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2.605-2.656.167-.429.414-1.055.644-1.517a10.195 10.195 0 0 1-.052-1.086c0-1.331.282-2.499 1.132-3.368.397-.406.89-.717 1.474-.952 1.399-1.136 3.392-2.093 6.122-2.093 2.731 0 4.767.957 6.166 2.093.584.235 1.077.546 1.474.952.85.869 1.132 2.037 1.132 3.368 0 .368-.014.733-.052 1.086.23.462.477 1.088.644 1.517 1.258.364 2.233 1.721 2.605 2.656a.832.832 0 0 1 .053.22v2.869a.641.641 0 0 1-.078.256ZM12.172 11h-.344a4.323 4.323 0 0 1-.355.508C10.703 12.455 9.555 13 7.965 13c-1.725 0-2.989-.359-3.782-1.259a2.005 2.005 0 0 1-.085-.104L4 11.741v6.585c1.435.779 4.514 2.179 8 2.179 3.486 0 6.565-1.4 8-2.179v-6.585l-.098-.104s-.033.045-.085.104c-.793.9-2.057 1.259-3.782 1.259-1.59 0-2.738-.545-3.508-1.492a4.323 4.323 0 0 1-.355-.508h-.016.016Zm.641-2.935c.136 1.057.403 1.913.878 2.497.442.544 1.134.938 2.344.938 1.573 0 2.292-.337 2.657-.751.384-.435.558-1.15.558-2.361 0-1.14-.243-1.847-.705-2.319-.477-.488-1.319-.862-2.824-1.025-1.487-.161-2.192.138-2.533.529-.269.307-.437.808-.438 1.578v.021c0 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0v3.5A1.75 1.75 0 0 1 12.25 14h-8.5A1.75 1.75 0 0 1 2 12.25v-8.5C2 2.784 2.784 2 3.75 2Zm6.854-1h4.146a.25.25 0 0 1 .25.25v4.146a.25.25 0 0 1-.427.177L13.03 4.03 9.28 7.78a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042l3.75-3.75-1.543-1.543A.25.25 0 0 1 10.604 1Z"></path> </svg> </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary Link--external" target="_blank" data-analytics-event="{"location":"navbar","action":"github_skills","context":"product","tag":"link","label":"github_skills_link_product_navbar"}" href="https://skills.github.com"> GitHub Skills <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-link-external HeaderMenu-external-icon color-fg-subtle"> <path d="M3.75 2h3.5a.75.75 0 0 1 0 1.5h-3.5a.25.25 0 0 0-.25.25v8.5c0 .138.112.25.25.25h8.5a.25.25 0 0 0 .25-.25v-3.5a.75.75 0 0 1 1.5 0v3.5A1.75 1.75 0 0 1 12.25 14h-8.5A1.75 1.75 0 0 1 2 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</div> </modal-dialog></div> </div> <div data-action="click:qbsearch-input#retract" class="dark-backdrop position-fixed" hidden data-target="qbsearch-input.darkBackdrop"></div> <div class="color-fg-default"> <dialog-helper> <dialog data-target="qbsearch-input.feedbackDialog" data-action="close:qbsearch-input#handleDialogClose cancel:qbsearch-input#handleDialogClose" id="feedback-dialog" aria-modal="true" aria-labelledby="feedback-dialog-title" aria-describedby="feedback-dialog-description" data-view-component="true" class="Overlay Overlay-whenNarrow Overlay--size-medium Overlay--motion-scaleFade Overlay--disableScroll"> <div data-view-component="true" class="Overlay-header"> <div class="Overlay-headerContentWrap"> <div class="Overlay-titleWrap"> <h1 class="Overlay-title " id="feedback-dialog-title"> Provide feedback </h1> </div> <div class="Overlay-actionWrap"> <button data-close-dialog-id="feedback-dialog" aria-label="Close" type="button" data-view-component="true" class="close-button 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seriously.</p> <textarea name="feedback" class="form-control width-full mb-2" style="height: 120px" id="feedback"></textarea> <input name="include_email" id="include_email" aria-label="Include my email address so I can be contacted" class="form-control mr-2" type="checkbox"> <label for="include_email" style="font-weight: normal">Include my email address so I can be contacted</label> </form></div> </scrollable-region> <div data-view-component="true" class="Overlay-footer Overlay-footer--alignEnd"> <button data-close-dialog-id="feedback-dialog" type="button" data-view-component="true" class="btn"> Cancel </button> <button form="code-search-feedback-form" data-action="click:qbsearch-input#submitFeedback" type="submit" data-view-component="true" class="btn-primary btn"> Submit feedback </button> </div> </dialog></dialog-helper> <custom-scopes data-target="qbsearch-input.customScopesManager"> <dialog-helper> <dialog data-target="custom-scopes.customScopesModalDialog" data-action="close:qbsearch-input#handleDialogClose cancel:qbsearch-input#handleDialogClose" id="custom-scopes-dialog" aria-modal="true" aria-labelledby="custom-scopes-dialog-title" aria-describedby="custom-scopes-dialog-description" data-view-component="true" class="Overlay Overlay-whenNarrow Overlay--size-medium Overlay--motion-scaleFade Overlay--disableScroll"> <div data-view-component="true" class="Overlay-header Overlay-header--divided"> <div class="Overlay-headerContentWrap"> <div class="Overlay-titleWrap"> <h1 class="Overlay-title " id="custom-scopes-dialog-title"> Saved searches </h1> <h2 id="custom-scopes-dialog-description" class="Overlay-description">Use saved searches to filter your results more quickly</h2> </div> <div class="Overlay-actionWrap"> <button data-close-dialog-id="custom-scopes-dialog" aria-label="Close" type="button" data-view-component="true" class="close-button Overlay-closeButton"><svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" 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src=\"https://camo.githubusercontent.com/17aebe83d2ca93fc83c7d74ec6a87455a7469e5be43c3933c918a64121725a21/68747470733a2f2f6578706c6f73696f6e2e61692f6173736574732f696d672f6c6f676f2e737667\" width=\"125\" height=\"125\" align=\"right\" data-canonical-src=\"https://explosion.ai/assets/img/logo.svg\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch1 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eThinc: A refreshing functional take on deep learning, compatible with your favorite libraries\u003c/h1\u003e\u003ca id=\"user-content-thinc-a-refreshing-functional-take-on-deep-learning-compatible-with-your-favorite-libraries\" class=\"anchor\" aria-label=\"Permalink: Thinc: A refreshing functional take on deep learning, compatible with your favorite libraries\" href=\"#thinc-a-refreshing-functional-take-on-deep-learning-compatible-with-your-favorite-libraries\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eFrom the makers of \u003ca href=\"https://spacy.io\" rel=\"nofollow\"\u003espaCy\u003c/a\u003e and \u003ca href=\"https://prodi.gy\" rel=\"nofollow\"\u003eProdigy\u003c/a\u003e\u003c/h3\u003e\u003ca id=\"user-content-from-the-makers-of-spacy-and-prodigy\" class=\"anchor\" aria-label=\"Permalink: From the makers of spaCy and Prodigy\" href=\"#from-the-makers-of-spacy-and-prodigy\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003ca href=\"https://thinc.ai\" rel=\"nofollow\"\u003eThinc\u003c/a\u003e is a \u003cstrong\u003elightweight deep learning library\u003c/strong\u003e that offers\nan elegant, type-checked, functional-programming API for \u003cstrong\u003ecomposing models\u003c/strong\u003e,\nwith support for layers defined in other frameworks such as \u003cstrong\u003ePyTorch,\nTensorFlow and MXNet\u003c/strong\u003e. You can use Thinc as an interface layer, a standalone\ntoolkit or a flexible way to develop new models. Previous versions of Thinc have\nbeen running quietly in production in thousands of companies, via both\n\u003ca href=\"https://spacy.io\" rel=\"nofollow\"\u003espaCy\u003c/a\u003e and \u003ca href=\"https://prodi.gy\" rel=\"nofollow\"\u003eProdigy\u003c/a\u003e. We wrote the new\nversion to let users \u003cstrong\u003ecompose, configure and deploy custom models\u003c/strong\u003e built with\ntheir favorite framework.