line 46) | static endFooter(s){return s.endObject()}
    method finishFooterBuffer (line 46) | static finishFooterBuffer(s,a){s.finish(a)}
    method createFooter (line 46) | static createFooter(s,a,c,l,d){return i.startFooter(s),i.addVersion(s,...
    method constructor (line 46) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 46) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method offset (line 46) | offset(){return this.bb.readInt64(this.bb_pos)}
    method metaDataLength (line 46) | metaDataLength(){return this.bb.readInt32(this.bb_pos+8)}
    method bodyLength (line 46) | bodyLength(){return this.bb.readInt64(this.bb_pos+16)}
    method createBlock (line 46) | static createBlock(s,a,c,l){return s.prep(8,24),s.writeInt64(l),s.pad(...
  class i (line 40) | class i{constructor(){this.bb=null,this.bb_pos=0}__init(s,a){return this...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsNull (line 40) | static getRootAsNull(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startNull (line 40) | static startNull(s){s.startObject(0)}
    method endNull (line 40) | static endNull(s){return s.endObject()}
    method createNull (line 40) | static createNull(s){return i.startNull(s),i.endNull(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsStruct_ (line 40) | static getRootAsStruct_(s,a){return(a||new i).__init(s.readInt32(s.pos...
    method startStruct_ (line 40) | static startStruct_(s){s.startObject(0)}
    method endStruct_ (line 40) | static endStruct_(s){return s.endObject()}
    method createStruct_ (line 40) | static createStruct_(s){return i.startStruct_(s),i.endStruct_(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsList (line 40) | static getRootAsList(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startList (line 40) | static startList(s){s.startObject(0)}
    method endList (line 40) | static endList(s){return s.endObject()}
    method createList (line 40) | static createList(s){return i.startList(s),i.endList(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeList (line 40) | static getRootAsLargeList(s,a){return(a||new i).__init(s.readInt32(s.p...
    method startLargeList (line 40) | static startLargeList(s){s.startObject(0)}
    method endLargeList (line 40) | static endLargeList(s){return s.endObject()}
    method createLargeList (line 40) | static createLargeList(s){return i.startLargeList(s),i.endLargeList(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFixedSizeList (line 40) | static getRootAsFixedSizeList(s,a){return(a||new i).__init(s.readInt32...
    method listSize (line 40) | listSize(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.read...
    method startFixedSizeList (line 40) | static startFixedSizeList(s){s.startObject(1)}
    method addListSize (line 40) | static addListSize(s,a){s.addFieldInt32(0,a,0)}
    method endFixedSizeList (line 40) | static endFixedSizeList(s){return s.endObject()}
    method createFixedSizeList (line 40) | static createFixedSizeList(s,a){return i.startFixedSizeList(s),i.addLi...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsMap (line 40) | static getRootAsMap(s,a){return(a||new i).__init(s.readInt32(s.positio...
    method keysSorted (line 40) | keysSorted(){let s=this.bb.__offset(this.bb_pos,4);return s?!!this.bb....
    method startMap (line 40) | static startMap(s){s.startObject(1)}
    method addKeysSorted (line 40) | static addKeysSorted(s,a){s.addFieldInt8(0,+a,0)}
    method endMap (line 40) | static endMap(s){return s.endObject()}
    method createMap (line 40) | static createMap(s,a){return i.startMap(s),i.addKeysSorted(s,a),i.endM...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsUnion (line 40) | static getRootAsUnion(s,a){return(a||new i).__init(s.readInt32(s.posit...
    method mode (line 40) | mode(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.readInt1...
    method typeIds (line 40) | typeIds(s){let a=this.bb.__offset(this.bb_pos,6);return a?this.bb.read...
    method typeIdsLength (line 40) | typeIdsLength(){let s=this.bb.__offset(this.bb_pos,6);return s?this.bb...
    method typeIdsArray (line 40) | typeIdsArray(){let s=this.bb.__offset(this.bb_pos,6);return s?new Int3...
    method startUnion (line 40) | static startUnion(s){s.startObject(2)}
    method addMode (line 40) | static addMode(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.UnionMo...
    method addTypeIds (line 40) | static addTypeIds(s,a){s.addFieldOffset(1,a,0)}
    method createTypeIdsVector (line 40) | static createTypeIdsVector(s,a){s.startVector(4,a.length,4);for(let c=...
    method startTypeIdsVector (line 40) | static startTypeIdsVector(s,a){s.startVector(4,a,4)}
    method endUnion (line 40) | static endUnion(s){return s.endObject()}
    method createUnion (line 40) | static createUnion(s,a,c){return i.startUnion(s),i.addMode(s,a),i.addT...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsInt (line 40) | static getRootAsInt(s,a){return(a||new i).__init(s.readInt32(s.positio...
    method bitWidth (line 40) | bitWidth(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.read...
    method isSigned (line 40) | isSigned(){let s=this.bb.__offset(this.bb_pos,6);return s?!!this.bb.re...
    method startInt (line 40) | static startInt(s){s.startObject(2)}
    method addBitWidth (line 40) | static addBitWidth(s,a){s.addFieldInt32(0,a,0)}
    method addIsSigned (line 40) | static addIsSigned(s,a){s.addFieldInt8(1,+a,0)}
    method endInt (line 40) | static endInt(s){return s.endObject()}
    method createInt (line 40) | static createInt(s,a,c){return i.startInt(s),i.addBitWidth(s,a),i.addI...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFloatingPoint (line 40) | static getRootAsFloatingPoint(s,a){return(a||new i).__init(s.readInt32...
    method precision (line 40) | precision(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method startFloatingPoint (line 40) | static startFloatingPoint(s){s.startObject(1)}
    method addPrecision (line 40) | static addPrecision(s,a){s.addFieldInt16(0,a,e.apache.arrow.flatbuf.Pr...
    method endFloatingPoint (line 40) | static endFloatingPoint(s){return s.endObject()}
    method createFloatingPoint (line 40) | static createFloatingPoint(s,a){return i.startFloatingPoint(s),i.addPr...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsUtf8 (line 40) | static getRootAsUtf8(s,a){return(a||new i).__init(s.readInt32(s.positi...
    method startUtf8 (line 40) | static startUtf8(s){s.startObject(0)}
    method endUtf8 (line 40) | static endUtf8(s){return s.endObject()}
    method createUtf8 (line 40) | static createUtf8(s){return i.startUtf8(s),i.endUtf8(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsBinary (line 40) | static getRootAsBinary(s,a){return(a||new i).__init(s.readInt32(s.posi...
    method startBinary (line 40) | static startBinary(s){s.startObject(0)}
    method endBinary (line 40) | static endBinary(s){return s.endObject()}
    method createBinary (line 40) | static createBinary(s){return i.startBinary(s),i.endBinary(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeUtf8 (line 40) | static getRootAsLargeUtf8(s,a){return(a||new i).__init(s.readInt32(s.p...
