build based on 29e4578

dev/.documenter-siteinfo.json

@@ -1 +1 @@
-{"documenter":{"julia_version":"1.11.1","generation_timestamp":"2024-11-11T14:23:00","documenter_version":"1.7.0"}}
+{"documenter":{"julia_version":"1.11.1","generation_timestamp":"2024-11-11T14:42:18","documenter_version":"1.7.0"}}

dev/citation/index.html

@@ -21,4 +21,4 @@
   title   = {Mill.jl framework: a flexible library for (hierarchical) multi-instance learning},
   url     = {https://github.com/CTUAvastLab/Mill.jl},
   version = {...},
-}</code></pre></li></ul></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../references/">« References</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.7.0 on <span class="colophon-date" title="Monday 11 November 2024 14:22">Monday 11 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+}</code></pre></li></ul></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../references/">« References</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.7.0 on <span class="colophon-date" title="Monday 11 November 2024 14:42">Monday 11 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

dev/examples/dag/index.html

@@ -28,4 +28,4 @@
 end
 
 millneighbors!(cache, g::DagGraph, model::DagModel, i::Int) = millneighbors!(cache, g, model, inneighbors(g.g, i))
-ChainRulesCore.@non_differentiable inneighbors(g, i)</code></pre><p>Note that this recursive approach is not the most efficient way to implement this. It would be better to spent a little time with graphs to identify sets of vertices that can be processed in parallel and for which all ancestors are known. But this was a fun little exercise.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../gnn/">« GNNs in 16 lines</a><a class="docs-footer-nextpage" href="../../tools/hierarchical/">HierarchicalUtils.jl »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.7.0 on <span class="colophon-date" title="Monday 11 November 2024 14:22">Monday 11 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+ChainRulesCore.@non_differentiable inneighbors(g, i)</code></pre><p>Note that this recursive approach is not the most efficient way to implement this. It would be better to spent a little time with graphs to identify sets of vertices that can be processed in parallel and for which all ancestors are known. But this was a fun little exercise.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../gnn/">« GNNs in 16 lines</a><a class="docs-footer-nextpage" href="../../tools/hierarchical/">HierarchicalUtils.jl »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.7.0 on <span class="colophon-date" title="Monday 11 November 2024 14:42">Monday 11 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

