From 0cc646f1533d7916549d7bfc560012dc021c33aa Mon Sep 17 00:00:00 2001 From: Dref360 Date: Sun, 19 Jun 2022 16:08:29 -0400 Subject: [PATCH 01/10] Add structure for mkdocs instead of Sphinx --- .github/ISSUE_TEMPLATE/bug_report.md | 4 +- CONTRIBUTING.md | 2 +- README.md | 6 +- .../dirichlet_calibration.md | 0 docs/{reports => blog}/double_descend.md | 0 docs/{reports => blog}/images/ALL_active.png | Bin .../images/BALDvsCBALD_active.png | Bin docs/{reports => blog}/images/CBALDvsBALD.png | Bin .../images/CBALDvsBALDECE.png | Bin .../images/EntvsCEnt_active.png | Bin .../images/dirichlet_calib.png | Bin .../images/doubledescend_01.png | Bin .../images/doubledescend_02.png | Bin .../images/doubledescend_03.png | Bin .../images/doubledescend_04.png | Bin docs/conf.py | 231 ---- docs/index.md | 41 +- docs/industry/index.md | 0 docs/{tutorials => industry}/label-studio.md | 0 docs/research/index.md | 2 + .../literature/Additional papers/dmi.md | 0 .../literature/Additional papers/duq.md | 0 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| 2 + docs/user_guide/index.md | 2 +- mkdocs.yml | 50 + poetry.lock | 1128 +++++------------ pyproject.toml | 19 +- 49 files changed, 367 insertions(+), 1122 deletions(-) rename docs/{reports => blog}/dirichlet_calibration.md (100%) rename docs/{reports => blog}/double_descend.md (100%) rename docs/{reports => blog}/images/ALL_active.png (100%) rename docs/{reports => blog}/images/BALDvsCBALD_active.png (100%) rename docs/{reports => blog}/images/CBALDvsBALD.png (100%) rename docs/{reports => blog}/images/CBALDvsBALDECE.png (100%) rename docs/{reports => blog}/images/EntvsCEnt_active.png (100%) rename docs/{reports => blog}/images/dirichlet_calib.png (100%) rename docs/{reports => blog}/images/doubledescend_01.png (100%) rename docs/{reports => blog}/images/doubledescend_02.png (100%) rename docs/{reports => blog}/images/doubledescend_03.png (100%) rename docs/{reports => blog}/images/doubledescend_04.png (100%) delete mode 100644 docs/conf.py create mode 100644 docs/industry/index.md 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--- a/.github/ISSUE_TEMPLATE/bug_report.md +++ b/.github/ISSUE_TEMPLATE/bug_report.md @@ -15,7 +15,7 @@ A clear and concise description of what the bug is. Some advices: * Please don't use custom data or custom paths. * Use random arrays or even np.ones, np.zeros. -* The example should run with BaaL (and deps) alone. +* The example should run with Baal (and deps) alone. * Should be Python3 compatible. * Should not be OS specific. * The file should reproduce the bug with **high* fidelity. @@ -29,7 +29,7 @@ A clear and concise description of what you expected to happen. **Vesion (please complete the following information):** - OS: - Python: - - BaaL version: + - Baal version: **Additional context** Add any other context about the problem here. diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 8afb10f0..5e87b0a4 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -1,4 +1,4 @@ -## How can you contribute to BaaL. +## How can you contribute to Baal. ### Bug fixes diff --git a/README.md b/README.md index 1d264f6e..a03ea2bb 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@

-

Bayesian Active Learning (BaaL) +

Bayesian Active Learning (Baal)
Python CI @@ -21,7 +21,7 @@

-BaaL is an active learning library developed at +Baal is an active learning library developed at [ElementAI](https://www.elementai.com/). This repository contains techniques and reusable components to make active learning accessible for all. @@ -88,7 +88,7 @@ The framework consists of four main parts, as demonstrated in the flowchart belo - ActiveLearningLoop

- +

To get started, wrap your dataset in our _[**ActiveLearningDataset**](baal/active/dataset.py)_ class. This will ensure that the dataset is split into diff --git a/docs/reports/dirichlet_calibration.md b/docs/blog/dirichlet_calibration.md similarity index 100% rename from docs/reports/dirichlet_calibration.md rename to docs/blog/dirichlet_calibration.md diff --git a/docs/reports/double_descend.md b/docs/blog/double_descend.md similarity index 100% rename from docs/reports/double_descend.md rename to docs/blog/double_descend.md diff --git a/docs/reports/images/ALL_active.png b/docs/blog/images/ALL_active.png similarity index 100% rename from docs/reports/images/ALL_active.png rename to docs/blog/images/ALL_active.png diff --git a/docs/reports/images/BALDvsCBALD_active.png b/docs/blog/images/BALDvsCBALD_active.png similarity index 100% rename from docs/reports/images/BALDvsCBALD_active.png rename to docs/blog/images/BALDvsCBALD_active.png diff --git a/docs/reports/images/CBALDvsBALD.png b/docs/blog/images/CBALDvsBALD.png similarity index 100% rename from docs/reports/images/CBALDvsBALD.png rename to docs/blog/images/CBALDvsBALD.png diff --git a/docs/reports/images/CBALDvsBALDECE.png b/docs/blog/images/CBALDvsBALDECE.png similarity index 100% rename from docs/reports/images/CBALDvsBALDECE.png rename to docs/blog/images/CBALDvsBALDECE.png diff --git a/docs/reports/images/EntvsCEnt_active.png b/docs/blog/images/EntvsCEnt_active.png similarity index 100% rename from docs/reports/images/EntvsCEnt_active.png rename to docs/blog/images/EntvsCEnt_active.png diff --git a/docs/reports/images/dirichlet_calib.png b/docs/blog/images/dirichlet_calib.png similarity index 100% rename from docs/reports/images/dirichlet_calib.png rename to docs/blog/images/dirichlet_calib.png diff --git a/docs/reports/images/doubledescend_01.png b/docs/blog/images/doubledescend_01.png similarity index 100% rename from docs/reports/images/doubledescend_01.png rename to docs/blog/images/doubledescend_01.png diff --git a/docs/reports/images/doubledescend_02.png b/docs/blog/images/doubledescend_02.png similarity index 100% rename from docs/reports/images/doubledescend_02.png rename to docs/blog/images/doubledescend_02.png diff --git a/docs/reports/images/doubledescend_03.png b/docs/blog/images/doubledescend_03.png similarity index 100% rename from docs/reports/images/doubledescend_03.png rename to docs/blog/images/doubledescend_03.png diff --git a/docs/reports/images/doubledescend_04.png b/docs/blog/images/doubledescend_04.png similarity index 100% rename from docs/reports/images/doubledescend_04.png rename to docs/blog/images/doubledescend_04.png diff --git a/docs/conf.py b/docs/conf.py deleted file mode 100644 index 14c88552..00000000 --- a/docs/conf.py +++ /dev/null @@ -1,231 +0,0 @@ -# -*- coding: utf-8 -*- -# -# Configuration file for the Sphinx documentation builder. -# -# This file does only contain a selection of the most common options. For a -# full list see the documentation: -# http://www.sphinx-doc.org/en/master/config - -# -- Path setup -------------------------------------------------------------- - -# If extensions (or modules to document with autodoc) are in another directory, -# add these directories to sys.path here. If the directory is relative to the -# documentation root, use os.path.abspath to make it absolute, like shown here. -# -import os -import pathlib -import shutil -import sys - -from recommonmark.transform import AutoStructify -import sphinx_rtd_theme -from recommonmark.parser import CommonMarkParser - -pjoin = os.path.join -parent_dir = pathlib.Path(__file__).resolve().parents[1] -sys.path.insert(0, os.path.abspath('./../')) - -shutil.rmtree('notebooks', ignore_errors=True) -shutil.copytree(pjoin(parent_dir, 'notebooks'), 'notebooks') - -# -- Project information ----------------------------------------------------- - -# Disable notebook execution -nbsphinx_execute = 'never' - -project = 'baal' -copyright = '2019, Parmida Atighehchian, Frédéric Branchaud-Charron, Jan Freyberg' -author = 'Parmida Atighehchian, Frédéric Branchaud-Charron, Jan Freyberg' - -# The short X.Y version -version = '' -# The full version, including alpha/beta/rc tags -release = '1.6.0' - -# -- General configuration --------------------------------------------------- - -# If your documentation needs a minimal Sphinx version, state it here. -# -# needs_sphinx = '1.0' - -# Add any Sphinx extension module names here, as strings. They can be -# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom -# ones. -extensions = [ - 'sphinx.ext.autodoc', - 'sphinx.ext.autosummary', - 'sphinx.ext.doctest', - 'sphinx.ext.todo', - 'sphinx.ext.mathjax', - 'sphinx.ext.viewcode', - 'sphinx_copybutton', - "sphinx_automodapi.automodapi", - "nbsphinx", - "recommonmark", - "numpydoc", - "sphinx.ext.napoleon" -] - -# We need to mock these packages to compile without deps. -autodoc_mock_imports = ["PIL", "tqdm", "structlog", "torch", "torchvision", "numpy", "sklearn", - "scipy", "baal.utils.cuda_utils", "transformers", "pytorch_lightning", - "datasets"] - -# Add any paths that contain templates here, relative to this directory. -templates_path = ['_templates'] - - - -source_parsers = { - '.md': CommonMarkParser, -} - -# The suffix(es) of source filenames. -# You can specify multiple suffix as a list of string: -# source_suffix = ['.rst', '.md', '.ipynb'] - -# The master toctree document. -master_doc = 'index' - -# The language for content autogenerated by Sphinx. Refer to documentation -# for a list of supported languages. -# -# This is also used if you do content translation via gettext catalogs. -# Usually you set "language" from the command line for these cases. -language = None - -# List of patterns, relative to source directory, that match files and -# directories to ignore when looking for source files. -# This pattern also affects html_static_path and html_extra_path. -exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store', '.ipynb_checkpoints'] - -# The name of the Pygments (syntax highlighting) style to use. -pygments_style = None - -# -- Options for HTML output ------------------------------------------------- - -# The theme to use for HTML and HTML Help pages. See the documentation for -# a list of builtin themes. -# -html_theme = "sphinx_rtd_theme" -html_theme_path = [sphinx_rtd_theme.get_html_theme_path()] -html_logo = "_static/images/logo-transparent.png" - -# Theme options are theme-specific and customize the look and feel of a theme -# further. For a list of options available for each theme, see the -# documentation. -# -# html_theme_options = {} - -# Add any paths that contain custom static files (such as style sheets) here, -# relative to this directory. They are copied after the builtin static files, -# so a file named "default.css" will overwrite the builtin "default.css". -html_static_path = ['_static', '_static/images'] -html_css_files = [ - 'css/default.css', -] - -# Custom sidebar templates, must be a dictionary that maps document names -# to template names. -# -# The default sidebars (for documents that don't match any pattern) are -# defined by theme itself. Builtin themes are using these templates by -# default: ``['localtoc.html', 'relations.html', 'sourcelink.html', -# 'searchbox.html']``. -# -# html_sidebars = {} - - -# -- Options for HTMLHelp output --------------------------------------------- - -# Output file base name for HTML help builder. -htmlhelp_basename = 'baaldoc' - -# -- Options for LaTeX output ------------------------------------------------ - -latex_elements = { - # The paper size ('letterpaper' or 'a4paper'). - # - # 'papersize': 'letterpaper', - # The font size ('10pt', '11pt' or '12pt'). - # - # 'pointsize': '10pt', - # Additional stuff for the LaTeX preamble. - # - # 'preamble': '', - # Latex figure (float) alignment - # - # 'figure_align': 'htbp', -} - -# Grouping the document tree into LaTeX files. List of tuples -# (source start file, target name, title, -# author, documentclass [howto, manual, or own class]). -latex_documents = [ - ( - master_doc, - 'baal.tex', - 'baal Documentation', - 'Parmida Atighehchian, Frédéric Branchaud-Charron, Jan Freyberg', - 'manual', - ) -] - -# -- Options for manual page output ------------------------------------------ - -# One entry per manual page. List of tuples -# (source start file, name, description, authors, manual section). -man_pages = [(master_doc, 'baal', 'baal Documentation', [author], 1)] - -# -- Options for Texinfo output ---------------------------------------------- - -# Grouping the document tree into Texinfo files. List of tuples -# (source start file, target name, title, author, -# dir menu entry, description, category) -texinfo_documents = [ - ( - master_doc, - 'baal', - 'baal Documentation', - author, - 'baal', - 'One line description of project.', - 'Miscellaneous', - ) -] - -# -- Options for Epub output ------------------------------------------------- - -# Bibliographic Dublin Core info. -epub_title = project - -# The unique identifier of the text. This can be a ISBN number -# or the project homepage. -# -# epub_identifier = '' - -# A unique identification for the text. -# -# epub_uid = '' - -# A list of files that should not be packed into the epub file. -epub_exclude_files = ['search.html'] - -# -- Extension configuration ------------------------------------------------- - -# -- Options for todo extension ---------------------------------------------- - -# If true, `todo` and `todoList` produce output, else they produce nothing. -todo_include_todos = True - - -# At the bottom of conf.py -def setup(app): - app.add_config_value('recommonmark_config', { - 'enable_auto_toc_tree': True, - 'enable_eval_rst': True, - 'enable_math': True, - 'enable_inline_math': True, - 'auto_toc_tree_section': 'Contents', - }, True) - app.add_transform(AutoStructify) diff --git a/docs/index.md b/docs/index.md index 30c794f5..12cbc38e 100644 --- a/docs/index.md +++ b/docs/index.md @@ -1,16 +1,6 @@ -```eval_rst -.. baal documentation master file, created by - sphinx-quickstart on Thu Apr 4 14:15:25 2019. - You can adapt this file completely to your liking, but it should at least - contain the root `toctree` directive. -``` - -# Welcome to the documentation for baal (**ba**yesian **a**ctive **l**earning) +# Welcome to Baal (**ba**yesian **a**ctive **l**earning) - -
Star - -BaaL is a Bayesian active learning library. +Baal is a Bayesian active learning library. We provide methods to estimate sampling from the posterior distribution in order to maximize the efficiency of labelling during active learning. Our library is suitable for research and industrial applications. @@ -23,20 +13,20 @@ If you have any question, we are reachable on [Slack](https://join.slack.com/t/b For support, we have several ways to help you: -* Our [FAQ](faq.md) +* Our [FAQ](support/faq.md) * Submit an issue on Github [here](https://github.com/ElementAI/baal/issues/new/choose) * Join our [Slack](https://join.slack.com/t/baal-world/shared_invite/zt-z0izhn4y-Jt6Zu5dZaV2rsAS9sdISfg)! -```eval_rst -.. toctree:: - :caption: Learn more about BaaL - :maxdepth: 1 +## :material-file-tree: Learn more about Baal + +* [:material-link: User Guide](user_guide) +* [:material-book-education: Active learning dataset and training loop classes](notebooks/fundamentals/active-learning.ipynb) +* [:material-book-education: Methods for approximating bayesian posteriors](notebooks/fundamentals/posteriors.ipynb) +* [:material-link: API Index](api) +* [:material-help: FAQ](support/faq.md) - User guide - Active learning dataset and training loop classes - Methods for approximating bayesian posteriors - API Index - FAQ +## :material-file-tree: Industry +* [:material-book-education: Active learning dataset and training loop classes](notebooks/fundamentals/active-learning.ipynb) .. toctree :: :caption: Tutorials @@ -70,10 +60,3 @@ For support, we have several ways to help you: Background literature Cheat Sheet ``` - -## Indices and tables - -```eval_rst -* :ref:`genindex` -* :ref:`search` -``` diff --git a/docs/industry/index.md b/docs/industry/index.md new file mode 100644 index 00000000..e69de29b diff --git a/docs/tutorials/label-studio.md b/docs/industry/label-studio.md similarity index 100% rename from docs/tutorials/label-studio.md rename to docs/industry/label-studio.md diff --git a/docs/research/index.md b/docs/research/index.md new file mode 100644 index 00000000..64473875 --- /dev/null +++ b/docs/research/index.md @@ -0,0 +1,2 @@ +# Bayesian active learning research + diff --git a/docs/literature/Additional papers/dmi.md b/docs/research/literature/Additional papers/dmi.md similarity index 100% rename from docs/literature/Additional papers/dmi.md rename to docs/research/literature/Additional papers/dmi.md diff --git a/docs/literature/Additional papers/duq.md b/docs/research/literature/Additional papers/duq.md similarity index 100% rename from docs/literature/Additional papers/duq.md rename to docs/research/literature/Additional papers/duq.md diff --git a/docs/literature/Additional papers/gyolov3.md b/docs/research/literature/Additional papers/gyolov3.md similarity index 100% rename from docs/literature/Additional papers/gyolov3.md rename to docs/research/literature/Additional papers/gyolov3.md diff --git a/docs/literature/Additional papers/lightcoresets.md b/docs/research/literature/Additional papers/lightcoresets.md similarity index 100% rename from docs/literature/Additional papers/lightcoresets.md rename to docs/research/literature/Additional papers/lightcoresets.md diff --git 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docs/research/literature/images/vaal/fig1.png diff --git a/docs/literature/images/vaal/fig2.png b/docs/research/literature/images/vaal/fig2.png similarity index 100% rename from docs/literature/images/vaal/fig2.png rename to docs/research/literature/images/vaal/fig2.png diff --git a/docs/literature/index.md b/docs/research/literature/index.md similarity index 100% rename from docs/literature/index.md rename to docs/research/literature/index.md diff --git a/docs/literature/more_papers.md b/docs/research/literature/more_papers.md similarity index 100% rename from docs/literature/more_papers.md rename to docs/research/literature/more_papers.md diff --git a/docs/faq.md b/docs/support/faq.md similarity index 98% rename from docs/faq.md rename to docs/support/faq.md index cd8269da..58d99618 100644 --- a/docs/faq.md +++ b/docs/support/faq.md @@ -135,7 +135,7 @@ active_dataset.label(ranks, labels) Bayesian active learning is a relatively small field with a lot of unknowns. This section aims at presenting some of our findings so that newcomers can quickly learn. -Don't forget to look at our [literature review](../literature/index.md) for a good introduction to the field. +Don't forget to look at our [literature review](../research/literature/index.md) for a good introduction to the field. ### Should you use early stopping? diff --git a/docs/support/index.md b/docs/support/index.md new file mode 100644 index 00000000..852c875b --- /dev/null +++ b/docs/support/index.md @@ -0,0 +1,2 @@ +# Support + diff --git a/docs/user_guide/index.md b/docs/user_guide/index.md index e60af564..4fc2a264 100644 --- a/docs/user_guide/index.md +++ b/docs/user_guide/index.md @@ -53,7 +53,7 @@ We hope that work in this area continues so that we can better understand the im **Resources** -* [Literature review](../literature/index.md) +* [Literature review](../research/literature/index.md) * [Active learning dataset and training loop classes](../notebooks/fundamentals/active-learning) * [Methods for approximating bayesian posteriors](../notebooks/fundamentals/posteriors) * [Full active learning example](../notebooks/active_learning_process) diff --git a/mkdocs.yml b/mkdocs.yml new file mode 100644 index 00000000..6b6a4c26 --- /dev/null +++ b/mkdocs.yml @@ -0,0 +1,50 @@ +site_name: Baal Documentation +repo_url: https://github.com/baal-org/baal +edit_uri: edit/master/docs/ +theme: + name: material + palette: + # Palette toggle for light mode + - media: "(prefers-color-scheme: light)" + scheme: default + primary: blue grey + toggle: + icon: material/brightness-7 + name: Switch to dark mode + + # Palette toggle for dark mode + - media: "(prefers-color-scheme: dark)" + scheme: slate + primary: blue grey + toggle: + icon: material/brightness-4 + name: Switch to light mode + features: + - navigation.tabs + - navigation.indexes + - navigation.instant + icon: + repo: fontawesome/brands/github +plugins: + - search + +markdown_extensions: + - attr_list + - pymdownx.emoji: + emoji_index: !!python/name:materialx.emoji.twemoji + emoji_generator: !!python/name:materialx.emoji.to_svg + +nav: + - Home: index.md + - User Guide: + - user_guide/index.md + - API: + - api/index.md + - Production: + - industry/index.md + - Research: + - research/index.md + - Blog: + - blog/index.md + - Support: + - support/index.md diff --git a/poetry.lock b/poetry.lock index 7ea02d0f..970d6b6d 100644 --- a/poetry.lock +++ b/poetry.lock @@ -42,79 +42,6 @@ python-versions = ">=3.6" [package.dependencies] frozenlist = ">=1.1.0" -[[package]] -name = "alabaster" -version = "0.7.12" -description = "A configurable sidebar-enabled Sphinx theme" -category = "dev" -optional = false -python-versions = "*" - -[[package]] -name = "appnope" -version = "0.1.2" -description = "Disable App Nap on macOS >= 10.9" -category = "dev" -optional = false -python-versions = "*" - -[[package]] -name = "argcomplete" -version = "2.0.0" -description = "Bash tab completion for argparse" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -importlib-metadata = {version = ">=0.23,<5", markers = "python_version == \"3.7\""} - -[package.extras] -test = ["coverage", "flake8", "pexpect", "wheel"] - -[[package]] -name = "argon2-cffi" -version = "21.3.0" -description = "The secure Argon2 password hashing algorithm." -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -argon2-cffi-bindings = "*" -typing-extensions = {version = "*", markers = "python_version < \"3.8\""} - -[package.extras] -dev = ["pre-commit", "cogapp", "tomli", "coverage[toml] (>=5.0.2)", "hypothesis", "pytest", "sphinx", "sphinx-notfound-page", "furo"] -docs = ["sphinx", "sphinx-notfound-page", "furo"] -tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest"] - -[[package]] -name = "argon2-cffi-bindings" -version = "21.2.0" -description = "Low-level CFFI bindings for Argon2" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -cffi = ">=1.0.1" - -[package.extras] -dev = ["pytest", "cogapp", "pre-commit", "wheel"] -tests = ["pytest"] - -[[package]] -name = "asteroid-sphinx-theme" -version = "0.0.3" -description = "Asteroid: Sphinx Theme" -category = "dev" -optional = false -python-versions = "*" - -[package.dependencies] -sphinx = "*" - [[package]] name = "async-timeout" version = "4.0.2" @@ -156,25 +83,6 @@ docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"] tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "cloudpickle"] tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "cloudpickle"] -[[package]] -name = "babel" -version = "2.9.1" -description = "Internationalization utilities" -category = "dev" -optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" - -[package.dependencies] -pytz = ">=2015.7" - -[[package]] -name = "backcall" -version = "0.2.0" -description = "Specifications for callback functions passed in to an API" -category = "dev" -optional = false -python-versions = "*" - [[package]] name = "bandit" version = "1.7.1" @@ -204,7 +112,10 @@ pathspec = ">=0.9.0,<1" platformdirs = ">=2" tomli = ">=0.2.6,<2.0.0" typed-ast = {version = ">=1.4.2", markers = "python_version < \"3.8\" and implementation_name == \"cpython\""} -typing-extensions = ">=3.10.0.0" +typing-extensions = [ + {version = ">=3.10.0.0", markers = "python_version < \"3.10\""}, + {version = "!