    method startLargeUtf8 (line 40) | static startLargeUtf8(s){s.startObject(0)}
    method endLargeUtf8 (line 40) | static endLargeUtf8(s){return s.endObject()}
    method createLargeUtf8 (line 40) | static createLargeUtf8(s){return i.startLargeUtf8(s),i.endLargeUtf8(s)}
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsLargeBinary (line 40) | static getRootAsLargeBinary(s,a){return(a||new i).__init(s.readInt32(s...
    method startLargeBinary (line 40) | static startLargeBinary(s){s.startObject(0)}
    method endLargeBinary (line 40) | static endLargeBinary(s){return s.endObject()}
    method createLargeBinary (line 40) | static createLargeBinary(s){return i.startLargeBinary(s),i.endLargeBin...
    method constructor (line 40) | constructor(){this.bb=null,this.bb_pos=0}
    method __init (line 40) | __init(s,a){return this.bb_pos=s,this.bb=a,this}
    method getRootAsFixedSizeBinary (line 40) | static getRootAsFixedSizeBinary(s,a){return(a||new i).__init(s.readInt...
    method byteWidth (line 40) | byteWidth(){let s=this.bb.__offset(this.bb_pos,4);return s?this.bb.rea...
    method startFixedSizeBinary (line 40) | static startFixedSizeBinary(s){s.startObject(1)}
    method addByteWidth (line 40) | static addByteWidth(s,a){s.addFieldInt32(0,a,0)}
    method endFixedSizeBinary (line 40) | static endFixedSizeBinary(s){return s.endObject()}
Copy disabled (too large) Download .json
Condensed preview — 290 files, each showing path, character count, and a content snippet. Download the .json file for the full structured content (10,618K chars).
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    "path": ".streamlit/config.toml",
    "chars": 796,
    "preview": "[global]\ndisableWatchdogWarning = false\nshowWarningOnDirectExecution = true\ndataFrameSerialization = \"arrow\"\n\n[logger]\nl"
  },
  {
    "path": "CONTRIBUTING.md",
    "chars": 1552,
    "preview": "# Contribution Guide\n\nAll Pull Requests are opened against `dev` branch which is our main development branch.\n\nThere are"
  },
  {
    "path": "Dockerfile",
    "chars": 941,
    "preview": "ARG IMAGE=tukirito/sygil-webui:base\n\n# Use the base image\nFROM ${IMAGE}\n\n# Set the working directory\nWORKDIR /workdir\n\n#"
  },
  {
    "path": "Dockerfile_base",
    "chars": 472,
    "preview": "ARG PYTORCH_IMAGE=hlky/pytorch:1.12.1-runtime\n\nFROM ${PYTORCH_IMAGE}\nSHELL [\"/bin/bash\", \"-c\"]\n\nWORKDIR /install\n\nRUN ap"
  },
  {
    "path": "Dockerfile_runpod",
    "chars": 770,
    "preview": "ARG IMAGE=tukirito/sygil-webui:base\n\nFROM ${IMAGE}\n\nWORKDIR /workdir\n\nSHELL [\"/bin/bash\", \"-c\"]\n\nENV PYTHONPATH=/sd\n\nEXP"
  },
  {
    "path": "LICENSE",
    "chars": 34523,
    "preview": "                    GNU AFFERO GENERAL PUBLIC LICENSE\n                       Version 3, 19 November 2007\n\n Copyright (C)"
  },
  {
    "path": "README.md",
    "chars": 10414,
    "preview": "# <center>Web-based UI for Stable Diffusion</center>\r\n\r\n## Created by [Sygil.Dev](https://github.com/sygil-dev)\r\n\r\n## Jo"
  },
  {
    "path": "Stable_Diffusion_v1_Model_Card.md",
    "chars": 8582,
    "preview": "# Stable Diffusion v1 Model Card\nThis model card focuses on the model associated with the Stable Diffusion model, availa"
  },
  {
    "path": "Web_based_UI_for_Stable_Diffusion_colab.ipynb",
    "chars": 28576,
    "preview": "{\n  \"cells\": [\n    {\n      \"cell_type\": \"markdown\",\n      \"metadata\": {\n        \"id\": \"S5RoIM-5IPZJ\"\n      },\n      \"sou"
  },
  {
    "path": "_config.yml",
    "chars": 237,
    "preview": "plugins:\n  - jekyll-relative-links\n  - jekyll-readme-index\n  - jemoji\n  - jekyll-remote-theme\nrelative_links:\n  enabled:"
  },
  {
    "path": "babel.config.js",
    "chars": 89,
    "preview": "module.exports = {\n  presets: [require.resolve('@docusaurus/core/lib/babel/preset')],\n};\n"
  },
  {
    "path": "blog/2022-10-20/1.Textual inversion usage competitio.md",
    "chars": 3821,
    "preview": "# Textual inversion usage competition\n\nWe are hosting a competition where the community can showcase their most inventiv"
  },
  {
    "path": "blog/authors.yml",
    "chars": 446,
    "preview": "endi:\n  name: Endilie Yacop Sucipto\n  title: Maintainer of Docusaurus\n  url: https://github.com/endiliey\n  image_url: ht"
  },
  {
    "path": "configs/autoencoder/autoencoder_kl_16x16x16.yaml",
    "chars": 1145,
    "preview": "model:\n  base_learning_rate: 4.5e-6\n  target: ldm.models.autoencoder.AutoencoderKL\n  params:\n    monitor: \"val/rec_loss\""
  },
  {
    "path": "configs/autoencoder/autoencoder_kl_32x32x4.yaml",
    "chars": 1140,
    "preview": "model:\n  base_learning_rate: 4.5e-6\n  target: ldm.models.autoencoder.AutoencoderKL\n  params:\n    monitor: \"val/rec_loss\""
  },
  {
    "path": "configs/autoencoder/autoencoder_kl_64x64x3.yaml",
    "chars": 1139,
    "preview": "model:\n  base_learning_rate: 4.5e-6\n  target: ldm.models.autoencoder.AutoencoderKL\n  params:\n    monitor: \"val/rec_loss\""
  },
  {
    "path": "configs/autoencoder/autoencoder_kl_8x8x64.yaml",
    "chars": 1148,
    "preview": "model:\n  base_learning_rate: 4.5e-6\n  target: ldm.models.autoencoder.AutoencoderKL\n  params:\n    monitor: \"val/rec_loss\""
  },
  {
    "path": "configs/blip/bert_config.json",
    "chars": 482,
    "preview": "{\n  \"architectures\": [\n    \"BertModel\"\n  ],\n  \"attention_probs_dropout_prob\": 0.1,\n  \"hidden_act\": \"gelu\",\n  \"hidden_dro"
  },
  {
    "path": "configs/blip/caption_coco.yaml",
    "chars": 648,
    "preview": "image_root: '/export/share/datasets/vision/coco/images/'\nann_root: 'annotation'\ncoco_gt_root: 'annotation/coco_gt'\n\n# se"