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003ca href=\"https://github.com/explosion/thinc/actions/workflows/tests.yml\"\u003e\u003cimg src=\"https://github.com/explosion/thinc/actions/workflows/tests.yml/badge.svg\" alt=\"tests\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\n\u003ca href=\"https://github.com/explosion/thinc/releases\"\u003e\u003cimg src=\"https://camo.githubusercontent.com/8ca428dbc0b15a70658251b9e8cce80fd9fb207ddf75813a7cb773dbb1295ed4/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f762f72656c656173652f6578706c6f73696f6e2f7468696e632e7376673f696e636c7564655f70726572656c656173657326736f72743d73656d766572267374796c653d666c61742d737175617265266c6f676f3d676974687562\" alt=\"Current Release Version\" 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data-canonical-src=\"https://img.shields.io/badge/wheels-%E2%9C%93-4c1.svg?longCache=true\u0026amp;style=flat-square\u0026amp;logo=python\u0026amp;logoColor=white\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\n\u003ca href=\"https://github.com/ambv/black\"\u003e\u003cimg src=\"https://camo.githubusercontent.com/0caca0b2f07dc43ff3ffde815d52da5fba5d07d6a3107c0aac87be0ded3a5961/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f636f64652532307374796c652d626c61636b2d3030303030302e7376673f7374796c653d666c61742d737175617265\" alt=\"Code style: black\" data-canonical-src=\"https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\n\u003ca href=\"https://colab.research.google.com/github/explosion/thinc/blob/master/examples/00_intro_to_thinc.ipynb\" rel=\"nofollow\"\u003e\u003cimg src=\"https://camo.githubusercontent.com/3849d344afe7bbbe577b262f33f11fab6938e6e6e53fcba5a6d579de9c436717/68747470733a2f2f6769737463646e2e6769746861636b2e636f6d2f696e65732f64636633353461613731613736363561653139383731643766643134613465302f7261772f343631666331663631613762633538363066393433636434623662636661626238633839303665372f636f6c61622d62616467652e737667\" alt=\"Open demo in Colab\" data-canonical-src=\"https://gistcdn.githack.com/ines/dcf354aa71a7665ae19871d7fd14a4e0/raw/461fc1f61a7bc5860f943cd4b6bcfabb8c8906e7/colab-badge.svg\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003e🔥 Features\u003c/h2\u003e\u003ca id=\"user-content--features\" class=\"anchor\" aria-label=\"Permalink: 🔥 Features\" href=\"#-features\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003cstrong\u003eType-check\u003c/strong\u003e your model definitions with custom types and\n\u003ca href=\"https://mypy.readthedocs.io/en/latest/\" rel=\"nofollow\"\u003e\u003ccode\u003emypy\u003c/code\u003e\u003c/a\u003e plugin.\u003c/li\u003e\n\u003cli\u003eWrap \u003cstrong\u003ePyTorch\u003c/strong\u003e, \u003cstrong\u003eTensorFlow\u003c/strong\u003e and \u003cstrong\u003eMXNet\u003c/strong\u003e models for use in your network.\u003c/li\u003e\n\u003cli\u003eConcise \u003cstrong\u003efunctional-programming\u003c/strong\u003e approach to model definition, using\ncomposition rather than inheritance.\u003c/li\u003e\n\u003cli\u003eOptional custom infix notation via \u003cstrong\u003eoperator overloading\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eIntegrated \u003cstrong\u003econfig system\u003c/strong\u003e to describe trees of objects and hyperparameters.\u003c/li\u003e\n\u003cli\u003eChoice of \u003cstrong\u003eextensible backends\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e\u003ca href=\"https://thinc.ai/docs\" rel=\"nofollow\"\u003eRead more →\u003c/a\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003e🚀 Quickstart\u003c/h2\u003e\u003ca id=\"user-content--quickstart\" class=\"anchor\" aria-label=\"Permalink: 🚀 Quickstart\" href=\"#-quickstart\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThinc is compatible with \u003cstrong\u003ePython 3.6+\u003c/strong\u003e and runs on \u003cstrong\u003eLinux\u003c/strong\u003e, \u003cstrong\u003emacOS\u003c/strong\u003e and\n\u003cstrong\u003eWindows\u003c/strong\u003e. The latest releases with binary wheels are available from\n\u003ca href=\"https://pypi.python.org/pypi/thinc\" rel=\"nofollow\"\u003epip\u003c/a\u003e. Before you install Thinc and its\ndependencies, make sure that your \u003ccode\u003epip\u003c/code\u003e, \u003ccode\u003esetuptools\u003c/code\u003e and \u003ccode\u003ewheel\u003c/code\u003e are up to\ndate. For the most recent releases, pip 19.3 or newer is recommended.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"pip install -U pip setuptools wheel\npip install thinc\"\u003e\u003cpre\u003epip install -U pip setuptools wheel\npip install thinc\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eSee the \u003ca href=\"https://thinc.ai/docs/install#extended\" rel=\"nofollow\"\u003eextended installation docs\u003c/a\u003e for\ndetails on optional dependencies for different backends and GPU. You might also\nwant to\n\u003ca href=\"https://thinc.ai/docs/install#type-checking\" rel=\"nofollow\"\u003eset up static type checking\u003c/a\u003e to\ntake advantage of Thinc's type system.\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp dir=\"auto\"\u003e\u003cg-emoji class=\"g-emoji\" alias=\"warning\"\u003e⚠️\u003c/g-emoji\u003e If you have installed PyTorch and you are using Python 3.7+, uninstall the\npackage \u003ccode\u003edataclasses\u003c/code\u003e with \u003ccode\u003epip uninstall dataclasses\u003c/code\u003e, since it may have been\ninstalled by PyTorch and is incompatible with Python 3.7+.\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003e📓 Selected examples and notebooks\u003c/h3\u003e\u003ca id=\"user-content--selected-examples-and-notebooks\" class=\"anchor\" aria-label=\"Permalink: 📓 Selected examples and notebooks\" href=\"#-selected-examples-and-notebooks\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eAlso see the \u003ca href=\"/explosion/thinc/blob/main/examples\"\u003e\u003ccode\u003e/examples\u003c/code\u003e\u003c/a\u003e directory and\n\u003ca href=\"https://thinc.ai/docs\" rel=\"nofollow\"\u003eusage documentation\u003c/a\u003e for more examples. Most examples\nare Jupyter notebooks – to launch them on\n\u003ca href=\"https://colab.research.google.com\" rel=\"nofollow\"\u003eGoogle Colab\u003c/a\u003e (with GPU support!) click on\nthe button next to the notebook name.