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@@ -818,15 +818,15 @@ <h2><a class="toc-backref" href="#id6" role="doc-backlink">PyTorch</a><a class="
 <p>Moreover, the methods above <strong>must</strong> accept stacking dimensions in <code class="docutils literal notranslate"><span class="pre">arr</span></code>.  If this does not hold, consider
 populating <code class="code docutils literal notranslate"><span class="pre">vectorize</span></code>.</p>
 </li>
-<li><p><code class="xref py py-class docutils literal notranslate"><span class="pre">*</span> <span class="pre">Auto-vectorization</span> <span class="pre">consists</span> <span class="pre">in</span> <span class="pre">decorating</span> <span class="pre">`kwargs</span></code>-specified arithmetic methods with <a class="reference external" href="https://pytorch.org/docs/stable/generated/torch.vmap.html#torch.vmap" title="(in PyTorch v2.4)"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.vmap()</span></code></a>.  See` – the <a class="reference external" href="https://pytorch.org/docs/stable/func.ux_limitations.html#vmap-limitations">PyTorch documentation</a> for known
+<li><p><code class="xref py py-class docutils literal notranslate"><span class="pre">*</span> <span class="pre">Auto-vectorization</span> <span class="pre">consists</span> <span class="pre">in</span> <span class="pre">decorating</span> <span class="pre">`kwargs</span></code>-specified arithmetic methods with <a class="reference external" href="https://pytorch.org/docs/stable/generated/torch.vmap.html#torch.vmap" title="(in PyTorch v2.5)"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.vmap()</span></code></a>.  See` – the <a class="reference external" href="https://pytorch.org/docs/stable/func.ux_limitations.html#vmap-limitations">PyTorch documentation</a> for known
 limitations.</p></li>
-<li><p><code class="xref py py-class docutils literal notranslate"><span class="pre">*</span> <span class="pre">Arithmetic</span> <span class="pre">methods</span> <span class="pre">are</span> <span class="pre">**not</span> <span class="pre">currently</span> <span class="pre">JIT-ed**</span> <span class="pre">even</span> <span class="pre">if</span> <span class="pre">`jit</span></code> is set` to <code class="docutils literal notranslate"><span class="pre">True</span></code>.  This is because of <code class="xref py py-class docutils literal notranslate"><span class="pre">the</span></code> – undocumented and currently poor interaction between <a class="reference external" href="https://pytorch.org/docs/stable/func.api.html#module-torch.func" title="(in PyTorch v2.4)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">torch.func</span></code></a> transforms and <a class="reference external" href="https://pytorch.org/docs/stable/generated/torch.compile.html#torch.compile" title="(in PyTorch v2.4)"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.compile()</span></code></a>.
+<li><p><code class="xref py py-class docutils literal notranslate"><span class="pre">*</span> <span class="pre">Arithmetic</span> <span class="pre">methods</span> <span class="pre">are</span> <span class="pre">**not</span> <span class="pre">currently</span> <span class="pre">JIT-ed**</span> <span class="pre">even</span> <span class="pre">if</span> <span class="pre">`jit</span></code> is set` to <code class="docutils literal notranslate"><span class="pre">True</span></code>.  This is because of <code class="xref py py-class docutils literal notranslate"><span class="pre">the</span></code> – undocumented and currently poor interaction between <a class="reference external" href="https://pytorch.org/docs/stable/func.api.html#module-torch.func" title="(in PyTorch v2.5)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">torch.func</span></code></a> transforms and <a class="reference external" href="https://pytorch.org/docs/stable/generated/torch.compile.html#torch.compile" title="(in PyTorch v2.5)"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.compile()</span></code></a>.
