deploy: SimplexLab/TorchJD@55c5a55

Author: ValerianRey

latest/docs/aggregation/aligned_mtl/index.html

@@ -247,7 +247,7 @@ <h1>Aligned-MTL<a class="headerlink" href="#aligned-mtl" title="Link to this hea
 <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://docs.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 class="field-odd"><p><strong>pref_vector</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 v2.8)"><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

@@ -243,7 +243,7 @@ <h1>Aggregator (abstract)<a class="headerlink" href="#aggregator-abstract" title
 <dl class="py class">
 <dt class="sig sig-object py" id="torchjd.aggregation.Aggregator">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torchjd.aggregation.</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/_aggregator_bases.py#L9-L37"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torchjd.aggregation.Aggregator" title="Link to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference external" href="https://docs.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>
+<dd><p>Bases: <a class="reference external" href="https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module" title="(in PyTorch v2.8)"><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/config/index.html

@@ -247,7 +247,7 @@ <h1>ConFIG<a class="headerlink" href="#config" title="Link to this heading">¶</
 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://docs.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
+<dd class="field-odd"><p><strong>pref_vector</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 v2.8)"><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

@@ -247,7 +247,7 @@ <h1>Constant<a class="headerlink" href="#constant" title="Link to this heading">
 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://docs.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 class="field-odd"><p><strong>weights</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 v2.8)"><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">

latest/docs/aggregation/dualproj/index.html

@@ -249,7 +249,7 @@ <h1>DualProj<a class="headerlink" href="#dualproj" title="Link to this heading">
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>pref_vector</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 v2.7)"><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 combine the rows. If not provided, defaults to
+<li><p><strong>pref_vector</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 v2.8)"><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 combine the rows. If not provided, defaults to
 the simple averaging.</p></li>
 <li><p><strong>norm_eps</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code></a></span>) – A small value to avoid division by zero when normalizing.</p></li>
 <li><p><strong>reg_eps</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code></a></span>) – A small value to add to the diagonal of the gramian of the matrix. Due to

latest/docs/aggregation/graddrop/index.html

@@ -251,7 +251,7 @@ <h1>GradDrop<a class="headerlink" href="#graddrop" title="Link to this heading">
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>f</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.python.org/3/library/collections.abc.html#collections.abc.Callable" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Callable</span></code></a></span>) – The function to apply to the Gradient Positive Sign Purity. It should be monotically
 increasing. Defaults to identity.</p></li>
-<li><p><strong>leak</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 v2.7)"><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 tensor of leak values, determining how much each row is allowed to leak
+<li><p><strong>leak</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 v2.8)"><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 tensor of leak values, determining how much each row is allowed to leak
 through. Defaults to None, which means no leak.</p></li>
 </ul>
 </dd>

latest/docs/aggregation/upgrad/index.html

@@ -249,7 +249,7 @@ <h1>UPGrad<a class="headerlink" href="#upgrad" title="Link to this heading">¶</
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>pref_vector</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 v2.7)"><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 combine the projected rows. If not provided,
+<li><p><strong>pref_vector</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 v2.8)"><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 combine the projected rows. If not provided,
 defaults to the simple averaging of the projected rows.</p></li>
 <li><p><strong>norm_eps</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code></a></span>) – A small value to avoid division by zero when normalizing.</p></li>
 <li><p><strong>reg_eps</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code></a></span>) – A small value to add to the diagonal of the gramian of the matrix. Due to

latest/docs/autojac/backward/index.html

@@ -249,10 +249,10 @@ <h1>backward<a class="headerlink" href="#backward" title="Link to this heading">
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>tensors</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.python.org/3/library/collections.abc.html#collections.abc.Sequence" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Sequence</span></code></a>[<a class="reference external" href="https://docs.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.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 tensor or tensors to differentiate. Should be non-empty. The Jacobian
+<li><p><strong>tensors</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.python.org/3/library/collections.abc.html#collections.abc.Sequence" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Sequence</span></code></a>[<a class="reference external" href="https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.8)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>] | <a class="reference external" href="https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.8)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a></span>) – The tensor or tensors to differentiate. Should be non-empty. The Jacobian
 matrices will have one row for each value of each of these tensors.</p></li>
 <li><p><strong>aggregator</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference internal" href="../../aggregation/bases/#torchjd.aggregation.Aggregator" title="torchjd.aggregation._aggregator_bases.Aggregator"><code class="xref py py-class docutils literal notranslate"><span class="pre">Aggregator</span></code></a></span>) – Aggregator used to reduce the Jacobian into a vector.</p></li>
-<li><p><strong>inputs</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.python.org/3/library/collections.abc.html#collections.abc.Iterable" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Iterable</span></code></a>[<a class="reference external" href="https://docs.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 tensors with respect to which the Jacobian must be computed. These must have
+<li><p><strong>inputs</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.python.org/3/library/collections.abc.html#collections.abc.Iterable" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Iterable</span></code></a>[<a class="reference external" href="https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.8)"><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 tensors with respect to which the Jacobian must be computed. These must have
 their <code class="docutils literal notranslate"><span class="pre">requires_grad</span></code> flag set to <code class="docutils literal notranslate"><span class="pre">True</span></code>. If not provided, defaults to the leaf tensors
 that were used to compute the <code class="docutils literal notranslate"><span class="pre">tensors</span></code> parameter.</p></li>
 <li><p><strong>retain_graph</strong> (<span class="sphinx_autodoc_typehints-type"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">bool</span></code></a></span>) – If <code class="docutils literal notranslate"><span class="pre">False</span></code>, the graph used to compute the grad will be freed. Defaults to