\u003c/p\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eNotebook\u003c/th\u003e\n\u003cth\u003eDescription\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/examples/00_intro_to_thinc.ipynb\"\u003e\u003ccode\u003eintro_to_thinc\u003c/code\u003e\u003c/a\u003e\u003cbr\u003e\u003ca href=\"https://colab.research.google.com/github/explosion/thinc/blob/master/examples/00_intro_to_thinc.ipynb\" rel=\"nofollow\"\u003e\u003cimg src=\"https://camo.githubusercontent.com/3849d344afe7bbbe577b262f33f11fab6938e6e6e53fcba5a6d579de9c436717/68747470733a2f2f6769737463646e2e6769746861636b2e636f6d2f696e65732f64636633353461613731613736363561653139383731643766643134613465302f7261772f343631666331663631613762633538363066393433636434623662636661626238633839303665372f636f6c61622d62616467652e737667\" alt=\"Open in Colab\" data-canonical-src=\"https://gistcdn.githack.com/ines/dcf354aa71a7665ae19871d7fd14a4e0/raw/461fc1f61a7bc5860f943cd4b6bcfabb8c8906e7/colab-badge.svg\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eEverything you need to know to get started. Composing and training a model on the MNIST data, using config files, registering custom functions and wrapping PyTorch, TensorFlow and MXNet models.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/examples/02_transformers_tagger_bert.ipynb\"\u003e\u003ccode\u003etransformers_tagger_bert\u003c/code\u003e\u003c/a\u003e\u003cbr\u003e\u003ca href=\"https://colab.research.google.com/github/explosion/thinc/blob/master/examples/02_transformers_tagger_bert.ipynb\" rel=\"nofollow\"\u003e\u003cimg src=\"https://camo.githubusercontent.com/3849d344afe7bbbe577b262f33f11fab6938e6e6e53fcba5a6d579de9c436717/68747470733a2f2f6769737463646e2e6769746861636b2e636f6d2f696e65732f64636633353461613731613736363561653139383731643766643134613465302f7261772f343631666331663631613762633538363066393433636434623662636661626238633839303665372f636f6c61622d62616467652e737667\" alt=\"Open in Colab\" data-canonical-src=\"https://gistcdn.githack.com/ines/dcf354aa71a7665ae19871d7fd14a4e0/raw/461fc1f61a7bc5860f943cd4b6bcfabb8c8906e7/colab-badge.svg\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eHow to use Thinc, \u003ccode\u003etransformers\u003c/code\u003e and PyTorch to train a part-of-speech tagger. From model definition and config to the training loop.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/examples/03_pos_tagger_basic_cnn.ipynb\"\u003e\u003ccode\u003epos_tagger_basic_cnn\u003c/code\u003e\u003c/a\u003e\u003cbr\u003e\u003ca href=\"https://colab.research.google.com/github/explosion/thinc/blob/master/examples/03_pos_tagger_basic_cnn.ipynb\" rel=\"nofollow\"\u003e\u003cimg src=\"https://camo.githubusercontent.com/3849d344afe7bbbe577b262f33f11fab6938e6e6e53fcba5a6d579de9c436717/68747470733a2f2f6769737463646e2e6769746861636b2e636f6d2f696e65732f64636633353461613731613736363561653139383731643766643134613465302f7261772f343631666331663631613762633538363066393433636434623662636661626238633839303665372f636f6c61622d62616467652e737667\" alt=\"Open in Colab\" data-canonical-src=\"https://gistcdn.githack.com/ines/dcf354aa71a7665ae19871d7fd14a4e0/raw/461fc1f61a7bc5860f943cd4b6bcfabb8c8906e7/colab-badge.svg\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eImplementing and training a basic CNN for part-of-speech tagging model without external dependencies and using different levels of Thinc's config system.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/examples/04_parallel_training_ray.ipynb\"\u003e\u003ccode\u003eparallel_training_ray\u003c/code\u003e\u003c/a\u003e\u003cbr\u003e\u003ca href=\"https://colab.research.google.com/github/explosion/thinc/blob/master/examples/04_parallel_training_ray.ipynb\" rel=\"nofollow\"\u003e\u003cimg src=\"https://camo.githubusercontent.com/3849d344afe7bbbe577b262f33f11fab6938e6e6e53fcba5a6d579de9c436717/68747470733a2f2f6769737463646e2e6769746861636b2e636f6d2f696e65732f64636633353461613731613736363561653139383731643766643134613465302f7261772f343631666331663631613762633538363066393433636434623662636661626238633839303665372f636f6c61622d62616467652e737667\" alt=\"Open in Colab\" data-canonical-src=\"https://gistcdn.githack.com/ines/dcf354aa71a7665ae19871d7fd14a4e0/raw/461fc1f61a7bc5860f943cd4b6bcfabb8c8906e7/colab-badge.svg\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eHow to set up synchronous and asynchronous parameter server training with Thinc and \u003ca href=\"https://ray.readthedocs.io/en/latest/\" rel=\"nofollow\"\u003eRay\u003c/a\u003e.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003e\u003ca href=\"/explosion/thinc/blob/main/examples\"\u003eView more →\u003c/a\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003e📖 Documentation \u0026amp; usage guides\u003c/h3\u003e\u003ca id=\"user-content--documentation--usage-guides\" class=\"anchor\" aria-label=\"Permalink: 📖 Documentation \u0026amp; usage guides\" href=\"#-documentation--usage-guides\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eDocumentation\u003c/th\u003e\n\u003cth\u003eDescription\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://thinc.ai/docs\" rel=\"nofollow\"\u003eIntroduction\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eEverything you need to know.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://thinc.ai/docs/concept\" rel=\"nofollow\"\u003eConcept \u0026amp; Design\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eThinc's conceptual model and how it works.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://thinc.ai/docs/usage-models\" rel=\"nofollow\"\u003eDefining and using models\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eHow to compose models and update state.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://thinc.ai/docs/usage-config\" rel=\"nofollow\"\u003eConfiguration system\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eThinc's config system and function registry.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://thinc.ai/docs/usage-frameworks\" rel=\"nofollow\"\u003eIntegrating PyTorch, TensorFlow \u0026amp; MXNet\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eInteroperability with machine learning frameworks\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://thinc.ai/docs/api-layers\" rel=\"nofollow\"\u003eLayers API\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eWeights layers, transforms, combinators and wrappers.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"https://thinc.ai/docs/usage-type-checking\" rel=\"nofollow\"\u003eType Checking\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eType-check your model definitions and more.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003e🗺 What's where\u003c/h2\u003e\u003ca id=\"user-content--whats-where\" class=\"anchor\" aria-label=\"Permalink: 🗺 What's where\" href=\"#-whats-where\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eModule\u003c/th\u003e\n\u003cth\u003eDescription\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/thinc/api.py\"\u003e\u003ccode\u003ethinc.api\u003c/code\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003e\u003cstrong\u003eUser-facing API.