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<div class="section" id="torch-vdot">
<h1>torch.vdot<a class="headerlink" href="#torch-vdot" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="torch.vdot">
<code class="sig-prename descclassname">torch.</code><code class="sig-name descname">vdot</code><span class="sig-paren">(</span><em class="sig-param">input</em>, <em class="sig-param">other</em>, <em class="sig-param">*</em>, <em class="sig-param">out=None</em><span class="sig-paren">)</span> → Tensor<a class="headerlink" href="#torch.vdot" title="Permalink to this definition">¶</a></dt>
<dd><p>Computes the dot product (inner product) of two tensors. The vdot(a, b) function
handles complex numbers differently than dot(a, b). If the first argument is complex,
the complex conjugate of the first argument is used for the calculation of the dot product.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>This function does not <a class="reference internal" href="../notes/broadcasting.html#broadcasting-semantics"><span class="std std-ref">broadcast</span></a>.</p>
</div>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>input</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a>) – first tensor in the dot product. Its conjugate is used if it’s complex.</p></li>
<li><p><strong>other</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a>) – second tensor in the dot product.</p></li>
</ul>
</dd>
<dt class="field-even">Keyword Arguments</dt>
<dd class="field-even"><p><strong>out</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a><em>, </em><em>optional</em>) – the output tensor.</p>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">vdot</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">]),</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">]))</span>
<span class="go">tensor(7)</span>
<span class="gp">>>> </span><span class="n">a</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">((</span><span class="mi">1</span> <span class="o">+</span><span class="mi">2</span><span class="n">j</span><span class="p">,</span> <span class="mi">3</span> <span class="o">-</span> <span class="mi">1</span><span class="n">j</span><span class="p">))</span>
<span class="gp">>>> </span><span class="n">b</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">((</span><span class="mi">2</span> <span class="o">+</span><span class="mi">1</span><span class="n">j</span><span class="p">,</span> <span class="mi">4</span> <span class="o">-</span> <span class="mi">0</span><span class="n">j</span><span class="p">))</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">vdot</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span>
<span class="go">tensor([16.+1.j])</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">vdot</span><span class="p">(</span><span class="n">b</span><span class="p">,</span> <span class="n">a</span><span class="p">)</span>
<span class="go">tensor([16.-1.j])</span>
</pre></div>
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