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Add minimal infrastructure for the docs (#431)
* Add minimal infrastructure for the docs * Add `glu` * Add reference Flux layers * Fix a couple of docstring references
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‎.github/workflows/ci.yml

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with:
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file: lcov.info
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# docs:
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# name: Documentation
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# runs-on: ubuntu-latest
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# steps:
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# - uses: actions/checkout@v2
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# - uses: julia-actions/setup-julia@v1
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# with:
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# version: '1'
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# - run: julia --project=docs .ci/develop.jl
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# - run: julia --project=docs docs/make.jl
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# env:
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# GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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# DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }}
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# doctests:
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# name: Doctests
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# runs-on: ubuntu-latest
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# steps:
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# - uses: actions/checkout@v2
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# - uses: julia-actions/setup-julia@v1
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# with:
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# version: '1'
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# - run: julia --project=docs .ci/develop.jl
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# - run: |
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# julia --project=docs -e '
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# using Documenter
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# using NNlib
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# # using NNlibCUDA
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# DocMeta.setdocmeta!(NNlib, :DocTestSetup, :(using NNlib); recursive=true)
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# # DocMeta.setdocmeta!(NNlibCUDA, :DocTestSetup, :(using NNlib, CUDA); recursive=true)
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# doctest(NNlib)
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# # doctest(NNlibCUDA)'
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docs:
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name: Documentation
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v2
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- uses: julia-actions/setup-julia@v1
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with:
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version: '1.6'
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- run: |
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julia --project=docs -e '
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using Pkg
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Pkg.develop(PackageSpec(path=pwd()))
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Pkg.instantiate()'
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- run: |
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julia --color=yes --project=docs/ -e '
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using NNlib
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# using Pkg; Pkg.activate("docs")
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using Documenter
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using Documenter: doctest
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DocMeta.setdocmeta!(NNlib, :DocTestSetup, :(using NNlib); recursive=true)
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doctest(NNlib)'
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- run: julia --project=docs docs/make.jl
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }}

‎.github/workflows/clean_preview.yml

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# from https://github.com/CliMA/ClimaTimeSteppers.jl
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name: Doc Preview Cleanup
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on:
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pull_request:
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types: [closed]
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jobs:
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doc-preview-cleanup:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout gh-pages branch
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uses: actions/checkout@v2
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with:
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ref: gh-pages
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- name: Delete preview and history + push changes
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run: |
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if [ -d "previews/PR$PRNUM" ]; then
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git config user.name "Documenter.jl"
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git config user.email "[email protected]"
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git rm -rf "previews/PR$PRNUM"
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git commit -m "delete preview"
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git branch gh-pages-new $(echo "delete history" | git commit-tree HEAD^{tree})
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git push --force origin gh-pages-new:gh-pages
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fi
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env:
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PRNUM: ${{ github.event.number }}

‎.github/workflows/pr_comment.yml

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name: pr_comment
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on:
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pull_request:
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types: [labeled]
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jobs:
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pr_comment:
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runs-on: ubuntu-latest
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steps:
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- name: Create PR comment
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if: github.event_name == 'pull_request' && github.repository == github.event.pull_request.head.repo.full_name && github.event.label.name == 'documentation' # if this is a pull request build AND the pull request is NOT made from a fork
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uses: thollander/actions-comment-pull-request@71efef56b184328c7ef1f213577c3a90edaa4aff
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with:
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message: 'Once the documentation build has completed, you can preview any updated documentation at this URL: https://fluxml.ai/NNlib.jl/previews/PR${{ github.event.number }}/'
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

‎docs/.gitignore

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build/
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site/

‎docs/make.jl

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using Documenter, NNlib
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DocMeta.setdocmeta!(NNlib, :DocTestSetup, :(using NNlib); recursive = true)
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makedocs(modules = [NNlib],
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sitename = "NNlib.jl",
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doctest = false,
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pages = ["Home" => "index.md",
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"Reference" => "reference.md"],
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format = Documenter.HTML(
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canonical = "https://fluxml.ai/NNlib.jl/stable/",
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# analytics = "UA-36890222-9",
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assets = ["assets/flux.css"],
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prettyurls = get(ENV, "CI", nothing) == "true"),
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)
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deploydocs(repo = "github.com/FluxML/NNlib.jl.git",
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target = "build",
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push_preview = true)