\u003c/strong\u003e All classes and functions should be imported from here.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/thinc/types.py\"\u003e\u003ccode\u003ethinc.types\u003c/code\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eCustom \u003ca href=\"https://thinc.ai/docs/api-types\" rel=\"nofollow\"\u003etypes and dataclasses\u003c/a\u003e.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/thinc/model.py\"\u003e\u003ccode\u003ethinc.model\u003c/code\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eThe \u003ccode\u003eModel\u003c/code\u003e class. All Thinc models are an instance (not a subclass) of \u003ccode\u003eModel\u003c/code\u003e.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/thinc/layers\"\u003e\u003ccode\u003ethinc.layers\u003c/code\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eThe layers. Each layer is implemented in its own module.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/thinc/shims\"\u003e\u003ccode\u003ethinc.shims\u003c/code\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eInterface for external models implemented in PyTorch, TensorFlow etc.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/thinc/loss.py\"\u003e\u003ccode\u003ethinc.loss\u003c/code\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eFunctions to calculate losses.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/thinc/optimizers.py\"\u003e\u003ccode\u003ethinc.optimizers\u003c/code\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eFunctions to create optimizers. Currently supports \"vanilla\" SGD, Adam and RAdam.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/thinc/schedules.py\"\u003e\u003ccode\u003ethinc.schedules\u003c/code\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eGenerators for different rates, schedules, decays or series.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/thinc/backends\"\u003e\u003ccode\u003ethinc.backends\u003c/code\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eBackends for \u003ccode\u003enumpy\u003c/code\u003e and \u003ccode\u003ecupy\u003c/code\u003e.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/thinc/config.py\"\u003e\u003ccode\u003ethinc.config\u003c/code\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eConfig parsing and validation and function registry system.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003ca href=\"/explosion/thinc/blob/main/thinc/util.py\"\u003e\u003ccode\u003ethinc.util\u003c/code\u003e\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eUtilities and helper functions.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003e🐍 Development notes\u003c/h2\u003e\u003ca id=\"user-content--development-notes\" class=\"anchor\" aria-label=\"Permalink: 🐍 Development notes\" href=\"#-development-notes\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThinc uses \u003ca href=\"https://github.com/psf/black\"\u003e\u003ccode\u003eblack\u003c/code\u003e\u003c/a\u003e for auto-formatting,\n\u003ca href=\"http://flake8.pycqa.org/en/latest/\" rel=\"nofollow\"\u003e\u003ccode\u003eflake8\u003c/code\u003e\u003c/a\u003e for linting and\n\u003ca href=\"https://mypy.readthedocs.io/en/latest/\" rel=\"nofollow\"\u003e\u003ccode\u003emypy\u003c/code\u003e\u003c/a\u003e for type checking. All code is\nwritten compatible with \u003cstrong\u003ePython 3.6+\u003c/strong\u003e, with type hints wherever possible. See\nthe \u003ca href=\"https://thinc.ai/docs/api-types\" rel=\"nofollow\"\u003etype reference\u003c/a\u003e for more details on\nThinc's custom types.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003e👷♀️ Building Thinc from source\u003c/h3\u003e\u003ca id=\"user-content-️-building-thinc-from-source\" class=\"anchor\" aria-label=\"Permalink: 👷♀️ Building Thinc from source\" href=\"#️-building-thinc-from-source\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eBuilding Thinc from source requires the full dependencies listed in\n\u003ca href=\"/explosion/thinc/blob/main/requirements.txt\"\u003e\u003ccode\u003erequirements.txt\u003c/code\u003e\u003c/a\u003e to be installed. You'll also need a\ncompiler to build the C extensions.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"git clone https://github.com/explosion/thinc\ncd thinc\npython -m venv .env\nsource .env/bin/activate\npip install -U pip setuptools wheel\npip install -r requirements.txt\npip install --no-build-isolation .\"\u003e\u003cpre\u003egit clone https://github.com/explosion/thinc\n\u003cspan class=\"pl-c1\"\u003ecd\u003c/span\u003e thinc\npython -m venv .env\n\u003cspan class=\"pl-c1\"\u003esource\u003c/span\u003e .env/bin/activate\npip install -U pip setuptools wheel\npip install -r requirements.txt\npip install --no-build-isolation \u003cspan class=\"pl-c1\"\u003e.\u003c/span\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eAlternatively, install in editable mode:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"pip install -r requirements.txt\npip install --no-build-isolation --editable .\"\u003e\u003cpre\u003epip install -r requirements.txt\npip install --no-build-isolation --editable \u003cspan class=\"pl-c1\"\u003e.\u003c/span\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eOr by setting \u003ccode\u003ePYTHONPATH\u003c/code\u003e:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"export PYTHONPATH=`pwd`\npip install -r requirements.txt\npython setup.py build_ext --inplace\"\u003e\u003cpre\u003e\u003cspan class=\"pl-k\"\u003eexport\u003c/span\u003e PYTHONPATH=\u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e`\u003c/span\u003epwd\u003cspan class=\"pl-pds\"\u003e`\u003c/span\u003e\u003c/span\u003e\npip install -r requirements.txt\npython setup.py build_ext --inplace\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003e🚦 Running tests\u003c/h3\u003e\u003ca id=\"user-content--running-tests\" class=\"anchor\" aria-label=\"Permalink: 🚦 Running tests\" href=\"#-running-tests\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThinc comes with an \u003ca href=\"/explosion/thinc/blob/main/thinc/tests\"\u003eextensive test suite\u003c/a\u003e. The following should\nall pass and not report any warnings or errors:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"python -m pytest thinc # test suite\npython -m mypy thinc # type checks\npython -m flake8 thinc # linting\"\u003e\u003cpre\u003epython -m pytest thinc \u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e test suite\u003c/span\u003e\npython -m mypy thinc \u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e type checks\u003c/span\u003e\npython -m flake8 thinc \u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e#\u003c/span\u003e linting\u003c/span\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eTo view test coverage, you can run \u003ccode\u003epython -m pytest thinc --cov=thinc\u003c/code\u003e. We aim\nfor a 100% test coverage. This doesn't mean that we meticulously write tests for\nevery single line – we ignore blocks that are not relevant or difficult to test\nand make sure that the tests execute all code paths.