 See <a class="reference external" href="https://github.com/pytorch/pytorch/issues/98822">this issue</a> for additional details.</p></li>
 <li><p><code class="xref py py-class docutils literal notranslate"><span class="pre">*</span> <span class="pre">For</span> <span class="pre">:py:class:`~pyxu.abc.DiffMap</span></code> (or subclasses thereof)`, <code class="xref py py-class docutils literal notranslate"><span class="pre">the</span> <span class="pre">methods</span> <span class="pre">:py:meth:`~pyxu.abc.DiffMap.jacobian</span></code>,` – <a class="reference internal" href="abc.html#pyxu.abc.DiffFunc.grad" title="pyxu.abc.DiffFunc.grad"><code class="xref py py-meth docutils literal notranslate"><span class="pre">grad()</span></code></a> and <a class="reference internal" href="abc.html#pyxu.abc.LinOp.adjoint" title="pyxu.abc.LinOp.adjoint"><code class="xref py py-meth docutils literal notranslate"><span class="pre">adjoint()</span></code></a> are defined implicitly if not provided
-using the auto-differentiation transforms from <a class="reference external" href="https://pytorch.org/docs/stable/func.api.html#module-torch.func" title="(in PyTorch v2.4)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">torch.func</span></code></a>.  As detailed <a class="reference external" href="https://pytorch.org/docs/stable/func.ux_limitations.html">on this page</a>, such transforms work well on pure functions (that
+using the auto-differentiation transforms from <a class="reference external" href="https://pytorch.org/docs/stable/func.api.html#module-torch.func" title="(in PyTorch v2.5)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">torch.func</span></code></a>.  As detailed <a class="reference external" href="https://pytorch.org/docs/stable/func.ux_limitations.html">on this page</a>, such transforms work well on pure functions (that
 is, functions where the output is completely determined by the input and that do not involve side effects like
-mutation), but may fail on more complex functions.  Moreover, <a class="reference external" href="https://pytorch.org/docs/stable/func.api.html#module-torch.func" title="(in PyTorch v2.4)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">torch.func</span></code></a> does not yet have full coverage
-over PyTorch operations.  For functions that call a <a class="reference external" href="https://pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module" title="(in PyTorch v2.4)"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.Module</span></code></a>, see <a class="reference external" href="https://pytorch.org/docs/stable/func.api.html#utilities-for-working-with-torch-nn-modules">here</a> for some utilities.</p></li>
+mutation), but may fail on more complex functions.  Moreover, <a class="reference external" href="https://pytorch.org/docs/stable/func.api.html#module-torch.func" title="(in PyTorch v2.5)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">torch.func</span></code></a> does not yet have full coverage
+over PyTorch operations.  For functions that call a <a class="reference external" href="https://pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module" title="(in PyTorch v2.5)"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.nn.Module</span></code></a>, see <a class="reference external" href="https://pytorch.org/docs/stable/func.api.html#utilities-for-working-with-torch-nn-modules">here</a> for some utilities.</p></li>
 <li><p><code class="xref py py-class docutils literal notranslate"> <span class="pre">Warning::</span></code> – Operators created with this wrapper do not support Dask inputs for now.</p></li>
 </ul>
 </p>
@@ -844,7 +844,7 @@ <h2><a class="toc-backref" href="#id6" role="doc-backlink">PyTorch</a><a class="
 <p>Convert a PyTorch tensor into a NumPy-like array, sharing data, dtype and device.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
-<dd class="field-odd"><p><strong>tensor</strong> (<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.4)"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Tensor</span></code></a>) – Input tensor.</p>
+<dd class="field-odd"><p><strong>tensor</strong> (<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.5)"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Tensor</span></code></a>) – Input tensor.</p>
 </dd>
 <dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p><strong>arr</strong> – Output array.</p>
@@ -874,7 +874,7 @@ <h2><a class="toc-backref" href="#id6" role="doc-backlink">PyTorch</a><a class="
 <dd class="field-even"><p><strong>tensor</strong> – Output tensor.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.4)"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Tensor</span></code></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.5)"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Tensor</span></code></a></p>
 </dd>
 </dl>
 <p class="rubric">Notes</p>

diff --git a/guide/diff_ops.html b/guide/diff_ops.html
@@ -292,7 +292,7 @@ <h2>Partial Derivatives<a class="headerlink" href="#Partial-Derivatives" title="
 <div class="math notranslate nohighlight">
 \[\mathbf{D} f [n] = f[n+1] - f[n]\]</div>
 <p>As we will see below, this is the forward finite difference approximation. This could be implemented in <strong>matrix-form</strong>, in which case it would look like this:</p>
-<center><p><img alt="875bb48c2d064c2e96edd550b6d7e188" class="no-scaled-link" src="../_images/matrix-form.png" style="width: 400px;"/></p>
+<center><p><img alt="f47ddc01c4a44acf91190c92942a9ad6" class="no-scaled-link" src="../_images/matrix-form.png" style="width: 400px;"/></p>
 </center><p>Or, it could be instead implemented via a for loop, in which the case of large input signals, would not require storing a large matrix:</p>
 <div class="nbinput nblast docutils container">
 <div class="prompt highlight-none notranslate"><div class="highlight"><pre><span></span>[1]:

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diff --git a/plot_directive/api/opt-solver-1.pdf b/plot_directive/api/opt-solver-1.pdf
diff --git a/plot_directive/api/opt-solver-2.pdf b/plot_directive/api/opt-solver-2.pdf
diff --git a/plot_directive/api/util-1.pdf b/plot_directive/api/util-1.pdf
diff --git a/plot_directive/api/util-2.pdf b/plot_directive/api/util-2.pdf