  },
  {
    "path": "configs/blip/med_config.json",
    "chars": 482,
    "preview": "{\n  \"architectures\": [\n    \"BertModel\"\n  ],\n  \"attention_probs_dropout_prob\": 0.1,\n  \"hidden_act\": \"gelu\",\n  \"hidden_dro"
  },
  {
    "path": "configs/blip/nlvr.yaml",
    "chars": 437,
    "preview": "image_root: '/export/share/datasets/vision/NLVR2/'\nann_root: 'annotation'\n\n# set pretrained as a file path or an url\npre"
  },
  {
    "path": "configs/blip/nocaps.yaml",
    "chars": 353,
    "preview": "image_root: '/export/share/datasets/vision/nocaps/'\nann_root: 'annotation'\n\n# set pretrained as a file path or an url\npr"
  },
  {
    "path": "configs/blip/pretrain.yaml",
    "chars": 473,
    "preview": "train_file: ['/export/share/junnan-li/VL_pretrain/annotation/coco_karpathy_train.json',\n             '/export/share/junn"
  },
  {
    "path": "configs/blip/retrieval_coco.yaml",
    "chars": 654,
    "preview": "image_root: '/export/share/datasets/vision/coco/images/'\nann_root: 'annotation'\ndataset: 'coco'\n\n# set pretrained as a f"
  },
  {
    "path": "configs/blip/retrieval_flickr.yaml",
    "chars": 657,
    "preview": "image_root: '/export/share/datasets/vision/flickr30k/'\nann_root: 'annotation'\ndataset: 'flickr'\n\n# set pretrained as a f"
  },
  {
    "path": "configs/blip/retrieval_msrvtt.yaml",
    "chars": 355,
    "preview": "video_root: '/export/share/dongxuli/data/msrvtt_retrieval/videos'\nann_root: 'annotation'\n\n# set pretrained as a file pat"
  },
  {
    "path": "configs/blip/vqa.yaml",
    "chars": 638,
    "preview": "vqa_root: '/export/share/datasets/vision/VQA/Images/mscoco/' #followed by train2014/\nvg_root: '/export/share/datasets/vi"
  },
  {
    "path": "configs/latent-diffusion/celebahq-ldm-vq-4.yaml",
    "chars": 2029,
    "preview": "model:\n  base_learning_rate: 2.0e-06\n  target: ldm.models.diffusion.ddpm.LatentDiffusion\n  params:\n    linear_start: 0.0"
  },
  {
    "path": "configs/latent-diffusion/cin-ldm-vq-f8.yaml",
    "chars": 2361,
    "preview": "model:\n  base_learning_rate: 1.0e-06\n  target: ldm.models.diffusion.ddpm.LatentDiffusion\n  params:\n    linear_start: 0.0"
  },
  {
    "path": "configs/latent-diffusion/cin256-v2.yaml",
    "chars": 1541,
    "preview": "model:\n  base_learning_rate: 0.0001\n  target: ldm.models.diffusion.ddpm.LatentDiffusion\n  params:\n    linear_start: 0.00"
  },
  {
    "path": "configs/latent-diffusion/ffhq-ldm-vq-4.yaml",
    "chars": 2021,
    "preview": "model:\n  base_learning_rate: 2.0e-06\n  target: ldm.models.diffusion.ddpm.LatentDiffusion\n  params:\n    linear_start: 0.0"
  },
  {
    "path": "configs/latent-diffusion/lsun_bedrooms-ldm-vq-4.yaml",
    "chars": 2025,
    "preview": "model:\n  base_learning_rate: 2.0e-06\n  target: ldm.models.diffusion.ddpm.LatentDiffusion\n  params:\n    linear_start: 0.0"
  },
  {
    "path": "configs/latent-diffusion/lsun_churches-ldm-kl-8.yaml",
    "chars": 2285,
    "preview": "model:\n  base_learning_rate: 5.0e-5   # set to target_lr by starting main.py with '--scale_lr False'\n  target: ldm.model"
  },
  {
    "path": "configs/latent-diffusion/txt2img-1p4B-eval.yaml",
    "chars": 1614,
    "preview": "model:\n  base_learning_rate: 5.0e-05\n  target: ldm.models.diffusion.ddpm.LatentDiffusion\n  params:\n    linear_start: 0.0"
  },
  {
    "path": "configs/retrieval-augmented-diffusion/768x768.yaml",
    "chars": 1616,
    "preview": "model:\n  base_learning_rate: 0.0001\n  target: ldm.models.diffusion.ddpm.LatentDiffusion\n  params:\n    linear_start: 0.00"
  },
  {
    "path": "configs/stable-diffusion/v1-inference.yaml",
    "chars": 1873,
    "preview": "model:\n  base_learning_rate: 1.0e-04\n  target: ldm.models.diffusion.ddpm.LatentDiffusion\n  params:\n    linear_start: 0.0"
  },
  {
    "path": "configs/stable-diffusion/v2-inference-v.yaml",
    "chars": 1815,
    "preview": "model:\n  base_learning_rate: 1.0e-4\n  target: ldm.models.diffusion.ddpm.LatentDiffusion\n  params:\n    parameterization: "
  },
  {
    "path": "configs/stable-diffusion/v2-inference.yaml",
    "chars": 1789,
    "preview": "model:\n  base_learning_rate: 1.0e-4\n  target: ldm.models.diffusion.ddpm.LatentDiffusion\n  params:\n    linear_start: 0.00"
  },
  {
    "path": "configs/stable-diffusion/v2-inpainting-inference.yaml",
    "chars": 4450,
    "preview": "model:\n  base_learning_rate: 5.0e-05\n  target: ldm.models.diffusion.ddpm.LatentInpaintDiffusion\n  params:\n    linear_sta"
  },
  {
    "path": "configs/stable-diffusion/v2-midas-inference.yaml",
    "chars": 1867,
    "preview": "model:\n  base_learning_rate: 5.0e-07\n  target: ldm.models.diffusion.ddpm.LatentDepth2ImageDiffusion\n  params:\n    linear"
  },
  {
    "path": "configs/stable-diffusion/x4-upscaling.yaml",
    "chars": 2250,
    "preview": "model:\n  base_learning_rate: 1.0e-04\n  target: ldm.models.diffusion.ddpm.LatentUpscaleDiffusion\n  params:\n    parameteri"
  },
  {
    "path": "configs/webui/webui.yaml",
    "chars": 2777,
    "preview": "# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\n# Copyright 2022 Sygil-Dev team.\n# This"
  },
  {
    "path": "configs/webui/webui_flet.yaml",
    "chars": 5932,
    "preview": "# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\n# Copyright 2022 Sygil-Dev team.\n# This"
  },
  {
    "path": "configs/webui/webui_streamlit.yaml",
    "chars": 12826,
    "preview": "# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\n# Copyright 2022 Sygil-Dev team.\n# This"
  },
  {
    "path": "daisi_app.py",