\u003c/p\u003e\n\u003c/article\u003e","loaded":true,"timedOut":false,"errorMessage":null,"headerInfo":{"toc":[{"level":1,"text":"Thinc: A refreshing functional take on deep learning, compatible with your favorite libraries","anchor":"thinc-a-refreshing-functional-take-on-deep-learning-compatible-with-your-favorite-libraries","htmlText":"Thinc: A refreshing functional take on deep learning, compatible with your favorite libraries"},{"level":3,"text":"From the makers of spaCy and Prodigy","anchor":"from-the-makers-of-spacy-and-prodigy","htmlText":"From the makers of spaCy and Prodigy"},{"level":2,"text":"🔥 Features","anchor":"-features","htmlText":"🔥 Features"},{"level":2,"text":"🚀 Quickstart","anchor":"-quickstart","htmlText":"🚀 Quickstart"},{"level":3,"text":"📓 Selected examples and notebooks","anchor":"-selected-examples-and-notebooks","htmlText":"📓 Selected examples and notebooks"},{"level":3,"text":"📖 Documentation \u0026 usage guides","anchor":"-documentation--usage-guides","htmlText":"📖 Documentation \u0026amp; usage guides"},{"level":2,"text":"🗺 What's where","anchor":"-whats-where","htmlText":"🗺 What's where"},{"level":2,"text":"🐍 Development notes","anchor":"-development-notes","htmlText":"🐍 Development notes"},{"level":3,"text":"👷♀️ Building Thinc from source","anchor":"️-building-thinc-from-source","htmlText":"👷♀️ Building Thinc from source"},{"level":3,"text":"🚦 Running tests","anchor":"-running-tests","htmlText":"🚦 Running tests"}],"siteNavLoginPath":"/login?return_to=https%3A%2F%2Fgithub.com%2Fexplosion%2Fthinc"}},{"displayName":"LICENSE","repoName":"thinc","refName":"main","path":"LICENSE","preferredFileType":"license","tabName":"MIT","richText":null,"loaded":false,"timedOut":false,"errorMessage":null,"headerInfo":{"toc":null,"siteNavLoginPath":"/login?return_to=https%3A%2F%2Fgithub.com%2Fexplosion%2Fthinc"}}],"overviewFilesProcessingTime":0}},"appPayload":{"helpUrl":"https://docs.github.com","findFileWorkerPath":"/assets-cdn/worker/find-file-worker-7d7eb7c71814.js","findInFileWorkerPath":"/assets-cdn/worker/find-in-file-worker-708ec8ade250.js","githubDevUrl":null,"enabled_features":{"copilot_workspace":null,"code_nav_ui_events":false,"overview_shared_code_dropdown_button":true,"react_blob_overlay":false,"accessible_code_button":true,"github_models_repo_integration":false}}}}</script> <div data-target="react-partial.reactRoot"><style data-styled="true" 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js-snippet-clipboard-copy-unpositioned undefined" data-hpc="true"><article class="markdown-body entry-content container-lg" itemprop="text"><p dir="auto"><a href="https://explosion.ai" rel="nofollow"><img src="https://camo.githubusercontent.com/17aebe83d2ca93fc83c7d74ec6a87455a7469e5be43c3933c918a64121725a21/68747470733a2f2f6578706c6f73696f6e2e61692f6173736574732f696d672f6c6f676f2e737667" width="125" height="125" align="right" data-canonical-src="https://explosion.ai/assets/img/logo.svg" style="max-width: 100%;"></a></p> <div class="markdown-heading" dir="auto"><h1 tabindex="-1" class="heading-element" dir="auto">Thinc: A refreshing functional take on deep learning, compatible with your favorite libraries</h1><a id="user-content-thinc-a-refreshing-functional-take-on-deep-learning-compatible-with-your-favorite-libraries" class="anchor" aria-label="Permalink: Thinc: A refreshing functional take on deep learning, compatible with your favorite libraries" href="#thinc-a-refreshing-functional-take-on-deep-learning-compatible-with-your-favorite-libraries"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">From the makers of <a href="https://spacy.io" rel="nofollow">spaCy</a> and <a href="https://prodi.gy" rel="nofollow">Prodigy</a></h3><a id="user-content-from-the-makers-of-spacy-and-prodigy" class="anchor" aria-label="Permalink: From the makers of spaCy and Prodigy" href="#from-the-makers-of-spacy-and-prodigy"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto"><a href="https://thinc.ai" rel="nofollow">Thinc</a> is a <strong>lightweight deep learning library</strong> that offers an elegant, type-checked, functional-programming API for <strong>composing models</strong>, with support for layers defined in other frameworks such as <strong>PyTorch, TensorFlow and MXNet</strong>. You can use Thinc as an interface layer, a standalone toolkit or a flexible way to develop new models. Previous versions of Thinc have been running quietly in production in thousands of companies, via both <a href="https://spacy.io" rel="nofollow">spaCy</a> and <a href="https://prodi.gy" rel="nofollow">Prodigy</a>. We wrote the new version to let users <strong>compose, configure and deploy custom models</strong> built with their favorite framework.</p> <p dir="auto"><a href="https://github.com/explosion/thinc/actions/workflows/tests.yml"><img src="https://github.com/explosion/thinc/actions/workflows/tests.yml/badge.svg" alt="tests" style="max-width: 100%;"></a> <a href="https://github.com/explosion/thinc/releases"><img src="https://camo.githubusercontent.com/8ca428dbc0b15a70658251b9e8cce80fd9fb207ddf75813a7cb773dbb1295ed4/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f762f72656c656173652f6578706c6f73696f6e2f7468696e632e7376673f696e636c7564655f70726572656c656173657326736f72743d73656d766572267374796c653d666c61742d737175617265266c6f676f3d676974687562" alt="Current Release Version" data-canonical-src="https://img.shields.io/github/v/release/explosion/thinc.svg?include_prereleases&sort=semver&style=flat-square&logo=github" style="max-width: 100%;"></a> <a 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data-canonical-src="https://img.shields.io/conda/vn/conda-forge/thinc.svg?style=flat-square&logo=conda-forge&logoColor=white" style="max-width: 100%;"></a> <a href="https://github.com/explosion/wheelwright/releases"><img src="https://camo.githubusercontent.com/fdd69162e4890edaab2e64d4c8e88c3dd9408c0d4afc20aafce8368df39f3a14/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f776865656c732d2545322539432539332d3463312e7376673f6c6f6e6743616368653d74727565267374796c653d666c61742d737175617265266c6f676f3d707974686f6e266c6f676f436f6c6f723d7768697465" alt="Python wheels" data-canonical-src="https://img.shields.io/badge/wheels-%E2%9C%93-4c1.svg?longCache=true&style=flat-square&logo=python&logoColor=white" style="max-width: 100%;"></a> <a href="https://github.com/ambv/black"><img