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Expand Down Expand Up @@ -373,18 +373,53 @@ <h1>Source code for dpnp.dpnp_iface_linearalgebra</h1><div class="highlight"><pr
<span class="n">order</span><span class="o">=</span><span class="s2">&quot;K&quot;</span><span class="p">,</span>
<span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">subok</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
<span class="n">signature</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">extobj</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">axes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="p">):</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Matrix product of two arrays.</span>

<span class="sd"> For full documentation refer to :obj:`numpy.matmul`.</span>

<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> x1 : {dpnp_array, usm_ndarray}</span>
<span class="sd"> First input array.</span>
<span class="sd"> x2 : {dpnp_array, usm_ndarray}</span>
<span class="sd"> Second input array.</span>
<span class="sd"> out : {dpnp.ndarray, usm_ndarray}, optional</span>
<span class="sd"> Alternative output array in which to place the result. It must have</span>
<span class="sd"> a shape that matches the signature `(n,k),(k,m)-&gt;(n,m)` but the type</span>
<span class="sd"> (of the calculated values) will be cast if necessary. Default: ``None``.</span>
<span class="sd"> dtype : dtype, optional</span>
<span class="sd"> Type to use in computing the matrix product. By default, the returned</span>
<span class="sd"> array will have data type that is determined by considering</span>
<span class="sd"> Promotion Type Rule and device capabilities.</span>
<span class="sd"> casting : {&#39;no&#39;, &#39;equiv&#39;, &#39;safe&#39;, &#39;same_kind&#39;, &#39;unsafe&#39;}, optional</span>
<span class="sd"> Controls what kind of data casting may occur. Default: ``&quot;same_kind&quot;``.</span>
<span class="sd"> order : {&quot;C&quot;, &quot;F&quot;, &quot;A&quot;, &quot;K&quot;, None}, optional</span>
<span class="sd"> Memory layout of the newly output array, if parameter `out` is ``None``.</span>
<span class="sd"> Default: &quot;K&quot;.</span>
<span class="sd"> axes : list of tuples, optional</span>
<span class="sd"> A list of tuples with indices of axes the matrix product should operate on.</span>
<span class="sd"> For instance, for the signature of ``(i,j),(j,k)-&gt;(i,k)``, the base elements</span>
<span class="sd"> are 2d matrices and these are taken to be stored in the two last axes of each</span>
<span class="sd"> argument. The corresponding axes keyword would be [(-2, -1), (-2, -1), (-2, -1)].</span>
<span class="sd"> Default: ``None``.</span>

<span class="sd"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> out : dpnp.ndarray</span>
<span class="sd"> Returns the matrix product of the inputs.</span>
<span class="sd"> This is a 0-d array only when both `x1`, `x2` are 1-d vectors.</span>

<span class="sd"> Limitations</span>
<span class="sd"> -----------</span>
<span class="sd"> Input arrays and parameter `out` are supported as either :class:`dpnp.ndarray`</span>
<span class="sd"> or :class:`dpctl.tensor.usm_ndarray`.</span>
<span class="sd"> Keyword argument `subok` is currently unsupported.</span>
<span class="sd"> Input array data types are limited by supported DPNP :ref:`Data types`.</span>
<span class="sd"> Keyword arguments `subok`, `signature`, `extobj`, and `axis` are</span>
<span class="sd"> only supported with their default value.</span>
<span class="sd"> Otherwise ``NotImplementedError`` exception will be raised.</span>

<span class="sd"> See Also</span>
<span class="sd"> --------</span>
Expand Down Expand Up @@ -445,6 +480,18 @@ <h1>Source code for dpnp.dpnp_iface_linearalgebra</h1><div class="highlight"><pr
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span>
<span class="s2">&quot;subok keyword argument is only supported by its default value.&quot;</span>
<span class="p">)</span>
<span class="k">elif</span> <span class="n">signature</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span>
<span class="s2">&quot;signature keyword argument is only supported by its default value.&quot;</span>
<span class="p">)</span>
<span class="k">elif</span> <span class="n">extobj</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span>
<span class="s2">&quot;extobj keyword argument is only supported by its default value.&quot;</span>
<span class="p">)</span>
<span class="k">elif</span> <span class="n">axis</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span>
<span class="s2">&quot;axis keyword argument is only supported by its default value.&quot;</span>
<span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">dpnp_matmul</span><span class="p">(</span>
<span class="n">x1</span><span class="p">,</span>
Expand All @@ -453,6 +500,7 @@ <h1>Source code for dpnp.dpnp_iface_linearalgebra</h1><div class="highlight"><pr
<span class="n">casting</span><span class="o">=</span><span class="n">casting</span><span class="p">,</span>
<span class="n">order</span><span class="o">=</span><span class="n">order</span><span class="p">,</span>
<span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span>
<span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span>
<span class="p">)</span></div>


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