build based on d09d1b1

Author: Documenter.jl

dev/examples/Thermal_Generation_Dispatch_Example/index.html

@@ -93,4 +93,4 @@
 custom_loss(train_X, train_Y) = 1.691865f0
 custom_loss(train_X, train_Y) = 1.610134f0
 custom_loss(train_X, train_Y) = 1.5316879f0
-109.718281 seconds (76.78 M allocations: 4.763 GiB, 1.44% gc time, 0.71% compilation time)</code></pre><p>Although our custom implementation takes time, it is able to reach similar accuracy as the usual ReLU function implementation.</p><h2 id="Accuracy-results"><a class="docs-heading-anchor" href="#Accuracy-results">Accuracy results</a><a id="Accuracy-results-1"></a><a class="docs-heading-anchor-permalink" href="#Accuracy-results" title="Permalink"></a></h2><p>Average of correct guesses</p><pre><code class="language-julia hljs">accuracy(x, y) = Statistics.mean(Flux.onecold(m(x)) .== Flux.onecold(y));</code></pre><p>Training accuracy</p><pre><code class="language-julia hljs">accuracy(train_X, train_Y)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">0.562</code></pre><p>Test accuracy</p><pre><code class="language-julia hljs">accuracy(test_X, test_Y)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">0.478</code></pre><p>Note that the accuracy is low due to simplified training. It is possible to increase the number of samples <code>N</code>, the number of epochs <code>epoch</code> and the connectivity <code>inner</code>.</p><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../chainrules_unit/">« ChainRules integration demo: Relaxed Unit Commitment</a><a class="docs-footer-nextpage" href="../matrix-inversion-manual/">Differentiating a QP wrt a single variable »</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="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 0.27.25 on <span class="colophon-date" title="Wednesday 8 January 2025 17:03">Wednesday 8 January 2025</span>. Using Julia version 1.11.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+108.495299 seconds (76.71 M allocations: 4.762 GiB, 1.47% gc time, 0.71% compilation time)</code></pre><p>Although our custom implementation takes time, it is able to reach similar accuracy as the usual ReLU function implementation.</p><h2 id="Accuracy-results"><a class="docs-heading-anchor" href="#Accuracy-results">Accuracy results</a><a id="Accuracy-results-1"></a><a class="docs-heading-anchor-permalink" href="#Accuracy-results" title="Permalink"></a></h2><p>Average of correct guesses</p><pre><code class="language-julia hljs">accuracy(x, y) = Statistics.mean(Flux.onecold(m(x)) .== Flux.onecold(y));</code></pre><p>Training accuracy</p><pre><code class="language-julia hljs">accuracy(train_X, train_Y)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">0.562</code></pre><p>Test accuracy</p><pre><code class="language-julia hljs">accuracy(test_X, test_Y)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">0.478</code></pre><p>Note that the accuracy is low due to simplified training. It is possible to increase the number of samples <code>N</code>, the number of epochs <code>epoch</code> and the connectivity <code>inner</code>.</p><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../chainrules_unit/">« ChainRules integration demo: Relaxed Unit Commitment</a><a class="docs-footer-nextpage" href="../matrix-inversion-manual/">Differentiating a QP wrt a single variable »</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="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 0.27.25 on <span class="colophon-date" title="Wednesday 8 January 2025 22:10">Wednesday 8 January 2025</span>. Using Julia version 1.11.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