dev/examples/gnn/index.html

@@ -47,4 +47,4 @@
   0.00016222768
   0.00021448887
   0.00030102703
- -0.00046899694</code><br/><code class="language-julia-repl hljs" style="display:block;">julia&gt; gradient(m -&gt; m(g, X, 5) |&gt; sum, gnn)</code><code class="nohighlight hljs ansi" style="display:block;">((lift = (m = (layers = ((weight = Float32[0.023729375 0.0073043876 0.00507586; 0.0034009127 -0.00055816496 -0.001996559; 0.0074122837 -0.012157058 -0.0032464762; 0.019973766 -0.002466879 -0.008808151], bias = Float32[0.031564355, 0.007343511, -0.0030228072, -0.009473307], σ = nothing), (weight = Float32[0.0010020004 -0.004688316 0.025474805 0.040968303; 0.004139893 0.00063540856 0.037446007 0.060782257; -0.011153192 -0.01265391 -0.017427681 -0.028889604; -0.0030410632 -0.0043758284 0.013323379 0.021474218], bias = Float32[0.033730146, 0.064496905, -0.051303748, 0.01573436], σ = nothing)),),), mp = (im = (m = (layers = ((weight = Float32[-0.0343868 0.028065441 -0.022546805 -0.030715173; 0.044193078 -0.04215087 -0.008396544 -0.03416454; -0.017730065 0.028343473 -0.004356968 0.025194738; 0.0025157235 0.029422589 0.0075494736 -0.020511081], bias = Float32[-0.01040332, 0.11693167, 0.027748574, 0.06606675], σ = nothing), (weight = Float32[0.011344679 0.0293103 -0.00657038 0.0055761575; -0.0030732683 -0.02212625 -0.01653417 -0.0044274977; 0.008140642 -0.0019123852 0.016163364 -0.0073407902; 0.013540533 -0.016273316 0.015952319 -0.00794171], bias = Float32[0.02243815, 0.020000346, -0.29838583, -0.09716275], σ = nothing)),),), a = (fs = ((ψ = Float32[0.0, 0.0, 0.0, 0.0],), (ψ = Float32[0.0, 0.0, 0.0, 0.0],)),), bm = (layers = ((weight = Float32[-0.020415353 0.023660988 … -0.0028440235 0.007423374; -0.015537388 0.009754301 … -0.0022147452 -0.004587447; 0.01613906 -0.013099574 … -0.00021842607 -0.02126051; 0.0125365555 -0.0090761045 … 0.0013786387 -0.007008895], bias = Float32[-0.025294017, 0.16506173, -0.08604198, 0.16027108], σ = nothing), (weight = Float32[0.0032370002 0.007290289 -0.0015835441 -0.0907538; 0.010025288 0.024912367 0.037466925 -0.075727746; -0.010327265 -0.02448437 -0.013396049 0.045430623; 0.0025176767 0.0047642025 0.011162643 -0.0017723107], bias = Float32[-0.20535398, -0.11515407, -0.2677527, -0.15884492], σ = nothing)),)), m = (layers = ((weight = Float32[0.0 0.0 … 0.0 0.0; 0.0 0.0 … 0.0 0.0; -0.012068051 0.011812808 … 0.0032108114 -0.0027346285; 0.0 0.0 … 0.0 0.0], bias = Float32[0.0, -0.0, 0.30443656, -0.0], σ = nothing), (weight = Float32[0.0 0.0 0.0006856819 0.0; 0.0 0.0 0.0006856819 0.0; 0.0 0.0 0.0006856819 0.0; 0.0 0.0 0.0006856819 0.0], bias = Fill(1.0f0, 4), σ = nothing)),)),)</code></pre><p>The above implementation is surprisingly general, as it supports an arbitrarily rich description of vertices. For simplicity, we used only vectors in <code>X</code>, however, any <a href="https://github.com/CTUAvastLab/Mill.jl"><code>Mill.jl</code></a> hierarchy is applicable.</p><p>To put different weights on edges, one can use <a href="../../manual/aggregation/#Weighted-aggregation">Weighted aggregation</a>.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../jsons/">« Processing JSONs</a><a class="docs-footer-nextpage" href="../dag/">DAGs »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.7.0 on <span class="colophon-date" title="Monday 11 November 2024 14:22">Monday 11 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+ -0.00046899694</code><br/><code class="language-julia-repl hljs" style="display:block;">julia&gt; gradient(m -&gt; m(g, X, 5) |&gt; sum, gnn)</code><code class="nohighlight hljs ansi" style="display:block;">((lift = (m = (layers = ((weight = Float32[0.023729375 0.0073043876 0.00507586; 0.0034009127 -0.00055816496 -0.001996559; 0.0074122837 -0.012157058 -0.0032464762; 0.019973766 -0.002466879 -0.008808151], bias = Float32[0.031564355, 0.007343511, -0.0030228072, -0.009473307], σ = nothing), (weight = Float32[0.0010020004 -0.004688316 0.025474805 0.040968303; 0.004139893 0.00063540856 0.037446007 0.060782257; -0.011153192 -0.01265391 -0.017427681 -0.028889604; -0.0030410632 -0.0043758284 0.013323379 0.021474218], bias = Float32[0.033730146, 0.064496905, -0.051303748, 0.01573436], σ = nothing)),),), mp = (im = (m = (layers = ((weight = Float32[-0.0343868 0.028065441 -0.022546805 -0.030715173; 0.044193078 -0.04215087 -0.008396544 -0.03416454; -0.017730065 0.028343473 -0.004356968 0.025194738; 0.0025157235 0.029422589 0.0075494736 -0.020511081], bias = Float32[-0.01040332, 0.11693167, 0.027748574, 0.06606675], σ = nothing), (weight = Float32[0.011344679 0.0293103 -0.00657038 0.0055761575; -0.0030732683 -0.02212625 -0.01653417 -0.0044274977; 0.008140642 -0.0019123852 0.016163364 -0.0073407902; 0.013540533 -0.016273316 0.015952319 -0.00794171], bias = Float32[0.02243815, 0.020000346, -0.29838583, -0.09716275], σ = nothing)),),), a = (fs = ((ψ = Float32[0.0, 0.0, 0.0, 0.0],), (ψ = Float32[0.0, 0.0, 0.0, 0.0],)),), bm = (layers = ((weight = Float32[-0.020415353 0.023660988 … -0.0028440235 0.007423374; -0.015537388 0.009754301 … -0.0022147452 -0.004587447; 0.01613906 -0.013099574 … -0.00021842607 -0.02126051; 0.0125365555 -0.0090761045 … 0.0013786387 -0.007008895], bias = Float32[-0.025294017, 0.16506173, -0.08604198, 0.16027108], σ = nothing), (weight = Float32[0.0032370002 0.007290289 -0.0015835441 -0.0907538; 0.010025288 0.024912367 0.037466925 -0.075727746; -0.010327265 -0.02448437 -0.013396049 0.045430623; 0.0025176767 0.0047642025 0.011162643 -0.0017723107], bias = Float32[-0.20535398, -0.11515407, -0.2677527, -0.15884492], σ = nothing)),)), m = (layers = ((weight = Float32[0.0 0.0 … 0.0 0.0; 0.0 0.0 … 0.0 0.0; -0.012068051 0.011812808 … 0.0032108114 -0.0027346285; 0.0 0.0 … 0.0 0.0], bias = Float32[0.0, -0.0, 0.30443656, -0.0], σ = nothing), (weight = Float32[0.0 0.0 0.0006856819 0.0; 0.0 0.0 0.0006856819 0.0; 0.0 0.0 0.0006856819 0.0; 0.0 0.0 0.0006856819 0.0], bias = Fill(1.0f0, 4), σ = nothing)),)),)</code></pre><p>The above implementation is surprisingly general, as it supports an arbitrarily rich description of vertices. For simplicity, we used only vectors in <code>X</code>, however, any <a href="https://github.com/CTUAvastLab/Mill.jl"><code>Mill.jl</code></a> hierarchy is applicable.</p><p>To put different weights on edges, one can use <a href="../../manual/aggregation/#Weighted-aggregation">Weighted aggregation</a>.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../jsons/">« Processing JSONs</a><a class="docs-footer-nextpage" href="../dag/">DAGs »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.7.0 on <span class="colophon-date" title="Monday 11 November 2024 14:42">Monday 11 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>