=3.10.0.1", markers = "python_version >= \"3.10\""}, +] [package.extras] colorama = ["colorama (>=0.4.3)"] @@ -292,17 +203,6 @@ category = "main" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" -[[package]] -name = "commonmark" -version = "0.9.1" -description = "Python parser for the CommonMark Markdown spec" -category = "dev" -optional = false -python-versions = "*" - -[package.extras] -test = ["flake8 (==3.7.8)", "hypothesis (==3.55.3)"] - [[package]] name = "coverage" version = "6.2" @@ -349,32 +249,16 @@ xxhash = "*" apache-beam = ["apache-beam (>=2.26.0)"] audio = ["librosa"] benchmarks = ["numpy (==1.18.5)", "tensorflow (==2.3.0)", "torch (==1.6.0)", "transformers (==3.0.2)"] -dev = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch", "aiobotocore", "boto3", "botocore", "faiss-cpu (>=1.6.4)", "fsspec", "moto[s3,server] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "torch", "torchaudio", "transformers", "bs4", "conllu", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "Pillow (>=6.2.1)", "wget (>=3.2)", "pytorch-nlp (==0.5.0)", "pytorch-lightning", "fastBPE (==0.1.0)", "fairseq", "black (==21.4b0)", "flake8 (>=3.8.3)", "isort (>=5.0.0)", "pyyaml (>=5.3.1)", "importlib-resources"] +dev = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch", "aiobotocore", "boto3", "botocore", "faiss-cpu (>=1.6.4)", "fsspec", "moto[server,s3] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "torch", "torchaudio", "transformers", "bs4", "conllu", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "Pillow (>=6.2.1)", "wget (>=3.2)", "pytorch-nlp (==0.5.0)", "pytorch-lightning", "fastBPE (==0.1.0)", "fairseq", "black (==21.4b0)", "flake8 (>=3.8.3)", "isort (>=5.0.0)", "pyyaml (>=5.3.1)", "importlib-resources"] docs = ["docutils (==0.16.0)", "recommonmark", "sphinx (==3.1.2)", "sphinx-markdown-tables", "sphinx-rtd-theme (==0.4.3)", "sphinxext-opengraph (==0.4.1)", "sphinx-copybutton", "fsspec (<2021.9.0)", "s3fs", "sphinx-panels", "sphinx-inline-tabs", "myst-parser", "Markdown (!=3.3.5)"] quality = ["black (==21.4b0)", "flake8 (>=3.8.3)", "isort (>=5.0.0)", "pyyaml (>=5.3.1)"] s3 = ["fsspec", "boto3", "botocore", "s3fs"] tensorflow = ["tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)"] tensorflow_gpu = ["tensorflow-gpu (>=2.2.0,!=2.6.0,!=2.6.1)"] -tests = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch", "aiobotocore", "boto3", "botocore", "faiss-cpu (>=1.6.4)", "fsspec", "moto[s3,server] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "torch", "torchaudio", "transformers", "bs4", "conllu", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "Pillow (>=6.2.1)", "wget (>=3.2)", "pytorch-nlp (==0.5.0)", "pytorch-lightning", "fastBPE (==0.1.0)", "fairseq", "importlib-resources"] +tests = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch", "aiobotocore", "boto3", "botocore", "faiss-cpu (>=1.6.4)", "fsspec", "moto[server,s3] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "torch", "torchaudio", "transformers", "bs4", "conllu", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "Pillow (>=6.2.1)", "wget (>=3.2)", "pytorch-nlp (==0.5.0)", "pytorch-lightning", "fastBPE (==0.1.0)", "fairseq", "importlib-resources"] torch = ["torch"] vision = ["Pillow (>=6.2.1)"] -[[package]] -name = "debugpy" -version = "1.5.1" -description = "An implementation of the Debug Adapter Protocol for Python" -category = "dev" -optional = false -python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*" - -[[package]] -name = "decorator" -version = "5.1.1" -description = "Decorators for Humans" -category = "dev" -optional = false -python-versions = ">=3.5" - [[package]] name = "defusedxml" version = "0.7.1" @@ -489,11 +373,11 @@ python-versions = ">=3.6" [[package]] name = "fsspec" -version = "2022.1.0" +version = "2022.5.0" description = "File-system specification" category = "main" optional = false -python-versions = ">=3.6" +python-versions = ">=3.7" [package.dependencies] aiohttp = {version = "*", optional = true, markers = "extra == \"http\""} @@ -520,6 +404,7 @@ s3 = ["s3fs"] sftp = ["paramiko"] smb = ["smbprotocol"] ssh = ["paramiko"] +tqdm = ["tqdm"] [[package]] name = "future" @@ -529,6 +414,20 @@ category = "dev" optional = false python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*" +[[package]] +name = "ghp-import" +version = "2.1.0" +description = "Copy your docs directly to the gh-pages branch." +category = "dev" +optional = false +python-versions = "*" + +[package.dependencies] +python-dateutil = ">=2.8.1" + +[package.extras] +dev = ["twine", "markdown", "flake8", "wheel"] + [[package]] name = "gitdb" version = "4.0.9" @@ -667,14 +566,6 @@ category = "main" optional = false python-versions = ">=3.5" -[[package]] -name = "imagesize" -version = "1.3.0" -description = "Getting image size from png/jpeg/jpeg2000/gif file" -category = "dev" -optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" - [[package]] name = "importlib-metadata" version = "4.10.0" @@ -715,61 +606,6 @@ category = "dev" optional = false python-versions = "*" -[[package]] -name = "ipykernel" -version = "6.6.1" -description = "IPython Kernel for Jupyter" -category = "dev" -optional = false -python-versions = ">=3.7" - -[package.dependencies] -appnope = {version = "*", markers = "platform_system == \"Darwin\""} -argcomplete = {version = ">=1.12.3", markers = "python_version < \"3.8.0\""} -debugpy = ">=1.0.0,<2.0" -importlib-metadata = {version = "<5", markers = "python_version < \"3.8.0\""} -ipython = ">=7.23.1" -jupyter-client = "<8.0" -matplotlib-inline = ">=0.1.0,<0.2.0" -nest-asyncio = "*" -tornado = ">=4.2,<7.0" -traitlets = ">=5.1.0,<6.0" - -[package.extras] -test = ["pytest (!=5.3.4)", "pytest-cov", "flaky", "ipyparallel"] - -[[package]] -name = "ipython" -version = "7.31.1" -description = "IPython: Productive Interactive Computing" -category = "dev" -optional = false -python-versions = ">=3.7" - -[package.dependencies] -appnope = {version = "*", markers = "sys_platform == \"darwin\""} -backcall = "*" -colorama = {version = "*", markers = "sys_platform == \"win32\""} -decorator = "*" -jedi = ">=0.16" -matplotlib-inline = "*" -pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""} -pickleshare = "*" -prompt-toolkit = ">=2.0.0,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.1.0" -pygments = "*" -traitlets = ">=4.2" - -[package.extras] -all = ["Sphinx (>=1.3)", "ipykernel", "ipyparallel", "ipywidgets", "nbconvert", "nbformat", "nose (>=0.10.1)", "notebook", "numpy (>=1.17)", "pygments", "qtconsole", "requests", "testpath"] -doc = ["Sphinx (>=1.3)"] -kernel = ["ipykernel"] -nbconvert = ["nbconvert"] -nbformat = ["nbformat"] -notebook = ["notebook", "ipywidgets"] -parallel = ["ipyparallel"] -qtconsole = ["qtconsole"] -test = ["nose (>=0.10.1)", "requests", "testpath", "pygments", "nbformat", "ipykernel", "numpy (>=1.17)"] - [[package]] name = "ipython-genutils" version = "0.2.0" @@ -778,41 +614,6 @@ category = "dev" optional = false python-versions = "*" -[[package]] -name = "ipywidgets" -version = "7.6.5" -description = "IPython HTML widgets for Jupyter" -category = "dev" -optional = false -python-versions = "*" - -[package.dependencies] -ipykernel = ">=4.5.1" -ipython = {version = ">=4.0.0", markers = "python_version >= \"3.3\""} -ipython-genutils = ">=0.2.0,<0.3.0" -jupyterlab-widgets = {version = ">=1.0.0", markers = "python_version >= \"3.6\""} -nbformat = ">=4.2.0" -traitlets = ">=4.3.1" -widgetsnbextension = ">=3.5.0,<3.6.0" - -[package.extras] -test = ["pytest (>=3.6.0)", "pytest-cov", "mock"] - -[[package]] -name = "jedi" -version = "0.18.1" -description = "An autocompletion tool for Python that can be used for text editors." -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -parso = ">=0.8.0,<0.9.0" - -[package.extras] -qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] -testing = ["Django (<3.1)", "colorama", "docopt", "pytest (<7.0.0)"] - [[package]] name = "jinja2" version = "3.0.3" @@ -837,7 +638,7 @@ python-versions = ">=3.6" [[package]] name = "jsonargparse" -version = "4.1.4" +version = "4.9.0" description = "Parsing of command line options, yaml/jsonnet config files and/or environment variables based on argparse." category = "dev" optional = false @@ -851,11 +652,12 @@ PyYAML = ">=3.13" all = ["docstring-parser (>=0.7.3)", "jsonschema (>=3.2.0)", "jsonnet (>=0.13.0)", "validators (>=0.14.2)", "requests (>=2.18.4)", "fsspec (>=0.8.4)", "argcomplete (>=2.0.0)", "ruyaml (>=0.20.0)", "omegaconf (>=2.1.1)", "reconplogger (>=4.4.0)", "typing-extensions (>=3.10.0.0)", "dataclasses (>=0.8)"] argcomplete = ["argcomplete (>=2.0.0)"] dataclasses = ["dataclasses (>=0.8)"] -dev = ["coverage (>=4.5.1)", "responses (>=0.12.0)", "pylint (>=1.8.3)", "pycodestyle (>=2.5.0)", "mypy (>=0.701)", "bump2version (>=0.5.11)", "twine (>=3.1.1)"] +dev = ["coverage (>=4.5.1)", "responses (>=0.12.0)", "Sphinx (>=1.7.9)", "sphinx-rtd-theme (>=0.4.3)", "autodocsumm (>=0.1.10)", "sphinx-autodoc-typehints (>=1.11.1)", "pre-commit (>=2.19.0)", "pylint (>=1.8.3)", "pycodestyle (>=2.5.0)", "mypy (>=0.701)", "tox (>=3.25.0)"] doc = ["Sphinx (>=1.7.9)", "sphinx-rtd-theme (>=0.4.3)", "autodocsumm (>=0.1.10)", "sphinx-autodoc-typehints (>=1.11.1)"] fsspec = ["fsspec (>=0.8.4)"] jsonnet = ["jsonnet (>=0.13.0)"] jsonschema = ["jsonschema (>=3.2.0)"] +maintainer = ["bump2version (>=0.5.11)", "twine (>=4.0.0)"] omegaconf = ["omegaconf (>=2.1.1)"] reconplogger = ["reconplogger (>=4.4.0)"] ruyaml = ["ruyaml (>=0.20.0)"] @@ -917,21 +719,6 @@ python-versions = ">=3.6" pywin32 = {version = ">=1.0", markers = "sys_platform == \"win32\" and platform_python_implementation != \"PyPy\""} traitlets = "*" -[[package]] -name = "jupyter-sphinx" -version = "0.3.2" -description = "Jupyter Sphinx Extensions" -category = "dev" -optional = false -python-versions = ">= 3.6" - -[package.dependencies] -IPython = "*" -ipywidgets = ">=7.0.0" -nbconvert = ">=5.5" -nbformat = "*" -Sphinx = ">=2" - [[package]] name = "jupyterlab-pygments" version = "0.1.2" @@ -944,12 +731,23 @@ python-versions = "*" pygments = ">=2.4.1,<3" [[package]] -name = "jupyterlab-widgets" -version = "1.0.2" -description = "A JupyterLab extension." +name = "jupytext" +version = "1.13.8" +description = "Jupyter notebooks as Markdown documents, Julia, Python or R scripts" category = "dev" optional = false -python-versions = ">=3.6" +python-versions = "~=3.6" + +[package.dependencies] +markdown-it-py = ">=1.0.0,<3.0.0" +mdit-py-plugins = "*" +nbformat = "*" +pyyaml = "*" +toml = "*" + +[package.extras] +rst2md = ["sphinx-gallery (>=0.7.0,<0.8.0)"] +toml = ["toml"] [[package]] name = "kiwisolver" @@ -994,8 +792,8 @@ test = ["codecov (>=2.1)", "pytest (>=6.0)", "pytest-cov (>2.10)", "flake8", "ch [[package]] name = "lightning-flash" -version = "0.7.0rc0" -description = "Flash is a framework for fast prototyping, finetuning, and solving most standard deep learning challenges" +version = "0.8.0.dev0" +description = "Your PyTorch AI Factory - Flash enables you to easily configure and run complex AI recipes." category = "dev" optional = false python-versions = ">=3.6" @@ -1010,6 +808,7 @@ numpy = "*" packaging = "*" pandas = ">=1.1.0" Pillow = {version = ">=7.2", optional = true, markers = "extra == \"image\""} +protobuf = "<=3.20.1" pyDeprecate = "*" pystiche = {version = ">=1.0.0,<2.0.0", optional = true, markers = "extra == \"image\""} pytorch-lightning = ">=1.3.6" @@ -1020,28 +819,30 @@ torchmetrics = ">=0.5.0,<0.5.1 || >0.5.1" torchvision = {version = "*", optional = true, markers = "extra == \"image\""} [package.extras] -all = ["pytorch-forecasting (>=0.9.0)", "torchmetrics[text] (>=0.5.1)", "pytorchvideo (==0.1.2)", "timm (>=0.4.5)", "Pillow (>=7.2)", "pystiche (>=1.0.0,<2.0.0)", "pytorch-tabular (==0.7.0)", "transformers (>=4.5)", "librosa (>=0.8.1)", "filelock", "datasets (>=1.8)", "torchaudio", "scikit-learn", "lightning-bolts (>=0.3.3)", "kornia (>=0.5.1)", "sentencepiece (>=0.1.95)", "sentence-transformers", "transformers (>=4.13.0)", "datasets (>=1.16.1)", "torchvision", "segmentation-models-pytorch"] -audio = ["torchaudio", "transformers (>=4.13.0)", "librosa (>=0.8.1)", "datasets (>=1.16.1)"] -dev = ["myst-parser (>=0.15)", "pytorch-forecasting (>=0.9.0)", "torchmetrics[text] (>=0.5.1)", "ipython", "coverage", "sphinxcontrib-fulltoc (>=1.0)", "docutils (>=0.16)", "pytorchvideo (==0.1.2)", "pytest-flake8", "timm (>=0.4.5)", "Pillow (>=7.2)", "torch-optimizer", "sphinx-autodoc-typehints (>=1.0)", "pytest-rerunfailures (>=10.0)", "pytest-mock", "nbsphinx (>=0.8.5)", "pystiche (>=1.0.0,<2.0.0)", "pytorch-tabular (==0.7.0)", "sphinx-togglebutton (>=0.2)", "transformers (>=4.5)", "pre-commit", "sphinx (>=4.0,<5.0)", "librosa (>=0.8.1)", "pytest-doctestplus (>=0.9.0)", "filelock", "datasets (>=1.8)", "torchaudio", "scikit-learn", "lightning-bolts (>=0.3.3)", "kornia (>=0.5.1)", "check-manifest", "isort", "codecov (>=2.1)", "sentencepiece (>=0.1.95)", "flake8", "pandoc (>=1.0)", "sentence-transformers", "transformers (>=4.13.0)", "twine (==3.2)", "datasets (>=1.16.1)", "pytest (>=5.0,<7.0)", "sphinxcontrib-mockautodoc", "torchvision", "segmentation-models-pytorch", "sphinx-copybutton (>=0.3)", "sphinx-paramlinks (>=0.5.1)"] -docs = ["myst-parser (>=0.15)", "ipython", "sphinxcontrib-fulltoc (>=1.0)", "sphinx (>=4.0,<5.0)", "docutils (>=0.16)", "sphinxcontrib-mockautodoc", "sphinx-paramlinks (>=0.5.1)", "sphinx-copybutton (>=0.3)", "pandoc (>=1.0)", "sphinx-autodoc-typehints (>=1.0)", "sphinx-togglebutton (>=0.2)", "nbsphinx (>=0.8.5)"] -graph = ["torch-cluster", "networkx", "torch-geometric (>=2.0.0)", "torch-sparse", "torch-scatter"] -image = ["pystiche (>=1.0.0,<2.0.0)", "kornia (>=0.5.1)", "timm (>=0.4.5)", "Pillow (>=7.2)", "torchvision", "segmentation-models-pytorch", "lightning-bolts (>=0.3.3)"] -image_extras = ["timm (>=0.4.5)", "Pillow (>=7.2)", "matplotlib", "pystiche (>=1.0.0,<2.0.0)", "effdet", "fastface", "albumentations", "baal", "lightning-bolts (>=0.3.3)", "kornia (>=0.5.1)", "icedata", "classy-vision", "fiftyone", "icevision (>=0.8)", "structlog (==21.1.0)", "torchvision", "learn2learn", "segmentation-models-pytorch", "vissl (>=0.1.5)", "fairscale"] -notebooks = ["jupyter", "jupyter-client", "nbconvert"] -pointcloud = ["open3d (==0.13)", "tensorboard", "torchvision", "torch (==1.7.1)"] -serve = ["pillow", "uvicorn[standard] (>=0.12.0,<0.14.0)", "jinja2", "cytoolz", "graphviz", "aiofiles", "torchvision", "starlette (==0.14.2)", "numpy", "fastapi (>=0.65.2,<0.66.0)", "pyyaml", "tqdm", "pydantic (>1.8.1,<2.0.0)", "importlib-metadata (>=0.12,<3)"] -tabular = ["scikit-learn", "pytorch-forecasting (>=0.9.0)", "pytorch-tabular (==0.7.0)"] -test = ["check-manifest", "twine (==3.2)", "coverage", "pre-commit", "isort", "pytest (>=5.0,<7.0)", "codecov (>=2.1)", "pytest-flake8", "pytest-doctestplus (>=0.9.0)", "torch-optimizer", "flake8", "scikit-learn", "pytest-rerunfailures (>=10.0)", "pytest-mock"] -text = ["torchmetrics[text] (>=0.5.1)", "transformers (>=4.5)", "sentencepiece (>=0.1.95)", "filelock", "datasets (>=1.8)", "sentence-transformers"] -video = ["Pillow (>=7.2)", "kornia (>=0.5.1)", "torchvision", "pytorchvideo (==0.1.2)"] -video_extras = ["kornia (>=0.5.1)", "pytorchvideo (==0.1.2)", "Pillow (>=7.2)", "fiftyone", "torchvision"] -vision = ["pystiche (>=1.0.0,<2.0.0)", "kornia (>=0.5.1)", "pytorchvideo (==0.1.2)", "timm (>=0.4.5)", "Pillow (>=7.2)", "torchvision", "segmentation-models-pytorch", "lightning-bolts (>=0.3.3)"] +all = ["datasets (>=1.8)", "torchmetrics[text] (>=0.5.1)", "segmentation-models-pytorch", "pytorchvideo (==0.1.2)", "pytorch-tabular (==0.7.0)", "sentencepiece (>=0.1.95)", "pytorch-forecasting (>=0.9.0)", "transformers (>=4.13.0)", "kornia (>=0.5.1)", "pystiche (>=1.0.0,<2.0.0)", "timm (>=0.4.5)", "lightning-bolts (>=0.3.3)", "torchaudio", "datasets (>=1.16.1)", "scikit-learn", "torchmetrics (<0.8.0)", "torchvision", "Pillow (>=7.2)", "filelock", "sentence-transformers", "librosa (>=0.8.1)", "transformers (>=4.5)", "omegaconf (<=2.1.1)"] +audio = ["datasets (>=1.16.1)", "transformers (>=4.13.0)", "librosa (>=0.8.1)", "torchaudio"] +core = ["torchvision", "torchmetrics (<0.8.0)", "pystiche (>=1.0.0,<2.0.0)", "Pillow (>=7.2)", "pytorch-tabular (==0.7.0)", "omegaconf (<=2.1.1)", "datasets (>=1.8)", "sentence-transformers", "transformers (>=4.5)", "torchmetrics[text] (>=0.5.1)", "timm (>=0.4.5)", "sentencepiece (>=0.1.95)", "lightning-bolts (>=0.3.3)", "pytorch-forecasting (>=0.9.0)", "filelock", "scikit-learn", "segmentation-models-pytorch", "kornia (>=0.5.1)"] +dev = ["datasets (>=1.8)", "pandoc (>=1.0)", "torchmetrics[text] (>=0.5.1)", "pytest-flake8", "segmentation-models-pytorch", "pre-commit", "codecov (>=2.1)", "pt-lightning-sphinx-theme", "pytorchvideo (==0.1.2)", "sphinx (>=4.0,<5.0)", "sphinx-autodoc-typehints (>=1.0)", "sphinx-copybutton (>=0.3)", "sphinxcontrib-mockautodoc", "pytorch-tabular (==0.7.0)", "pytest-doctestplus (>=0.9.0)", "sphinxcontrib-fulltoc (>=1.0)", "sentencepiece (>=0.1.95)", "pytorch-forecasting (>=0.9.0)", "transformers (>=4.13.0)", "pytest-mock", "torch-optimizer", "kornia (>=0.5.1)", "twine (==3.2)", "pystiche (>=1.0.0,<2.0.0)", "flake8", "pytest (>=5.0,<7.0)", "coverage", "sphinx-paramlinks (>=0.5.1)", "sphinx-togglebutton (>=0.2)", "timm (>=0.4.5)", "pytest-rerunfailures (>=10.0)", "lightning-bolts (>=0.3.3)", "torchaudio", "datasets (>=1.16.1)", "docutils (>=0.16)", "check-manifest", "scikit-learn", "torchmetrics (<0.8.0)", "torchvision", "Pillow (>=7.2)", "nbsphinx (>=0.8.5)", "filelock", "isort", "myst-parser (>=0.15)", "jinja2 (>=3.0.0,<3.1.0)", "ipython", "sentence-transformers", "pytest-forked", "librosa (>=0.8.1)", "transformers (>=4.5)", "omegaconf (<=2.1.1)"] +docs = ["sphinx (>=4.0,<5.0)", "sphinx-autodoc-typehints (>=1.0)", "sphinx-copybutton (>=0.3)", "sphinxcontrib-mockautodoc", "nbsphinx (>=0.8.5)", "sphinx-paramlinks (>=0.5.1)", "sphinxcontrib-fulltoc (>=1.0)", "sphinx-togglebutton (>=0.2)", "myst-parser (>=0.15)", "jinja2 (>=3.0.0,<3.1.0)", "docutils (>=0.16)", "ipython", "pandoc (>=1.0)", "pt-lightning-sphinx-theme"] +graph = ["torch-geometric (>=2.0.0)", "networkx", "torch-scatter", "torch-sparse", "class-resolver (>=0.3.2)", "torch-cluster"] +image = ["torchvision", "pystiche (>=1.0.0,<2.0.0)", "Pillow (>=7.2)", "timm (>=0.4.5)", "lightning-bolts (>=0.3.3)", "segmentation-models-pytorch", "kornia (>=0.5.1)"] +image_extras = ["vissl (>=0.1.5)", "effdet", "segmentation-models-pytorch", "learn2learn", "matplotlib", "pytorch-lightning (<1.5.0)", "icevision (>=0.8)", "kornia (>=0.5.1)", "pystiche (>=1.0.0,<2.0.0)", "fastface", "icedata", "classy-vision", "timm (>=0.4.5)", "fiftyone", "lightning-bolts (>=0.3.3)", "fairscale", "torchmetrics (<0.8.0)", "torchvision", "albumentations", "Pillow (>=7.2)"] +image_extras_baal = ["torchvision", "pystiche (>=1.0.0,<2.0.0)", "Pillow (>=7.2)", "baal (>=1.3.2)", "timm (>=0.4.5)", "lightning-bolts (>=0.3.3)", "segmentation-models-pytorch", "kornia (>=0.5.1)"] +notebooks = ["jupyter-client", "nbconvert", "jupyter"] +pointcloud = ["torchvision", "tensorboard", "torch (==1.7.1)", "open3d (==0.13)"] +serve = ["pillow", "torchvision", "numpy", "cytoolz", "tqdm", "fastapi (>=0.65.2)", "pydantic (>1.8.1)", "graphviz", "uvicorn[standard] (>=0.12.0)", "aiofiles", "starlette (==0.14.2)", "jinja2 (>=3.0.0,<3.1.0)", "pyyaml"] +tabular = ["torchmetrics (<0.8.0)", "pytorch-tabular (==0.7.0)", "pytorch-forecasting (>=0.9.0)", "scikit-learn", "omegaconf (<=2.1.1)"] +test = ["codecov (>=2.1)", "twine (==3.2)", "flake8", "check-manifest", "pytest (>=5.0,<7.0)", "pytest-doctestplus (>=0.9.0)", "coverage", "torch-optimizer", "pytest-rerunfailures (>=10.0)", "isort", "pytest-mock", "pytest-forked", "pytest-flake8", "scikit-learn", "pre-commit"] +text = ["datasets (>=1.8)", "sentence-transformers", "torchmetrics[text] (>=0.5.1)", "sentencepiece (>=0.1.95)", "filelock", "transformers (>=4.5)"] +video = ["Pillow (>=7.2)", "torchvision", "pytorchvideo (==0.1.2)", "kornia (>=0.5.1)"] +video_extras = ["torchvision", "pytorchvideo (==0.1.2)", "Pillow (>=7.2)", "fiftyone", "kornia (>=0.5.1)"] +vision = ["torchvision", "pystiche (>=1.0.0,<2.0.0)", "pytorchvideo (==0.1.2)", "Pillow (>=7.2)", "timm (>=0.4.5)", "lightning-bolts (>=0.3.3)", "segmentation-models-pytorch", "kornia (>=0.5.1)"] [package.source] type = "git" url = "https://github.com/PyTorchLightning/lightning-flash.git" reference = "master" -resolved_reference = "450902d713980e0edefcfd2d2a2a35eb875072d7" +resolved_reference = "4bddc0841be95783270757383a0a6f5a26bdedc0" [[package]] name = "markdown" @@ -1057,6 +858,28 @@ importlib-metadata = {version = ">=4.4", markers = "python_version < \"3.10\""} [package.extras] testing = ["coverage", "pyyaml"] +[[package]] +name = "markdown-it-py" +version = "2.1.0" +description = "Python port of markdown-it. Markdown parsing, done right!" +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +mdurl = ">=0.1,<1.0" +typing_extensions = {version = ">=3.7.4", markers = "python_version < \"3.8\""} + +[package.extras] +benchmarking = ["psutil", "pytest", "pytest-benchmark (>=3.2,<4.0)"] +code_style = ["pre-commit (==2.6)"] +compare = ["commonmark (>=0.9.1,<0.10.0)", "markdown (>=3.3.6,<3.4.0)", "mistletoe (>=0.8.1,<0.9.0)", "mistune (>=2.0.2,<2.1.0)", "panflute (>=2.1.3,<2.2.0)"] +linkify = ["linkify-it-py (>=1.0,<2.0)"] +plugins = ["mdit-py-plugins"] +profiling = ["gprof2dot"] +rtd = ["attrs", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx-book-theme"] +testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"] + [[package]] name = "markupsafe" version = "2.0.1" @@ -1085,23 +908,44 @@ python-dateutil = ">=2.7" setuptools_scm = ">=4" [[package]] -name = "matplotlib-inline" -version = "0.1.3" -description = "Inline Matplotlib backend for Jupyter" +name = "mccabe" +version = "0.6.1" +description = "McCabe checker, plugin for flake8" category = "dev" optional = false -python-versions = ">=3.5" +python-versions = "*" + +[[package]] +name = "mdit-py-plugins" +version = "0.3.0" +description = "Collection of plugins for markdown-it-py" +category = "dev" +optional = false +python-versions = "~=3.6" [package.dependencies] -traitlets = "*" +markdown-it-py = ">=1.0.0,<3.0.0" + +[package.extras] +code_style = ["pre-commit (==2.6)"] +rtd = ["myst-parser (>=0.14.0,<0.15.0)", "sphinx-book-theme (>=0.1.0,<0.2.0)"] +testing = ["coverage", "pytest (>=3.6,<4)", "pytest-cov", "pytest-regressions"] [[package]] -name = "mccabe" -version = "0.6.1" -description = "McCabe checker, plugin for flake8" +name = "mdurl" +version = "0.1.1" +description = "Markdown URL utilities" category = "dev" optional = false -python-versions = "*" +python-versions = ">=3.7" + +[[package]] +name = "mergedeep" +version = "1.3.4" +description = "A deep merge function for 🐍." +category = "dev" +optional = false +python-versions = ">=3.6" [[package]] name = "mistune" @@ -1111,6 +955,68 @@ category = "dev" optional = false python-versions = "*" +[[package]] +name = "mkdocs" +version = "1.3.0" +description = "Project documentation with Markdown." +category = "dev" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +click = ">=3.3" +ghp-import = ">=1.0" +importlib-metadata = ">=4.3" +Jinja2 = ">=2.10.2" +Markdown = ">=3.2.1" +mergedeep = ">=1.3.4" +packaging = ">=20.5" +PyYAML = ">=3.10" +pyyaml-env-tag = ">=0.1" +watchdog = ">=2.0" + +[package.extras] +i18n = ["babel (>=2.9.0)"] + +[[package]] +name = "mkdocs-jupyter" +version = "0.21.0" +description = "Use Jupyter in mkdocs websites" +category = "dev" +optional = false +python-versions = ">=3.7.1,<4" + +[package.dependencies] +jupytext = ">=1.13.8,<2.0.0" +mkdocs = ">=1.2.3,<2.0.0" +mkdocs-material = ">=8.0.0,<9.0.0" +nbconvert = ">=6.2.0,<7.0.0" +Pygments = ">=2.12.0,<3.0.0" + +[[package]] +name = "mkdocs-material" +version = "8.3.6" +description = "Documentation that simply works" +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +jinja2 = ">=3.0.2" +markdown = ">=3.2" +mkdocs = ">=1.3.0" +mkdocs-material-extensions = ">=1.0.3" +pygments = ">=2.12" +pymdown-extensions = ">=9.4" + +[[package]] +name = "mkdocs-material-extensions" +version = "1.0.3" +description = "Extension pack for Python Markdown." +category = "dev" +optional = false +python-versions = ">=3.6" + [[package]] name = "multidict" version = "5.2.0" @@ -1238,22 +1144,6 @@ traitlets = ">=4.1" fast = ["fastjsonschema"] test = ["check-manifest", "fastjsonschema", "testpath", "pytest", "pytest-cov"] -[[package]] -name = "nbsphinx" -version = "0.8.8" -description = "Jupyter Notebook Tools for Sphinx" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -docutils = "*" -jinja2 = "*" -nbconvert = "!