src="https://camo.githubusercontent.com/0caca0b2f07dc43ff3ffde815d52da5fba5d07d6a3107c0aac87be0ded3a5961/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f636f64652532307374796c652d626c61636b2d3030303030302e7376673f7374796c653d666c61742d737175617265" alt="Code style: black" data-canonical-src="https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square" style="max-width: 100%;"></a> <a href="https://colab.research.google.com/github/explosion/thinc/blob/master/examples/00_intro_to_thinc.ipynb" rel="nofollow"><img src="https://camo.githubusercontent.com/3849d344afe7bbbe577b262f33f11fab6938e6e6e53fcba5a6d579de9c436717/68747470733a2f2f6769737463646e2e6769746861636b2e636f6d2f696e65732f64636633353461613731613736363561653139383731643766643134613465302f7261772f343631666331663631613762633538363066393433636434623662636661626238633839303665372f636f6c61622d62616467652e737667" alt="Open demo in Colab" data-canonical-src="https://gistcdn.githack.com/ines/dcf354aa71a7665ae19871d7fd14a4e0/raw/461fc1f61a7bc5860f943cd4b6bcfabb8c8906e7/colab-badge.svg" style="max-width: 100%;"></a></p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">🔥 Features</h2><a id="user-content--features" class="anchor" aria-label="Permalink: 🔥 Features" href="#-features"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <ul dir="auto"> <li><strong>Type-check</strong> your model definitions with custom types and <a href="https://mypy.readthedocs.io/en/latest/" rel="nofollow"><code>mypy</code></a> plugin.</li> <li>Wrap <strong>PyTorch</strong>, <strong>TensorFlow</strong> and <strong>MXNet</strong> models for use in your network.</li> <li>Concise <strong>functional-programming</strong> approach to model definition, using composition rather than inheritance.</li> <li>Optional custom infix notation via <strong>operator overloading</strong>.</li> <li>Integrated <strong>config system</strong> to describe trees of objects and hyperparameters.</li> <li>Choice of <strong>extensible backends</strong>.</li> <li><strong><a href="https://thinc.ai/docs" rel="nofollow">Read more →</a></strong></li> </ul> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">🚀 Quickstart</h2><a id="user-content--quickstart" class="anchor" aria-label="Permalink: 🚀 Quickstart" href="#-quickstart"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Thinc is compatible with <strong>Python 3.6+</strong> and runs on <strong>Linux</strong>, <strong>macOS</strong> and <strong>Windows</strong>. The latest releases with binary wheels are available from <a href="https://pypi.python.org/pypi/thinc" rel="nofollow">pip</a>. Before you install Thinc and its dependencies, make sure that your <code>pip</code>, <code>setuptools</code> and <code>wheel</code> are up to date. For the most recent releases, pip 19.3 or newer is recommended.</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="pip install -U pip setuptools wheel pip install thinc"><pre>pip install -U pip setuptools wheel pip install thinc</pre></div> <p dir="auto">See the <a href="https://thinc.ai/docs/install#extended" rel="nofollow">extended installation docs</a> for details on optional dependencies for different backends and GPU. You might also want to <a href="https://thinc.ai/docs/install#type-checking" rel="nofollow">set up static type checking</a> to take advantage of Thinc's type system.</p> <blockquote> <p dir="auto"><g-emoji class="g-emoji" alias="warning">⚠️</g-emoji> If you have installed PyTorch and you are using Python 3.7+, uninstall the package <code>dataclasses</code> with <code>pip uninstall dataclasses</code>, since it may have been installed by PyTorch and is incompatible with Python 3.7+.</p> </blockquote> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">📓 Selected examples and notebooks</h3><a id="user-content--selected-examples-and-notebooks" class="anchor" aria-label="Permalink: 📓 Selected examples and notebooks" href="#-selected-examples-and-notebooks"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Also see the <a href="/explosion/thinc/blob/main/examples"><code>/examples</code></a> directory and <a href="https://thinc.ai/docs" rel="nofollow">usage documentation</a> for more examples. Most examples are Jupyter notebooks – to launch them on <a href="https://colab.research.google.com" rel="nofollow">Google Colab</a> (with GPU support!) click on the button next to the notebook name.</p> <markdown-accessiblity-table><table> <thead> <tr> <th>Notebook</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><a href="/explosion/thinc/blob/main/examples/00_intro_to_thinc.ipynb"><code>intro_to_thinc</code></a><br><a href="https://colab.research.google.com/github/explosion/thinc/blob/master/examples/00_intro_to_thinc.ipynb" rel="nofollow"><img src="https://camo.githubusercontent.com/3849d344afe7bbbe577b262f33f11fab6938e6e6e53fcba5a6d579de9c436717/68747470733a2f2f6769737463646e2e6769746861636b2e636f6d2f696e65732f64636633353461613731613736363561653139383731643766643134613465302f7261772f343631666331663631613762633538363066393433636434623662636661626238633839303665372f636f6c61622d62616467652e737667" alt="Open in Colab" data-canonical-src="https://gistcdn.githack.com/ines/dcf354aa71a7665ae19871d7fd14a4e0/raw/461fc1f61a7bc5860f943cd4b6bcfabb8c8906e7/colab-badge.svg" style="max-width: 100%;"></a></td> <td>Everything you need to know to get started. Composing and training a model on the MNIST data, using config files, registering custom functions and wrapping PyTorch, TensorFlow and MXNet models.</td> </tr> <tr> <td><a href="/explosion/thinc/blob/main/examples/02_transformers_tagger_bert.ipynb"><code>transformers_tagger_bert</code></a><br><a href="https://colab.research.google.com/github/explosion/thinc/blob/master/examples/02_transformers_tagger_bert.ipynb" rel="nofollow"><img src="https://camo.githubusercontent.com/3849d344afe7bbbe577b262f33f11fab6938e6e6e53fcba5a6d579de9c436717/68747470733a2f2f6769737463646e2e6769746861636b2e636f6d2f696e65732f64636633353461613731613736363561653139383731643766643134613465302f7261772f343631666331663631613762633538363066393433636434623662636661626238633839303665372f636f6c61622d62616467652e737667" alt="Open in Colab" data-canonical-src="https://gistcdn.githack.com/ines/dcf354aa71a7665ae19871d7fd14a4e0/raw/461fc1f61a7bc5860f943cd4b6bcfabb8c8906e7/colab-badge.svg" style="max-width: 100%;"></a></td> <td>How to use Thinc, <code>transformers</code> and PyTorch to train a part-of-speech tagger. From model definition and config to the training loop.