deploy: SimplexLab/TorchJD@d1973e7

Author: ValerianRey

latest/docs/aggregation/cagrad/index.html

@@ -302,7 +302,7 @@
 <h1>CAGrad<a class="headerlink" href="#cagrad" title="Link to this heading">¶</a></h1>
 <dl class="py class">
 <dt class="sig sig-object py" id="torchjd.aggregation.CAGrad">
-<span class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></span><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.</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/SimplexLab/TorchJD/blob/main/src/torchjd/aggregation/_cagrad.py#L95-L140"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.CAGrad" title="Link to this definition">¶</a></dt>
+<span class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></span><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.</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/SimplexLab/TorchJD/blob/main/src/torchjd/aggregation/_cagrad.py#L96-L138"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.CAGrad" title="Link to this definition">¶</a></dt>
 <dd><p><a class="reference internal" href="../#torchjd.aggregation.GramianWeightedAggregator" title="torchjd.aggregation.GramianWeightedAggregator"><code class="xref py py-class docutils literal notranslate"><span class="pre">GramianWeightedAggregator</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">
@@ -322,14 +322,14 @@ <h1>CAGrad<a class="headerlink" href="#cagrad" title="Link to this heading">¶</
 </div>
 <dl class="py method">
 <dt class="sig sig-object py" id="torchjd.aggregation.CAGrad.__call__">
-<span class="sig-name descname"><span class="pre">__call__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span></em>, <em class="sig-param"><span class="positional-only-separator o"><abbr title="Positional-only parameter separator (PEP 570)"><span class="pre">/</span></abbr></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/SimplexLab/TorchJD/blob/main/src/torchjd/aggregation/_aggregator_bases.py#L32-L39"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.CAGrad.__call__" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">__call__</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/SimplexLab/TorchJD/blob/main/src/torchjd/aggregation/_mixins.py#L27-L29"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.CAGrad.__call__" title="Link to this definition">¶</a></dt>
 <dd><p>Computes the aggregation from the input matrix and applies all registered hooks.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
-<dd class="field-odd"><p><strong>matrix</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.11)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a></span>) – The Jacobian to aggregate.</p>
+<dd class="field-odd"><p><strong>matrix</strong> – The Jacobian to aggregate.</p>
 </dd>
 <dt class="field-even">Return type<span class="colon">:</span></dt>
-<dd class="field-even"><p><span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.11)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a></span></p>
+<dd class="field-even"><p><span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.14)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Any</span></code></a></span></p>
 </dd>
 </dl>
 </dd></dl>
@@ -338,7 +338,7 @@ <h1>CAGrad<a class="headerlink" href="#cagrad" title="Link to this heading">¶</
 