=5.4" -nbformat = "*" -sphinx = ">=1.8" -traitlets = "*" - [[package]] name = "nest-asyncio" version = "1.5.4" @@ -1262,36 +1152,6 @@ category = "dev" optional = false python-versions = ">=3.5" -[[package]] -name = "notebook" -version = "6.4.6" -description = "A web-based notebook environment for interactive computing" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -argon2-cffi = "*" -ipykernel = "*" -ipython-genutils = "*" -jinja2 = "*" -jupyter-client = ">=5.3.4" -jupyter-core = ">=4.6.1" -nbconvert = "*" -nbformat = "*" -nest-asyncio = ">=1.5" -prometheus-client = "*" -pyzmq = ">=17" -Send2Trash = ">=1.8.0" -terminado = ">=0.8.3" -tornado = ">=6.1" -traitlets = ">=4.2.1" - -[package.extras] -docs = ["sphinx", "nbsphinx", "sphinxcontrib-github-alt", "sphinx-rtd-theme", "myst-parser"] -json-logging = ["json-logging"] -test = ["pytest", "coverage", "requests", "nbval", "selenium", "pytest-cov", "requests-unixsocket"] - [[package]] name = "numpy" version = "1.21.5" @@ -1300,21 +1160,6 @@ category = "main" optional = false python-versions = ">=3.7,<3.11" -[[package]] -name = "numpydoc" -version = "1.1.0" -description = "Sphinx extension to support docstrings in Numpy format" -category = "dev" -optional = false -python-versions = ">=3.5" - -[package.dependencies] -Jinja2 = ">=2.3" -sphinx = ">=1.6.5" - -[package.extras] -testing = ["matplotlib", "pytest", "pytest-cov"] - [[package]] name = "oauthlib" version = "3.1.1" @@ -1363,18 +1208,6 @@ category = "dev" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" -[[package]] -name = "parso" -version = "0.8.3" -description = "A Python Parser" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.extras] -qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] -testing = ["docopt", "pytest (<6.0.0)"] - [[package]] name = "pathspec" version = "0.9.0" @@ -1391,25 +1224,6 @@ category = "dev" optional = false python-versions = ">=2.6" -[[package]] -name = "pexpect" -version = "4.8.0" -description = "Pexpect allows easy control of interactive console applications." -category = "dev" -optional = false -python-versions = "*" - -[package.dependencies] -ptyprocess = ">=0.5" - -[[package]] -name = "pickleshare" -version = "0.7.5" -description = "Tiny 'shelve'-like database with concurrency support" -category = "dev" -optional = false -python-versions = "*" - [[package]] name = "pillow" version = "9.0.0" @@ -1459,28 +1273,6 @@ torch = "*" torchvision = "*" tqdm = "*" -[[package]] -name = "prometheus-client" -version = "0.12.0" -description = "Python client for the Prometheus monitoring system." -category = "dev" -optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" - -[package.extras] -twisted = ["twisted"] - -[[package]] -name = "prompt-toolkit" -version = "3.0.24" -description = "Library for building powerful interactive command lines in Python" -category = "dev" -optional = false -python-versions = ">=3.6.2" - -[package.dependencies] -wcwidth = "*" - [[package]] name = "protobuf" version = "3.19.1" @@ -1489,14 +1281,6 @@ category = "dev" optional = false python-versions = ">=3.5" -[[package]] -name = "ptyprocess" -version = "0.7.0" -description = "Run a subprocess in a pseudo terminal" -category = "dev" -optional = false -python-versions = "*" - 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-mypy = "^0.910" -bandit = "^1.7.1" + # Lightning lightning-flash = {git = "https://github.com/PyTorchLightning/lightning-flash.git", extras = ["image"]} +mkdocs-jupyter = "^0.21.0" +mkdocs-material = "^8.3.6" [tool.poetry.extras] vision = ["torchvision"] From 4db203131eceec300eabe019631cc0cc93d34db4 Mon Sep 17 00:00:00 2001 From: Dref360 Date: Sun, 26 Jun 2022 16:28:25 -0400 Subject: [PATCH 02/10] Update content --- docs/Makefile | 21 +- docs/_templates/layout.html | 6 - docs/api/bayesian.md | 11 +- docs/api/calibration.md | 7 +- docs/api/compatibility/huggingface.md | 11 +- docs/api/compatibility/pytorch-lightning.md | 14 +- docs/api/dataset_management.md | 14 +- docs/api/heuristics.md | 15 +- docs/api/index.md | 33 +- docs/api/modelwrapper.md | 7 +- docs/api/utils.md | 7 +- docs/index.md | 50 +- docs/industry/index.md | 0 docs/javascripts/mathjax.js | 16 + .../dirichlet_calibration.md | 98 +- .../double_descent.md} | 72 +- docs/{blog => research}/images/ALL_active.png | Bin .../images/BALDvsCBALD_active.png | Bin .../{blog => research}/images/CBALDvsBALD.png | Bin .../images/CBALDvsBALDECE.png | Bin .../images/EntvsCEnt_active.png | Bin .../images/dirichlet_calib.png | Bin .../images/doubledescend_01.png | Bin .../images/doubledescend_02.png | Bin .../images/doubledescend_03.png | Bin .../images/doubledescend_04.png | Bin .../literature/Additional papers/duq.md | 12 +- .../Additional papers/lightcoresets.md | 12 +- .../Additional papers/sparse_selection.md | 10 +- docs/research/literature/index.md | 4 +- docs/support/faq.md | 8 +- docs/support/index.md | 7 + docs/tutorials/index.md | 16 + docs/{industry => tutorials}/label-studio.md | 0 docs/user_guide/baal_cheatsheet.md | 23 +- docs/user_guide/index.md | 7 +- mkdocs.yml | 60 +- notebooks/active_learning_process.ipynb | 869 ++----------- notebooks/deep_ensemble.ipynb | 1115 +---------------- notebooks/fairness/ActiveFairness.ipynb | 84 +- notebooks/fundamentals/active-learning.ipynb | 108 +- notebooks/fundamentals/posteriors.ipynb | 141 ++- poetry.lock | 139 +- pyproject.toml | 4 + 44 files changed, 785 insertions(+), 2216 deletions(-) delete mode 100644 docs/_templates/layout.html delete mode 100644 docs/industry/index.md create mode 100644 docs/javascripts/mathjax.js rename docs/{blog => research}/dirichlet_calibration.md (60%) rename docs/{blog/double_descend.md => research/double_descent.md} (81%) rename docs/{blog => research}/images/ALL_active.png (100%) rename docs/{blog => research}/images/BALDvsCBALD_active.png (100%) rename docs/{blog => research}/images/CBALDvsBALD.png (100%) rename docs/{blog => research}/images/CBALDvsBALDECE.png (100%) rename docs/{blog => research}/images/EntvsCEnt_active.png (100%) rename docs/{blog => research}/images/dirichlet_calib.png (100%) rename docs/{blog => research}/images/doubledescend_01.png (100%) rename docs/{blog => research}/images/doubledescend_02.png (100%) rename docs/{blog => research}/images/doubledescend_03.png (100%) rename docs/{blog => research}/images/doubledescend_04.png (100%) create mode 100644 docs/tutorials/index.md rename docs/{industry => tutorials}/label-studio.md (100%) diff --git a/docs/Makefile b/docs/Makefile index a16605d4..554dcade 100644 --- a/docs/Makefile +++ b/docs/Makefile @@ -1,23 +1,10 @@ -# Minimal makefile for Sphinx documentation +# Minimal makefile for Mkdocs documentation # -# You can set these variables from the command line. -SPHINXOPTS = -SPHINXBUILD = sphinx-build -SOURCEDIR = . -BUILDDIR = _build - # Put it first so that "make" without argument is like "make help". -help: - @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) - -.PHONY: help Makefile - -# Catch-all target: route all unknown targets to Sphinx using the new -# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). -%: Makefile - @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) +build: + mkdocs build server: - open _build/html/index.html \ No newline at end of file + mkdocs watch \ No newline at end of file diff --git a/docs/_templates/layout.html b/docs/_templates/layout.html deleted file mode 100644 index 462ed4c0..00000000 --- a/docs/_templates/layout.html +++ /dev/null @@ -1,6 +0,0 @@ -{% extends "!layout.html" %} - -{%- block extrahead %} - - -{% endblock %} \ No newline at end of file diff --git a/docs/api/bayesian.md b/docs/api/bayesian.md index 73441544..e0e7902e 100644 --- a/docs/api/bayesian.md +++ b/docs/api/bayesian.md @@ -22,11 +22,10 @@ model = MCDropoutConnectModule(model, layers=["Linear"], weight_dropout=0.5) ## API -```eval_rst -.. autoclass:: baal.bayesian.dropout.MCDropoutModule - :members: __init__ +### baal.bayesian.dropout.MCDropoutModule -..autoclass:: baal.bayesian.weight_drop.MCDropoutConnectModule - :members: __init__ +::: baal.bayesian.dropout.MCDropoutModule -``` \ No newline at end of file +### baal.bayesian.weight_drop.MCDropoutConnectModule + +::: baal.bayesian.weight_drop.MCDropoutConnectModule \ No newline at end of file diff --git a/docs/api/calibration.md b/docs/api/calibration.md index 6501afa3..5ba08511 100644 --- a/docs/api/calibration.md +++ b/docs/api/calibration.md @@ -1,6 +1,5 @@ # Calibration Wrapper -```eval_rst -.. autoclass:: baal.calibration.DirichletCalibrator - :members: -``` +### baal.calibration.DirichletCalibrator + +::: baal.calibration.DirichletCalibrator diff --git a/docs/api/compatibility/huggingface.md b/docs/api/compatibility/huggingface.md index 3d1e6b6b..757667f6 100644 --- a/docs/api/compatibility/huggingface.md +++ b/docs/api/compatibility/huggingface.md @@ -1,10 +1,7 @@ ## HuggingFace Compatibility - ```eval_rst -.. autoclass:: baal.transformers_trainer_wrapper.BaalTransformersTrainer - :members: predict_on_dataset, predict_on_dataset_generator +**baal.transformers_trainer_wrapper.BaalTransformersTrainer** +::: baal.transformers_trainer_wrapper.BaalTransformersTrainer -.. autoclass:: baal.active.nlp_datasets.HuggingFaceDatasets - :members: - -``` \ No newline at end of file +**baal.active.dataset.nlp_datasets.HuggingFaceDatasets** +::: baal.active.dataset.nlp_datasets.HuggingFaceDatasets \ No newline at end of file diff --git a/docs/api/compatibility/pytorch-lightning.md b/docs/api/compatibility/pytorch-lightning.md index f1fffb4d..d9f5a27e 100644 --- a/docs/api/compatibility/pytorch-lightning.md +++ b/docs/api/compatibility/pytorch-lightning.md @@ -1,12 +1,10 @@ ## Pytorch Lightning Compatibility - ```eval_rst -.. autoclass:: baal.utils.pytorch_lightning.ResetCallback - :members: on_train_start +**baal.utils.pytorch_lightning.ResetCallback** +::: baal.utils.pytorch_lightning.ResetCallback -.. autoclass:: baal.utils.pytorch_lightning.BaalTrainer - :members: predict_on_dataset, predict_on_dataset_generator +**baal.utils.pytorch_lightning.BaalTrainer** +::: baal.utils.pytorch_lightning.BaalTrainer -.. autoclass:: baal.utils.pytorch_lightning.BaaLDataModule - :members: pool_dataloader -``` \ No newline at end of file +**baal.utils.pytorch_lightning.BaaLDataModule** +::: baal.utils.pytorch_lightning.BaaLDataModule \ No newline at end of file diff --git a/docs/api/dataset_management.md b/docs/api/dataset_management.md index 3cb76b7f..da7df591 100644 --- a/docs/api/dataset_management.md +++ b/docs/api/dataset_management.md @@ -36,13 +36,11 @@ assert al_dataset.pool.transform is None ### API -```eval_rst -.. autoclass:: baal.active.ActiveLearningDataset - :members: +### baal.active.ActiveLearningDataset +::: baal.active.ActiveLearningDataset -.. autoclass:: baal.active.ActiveLearningLoop - :members: +### baal.active.ActiveLearningLoop +::: baal.active.ActiveLearningLoop -.. autoclass:: baal.active.FileDataset - :members: -``` \ No newline at end of file +### baal.active.FileDataset +::: baal.active.FileDataset \ No newline at end of file diff --git a/docs/api/heuristics.md b/docs/api/heuristics.md index 635847cb..8172e239 100644 --- a/docs/api/heuristics.md +++ b/docs/api/heuristics.md @@ -33,13 +33,14 @@ BALD(reduction="mean") ### API -```eval_rst -.. autoclass:: baal.active.heuristics.AbstractHeuristic - :members: +### baal.active.heuristics.AbstractHeuristic +::: baal.active.heuristics.AbstractHeuristic -.. autoclass:: baal.active.heuristics.BALD +### baal.active.heuristics.BALD +::: baal.active.heuristics.BALD -.. autoclass:: baal.active.heuristics.Random +### baal.active.heuristics.Random +::: baal.active.heuristics.Random -.. autoclass:: baal.active.heuristics.Entropy -``` \ No newline at end of file +### baal.active.heuristics.Entropy +::: baal.active.heuristics.Entropy \ No newline at end of file diff --git a/docs/api/index.md b/docs/api/index.md index 3d28b609..1c5464d5 100644 --- a/docs/api/index.md +++ b/docs/api/index.md @@ -1,25 +1,18 @@ # API Reference -```eval_rst -.. toctree:: - :caption: API Definition - :maxdepth: 1 - - baal.modelwrapper.ModelWrapper <./modelwrapper> - baal.bayesian <./bayesian> - baal.active <./dataset_management> - baal.active.heuristics <./heuristics> - baal.calibration <./calibration> - baal.utils <./utils> - -.. toctree:: - :caption: Compatibility - :maxdepth: 1 - - baal.utils.pytorch_lightning <./compatibility/pytorch-lightning> - baal.transformers_trainer_wrapper <./compatibility/huggingface> - -``` +### :material-file-tree: API Definition + +* [baal.modelwrapper.ModelWrapper](./modelwrapper.md) +* [baal.bayesian](./bayesian.md) +* [baal.active](./dataset_management.md) +* [baal.active.heuristics](./heuristics.md) +* [baal.calibration](./calibration.md) +* [baal.utils](./utils.md) + +### :material-file-tree: Compatibility + +* [baal.utils.pytorch_lightning] (./compatibility/pytorch-lightning) +* [baal.transformers_trainer_wrapper](./compatibility/huggingface) diff --git a/docs/api/modelwrapper.md b/docs/api/modelwrapper.md index e8ef4eeb..72811d32 100644 --- a/docs/api/modelwrapper.md +++ b/docs/api/modelwrapper.md @@ -32,7 +32,6 @@ predictions.shape ### API -```eval_rst -.. autoclass:: baal.ModelWrapper - :members: -``` \ No newline at end of file +### baal.ModelWrapper + +::: baal.ModelWrapper \ No newline at end of file diff --git a/docs/api/utils.md b/docs/api/utils.md index 36643632..06073998 100644 --- a/docs/api/utils.md +++ b/docs/api/utils.md @@ -5,7 +5,6 @@ To work with `baal.modelwrapper.ModelWrapper`, we provide `Metrics`. -```eval_rst -.. automodule:: baal.utils.metrics - :members: -``` \ No newline at end of file +### baal.utils.metrics + +::: baal.utils.metrics \ No newline at end of file diff --git a/docs/index.md b/docs/index.md index 12cbc38e..5bcdac01 100644 --- a/docs/index.md +++ b/docs/index.md @@ -13,50 +13,6 @@ If you have any question, we are reachable on [Slack](https://join.slack.com/t/b For support, we have several ways to help you: -* Our [FAQ](support/faq.md) -* Submit an issue on Github [here](https://github.com/ElementAI/baal/issues/new/choose) -* Join our [Slack](https://join.slack.com/t/baal-world/shared_invite/zt-z0izhn4y-Jt6Zu5dZaV2rsAS9sdISfg)! - -## :material-file-tree: Learn more about Baal - -* [:material-link: User Guide](user_guide) -* [:material-book-education: Active learning dataset and training loop classes](notebooks/fundamentals/active-learning.ipynb) -* [:material-book-education: Methods for approximating bayesian posteriors](notebooks/fundamentals/posteriors.ipynb) -* [:material-link: API Index](api) -* [:material-help: FAQ](support/faq.md) - -## :material-file-tree: Industry -* [:material-book-education: Active learning dataset and training loop classes](notebooks/fundamentals/active-learning.ipynb) - -.. toctree :: - :caption: Tutorials - :maxdepth: 1 - - How to use BaaL with Label Studio - How to do research and plot progress - How to use in production - How to use deep ensembles - -.. toctree :: - :caption: Compatibility with other libraries - :maxdepth: 1 - - How to use with Pytorch Lightning - How to use with HuggingFace - How to use with Scikit-Learn - -.. toctree :: - :caption: Technical Reports - :maxdepth: 1 - - Combining calibration and variational inference for active learning - Double descend in active learning - Can active learning mitigate bias in datasets - -.. toctree:: - :caption: Literature and support - :maxdepth: 2 - - Background literature - Cheat Sheet -``` +* Our [:material-help: FAQ](support/faq.md) +* Submit an issue on Github [here](https://github.com/baal-org/baal/issues/new/choose) +* Join our [:material-slack: Slack](https://join.slack.com/t/baal-world/shared_invite/zt-z0izhn4y-Jt6Zu5dZaV2rsAS9sdISfg)! diff --git a/docs/industry/index.md b/docs/industry/index.md deleted file mode 100644 index e69de29b..00000000 diff --git a/docs/javascripts/mathjax.js b/docs/javascripts/mathjax.js new file mode 100644 index 00000000..06dbf38b --- /dev/null +++ b/docs/javascripts/mathjax.js @@ -0,0 +1,16 @@ +window.MathJax = { + tex: { + inlineMath: [["\\(", "\\)"]], + displayMath: [["\\[", "\\]"]], + processEscapes: true, + processEnvironments: true + }, + options: { + ignoreHtmlClass: ".*|", + processHtmlClass: "arithmatex" + } +}; + +document$.subscribe(() => { + MathJax.typesetPromise() +}) diff --git a/docs/blog/dirichlet_calibration.md b/docs/research/dirichlet_calibration.md similarity index 60% rename from docs/blog/dirichlet_calibration.md rename to docs/research/dirichlet_calibration.md index 368c7509..0cd46019 100644 --- a/docs/blog/dirichlet_calibration.md +++ b/docs/research/dirichlet_calibration.md @@ -4,15 +4,12 @@ A [paper recently published at NeurIPS 2019](https://dirichletcal.github.io/) pr To achieve that, they add a new linear layer at the end of the network and train it individually on a held-out set. -Here is a figure from the authors' NeurIPS 2019 presentation. You can find the full presention on the website above. - -```eval_rst -.. figure:: images/dirichlet_calib.png - :width: 400px - :height: 200px - :alt: alternate text - :align: center -``` +Here is a figure from the authors' NeurIPS 2019 presentation. You can find the full presentation on the website above. + +
+![](./images/dirichlet_calib.png){ width="500" } +
Dirichlet Calibration NeurIPS 2019
+
Our hypothesis is as follows: by modelling the uncertainty on an held-out set, we want to create a better estimation of the overall uncertainty. @@ -24,15 +21,15 @@ Current SotA methods for active learning rely on VI to estimate the model uncert ## Methodology -Our methodology follows a standard active learning pipeline, but we add a new training set :math:`D_{L}` which is used to train the calibration layer. After training the model on the training set :math:`D_{train}` to convergence, we train it on this held-out set and train the newly added layer. +Our methodology follows a standard active learning pipeline, but we add a new training set $D_{L}$ which is used to train the calibration layer. After training the model on the training set $D_{train}$ to convergence, we train it on this held-out set and train the newly added layer. -We call the augmented model :math:`M_{calib}`. We perform the sample selection using one of the following techniques: +We call the augmented model $M_{calib}$. We perform the sample selection using one of the following techniques: -* Entropy: :math:`\sum_c p_i \log(p_i)` -* BALD using MC-Dropout: :math:`H[y \mid x, D_{L}] - E_{p(w \mid D_L)}(H[y \mid x, w])` +* Entropy: $\sum_c p_i \log(p_i)$ +* BALD using MC-Dropout: $H[y \mid x, D_{L}] - E_{p(w \mid D_L)}(H[y \mid x, w])$ * Uniform random selection -Because we want to analyze the actual gain of using calibration, we compare the effect of using :math:`M` versus :math:`M_{calib}` across all techniques. +Because we want to analyze the actual gain of using calibration, we compare the effect of using $M$ versus $M_{calib}$ across all techniques. ## Experiments @@ -42,70 +39,51 @@ We test our hypothesis on CIFAR10 using a VGG-16. We initially label 1000 sample We first want to ensure that calibration works properly. In Fig. 2, we show that throughout the active learning procedure, the calibrated loss is better than the non-calibrated loss. -```eval_rst -.. figure:: images/CBALDvsBALD.png - :width: 400px - :height: 200px - :alt: alternate text - :align: center - - Comparison between the calibrated loss and the uncalibrated loss. -``` +
+![](./images/CBALDvsBALD.png){ width="500" align="center"} +
Comparison between the calibrated loss and the uncalibrated loss.
+
+ Furthermore, we compute the ECE between both cases. -```eval_rst -.. figure:: images/CBALDvsBALDECE.png - :width: 400px - :height: 200px - :alt: alternate text - :align: center - - Comparison between ECE for both Calibrated BALD and BALD. -``` +
+![](./images/CBALDvsBALDECE.png){ width="500" align="center"} +
Comparison between ECE for both Calibrated BALD and BALD.
+
### Impact of calibration on active learning For each method, we present the calibrated NLL at each active learning step. -We want to compare the selection process between :math:`M` and :math:`M_{calib}`. +We want to compare the selection process between $M$ and $M_{calib}$. Our reasoning is as follow. We want to see if the calibrated model would pick better items over the normal one. -To do so we make two experiments, one where we use :math:`M` to select the new samples and the other uses :math:`M_{calib}`. +To do so we make two experiments, one where we use $M$ to select the new samples and the other uses $M_{calib}$. In both cases, we will get a calibrated model to compare the calibrated loss. -```eval_rst -.. figure:: images/BALDvsCBALD_active.png - :width: 400px - :height: 200px - :alt: alternate text - :align: center - - Comparison between a calibrated selector and an uncalibrated one using BALD. - - -.. figure:: images/EntvsCEnt_active.png - :width: 400px - :height: 200px - :alt: alternate text - :align: center - - Comparison between a calibrated selector and an uncalibrated one using Entropy. +
+![](images/BALDvsCBALD_active.png){ width="500"} +
Comparison between a calibrated selector and an uncalibrated one using BALD.
+
+ +
+![](images/EntvsCEnt_active.png){ width="500"} +
Comparison between a calibrated selector and an uncalibrated one using Entropy.
+
+ +
+![](images/ALL_active.png){ width="500" } +
Comparison between calibrated selectors.
+
+ In addition, we show that BALD is still better in all cases. -.. figure:: images/ALL_active.png - :width: 400px - :height: 200px - :alt: alternate text - :align: center - - Comparison between calibrated selectors. -``` ## Discussion -While we have not seen improvments by using calibration on an active learning benchmark, we still find this report useful. Active learning is but a part of the Human-ai-interaction (HAII) process. By adding an easy to use calibration method, we can further the collaboration between the human and our model. +While we have not seen improvements by using calibration on an active learning benchmark, we still find this report useful. Active learning is but a part of the Human-ai-interaction (HAII) process. By adding an easy to use calibration method, we can further the collaboration between the human and our model. By giving more nuanced predictions, the model is deemed more trustable by the human annotator. diff --git a/docs/blog/double_descend.md b/docs/research/double_descent.md similarity index 81% rename from docs/blog/double_descend.md rename to docs/research/double_descent.md index 0fc9548e..9cd81963 100644 --- a/docs/blog/double_descend.md +++ b/docs/research/double_descent.md @@ -40,47 +40,26 @@ We ran 4 categories of experiments: Dataset: CIFAR10 Model: Vgg16 trained on imagenet -```eval_rst -.. figure:: images/doubledescend_03.png - :width: 400px - :height: 200px - :alt: alternate text - :align: center - - Using early stopping and reset the weights of the linear layers after each active learning step. -``` - - -```eval_rst -.. figure:: images/doubledescend_04.png - :width: 400px - :height: 200px - :alt: alternate text - :align: center - - Using early stopping and reset all the weights after each active learning step. -``` - - -```eval_rst -.. figure:: images/doubledescend_02.png - :width: 400px - :height: 200px - :alt: alternate text - :align: center - - Overfitting the training set and reset the weights of the linear layers after each active learning step. -``` - -```eval_rst -.. figure:: images/doubledescend_01.png - :width: 400px - :height: 200px - :alt: alternate text - :align: center - - Overfitting the training set and reset all the weights after each active learning step. -``` +
+![](images/doubledescend_03.png){ width="500" } +
Using early stopping and reset the weights of the linear layers after each active learning step.
+
+ +
+![](images/doubledescend_04.png){ width="500" } +
Using early stopping and reset all the weights after each active learning step.
+
+ +
+![](images/doubledescend_02.png){ width="500" } +
Overfitting the training set and reset the weights of the linear layers after each active learning step.
+
+ +
+![](images/doubledescend_01.png){ width="500" } +
Overfitting the training set and reset all the weights after each active learning step.