dev/examples/autotuning-ridge/index.html

@@ -68,4 +68,4 @@
     0.0 * index(x[1]) - 1.0,  # to indicate the direction vector to get directional derivatives
 )</code></pre><p>Note that <code>0.0 * index(x[1])</code> is used to make its type <code>typeof(0.0 * index(x[1]) - 1.0) &lt;: MOI.AbstractScalarFunction</code>. To indicate different direction to get directional derivative, users should replace <code>0.0 * index(x[1]) - 1.0</code> as the form of <code>dG*x - dh</code>, where <code>dG</code> and <code>dh</code> correspond to the elements of direction vectors along <code>G</code> and <code>h</code> axes, respectively.</p><p>Compute derivatives</p><pre><code class="language-julia hljs">DiffOpt.forward_differentiate!(model)</code></pre><p>Query derivative</p><pre><code class="language-julia hljs">dx = MOI.get.(model, DiffOpt.ForwardVariablePrimal(), x)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">2-element Vector{Float64}:
  0.2500000038571342
- 0.7500000115714025</code></pre><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../custom-relu/">« Custom ReLU layer</a><a class="docs-footer-nextpage" href="../nearest_correlation/">Nearest correlation »</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="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 0.27.25 on <span class="colophon-date" title="Wednesday 8 January 2025 17:03">Wednesday 8 January 2025</span>. Using Julia version 1.11.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+ 0.7500000115714025</code></pre><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../custom-relu/">« Custom ReLU layer</a><a class="docs-footer-nextpage" href="../nearest_correlation/">Nearest correlation »</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="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 0.27.25 on <span class="colophon-date" title="Wednesday 8 January 2025 22:10">Wednesday 8 January 2025</span>. Using Julia version 1.11.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

dev/examples/chainrules_unit/index.html

@@ -37,12 +37,12 @@
 ------------------------------------------------------------------
  iter | pri res | dua res |   gap   |   obj   |  scale  | time (s)
 ------------------------------------------------------------------
-     0| 9.98e-01  3.35e+00  2.27e+01 -1.27e+01  1.00e-01  1.31e-04
-    75| 5.98e-05  2.10e-06  1.25e-04 -6.72e+00  1.00e-01  3.78e-04
+     0| 9.98e-01  3.35e+00  2.27e+01 -1.27e+01  1.00e-01  1.20e-04
+    75| 5.98e-05  2.10e-06  1.25e-04 -6.72e+00  1.00e-01  3.68e-04
 ------------------------------------------------------------------
 status:  solved
-timings: total: 3.79e-04s = setup: 4.94e-05s + solve: 3.30e-04s
-	 lin-sys: 2.31e-05s, cones: 2.04e-04s, accel: 5.01e-06s
+timings: total: 3.69e-04s = setup: 4.65e-05s + solve: 3.22e-04s
+	 lin-sys: 2.29e-05s, cones: 2.04e-04s, accel: 3.92e-06s
 ------------------------------------------------------------------
 objective = -6.721507
 ------------------------------------------------------------------</code></pre><p>The projection of <code>A</code> is:</p><pre><code class="language-julia hljs">X</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">3×3 Matrix{Float64}:
@@ -72,12 +72,12 @@
 ------------------------------------------------------------------
  iter | pri res | dua res |   gap   |   obj   |  scale  | time (s)
 ------------------------------------------------------------------
-     0| 1.02e+00  3.57e+00  3.24e+01 -3.42e+01  1.00e-01  1.60e-04
-    75| 2.52e-05  7.03e-07  7.14e-05 -1.74e+01  1.00e-01  4.85e-04
+     0| 1.02e+00  3.57e+00  3.24e+01 -3.42e+01  1.00e-01  1.01e-04
+    75| 2.52e-05  7.03e-07  7.14e-05 -1.74e+01  1.00e-01  4.27e-04
 ------------------------------------------------------------------
 status:  solved
-timings: total: 4.86e-04s = setup: 7.75e-05s + solve: 4.09e-04s
-	 lin-sys: 3.26e-05s, cones: 2.70e-04s, accel: 4.39e-06s
+timings: total: 4.28e-04s = setup: 4.84e-05s + solve: 3.79e-04s
+	 lin-sys: 3.17e-05s, cones: 2.66e-04s, accel: 4.22e-06s
 ------------------------------------------------------------------
 objective = -17.447239
 ------------------------------------------------------------------</code></pre><p>The projection of <code>A</code> is:</p><pre><code class="language-julia hljs">X</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">4×4 Matrix{Float64}:
@@ -88,4 +88,4 @@
   0.101794    0.228658   -0.0880952  -0.0490976
   0.228658    0.0565823   0.158685   -0.0880952
  -0.0880952   0.158685    0.0565823   0.228658
- -0.0490976  -0.0880952   0.228658    0.101794</code></pre><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../matrix-inversion-manual/">« Differentiating a QP wrt a single variable</a><a class="docs-footer-nextpage" href="../polyhedral_project/">Polyhedral QP layer »</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="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 0.27.25 on <span class="colophon-date" title="Wednesday 8 January 2025 17:03">Wednesday 8 January 2025</span>. Using Julia version 1.11.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+ -0.0490976  -0.0880952   0.228658    0.101794</code></pre><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../matrix-inversion-manual/">« Differentiating a QP wrt a single variable</a><a class="docs-footer-nextpage" href="../polyhedral_project/">Polyhedral QP layer »</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="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 0.27.25 on <span class="colophon-date" title="Wednesday 8 January 2025 22:10">Wednesday 8 January 2025</span>. Using Julia version 1.11.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