    "chars": 1155,
    "preview": "import os, subprocess\nimport yaml\n\nprint(os.getcwd)\n\ntry:\n    with open(\"environment.yaml\") as file_handle:\n        envi"
  },
  {
    "path": "data/img2txt/artists.txt",
    "chars": 169238,
    "preview": "A B Jackson\nA J Casson\nA R Middleton Todd\nA. B. Jackson\nA. J. Casson\nA. R. Middleton Todd\nA.B. Frost\nA.D.M. Cooper\nAB Fr"
  },
  {
    "path": "data/img2txt/flavors.txt",
    "chars": 1833076,
    "preview": "\bmoebius\n! apocalypse landscape!!\n! baron harkonnen!\n! dream\n! dream artgerm\n! haute couture!\n! holding in his hand !\n! "
  },
  {
    "path": "data/img2txt/mediums.txt",
    "chars": 1681,
    "preview": "a 2 koma\na 2koma\na 3D render\na 4 koma\na 4koma\na 6 koma\na 6koma\na 8 koma\na 8koma\na black and white photo\na bronze sculptu"
  },
  {
    "path": "data/img2txt/movements.txt",
    "chars": 2681,
    "preview": "abstract art\nabstract expressionism\nabstract illusionism\nacademic art\naction painting\naestheticism\nafrofuturism\naltermod"
  },
  {
    "path": "data/img2txt/sites.txt",
    "chars": 168,
    "preview": "Artstation\nbehance\ncg society\ncgsociety\ndeviantart\ndribble\nflickr\ninstagram\npexels\npinterest\npixabay\npixiv\npolycount\nred"
  },
  {
    "path": "data/img2txt/subreddits.txt",
    "chars": 3330,
    "preview": "/r/ImaginaryAetherpunk\n/r/ImaginaryAgriculture\n/r/ImaginaryAirships\n/r/ImaginaryAliens\n/r/ImaginaryAngels\n/r/ImaginaryAn"
  },
  {
    "path": "data/img2txt/tags.txt",
    "chars": 22403,
    "preview": "04matsuko\n100-percent-donmai\n101-goushitsu\n35-machi\n39tei\n3dlive\n5505-project\n5base\n6channel\n6no1\n6tsuno87\n774cake\na-kyo"
  },
  {
    "path": "data/img2txt/techniques.txt",
    "chars": 586,
    "preview": "Fine Art\nDiagrammatic\nGeometric\nArchitectural\nAnalytic\n3D\nAnamorphic\nPencil\nColor Pencil\nCharcoal\nGraphite\nChalk\nPen\nInk"
  },
  {
    "path": "data/scn2img_examples/cat_at_beach.scn2img.md",
    "chars": 1038,
    "preview": "// blend it together and finish it with details\nprompt: cute happy orange cat sitting at beach, beach in background, tre"
  },
  {
    "path": "data/scn2img_examples/corgi_3d_transformation.scn2img.md",
    "chars": 889,
    "preview": "initial_seed: 2\n\n// select background and img2img over it\nmask_by_color_at: 64, 64\nmask_invert: True\n\nprompt: corgi\nddim"
  },
  {
    "path": "data/scn2img_examples/corgi_at_beach.scn2img.md",
    "chars": 598,
    "preview": "// blend it together and finish it with some details\nprompt: cute corgi at beach, trending on artstation\nddim_steps: 50\n"
  },
  {
    "path": "data/scn2img_examples/corgi_at_beach_2.scn2img.md",
    "chars": 845,
    "preview": "// give it some polish and details\nsize: 512, 512\nprompt: cute corgi at beach, intricate details, photorealistic, trendi"
  },
  {
    "path": "data/scn2img_examples/landscape_3d.scn2img.md",
    "chars": 877,
    "preview": "size: 512,512\nmask_blur: 6\n\nprompt: fantasy landscape with castle and forest and waterfalls, trending on artstation\ndeno"
  },
  {
    "path": "data/tags/config.json",
    "chars": 635,
    "preview": "{\n\t\"tagFile\": \"danbooru.csv\",\n\t\"maxResults\": 5,\n\t\"replaceUnderscores\": true,\n\t\"escapeParentheses\": true,\n\t\"colors\": {\n\t\t"
  },
  {
    "path": "data/tags/danbooru.csv",
    "chars": 1839510,
    "preview": "1girl,0\nsolo,0\nhighres,5\nlong_hair,0\ncommentary_request,5\nbreasts,0\nlooking_at_viewer,0\nblush,0\nsmile,0\nshort_hair,0\nope"
  },
  {
    "path": "data/tags/e621.csv",
    "chars": 990964,
    "preview": "mammal,5\nanthro,0\nhi_res,7\nfemale,0\nmale,0\nsolo,0\ngenitals,0\nclothing,0\nbreasts,0\nhair,0\nfur,0\nduo,0\npenis,0\nbodily_flui"
  },
  {
    "path": "data/tags/key_phrases.json",
    "chars": 1179345,
    "preview": "{\n    \"Abstract Concept\": {\n        \"priority\": \"\",\n        \"pattern\": \"[, {} {|}]\",\n        \"trigger\": \"\",\n        \"id\""
  },
  {
    "path": "docker-compose.yml",
    "chars": 549,
    "preview": "version: '3.9'\n\nservices:\n  stable-diffusion:\n    container_name: sd-webui\n    build:\n      context: .\n      dockerfile:"
  },
  {
    "path": "docs/1.Installation/1.one-click-installer.md",
    "chars": 942,
    "preview": "# Installer\n\n---\n\n### Sygil WebUI\n\nHome Page: https://github.com/Sygil-Dev/sygil-webui\n\n### Installation on Windows:\n\n\n\n"
  },
  {
    "path": "docs/1.Installation/2.windows-installation.md",
    "chars": 7532,
    "preview": "---\ntitle: Manual Windows Installation\n---\n\n<!--\nThis file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-we"
  },
  {
    "path": "docs/1.Installation/3.linux-installation.md",
    "chars": 7268,
    "preview": "---\ntitle: Manual Linux Installation\n---\n\n<!--\nThis file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webu"
  },
  {
    "path": "docs/1.Installation/4.docker-guide.md",
    "chars": 9612,
    "preview": "---\ntitle: Running Stable Diffusion WebUI Using Docker\n---\n<!--\nThis file is part of sygil-webui (https://github.com/Syg"
  },
  {
    "path": "docs/2.Streamlit/1.streamlit-interface.md",
    "chars": 8378,
    "preview": "# Streamlit Web UI Interface\n\n## Features:\n\n- Clean and easy to use UI: A clean and simple UI with an easy to use design"
  },
  {
    "path": "docs/3.Gradio/2.gradio-interface.md",
    "chars": 14531,
    "preview": "# Gradio Web UI Interface\n\n:::danger Warning\n\nThe Gradio WebUI is considered legacy or deprecated, it is no longer being"
  },
  {
    "path": "docs/4.post-processing.md",
    "chars": 4896,
