Deploying to gh-pages from @ bdbf320 🚀

Author: lucascolley

generated/array_api_extra.broadcast_shapes.html

@@ -282,7 +282,7 @@ <h1>array_api_extra.broadcast_shapes<a class="headerlink" href="#array-api-extra
 <dt class="sig sig-object py" id="array_api_extra.broadcast_shapes">
 <span class="sig-prename descclassname"><span class="pre">array_api_extra.</span></span><span class="sig-name descname"><span class="pre">broadcast_shapes</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">shapes</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#array_api_extra.broadcast_shapes" title="Link to this definition">¶</a></dt>
 <dd><p>Compute the shape of the broadcasted arrays.</p>
-<p>Duplicates <a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.broadcast_shapes.html#numpy.broadcast_shapes" title="(in NumPy v2.3)"><code class="xref py py-func docutils literal notranslate"><span class="pre">numpy.broadcast_shapes()</span></code></a>, with additional support for
+<p>Duplicates <a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.broadcast_shapes.html#numpy.broadcast_shapes" title="(in NumPy v2.4)"><code class="xref py py-func docutils literal notranslate"><span class="pre">numpy.broadcast_shapes()</span></code></a>, with additional support for
 None and NaN sizes.</p>
 <p>This is equivalent to <code class="docutils literal notranslate"><span class="pre">xp.broadcast_arrays(arr1,</span> <span class="pre">arr2,</span> <span class="pre">...)[0].shape</span></code>
 without needing to worry about the backend potentially deep copying
@@ -301,7 +301,7 @@ <h1>array_api_extra.broadcast_shapes<a class="headerlink" href="#array-api-extra
 <div class="admonition seealso">
 <p class="admonition-title">See also</p>
 <dl class="simple">
-<dt><a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.broadcast_shapes.html#numpy.broadcast_shapes" title="(in NumPy v2.3)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.broadcast_shapes</span></code></a></dt><dd><p>Equivalent NumPy function.</p>
+<dt><a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.broadcast_shapes.html#numpy.broadcast_shapes" title="(in NumPy v2.4)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.broadcast_shapes</span></code></a></dt><dd><p>Equivalent NumPy function.</p>
 </dd>
 <dt><a class="reference external" href="https://data-apis.org/array-api/draft/API_specification/generated/array_api.broadcast_arrays.html#array_api.broadcast_arrays" title="(in Python array API standard)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">array_api.broadcast_arrays</span></code></a></dt><dd><p>Function to broadcast actual arrays.</p>
 </dd>

generated/array_api_extra.lazy_apply.html

@@ -297,7 +297,7 @@ <h1>array_api_extra.lazy_apply<a class="headerlink" href="#array-api-extra-lazy-
 backend it may be executed more than once or never.</p>
 </p></li>
 <li><p><strong>*args</strong> (<em>Array</em><em> | </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a><em> | </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#complex" title="(in Python v3.14)"><em>complex</em></a><em> | </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.14)"><em>bool</em></a><em> | </em><em>None</em>) – <p>One or more Array API compliant arrays, Python scalars, or None’s.</p>
-<p>If <cite>as_numpy=True</cite>, you need to be able to apply <a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.asarray.html#numpy.asarray" title="(in NumPy v2.3)"><code class="xref py py-func docutils literal notranslate"><span class="pre">numpy.asarray()</span></code></a> to
+<p>If <cite>as_numpy=True</cite>, you need to be able to apply <a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.asarray.html#numpy.asarray" title="(in NumPy v2.4)"><code class="xref py py-func docutils literal notranslate"><span class="pre">numpy.asarray()</span></code></a> to
 non-None args to convert them to NumPy; read notes below about specific
 backends.</p>
 </p></li>
@@ -349,7 +349,7 @@ <h1>array_api_extra.lazy_apply<a class="headerlink" href="#array-api-extra-lazy-
 arrays on a GPU device to NumPy.</p>
 </dd>
 <dt>Sparse</dt><dd><p>If <code class="docutils literal notranslate"><span class="pre">as_numpy=True</span></code>, by default sparse prevents implicit densification through
-<a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.asarray.html#numpy.asarray" title="(in NumPy v2.3)"><code class="xref py py-func docutils literal notranslate"><span class="pre">numpy.asarray()</span></code></a>. <a class="reference external" href="https://sparse.pydata.org/en/stable/operations.html#package-configuration">This safety mechanism can be disabled</a>.</p>
+<a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.asarray.html#numpy.asarray" title="(in NumPy v2.4)"><code class="xref py py-func docutils literal notranslate"><span class="pre">numpy.asarray()</span></code></a>. <a class="reference external" href="https://sparse.pydata.org/en/stable/operations.html#package-configuration">This safety mechanism can be disabled</a>.</p>
 </dd>
 <dt>Dask</dt><dd><p>This allows applying eager functions to Dask arrays.
 The Dask graph won’t be computed until the user calls <code class="docutils literal notranslate"><span class="pre">compute()</span></code> or