‎docs/src/assets/flux.css

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@import url('https://fonts.googleapis.com/css?family=Lato:400,400i');
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body {
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font-family: Lato, "Segoe UI",Roboto,"Helvetica Neue",Arial,sans-serif;
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}
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nav.toc {
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padding-top: 0;
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background: rgb(240, 240, 240);
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line-height: 2em;
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cursor: default;
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user-select: none;
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}
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h1+h2 {
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margin-top: 0;
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}
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/* Green banner in ToC */
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nav.toc > h1 {
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margin-top: 0;
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padding-top: 0.4em;
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padding-bottom: 0.5em;
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border-bottom: 5px solid white;
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box-shadow: 0px -2px 5px rgb(60,60,60);
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margin-bottom: 0.5em;
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background: rgb(60, 150, 60);
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font-style: italic;
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font-weight: normal;
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font-size: 50pt;
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text-transform: lowercase;
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text-shadow: 2px 2px 5px rgba(0,0,0,0.2);
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color: white;
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}
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/* Reduce ToC font size */
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.toctext {
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font-size: 10pt;
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}
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/* Fade out non-clickable ToC headers */
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nav.toc ul span.toctext {
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color: rgb(180, 180, 180);
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}
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nav.toc ul .toctext {
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color: rgb(100, 100, 100);
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}
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nav.toc ul a.toctext:hover {
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color: inherit;
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background: rgb(220, 220, 220);
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cursor: default;
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}
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nav.toc li.current > .toctext {
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background: linear-gradient(90deg, rgb(245,245,245) 0%, white 90%);
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font-weight: normal;
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}
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nav.toc ul.internal li.toplevel {
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font-weight: normal;
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}
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/* Content */
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article { max-width: none; }
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article > p, article > ul {
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max-width: 45em;
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}
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/* Links */
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a, a:visited { color: rgb(0, 120, 0); }
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article p a { border-bottom: 1px solid rgb(200, 230, 200); }
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a:hover, a:visited:hover { color: rgb(0, 80, 0); }
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/* Article Links */
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article p a { border-bottom: 1px solid rgb(200, 230, 200); }
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article p a:hover, article a:visited:hover { color: rgb(0, 120, 0); }
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article p a:hover { border-bottom: 1px solid rgb(150, 200, 150); }
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/* Doctstrings */
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article section.docstring {
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padding: 0.5em 0;
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border-left: none;
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border-right: none;
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border-bottom: none;
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}
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/* Code */
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article pre, article p > code {
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background: rgb(245, 250, 245);
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}
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article pre {
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border: none;
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max-width: none;
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padding: 1em;
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border-radius: 10px 0px 0px 10px;
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margin-left: -1em;
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margin-right: -2em;
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}
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.hljs-comment {
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font-style: italic;
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}
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.hljs-number {
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color: rgb(0, 150, 150);
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}

‎docs/src/index.md

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# NNlib.jl
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`NNlib` provides a library of functions useful for neural networks, such as softmax, sigmoid, batched multiplication, convolutions and pooling. Many of these are used by [Flux.jl](https://github.com/FluxML/Flux.jl), which loads this package, but they may be used independently.
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For use with automatic differentiation, this package defines gradients using [ChainRules.jl](https://github.com/JuliaDiff/ChainRules.jl). These will be seen by various packages including [Zygote.jl](https://github.com/FluxML/Zygote.jl).
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To use these functions with [CUDA.jl](https://github.com/JuliaGPU/CUDA.jl) you will need [NNlibCUDA.jl](https://github.com/FluxML/NNlibCUDA.jl) as well.

‎docs/src/reference.md

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# Reference
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The API reference of `NNlib`.
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## Activation Functions
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Non-linearities that go between layers of your model. Note that, unless otherwise stated, activation functions operate on scalars. To apply them to an array you can call `σ.(xs)`, `relu.(xs)` and so on.
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```@docs
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celu
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elu
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gelu
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hardsigmoid
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sigmoid_fast
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hardtanh
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tanh_fast
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leakyrelu
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lisht
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logcosh
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logsigmoid
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mish
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relu
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relu6
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rrelu
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selu
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sigmoid
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softplus
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softshrink
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softsign
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swish
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hardswish
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tanhshrink
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trelu
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```
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## Softmax
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`Flux`'s `logitcrossentropy` uses `NNlib.softmax` internally.
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```@docs
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softmax
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logsoftmax
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```
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## Pooling
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`Flux`'s `AdaptiveMaxPool`, `AdaptiveMeanPool`, `GlobalMaxPool`, `GlobalMeanPool`, `MaxPool`, and `MeanPool` use `NNlib.PoolDims`, `NNlib.maxpool`, and `NNlib.meanpool` as their backend.
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```@docs
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PoolDims
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maxpool
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meanpool
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```
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## Padding
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```@docs
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pad_reflect
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pad_constant
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pad_repeat
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pad_zeros
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```
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## Convolution
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`Flux`'s `Conv` and `CrossCor` layers use `NNlib.DenseConvDims` and `NNlib.conv` internally.
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```@docs
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conv
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ConvDims
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depthwiseconv
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DepthwiseConvDims
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DenseConvDims
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```
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## Upsampling
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`Flux`'s `Upsample` layer uses `NNlib.upsample_nearest`, `NNlib.upsample_bilinear`, and `NNlib.upsample_trilinear` as its backend. Additionally, `Flux`'s `PixelShuffle` layer uses `NNlib.pixel_shuffle` as its backend.
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```@docs
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upsample_nearest
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∇upsample_nearest
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upsample_linear
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∇upsample_linear
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upsample_bilinear
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∇upsample_bilinear
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upsample_trilinear
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∇upsample_trilinear
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pixel_shuffle
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```
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## Batched Operations
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`Flux`'s `Bilinear` layer uses `NNlib.batched_mul` internally.
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```@docs
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batched_mul
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batched_mul!
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batched_adjoint
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batched_transpose
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batched_vec
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```
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## Gather and Scatter
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`Flux`'s `Embedding` layer uses `NNlib.gather` as its backend.
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```@docs
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NNlib.gather
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NNlib.gather!
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NNlib.scatter
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NNlib.scatter!
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```
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## Sampling
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```@docs
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grid_sample
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∇grid_sample
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```
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## Losses
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```@docs
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ctc_loss
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```
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## Miscellaneous
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```@docs
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logsumexp
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NNlib.glu
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```

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