    "preview": "---\ntitle: Post Processing\n---\n<!--\nThis file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\nCopyr"
  },
  {
    "path": "docs/5.concepts-library.md",
    "chars": 461,
    "preview": "# SD Concepts Library\n\n## SD Concepts Library\n\n---\n\n![](../images/streamlit/streamlit-concepts.png)\n\nThe Concept Library"
  },
  {
    "path": "docs/6.custom-models.md",
    "chars": 1949,
    "preview": "# Custom Models\n\n<!--\nThis file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\nCopyright 2022 Sygi"
  },
  {
    "path": "docusaurus.config.js",
    "chars": 6790,
    "preview": "// @ts-check\n// Note: type annotations allow type checking and IDEs autocompletion\n\nconst lightCodeTheme = require('pris"
  },
  {
    "path": "entrypoint.sh",
    "chars": 6104,
    "preview": "#!/bin/bash\n# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\n# Copyright 2022 Sygil-Dev "
  },
  {
    "path": "environment.yaml",
    "chars": 1166,
    "preview": "name: ldm\n# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\n# Copyright 2022 Sygil-Dev te"
  },
  {
    "path": "frontend/.eslintrc.js",
    "chars": 532,
    "preview": "module.exports = {\n  env: {\n    node: true\n  },\n  'extends': [\n    'plugin:vue/vue3-essential',\n    \"plugin:@typescript-"
  },
  {
    "path": "frontend/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "frontend/css/custom.css",
    "chars": 5400,
    "preview": "/* ----------------------------------------------\n * Generated by Animista on 2022-9-3 12:0:51\n * Licensed under FreeBSD"
  },
  {
    "path": "frontend/css/docs_custom.css",
    "chars": 1042,
    "preview": "/**\n * Any CSS included here will be global. The classic template\n * bundles Infima by default. Infima is a CSS framewor"
  },
  {
    "path": "frontend/css/no_progress_bar.css",
    "chars": 919,
    "preview": "/*\nThis file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\nCopyright 2022 Sygil-Dev team.\nThis pr"
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  {
    "path": "frontend/css/streamlit.main.css",
    "chars": 4476,
    "preview": "/*\nThis file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\nCopyright 2022 Sygil-Dev team.\nThis pr"
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  {
    "path": "frontend/css/styles.css",
    "chars": 2177,
    "preview": "/*\nThis file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\nCopyright 2022 Sygil-Dev team.\nThis pr"
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  {
    "path": "frontend/css_and_js.py",
    "chars": 1876,
    "preview": "# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\n# Copyright 2022 Sygil-Dev team.\n# This"
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  {
    "path": "frontend/dists/concept-browser/dist/assets/index.3ab9729b.css",
    "chars": 43238,
    "preview": "svg.no-preview-icon{fill:var(--text-color);width:72px;height:72px;opacity:.2}.no-preview{align-self:center;text-align:ce"
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  {
    "path": "frontend/dists/concept-browser/dist/assets/index.b5b962e4.js",
    "chars": 329030,
    "preview": "const vp=function(){const t=document.createElement(\"link\").relList;if(t&&t.supports&&t.supports(\"modulepreload\"))return;"
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  {
    "path": "frontend/dists/concept-browser/dist/index.html",
    "chars": 294,
    "preview": "<!DOCTYPE html>\n<html lang=\"en\">\n<head>\n    <meta charset=\"UTF-8\">\n    <title>Component Template</title>\n  <script type="
  },
  {
    "path": "frontend/dists/sd-gallery/dist/assets/index.4194368f.css",
    "chars": 22372,
    "preview": "@font-face{font-family:lg;src:url(data:font/woff2;base64,d09GMgABAAAAAAkcAAsAAAAAEogAAAjNAAEAAAAAAAAAAAAAAAAAAAAAAAAAAAA"
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  {
    "path": "frontend/dists/sd-gallery/dist/assets/index.aeaed602.js",
    "chars": 503361,
    "preview": "const zm=function(){const t=document.createElement(\"link\").relList;if(t&&t.supports&&t.supports(\"modulepreload\"))return;"
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  {
    "path": "frontend/dists/sd-gallery/dist/index.html",
    "chars": 294,
    "preview": "<!DOCTYPE html>\n<html lang=\"en\">\n<head>\n    <meta charset=\"UTF-8\">\n    <title>Component Template</title>\n  <script type="
  },
  {
    "path": "frontend/frontend.py",
    "chars": 72174,
    "preview": "# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\n# Copyright 2022 Sygil-Dev team.\n# This"
  },
  {
    "path": "frontend/image_metadata.py",
    "chars": 2869,
    "preview": "# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\n# Copyright 2022 Sygil-Dev team.\n# This"
  },
  {
    "path": "frontend/index.html",
    "chars": 208,
    "preview": "<!DOCTYPE html>\n<html lang=\"en\">\n<head>\n    <meta charset=\"UTF-8\">\n    <title>Component Template</title>\n</head>\n<body>\n"
  },
  {
    "path": "frontend/job_manager.py",
    "chars": 26567,
    "preview": "# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\n# Copyright 2022 Sygil-Dev team.\n# This"
  },
  {
    "path": "frontend/js/index.js",
    "chars": 5891,
    "preview": "window.SD = (() => {\n  /*\n   * Painterro is made a field of the SD global object\n   * To provide convinience when using "
  },
  {
    "path": "frontend/package.json",
    "chars": 912,
    "preview": "{\n  \"name\": \"@codedealer/streamlit_template_vue\",\n  \"version\": \"0.1.0\",\n  \"description\": \"Starter template to build Stre"
  },
  {
    "path": "frontend/src/Component.vue",
    "chars": 6668,