 <dl class="py class">
 <dt class="sig sig-object py" id="torchjd.aggregation.CAGradWeighting">
-<span class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></span><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.</span></span><span class="sig-name descname"><span class="pre">CAGradWeighting</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/SimplexLab/TorchJD/blob/main/src/torchjd/aggregation/_cagrad.py#L21-L92"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.CAGradWeighting" title="Link to this definition">¶</a></dt>
+<span class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></span><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.</span></span><span class="sig-name descname"><span class="pre">CAGradWeighting</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/SimplexLab/TorchJD/blob/main/src/torchjd/aggregation/_cagrad.py#L22-L93"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.CAGradWeighting" title="Link to this definition">¶</a></dt>
 <dd><p><a class="reference internal" href="../#torchjd.aggregation.Weighting" title="torchjd.aggregation.Weighting"><code class="xref py py-class docutils literal notranslate"><span class="pre">Weighting</span></code></a> [<a class="reference internal" href="../../linalg/psd_matrix/#torchjd.linalg.PSDMatrix" title="torchjd.linalg.PSDMatrix"><code class="xref py py-class docutils literal notranslate"><span class="pre">PSDMatrix</span></code></a>]
 giving the weights of <a class="reference internal" href="#torchjd.aggregation.CAGrad" title="torchjd.aggregation.CAGrad"><code class="xref py py-class docutils literal notranslate"><span class="pre">CAGrad</span></code></a>.</p>
 <dl class="field-list simple">
@@ -358,14 +358,14 @@ <h1>CAGrad<a class="headerlink" href="#cagrad" title="Link to this heading">¶</
 </div>
 <dl class="py method">
 <dt class="sig sig-object py" id="torchjd.aggregation.CAGradWeighting.__call__">
-<span class="sig-name descname"><span class="pre">__call__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">gramian</span></span></em>, <em class="sig-param"><span class="positional-only-separator o"><abbr title="Positional-only parameter separator (PEP 570)"><span class="pre">/</span></abbr></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/SimplexLab/TorchJD/blob/main/src/torchjd/aggregation/_weighting_bases.py#L72-L78"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.CAGradWeighting.__call__" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">__call__</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/SimplexLab/TorchJD/blob/main/src/torchjd/aggregation/_mixins.py#L27-L29"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.CAGradWeighting.__call__" title="Link to this definition">¶</a></dt>
 <dd><p>Computes the vector of weights from the input Gramian and applies all registered hooks.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
-<dd class="field-odd"><p><strong>gramian</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.11)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a></span>) – The Gramian from which the weights must be extracted.</p>
+<dd class="field-odd"><p><strong>gramian</strong> – The Gramian from which the weights must be extracted.</p>
 </dd>
 <dt class="field-even">Return type<span class="colon">:</span></dt>
-<dd class="field-even"><p><span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.11)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a></span></p>
+<dd class="field-even"><p><span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.14)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Any</span></code></a></span></p>
 </dd>
 </dl>
 </dd></dl>

latest/docs/aggregation/config/index.html

@@ -302,7 +302,7 @@
 <h1>ConFIG<a class="headerlink" href="#config" title="Link to this heading">¶</a></h1>
 <dl class="py class">
 <dt class="sig sig-object py" id="torchjd.aggregation.ConFIG">
-<span class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></span><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.</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/SimplexLab/TorchJD/blob/main/src/torchjd/aggregation/_config.py#L16-L61"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.ConFIG" title="Link to this definition">¶</a></dt>
+<span class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></span><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.</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/SimplexLab/TorchJD/blob/main/src/torchjd/aggregation/_config.py#L17-L59"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.ConFIG" title="Link to this definition">¶</a></dt>
 <dd><p><a class="reference internal" href="../#torchjd.aggregation.Aggregator" title="torchjd.aggregation.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">
@@ -317,14 +317,14 @@ <h1>ConFIG<a class="headerlink" href="#config" title="Link to this heading">¶</
 </div>
 <dl class="py method">
 <dt class="sig sig-object py" id="torchjd.aggregation.ConFIG.__call__">
-<span class="sig-name descname"><span class="pre">__call__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span></em>, <em class="sig-param"><span class="positional-only-separator o"><abbr title="Positional-only parameter separator (PEP 570)"><span class="pre">/</span></abbr></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/SimplexLab/TorchJD/blob/main/src/torchjd/aggregation/_aggregator_bases.py#L32-L39"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.ConFIG.__call__" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">__call__</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/SimplexLab/TorchJD/blob/main/src/torchjd/aggregation/_mixins.py#L27-L29"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.ConFIG.__call__" title="Link to this definition">¶</a></dt>
 <dd><p>Computes the aggregation from the input matrix and applies all registered hooks.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
-<dd class="field-odd"><p><strong>matrix</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.11)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a></span>) – The Jacobian to aggregate.</p>
+<dd class="field-odd"><p><strong>matrix</strong> – The Jacobian to aggregate.</p>
 </dd>
 <dt class="field-even">Return type<span class="colon">:</span></dt>
-<dd class="field-even"><p><span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.11)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a></span></p>
+<dd class="field-even"><p><span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.14)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Any</span></code></a></span></p>
 </dd>
 </dl>
 </dd></dl>