dev/examples/custom-relu/index.html

@@ -119,4 +119,4 @@
 custom_loss(train_X, train_Y) = 0.7472685f0
 custom_loss(train_X, train_Y) = 0.65253365f0
 custom_loss(train_X, train_Y) = 0.5644549f0
- 64.838840 seconds (35.89 M allocations: 4.149 GiB, 2.35% gc time, 1.40% compilation time)</code></pre><p>Although our custom implementation takes time, it is able to reach similar accuracy as the usual ReLU function implementation.</p><h2 id="Accuracy-results"><a class="docs-heading-anchor" href="#Accuracy-results">Accuracy results</a><a id="Accuracy-results-1"></a><a class="docs-heading-anchor-permalink" href="#Accuracy-results" title="Permalink"></a></h2><p>Average of correct guesses</p><pre><code class="language-julia hljs">accuracy(x, y) = Statistics.mean(Flux.onecold(m(x)) .== Flux.onecold(y));</code></pre><p>Training accuracy</p><pre><code class="language-julia hljs">accuracy(train_X, train_Y)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">0.9</code></pre><p>Test accuracy</p><pre><code class="language-julia hljs">accuracy(test_X, test_Y)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">0.744</code></pre><p>Note that the accuracy is low due to simplified training. It is possible to increase the number of samples <code>N</code>, the number of epochs <code>epoch</code> and the connectivity <code>inner</code>.</p><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../nearest_correlation/">« Nearest correlation</a><a class="docs-footer-nextpage" href="../sensitivity-analysis-ridge/">Sensitivity Analysis of Ridge Regression »</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="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 0.27.25 on <span class="colophon-date" title="Wednesday 8 January 2025 17:03">Wednesday 8 January 2025</span>. Using Julia version 1.11.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+ 64.343004 seconds (35.89 M allocations: 4.149 GiB, 2.37% gc time, 1.43% compilation time)</code></pre><p>Although our custom implementation takes time, it is able to reach similar accuracy as the usual ReLU function implementation.</p><h2 id="Accuracy-results"><a class="docs-heading-anchor" href="#Accuracy-results">Accuracy results</a><a id="Accuracy-results-1"></a><a class="docs-heading-anchor-permalink" href="#Accuracy-results" title="Permalink"></a></h2><p>Average of correct guesses</p><pre><code class="language-julia hljs">accuracy(x, y) = Statistics.mean(Flux.onecold(m(x)) .== Flux.onecold(y));</code></pre><p>Training accuracy</p><pre><code class="language-julia hljs">accuracy(train_X, train_Y)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">0.9</code></pre><p>Test accuracy</p><pre><code class="language-julia hljs">accuracy(test_X, test_Y)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">0.744</code></pre><p>Note that the accuracy is low due to simplified training. It is possible to increase the number of samples <code>N</code>, the number of epochs <code>epoch</code> and the connectivity <code>inner</code>.</p><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../nearest_correlation/">« Nearest correlation</a><a class="docs-footer-nextpage" href="../sensitivity-analysis-ridge/">Sensitivity Analysis of Ridge Regression »</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="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 0.27.25 on <span class="colophon-date" title="Wednesday 8 January 2025 22:10">Wednesday 8 January 2025</span>. Using Julia version 1.11.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>