    "preview": "<template>\n  <div class=\"bootstrap-wrapper pt-4\">\n    <div class=\"concept-gallery row\">\n      <div v-for=\"concept in arg"
  },
  {
    "path": "frontend/src/app.vue",
    "chars": 42700,
    "preview": "<!--\n  We bootstrap our Component to Streamlit with our scoped slot in the top-level App.\n  This is where scoped slot pa"
  },
  {
    "path": "frontend/src/env.d.ts",
    "chars": 281,
    "preview": "/// <reference types=\"vite/client\" />\n\ndeclare module '*.vue' {\n  import type { DefineComponent } from 'vue'\n  // eslint"
  },
  {
    "path": "frontend/src/main.ts",
    "chars": 90,
    "preview": "import { createApp } from 'vue'\nimport App from './app.vue'\n\ncreateApp(App).mount('#app')\n"
  },
  {
    "path": "frontend/src/streamlit/StreamlitVue.ts",
    "chars": 773,
    "preview": "/**\n * Vue.js specific composables\n */\nimport { onMounted, onUpdated } from \"vue\"\nimport { Streamlit } from \"streamlit-c"
  },
  {
    "path": "frontend/src/streamlit/WithStreamlitConnection.vue",
    "chars": 2335,
    "preview": "<template>\n  <div>\n    <!--  Error boundary. If our wrapped component threw an error, display it. -->\n    <div v-if=\"com"
  },
  {
    "path": "frontend/src/streamlit/index.ts",
    "chars": 661,
    "preview": "/**\n * @license\n * Copyright 2018-2020 Streamlit Inc.\n *\n * Licensed under the Apache License, Version 2.0 (the \"License"
  },
  {
    "path": "frontend/tsconfig.json",
    "chars": 716,
    "preview": "{\n  \"compilerOptions\": {\n    \"baseUrl\": \".\",\n    \"outDir\": \"dist\",\n    \"declaration\": false,\n    \"target\": \"esnext\",\n   "
  },
  {
    "path": "frontend/tsconfig.node.json",
    "chars": 143,
    "preview": "{\n  \"compilerOptions\": {\n    \"composite\": false,\n    \"module\": \"esnext\",\n    \"moduleResolution\": \"node\"\n  },\n  \"include\""
  },
  {
    "path": "frontend/ui_functions.py",
    "chars": 10419,
    "preview": "# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\n# Copyright 2022 Sygil-Dev team.\n# This"
  },
  {
    "path": "frontend/vite.config.ts",
    "chars": 435,
    "preview": "import { resolve } from 'path'\nimport { defineConfig } from 'vite'\nimport vue from '@vitejs/plugin-vue'\n\nexport default "
  },
  {
    "path": "horde_bridge.cmd",
    "chars": 3647,
    "preview": "@echo off\n:: This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\n:: Copyright 2022 Sygil-Dev "
  },
  {
    "path": "horde_bridge.sh",
    "chars": 7485,
    "preview": "#!/bin/bash -i\n# This file is part of sygil-webui (https://github.com/Sygil-Dev/sygil-webui/).\n\n# Copyright 2022 Sygil-D"
  },
  {
    "path": "installer/create_installers.sh",
    "chars": 748,
    "preview": "#!/bin/bash\n\n# For developers only! Not for users!\n# This creates the installer zip files that will be distributed to us"
  },
  {
    "path": "installer/install.bat",
    "chars": 3665,
    "preview": "@echo off\n\n@rem This script will install git and conda (if not found on the PATH variable)\n@rem  using micromamba (an 8m"
  },
  {
    "path": "installer/install.sh",
    "chars": 3335,
    "preview": "#!/bin/bash\n\n# This script will install git and conda (if not found on the PATH variable)\n#  using micromamba (an 8mb st"
  },
  {
    "path": "ldm/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "ldm/data/__init__.py",
    "chars": 5978,
    "preview": "import torch\nfrom torch.utils.data import DataLoader\nfrom torchvision import transforms\nfrom torchvision.transforms.func"
  },
  {
    "path": "ldm/data/base.py",
    "chars": 657,
    "preview": "from abc import abstractmethod\nfrom torch.utils.data import IterableDataset\n\n\nclass Txt2ImgIterableBaseDataset(IterableD"
  },
  {
    "path": "ldm/data/coco_karpathy_dataset.py",
    "chars": 4469,
    "preview": "import os\nimport json\n\nfrom torch.utils.data import Dataset\nfrom torchvision.datasets.utils import download_url\n\nfrom PI"
  },
  {
    "path": "ldm/data/flickr30k_dataset.py",
    "chars": 3171,
    "preview": "import os\nimport json\n\nfrom torch.utils.data import Dataset\nfrom torchvision.datasets.utils import download_url\n\nfrom PI"
  },
  {
    "path": "ldm/data/imagenet.py",
    "chars": 16042,
    "preview": "import os, yaml, pickle, shutil, tarfile, glob\nimport cv2\nimport albumentations\nimport PIL\nimport numpy as np\nimport tor"
  },
  {
    "path": "ldm/data/lsun.py",
    "chars": 3373,
    "preview": "import os\nimport numpy as np\nimport PIL\nfrom PIL import Image\nfrom torch.utils.data import Dataset\nfrom torchvision impo"
  },
  {
    "path": "ldm/data/nlvr_dataset.py",
    "chars": 2589,
    "preview": "import os\nimport json\nimport random\n\nfrom torch.utils.data import Dataset\nfrom torchvision.datasets.utils import downloa"
  },
  {
    "path": "ldm/data/nocaps_dataset.py",
    "chars": 1086,
    "preview": "import os\nimport json\n\nfrom torch.utils.data import Dataset\nfrom torchvision.datasets.utils import download_url\n\nfrom PI"
  },
  {
    "path": "ldm/data/personalized.py",
    "chars": 5451,
    "preview": "import os\nimport numpy as np\nimport PIL\nfrom PIL import Image\nfrom torch.utils.data import Dataset\nfrom torchvision impo"
  },
  {
    "path": "ldm/data/personalized_file.py",
    "chars": 4969,
    "preview": "import os\nimport numpy as np\nimport PIL\nfrom PIL import Image\nfrom torch.utils.data import Dataset\nfrom torchvision impo"
  },
  {
    "path": "ldm/data/pretrain_dataset.py",
    "chars": 1542,
    "preview": "import json\nimport os\n\nfrom torch.utils.data import Dataset\n\nfrom PIL import Image\nfrom PIL import ImageFile\n\nImageFile."