</td> </tr> <tr> <td><a href="/explosion/thinc/blob/main/examples/03_pos_tagger_basic_cnn.ipynb"><code>pos_tagger_basic_cnn</code></a><br><a href="https://colab.research.google.com/github/explosion/thinc/blob/master/examples/03_pos_tagger_basic_cnn.ipynb" rel="nofollow"><img src="https://camo.githubusercontent.com/3849d344afe7bbbe577b262f33f11fab6938e6e6e53fcba5a6d579de9c436717/68747470733a2f2f6769737463646e2e6769746861636b2e636f6d2f696e65732f64636633353461613731613736363561653139383731643766643134613465302f7261772f343631666331663631613762633538363066393433636434623662636661626238633839303665372f636f6c61622d62616467652e737667" alt="Open in Colab" data-canonical-src="https://gistcdn.githack.com/ines/dcf354aa71a7665ae19871d7fd14a4e0/raw/461fc1f61a7bc5860f943cd4b6bcfabb8c8906e7/colab-badge.svg" style="max-width: 100%;"></a></td> <td>Implementing and training a basic CNN for part-of-speech tagging model without external dependencies and using different levels of Thinc's config system.</td> </tr> <tr> <td><a href="/explosion/thinc/blob/main/examples/04_parallel_training_ray.ipynb"><code>parallel_training_ray</code></a><br><a href="https://colab.research.google.com/github/explosion/thinc/blob/master/examples/04_parallel_training_ray.ipynb" rel="nofollow"><img src="https://camo.githubusercontent.com/3849d344afe7bbbe577b262f33f11fab6938e6e6e53fcba5a6d579de9c436717/68747470733a2f2f6769737463646e2e6769746861636b2e636f6d2f696e65732f64636633353461613731613736363561653139383731643766643134613465302f7261772f343631666331663631613762633538363066393433636434623662636661626238633839303665372f636f6c61622d62616467652e737667" alt="Open in Colab" data-canonical-src="https://gistcdn.githack.com/ines/dcf354aa71a7665ae19871d7fd14a4e0/raw/461fc1f61a7bc5860f943cd4b6bcfabb8c8906e7/colab-badge.svg" style="max-width: 100%;"></a></td> <td>How to set up synchronous and asynchronous parameter server training with Thinc and <a href="https://ray.readthedocs.io/en/latest/" rel="nofollow">Ray</a>.</td> </tr> </tbody> </table></markdown-accessiblity-table> <p dir="auto"><strong><a href="/explosion/thinc/blob/main/examples">View more →</a></strong></p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">📖 Documentation & usage guides</h3><a id="user-content--documentation--usage-guides" class="anchor" aria-label="Permalink: 📖 Documentation & usage guides" href="#-documentation--usage-guides"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <markdown-accessiblity-table><table> <thead> <tr> <th>Documentation</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><a href="https://thinc.ai/docs" rel="nofollow">Introduction</a></td> <td>Everything you need to know.</td> </tr> <tr> <td><a href="https://thinc.ai/docs/concept" rel="nofollow">Concept & Design</a></td> <td>Thinc's conceptual model and how it works.</td> </tr> <tr> <td><a href="https://thinc.ai/docs/usage-models" rel="nofollow">Defining and using models</a></td> <td>How to compose models and update state.</td> </tr> <tr> <td><a href="https://thinc.ai/docs/usage-config" rel="nofollow">Configuration system</a></td> <td>Thinc's config system and function registry.</td> </tr> <tr> <td><a href="https://thinc.ai/docs/usage-frameworks" rel="nofollow">Integrating PyTorch, TensorFlow & MXNet</a></td> <td>Interoperability with machine learning frameworks</td> </tr> <tr> <td><a href="https://thinc.ai/docs/api-layers" rel="nofollow">Layers API</a></td> <td>Weights layers, transforms, combinators and wrappers.</td> </tr> <tr> <td><a href="https://thinc.ai/docs/usage-type-checking" rel="nofollow">Type Checking</a></td> <td>Type-check your model definitions and more.</td> </tr> </tbody> </table></markdown-accessiblity-table> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">🗺 What's where</h2><a id="user-content--whats-where" class="anchor" aria-label="Permalink: 🗺 What's where" href="#-whats-where"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <markdown-accessiblity-table><table> <thead> <tr> <th>Module</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><a href="/explosion/thinc/blob/main/thinc/api.py"><code>thinc.api</code></a></td> <td><strong>User-facing API.</strong> All classes and functions should be imported from here.</td> </tr> <tr> <td><a href="/explosion/thinc/blob/main/thinc/types.py"><code>thinc.types</code></a></td> <td>Custom <a href="https://thinc.ai/docs/api-types" rel="nofollow">types and dataclasses</a>.</td> </tr> <tr> <td><a href="/explosion/thinc/blob/main/thinc/model.py"><code>thinc.model</code></a></td> <td>The <code>Model</code> class. All Thinc models are an instance (not a subclass) of <code>Model</code>.</td> </tr> <tr> <td><a href="/explosion/thinc/blob/main/thinc/layers"><code>thinc.layers</code></a></td> <td>The layers. Each layer is implemented in its own module.</td> </tr> <tr> <td><a href="/explosion/thinc/blob/main/thinc/shims"><code>thinc.shims</code></a></td> <td>Interface for external models implemented in PyTorch, TensorFlow etc.</td> </tr> <tr> <td><a href="/explosion/thinc/blob/main/thinc/loss.py"><code>thinc.loss</code></a></td> <td>Functions to calculate losses.</td> </tr> <tr> <td><a href="/explosion/thinc/blob/main/thinc/optimizers.py"><code>thinc.optimizers</code></a></td> <td>Functions to create optimizers. Currently supports "vanilla" SGD, Adam and RAdam.</td> </tr> <tr> <td><a href="/explosion/thinc/blob/main/thinc/schedules.py"><code>thinc.schedules</code></a></td> <td>Generators for different rates, schedules, decays or series.</td> </tr> <tr> <td><a href="/explosion/thinc/blob/main/thinc/backends"><code>thinc.backends</code></a></td> <td>Backends for <code>numpy</code> and <code>cupy</code>.</td> </tr> <tr> <td><a href="/explosion/thinc/blob/main/thinc/config.py"><code>thinc.config</code></a></td> <td>Config parsing and validation and function registry system.</td> </tr> <tr> <td><a href="/explosion/thinc/blob/main/thinc/util.py"><code>thinc.util</code></a></td> <td>Utilities and helper functions.</td> </tr> </tbody> </table></markdown-accessiblity-table> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">🐍 Development notes</h2><a id="user-content--development-notes" class="anchor" aria-label="Permalink: 🐍 Development notes" href="#-development-notes"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Thinc uses <a href="https://github.com/psf/black"><code>black</code></a> for auto-formatting, <a href="http://flake8.pycqa.org/en/latest/" rel="nofollow"><code>flake8</code></a> for linting and <a href="https://mypy.readthedocs.io/en/latest/" rel="nofollow"><code>mypy</code></a> for type checking. All code is written compatible with <strong>Python 3.6+</strong>, with type hints wherever possible. See the <a href="https://thinc.ai/docs/api-types" rel="nofollow">type reference</a> for more details on Thinc's custom types.</p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">👷♀️ Building Thinc from source</h3><a id="user-content-️-building-thinc-from-source" class="anchor" aria-label="Permalink: 👷♀️ Building Thinc from source" href="#️-building-thinc-from-source"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Building Thinc from source requires the full dependencies listed in <a href="/explosion/thinc/blob/main/requirements.txt"><code>requirements.txt</code></a> to be installed. You'll also need a compiler to build the C extensions.