+
+ In the first two experiments, if we are using early stopping, the partial reset will provoke a double descent. A closer look in the second diagram shows that although in the case of fully resetting the model weights, we can prevent the @@ -95,12 +74,11 @@ with a negligible peak. Moreover, letting the model train well before performing key to encourage smooth training, we show the difference between letting the model to train for 10 epochs vs 5 epochs before adding samples to the labelled set. -```eval_rst -NOTE: In the case of not using early stopping, `p` is used to show the number of epochs we train the model before -estimating uncertainties and increase the labelled set. -All in all, not using early stopping and fully resetting the model weights i.e. the last graph, could certify a smooth -training procedure without being worried about other elements such as weight decay. -``` +!!! note + In the case of not using early stopping, `p` is used to show the number of epochs we train the model before + estimating uncertainties and increase the labelled set. + All in all, not using early stopping and fully resetting the model weights i.e. the last graph, could certify a smooth + training procedure without being worried about other elements such as weight decay. ### Our Hypothesis diff --git a/docs/blog/images/ALL_active.png b/docs/research/images/ALL_active.png similarity index 100% rename from docs/blog/images/ALL_active.png rename to docs/research/images/ALL_active.png diff --git a/docs/blog/images/BALDvsCBALD_active.png b/docs/research/images/BALDvsCBALD_active.png similarity index 100% rename from docs/blog/images/BALDvsCBALD_active.png rename to docs/research/images/BALDvsCBALD_active.png diff --git a/docs/blog/images/CBALDvsBALD.png b/docs/research/images/CBALDvsBALD.png similarity index 100% rename from docs/blog/images/CBALDvsBALD.png rename to docs/research/images/CBALDvsBALD.png diff --git a/docs/blog/images/CBALDvsBALDECE.png b/docs/research/images/CBALDvsBALDECE.png similarity index 100% rename from docs/blog/images/CBALDvsBALDECE.png rename to docs/research/images/CBALDvsBALDECE.png diff --git a/docs/blog/images/EntvsCEnt_active.png b/docs/research/images/EntvsCEnt_active.png similarity index 100% rename from docs/blog/images/EntvsCEnt_active.png rename to docs/research/images/EntvsCEnt_active.png diff --git a/docs/blog/images/dirichlet_calib.png b/docs/research/images/dirichlet_calib.png similarity index 100% rename from docs/blog/images/dirichlet_calib.png rename to docs/research/images/dirichlet_calib.png diff --git a/docs/blog/images/doubledescend_01.png b/docs/research/images/doubledescend_01.png similarity index 100% rename from docs/blog/images/doubledescend_01.png rename to docs/research/images/doubledescend_01.png diff --git a/docs/blog/images/doubledescend_02.png b/docs/research/images/doubledescend_02.png similarity index 100% rename from docs/blog/images/doubledescend_02.png rename to docs/research/images/doubledescend_02.png diff --git a/docs/blog/images/doubledescend_03.png b/docs/research/images/doubledescend_03.png similarity index 100% rename from docs/blog/images/doubledescend_03.png rename to docs/research/images/doubledescend_03.png diff --git a/docs/blog/images/doubledescend_04.png b/docs/research/images/doubledescend_04.png similarity index 100% rename from docs/blog/images/doubledescend_04.png rename to docs/research/images/doubledescend_04.png diff --git a/docs/research/literature/Additional papers/duq.md b/docs/research/literature/Additional papers/duq.md index e7219528..206e118d 100644 --- a/docs/research/literature/Additional papers/duq.md +++ b/docs/research/literature/Additional papers/duq.md @@ -17,22 +17,22 @@ DUQ uses a RBF Network to compute centroids for each class. The model is trained For a model f, a centroid matrix W and a centroid e, we compute the similarity using a RBF kernel. Theta is a hyper parameter. -``$`K_c(f_\theta, e_c) = exp(-\frac{\frac{1}{n}\mid \mid W_cf_\theta(x) - e_c\mid\mid^2_2}{2\sigma^2})`$`` +$K_c(f_\theta, e_c) = exp(-\frac{\frac{1}{n}\mid \mid W_cf_\theta(x) - e_c\mid\mid^2_2}{2\sigma^2})$ with this similarity we can make a prediction by selecting the centroid with the highest similarity. The loss function is now simply -``$`L(x,y) = - \sum_c y_clog(K_c) + (1 - y_c)log(1-K_c)`$``, +$L(x,y) = - \sum_c y_clog(K_c) + (1 - y_c)log(1-K_c)$, -where ``$`K_c(f_\theta, e_c)=K_c`$`` +where $K_c(f_\theta, e_c)=K_c$ After each batch, we update the centroid matrix using an exponential moving average. ### Regularization -To avoid feature collapse, the authors introduce a gradient penalty directly applied to ``$`K_c`$``: -``$`\lambda* (\mid\mid \nabla_x \sum_c K_c\mid\mid^2_2 - 1)^2`$`` -where 1 is the Lipschitz constant. In their experiments, they use ``$`\lambda=0.05`$``. +To avoid feature collapse, the authors introduce a gradient penalty directly applied to $K_c$: +$\lambda* (\mid\mid \nabla_x \sum_c K_c\mid\mid^2_2 - 1)^2$ +where 1 is the Lipschitz constant. In their experiments, they use $\lambda=0.05$. In summary, this simple technique is faster and better than ensembles. It also shows that RBF networks work on large datasets. diff --git a/docs/research/literature/Additional papers/lightcoresets.md b/docs/research/literature/Additional papers/lightcoresets.md index a1108ef0..7d9b4d32 100644 --- a/docs/research/literature/Additional papers/lightcoresets.md +++ b/docs/research/literature/Additional papers/lightcoresets.md @@ -6,16 +6,16 @@ This paper presents a novel Coreset algorithm called *Light Coreset*. -Let ``$`X`$`` be the dataset, ``$`d`$`` a distance function and ``$`\mu(X)`$`` the mean of the dataset per feature. +Let $X$ be the dataset, $d$ a distance function and $\mu(X)$ the mean of the dataset per feature. -We compute the distribution ``$`q`$``with: +We compute the distribution $q$with: -``$`q(x) = 0.5 * \frac{1}{\vert X \vert} + 0.5 * \frac{d(x, \mu(X))^2}{\sum_{x' \in X} d(x', \mu(X))^2}`$``, -where ``$`x \in X`$``. +$q(x) = 0.5 * \frac{1}{\vert X \vert} + 0.5 * \frac{d(x, \mu(X))^2}{\sum_{x' \in X} d(x', \mu(X))^2}$, +where $x \in X$. -We can then select ``$`m`$`` samples by sampling from this distribution. For their experiments, they used the L2 distance for *d*. +We can then select $m$ samples by sampling from this distribution. For their experiments, they used the L2 distance for *d*. -Let A be the first part of the equation ``$`q`$`` and B the second. The authors offers the following explanation : +Let A be the first part of the equation $q$ and B the second. The authors offers the following explanation : >The first component (A) is the uniform distribution and ensures that all points are sampled with nonzero probability. The second diff --git a/docs/research/literature/Additional papers/sparse_selection.md b/docs/research/literature/Additional papers/sparse_selection.md index 0e029c58..91244022 100644 --- a/docs/research/literature/Additional papers/sparse_selection.md +++ b/docs/research/literature/Additional papers/sparse_selection.md @@ -11,16 +11,16 @@ Published at NeurIPS 2019 A known issue of BALD, when used in Batch Active Learning is that it selects highly correlated samples. By combining BNNs with a novel coreset algorithm, the authors propose a way to estimate the true posterior data distribution. -In brief, they want to select a batch ``$`D'`$`` such that the posterior distribution best approximate the complete data posterior. +In brief, they want to select a batch $D'$ such that the posterior distribution best approximate the complete data posterior. Because we do not know the complete posterior, the authors approximate it using the predictive distribution. The idea is summarized in Eq. 4. ![](../images/sparse_selection/eq4.png) -This measure can be optimized using Frank-Wolfe which uses the dot-product ``$`\langle L_m, L_n\rangle`$`` to estimate the affectations. +This measure can be optimized using Frank-Wolfe which uses the dot-product $\langle L_m, L_n\rangle$ to estimate the affectations. -While a closed-form procedure exists to compute this dot-product, it is expensive to run (``$`O(||P||^2)`$``). -The authors suggest the use of random projections drawn from the parameters distribution ``$`\hat\pi`$``. -This approximation makes the algorithm ``$`O(||P||J)`$``, where J is the number of samples drawn from ``$`\hat\pi`$``. +While a closed-form procedure exists to compute this dot-product, it is expensive to run ($O(||P||^2)$). +The authors suggest the use of random projections drawn from the parameters distribution $\hat\pi$. +This approximation makes the algorithm $O(||P||J)$, where J is the number of samples drawn from $\hat\pi$. diff --git a/docs/research/literature/index.md b/docs/research/literature/index.md index 325468b8..e68741fc 100644 --- a/docs/research/literature/index.md +++ b/docs/research/literature/index.md @@ -4,8 +4,8 @@ This page is here to collect summaries of papers that focus on active learning. The idea is to share knowledge on recent developments in active learning. If you've read a paper recently, write a little summary in markdown, put it in -the folder `docs/literature` and make a pull request. You can even do all of -that right in the github web UI! +the folder `docs/research/literature` and make a pull request. You can even do all of +that right in the Github web UI! ```eval_rst .. toctree:: diff --git a/docs/support/faq.md b/docs/support/faq.md index 58d99618..5f72acbd 100644 --- a/docs/support/faq.md +++ b/docs/support/faq.md @@ -103,11 +103,11 @@ al_dataset.label_randomly(10) pool = al_dataset.pool ``` -From a rigorous point of view: ``$`D = ds `$`` , ``$`D_L=al\_dataset `$`` and ``$`D_U = D \setminus D_L = pool `$``. -Then, we train our model on ``$`D_L `$`` and compute the uncertainty on ``$`D_U `$``. The most uncertains samples are -labelled and added to ``$`D_L `$``, removed from ``$`D_U `$``. +From a rigorous point of view: $D = ds $ , $D_L=al\_dataset $ and $D_U = D \setminus D_L = pool $. +Then, we train our model on $D_L $ and compute the uncertainty on $D_U $. The most uncertains samples are +labelled and added to $D_L $, removed from $D_U $. -Let a method `query_human` performs the annotations, we can label our dataset using indices relative to``$`D_U `$``. +Let a method `query_human` performs the annotations, we can label our dataset using indices relative to$D_U $. This assumes that your dataset class `YourDataset` has a method named `label` which has the following definition: `def label(self, idx, value)` where we give the label for index `idx`. There the index is not relative to the pool, so you don't have to worry about it. diff --git a/docs/support/index.md b/docs/support/index.md index 852c875b..20d656be 100644 --- a/docs/support/index.md +++ b/docs/support/index.md @@ -1,2 +1,9 @@ # Support +For support, we have several ways to help you: + +* Our [:material-help: FAQ](faq.md) +* Submit an issue on Github [here](https://github.com/baal-org/baal/issues/new/choose) +* Join our [:material-slack: Slack](https://join.slack.com/t/baal-world/shared_invite/zt-z0izhn4y-Jt6Zu5dZaV2rsAS9sdISfg)! + * General questions can be asked under the #questions channel + \ No newline at end of file diff --git a/docs/tutorials/index.md b/docs/tutorials/index.md new file mode 100644 index 00000000..82e70532 --- /dev/null +++ b/docs/tutorials/index.md @@ -0,0 +1,16 @@ +# Tutorials + +Tutorials are split in two sections, "How-to" and "Compatibility". The first one focuses on Baal's capabilities and the +latter on how we integrate with other common frameworks such as [Label Studio], [HuggingFace] or [Lightning Flash]. + +## :material-file-tree: How to + +* Run an active learning experiments +* Active learning in production +* Deep Ensembles + +## :material-file-tree: Compatibility + +* [:material-link: Lightning Flash](https://devblog.pytorchlightning.ai/active-learning-made-simple-using-flash-and-baal-2216df6f872c) +* [HuggingFace](../notebooks/compatibility/nlp_classification.ipynb) +* [Scikit-Learn](../notebooks/compatibility/sklearn_tutorial.ipynb) \ No newline at end of file diff --git a/docs/industry/label-studio.md b/docs/tutorials/label-studio.md similarity index 100% rename from docs/industry/label-studio.md rename to docs/tutorials/label-studio.md diff --git a/docs/user_guide/baal_cheatsheet.md b/docs/user_guide/baal_cheatsheet.md index 57975ca6..c7200fba 100644 --- a/docs/user_guide/baal_cheatsheet.md +++ b/docs/user_guide/baal_cheatsheet.md @@ -7,9 +7,9 @@ In the table below, we have a mapping between common equations and the BaaL API. Here are the types for all variables needed. ```python -model : torch.nn.Module -wrapper : baal.ModelWrapper -dataset: torch.utils.data_utils.Dataset +model: torch.nn.Module +wrapper: baal.ModelWrapper +dataset: torch.utils.data_utils.Dataset bald = baal.active.heuristics.BALD() entropy = baal.active.heuristics.Entropy() ``` @@ -18,17 +18,12 @@ We assume that `baal.bayesian.dropout.patch_module` has been applied to the mode `model = baal.bayesian.dropout.patch_module(model)` -```eval_rst -.. csv-table:: BaaL cheat sheet - :header: "Description", "Equation", "BaaL" - :widths: 20, 20, 40 - - "Bayesian Model Averaging", ":math:`\hat{T} = p(y \mid x, {\cal D})= \int p(y \mid x, \theta)p(\theta \mid D) d\theta`", "`wrapper.predict_on_dataset(dataset, batch_size=B, iterations=I, use_cuda=True).mean(-1)`" - "MC-Dropout", ":math:`T = \{p(y\mid x_j, \theta_i)\} \mid x_j \in {\cal D}' ,i \in \{1, \ldots, I\}`", "`wrapper.predict_on_dataset(dataset, batch_size=B, iterations=I, use_cuda=True)`" - "BALD", ":math:`{\cal I}[y, \theta \mid x, {\cal D}] = {\cal H}[y \mid x, {\cal D}] - {\cal E}_{p(\theta \mid {\cal D})}[{\cal H}[y \mid x, \theta]]`", "`bald.get_uncertainties(T)`" - "Entropy", ":math:`\sum_c \hat{T}_c \log(\hat{T}_c)`", "`entropy.get_uncertainties(T)`" - -``` +| Description | Equation | BaaL | +|--------------------------|----------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------| +| Bayesian Model Averaging | $\hat{T} = p(y \mid x, {\cal D})= \int p(y \mid x, \theta)p(\theta \mid D) d\theta$ | `wrapper.predict_on_dataset(dataset, batch_size=B, iterations=I, use_cuda=True).mean(-1)` | +| MC-Dropout | $T = \{p(y\mid x_j, \theta_i)\} \mid x_j \in {\cal D}' ,i \in \{1, \ldots, I\}$ | `wrapper.predict_on_dataset(dataset, batch_size=B, iterations=I, use_cuda=True)` | +| BALD | ${\cal I}[y, \theta \mid x, {\cal D}] = {\cal H}[y \mid x, {\cal D}] - {\cal E}_{p(\theta \mid {\cal D})}[{\cal H}[y \mid x, \theta]]$ | `bald.get_uncertainties(T)` | +| Entropy | $\sum_c \hat{T}_c \log(\hat{T}_c)$ | `entropy.get_uncertainties(T)` | **Contributing** diff --git a/docs/user_guide/index.md b/docs/user_guide/index.md index 4fc2a264..bc27f9e7 100644 --- a/docs/user_guide/index.md +++ b/docs/user_guide/index.md @@ -6,9 +6,9 @@ In addition, we propose a [cheat sheet](./baal_cheatsheet.md) that will help use ### Notations and glossary -* Training dataset ``$`D_L`$`` -* Pool, the unlabelled portion of the dataset ``$`D_U`$`` -* Heuristic, the function that computes the uncertainty (ex. BALD) ``$`U `$`` +* Training dataset $D_L$ +* Pool, the unlabelled portion of the dataset $D_U$ +* Heuristic, the function that computes the uncertainty (ex. BALD) $U$ * Active learning step, the sequence of training, selecting and labelling one or many examples. * BALD, an heuristic that works well with deep learning models that are overconfident. * Query size, the number of items to label between retraining. @@ -60,6 +60,7 @@ We hope that work in this area continues so that we can better understand the im **References** + * Kirsch, Andreas, Joost Van Amersfoort, and Yarin Gal. "Batchbald: Efficient and diverse batch acquisition for deep bayesian active learning." NeurIPS (2019). * Jain, Siddhartha, Ge Liu, and David Gifford. "Information Condensing Active Learning." arXiv preprint arXiv:2002.07916 (2020). * Houlsby, Neil, et al. "Bayesian active learning for classification and preference learning." arXiv preprint arXiv:1112.5745 (2011). diff --git a/mkdocs.yml b/mkdocs.yml index 6b6a4c26..8073c11d 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -21,30 +21,82 @@ theme: name: Switch to light mode features: - navigation.tabs + - navigation.tabs.sticky - navigation.indexes - navigation.instant icon: repo: fontawesome/brands/github plugins: - search + - mkdocs-jupyter + - mkdocstrings markdown_extensions: + - md_in_html - attr_list + - pymdownx.arithmatex: + generic: true - pymdownx.emoji: emoji_index: !!python/name:materialx.emoji.twemoji emoji_generator: !!python/name:materialx.emoji.to_svg + - pymdownx.highlight: + anchor_linenums: true + - pymdownx.inlinehilite + - pymdownx.snippets + - pymdownx.superfences + +extra_javascript: + - javascripts/mathjax.js + - https://polyfill.io/v3/polyfill.min.js?features=es6 + - https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js nav: - Home: index.md - User Guide: - user_guide/index.md + - Cheat Sheet: user_guide/baal_cheatsheet.md + - Active data structure: notebooks/fundamentals/active-learning.ipynb + - Computing uncertainty: + - Stochastic models: notebooks/fundamentals/active-learning.ipynb + - Heuristics: user_guide/heuristics.md - API: - api/index.md - - Production: - - industry/index.md + - api/bayesian.md + - api/calibration.md + - api/dataset_management.md + - api/heuristics.md + - api/modelwrapper.md + - api/utils.md + - Compatibility: + - api/compatibility/huggingface.md + - api/compatibility/pytorch-lightning.md + + - Tutorials: + - tutorials/index.md + - Compatibility: + - tutorials/label-studio.md + - notebooks/compatibility/nlp_classification.ipynb + - notebooks/compatibility/sklearn_tutorial.ipynb + - notebooks/baal_prod_cls.ipynb + - notebooks/deep_ensemble.ipynb - Research: - research/index.md - - Blog: - - blog/index.md + - Technical Reports: + - notebooks/fairness/ActiveFairness.ipynb + - research/dirichlet_calibration.md + - research/double_descent.md + - Literature: + - research/literature/index.md + - research/literature/core-papers.md + - Additional papers: + - research/literature/more_papers.md + - research/literature/Additional papers/dmi.md + - research/literature/Additional papers/duq.md + - research/literature/Additional papers/gyolov3.md + - research/literature/Additional papers/lightcoresets.md + - research/literature/Additional papers/sparse_selection.md + - research/literature/Additional papers/vaal.md + - Support: - support/index.md + - support/faq.md diff --git a/notebooks/active_learning_process.ipynb b/notebooks/active_learning_process.ipynb index 9faf3f2e..37b91082 100644 --- a/notebooks/active_learning_process.ipynb +++ b/notebooks/active_learning_process.ipynb @@ -2,11 +2,15 @@ "cells": [ { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, "source": [ "# How to do research and visualize progress\n", "\n", - "In this tutorial, we will show how to use BaaL for research ie. when we know the labels.\n", + "In this tutorial, we will show how to use Baal for research ie. when we know the labels.\n", "We will introduce notions such as dataset management, MC-Dropout, BALD. If you need more documentation, be sure to check our **Additional resources** section below!\n", "\n", "BaaL can be used on a variety of research domains:\n", @@ -38,7 +42,11 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [], "source": [ "# Let's start with a bunch of imports.\n", @@ -73,7 +81,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, "source": [ "### Dataset management and the pool\n", "\n", @@ -111,7 +123,11 @@ { "cell_type": "code", "execution_count": 2, - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [], "source": [ "\"\"\"\n", @@ -139,7 +155,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, "source": [ "Here we define our Experiment configuration, this can come from your favorite experiment manager like MLFlow.\n", "BaaL does not expect a particular format as all arguments are supplied." @@ -148,7 +168,11 @@ { "cell_type": "code", "execution_count": 3, - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [], "source": [ "\n", @@ -183,7 +207,11 @@ { "cell_type": "code", "execution_count": 4, - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [], "source": [ "def get_datasets(initial_pool):\n", @@ -261,7 +289,11 @@ { "cell_type": "code", "execution_count": 5, - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [ { "name": "stdout", @@ -316,7 +348,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, "source": [ "### What is an active learning loop\n", "\n", @@ -329,775 +365,14 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "db80f856c34647a1a8e129a84339a57f", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/200 [00:00" ] } ], diff --git a/poetry.lock b/poetry.lock index 970d6b6d..e41cbd4e 100644 --- a/poetry.lock +++ b/poetry.lock @@ -42,6 +42,17 @@ python-versions = ">=3.6" [package.dependencies] frozenlist = ">=1.1.0" +[[package]] +name = "astunparse" +version = "1.6.3" +description = "An AST unparser for Python" +category = "dev" +optional = false +python-versions = "*" + +[package.dependencies] +six = ">=1.6.1,<2.0" + [[package]] name = "async-timeout" version = "4.0.2" @@ -485,6 +496,20 @@ requests-oauthlib = ">=0.7.0" [package.extras] tool = ["click (>=6.0.0)"] +[[package]] +name = "griffe" +version = "0.21.0" +description = "Signatures for entire Python programs. Extract the structure, the frame, the skeleton of your project, to generate API documentation or find breaking changes in your API." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +cached-property = {version = "*", markers = "python_version < \"3.8\""} + +[package.extras] +async = ["aiofiles (>=0.7,<1.0)"] + [[package]] name = "grpcio" version = "1.43.0" @@ -638,7 +663,7 @@ python-versions = ">=3.6" [[package]] name = "jsonargparse" -version = "4.9.0" +version = "4.10.0" description = "Parsing of command line options, yaml/jsonnet config files and/or environment variables based on argparse." category = "dev" optional = false @@ -649,9 +674,8 @@ docstring-parser = {version = ">=0.7.3", optional = true, markers = "extra == \" PyYAML = ">=3.13" [package.extras] -all = ["docstring-parser (>=0.7.3)", "jsonschema (>=3.2.0)", "jsonnet (>=0.13.0)", "validators (>=0.14.2)", "requests (>=2.18.4)", "fsspec (>=0.8.4)", "argcomplete (>=2.0.0)", "ruyaml 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+[[package]] +name = "mkdocs-autorefs" +version = "0.4.1" +description = "Automatically link across pages in MkDocs." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +Markdown = ">=3.3" +mkdocs = ">=1.1" + [[package]] name = "mkdocs-jupyter" version = "0.21.0" @@ -1017,6 +1053,53 @@ category = "dev" optional = false python-versions = ">=3.6" +[[package]] +name = "mkdocstrings" +version = "0.18.1" +description = "Automatic documentation from sources, for MkDocs." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +Jinja2 = ">=2.11.1" +Markdown = ">=3.3" +MarkupSafe = ">=1.1" +mkdocs = ">=1.2" +mkdocs-autorefs = ">=0.3.1" +mkdocstrings-python = {version = ">=0.5.2", optional = true, markers = "extra == \"python\""} +mkdocstrings-python-legacy = ">=0.2" +pymdown-extensions = ">=6.3" + +[package.extras] +crystal = ["mkdocstrings-crystal (>=0.3.4)"] +python = ["mkdocstrings-python (>=0.5.2)"] +python-legacy = ["mkdocstrings-python-legacy (>=0.2.1)"] + +[[package]] +name = "mkdocstrings-python" +version = "0.6.6" +description = "A Python handler for mkdocstrings." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +griffe = ">=0.11.1" +mkdocstrings = ">=0.18" + +[[package]] +name = "mkdocstrings-python-legacy" +version = "0.2.2" +description = "A legacy Python handler for mkdocstrings." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +mkdocstrings = ">=0.18" +pytkdocs = ">=0.14" + [[package]] name = "multidict" version = "5.2.0" @@ -1466,6 +1549,22 @@ python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" [package.dependencies] six = ">=1.5" +[[package]] +name = "pytkdocs" +version = "0.16.1" +description = "Load Python objects documentation." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +astunparse = {version = ">=1.6", markers = "python_version < \"3.9\""} +cached-property 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"sha256:e2ccf6dfe9dbbceb09818673f040f1a7c32ed0bffb2d709b06be6453c4026045"}, +] pytorch-lightning = [ {file = "pytorch-lightning-1.5.8.tar.gz", hash = "sha256:57e7c9ea3663e5d8416be6a340d3a8d9271eb105fba82b7f7497cf0299880939"}, {file = "pytorch_lightning-1.5.8-py3-none-any.whl", hash = "sha256:75783eb6c4d043d95691a341a81e7df2bcb02254779992f86c4276cf6ff3739b"}, diff --git a/pyproject.toml b/pyproject.toml index 73a776a9..f270cfbe 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -49,8 +49,12 @@ docutils = "0.16" # Lightning lightning-flash = {git = "https://github.com/PyTorchLightning/lightning-flash.git", extras = ["image"]} + +# Documentation mkdocs-jupyter = "^0.21.0" mkdocs-material = "^8.3.6" +Pygments = "^2.12.0" +mkdocstrings = {extras = ["python"], version = "^0.18.1"} [tool.poetry.extras] vision = ["torchvision"] From 5fbdcccfe5e4a978b224cc51072270b9025c084e Mon Sep 17 00:00:00 2001 From: Dref360 Date: Sat, 9 Jul 2022 16:46:06 -0400 Subject: [PATCH 03/10] Changes according to review --- docs/index.md | 13 +++++++ docs/notebooks | 1 + docs/research/index.md | 12 ++++++- docs/research/literature/core-papers.md | 39 --------------------- docs/research/literature/index.md | 45 ++++++++++++++++++++----- docs/research/literature/more_papers.md | 12 ------- docs/tutorials/index.md | 8 ++--- docs/user_guide/heuristics.md | 34 +++++++++++++++++++ mkdocs.yml | 13 +++---- 9 files changed, 107 insertions(+), 70 deletions(-) create mode 120000 docs/notebooks delete mode 100644 docs/research/literature/core-papers.md delete mode 100644 docs/research/literature/more_papers.md create mode 100644 docs/user_guide/heuristics.md diff --git a/docs/index.md b/docs/index.md index 5bcdac01..4fd4ca7a 100644 --- a/docs/index.md +++ b/docs/index.md @@ -9,6 +9,19 @@ To know more on what is Bayesian active learning, see our [User guide](user_guid We are a member of Pytorch's ecosystem, and we welcome contributions from the community. If you have any question, we are reachable on [Slack](https://join.slack.com/t/baal-world/shared_invite/zt-z0izhn4y-Jt6Zu5dZaV2rsAS9sdISfg). +## Installation + +Baal is available as a package on PyPI: + +`pip install baal` + +??? "Additional dependencies for vision and NLP" + + `baal[nlp]` installs needed dependencies for HuggingFace support. + + `baal[vision]` installs dependencies for our Lightning-Flash integration. + + ## Support For support, we have several ways to help you: diff --git a/docs/notebooks b/docs/notebooks new file mode 120000 index 00000000..8f9a5b2e --- /dev/null +++ b/docs/notebooks @@ -0,0 +1 @@ +../notebooks \ No newline at end of file diff --git a/docs/research/index.md b/docs/research/index.md index 64473875..86598ed8 100644 --- a/docs/research/index.md +++ b/docs/research/index.md @@ -1,2 +1,12 @@ -# Bayesian active learning research +# Bayesian deep active learning research +Research in this field is quite dynamic with multiple labs around the world working on this problem. + +In a nutshell, we want to: + +> Optimize labelling by maximizing the information obtained after each label. + +Another critical goal of our research is to better understand the sampling bias active learning creates. +Recent research has shown that active learning creates more balanced, fairer datasets. + +We strongly suggest to go through our [literature review](./literature/index.md). diff --git a/docs/research/literature/core-papers.md b/docs/research/literature/core-papers.md deleted file mode 100644 index 0606e5fd..00000000 --- a/docs/research/literature/core-papers.md +++ /dev/null @@ -1,39 +0,0 @@ -# The theory behind Bayesian active learning - -In this document, we keep a list of the papers to get you started in Bayesian deep learning and Bayesian active learning. - -We hope to include a summary for each of then in the future, but for now we have this list with some notes. - - -### How to estimate uncertainty in Deep Learning networks - -* [Excellent tutorial from AGW on Bayesian Deep Learning](https://icml.cc/virtual/2020/tutorial/5750) - * This is inspired by his publication [Bayesian Deep Learning and a Probabilistic Perspective of Generalization](https://arxiv.org/abs/2002.08791) -* [Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning](https://arxiv.org/pdf/1506.02142.pdf) (Gal and Ghahramani, 2016) - * This describes Monte-Carlo Dropout, a way to estimate uncertainty through stochastic dropout at test time -* [Bayesian Uncertainty Estimation for Batch Normalized Deep Networks](https://arxiv.org/abs/1802.06455) (Teye et al. 2018) - * This describes Monte-Carlo BatchNorm, a way to estimate uncertainty through random batch norm parameters at test time -* [Bayesian Deep Learning and a Probabilistic Perspective of Generalization](https://arxiv.org/abs/2002.08791) (Gordon Wilson and Izmailov, 2020) - * Presentation of multi-SWAG a mix between VI and Ensembles. -* [Advances in Variational inference](https://arxiv.org/pdf/1711.05597.pdf) (Zhang et al, 2018) - * Gives a quick introduction to VI and the most recent advances. -* [A Simple Baseline for Bayesian Uncertainty in Deep Learning](https://arxiv.org/abs/1902.02476) (Maddox et al. 2019) - * Presents SWAG, an easy way to create ensembles. - - - - -### Bayesian active learning -* [Deep Bayesian Active Learning with Image Data](https://arxiv.org/pdf/1703.02910.pdf) (Gal and Islam and Ghahramani, 2017) - * Fundamental paper on how to do Bayesian active learning. A must read. -* [Sampling bias in active learning](http://cseweb.ucsd.edu/~dasgupta/papers/twoface.pdf) (Dasgupta 2009) - * Presents sampling bias and how to solve it by combining heuristics and random selection. - -* [Bayesian Active Learning for Classification and Preference Learning](https://arxiv.org/pdf/1112.5745.pdf) (Houlsby et al. 2011) - * Fundamental paper on one of the main heuristic BALD. - - -### Bayesian active learning on NLP - -* [Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study](https://arxiv.org/abs/1808.05697) (Siddhant and Lipton, 2018) - * Experimental paper on how to use Bayesian active learning on NLP tasks. diff --git a/docs/research/literature/index.md b/docs/research/literature/index.md index e68741fc..02f7dc58 100644 --- a/docs/research/literature/index.md +++ b/docs/research/literature/index.md @@ -7,13 +7,42 @@ If you've read a paper recently, write a little summary in markdown, put it in the folder `docs/research/literature` and make a pull request. You can even do all of that right in the Github web UI! -```eval_rst -.. toctree:: - :caption: Literature review - :maxdepth: 1 - :glob: +## The theory behind Bayesian active learning - * -``` +In this document, we keep a list of the papers to get you started in Bayesian deep learning and Bayesian active learning. ---- \ No newline at end of file +We hope to include a summary for each of then in the future, but for now we have this list with some notes. + + +### How to estimate uncertainty in Deep Learning networks + +* [Excellent tutorial from AGW on Bayesian Deep Learning](https://icml.cc/virtual/2020/tutorial/5750) + * This is inspired by his publication [Bayesian Deep Learning and a Probabilistic Perspective of Generalization](https://arxiv.org/abs/2002.08791) +* [Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning](https://arxiv.org/pdf/1506.02142.pdf) (Gal and Ghahramani, 2016) + * This describes Monte-Carlo Dropout, a way to estimate uncertainty through stochastic dropout at test time +* [Bayesian Uncertainty Estimation for Batch Normalized Deep Networks](https://arxiv.org/abs/1802.06455) (Teye et al. 2018) + * This describes Monte-Carlo BatchNorm, a way to estimate uncertainty through random batch norm parameters at test time +* [Bayesian Deep Learning and a Probabilistic Perspective of Generalization](https://arxiv.org/abs/2002.08791) (Gordon Wilson and Izmailov, 2020) + * Presentation of multi-SWAG a mix between VI and Ensembles. +* [Advances in Variational inference](https://arxiv.org/pdf/1711.05597.pdf) (Zhang et al, 2018) + * Gives a quick introduction to VI and the most recent advances. +* [A Simple Baseline for Bayesian Uncertainty in Deep Learning](https://arxiv.org/abs/1902.02476) (Maddox et al. 2019) + * Presents SWAG, an easy way to create ensembles. + + + + +### Bayesian active learning +* [Deep Bayesian Active Learning with Image Data](https://arxiv.org/pdf/1703.02910.pdf) (Gal and Islam and Ghahramani, 2017) + * Fundamental paper on how to do Bayesian active learning. A must read. +* [Sampling bias in active learning](http://cseweb.ucsd.edu/~dasgupta/papers/twoface.pdf) (Dasgupta 2009) + * Presents sampling bias and how to solve it by combining heuristics and random selection. + +* [Bayesian Active Learning for Classification and Preference Learning](https://arxiv.org/pdf/1112.5745.pdf) (Houlsby et al. 2011) + * Fundamental paper on one of the main heuristic BALD. + + +### Bayesian active learning on NLP + +* [Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study](https://arxiv.org/abs/1808.05697) (Siddhant and Lipton, 2018) + * Experimental paper on how to use Bayesian active learning on NLP tasks. diff --git a/docs/research/literature/more_papers.md b/docs/research/literature/more_papers.md deleted file mode 100644 index 0326ab1a..00000000 --- a/docs/research/literature/more_papers.md +++ /dev/null @@ -1,12 +0,0 @@ -## Additional papers that are interesting - -In this section, we put additional papers that can be interesting. - -```eval_rst -.. toctree:: - :maxdepth: 1 - :caption: Additional papers - :glob: - - Additional papers/* -``` \ No newline at end of file diff --git a/docs/tutorials/index.md b/docs/tutorials/index.md index 82e70532..a8711f11 100644 --- a/docs/tutorials/index.md +++ b/docs/tutorials/index.md @@ -1,13 +1,13 @@ # Tutorials Tutorials are split in two sections, "How-to" and "Compatibility". The first one focuses on Baal's capabilities and the -latter on how we integrate with other common frameworks such as [Label Studio], [HuggingFace] or [Lightning Flash]. +latter on how we integrate with other common frameworks such as Label Studio, HuggingFace or Lightning Flash. ## :material-file-tree: How to -* Run an active learning experiments -* Active learning in production -* Deep Ensembles +* [Run an active learning experiments](notebooks/active_learning_process.ipynb) +* [Active learning in production](notebooks/baal_prod_cls.ipynb) +* [Deep Ensembles](../notebooks/deep_ensemble.ipynb) ## :material-file-tree: Compatibility diff --git a/docs/user_guide/heuristics.md b/docs/user_guide/heuristics.md new file mode 100644 index 00000000..019f7ecb --- /dev/null +++ b/docs/user_guide/heuristics.md @@ -0,0 +1,34 @@ +# Active learning heuristics + +**Heuristics** take a set of predictions and outputs the order in which they should be labelled. + +A simple heuristic would be to prioritize items where the model had low confidence. +We will cover the two main heuristics: **Entropy** and **BALD**. + + +### Entropy + +The goal of this heuristic is to maximize information. To do so, we will compute the entropy of each prediction before ordering them. + +Let $p_c(x)$ be the probability of input $x$ to be from class $c$. The entropy can be computed as: + +$$ +H(x) = \sum_c^C p_c(x) +$$ + +This score reflects the informativeness of knowing the true label of $x$. +Naturally the next item to label would be $argmax_{x \in {\cal D}} H(x)$, where ${\cal D} is our dataset$ + +A drawback of this method is that it doesn't differentiate between *aleatoric* uncertainty and *epistemic* uncertainty. +To do so, we will use BALD + +### BALD + +Bayesian active learning by disagrement or BALD (Houslby et al. 2013) is the basis of most modern active learning heuristics. + +From a Bayesian model $f$, we draw $I$ predictions per sample $x$. + +Then, we want to maximize the mutual information between a prediction and the model's parameters. This is done by looking at how the predictions are disagreeing with each others. +If the prediction "flips" often, it means that the item is close to a decision boundary and thus hard to fit. + + ${\cal I}[y, \theta \mid x, {\cal D}] = {\cal H}[y \mid x, {\cal D}] - {\cal E}_{p(\theta \mid {\cal D})}[{\cal H}[y \mid x, \theta]]$ diff --git a/mkdocs.yml b/mkdocs.yml index 8073c11d..5db0fab7 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -41,6 +41,8 @@ markdown_extensions: emoji_generator: !!python/name:materialx.emoji.to_svg - pymdownx.highlight: anchor_linenums: true + - admonition + - pymdownx.details - pymdownx.inlinehilite - pymdownx.snippets - pymdownx.superfences @@ -57,7 +59,7 @@ nav: - Cheat Sheet: user_guide/baal_cheatsheet.md - Active data structure: notebooks/fundamentals/active-learning.ipynb - Computing uncertainty: - - Stochastic models: notebooks/fundamentals/active-learning.ipynb + - Stochastic models: notebooks/fundamentals/posteriors.ipynb - Heuristics: user_guide/heuristics.md - API: - api/index.md @@ -77,19 +79,18 @@ nav: - tutorials/label-studio.md - notebooks/compatibility/nlp_classification.ipynb - notebooks/compatibility/sklearn_tutorial.ipynb - - notebooks/baal_prod_cls.ipynb - - notebooks/deep_ensemble.ipynb + - Active learning for research: notebooks/active_learning_process.ipynb + - Active learning for production: notebooks/baal_prod_cls.ipynb + - Deep Ensembles for active learning: notebooks/deep_ensemble.ipynb - Research: - research/index.md - Technical Reports: - - notebooks/fairness/ActiveFairness.ipynb + - Active Fairness: notebooks/fairness/ActiveFairness.ipynb - research/dirichlet_calibration.md - research/double_descent.md - Literature: - research/literature/index.md - - research/literature/core-papers.md - Additional papers: - - research/literature/more_papers.md - research/literature/Additional papers/dmi.md - research/literature/Additional papers/duq.md - research/literature/Additional papers/gyolov3.md From b1e6937127bb6c195a1ceed833de5e8851625153 Mon Sep 17 00:00:00 2001 From: Dref360 Date: Thu, 14 Jul 2022 16:23:40 -0400 Subject: [PATCH 04/10] Merge master --- poetry.lock | 1963 ++++++++++----------------------------------------- 1 file changed, 372 insertions(+), 1591 deletions(-) diff --git a/poetry.lock b/poetry.lock index c77306c1..4829b32c 100644 --- a/poetry.lock +++ b/poetry.lock @@ -40,63 +40,15 @@ python-versions = ">=3.6" frozenlist = ">=1.1.0" [[package]] -name = "alabaster" -version = "0.7.12" -description = "A configurable sidebar-enabled Sphinx theme" -category = "dev" -optional = false -python-versions = "*" - -[[package]] -name = "appnope" -version = "0.1.3" -description = "Disable App Nap on macOS >= 10.9" -category = "dev" -optional = false -python-versions = "*" - -[[package]] -name = "argon2-cffi" -version = "21.3.0" -description = "The secure Argon2 password hashing algorithm." -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -argon2-cffi-bindings = "*" -typing-extensions = {version = "*", markers = "python_version < \"3.8\""} - -[package.extras] -dev = ["pre-commit", "cogapp", "tomli", "coverage[toml] (>=5.0.2)", "hypothesis", "pytest", "sphinx", "sphinx-notfound-page", "furo"] -docs = ["sphinx", "sphinx-notfound-page", "furo"] -tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest"] - -[[package]] -name = "argon2-cffi-bindings" -version = "21.2.0" -description = "Low-level CFFI bindings for Argon2" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -cffi = ">=1.0.1" - -[package.extras] -dev = ["pytest", "cogapp", "pre-commit", "wheel"] -tests = ["pytest"] - -[[package]] -name = "asteroid-sphinx-theme" -version = "0.0.3" -description = "Asteroid: Sphinx Theme" +name = "astunparse" +version = "1.6.3" +description = "An AST unparser for Python" category = "dev" optional = false python-versions = "*" [package.dependencies] -sphinx = "*" +six = ">=1.6.1,<2.0" [[package]] name = "async-timeout" @@ -139,25 +91,6 @@ docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"] tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "cloudpickle"] tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "cloudpickle"] -[[package]] -name = "babel" -version = "2.10.3" -description = "Internationalization utilities" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -pytz = ">=2015.7" - -[[package]] -name = "backcall" -version = "0.2.0" -description = "Specifications for callback functions passed in to an API" -category = "dev" -optional = false -python-versions = "*" - [[package]] name = "bandit" version = "1.7.4" @@ -194,25 +127,29 @@ lxml = ["lxml"] [[package]] name = "black" -version = "22.6.0" +version = "21.12b0" description = "The uncompromising code formatter." category = "dev" optional = false python-versions = ">=3.6.2" [package.dependencies] -click = ">=8.0.0" +click = ">=7.1.2" mypy-extensions = ">=0.4.3" -pathspec = ">=0.9.0" +pathspec = ">=0.9.0,<1" platformdirs = ">=2" -tomli = {version = ">=1.1.0", markers = "python_full_version < \"3.11.0a7\""} +tomli = ">=0.2.6,<2.0.0" typed-ast = {version = ">=1.4.2", markers = "python_version < \"3.8\" and implementation_name == \"cpython\""} -typing-extensions = {version = ">=3.10.0.0", markers = "python_version < \"3.10\""} +typing-extensions = [ + {version = ">=3.10.0.0", markers = "python_version < \"3.10\""}, + {version = "!=3.10.0.1", markers = "python_version >= \"3.10\""}, +] [package.extras] colorama = ["colorama (>=0.4.3)"] d = ["aiohttp (>=3.7.4)"] jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"] +python2 = ["typed-ast (>=1.4.3)"] uvloop = ["uvloop (>=0.15.2)"] [[package]] @@ -231,6 +168,14 @@ webencodings = "*" css = ["tinycss2 (>=1.1.0,<1.2)"] dev = ["build (==0.8.0)", "flake8 (==4.0.1)", "hashin (==0.17.0)", "pip-tools (==6.6.2)", "pytest (==7.1.2)", "Sphinx (==4.3.2)", "tox (==3.25.0)", "twine (==4.0.1)", "wheel (==0.37.1)", "black (==22.3.0)", "mypy (==0.961)"] +[[package]] +name = "cached-property" +version = "1.5.2" +description = "A decorator for caching properties in classes." +category = "dev" +optional = false +python-versions = "*" + [[package]] name = "cachetools" version = "5.2.0" @@ -289,17 +234,6 @@ category = "main" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" -[[package]] -name = "commonmark" -version = "0.9.1" -description = "Python parser for the CommonMark Markdown spec" -category = "dev" -optional = false -python-versions = "*" - -[package.extras] -test = ["flake8 (==3.7.8)", "hypothesis (==3.55.3)"] - [[package]] name = "coverage" version = "6.4.1" @@ -347,32 +281,16 @@ xxhash = "*" apache-beam = ["apache-beam (>=2.26.0)"] audio = ["librosa"] benchmarks = ["numpy (==1.18.5)", "tensorflow (==2.3.0)", "torch (==1.6.0)", "transformers (==3.0.2)"] -dev = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch (<8.0.0)", "aiobotocore", "boto3", "botocore", "faiss-cpu (>=1.6.4)", "fsspec", "moto[s3,server] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "torch", "torchaudio", "soundfile", "transformers", "bs4", "conllu", "h5py", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "torchmetrics (==0.6.0)", "mauve-text", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "Pillow (>=6.2.1)", "librosa", "wget (>=3.2)", "pytorch-nlp (==0.5.0)", "pytorch-lightning", "fastBPE (==0.1.0)", "fairseq", "black (>=22.0,<23.0)", "flake8 (>=3.8.3)", "isort (>=5.0.0)", "pyyaml (>=5.3.1)", "importlib-resources"] +dev = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch (<8.0.0)", "aiobotocore", "boto3", "botocore", "faiss-cpu (>=1.6.4)", "fsspec", "moto[server,s3] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "torch", "torchaudio", "soundfile", "transformers", "bs4", "conllu", "h5py", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "torchmetrics (==0.6.0)", "mauve-text", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "Pillow (>=6.2.1)", "librosa", "wget (>=3.2)", "pytorch-nlp (==0.5.0)", "pytorch-lightning", "fastBPE (==0.1.0)", "fairseq", "black (>=22.0,<23.0)", "flake8 (>=3.8.3)", "isort (>=5.0.0)", "pyyaml (>=5.3.1)", "importlib-resources"] docs = ["docutils (==0.16.0)", "recommonmark", "sphinx (==3.1.2)", "sphinx-markdown-tables", "sphinx-rtd-theme (==0.4.3)", "sphinxext-opengraph (==0.4.1)", "sphinx-copybutton", "fsspec (<2021.9.0)", "s3fs", "sphinx-panels", "sphinx-inline-tabs", "myst-parser", "Markdown (!=3.3.5)"] quality = ["black (>=22.0,<23.0)", "flake8 (>=3.8.3)", "isort (>=5.0.0)", "pyyaml (>=5.3.1)"] s3 = ["fsspec", "boto3", "botocore", "s3fs"] tensorflow = ["tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)"] tensorflow_gpu = ["tensorflow-gpu (>=2.2.0,!=2.6.0,!=2.6.1)"] -tests = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch (<8.0.0)", "aiobotocore", "boto3", "botocore", "faiss-cpu (>=1.6.4)", "fsspec", "moto[s3,server] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "torch", "torchaudio", "soundfile", "transformers", "bs4", "conllu", "h5py", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "torchmetrics (==0.6.0)", "mauve-text", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "Pillow (>=6.2.1)", "librosa", "wget (>=3.2)", "pytorch-nlp (==0.5.0)", "pytorch-lightning", "fastBPE (==0.1.0)", "fairseq", "importlib-resources"] +tests = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch (<8.0.0)", "aiobotocore", "boto3", "botocore", "faiss-cpu (>=1.6.4)", "fsspec", "moto[server,s3] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "torch", "torchaudio", "soundfile", "transformers", "bs4", "conllu", "h5py", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "torchmetrics (==0.6.0)", "mauve-text", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "Pillow (>=6.2.1)", "librosa", "wget (>=3.2)", "pytorch-nlp (==0.5.0)", "pytorch-lightning", "fastBPE (==0.1.0)", "fairseq", "importlib-resources"] torch = ["torch"] vision = ["Pillow (>=6.2.1)"] -[[package]] -name = "debugpy" -version = "1.6.0" -description = "An implementation of the Debug Adapter Protocol for Python" -category = "dev" -optional = false -python-versions = ">=3.7" - -[[package]] -name = "decorator" -version = "5.1.1" -description = "Decorators for Humans" -category = "dev" -optional = false -python-versions = ">=3.5" - [[package]] name = "defusedxml" version = "0.7.1" @@ -518,6 +436,20 @@ smb = ["smbprotocol"] ssh = ["paramiko"] tqdm = ["tqdm"] +[[package]] +name = "ghp-import" +version = "2.1.0" +description = "Copy your docs directly to the gh-pages branch." +category = "dev" +optional = false +python-versions = "*" + +[package.dependencies] +python-dateutil = ">=2.8.1" + +[package.extras] +dev = ["twine", "markdown", "flake8", "wheel"] + [[package]] name = "gitdb" version = "4.0.9" @@ -576,6 +508,20 @@ requests-oauthlib = ">=0.7.0" [package.extras] tool = ["click (>=6.0.0)"] +[[package]] +name = "griffe" +version = "0.22.0" +description = "Signatures for entire Python programs. Extract the structure, the frame, the skeleton of your project, to generate API documentation or find breaking changes in your API." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +cached-property = {version = "*", markers = "python_version < \"3.8\""} + +[package.extras] +async = ["aiofiles (>=0.7,<1.0)"] + [[package]] name = "grpcio" version = "1.47.0" @@ -657,14 +603,6 @@ category = "main" optional = false python-versions = ">=3.5" -[[package]] -name = "imagesize" -version = "1.4.1" -description = "Getting image size from png/jpeg/jpeg2000/gif file" -category = "dev" -optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" - [[package]] name = "importlib-metadata" version = "4.12.0" @@ -705,104 +643,6 @@ category = "dev" optional = false python-versions = "*" -[[package]] -name = "ipykernel" -version = "6.15.0" -description = "IPython Kernel for Jupyter" -category = "dev" -optional = false -python-versions = ">=3.7" - -[package.dependencies] -appnope = {version = "*", markers = "platform_system == \"Darwin\""} -debugpy = ">=1.0" -ipython = ">=7.23.1" -jupyter-client = ">=6.1.12" -matplotlib-inline = ">=0.1" -nest-asyncio = "*" -packaging = "*" -psutil = "*" -pyzmq = ">=17" -tornado = ">=6.1" -traitlets = ">=5.1.0" - -[package.extras] -test = ["flaky", "ipyparallel", "pre-commit", "pytest-cov", "pytest-timeout", "pytest (>=6.0)"] - -[[package]] -name = "ipython" -version = "7.34.0" -description = "IPython: Productive Interactive Computing" -category = "dev" -optional = false -python-versions = ">=3.7" - -[package.dependencies] -appnope = {version = "*", markers = "sys_platform == \"darwin\""} -backcall = "*" -colorama = {version = "*", markers = "sys_platform == \"win32\""} -decorator = "*" -jedi = ">=0.16" -matplotlib-inline = "*" -pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""} -pickleshare = "*" -prompt-toolkit = ">=2.0.0,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.1.0" -pygments = "*" -traitlets = ">=4.2" - -[package.extras] -all = ["Sphinx (>=1.3)", "ipykernel", "ipyparallel", "ipywidgets", "nbconvert", "nbformat", "nose (>=0.10.1)", "notebook", "numpy (>=1.17)", "pygments", "qtconsole", "requests", "testpath"] -doc = ["Sphinx (>=1.3)"] -kernel = ["ipykernel"] -nbconvert = ["nbconvert"] -nbformat = ["nbformat"] -notebook = ["notebook", "ipywidgets"] -parallel = ["ipyparallel"] -qtconsole = ["qtconsole"] -test = ["nose (>=0.10.1)", "requests", "testpath", "pygments", "nbformat", "ipykernel", "numpy (>=1.17)"] - -[[package]] -name = "ipython-genutils" -version = "0.2.0" -description = "Vestigial utilities from IPython" -category = "dev" -optional = false -python-versions = "*" - -[[package]] -name = "ipywidgets" -version = "7.7.1" -description = "IPython HTML widgets for Jupyter" -category = "dev" -optional = false -python-versions = "*" - -[package.dependencies] -ipykernel = ">=4.5.1" -ipython = {version = ">=4.0.0", markers = "python_version >= \"3.3\""} -ipython-genutils = ">=0.2.0,<0.3.0" -jupyterlab-widgets = {version = ">=1.0.0", markers = "python_version >= \"3.6\""} -traitlets = ">=4.3.1" -widgetsnbextension = ">=3.6.0,<3.7.0" - -[package.extras] -test = ["pytest (>=3.6.0)", "pytest-cov", "mock"] - -[[package]] -name = "jedi" -version = "0.18.1" -description = "An autocompletion tool for Python that can be used for text editors." -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -parso = ">=0.8.0,<0.9.0" - -[package.extras] -qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] -testing = ["Django (<3.1)", "colorama", "docopt", "pytest (<7.0.0)"] - [[package]] name = "jinja2" version = "3.1.2" @@ -827,7 +667,7 @@ python-versions = ">=3.6" [[package]] name = "jsonargparse" -version = "4.10.2" +version = "4.11.0" description = "Parsing of command line options, yaml/jsonnet config files and/or environment variables based on argparse." category = "main" optional = true @@ -910,21 +750,6 @@ traitlets = "*" [package.extras] test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"] -[[package]] -name = "jupyter-sphinx" -version = "0.3.2" -description = "Jupyter Sphinx Extensions" -category = "dev" -optional = false -python-versions = ">= 3.6" - -[package.dependencies] -IPython = "*" -ipywidgets = ">=7.0.0" -nbconvert = ">=5.5" -nbformat = "*" -Sphinx = ">=2" - [[package]] name = "jupyterlab-pygments" version = "0.2.2" @@ -934,12 +759,23 @@ optional = false python-versions = ">=3.7" [[package]] -name = "jupyterlab-widgets" -version = "1.1.1" -description = "A JupyterLab extension." +name = "jupytext" +version = "1.14.0" +description = "Jupyter notebooks as Markdown documents, Julia, Python or R scripts" category = "dev" optional = false -python-versions = ">=3.6" +python-versions = "~=3.6" + +[package.dependencies] +markdown-it-py = ">=1.0.0,<3.0.0" +mdit-py-plugins = "*" +nbformat = "*" +pyyaml = "*" +toml = "*" + +[package.extras] +rst2md = ["sphinx-gallery (>=0.7.0,<0.8.0)"] +toml = ["toml"] [[package]] name = "kiwisolver" @@ -996,7 +832,7 @@ name = "markdown" version = "3.3.7" description = "Python implementation of Markdown." category = "main" -optional = true +optional = false python-versions = ">=3.6" [package.dependencies] @@ -1005,6 +841,28 @@ importlib-metadata = {version = ">=4.4", markers = "python_version < \"3.10\""} [package.extras] testing = ["coverage", "pyyaml"] +[[package]] +name = "markdown-it-py" +version = "2.1.0" +description = "Python port of markdown-it. Markdown parsing, done right!" +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +mdurl = ">=0.1,<1.0" +typing_extensions = {version = ">=3.7.4", markers = "python_version < \"3.8\""} + +[package.extras] +benchmarking = ["psutil", "pytest", "pytest-benchmark (>=3.2,<4.0)"] +code_style = ["pre-commit (==2.6)"] +compare = ["commonmark (>=0.9.1,<0.10.0)", "markdown (>=3.3.6,<3.4.0)", "mistletoe (>=0.8.1,<0.9.0)", "mistune (>=2.0.2,<2.1.0)", "panflute (>=2.1.3,<2.2.0)"] +linkify = ["linkify-it-py (>=1.0,<2.0)"] +plugins = ["mdit-py-plugins"] +profiling = ["gprof2dot"] +rtd = ["attrs", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx-book-theme"] +testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"] + [[package]] name = "markupsafe" version = "2.1.1" @@ -1033,23 +891,44 @@ python-dateutil = ">=2.7" setuptools_scm = ">=4" [[package]] -name = "matplotlib-inline" -version = "0.1.3" -description = "Inline Matplotlib backend for Jupyter" +name = "mccabe" +version = "0.6.1" +description = "McCabe checker, plugin for flake8" category = "dev" optional = false -python-versions = ">=3.5" +python-versions = "*" + +[[package]] +name = "mdit-py-plugins" +version = "0.3.0" +description = "Collection of plugins for markdown-it-py" +category = "dev" +optional = false +python-versions = "~=3.6" [package.dependencies] -traitlets = "*" +markdown-it-py = ">=1.0.0,<3.0.0" + +[package.extras] +code_style = ["pre-commit (==2.6)"] +rtd = ["myst-parser (>=0.14.0,<0.15.0)", "sphinx-book-theme (>=0.1.0,<0.2.0)"] +testing = ["coverage", "pytest (>=3.6,<4)", "pytest-cov", "pytest-regressions"] [[package]] -name = "mccabe" -version = "0.6.1" -description = "McCabe checker, plugin for flake8" +name = "mdurl" +version = "0.1.1" +description = "Markdown URL utilities" category = "dev" optional = false -python-versions = "*" +python-versions = ">=3.7" + +[[package]] +name = "mergedeep" +version = "1.3.4" +description = "A deep merge function for 🐍." +category = "dev" +optional = false +python-versions = ">=3.6" [[package]] name = "mistune" @@ -1059,6 +938,127 @@ category = "dev" optional = false python-versions = "*" +[[package]] +name = "mkdocs" +version = "1.3.0" +description = "Project documentation with Markdown." +category = "dev" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +click = ">=3.3" +ghp-import = ">=1.0" +importlib-metadata = ">=4.3" +Jinja2 = ">=2.10.2" +Markdown = ">=3.2.1" +mergedeep = ">=1.3.4" +packaging = ">=20.5" +PyYAML = ">=3.10" +pyyaml-env-tag = ">=0.1" +watchdog = ">=2.0" + +[package.extras] +i18n = ["babel (>=2.9.0)"] + +[[package]] +name = "mkdocs-autorefs" +version = "0.4.1" +description = "Automatically link across pages in MkDocs." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +Markdown = ">=3.3" +mkdocs = ">=1.1" + +[[package]] +name = "mkdocs-jupyter" +version = "0.21.0" +description = "Use Jupyter in mkdocs websites" +category = "dev" +optional = false +python-versions = ">=3.7.1,<4" + +[package.dependencies] +jupytext = ">=1.13.8,<2.0.0" +mkdocs = ">=1.2.3,<2.0.0" +mkdocs-material = ">=8.0.0,<9.0.0" +nbconvert = ">=6.2.0,<7.0.0" +Pygments = ">=2.12.0,<3.0.0" + +[[package]] +name = "mkdocs-material" +version = "8.3.9" +description = "Documentation that simply works" +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +jinja2 = ">=3.0.2" +markdown = ">=3.2" +mkdocs = ">=1.3.0" +mkdocs-material-extensions = ">=1.0.3" +pygments = ">=2.12" +pymdown-extensions = ">=9.4" + +[[package]] +name = "mkdocs-material-extensions" +version = "1.0.3" +description = "Extension pack for Python Markdown." +category = "dev" +optional = false +python-versions = ">=3.6" + +[[package]] +name = "mkdocstrings" +version = "0.18.1" +description = "Automatic documentation from sources, for MkDocs." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +Jinja2 = ">=2.11.1" +Markdown = ">=3.3" +MarkupSafe = ">=1.1" +mkdocs = ">=1.2" +mkdocs-autorefs = ">=0.3.1" +mkdocstrings-python = {version = ">=0.5.2", optional = true, markers = "extra == \"python\""} +mkdocstrings-python-legacy = ">=0.2" +pymdown-extensions = ">=6.3" + +[package.extras] +crystal = ["mkdocstrings-crystal (>=0.3.4)"] +python = ["mkdocstrings-python (>=0.5.2)"] +python-legacy = ["mkdocstrings-python-legacy (>=0.2.1)"] + +[[package]] +name = "mkdocstrings-python" +version = "0.6.6" +description = "A Python handler for mkdocstrings." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +griffe = ">=0.11.1" +mkdocstrings = ">=0.18" + +[[package]] +name = "mkdocstrings-python-legacy" +version = "0.2.2" +description = "A legacy Python handler for mkdocstrings." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +mkdocstrings = ">=0.18" +pytkdocs = ">=0.14" + [[package]] name = "multidict" version = "6.0.2" @@ -1172,22 +1172,6 @@ traitlets = ">=5.1" [package.extras] test = ["check-manifest", "testpath", "pytest", "pre-commit"] -[[package]] -name = "nbsphinx" -version = "0.8.9" -description = "Jupyter Notebook Tools for Sphinx" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -docutils = "*" -jinja2 = "*" -nbconvert = "!=5.4" -nbformat = "*" -sphinx = ">=1.8" -traitlets = ">=5" - [[package]] name = "nest-asyncio" version = "1.5.5" @@ -1196,36 +1180,6 @@ category = "dev" optional = false python-versions = ">=3.5" -[[package]] -name = "notebook" -version = "6.4.12" -description = "A web-based notebook environment for interactive computing" -category = "dev" -optional = false -python-versions = ">=3.7" - -[package.dependencies] -argon2-cffi = "*" -ipykernel = "*" -ipython-genutils = "*" -jinja2 = "*" -jupyter-client = ">=5.3.4" -jupyter-core = ">=4.6.1" -nbconvert = ">=5" -nbformat = "*" -nest-asyncio = ">=1.5" -prometheus-client = "*" -pyzmq = ">=17" -Send2Trash = ">=1.8.0" -terminado = ">=0.8.3" -tornado = ">=6.1" -traitlets = ">=4.2.1" - -[package.extras] -docs = ["sphinx", "nbsphinx", "sphinxcontrib-github-alt", "sphinx-rtd-theme", "myst-parser"] -json-logging = ["json-logging"] -test = ["pytest", "coverage", "requests", "testpath", "nbval", "selenium", "pytest-cov", "requests-unixsocket"] - [[package]] name = "numpy" version = "1.21.6" @@ -1234,21 +1188,6 @@ category = "main" optional = false python-versions = ">=3.7,<3.11" -[[package]] -name = "numpydoc" -version = "1.4.0" -description = "Sphinx extension to support docstrings in Numpy format" -category = "dev" -optional = false -python-versions = ">=3.7" - -[package.dependencies] -Jinja2 = ">=2.10" -sphinx = ">=3.0" - -[package.extras] -testing = ["pytest", "pytest-cov", "matplotlib"] - [[package]] name = "oauthlib" version = "3.2.0" @@ -1297,18 +1236,6 @@ category = "dev" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" -[[package]] -name = "parso" -version = "0.8.3" -description = "A Python Parser" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.extras] -qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] -testing = ["docopt", "pytest (<6.0.0)"] - [[package]] name = "pathspec" version = "0.9.0" @@ -1325,25 +1252,6 @@ category = "dev" optional = false python-versions = ">=2.6" -[[package]] -name = "pexpect" -version = "4.8.0" -description = "Pexpect allows easy control of interactive console applications." -category = "dev" -optional = false -python-versions = "*" - -[package.dependencies] -ptyprocess = ">=0.5" - -[[package]] -name = "pickleshare" -version = "0.7.5" -description = "Tiny 'shelve'-like database with concurrency support" -category = "dev" -optional = false -python-versions = "*" - [[package]] name = "pillow" version = "9.2.0" @@ -1383,28 +1291,6 @@ importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""} dev = ["pre-commit", "tox"] testing = ["pytest", "pytest-benchmark"] -[[package]] -name = "prometheus-client" -version = "0.14.1" -description = "Python client for the Prometheus monitoring system." -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.extras] -twisted = ["twisted"] - -[[package]] -name = "prompt-toolkit" -version = "3.0.30" -description = "Library for building powerful interactive command lines in Python" -category = "dev" -optional = false -python-versions = ">=3.6.2" - -[package.dependencies] -wcwidth = "*" - [[package]] name = "protobuf" version = "3.19.4" @@ -1413,25 +1299,6 @@ category = "main" optional = true python-versions = ">=3.5" -[[package]] -name = "psutil" -version = "5.9.1" -description = "Cross-platform lib for process and system monitoring in Python." -category = "dev" -optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" - -[package.extras] -test = ["ipaddress", "mock", "enum34", "pywin32", "wmi"] - -[[package]] -name = "ptyprocess" -version = "0.7.0" -description = "Run a subprocess in a pseudo terminal" -category = "dev" -optional = false -python-versions = "*" - [[package]] name = "py" version = "1.11.0" @@ -1510,6 +1377,17 @@ category = "dev" optional = false python-versions = ">=3.6" +[[package]] +name = "pymdown-extensions" +version = "9.5" +description = "Extension pack for Python Markdown." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +markdown = ">=3.2" + [[package]] name = "pyparsing" version = "3.0.9" @@ -1592,6 +1470,22 @@ python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" [package.dependencies] six = ">=1.5" +[[package]] +name = "pytkdocs" +version = "0.16.1" +description = "Load Python objects documentation." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +astunparse = {version = ">=1.6", markers = "python_version < \"3.9\""} +cached-property = {version = ">=1.5", markers = "python_version < \"3.8\""} +typing-extensions = {version = ">=3.7", markers = "python_version < \"3.8\""} + +[package.extras] +numpy-style = ["docstring_parser (>=0.7)"] + [[package]] name = "pytorch-lightning" version = "1.6.4" @@ -1631,7 +1525,7 @@ name = "pytz" version = "2022.1" description = "World timezone definitions, modern and historical" category = "main" -optional = false +optional = true python-versions = "*" [[package]] @@ -1642,14 +1536,6 @@ category = "dev" optional = false python-versions = "*" -[[package]] -name = "pywinpty" -version = "2.0.5" -description = "Pseudo terminal support for Windows from Python." -category = "dev" -optional = false -python-versions = ">=3.7" - [[package]] name = "pyyaml" version = "6.0" @@ -1659,29 +1545,27 @@ optional = false python-versions = ">=3.6" [[package]] -name = "pyzmq" -version = "23.2.0" -description = "Python bindings for 0MQ" +name = "pyyaml-env-tag" +version = "0.1" +description = "A custom YAML tag for referencing environment variables in YAML files. " category = "dev" optional = false python-versions = ">=3.6" [package.dependencies] -cffi = {version = "*", markers = "implementation_name == \"pypy\""} -py = {version = "*", markers = "implementation_name == \"pypy\""} +pyyaml = "*" [[package]] -name = "recommonmark" -version = "0.7.1" -description = "A docutils-compatibility bridge to CommonMark, enabling you to write CommonMark inside of Docutils & Sphinx projects." +name = "pyzmq" +version = "23.2.0" +description = "Python bindings for 0MQ" category = "dev" optional = false -python-versions = "*" +python-versions = ">=3.6" [package.dependencies] -commonmark = ">=0.8.1" -docutils = ">=0.11" -sphinx = ">=1.3.1" +cffi = {version = "*", markers = "implementation_name == \"pypy\""} +py = {version = "*", markers = "implementation_name == \"pypy\""} [[package]] name = "regex" @@ -1781,19 +1665,6 @@ python-versions = ">=3.7,<3.11" [package.dependencies] numpy = ">=1.16.5,<1.23.0" -[[package]] -name = "send2trash" -version = "1.8.0" -description = "Send file to trash natively under Mac OS X, Windows and Linux." -category = "dev" -optional = false -python-versions = "*" - -[package.extras] -nativelib = ["pyobjc-framework-cocoa", "pywin32"] -objc = ["pyobjc-framework-cocoa"] -win32 = ["pywin32"] - [[package]] name = "setuptools-scm" version = "7.0.4" @@ -1828,14 +1699,6 @@ category = "dev" optional = false python-versions = ">=3.6" -[[package]] -name = "snowballstemmer" -version = "2.2.0" -description = "This package provides 29 stemmers for 28 languages generated from Snowball algorithms." -category = "dev" -optional = false -python-versions = "*" - [[package]] name = "soupsieve" version = "2.3.2.post1" @@ -1844,153 +1707,6 @@ category = "dev" optional = false python-versions = ">=3.6" -[[package]] -name = "sphinx" -version = "5.0.2" -description = "Python documentation generator" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -alabaster = ">=0.7,<0.8" -babel = ">=1.3" -colorama = {version = ">=0.3.5", markers = "sys_platform == \"win32\""} -docutils = ">=0.14,<0.19" -imagesize = "*" -importlib-metadata = {version = ">=4.4", markers = "python_version < \"3.10\""} -Jinja2 = ">=2.3" -packaging = "*" -Pygments = ">=2.0" -requests = ">=2.5.0" -snowballstemmer = ">=1.1" -sphinxcontrib-applehelp = "*" -sphinxcontrib-devhelp = "*" -sphinxcontrib-htmlhelp = ">=2.0.0" -sphinxcontrib-jsmath = "*" -sphinxcontrib-qthelp = "*" -sphinxcontrib-serializinghtml = ">=1.1.5" - 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notebooks/active_learning_process.ipynb | 2 + notebooks/baal_prod_cls.ipynb | 51 +- .../compatibility/nlp_classification.ipynb | 69 +- .../compatibility/sklearn_tutorial.ipynb | 2 + notebooks/deep_ensemble.ipynb | 2 + notebooks/fairness/ActiveFairness.ipynb | 2 + notebooks/fundamentals/active-learning.ipynb | 4 +- notebooks/fundamentals/posteriors.ipynb | 2 + poetry.lock | 1063 ++--------------- pyproject.toml | 2 +- 14 files changed, 153 insertions(+), 1056 deletions(-) diff --git a/docs/tutorials/index.md b/docs/tutorials/index.md index a8711f11..c1e3095b 100644 --- a/docs/tutorials/index.md +++ b/docs/tutorials/index.md @@ -13,4 +13,5 @@ latter on how we integrate with other common frameworks such as Label Studio, Hu * [:material-link: Lightning Flash](https://devblog.pytorchlightning.ai/active-learning-made-simple-using-flash-and-baal-2216df6f872c) * [HuggingFace](../notebooks/compatibility/nlp_classification.ipynb) -* [Scikit-Learn](../notebooks/compatibility/sklearn_tutorial.ipynb) \ No newline at end of file +* [Scikit-Learn](../notebooks/compatibility/sklearn_tutorial.ipynb) +* [Label Studio](./label-studio.md) \ No newline at end of file diff --git a/docs/tutorials/label-studio.md b/docs/tutorials/label-studio.md index 206f103b..54832e7a 100644 --- a/docs/tutorials/label-studio.md +++ b/docs/tutorials/label-studio.md @@ -11,10 +11,12 @@ This is also a good way to start the conversation between your labelling team an We will built upon Label Studio's [Pytorch transfer learning](https://github.com/heartexlabs/label-studio-ml-backend/blob/master/label_studio_ml/examples/pytorch_transfer_learning.py) example, so be sure to download it and try to run it before adding BaaL to it. The full example can be found [here](https://gist.github.com/Dref360/288845b2fbb0504e4cfc216a76b547e7). More info: + * [BaaL documentation](https://baal.readthedocs.io/en/latest/) * [Bayesian Deep Learning cheatsheet](https://baal.readthedocs.io/en/latest/user_guide/baal_cheatsheet.html) Support: + * [Github](https://github.com/ElementAI/baal) * [Gitter](https://gitter.im/eai-baal/community) @@ -30,7 +32,7 @@ RUN pip install --no-cache \ uwsgi==2.0.19.1 \ supervisor==4.2.2 \ label-studio==1.0.2 \ - baal==1.3.0 \ + baal \ click==7.1.2 \ git+https://github.com/heartexlabs/label-studio-ml-backend ``` diff --git a/docs/user_guide/heuristics.md b/docs/user_guide/heuristics.md index 019f7ecb..ec82df4d 100644 --- a/docs/user_guide/heuristics.md +++ b/docs/user_guide/heuristics.md @@ -10,7 +10,7 @@ We will cover the two main heuristics: **Entropy** and **BALD**. The goal of this heuristic is to maximize information. To do so, we will compute the entropy of each prediction before ordering them. -Let $p_c(x)$ be the probability of input $x$ to be from class $c$. The entropy can be computed as: +Let $p_{c}(x)$ be the probability of input $x$ to be from class $c$. The entropy can be computed as: $$ H(x) = \sum_c^C p_c(x) diff --git a/mkdocs.yml b/mkdocs.yml index 5db0fab7..2febadb1 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -27,7 +27,6 @@ theme: icon: repo: fontawesome/brands/github plugins: - - search - mkdocs-jupyter - mkdocstrings diff --git a/notebooks/active_learning_process.ipynb b/notebooks/active_learning_process.ipynb index 37b91082..0bd05c6c 100644 --- a/notebooks/active_learning_process.ipynb +++ b/notebooks/active_learning_process.ipynb @@ -10,6 +10,8 @@ "source": [ "# How to do research and visualize progress\n", "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/baal-org/baal/blob/master/notebooks/active_learning_process.ipynb)\n", + "\n", "In this tutorial, we will show how to use Baal for research ie. when we know the labels.\n", "We will introduce notions such as dataset management, MC-Dropout, BALD. If you need more documentation, be sure to check our **Additional resources** section below!\n", "\n", diff --git a/notebooks/baal_prod_cls.ipynb b/notebooks/baal_prod_cls.ipynb index 99f9a50c..01affdc2 100644 --- a/notebooks/baal_prod_cls.ipynb +++ b/notebooks/baal_prod_cls.ipynb @@ -11,6 +11,8 @@ "source": [ "# Use BaaL in production (Classification)\n", "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/baal-org/baal/blob/master/notebooks/baal_prod_cls.ipynb)\n", + "\n", "In this tutorial, we will show you how to use BaaL during your labeling task.\n", "\n", "**NOTE** In this tutorial, we assume that we do not know the labels!\n", @@ -378,55 +380,14 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": { "pycharm": { - "name": "#%%\n" + "name": "#%%\n", + "is_executing": true } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Training on 110 items!\n", - "[103-MainThread ] [baal.modelwrapper:train_on_dataset:109] 2021-07-28T14:50:02.089160Z [\u001B[32minfo ] Starting training dataset=110 epoch=5\n", - "[103-MainThread ] [baal.modelwrapper:train_on_dataset:119] 2021-07-28T14:50:19.678241Z [\u001B[32minfo ] Training complete train_loss=1.9793428182601929\n", - "[103-MainThread ] [baal.modelwrapper:test_on_dataset:147] 2021-07-28T14:50:19.681509Z [\u001B[32minfo ] Starting evaluating dataset=1725\n", - "[103-MainThread ] [baal.modelwrapper:test_on_dataset:156] 2021-07-28T14:50:33.777658Z [\u001B[32minfo ] Evaluation complete test_loss=2.013453960418701\n", - "Metrics: {'test_loss': 2.013453960418701, 'train_loss': 1.9793428182601929}\n", - "[103-MainThread ] [baal.modelwrapper:predict_on_dataset_generator:241] 2021-07-28T14:50:33.784990Z [\u001B[32minfo ] Start Predict dataset=5064\n", - "Training on 120 items!\n", - "[103-MainThread ] [baal.modelwrapper:train_on_dataset:109] 2021-07-28T14:52:14.295969Z [\u001B[32minfo ] Starting training dataset=120 epoch=5\n", - "[103-MainThread ] [baal.modelwrapper:train_on_dataset:119] 2021-07-28T14:52:32.482238Z [\u001B[32minfo ] Training complete train_loss=1.8900309801101685\n", - "[103-MainThread ] [baal.modelwrapper:test_on_dataset:147] 2021-07-28T14:52:32.484473Z [\u001B[32minfo ] Starting evaluating dataset=1725\n", - "[103-MainThread ] [baal.modelwrapper:test_on_dataset:156] 2021-07-28T14:52:46.287436Z [\u001B[32minfo ] Evaluation complete test_loss=1.8315811157226562\n", - "Metrics: {'test_loss': 1.8315811157226562, 'train_loss': 1.8900309801101685}\n", - "[103-MainThread ] [baal.modelwrapper:predict_on_dataset_generator:241] 2021-07-28T14:52:46.367016Z [\u001B[32minfo ] Start Predict dataset=5054\n", - "Training on 130 items!\n", - "[103-MainThread ] [baal.modelwrapper:train_on_dataset:109] 2021-07-28T14:54:26.794349Z [\u001B[32minfo ] Starting training dataset=130 epoch=5\n", - "[103-MainThread ] [baal.modelwrapper:train_on_dataset:119] 2021-07-28T14:54:44.481490Z [\u001B[32minfo ] Training complete train_loss=1.961772084236145\n", - "[103-MainThread ] [baal.modelwrapper:test_on_dataset:147] 2021-07-28T14:54:44.483477Z [\u001B[32minfo ] Starting evaluating dataset=1725\n", - "[103-MainThread ] [baal.modelwrapper:test_on_dataset:156] 2021-07-28T14:54:58.268424Z [\u001B[32minfo ] Evaluation complete test_loss=1.859472393989563\n", - "Metrics: {'test_loss': 1.859472393989563, 'train_loss': 1.961772084236145}\n", - "[103-MainThread ] [baal.modelwrapper:predict_on_dataset_generator:241] 2021-07-28T14:54:58.276565Z [\u001B[32minfo ] Start Predict dataset=5044\n", - "Training on 140 items!\n", - "[103-MainThread ] [baal.modelwrapper:train_on_dataset:109] 2021-07-28T14:56:38.406344Z [\u001B[32minfo ] Starting training dataset=140 epoch=5\n", - "[103-MainThread ] [baal.modelwrapper:train_on_dataset:119] 2021-07-28T14:56:57.088064Z [\u001B[32minfo ] Training complete train_loss=1.8688158988952637\n", - "[103-MainThread ] [baal.modelwrapper:test_on_dataset:147] 2021-07-28T14:56:57.091358Z [\u001B[32minfo ] Starting evaluating dataset=1725\n", - "[103-MainThread ] [baal.modelwrapper:test_on_dataset:156] 2021-07-28T14:57:10.968456Z [\u001B[32minfo ] Evaluation complete test_loss=1.7242822647094727\n", - "Metrics: {'test_loss': 1.7242822647094727, 'train_loss': 1.8688158988952637}\n", - "[103-MainThread ] [baal.modelwrapper:predict_on_dataset_generator:241] 2021-07-28T14:57:10.977104Z [\u001B[32minfo ] Start Predict dataset=5034\n", - "Training on 150 items!\n", - "[103-MainThread ] [baal.modelwrapper:train_on_dataset:109] 2021-07-28T14:58:51.197386Z [\u001B[32minfo ] Starting training dataset=150 epoch=5\n", - "[103-MainThread ] [baal.modelwrapper:train_on_dataset:119] 2021-07-28T14:59:09.779341Z [\u001B[32minfo ] Training complete train_loss=1.8381125926971436\n", - "[103-MainThread ] [baal.modelwrapper:test_on_dataset:147] 2021-07-28T14:59:09.782580Z [\u001B[32minfo ] Starting evaluating dataset=1725\n", - "[103-MainThread ] [baal.modelwrapper:test_on_dataset:156] 2021-07-28T14:59:23.176680Z [\u001B[32minfo ] Evaluation complete test_loss=1.7318601608276367\n", - "Metrics: {'test_loss': 1.7318601608276367, 'train_loss': 1.8381125926971436}\n", - "[103-MainThread ] [baal.modelwrapper:predict_on_dataset_generator:241] 2021-07-28T14:59:23.184444Z [\u001B[32minfo ] Start Predict dataset=5024\n" - ] - } - ], + "outputs": [], "source": [ "# 5. If not done, go back to 2.\n", "for step in range(5): # 5 Active Learning step!\n", diff --git a/notebooks/compatibility/nlp_classification.ipynb b/notebooks/compatibility/nlp_classification.ipynb index e743c7a6..71c76144 100644 --- a/notebooks/compatibility/nlp_classification.ipynb +++ b/notebooks/compatibility/nlp_classification.ipynb @@ -3,9 +3,16 @@ { "cell_type": "markdown", "id": "still-resident", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, "source": [ "# Active Learning for NLP Classification\n", + "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/baal-org/baal/blob/master/notebooks/compatibility/nlp_classification.ipynb)\n", + "\n", "In this tutorial, we guide you through using our new [HuggingFace](https://huggingface.co/transformers/main_classes/trainer.html) trainer wrapper to do active learning with transformers models.\n", " Any model which could be trained by HuggingFace trainer and has `Dropout` layers could be used in the same manner.\n", "\n", @@ -18,7 +25,11 @@ "cell_type": "code", "execution_count": 1, "id": "sixth-wound", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [ { "name": "stderr", @@ -37,7 +48,11 @@ { "cell_type": "markdown", "id": "mechanical-tennessee", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, "source": [ "## ActiveLearning Dataset\n", "In order to create an active learning dataset, we need to wrap the dataset with `baal.ActiveLearningDataset`.\n", @@ -49,7 +64,11 @@ "cell_type": "code", "execution_count": 2, "id": "liquid-replacement", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [ { "name": "stdout", @@ -77,7 +96,11 @@ { "cell_type": "markdown", "id": "ready-participation", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, "source": [ "## Active Learning Model\n", "The process of making a model bayesian is exactly the same as before. In this case, we will get the `Bert` model and use `baal.bayesian.dropout.patch_module` to make the dropout layer stochastic at inference time. " @@ -87,7 +110,11 @@ "cell_type": "code", "execution_count": 3, "id": "baking-coalition", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [ { "name": "stderr", @@ -119,7 +146,11 @@ { "cell_type": "markdown", "id": "eleven-portugal", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, "source": [ "## Heuristic\n", "\n", @@ -133,7 +164,11 @@ "cell_type": "code", "execution_count": 4, "id": "cooperative-constant", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [], "source": [ "from baal.active import get_heuristic\n", @@ -144,7 +179,11 @@ { "cell_type": "markdown", "id": "listed-kelly", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, "source": [ "## HugginFace Trainer Wrapper\n", "\n", @@ -158,7 +197,11 @@ "cell_type": "code", "execution_count": 5, "id": "moving-olive", - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [ { "data": { @@ -200,7 +243,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "[93-MainThread ] [baal.transformers_trainer_wrapper:predict_on_dataset_generator:61] 2021-03-08T20:15:36.980534Z [\u001b[32minfo ] Start Predict dataset=67249\n" + "[93-MainThread ] [baal.transformers_trainer_wrapper:predict_on_dataset_generator:61] 2021-03-08T20:15:36.980534Z [\u001B[32minfo ] Start Predict dataset=67249\n" ] }, { @@ -394,7 +437,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "[93-MainThread ] [baal.transformers_trainer_wrapper:predict_on_dataset_generator:61] 2021-03-08T20:28:15.903378Z [\u001b[32minfo ] Start Predict dataset=67239\n" + "[93-MainThread ] [baal.transformers_trainer_wrapper:predict_on_dataset_generator:61] 2021-03-08T20:28:15.903378Z [\u001B[32minfo ] Start Predict dataset=67239\n" ] }, { @@ -620,4 +663,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/notebooks/compatibility/sklearn_tutorial.ipynb b/notebooks/compatibility/sklearn_tutorial.ipynb index f227082c..c6f2c81a 100644 --- a/notebooks/compatibility/sklearn_tutorial.ipynb +++ b/notebooks/compatibility/sklearn_tutorial.ipynb @@ -11,6 +11,8 @@ "source": [ "# How to use BaaL with Scikit-Learn models\n", "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/baal-org/baal/blob/master/notebooks/compatibility/sklearn_tutorial.ipynb)\n", + "\n", "In this tutorial, you will learn how to use BaaL on a scikit-learn model.\n", "In this case, we will use `RandomForestClassifier`.\n", "\n", diff --git a/notebooks/deep_ensemble.ipynb b/notebooks/deep_ensemble.ipynb index 4dac30b8..fbf15206 100644 --- a/notebooks/deep_ensemble.ipynb +++ b/notebooks/deep_ensemble.ipynb @@ -10,6 +10,8 @@ "source": [ "# How to use Deep ensembles in BaaL\n", "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/baal-org/baal/blob/master/notebooks/deep_ensemble.ipynb)\n", + "\n", "Ensemble are one of the easiest form of Bayesian deep learning.\n", " The main drawback from this approach is the important amount of computational resources needed to perform it.\n", " In this notebook, we will present BaaL's Ensemble API namely `EnsembleModelWrapper`.\n", diff --git a/notebooks/fairness/ActiveFairness.ipynb b/notebooks/fairness/ActiveFairness.ipynb index 168ed79d..970c4924 100644 --- a/notebooks/fairness/ActiveFairness.ipynb +++ b/notebooks/fairness/ActiveFairness.ipynb @@ -11,6 +11,8 @@ "## Can active learning preemptively mitigate fairness issues?\n", "*By Parmida Atighehchian*\n", "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/baal-org/baal/blob/master/notebooks/fairness/ActiveFairness.ipynb)\n", + "\n", "The purpose of this notebook is to demonstrate the prilimary results of our recent [contribution](https://arxiv.org/abs/2104.06879) to ICLR workshop of Responsible AI 2021.\n", "We show that active learning could help in creating fairer datasets without the need to know the bias in the dataset. This is important since in real scenarios, the source of bias is often unknown. Using active learning (i.e. BALD), we show that the prior knowledge of the bias is not necessary and hence it could be easier to integrate this setup in pipelines to make sure that the dataset is generally fairer and the possible biases are reduced. \n", "\n", diff --git a/notebooks/fundamentals/active-learning.ipynb b/notebooks/fundamentals/active-learning.ipynb index 068e39fb..05b103b2 100644 --- a/notebooks/fundamentals/active-learning.ipynb +++ b/notebooks/fundamentals/active-learning.ipynb @@ -10,6 +10,8 @@ "source": [ "# Active learning infrastructure objects\n", "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/baal-org/baal/blob/master/notebooks/fundamentals/active-learning.ipynb)\n", + "\n", "Active learning, or interactively choosing datapoints to request labels for,\n", "presents a challenge that requires some data handling infrastructure that's\n", "slightly different to the normal pytorch dataset classes. In particular, a\n", @@ -38,7 +40,7 @@ }, "outputs": [], "source": [ - "path = \"/Users/jan/datasets/mnist/\"" + "path = \"/tmp\"" ] }, { diff --git a/notebooks/fundamentals/posteriors.ipynb b/notebooks/fundamentals/posteriors.ipynb index 0acb9254..d59fe1a1 100644 --- a/notebooks/fundamentals/posteriors.ipynb +++ b/notebooks/fundamentals/posteriors.ipynb @@ -10,6 +10,8 @@ "source": [ "# Methods for approximating bayesian posteriors \n", "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/baal-org/baal/blob/master/notebooks/fundamentals/posteriors.ipynb)\n", + "\n", "When we started developing active learning methods, we realised that what we wanted to\n", "achieve required estimating the uncertainty of models. Doing so for neural networks is\n", "an ongoing active research area.\n", diff --git a/poetry.lock b/poetry.lock index 4829b32c..d6e6b225 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2085,223 +2085,42 @@ vision = ["torchvision", "lightning-flash"] [metadata] lock-version = "1.1" python-versions = ">=3.7.1,<3.11" -content-hash = "b078b2c2d31acd58eeebb4073f106d97bffe25443962a34129c5be61c91eb51b" +content-hash = "8b24bf08ccb4adbc089aba994c49152a88064877e50237bb5747f814f7dfd15b" [metadata.files] absl-py = [] -aiohttp = [ - {file = "aiohttp-3.8.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:1ed0b6477896559f17b9eaeb6d38e07f7f9ffe40b9f0f9627ae8b9926ae260a8"}, - {file = "aiohttp-3.8.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7dadf3c307b31e0e61689cbf9e06be7a867c563d5a63ce9dca578f956609abf8"}, - {file = "aiohttp-3.8.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a79004bb58748f31ae1cbe9fa891054baaa46fb106c2dc7af9f8e3304dc30316"}, - {file = "aiohttp-3.8.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:12de6add4038df8f72fac606dff775791a60f113a725c960f2bab01d8b8e6b15"}, - 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search + - exclude-search: + exclude: + - notebooks/active_learning_process.md - mkdocs-jupyter - mkdocstrings + markdown_extensions: - md_in_html - attr_list diff --git a/notebooks/active_learning_process.ipynb b/notebooks/active_learning_process.ipynb index 0bd05c6c..00b57ee3 100644 --- a/notebooks/active_learning_process.ipynb +++ b/notebooks/active_learning_process.ipynb @@ -2,11 +2,6 @@ "cells": [ { "cell_type": "markdown", - "metadata": { - "pycharm": { - "name": "#%% md\n" - } - }, "source": [ "# How to do research and visualize progress\n", "\n", @@ -24,14 +19,6 @@ "\n", "Today we will focus on a simple example with CIFAR10 and we will animate the progress of active learning!\n", "\n", - "#### Requirements\n", - "\n", - "In addition to BaaL standard requirements, you will need to install:\n", - "\n", - "* MulticoreTSNE\n", - "* Matplotlib\n", - "\n", - "\n", "#### Additional resources\n", "\n", "* More info on the inner working of Active Learning Dataset [here](./fundamentals/active-learning.ipynb).\n", @@ -39,16 +26,17 @@ " [Literature review](https://baal.readthedocs.io/en/latest/literature/core-papers.html).\n", "\n", "### Let's do this!" - ] - }, - { - "cell_type": "code", - "execution_count": 1, + ], "metadata": { + "collapsed": false, "pycharm": { - "name": "#%%\n" + "name": "#%% md\n" } - }, + } + }, + { + "cell_type": "code", + "execution_count": null, "outputs": [], "source": [ "# Let's start with a bunch of imports.