  },
  {
    "path": "ldm/data/util.py",
    "chars": 632,
    "preview": "import torch\n\nfrom ldm.modules.midas.api import load_midas_transform\n\n\nclass AddMiDaS(object):\n    def __init__(self, mo"
  },
  {
    "path": "ldm/data/video_dataset.py",
    "chars": 4259,
    "preview": "from torch.utils.data import Dataset\nfrom torchvision.datasets.utils import download_url\n\nimport torch\nimport numpy as n"
  },
  {
    "path": "ldm/data/vqa_dataset.py",
    "chars": 3500,
    "preview": "import os\nimport json\nfrom PIL import Image\n\nimport torch\nfrom torch.utils.data import Dataset\nfrom data.utils import pr"
  },
  {
    "path": "ldm/devices/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "ldm/devices/devices.py",
    "chars": 892,
    "preview": "import torch\nfrom torch import autocast\nfrom contextlib import nullcontext\n\n\ndef choose_torch_device() -> str:\n    \"\"\"Co"
  },
  {
    "path": "ldm/lr_scheduler.py",
    "chars": 4286,
    "preview": "import numpy as np\n\n\nclass LambdaWarmUpCosineScheduler:\n    \"\"\"\n    note: use with a base_lr of 1.0\n    \"\"\"\n\n    def __i"
  },
  {
    "path": "ldm/models/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "ldm/models/autoencoder.py",
    "chars": 18075,
    "preview": "import torch\nimport pytorch_lightning as pl\nimport torch.nn.functional as F\nfrom contextlib import contextmanager\n\nfrom "
  },
  {
    "path": "ldm/models/blip.py",
    "chars": 9895,
    "preview": "\"\"\"\n * Copyright (c) 2022, salesforce.com, inc.\n * All rights reserved.\n * SPDX-License-Identifier: BSD-3-Clause\n * For "
  },
  {
    "path": "ldm/models/blip_itm.py",
    "chars": 2839,
    "preview": "from models.med import BertConfig, BertModel\n\nimport torch\nfrom torch import nn\nimport torch.nn.functional as F\n\nfrom mo"
  },
  {
    "path": "ldm/models/blip_nlvr.py",
    "chars": 4083,
    "preview": "from models.med import BertConfig\nfrom models.nlvr_encoder import BertModel\nfrom models.vit import interpolate_pos_embed"
  },
  {
    "path": "ldm/models/blip_pretrain.py",
    "chars": 15530,
    "preview": "\"\"\"\n * Copyright (c) 2022, salesforce.com, inc.\n * All rights reserved.\n * SPDX-License-Identifier: BSD-3-Clause\n * For "
  },
  {
    "path": "ldm/models/blip_retrieval.py",
    "chars": 13192,
    "preview": "from models.med import BertConfig, BertModel\n\nimport torch\nfrom torch import nn\nimport torch.nn.functional as F\n\nfrom mo"
  },
  {
    "path": "ldm/models/blip_vqa.py",
    "chars": 8040,
    "preview": "from models.med import BertConfig, BertModel, BertLMHeadModel\nfrom models.blip import create_vit, init_tokenizer, load_c"
  },
  {
    "path": "ldm/models/diffusion/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "ldm/models/diffusion/classifier.py",
    "chars": 10695,
    "preview": "import os\nimport torch\nimport pytorch_lightning as pl\nfrom omegaconf import OmegaConf\nfrom torch.nn import functional as"
  },
  {
    "path": "ldm/models/diffusion/ddim.py",
    "chars": 13535,
    "preview": "\"\"\"SAMPLING ONLY.\"\"\"\n\nimport torch\nimport numpy as np\nfrom tqdm import tqdm\n\nfrom ldm.modules.diffusionmodules.util impo"
  },
  {
    "path": "ldm/models/diffusion/ddpm.py",
    "chars": 71699,
    "preview": "\"\"\"\nwild mixture of\nhttps://github.com/lucidrains/denoising-diffusion-pytorch/blob/7706bdfc6f527f58d33f84b7b522e61e6e316"
  },
  {
    "path": "ldm/models/diffusion/dpm_solver/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "ldm/models/diffusion/dpm_solver/dpm_solver.py",
    "chars": 69897,
    "preview": "import torch\nimport math\nfrom tqdm import tqdm\n\n\nclass NoiseScheduleVP:\n    def __init__(\n        self,\n        schedule"
  },
  {
    "path": "ldm/models/diffusion/dpm_solver/sampler.py",
    "chars": 3163,
    "preview": "\"\"\"SAMPLING ONLY.\"\"\"\nimport torch\n\nfrom .dpm_solver import NoiseScheduleVP, model_wrapper, DPM_Solver\n\n\nMODEL_TYPES = {\""
  },
  {
    "path": "ldm/models/diffusion/kdiffusion.py",
    "chars": 2251,
    "preview": "import k_diffusion as K\nimport torch\nimport torch.nn as nn\n\n\nclass KDiffusionSampler:\n    def __init__(self, m, sampler,"
  },
  {
    "path": "ldm/models/diffusion/plms.py",
    "chars": 12814,
    "preview": "\"\"\"SAMPLING ONLY.\"\"\"\n\nimport torch\nimport numpy as np\nfrom tqdm import tqdm\n\nfrom ldm.modules.diffusionmodules.util impo"
  },
  {
    "path": "ldm/models/diffusion/sampling_util.py",
    "chars": 742,
    "preview": "def append_dims(x, target_dims):\n    \"\"\"Appends dimensions to the end of a tensor until it has target_dims dimensions.\n "
  },
  {
    "path": "ldm/models/med.py",
    "chars": 42977,
    "preview": "\"\"\"\n * Copyright (c) 2022, salesforce.com, inc.\n * All rights reserved.\n * SPDX-License-Identifier: BSD-3-Clause\n * For "
  },
  {
    "path": "ldm/models/nlvr_encoder.py",
    "chars": 37856,
    "preview": "import math\nfrom typing import Tuple\n\nimport torch\nfrom torch import Tensor, device, nn\nimport torch.utils.checkpoint\nfr"
  },
  {
    "path": "ldm/models/vit.py",
    "chars": 15641,
    "preview": "\"\"\"\n * Copyright (c) 2022, salesforce.com, inc.\n * All rights reserved.\n * SPDX-License-Identifier: BSD-3-Clause\n * For "
  },
  {
    "path": "ldm/modules/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "ldm/modules/attention.py",
    "chars": 11133,
    "preview": "from inspect import isfunction\nimport math\nimport torch\nimport torch.nn.functional as F\nfrom torch import nn, einsum\nfro"
  },
  {
    "path": "ldm/modules/diffusionmodules/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "ldm/modules/diffusionmodules/model.py",
    "chars": 33299,
    "preview": "# pytorch_diffusion + derived encoder decoder\nimport gc\nimport math\nimport torch\nimport torch.nn as nn\nimport numpy as n"
  },
  {
    "path": "ldm/modules/diffusionmodules/openaimodel.py",
    "chars": 35786,
    "preview": "from abc import abstractmethod\nimport math\n\nimport numpy as np\nimport torch as th\nimport torch.nn as nn\nimport torch.nn."
