deploy: SimplexLab/TorchJD@0b5b419

Author: ValerianRey

latest/docs/aggregation/aligned_mtl/index.html

@@ -241,12 +241,12 @@
 <span id="aligned-mtl"></span><h1>Aligned-MTL<a class="headerlink" href="#module-torchjd.aggregation.aligned_mtl" title="Link to this heading">¶</a></h1>
 <dl class="py class">
 <dt class="sig sig-object py" id="torchjd.aggregation.aligned_mtl.AlignedMTL">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.aligned_mtl.</span></span><span class="sig-name descname"><span class="pre">AlignedMTL</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pref_vector</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#torchjd.aggregation.aligned_mtl.AlignedMTL" title="Link to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.aligned_mtl.</span></span><span class="sig-name descname"><span class="pre">AlignedMTL</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pref_vector</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/TorchJD/torchjd/blob/main/src/torchjd/aggregation/aligned_mtl.py#L36-L73"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.aligned_mtl.AlignedMTL" title="Link to this definition">¶</a></dt>
 <dd><p><a class="reference internal" href="../bases/#torchjd.aggregation.bases.Aggregator" title="torchjd.aggregation.bases.Aggregator"><code class="xref py py-class docutils literal notranslate"><span class="pre">Aggregator</span></code></a> as defined in Algorithm 1 of
 <a class="reference external" href="https://openaccess.thecvf.com/content/CVPR2023/papers/Senushkin_Independent_Component_Alignment_for_Multi-Task_Learning_CVPR_2023_paper.pdf">Independent Component Alignment for Multi-Task Learning</a>.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
-<dd class="field-odd"><p><strong>pref_vector</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.6)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a> | <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">None</span></code></a></span>) – The preference vector to use.</p>
+<dd class="field-odd"><p><strong>pref_vector</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.7)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a> | <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">None</span></code></a></span>) – The preference vector to use.</p>
 </dd>
 </dl>
 <div class="admonition-example admonition">

latest/docs/aggregation/bases/index.html

@@ -241,8 +241,8 @@
 <span id="aggregator-abstract"></span><h1>Aggregator (abstract)<a class="headerlink" href="#module-torchjd.aggregation.bases" title="Link to this heading">¶</a></h1>
 <dl class="py class">
 <dt class="sig sig-object py" id="torchjd.aggregation.bases.Aggregator">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.bases.</span></span><span class="sig-name descname"><span class="pre">Aggregator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#torchjd.aggregation.bases.Aggregator" title="Link to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference external" href="https://pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module" title="(in PyTorch v2.6)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/abc.html#abc.ABC" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">ABC</span></code></a></p>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.bases.</span></span><span class="sig-name descname"><span class="pre">Aggregator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/TorchJD/torchjd/blob/main/src/torchjd/aggregation/bases.py#L6-L42"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.bases.Aggregator" title="Link to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference external" href="https://pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module" title="(in PyTorch v2.7)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/abc.html#abc.ABC" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">ABC</span></code></a></p>
 <p>Abstract base class for all aggregators. It has the role of aggregating matrices of dimension
 <span class="math notranslate nohighlight">\(m \times n\)</span> into row vectors of dimension <span class="math notranslate nohighlight">\(n\)</span>.</p>
 </dd></dl>

latest/docs/aggregation/cagrad/index.html

@@ -241,7 +241,7 @@
 <span id="cagrad"></span><h1>CAGrad<a class="headerlink" href="#module-torchjd.aggregation.cagrad" title="Link to this heading">¶</a></h1>
 <dl class="py class">
 <dt class="sig sig-object py" id="torchjd.aggregation.cagrad.CAGrad">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.cagrad.</span></span><span class="sig-name descname"><span class="pre">CAGrad</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">c</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm_eps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0001</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#torchjd.aggregation.cagrad.CAGrad" title="Link to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.cagrad.</span></span><span class="sig-name descname"><span class="pre">CAGrad</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">c</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm_eps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0001</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/TorchJD/torchjd/blob/main/src/torchjd/aggregation/cagrad.py#L10-L44"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.cagrad.CAGrad" title="Link to this definition">¶</a></dt>
 <dd><p><a class="reference internal" href="../bases/#torchjd.aggregation.bases.Aggregator" title="torchjd.aggregation.bases.Aggregator"><code class="xref py py-class docutils literal notranslate"><span class="pre">Aggregator</span></code></a> as defined in Algorithm 1 of
 <a class="reference external" href="https://arxiv.org/pdf/2110.14048.pdf">Conflict-Averse Gradient Descent for Multi-task Learning</a>.</p>
 <dl class="field-list simple">

latest/docs/aggregation/config/index.html

@@ -241,12 +241,12 @@
 <span id="config"></span><h1>ConFIG<a class="headerlink" href="#module-torchjd.aggregation.config" title="Link to this heading">¶</a></h1>
 <dl class="py class">
 <dt class="sig sig-object py" id="torchjd.aggregation.config.ConFIG">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.config.</span></span><span class="sig-name descname"><span class="pre">ConFIG</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pref_vector</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#torchjd.aggregation.config.ConFIG" title="Link to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.config.</span></span><span class="sig-name descname"><span class="pre">ConFIG</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pref_vector</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/TorchJD/torchjd/blob/main/src/torchjd/aggregation/config.py#L36-L83"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.config.ConFIG" title="Link to this definition">¶</a></dt>
 <dd><p><a class="reference internal" href="../bases/#torchjd.aggregation.bases.Aggregator" title="torchjd.aggregation.bases.Aggregator"><code class="xref py py-class docutils literal notranslate"><span class="pre">Aggregator</span></code></a> as defined in Equation 2 of <a class="reference external" href="https://arxiv.org/pdf/2408.11104">ConFIG: Towards
 Conflict-free Training of Physics Informed Neural Networks</a>.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
-<dd class="field-odd"><p><strong>pref_vector</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.6)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a> | <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">None</span></code></a></span>) – The preference vector used to weight the rows. If not provided, defaults to
+<dd class="field-odd"><p><strong>pref_vector</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.7)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a> | <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">None</span></code></a></span>) – The preference vector used to weight the rows. If not provided, defaults to
 equal weights of 1.</p>
 </dd>
 </dl>

latest/docs/aggregation/constant/index.html

@@ -241,12 +241,12 @@
 <span id="constant"></span><h1>Constant<a class="headerlink" href="#module-torchjd.aggregation.constant" title="Link to this heading">¶</a></h1>
 <dl class="py class">
 <dt class="sig sig-object py" id="torchjd.aggregation.constant.Constant">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.constant.</span></span><span class="sig-name descname"><span class="pre">Constant</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">weights</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#torchjd.aggregation.constant.Constant" title="Link to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.constant.</span></span><span class="sig-name descname"><span class="pre">Constant</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">weights</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/TorchJD/torchjd/blob/main/src/torchjd/aggregation/constant.py#L7-L37"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.constant.Constant" title="Link to this definition">¶</a></dt>
 <dd><p><a class="reference internal" href="../bases/#torchjd.aggregation.bases.Aggregator" title="torchjd.aggregation.bases.Aggregator"><code class="xref py py-class docutils literal notranslate"><span class="pre">Aggregator</span></code></a> that makes a linear combination of the rows of
 the provided matrix, with constant, pre-determined weights.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
-<dd class="field-odd"><p><strong>weights</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.6)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a></span>) – The weights associated to the rows of the input matrices.</p>
+<dd class="field-odd"><p><strong>weights</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.7)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a></span>) – The weights associated to the rows of the input matrices.</p>
 </dd>
 </dl>
 <div class="admonition-example admonition">