\n", @@ -60,6 +48,7 @@ "import numpy as np\n", "import torch\n", "import torch.backends\n", + "import torch.utils.data as torchdata\n", "from torch import optim\n", "from torch.hub import load_state_dict_from_url\n", "from torch.nn import CrossEntropyLoss\n", @@ -73,21 +62,23 @@ "from baal.bayesian.dropout import patch_module\n", "from baal.modelwrapper import ModelWrapper\n", "\n", + "\n", "def vgg16(num_classes):\n", " model = models.vgg16(pretrained=False, num_classes=num_classes)\n", " weights = load_state_dict_from_url('https://download.pytorch.org/models/vgg16-397923af.pth')\n", " weights = {k: v for k, v in weights.items() if 'classifier.6' not in k}\n", " model.load_state_dict(weights, strict=False)\n", " return model" - ] - }, - { - "cell_type": "markdown", + ], "metadata": { + "collapsed": false, "pycharm": { - "name": "#%% md\n" + "name": "#%%\n" } - }, + } + }, + { + "cell_type": "markdown", "source": [ "### Dataset management and the pool\n", "\n", @@ -120,68 +111,37 @@ "`ActiveLearningDataset(your_dataset, pool_specifics:{'transform': test_transform}`\n", "\n", "where `test_transform` is the test version of `transform` without data augmentation.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 2, + ], "metadata": { + "collapsed": false, "pycharm": { - "name": "#%%\n" + "name": "#%% md\n" } - }, - "outputs": [], - "source": [ - "\"\"\"\n", - "We will make an adapter so that `pool_specifics` modifies the transform correctly.\n", - "Because the training set is now a torchdata.Subset, modifying the `transform` attribute is harder.\n", - "\"\"\"\n", - "\n", - "import torch.utils.data as torchdata\n", - "\n", - "\n", - "class TransformAdapter(torchdata.Subset):\n", - "\n", - " @property\n", - " def transform(self):\n", - " if hasattr(self.dataset, 'transform'):\n", - " return self.dataset.transform\n", - " else:\n", - " raise AttributeError()\n", - "\n", - " @transform.setter\n", - " def transform(self, transform):\n", - " if hasattr(self.dataset, 'transform'):\n", - " self.dataset.transform = transform" - ] + } }, { "cell_type": "markdown", + "source": [ + "Here we define our Experiment configuration, this can come from your favorite experiment manager like MLFlow.\n", + "BaaL does not expect a particular format as all arguments are supplied." + ], "metadata": { + "collapsed": false, "pycharm": { "name": "#%% md\n" } - }, - "source": [ - "Here we define our Experiment configuration, this can come from your favorite experiment manager like MLFlow.\n", - "BaaL does not expect a particular format as all arguments are supplied." - ] + } }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, + "execution_count": null, "outputs": [], "source": [ "\n", "\n", "@dataclass\n", "class ExperimentConfig:\n", - " epoch: int = 20000//100\n", + " epoch: int = 20000 // 100\n", " batch_size: int = 32\n", " initial_pool: int = 512\n", " query_size: int = 100\n", @@ -189,31 +149,33 @@ " heuristic: str = 'bald'\n", " iterations: int = 40\n", " training_duration: int = 10\n", - " \n" - ] - }, - { - "cell_type": "markdown", + "\n" + ], "metadata": { + "collapsed": false, "pycharm": { - "name": "#%% md\n" + "name": "#%%\n" } - }, + } + }, + { + "cell_type": "markdown", "source": [ "### Problem definition\n", "\n", "We will perform active learning on a toy dataset, CIFAR-3 where we only keep dogs, cats and airplanes. This will make\n", "visualization easier." - ] - }, - { - "cell_type": "code", - "execution_count": 4, + ], "metadata": { + "collapsed": false, "pycharm": { - "name": "#%%\n" + "name": "#%% md\n" } - }, + } + }, + { + "cell_type": "code", + "execution_count": null, "outputs": [], "source": [ "def get_datasets(initial_pool):\n", @@ -228,6 +190,22 @@ " Returns:\n", " ActiveLearningDataset, Dataset, the training and test set.\n", " \"\"\"\n", + "\n", + " class TransformAdapter(torchdata.Subset):\n", + " # We need a custom Subset class as we need to override \"transforms\" as well.\n", + " # This shouldn't be needed for your experiments.\n", + " @property\n", + " def transform(self):\n", + " if hasattr(self.dataset, 'transform'):\n", + " return self.dataset.transform\n", + " else:\n", + " raise AttributeError()\n", + "\n", + " @transform.setter\n", + " def transform(self, transform):\n", + " if hasattr(self.dataset, 'transform'):\n", + " self.dataset.transform = transform\n", + "\n", " # airplane, cat, dog\n", " classes_to_keep = [0, 3, 5]\n", " transform = transforms.Compose(\n", @@ -245,31 +223,32 @@ " )\n", " train_ds = datasets.CIFAR10('.', train=True,\n", " transform=transform, target_transform=None, download=True)\n", - " \n", + "\n", " train_mask = np.where([y in classes_to_keep for y in train_ds.targets])[0]\n", " train_ds = TransformAdapter(train_ds, train_mask)\n", - " \n", + "\n", " # In a real application, you will want a validation set here.\n", " test_set = datasets.CIFAR10('.', train=False,\n", " transform=test_transform, target_transform=None, download=True)\n", " test_mask = np.where([y in classes_to_keep for y in test_set.targets])[0]\n", " test_set = TransformAdapter(test_set, test_mask)\n", - " \n", + "\n", " # Here we set `pool_specifics`, where we set the transform attribute for the pool.\n", " active_set = ActiveLearningDataset(train_ds, pool_specifics={'transform': test_transform})\n", "\n", " # We start labeling randomly.\n", " active_set.label_randomly(initial_pool)\n", " return active_set, test_set" - ] - }, - { - "cell_type": "markdown", + ], "metadata": { + "collapsed": false, "pycharm": { - "name": "#%% md\n" + "name": "#%%\n" } - }, + } + }, + { + "cell_type": "markdown", "source": [ "## Creating our experiment\n", "\n", @@ -286,26 +265,18 @@ " * Training/testing loops\n", "* ActiveLearningLoop\n", " * Will make prediction on the pool and label the most uncertain examples." - ] - }, - { - "cell_type": "code", - "execution_count": 5, + ], "metadata": { + "collapsed": false, "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Files already downloaded and verified\n", - "Files already downloaded and verified\n" - ] + "name": "#%% md\n" } - ], + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], "source": [ "hyperparams = ExperimentConfig()\n", "use_cuda = torch.cuda.is_available()\n", @@ -346,15 +317,16 @@ "\n", "# We will reset the weights at each active learning step so we make a copy.\n", "init_weights = deepcopy(model.state_dict())" - ] - }, - { - "cell_type": "markdown", + ], "metadata": { + "collapsed": false, "pycharm": { - "name": "#%% md\n" + "name": "#%%\n" } - }, + } + }, + { + "cell_type": "markdown", "source": [ "### What is an active learning loop\n", "\n", @@ -363,27 +335,27 @@ "1. Training\n", "2. Estimate uncertainty on the pool\n", "3. Label the most uncertain examples.\n" - ] + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } }, { "cell_type": "code", "execution_count": null, - "metadata": { - "pycharm": { - "name": "#%%\n", - "is_executing": true - } - }, "outputs": [], "source": [ "labelling_progress = active_set._labelled.copy().astype(np.uint16)\n", "for epoch in tqdm(range(hyperparams.epoch)):\n", " # Load the initial weights.\n", " model.load_state_dict(init_weights)\n", - " \n", + "\n", " # Train the model on the currently labelled dataset.\n", " _ = model.train_on_dataset(active_set, optimizer=optimizer, batch_size=hyperparams.batch_size,\n", - " use_cuda=use_cuda, epoch=hyperparams.training_duration)\n", + " use_cuda=use_cuda, epoch=hyperparams.training_duration)\n", "\n", " # Get test NLL!\n", " model.test_on_dataset(test_set, hyperparams.batch_size, use_cuda,\n", @@ -395,7 +367,7 @@ " # Keep track of progress\n", " labelling_progress += active_set._labelled.astype(np.uint16)\n", " if not should_continue:\n", - " break\n", + " break\n", "\n", " test_loss = metrics['test_loss'].value\n", " logs = {\n", @@ -403,68 +375,64 @@ " \"epoch\": epoch,\n", " \"Next Training set size\": len(active_set)\n", " }" - ] + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "markdown", + "source": [ + "We will now save our progress on disk." + ], "metadata": { + "collapsed": false, "pycharm": { "name": "#%% md\n" } - }, - "source": [ - "We will now save our progress on disk." - ] + } }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "odict_keys(['features.0.weight', 'features.0.bias', 'features.2.weight', 'features.2.bias', 'features.5.weight', 'features.5.bias', 'features.7.weight', 'features.7.bias', 'features.10.weight', 'features.10.bias', 'features.12.weight', 'features.12.bias', 'features.14.weight', 'features.14.bias', 'features.17.weight', 'features.17.bias', 'features.19.weight', 'features.19.bias', 'features.21.weight', 'features.21.bias', 'features.24.weight', 'features.24.bias', 'features.26.weight', 'features.26.bias', 'features.28.weight', 'features.28.bias', 'classifier.0.weight', 'classifier.0.bias', 'classifier.3.weight', 'classifier.3.bias', 'classifier.6.weight', 'classifier.6.bias']) dict_keys(['labelled', 'random_state']) [103 89 135 ... 121 15 77]\n" - ] - } - ], + "execution_count": null, + "outputs": [], "source": [ "model_weight = model.state_dict()\n", "dataset = active_set.state_dict()\n", - "torch.save({'model':model_weight, 'dataset':dataset, 'labelling_progress':labelling_progress},\n", + "torch.save({'model': model_weight, 'dataset': dataset, 'labelling_progress': labelling_progress},\n", " 'checkpoint.pth')\n", "print(model.state_dict().keys(), dataset.keys(), labelling_progress)" - ] - }, - { - "cell_type": "markdown", + ], "metadata": { + "collapsed": false, "pycharm": { - "name": "#%% md\n" + "name": "#%%\n" } - }, + } + }, + { + "cell_type": "markdown", "source": [ "## Visualization\n", "\n", "Now that our active learning experiment is completed, we can visualize it!\n", "\n", "## Get t-SNE features.\n", - "We will use MultiCoreTSNE to get a t-SNE representation of our dataset. This will allows us to visualize the progress." - ] - }, - { - "cell_type": "code", - "execution_count": 8, + "We will use scikit-learn to get a t-SNE representation of our dataset. This will allows us to visualize the progress." + ], "metadata": { + "collapsed": false, "pycharm": { - "name": "#%%\n" + "name": "#%% md\n" } - }, + } + }, + { + "cell_type": "code", + "execution_count": null, "outputs": [], "source": [ "# modify our model to get features\n", @@ -477,34 +445,42 @@ " def __init__(self, model):\n", " super().__init__()\n", " self.model = model\n", + "\n", " def forward(self, x):\n", - " return torch.flatten(self.model.features(x),1)\n", - " \n", + " return torch.flatten(self.model.features(x), 1)\n", + "\n", "\n", "features = FeatureExtractor(model.model)\n", "acc = []\n", - "for x,y in DataLoader(active_set._dataset, batch_size=10):\n", + "for x, y in DataLoader(active_set._dataset, batch_size=10):\n", " acc.append((features(x.cuda()).detach().cpu().numpy(), y.detach().cpu().numpy()))\n", - " \n", + "\n", "xs, ys = zip(*acc)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, + ], "metadata": { + "collapsed": false, "pycharm": { "name": "#%%\n" } - }, + } + }, + { + "cell_type": "code", + "execution_count": null, "outputs": [], "source": [ - "from MulticoreTSNE import MulticoreTSNE as TSNE\n", + "from sklearn.manifold import TSNE\n", "\n", "# Compute t-SNE on the extracted features.\n", "tsne = TSNE(n_jobs=4)\n", "transformed = tsne.fit_transform(np.vstack(xs))" - ] + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "code", @@ -273101,6 +273077,7 @@ "import matplotlib.pyplot as plt\n", "from matplotlib import animation\n", "\n", + "\n", "def plot_images(img_list):\n", " def init():\n", " img.set_data(img_list[0])\n", @@ -273110,13 +273087,14 @@ " img.set_data(img_list[i])\n", " return (img,)\n", "\n", - " fig = plt.Figure(figsize=(10,10))\n", + " fig = plt.Figure(figsize=(10, 10))\n", " ax = fig.gca()\n", " img = ax.imshow(img_list[0])\n", " anim = animation.FuncAnimation(fig, animate, init_func=init,\n", - " frames=len(img_list), interval=60, blit=True)\n", + " frames=len(img_list), interval=60, blit=True)\n", " return anim\n", "\n", + "\n", "HTML(plot_images(frames).to_jshtml())" ] }, diff --git a/poetry.lock b/poetry.lock index d6e6b225..84ea91fc 100644 --- a/poetry.lock +++ b/poetry.lock @@ -281,13 +281,13 @@ xxhash = "*" apache-beam = ["apache-beam (>=2.26.0)"] audio = ["librosa"] benchmarks = ["numpy (==1.18.5)", "tensorflow (==2.3.0)", "torch (==1.6.0)", "transformers (==3.0.2)"] -dev = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch (<8.0.0)", "aiobotocore", "boto3", "botocore", "faiss-cpu (>=1.6.4)", "fsspec", "moto[server,s3] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "torch", "torchaudio", "soundfile", "transformers", "bs4", "conllu", "h5py", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "torchmetrics (==0.6.0)", "mauve-text", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "Pillow (>=6.2.1)", "librosa", "wget (>=3.2)", "pytorch-nlp (==0.5.0)", "pytorch-lightning", "fastBPE (==0.1.0)", "fairseq", "black (>=22.0,<23.0)", "flake8 (>=3.8.3)", "isort (>=5.0.0)", "pyyaml (>=5.3.1)", "importlib-resources"] +dev = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch (<8.0.0)", "aiobotocore", "boto3", "botocore", "faiss-cpu (>=1.6.4)", "fsspec", "moto[s3,server] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "torch", "torchaudio", "soundfile", "transformers", "bs4", "conllu", "h5py", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "torchmetrics (==0.6.0)", "mauve-text", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "Pillow (>=6.2.1)", "librosa", "wget (>=3.2)", "pytorch-nlp (==0.5.0)", "pytorch-lightning", "fastBPE (==0.1.0)", "fairseq", "black (>=22.0,<23.0)", "flake8 (>=3.8.3)", "isort (>=5.0.0)", "pyyaml (>=5.3.1)", "importlib-resources"] docs = ["docutils (==0.16.0)", "recommonmark", "sphinx (==3.1.2)", "sphinx-markdown-tables", "sphinx-rtd-theme (==0.4.3)", "sphinxext-opengraph (==0.4.1)", "sphinx-copybutton", "fsspec (<2021.9.0)", "s3fs", "sphinx-panels", "sphinx-inline-tabs", "myst-parser", "Markdown (!=3.3.5)"] quality = ["black (>=22.0,<23.0)", "flake8 (>=3.8.3)", "isort (>=5.0.0)", "pyyaml (>=5.3.1)"] s3 = ["fsspec", "boto3", "botocore", "s3fs"] tensorflow = ["tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)"] tensorflow_gpu = ["tensorflow-gpu (>=2.2.0,!=2.6.0,!=2.6.1)"] -tests = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch (<8.0.0)", "aiobotocore", "boto3", "botocore", "faiss-cpu (>=1.6.4)", "fsspec", "moto[server,s3] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "torch", "torchaudio", "soundfile", "transformers", "bs4", "conllu", "h5py", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "torchmetrics (==0.6.0)", "mauve-text", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "Pillow (>=6.2.1)", "librosa", "wget (>=3.2)", "pytorch-nlp (==0.5.0)", "pytorch-lightning", "fastBPE (==0.1.0)", "fairseq", "importlib-resources"] +tests = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch (<8.0.0)", "aiobotocore", "boto3", "botocore", "faiss-cpu (>=1.6.4)", "fsspec", "moto[s3,server] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "torch", "torchaudio", "soundfile", "transformers", "bs4", "conllu", "h5py", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "torchmetrics (==0.6.0)", "mauve-text", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "Pillow (>=6.2.1)", "librosa", "wget (>=3.2)", "pytorch-nlp (==0.5.0)", "pytorch-lightning", "fastBPE (==0.1.0)", "fairseq", "importlib-resources"] torch = ["torch"] vision = ["Pillow (>=6.2.1)"] @@ -403,7 +403,7 @@ python-versions = ">=3.7" [[package]] name = "fsspec" -version = "2022.5.0" +version = "2022.7.1" description = "File-system specification" category = "main" optional = true @@ -414,27 +414,27 @@ aiohttp = {version = "*", optional = true, markers = "extra == \"http\""} requests = {version = "*", optional = true, markers = "extra == \"http\""} [package.extras] -abfs = ["adlfs"] -adl = ["adlfs"] -arrow = ["pyarrow (>=1)"] -dask = ["dask", "distributed"] -dropbox = ["dropboxdrivefs", "requests", "dropbox"] -entrypoints = ["importlib-metadata"] -fuse = ["fusepy"] -gcs = ["gcsfs"] -git = ["pygit2"] -github = ["requests"] -gs = ["gcsfs"] -gui = ["panel"] -hdfs = ["pyarrow (>=1)"] -http = ["requests", "aiohttp"] -libarchive = ["libarchive-c"] -oci = ["ocifs"] -s3 = ["s3fs"] -sftp = ["paramiko"] -smb = ["smbprotocol"] -ssh = ["paramiko"] tqdm = ["tqdm"] +ssh = ["paramiko"] +smb = ["smbprotocol"] +sftp = ["paramiko"] +s3 = ["s3fs"] +oci = ["ocifs"] +libarchive = ["libarchive-c"] +http = ["aiohttp", "requests"] +hdfs = ["pyarrow (>=1)"] +gui = ["panel"] +gs = ["gcsfs"] +github = ["requests"] +git = ["pygit2"] +gcs = ["gcsfs"] +fuse = ["fusepy"] +entrypoints = ["importlib-metadata"] +dropbox = ["dropbox", "requests", "dropboxdrivefs"] +dask = ["distributed", "dask"] +arrow = ["pyarrow (>=1)"] +adl = ["adlfs"] +abfs = ["adlfs"] [[package]] name = "ghp-import" @@ -667,7 +667,7 @@ python-versions = ">=3.6" [[package]] name = "jsonargparse" -version = "4.11.0" +version = "4.13.1" description = "Parsing of command line options, yaml/jsonnet config files and/or environment variables based on argparse." category = "main" optional = true @@ -678,22 +678,22 @@ docstring-parser = {version = ">=0.7.3", optional = true, markers = "extra == \" PyYAML = ">=3.13" [package.extras] -all = ["docstring-parser (>=0.7.3)", "jsonschema (>=3.2.0)", "jsonnet (>=0.13.0)", "validators (>=0.14.2)", "requests (>=2.18.4)", "fsspec (>=0.8.4)", "argcomplete (>=2.0.0)", "ruyaml (>=0.20.0)", "omegaconf (>=2.1.1)", "reconplogger (>=4.4.0)", "typing-extensions (>=3.10.0.0)"] -argcomplete = ["argcomplete (>=2.0.0)"] -dev = ["coverage (>=4.5.1)", "responses (>=0.12.0)", "Sphinx (>=1.7.9)", "sphinx-rtd-theme (>=0.4.3)", "autodocsumm (>=0.1.10)", "sphinx-autodoc-typehints (>=1.11.1)", "pre-commit (>=2.19.0)", "pylint (>=1.8.3)", "pycodestyle (>=2.5.0)", "mypy (>=0.701)", "tox (>=3.25.0)"] -doc = ["Sphinx (>=1.7.9)", "sphinx-rtd-theme (>=0.4.3)", "autodocsumm (>=0.1.10)", "sphinx-autodoc-typehints (>=1.11.1)"] -fsspec = ["fsspec (>=0.8.4)"] -jsonnet = ["jsonnet (>=0.13.0)"] -jsonschema = ["jsonschema (>=3.2.0)"] -maintainer = ["bump2version (>=0.5.11)", "twine (>=4.0.0)"] -omegaconf = ["omegaconf (>=2.1.1)"] -reconplogger = ["reconplogger (>=4.4.0)"] -ruyaml = ["ruyaml (>=0.20.0)"] -signatures = ["docstring-parser (>=0.7.3)"] -test = ["coverage (>=4.5.1)", "responses (>=0.12.0)"] -test_no_urls = ["coverage (>=4.5.1)"] +urls = ["requests (>=2.18.4)", "validators (>=0.14.2)"] typing_extensions = ["typing-extensions (>=3.10.0.0)"] -urls = ["validators (>=0.14.2)", "requests (>=2.18.4)"] +test_no_urls = ["coverage (>=4.5.1)"] +test = ["responses (>=0.12.0)", "coverage (>=4.5.1)"] +signatures = ["docstring-parser (>=0.7.3)"] +ruyaml = ["ruyaml (>=0.20.0)"] +reconplogger = ["reconplogger (>=4.4.0)"] +omegaconf = ["omegaconf (>=2.1.1)"] +maintainer = ["twine (>=4.0.0)", "bump2version (>=0.5.11)"] +jsonschema = ["jsonschema (>=3.2.0)"] +jsonnet = ["jsonnet (>=0.13.0)", "jsonnet-binary (>=0.17.0)"] +fsspec = ["fsspec (>=0.8.4)"] +doc = ["sphinx-autodoc-typehints (>=1.11.1)", "autodocsumm (>=0.1.10)", "sphinx-rtd-theme (>=0.4.3)", "Sphinx (>=1.7.9)"] +dev = ["tox (>=3.25.0)", "mypy (>=0.701)", "pycodestyle (>=2.5.0)", "pylint (>=1.8.3)", "pre-commit (>=2.19.0)", "sphinx-autodoc-typehints (>=1.11.1)", "autodocsumm (>=0.1.10)", "sphinx-rtd-theme (>=0.4.3)", "Sphinx (>=1.7.9)", "responses (>=0.12.0)", "coverage (>=4.5.1)"] +argcomplete = ["argcomplete (>=2.0.0)"] +all = ["typing-extensions (>=3.10.0.0)", "jsonnet (>=0.13.0)", "jsonnet-binary (>=0.17.0)", "reconplogger (>=4.4.0)", "omegaconf (>=2.1.1)", "ruyaml (>=0.20.0)", "argcomplete (>=2.0.0)", "fsspec (>=0.8.4)", "requests (>=2.18.4)", "validators (>=0.14.2)", "jsonschema (>=3.2.0)", "docstring-parser (>=0.7.3)"] [[package]] name = "jsonschema" @@ -973,6 +973,17 @@ python-versions = ">=3.7" Markdown = ">=3.3" mkdocs = ">=1.1" +[[package]] +name = "mkdocs-exclude-search" +version = "0.6.4" +description = "A mkdocs plugin that lets you exclude selected files or sections from the search index." +category = "dev" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +mkdocs = ">=1.0.4" + [[package]] name = "mkdocs-jupyter" version = "0.21.0" @@ -990,7 +1001,7 @@ Pygments = ">=2.12.0,<3.0.0" [[package]] name = "mkdocs-material" -version = "8.3.9" +version = "8.4.0" description = "Documentation that simply works" category = "dev" optional = false @@ -2085,7 +2096,7 @@ vision = ["torchvision", "lightning-flash"] [metadata] lock-version = "1.1" python-versions = ">=3.7.1,<3.11" -content-hash = "8b24bf08ccb4adbc089aba994c49152a88064877e50237bb5747f814f7dfd15b" +content-hash = "0f8919f0be4fd420c39103f9cbb3cdec17927afc818eb63227ffeab7b606db51" [metadata.files] absl-py = [] @@ -2156,6 +2167,7 @@ mergedeep = [] mistune = [] mkdocs = [] mkdocs-autorefs = [] +mkdocs-exclude-search = [] mkdocs-jupyter = [] mkdocs-material = [] mkdocs-material-extensions = [] diff --git a/pyproject.toml b/pyproject.toml index b39f4791..2a648105 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -52,6 +52,7 @@ mkdocs-jupyter = "^0.21.0" mkdocs-material = "^8.3.9" Pygments = "^2.12.0" mkdocstrings = {extras = ["python"], version = "^0.18.1"} +mkdocs-exclude-search = "^0.6.4" [tool.poetry.extras] vision = ["torchvision", "lightning-flash"] From 338702b355696bb29b08bc36c9c29f53b1e21536 Mon Sep 17 00:00:00 2001 From: Dref360 Date: Sun, 9 Oct 2022 13:26:46 -0400 Subject: [PATCH 07/10] Update logo --- docs/_static/css/default.css | 5116 ---------------------- docs/_static/images/logo-transparent.png | Bin 376940 -> 179037 bytes docs/_static/images/logo-vertical.png | Bin 0 -> 235441 bytes docs/_static/images/logo-with-bg.jpg | Bin 0 -> 285712 bytes docs/index.md | 5 + docs/stylesheets/extra.css | 3 + mkdocs.yml | 8 +- poetry.lock | 2 +- pyproject.toml | 3 +- 9 files changed, 17 insertions(+), 5120 deletions(-) delete mode 100644 docs/_static/css/default.css create mode 100644 docs/_static/images/logo-vertical.png create mode 100644 docs/_static/images/logo-with-bg.jpg create mode 100644 docs/stylesheets/extra.css diff --git a/docs/_static/css/default.css b/docs/_static/css/default.css deleted file mode 100644 index 18dba0dd..00000000 --- a/docs/_static/css/default.css +++ /dev/null @@ -1,5116 +0,0 @@ -/*CSS from divio-docs-theme*/ -@charset "UTF-8"; -@import url("https://fonts.googleapis.com/css?family=Nunito:400:600"); -* { - -webkit-box-sizing: border-box; - -moz-box-sizing: border-box; - box-sizing: border-box; } - -article, aside, details, figcaption, figure, footer, header, hgroup, 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content: ""; } - -.fa-building-o:before { - content: ""; } - -.fa-hospital-o:before { - content: ""; } - -.fa-ambulance:before { - content: ""; } - -.fa-medkit:before { - content: ""; } - -.fa-fighter-jet:before { - content: ""; } - -.fa-beer:before { - content: ""; } - -.fa-h-square:before { - content: ""; } - -.fa-plus-square:before { - content: ""; } - -.fa-angle-double-left:before { - content: ""; } - -.fa-angle-double-right:before { - content: ""; } - -.fa-angle-double-up:before { - content: ""; } - -.fa-angle-double-down:before { - content: ""; } - -.fa-angle-left:before { - content: ""; } - -.fa-angle-right:before { - content: ""; } - -.fa-angle-up:before { - content: ""; } - -.fa-angle-down:before { - content: ""; } - -.fa-desktop:before { - content: ""; } - -.fa-laptop:before { - content: ""; } - -.fa-tablet:before { - content: ""; } - -.fa-mobile-phone:before, -.fa-mobile:before { - content: ""; } - -.fa-circle-o:before { - content: ""; } - -.fa-quote-left:before { - content: ""; } - -.fa-quote-right:before { - content: ""; } - -.fa-spinner:before { - content: ""; } - -.fa-circle:before { - content: ""; } - -.fa-mail-reply:before, -.fa-reply:before { - content: ""; } - -.fa-github-alt:before { - content: ""; } - -.fa-folder-o:before { - content: ""; } - -.fa-folder-open-o:before { - content: ""; } - -.fa-smile-o:before { - content: ""; } - -.fa-frown-o:before { - content: ""; } - -.fa-meh-o:before { - content: ""; } - -.fa-gamepad:before { - content: ""; } - -.fa-keyboard-o:before { - content: ""; } - -.fa-flag-o:before { - content: ""; } - -.fa-flag-checkered:before { - content: ""; } - -.fa-terminal:before { - content: ""; } - -.fa-code:before { - content: ""; } - -.fa-mail-reply-all:before, -.fa-reply-all:before { - content: ""; } - -.fa-star-half-empty:before, -.fa-star-half-full:before, -.fa-star-half-o:before { - content: ""; } - -.fa-location-arrow:before { - content: ""; } - -.fa-crop:before { - content: ""; } - -.fa-code-fork:before { - content: ""; } - -.fa-unlink:before, -.fa-chain-broken:before { - content: ""; } - -.fa-question:before { - content: ""; } - -.fa-info:before { - content: ""; } - -.fa-exclamation:before { - content: ""; } - -.fa-superscript:before { - content: ""; } - -.fa-subscript:before { - content: ""; } - -.fa-eraser:before { - content: ""; } - -.fa-puzzle-piece:before { - content: ""; } - -.fa-microphone:before { - content: ""; } - -.fa-microphone-slash:before { - content: ""; } - -.fa-shield:before { - content: ""; } - -.fa-calendar-o:before { - content: ""; } - -.fa-fire-extinguisher:before { - content: ""; } - -.fa-rocket:before { - content: ""; } - -.fa-maxcdn:before { - content: ""; } - -.fa-chevron-circle-left:before { - content: ""; } - -.fa-chevron-circle-right:before { - content: ""; } - -.fa-chevron-circle-up:before { - content: ""; } - -.fa-chevron-circle-down:before { - content: ""; } - -.fa-html5:before { - content: ""; } - -.fa-css3:before { - content: ""; } - -.fa-anchor:before { - content: ""; } - -.fa-unlock-alt:before { - content: ""; } - -.fa-bullseye:before { - content: ""; } - -.fa-ellipsis-h:before { - content: ""; } - -.fa-ellipsis-v:before { - content: ""; } - -.fa-rss-square:before { - content: ""; } - -.fa-play-circle:before { - content: ""; } - -.fa-ticket:before { - content: ""; } - -.fa-minus-square:before { - content: ""; } - -.fa-minus-square-o:before { - content: ""; } - -.fa-level-up:before { - content: ""; } - -.fa-level-down:before { - content: ""; } - -.fa-check-square:before { - content: ""; } - -.fa-pencil-square:before { - content: ""; } - -.fa-external-link-square:before { - content: ""; } - -.fa-share-square:before { - content: ""; } - -.fa-compass:before { - content: ""; } - -.fa-toggle-down:before, -.fa-caret-square-o-down:before { - content: ""; } - -.fa-toggle-up:before, -.fa-caret-square-o-up:before { - content: ""; } - -.fa-toggle-right:before, -.fa-caret-square-o-right:before { - content: ""; } - -.fa-euro:before, -.fa-eur:before { - content: ""; } - -.fa-gbp:before { - content: ""; } - -.fa-dollar:before, -.fa-usd:before { - content: ""; } - -.fa-rupee:before, -.fa-inr:before { - content: ""; } - -.fa-cny:before, -.fa-rmb:before, -.fa-yen:before, -.fa-jpy:before { - content: ""; } - -.fa-ruble:before, -.fa-rouble:before, -.fa-rub:before { - content: ""; } - -.fa-won:before, -.fa-krw:before { - content: ""; } - -.fa-bitcoin:before, -.fa-btc:before { - content: ""; } - -.fa-file:before { - content: ""; } - -.fa-file-text:before { - content: ""; } - -.fa-sort-alpha-asc:before { - content: ""; } - -.fa-sort-alpha-desc:before { - content: ""; } - -.fa-sort-amount-asc:before { - content: ""; } - -.fa-sort-amount-desc:before { - content: ""; } - -.fa-sort-numeric-asc:before { - content: ""; } - -.fa-sort-numeric-desc:before { - content: ""; } - -.fa-thumbs-up:before { - content: ""; } - -.fa-thumbs-down:before { - content: ""; } - -.fa-youtube-square:before { - content: ""; } - -.fa-youtube:before { - content: ""; } - -.fa-xing:before { - content: ""; } - -.fa-xing-square:before { - content: ""; } - -.fa-youtube-play:before { - content: ""; } - -.fa-dropbox:before { - content: ""; } - -.fa-stack-overflow:before { - content: ""; } - -.fa-instagram:before { - content: ""; } - -.fa-flickr:before { - content: ""; } - -.fa-adn:before { - content: ""; } - -.fa-bitbucket:before, .icon-bitbucket:before { - content: ""; } - -.fa-bitbucket-square:before { - content: ""; } - -.fa-tumblr:before { - content: ""; } - -.fa-tumblr-square:before { - content: ""; } - -.fa-long-arrow-down:before { - content: ""; } - -.fa-long-arrow-up:before { - content: ""; } - -.fa-long-arrow-left:before { - content: ""; } - -.fa-long-arrow-right:before { - content: ""; } - -.fa-apple:before { - content: ""; } - -.fa-windows:before { - content: ""; } - -.fa-android:before { - content: ""; } - -.fa-linux:before { - content: ""; } - -.fa-dribbble:before { - content: ""; } - -.fa-skype:before { - content: ""; } - -.fa-foursquare:before { - content: ""; } - -.fa-trello:before { - content: ""; } - -.fa-female:before { - content: ""; } - -.fa-male:before { - content: ""; } - -.fa-gittip:before, -.fa-gratipay:before { - content: ""; } - -.fa-sun-o:before { - content: ""; } - -.fa-moon-o:before { - content: ""; } - -.fa-archive:before { - content: ""; } - -.fa-bug:before { - content: ""; } - -.fa-vk:before { - content: ""; } - -.fa-weibo:before { - content: ""; } - -.fa-renren:before { - content: ""; } - -.fa-pagelines:before { - content: ""; } - -.fa-stack-exchange:before { - content: ""; } - -.fa-arrow-circle-o-right:before { - content: ""; } - -.fa-arrow-circle-o-left:before { - content: ""; } - -.fa-toggle-left:before, -.fa-caret-square-o-left:before { - content: ""; } - -.fa-dot-circle-o:before { - content: ""; } - -.fa-wheelchair:before { - content: ""; } - -.fa-vimeo-square:before { - content: ""; } - -.fa-turkish-lira:before, -.fa-try:before { - content: ""; } - -.fa-plus-square-o:before { - content: ""; } - -.fa-space-shuttle:before { - content: ""; } - -.fa-slack:before { - content: ""; } - -.fa-envelope-square:before { - content: ""; } - -.fa-wordpress:before { - content: ""; } - -.fa-openid:before { - content: ""; } - -.fa-institution:before, -.fa-bank:before, -.fa-university:before { - content: ""; } - -.fa-mortar-board:before, -.fa-graduation-cap:before { - content: ""; } - -.fa-yahoo:before { - content: ""; } - -.fa-google:before { - content: ""; } - -.fa-reddit:before { - content: ""; } - -.fa-reddit-square:before { - content: ""; } - -.fa-stumbleupon-circle:before { - content: ""; } - -.fa-stumbleupon:before { - content: ""; } - -.fa-delicious:before { - content: ""; } - -.fa-digg:before { - content: ""; } - -.fa-pied-piper-pp:before { - content: ""; } - -.fa-pied-piper-alt:before { - content: ""; } - -.fa-drupal:before { - content: ""; } - -.fa-joomla:before { - content: ""; } - -.fa-language:before { - content: ""; } - -.fa-fax:before { - content: ""; } - -.fa-building:before { - content: ""; } - -.fa-child:before { - content: ""; } - -.fa-paw:before { - content: ""; } - -.fa-spoon:before { - content: ""; } - -.fa-cube:before { - content: ""; } - -.fa-cubes:before { - content: ""; } - -.fa-behance:before { - content: ""; } - -.fa-behance-square:before { - content: ""; } - -.fa-steam:before { - content: ""; } - -.fa-steam-square:before { - content: ""; } - -.fa-recycle:before { - content: ""; } - -.fa-automobile:before, -.fa-car:before { - content: ""; } - -.fa-cab:before, -.fa-taxi:before { - content: ""; } - -.fa-tree:before { - content: ""; } - -.fa-spotify:before { - content: ""; } - -.fa-deviantart:before { - content: ""; } - -.fa-soundcloud:before { - content: ""; } - -.fa-database:before { - content: ""; } - -.fa-file-pdf-o:before { - content: ""; } - -.fa-file-word-o:before { - content: ""; } - -.fa-file-excel-o:before { - content: ""; } - -.fa-file-powerpoint-o:before { - content: ""; } - -.fa-file-photo-o:before, -.fa-file-picture-o:before, -.fa-file-image-o:before { - content: ""; } - -.fa-file-zip-o:before, -.fa-file-archive-o:before { - content: ""; } - -.fa-file-sound-o:before, -.fa-file-audio-o:before { - content: ""; } - -.fa-file-movie-o:before, -.fa-file-video-o:before { - content: ""; } - -.fa-file-code-o:before { - content: ""; } - -.fa-vine:before { - content: ""; } - -.fa-codepen:before { - content: ""; } - -.fa-jsfiddle:before { - content: ""; } - -.fa-life-bouy:before, -.fa-life-buoy:before, -.fa-life-saver:before, -.fa-support:before, -.fa-life-ring:before { - content: ""; } - -.fa-circle-o-notch:before { - content: ""; } - -.fa-ra:before, -.fa-resistance:before, -.fa-rebel:before { - content: ""; } - -.fa-ge:before, -.fa-empire:before { - content: ""; } - -.fa-git-square:before { - content: ""; } - -.fa-git:before { - content: ""; } - -.fa-y-combinator-square:before, -.fa-yc-square:before, -.fa-hacker-news:before { - content: ""; } - -.fa-tencent-weibo:before { - content: ""; } - -.fa-qq:before { - content: ""; } - -.fa-wechat:before, -.fa-weixin:before { - content: ""; } - -.fa-send:before, -.fa-paper-plane:before { - content: ""; } - -.fa-send-o:before, -.fa-paper-plane-o:before { - content: ""; } - -.fa-history:before { - content: ""; } - -.fa-circle-thin:before { - content: ""; } - -.fa-header:before { - content: ""; } - -.fa-paragraph:before { - content: ""; } - -.fa-sliders:before { - content: ""; } - -.fa-share-alt:before { - content: ""; } - -.fa-share-alt-square:before { - content: ""; } - -.fa-bomb:before { - content: ""; } - -.fa-soccer-ball-o:before, -.fa-futbol-o:before { - content: ""; } - -.fa-tty:before { - content: ""; } - -.fa-binoculars:before { - content: ""; } - -.fa-plug:before { - content: ""; } - -.fa-slideshare:before { - content: ""; } - -.fa-twitch:before { - content: ""; } - -.fa-yelp:before { - content: ""; } - -.fa-newspaper-o:before { - content: ""; } - -.fa-wifi:before { - content: ""; } - -.fa-calculator:before { - content: ""; } - -.fa-paypal:before { - content: ""; } - -.fa-google-wallet:before { - content: ""; } - -.fa-cc-visa:before { - content: ""; } - -.fa-cc-mastercard:before { - content: ""; } - -.fa-cc-discover:before { - content: ""; } - -.fa-cc-amex:before { - content: ""; } - -.fa-cc-paypal:before { - content: ""; } - -.fa-cc-stripe:before { - content: ""; } - -.fa-bell-slash:before { - content: ""; } - -.fa-bell-slash-o:before { - content: ""; } - -.fa-trash:before { - content: ""; } - -.fa-copyright:before { - content: ""; } - -.fa-at:before { - content: ""; } - -.fa-eyedropper:before { - content: ""; } - -.fa-paint-brush:before { - content: ""; } - -.fa-birthday-cake:before { - content: ""; } - -.fa-area-chart:before { - content: ""; } - -.fa-pie-chart:before { - content: ""; } - -.fa-line-chart:before { - content: ""; } - -.fa-lastfm:before { - content: ""; } - -.fa-lastfm-square:before { - content: ""; } - -.fa-toggle-off:before { - content: ""; } - -.fa-toggle-on:before { - content: ""; } - -.fa-bicycle:before { - content: ""; } - -.fa-bus:before { - content: ""; } - -.fa-ioxhost:before { - content: ""; } - -.fa-angellist:before { - content: ""; } - -.fa-cc:before { - content: ""; } - -.fa-shekel:before, -.fa-sheqel:before, -.fa-ils:before { - content: ""; } - -.fa-meanpath:before { - content: ""; } - -.fa-buysellads:before { - content: ""; } - -.fa-connectdevelop:before { - content: ""; } - -.fa-dashcube:before { - content: ""; } - -.fa-forumbee:before { - content: ""; } - -.fa-leanpub:before { - content: ""; } - -.fa-sellsy:before { - content: ""; } - -.fa-shirtsinbulk:before { - content: ""; } - -.fa-simplybuilt:before { - content: ""; } - -.fa-skyatlas:before { - content: ""; } - -.fa-cart-plus:before { - content: ""; } - -.fa-cart-arrow-down:before { - content: ""; } - -.fa-diamond:before { - content: ""; } - -.fa-ship:before { - content: ""; } - -.fa-user-secret:before { - content: ""; } - -.fa-motorcycle:before { - content: ""; } - -.fa-street-view:before { - content: ""; } - -.fa-heartbeat:before { - content: ""; } - -.fa-venus:before { - content: ""; } - -.fa-mars:before { - content: ""; } - -.fa-mercury:before { - content: ""; } - -.fa-intersex:before, -.fa-transgender:before { - content: ""; } - -.fa-transgender-alt:before { - content: ""; } - -.fa-venus-double:before { - content: ""; } - -.fa-mars-double:before { - content: ""; } - -.fa-venus-mars:before { - content: ""; } - -.fa-mars-stroke:before { - content: ""; } - -.fa-mars-stroke-v:before { - content: ""; } - -.fa-mars-stroke-h:before { - content: ""; } - -.fa-neuter:before { - content: ""; } - -.fa-genderless:before { - content: ""; } - -.fa-facebook-official:before { - content: ""; } - -.fa-pinterest-p:before { - content: ""; } - -.fa-whatsapp:before { - content: ""; } - -.fa-server:before { - content: ""; } - -.fa-user-plus:before { - content: ""; } - -.fa-user-times:before { - content: ""; } - -.fa-hotel:before, -.fa-bed:before { - content: ""; } - -.fa-viacoin:before { - content: ""; } - -.fa-train:before { - content: ""; } - -.fa-subway:before { - content: ""; } - -.fa-medium:before { - content: ""; } - -.fa-yc:before, -.fa-y-combinator:before { - content: ""; } - -.fa-optin-monster:before { - content: ""; } - -.fa-opencart:before { - content: ""; } - -.fa-expeditedssl:before { - content: ""; } - -.fa-battery-4:before, -.fa-battery:before, -.fa-battery-full:before { - content: ""; } - -.fa-battery-3:before, -.fa-battery-three-quarters:before { - content: ""; } - -.fa-battery-2:before, -.fa-battery-half:before { - content: ""; } - -.fa-battery-1:before, -.fa-battery-quarter:before { - content: ""; } - -.fa-battery-0:before, -.fa-battery-empty:before { - content: ""; } - -.fa-mouse-pointer:before { - content: ""; } - -.fa-i-cursor:before { - content: ""; } - -.fa-object-group:before { - content: ""; } - -.fa-object-ungroup:before { - content: ""; } - -.fa-sticky-note:before { - content: ""; } - -.fa-sticky-note-o:before { - content: ""; } - -.fa-cc-jcb:before { - content: ""; } - -.fa-cc-diners-club:before { - content: ""; } - -.fa-clone:before { - content: ""; } - -.fa-balance-scale:before { - content: ""; } - -.fa-hourglass-o:before { - content: ""; } - -.fa-hourglass-1:before, -.fa-hourglass-start:before { - content: ""; } - -.fa-hourglass-2:before, -.fa-hourglass-half:before { - content: ""; } - -.fa-hourglass-3:before, -.fa-hourglass-end:before { - content: ""; } - -.fa-hourglass:before { - content: ""; } - -.fa-hand-grab-o:before, -.fa-hand-rock-o:before { - content: ""; } - -.fa-hand-stop-o:before, -.fa-hand-paper-o:before { - content: ""; } - -.fa-hand-scissors-o:before { - content: ""; } - -.fa-hand-lizard-o:before { - content: ""; } - -.fa-hand-spock-o:before { - content: ""; } - -.fa-hand-pointer-o:before { - content: ""; } - -.fa-hand-peace-o:before { - content: ""; } - -.fa-trademark:before { - content: ""; } - -.fa-registered:before { - content: ""; } - -.fa-creative-commons:before { - content: ""; } - -.fa-gg:before { - content: ""; } - -.fa-gg-circle:before { - content: ""; } - -.fa-tripadvisor:before { - content: ""; } - -.fa-odnoklassniki:before { - content: ""; } - -.fa-odnoklassniki-square:before { - content: ""; } - -.fa-get-pocket:before { - content: ""; } - -.fa-wikipedia-w:before { - content: ""; } - -.fa-safari:before { - content: ""; } - -.fa-chrome:before { - content: ""; } - -.fa-firefox:before { - content: ""; } - -.fa-opera:before { - content: ""; } - -.fa-internet-explorer:before { - content: ""; } - -.fa-tv:before, -.fa-television:before { - content: ""; } - -.fa-contao:before { - content: ""; } - -.fa-500px:before { - content: ""; } - -.fa-amazon:before { - content: ""; } - -.fa-calendar-plus-o:before { - content: ""; } - -.fa-calendar-minus-o:before { - content: ""; } - -.fa-calendar-times-o:before { - content: ""; } - -.fa-calendar-check-o:before { - content: ""; } - -.fa-industry:before { - content: ""; } - -.fa-map-pin:before { - content: ""; } - -.fa-map-signs:before { - content: ""; } - -.fa-map-o:before { - content: ""; } - -.fa-map:before { - content: ""; } - -.fa-commenting:before { - content: ""; } - -.fa-commenting-o:before { - content: ""; } - -.fa-houzz:before { - content: ""; } - -.fa-vimeo:before { - content: ""; } - -.fa-black-tie:before { - content: ""; } - -.fa-fonticons:before { - content: ""; } - -.fa-reddit-alien:before { - content: ""; } - -.fa-edge:before { - content: ""; } - -.fa-credit-card-alt:before { - content: ""; } - -.fa-codiepie:before { - content: ""; } - -.fa-modx:before { - content: ""; } - -.fa-fort-awesome:before { - content: ""; } - -.fa-usb:before { - content: ""; } - -.fa-product-hunt:before { - content: ""; } - -.fa-mixcloud:before { - content: ""; } - -.fa-scribd:before { - content: ""; } - -.fa-pause-circle:before { - content: ""; } - -.fa-pause-circle-o:before { - content: ""; } - -.fa-stop-circle:before { - content: ""; } - -.fa-stop-circle-o:before { - content: ""; } - -.fa-shopping-bag:before { - content: ""; } - -.fa-shopping-basket:before { - content: ""; } - -.fa-hashtag:before { - content: ""; } - -.fa-bluetooth:before { - content: ""; } - -.fa-bluetooth-b:before { - content: ""; } - -.fa-percent:before { - content: ""; } - -.fa-gitlab:before, .icon-gitlab:before { - content: ""; } - -.fa-wpbeginner:before { - content: ""; } - -.fa-wpforms:before { - content: ""; } - -.fa-envira:before { - content: ""; } - -.fa-universal-access:before { - content: ""; } - -.fa-wheelchair-alt:before { - content: ""; } - -.fa-question-circle-o:before { - content: ""; } - 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outline: thin dotted \9; - border-color: #333; } - -input.no-focus:focus { - border-color: #ccc !important; } - -input[type="file"]:focus, input[type="radio"]:focus, input[type="checkbox"]:focus { - outline: thin dotted #333; - outline: 1px auto #129FEA; } - -input[type="text"][disabled], input[type="password"][disabled], input[type="email"][disabled], input[type="url"][disabled], input[type="date"][disabled], input[type="month"][disabled], input[type="time"][disabled], input[type="datetime"][disabled], input[type="datetime-local"][disabled], input[type="week"][disabled], input[type="number"][disabled], input[type="search"][disabled], input[type="tel"][disabled], input[type="color"][disabled] { - cursor: not-allowed; - background-color: #fafafa; } - -input:focus:invalid, textarea:focus:invalid, select:focus:invalid { - color: #E74C3C; - border: 1px solid #E74C3C; } - -input:focus:invalid:focus, textarea:focus:invalid:focus, select:focus:invalid:focus { - border-color: #E74C3C; } - -input[type="file"]:focus:invalid:focus, input[type="radio"]:focus:invalid:focus, input[type="checkbox"]:focus:invalid:focus { - outline-color: #E74C3C; } - -input.wy-input-large { - padding: 12px; - font-size: 100%; } - -textarea { - overflow: auto; - vertical-align: top; - width: 100%; - font-family: "Nunito", Arial, sans-serif; } - -select, textarea { - padding: 0.5em 0.625em; - display: inline-block; - border: 1px solid #ccc; - font-size: 80%; - box-shadow: inset 0 1px 3px #ddd; - -webkit-transition: border 0.3s linear; - -moz-transition: border 0.3s linear; - transition: border 0.3s linear; } - -select { - border: 1px solid #ccc; - background-color: #fff; } - -select[multiple] { - height: auto; } - -select:focus, textarea:focus { - outline: 0; } - -select[disabled], textarea[disabled], input[readonly], select[readonly], textarea[readonly] { - cursor: not-allowed; - background-color: #fafafa; } - -input[type="radio"][disabled], input[type="checkbox"][disabled] { - cursor: not-allowed; } - -.wy-checkbox, .wy-radio { - margin: 6px 0; - color: #404040; - display: block; } - -.wy-checkbox input, .wy-radio input { - vertical-align: baseline; } - -.wy-form-message-inline { - display: inline-block; - *display: inline; - *zoom: 1; - vertical-align: middle; } - -.wy-input-prefix, .wy-input-suffix { - white-space: nowrap; - padding: 6px; } - -.wy-input-prefix .wy-input-context, .wy-input-suffix .wy-input-context { - line-height: 27px; - padding: 0 8px; - display: inline-block; - font-size: 80%; - background-color: #f3f6f6; - border: solid 1px #ccc; - color: #999; } - -.wy-input-suffix .wy-input-context { - border-left: 0; } - -.wy-input-prefix .wy-input-context { - border-right: 0; } - -.wy-switch { - position: relative; - display: block; - height: 24px; - margin-top: 12px; - cursor: pointer; } - -.wy-switch:before { - position: absolute; - content: ""; - display: block; - left: 0; - top: 0; - width: 36px; - height: 12px; - border-radius: 4px; - background: #ccc; 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.wy-form input[type="password"], .wy-form input[type="email"], .wy-form input[type="url"], .wy-form input[type="date"], .wy-form input[type="month"], .wy-form input[type="time"], .wy-form input[type="datetime"], .wy-form input[type="datetime-local"], .wy-form input[type="week"], .wy-form input[type="number"], .wy-form input[type="search"], .wy-form input[type="tel"], .wy-form input[type="color"] { - margin-bottom: 0.3em; - display: block; } - .wy-form label { - margin-bottom: 0.3em; - display: block; } - .wy-form input[type="password"], .wy-form input[type="email"], .wy-form input[type="url"], .wy-form input[type="date"], .wy-form input[type="month"], .wy-form input[type="time"], .wy-form input[type="datetime"], .wy-form input[type="datetime-local"], .wy-form input[type="week"], .wy-form input[type="number"], .wy-form input[type="search"], .wy-form input[type="tel"], .wy-form input[type="color"] { - margin-bottom: 0; } - .wy-form-aligned .wy-control-group label { - margin-bottom: 0.3em; - text-align: left; - display: block; - width: 100%; } - .wy-form-aligned .wy-control { - margin: 1.5em 0 0 0; } - .wy-form .wy-help-inline, .wy-form-message-inline, .wy-form-message { - display: block; - font-size: 80%; - padding: 6px 0; } } - -@media screen and (max-width: 768px) { - .tablet-hide { - display: none; } } - -@media screen and (max-width: 480px) { - .mobile-hide { - display: none; } } - -.float-left { - float: left; } - -.float-right { - float: right; } - -.full-width { - width: 100%; } - -.wy-table, .rst-content table.docutils, .rst-content table.field-list { - border-collapse: collapse; - border-spacing: 0; - empty-cells: show; - margin-bottom: 24px; } - -.wy-table caption, .rst-content table.docutils caption, .rst-content table.field-list caption { - color: #000; - font: italic 85%/1 arial, sans-serif; - padding: 1em 0; - text-align: center; } - -.wy-table td, .rst-content table.docutils td, .rst-content table.field-list td, .wy-table th, .rst-content table.docutils th, .rst-content table.field-list th { - font-size: 90%; - margin: 0; - overflow: visible; - padding: 8px 16px; } - -.wy-table td:first-child, .rst-content table.docutils td:first-child, .rst-content table.field-list td:first-child, .wy-table th:first-child, .rst-content table.docutils th:first-child, .rst-content table.field-list th:first-child { - border-left-width: 0; } - -.wy-table thead, .rst-content table.docutils thead, .rst-content table.field-list thead { - color: #000; - text-align: left; - vertical-align: bottom; - white-space: nowrap; } - -.wy-table thead th, .rst-content table.docutils thead th, .rst-content table.field-list thead th { - font-weight: 600; - border-bottom: solid 2px #e1e4e5; } - -.wy-table td, .rst-content table.docutils td, .rst-content table.field-list td { - background-color: transparent; - vertical-align: middle; } - -.wy-table td p, .rst-content table.docutils td p, .rst-content table.field-list td p { - line-height: 18px; } - -.wy-table td p:last-child, .rst-content table.docutils td p:last-child, .rst-content table.field-list td p:last-child { - margin-bottom: 0; } - -.wy-table .wy-table-cell-min, .rst-content table.docutils .wy-table-cell-min, .rst-content table.field-list .wy-table-cell-min { - width: 1%; - padding-right: 0; } - -.wy-table .wy-table-cell-min input[type=checkbox], .rst-content table.docutils .wy-table-cell-min input[type=checkbox], .rst-content table.field-list .wy-table-cell-min input[type=checkbox], .wy-table .wy-table-cell-min input[type=checkbox], .rst-content table.docutils .wy-table-cell-min input[type=checkbox], .rst-content table.field-list .wy-table-cell-min input[type=checkbox] { - margin: 0; } - -.wy-table-secondary { - color: gray; - font-size: 90%; } - -.wy-table-tertiary { - color: gray; - font-size: 80%; } - -.wy-table-odd td, .wy-table-striped tr:nth-child(2n-1) td, .rst-content table.docutils:not(.field-list) tr:nth-child(2n-1) td { - background-color: #f3f6f6; } - -.wy-table-backed { - background-color: #f3f6f6; } - -/* BORDERED TABLES */ -.wy-table-bordered-all, .rst-content table.docutils { - border: 1px solid #e1e4e5; } - -.wy-table-bordered-all td, .rst-content table.docutils td { - border-bottom: 1px solid #e1e4e5; - border-left: 1px solid #e1e4e5; } - -.wy-table-bordered-all tbody > tr:last-child td, .rst-content table.docutils tbody > tr:last-child td { - border-bottom-width: 0; } - -.wy-table-bordered { - border: 1px solid #e1e4e5; } - -.wy-table-bordered-rows td { - border-bottom: 1px solid #e1e4e5; } - -.wy-table-bordered-rows tbody > tr:last-child td { - border-bottom-width: 0; } - -.wy-table-horizontal tbody > tr:last-child td { - border-bottom-width: 0; } - -.wy-table-horizontal td, .wy-table-horizontal th { - border-width: 0 0 1px 0; - border-bottom: 1px solid #e1e4e5; } - -.wy-table-horizontal tbody > tr:last-child td { - border-bottom-width: 0; } - -/* RESPONSIVE TABLES */ -.wy-table-responsive { - margin-bottom: 24px; - max-width: 100%; - 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+ +

+ + # Welcome to Baal (**Ba**yesian **a**ctive **l**earning) Baal is a Bayesian active learning library. diff --git a/docs/stylesheets/extra.css b/docs/stylesheets/extra.css new file mode 100644 index 00000000..61f80500 --- /dev/null +++ b/docs/stylesheets/extra.css @@ -0,0 +1,3 @@ +img.rounded-corners { + border-radius: 50%; +} \ No newline at end of file diff --git a/mkdocs.yml b/mkdocs.yml index c97133d3..4ab14a4b 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -3,11 +3,12 @@ repo_url: https://github.com/baal-org/baal edit_uri: edit/master/docs/ theme: name: material + logo: _static/images/logo-transparent.png palette: # Palette toggle for light mode - media: "(prefers-color-scheme: light)" scheme: default - primary: blue grey + primary: black toggle: icon: material/brightness-7 name: Switch to dark mode @@ -29,8 +30,11 @@ theme: plugins: - search - exclude-search: + exclude_unreferenced: true exclude: - notebooks/active_learning_process.md + - /*/active_learning_process* + - /*/nbsphinx* - mkdocs-jupyter - mkdocstrings @@ -55,6 +59,8 @@ extra_javascript: - javascripts/mathjax.js - https://polyfill.io/v3/polyfill.min.js?features=es6 - https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js +extra_css: + - stylesheets/extra.css nav: - Home: index.md diff --git a/poetry.lock b/poetry.lock index a9c1cbef..0aace7ad 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2097,7 +2097,7 @@ vision = ["torchvision", "lightning-flash"] [metadata] lock-version = "1.1" python-versions = ">=3.8,<4" -content-hash = "9cb982d18241f2f14c4132b215665d87d492a9f0804535a2702301e91b96f6de" +content-hash = "146804eb73a03d155e981e6c07d6aadbfdd1453d84031e06986691c24be0fcad" [metadata.files] absl-py = [] diff --git a/pyproject.toml b/pyproject.toml index e7b49383..78cd6f53 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -51,10 +51,9 @@ docutils = "0.16" # Documentation mkdocs-jupyter = "^0.21.0" -mkdocs-material = "^8.3.9" +mkdocs-material = "^8.5.6" Pygments = "^2.12.0" mkdocstrings = {extras = ["python"], version = "^0.18.1"} -mkdocs-exclude-search = "^0.6.4" [tool.poetry.extras] vision = ["torchvision", "lightning-flash"] From 71ea45c8cc212ebd377881b284bc155d18d5b2e2 Mon Sep 17 00:00:00 2001 From: Dref360 Date: Sat, 15 Oct 2022 17:54:36 -0400 Subject: [PATCH 08/10] Update logo --- README.md | 2 +- docs/_static/images/logo-with-bg-solid.png | Bin 0 -> 104892 bytes docs/index.md | 3 ++- tests/utils/ssl_module_test.py | 4 ++-- 4 files changed, 5 insertions(+), 4 deletions(-) create mode 100644 docs/_static/images/logo-with-bg-solid.png diff --git a/README.md b/README.md index 7da3c7e3..da6a1ba0 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@

- +

Bayesian Active Learning (Baal)
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diff --git a/tests/utils/ssl_module_test.py b/tests/utils/ssl_module_test.py index ad20aa2c..2f66cbdf 100644 --- a/tests/utils/ssl_module_test.py +++ b/tests/utils/ssl_module_test.py @@ -55,8 +55,8 @@ def test_epoch(self): 'workers': 0} module = TestSSLModule(self.al_dataset, **hparams) - trainer = Trainer(max_epochs=1, num_sanity_val_steps=0, progress_bar_refresh_rate=0, logger=False, - checkpoint_callback=False) + trainer = Trainer(max_epochs=1, num_sanity_val_steps=0, logger=False, + enable_checkpointing=False) trainer.fit(module) assert len(module.labeled_data) == len(module.unlabeled_data) From 8ef3a42e039f700ed46dc288b044dcc8ec4b68da Mon Sep 17 00:00:00 2001 From: Dref360 Date: Sat, 15 Oct 2022 18:39:36 -0400 Subject: [PATCH 09/10] Add requirements for deploymnent --- docs/requirements.txt | 18 +++++------------- pyproject.toml | 2 +- 2 files changed, 6 insertions(+), 14 deletions(-) diff --git a/docs/requirements.txt b/docs/requirements.txt index 27ffc2fd..4152a7b0 100644 --- a/docs/requirements.txt +++ b/docs/requirements.txt @@ -1,13 +1,5 @@ -sphinx>2 -sphinx_rtd_theme -asteroid-sphinx-theme -jupyter_sphinx -Pygments>=2.6.1 -nbsphinx==0.8.6 -sphinx_automodapi -sphinx-copybutton -numpydoc -recommonmark -docutils==0.16 -Jinja2==2.11.3 -markupsafe==2.0.1 +mkdocs==1.4.0 +mkdocs-exclude-search==0.6.4 +mkdocs-jupyter==0.21.0 +mkdocstrings[python]==0.18.1 +Pygments==2.13.0 \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 78cd6f53..c9beaa3c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -33,7 +33,6 @@ lightning-flash = { version = "^0.7.5", optional=true } # NLP transformers = {version = "^4.10.2", optional=true} datasets = {version = "^1.11.0", optional=true} -mkdocs-exclude-search = "^0.6.4" [tool.poetry.dev-dependencies] pytest = "^6.2.5" @@ -54,6 +53,7 @@ mkdocs-jupyter = "^0.21.0" mkdocs-material = "^8.5.6" Pygments = "^2.12.0" mkdocstrings = {extras = ["python"], version = "^0.18.1"} +mkdocs-exclude-search = "^0.6.4" [tool.poetry.extras] vision = ["torchvision", "lightning-flash"] From 1ab33cabcd808dd8b9337e2fa99660dc7e91cead Mon Sep 17 00:00:00 2001 From: Dref360 Date: Wed, 26 Oct 2022 18:38:27 -0400 Subject: [PATCH 10/10] Use horizontal logo --- .../images/BAAL-horizontal-logo-black.png | Bin 0 -> 36890 bytes .../images/logo-horizontal-transparent.png | Bin 0 -> 58016 bytes docs/index.md | 6 ++---- 3 files changed, 2 insertions(+), 4 deletions(-) create mode 100644 docs/_static/images/BAAL-horizontal-logo-black.png create mode 100644 docs/_static/images/logo-horizontal-transparent.png diff --git a/docs/_static/images/BAAL-horizontal-logo-black.png b/docs/_static/images/BAAL-horizontal-logo-black.png new file mode 100644 index 0000000000000000000000000000000000000000..6e4a952075eefc36db9cbdb9cbe44e729f871ba4 GIT binary patch literal 36890 zcma%jc|6qL_y3@>B$6b_5@jmy2w58YmKKc)DZ40JmY6XZ3{eu1CW(wCd-h}-%h;l^ z?_(Qd--fXa2E+KidV7CbC3BkzPI;&DGagvG%@=S_4w z++Ois5$$J+)&osMw6pF|;P>xePT-Qf3HMRz8{C!-94)_-QbvwxGC69verI4yt|HzH4&Kd0;oPfk<)_*?>ihtK7bbH*Q@`l*m5AzT9-PIiUZyL$4 zxskev+onUYNi7B)l5w2|`0%!zGVY`^haUpL#bK=V2PgB*&MDMyPR{M82Vw^TtL3y2 z1o#;^o4N_dBuVom_u*nA?fFQfb*o>nLAJr>&+jVDRI5`e$#gkLAb0Tg%}wYJ$Nx4J zOi_MRcR)XmS@QdrJPF&#+XR3PF_5&fq{@-z?oV z_!%zw1Pm+i#SGV|8*+@3R8=Gox76U^0oH9xTbvs(T(bG2_9f{Bzt9;Ij#_qNj#XyS ziW@h}wjWPz!#GJYWUN>A_xfJ-{ zTACP4uXzn+#k%|^Y%6tVxvb%p7J}w$N64suEAV!Gq%IeKS8G*2DDaw$y2ds0= zaCLf7j{^A3R0xH#dD|?6GW&dolrkG%^DVJ!`y}(wTJl|D4 zA3^a~PkFK6{~xRA03DHQnc+5-^M$Gx+$CTIsOp%S$o*VNE!ub8hdZnOw}{YfuERSL z_2whLP_2sm%ylGm1;BcIS_my#MhNA1(zQiAq8@Qb#L`tQ#IJ~h&@H>lnoC-UDQ7L( zpyG!&6y1=O!v%xJAruG5fpO~u{-I>Z^6$5M6&1k<055a#T~+Ph`%lna1oEKdxYR?R;kF5nDZ@Goe7OE zdN6lrzBN%6_IeV;`!*!{kr=tda~&kK5PglP4ukx-o;N-5WOSaCc1hxJfsxjH;xmTesuFA6O%|^v~g%iz${8Z}!yN z3HY}6Er`b^`R`LKo2qMkrE2mmayW*$m%_hn(eUNLBCZ@<%R!5I z2<|Uyh=1-Uxf1a6c{yMme9@k2IP7)KxypeB zSZ1$kJBC7m#PxLEr5Bv7z2{i5YHzv2MALj|hKr~F5kIJG$~%;T2EQn5MU0U&WAN29 z3;pWYPzdEtnI2$t!o*`pti@#Saylz?Z7#aDx_oa=_jTr}s{iiAx+!Z>k1|^b$=)bq zIpJ6iZQ>XeZ&f$_48iQINvj5t*bnam#0&%zGs0RqLX?<=zQRg*fr)^x8>Poyd))q& zj8AfqNBKOyNaKzZIp~R^Iv@Ih`G63LP{#qapIxZjv)(A#^#z~)$1YNSE@R8%tVj;} z;Ti~cvMnb!Q$f9l8i7Ko;l%$vEs%0+eynZ}_lK3D$Xm|xA?p#?_UN4a0RC+2(a0GO zH;PXaKik-$AhBmtkfE~72oQYe7AAsgR+51KoH@9#$5}_PIsth&gmKO{Kpj71uYs^Dhtilk;JXBznFy%>uVg` zU*7D)A8A@1N(oT&Mk(TM|3|6T{Fvt6!M$;=zJee?Qa|s&Wgj6i`i@U4GbBbM+mn`e zx{+fI(uYwY8R`Awv{DLYN3j5NGCh({uIkTRT7hknvENQwXPCNSe}N%fNItin$okyH?I7U77N(uR4^C)aLdCB6JeB%E@DO$FW#C7Xlu<2c-Gm=m`U0Da>#H9U<%);1}Do|HnU5h zx8zd*m6^@y!+%W)fXS+vtI;k$y!rYt{seOA&5t#)jRyG+!DU-4z=rWgu@3hm1QPTX z?IKQE8st{eNAl3QXJX|umTg;al}amKbs}T-hW|T=A2?{;?Seb&BH9Q%6|X|Nh0$L+ zk{y}7?F5(gdf;Z%@9jihKsKrQ2;%$>#nGWNKlXMHC+5!TG{;et$JkOqU?P+<2gteT zu>0MF2VmZ(u{zj^YHLrw&S-;^{}Z^V7EM7L5MhG_n0MK&z#KdkmKu;T1`&9E&CC-M zQB7I*U+bIoUWtxsUw8kHegA||TpDq37eJq~jH}_Yllka}`4EAUeMsEoy78i&m`$a? 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-# Welcome to Baal (**Ba**yesian **a**ctive **l**earning) - Baal is a Bayesian active learning library. We provide methods to estimate sampling from the posterior distribution in order to maximize the efficiency of labelling during active learning. Our library is suitable for research and industrial applications.

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