  },
  {
    "path": "ldm/modules/diffusionmodules/upscaling.py",
    "chars": 3666,
    "preview": "import torch\nimport torch.nn as nn\nimport numpy as np\nfrom functools import partial\n\nfrom ldm.modules.diffusionmodules.u"
  },
  {
    "path": "ldm/modules/diffusionmodules/util.py",
    "chars": 9989,
    "preview": "# adopted from\n# https://github.com/openai/improved-diffusion/blob/main/improved_diffusion/gaussian_diffusion.py\n# and\n#"
  },
  {
    "path": "ldm/modules/distributions/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "ldm/modules/distributions/distributions.py",
    "chars": 3095,
    "preview": "import torch\nimport numpy as np\n\n\nclass AbstractDistribution:\n    def sample(self):\n        raise NotImplementedError()\n"
  },
  {
    "path": "ldm/modules/ema.py",
    "chars": 3066,
    "preview": "import torch\nfrom torch import nn\n\n\nclass LitEma(nn.Module):\n    def __init__(self, model, decay=0.9999, use_num_upates="
  },
  {
    "path": "ldm/modules/embedding_manager.py",
    "chars": 8469,
    "preview": "import torch\nfrom torch import nn\n\n\nfrom ldm.data.personalized import per_img_token_list\nfrom functools import partial\n\n"
  },
  {
    "path": "ldm/modules/encoders/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "ldm/modules/encoders/modules.py",
    "chars": 8806,
    "preview": "import torch\nimport torch.nn as nn\nfrom functools import partial\nimport clip\nfrom einops import repeat\nfrom transformers"
  },
  {
    "path": "ldm/modules/image_degradation/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "ldm/modules/image_degradation/bsrgan.py",
    "chars": 26144,
    "preview": "# -*- coding: utf-8 -*-\n\"\"\"\n# --------------------------------------------\n# Super-Resolution\n# ------------------------"
  },
  {
    "path": "ldm/modules/image_degradation/bsrgan_light.py",
    "chars": 22973,
    "preview": "# -*- coding: utf-8 -*-\nimport numpy as np\nimport cv2\nimport torch\n\nfrom functools import partial\nimport random\nfrom sci"
  },
  {
    "path": "ldm/modules/image_degradation/utils_image.py",
    "chars": 29700,
    "preview": "import os\nimport math\nimport random\nimport numpy as np\nimport torch\nimport cv2\nfrom torchvision.utils import make_grid\nf"
  },
  {
    "path": "ldm/modules/losses/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "ldm/modules/losses/contperceptual.py",
    "chars": 5976,
    "preview": "import torch\nimport torch.nn as nn\n\nfrom taming.modules.losses.vqperceptual import *  # TODO: taming dependency yes/no?\n"
  },
  {
    "path": "ldm/modules/losses/vqperceptual.py",
    "chars": 8337,
    "preview": "import torch\nfrom torch import nn\nimport torch.nn.functional as F\n\nfrom taming.modules.discriminator.model import NLayer"
  },
  {
    "path": "ldm/modules/midas/api.py",
    "chars": 5425,
    "preview": "# based on https://github.com/isl-org/MiDaS\n\nimport cv2\nimport torch\nimport torch.nn as nn\nfrom torchvision.transforms i"
  },
  {
    "path": "ldm/modules/midas/midas/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "ldm/modules/midas/midas/base_model.py",
    "chars": 367,
    "preview": "import torch\n\n\nclass BaseModel(torch.nn.Module):\n    def load(self, path):\n        \"\"\"Load model from file.\n\n        Arg"
  },
  {
    "path": "ldm/modules/midas/midas/blocks.py",
    "chars": 9800,
    "preview": "import torch\nimport torch.nn as nn\n\nfrom .vit import (\n    _make_pretrained_vitb_rn50_384,\n    _make_pretrained_vitl16_3"
  },
  {
    "path": "ldm/modules/midas/midas/dpt_depth.py",
    "chars": 3097,
    "preview": "import torch\nimport torch.nn as nn\n\nfrom .base_model import BaseModel\nfrom .blocks import (\n    FeatureFusionBlock_custo"
  },
  {
    "path": "ldm/modules/midas/midas/midas_net.py",
    "chars": 2726,
    "preview": "\"\"\"MidashNet: Network for monocular depth estimation trained by mixing several datasets.\nThis file contains code that is"
  },
  {
    "path": "ldm/modules/midas/midas/midas_net_custom.py",
    "chars": 5845,
    "preview": "\"\"\"MidashNet: Network for monocular depth estimation trained by mixing several datasets.\nThis file contains code that is"
  },
  {
    "path": "ldm/modules/midas/midas/transforms.py",
    "chars": 7854,
    "preview": "import numpy as np\nimport cv2\nimport math\n\n\ndef apply_min_size(sample, size, image_interpolation_method=cv2.INTER_AREA):"
  },
  {
    "path": "ldm/modules/midas/midas/vit.py",
    "chars": 14618,
    "preview": "import torch\nimport torch.nn as nn\nimport timm\nimport types\nimport math\nimport torch.nn.functional as F\n\n\nclass Slice(nn"
  },
  {
    "path": "ldm/modules/midas/utils.py",
    "chars": 4588,
    "preview": "\"\"\"Utils for monoDepth.\"\"\"\nimport sys\nimport re\nimport numpy as np\nimport cv2\nimport torch\n\n\ndef read_pfm(path):\n    \"\"\""
  },
  {
    "path": "ldm/modules/x_transformer.py",
    "chars": 20772,
    "preview": "\"\"\"shout-out to https://github.com/lucidrains/x-transformers/tree/main/x_transformers\"\"\"\nimport torch\nfrom torch import "
  },
  {
    "path": "ldm/util.py",
    "chars": 5838,
    "preview": "import importlib\n\nimport torch\nimport numpy as np\nfrom collections import abc\n\nimport multiprocessing as mp\nfrom threadi"
  },
  {
    "path": "optimizedSD/ddpm.py",
    "chars": 49948,
    "preview": "\"\"\"\nwild mixture of\nhttps://github.com/lucidrains/denoising-diffusion-pytorch/blob/7706bdfc6f527f58d33f84b7b522e61e6e316"
  },
  {
    "path": "optimizedSD/diffusers_txt2img.py",
    "chars": 502,
    "preview": "import torch\nfrom diffusers import LDMTextToImagePipeline\n\npipe = LDMTextToImagePipeline.from_pretrained(\n    \"CompVis/s"
  },
  {
    "path": "optimizedSD/openaimodelSplit.py",
    "chars": 30535,
    "preview": "from abc import abstractmethod\nimport math\nimport numpy as np\nimport torch as th\nimport torch.nn as nn\nimport torch.nn.f"
  },
  {
    "path": "optimizedSD/optimUtils.py",
    "chars": 2423,
    "preview": "import os\nimport pandas as pd\n\n\ndef split_weighted_subprompts(text):\n    \"\"\"\n    grabs all text up to the first occurren"
  },
  {
    "path": "optimizedSD/optimized_img2img.py",
    "chars": 11329,
    "preview": "import argparse, os, re\nimport torch\nimport numpy as np\nfrom random import randint\nfrom omegaconf import OmegaConf\nfrom "
  },
  {
    "path": "optimizedSD/optimized_txt2img.py",
    "chars": 10344,
    "preview": "import argparse, os, re\nimport torch\nimport numpy as np\nfrom random import randint\nfrom omegaconf import OmegaConf\nfrom "
  }
]

// ... and 90 more files (download for full content)

About this extraction

This page contains the full source code of the Sygil-Dev/sygil-webui GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 290 files (21.8 MB), approximately 2.5M tokens, and a symbol index with 6488 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.

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