</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="git clone https://github.com/explosion/thinc cd thinc python -m venv .env source .env/bin/activate pip install -U pip setuptools wheel pip install -r requirements.txt pip install --no-build-isolation ."><pre>git clone https://github.com/explosion/thinc <span class="pl-c1">cd</span> thinc python -m venv .env <span class="pl-c1">source</span> .env/bin/activate pip install -U pip setuptools wheel pip install -r requirements.txt pip install --no-build-isolation <span class="pl-c1">.</span></pre></div> <p dir="auto">Alternatively, install in editable mode:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="pip install -r requirements.txt pip install --no-build-isolation --editable ."><pre>pip install -r requirements.txt pip install --no-build-isolation --editable <span class="pl-c1">.</span></pre></div> <p dir="auto">Or by setting <code>PYTHONPATH</code>:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="export PYTHONPATH=`pwd` pip install -r requirements.txt python setup.py build_ext --inplace"><pre><span class="pl-k">export</span> PYTHONPATH=<span class="pl-s"><span class="pl-pds">`</span>pwd<span class="pl-pds">`</span></span> pip install -r requirements.txt python setup.py build_ext --inplace</pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">🚦 Running tests</h3><a id="user-content--running-tests" class="anchor" aria-label="Permalink: 🚦 Running tests" href="#-running-tests"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Thinc comes with an <a href="/explosion/thinc/blob/main/thinc/tests">extensive test suite</a>. The following should all pass and not report any warnings or errors:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="python -m pytest thinc # test suite python -m mypy thinc # type checks python -m flake8 thinc # linting"><pre>python -m pytest thinc <span class="pl-c"><span class="pl-c">#</span> test suite</span> python -m mypy thinc <span class="pl-c"><span class="pl-c">#</span> type checks</span> python -m flake8 thinc <span class="pl-c"><span class="pl-c">#</span> linting</span></pre></div> <p dir="auto">To view test coverage, you can run <code>python -m pytest thinc --cov=thinc</code>. We aim for a 100% test coverage. This doesn't mean that we meticulously write tests for every single line – we ignore blocks that are not relevant or difficult to test and make sure that the tests execute all code paths.</p> </article></div></div></div></div></div> <!-- --> <!-- --> <script type="application/json" id="__PRIMER_DATA_:R0:__">{"resolvedServerColorMode":"day"}</script></div> </react-partial> <input type="hidden" data-csrf="true" value="qh4nHoT4vFo6+tOvL0YtgrQrA5rbQ04Uk05aUMmfO2x5byrgfxV0B/AMfhvPLkput2ttfSDLFHxKGSNQx7H27Q==" /> </div> <div data-view-component="true" class="Layout-sidebar"> <div class="BorderGrid about-margin" data-pjax> <div class="BorderGrid-row"> <div class="BorderGrid-cell"> <div class="hide-sm hide-md"> <h2 class="mb-3 h4">About</h2> <p class="f4 my-3"> 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries </p> <div class="my-3 d-flex flex-items-center"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" 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class="Box-btn-octicon m-0 btn-octicon position-absolute right-0 top-0" type="button" aria-label="Close dialog" data-close-dialog> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-x"> <path d="M3.72 3.72a.75.75 0 0 1 1.06 0L8 6.94l3.22-3.22a.749.749 0 0 1 1.275.326.749.749 0 0 1-.215.734L9.06 8l3.22 3.22a.749.749 0 0 1-.326 1.275.749.749 0 0 1-.734-.215L8 9.06l-3.22 3.22a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042L6.94 8 3.72 4.78a.75.75 0 0 1 0-1.06Z"></path> </svg> </button> <div class="octocat-spinner my-6 js-details-dialog-spinner"></div> </details-dialog> </details> </template> <div class="Popover js-hovercard-content position-absolute" style="display: none; outline: none;"> <div class="Popover-message Popover-message--bottom-left Popover-message--large Box color-shadow-large" style="width:360px;"> </div> </div> <template id="snippet-clipboard-copy-button"> <div class="zeroclipboard-container position-absolute right-0 top-0"> <clipboard-copy aria-label="Copy" class="ClipboardButton btn js-clipboard-copy m-2 p-0" data-copy-feedback="Copied!" data-tooltip-direction="w"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-copy js-clipboard-copy-icon m-2"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 0 1 0 1.5h-1.5a.25.25 0 0 0-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 0 0 .25-.25v-1.5a.75.75 0 0 1 1.5 0v1.5A1.75 1.75 0 0 1 9.25 16h-7.5A1.75 1.75 0 0 1 0 14.25Z"></path><path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0 1 14.25 11h-7.5A1.75 1.75 0 0 1 5 9.25Zm1.75-.25a.25.25 0 0 0-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 0 0 .25-.25v-7.5a.25.25 0 0 0-.25-.25Z"></path> </svg> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-check js-clipboard-check-icon color-fg-success d-none m-2"> <path d="M13.78 4.22a.75.75 0 0 1 0 1.06l-7.25 7.25a.75.75 0 0 1-1.06 0L2.22 9.28a.751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018L6 10.94l6.72-6.72a.75.75 0 0 1 1.06 0Z"></path> </svg> </clipboard-copy> </div> </template> <template id="snippet-clipboard-copy-button-unpositioned"> <div class="zeroclipboard-container"> <clipboard-copy aria-label="Copy" class="ClipboardButton btn btn-invisible js-clipboard-copy m-2 p-0 d-flex flex-justify-center flex-items-center" data-copy-feedback="Copied!" data-tooltip-direction="w"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-copy js-clipboard-copy-icon"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 0 1 0 1.5h-1.5a.25.25 0 0 0-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 0 0 .25-.25v-1.5a.75.75 0 0 1 1.5 0v1.5A1.75 1.75 0 0 1 9.25 16h-7.5A1.75 1.75 0 0 1 0 14.25Z"></path><path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0 1 14.25 11h-7.5A1.75 1.75 0 0 1 5 9.25Zm1.75-.25a.25.25 0 0 0-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 0 0 .25-.25v-7.5a.25.25 0 0 0-.25-.25Z"></path> </svg> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-check js-clipboard-check-icon color-fg-success d-none"> <path d="M13.78 4.22a.75.75 0 0 1 0 1.06l-7.25 7.25a.75.75 0 0 1-1.06 0L2.22 9.28a.751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018L6 10.94l6.72-6.72a.75.75 0 0 1 1.06 0Z"></path> </svg> </clipboard-copy> </div> </template> </div> <div id="js-global-screen-reader-notice" class="sr-only mt-n1" aria-live="polite" aria-atomic="true" ></div> <div id="js-global-screen-reader-notice-assertive" class="sr-only mt-n1" aria-live="assertive" aria-atomic="true"></div> </body> </html>