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<div class="section" id="torch-addcdiv">
<h1>torch.addcdiv<a class="headerlink" href="#torch-addcdiv" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="torch.addcdiv">
<code class="sig-prename descclassname">torch.</code><code class="sig-name descname">addcdiv</code><span class="sig-paren">(</span><em class="sig-param">input</em>, <em class="sig-param">tensor1</em>, <em class="sig-param">tensor2</em>, <em class="sig-param">*</em>, <em class="sig-param">value=1</em>, <em class="sig-param">out=None</em><span class="sig-paren">)</span> → Tensor<a class="headerlink" href="#torch.addcdiv" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs the element-wise division of <code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor1</span></code> by <code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor2</span></code>,
multiply the result by the scalar <code class="xref py py-attr docutils literal notranslate"><span class="pre">value</span></code> and add it to <code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code>.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>Integer division with addcdiv is no longer supported, and in a future release
addcdiv will perform a true division of <code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor1</span></code> and <code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor2</span></code>.
The historic addcdiv behavior can be implemented using <a class="reference internal" href="torch.floor_divide.html#torch.floor_divide" title="torch.floor_divide"><code class="xref py py-func docutils literal notranslate"><span class="pre">floor_divide()</span></code></a>
for integral inputs
(<code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code> + <code class="xref py py-attr docutils literal notranslate"><span class="pre">value</span></code> * <code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor1</span></code> // <code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor2</span></code>)
and <a class="reference internal" href="torch.div.html#torch.div" title="torch.div"><code class="xref py py-func docutils literal notranslate"><span class="pre">div()</span></code></a> for float inputs
(<code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code> + <code class="xref py py-attr docutils literal notranslate"><span class="pre">value</span></code> * <code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor1</span></code> / <code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor2</span></code>).
The future addcdiv behavior can be implemented with <a class="reference internal" href="torch.true_divide.html#torch.true_divide" title="torch.true_divide"><code class="xref py py-func docutils literal notranslate"><span class="pre">true_divide()</span></code></a>
(<code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code> + <code class="xref py py-attr docutils literal notranslate"><span class="pre">value</span></code> * torch.true_divide(<code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor1</span></code>,
<code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor2</span></code>).</p>
</div>
<div class="math">
<span class="katex-display"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block"><semantics><mrow><msub><mtext>out</mtext><mi>i</mi></msub><mo>=</mo><msub><mtext>input</mtext><mi>i</mi></msub><mo>+</mo><mtext>value</mtext><mo>×</mo><mfrac><msub><mtext>tensor1</mtext><mi>i</mi></msub><msub><mtext>tensor2</mtext><mi>i</mi></msub></mfrac></mrow><annotation encoding="application/x-tex">\text{out}_i = \text{input}_i + \text{value} \times \frac{\text{tensor1}_i}{\text{tensor2}_i}
</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.76508em;vertical-align:-0.15em;"></span><span class="mord"><span class="mord text"><span class="mord">out</span></span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.31166399999999994em;"><span style="top:-2.5500000000000003em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight">i</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2777777777777778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:0.912em;vertical-align:-0.24414em;"></span><span class="mord"><span class="mord text"><span class="mord">input</span></span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.21752399999999997em;"><span style="top:-2.4558600000000004em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight">i</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.24414em;"><span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.77777em;vertical-align:-0.08333em;"></span><span class="mord text"><span class="mord">value</span></span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:2.1574400000000002em;vertical-align:-0.8360000000000001em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.32144em;"><span style="top:-2.3139999999999996em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord"><span class="mord text"><span class="mord">tensor2</span></span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.31166399999999994em;"><span style="top:-2.5500000000000003em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight">i</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord"><span class="mord text"><span class="mord">tensor1</span></span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.31166399999999994em;"><span style="top:-2.5500000000000003em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight">i</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.8360000000000001em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span></span></span></span></span>
</div><p>The shapes of <code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code>, <code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor1</span></code>, and <code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor2</span></code> must be
<a class="reference internal" href="../notes/broadcasting.html#broadcasting-semantics"><span class="std std-ref">broadcastable</span></a>.</p>
<p>For inputs of type <cite>FloatTensor</cite> or <cite>DoubleTensor</cite>, <code class="xref py py-attr docutils literal notranslate"><span class="pre">value</span></code> must be
a real number, otherwise an integer.</p>
<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>) – the tensor to be added</p></li>
<li><p><strong>tensor1</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a>) – the numerator tensor</p></li>
<li><p><strong>tensor2</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a>) – the denominator tensor</p></li>
<li><p><strong>value</strong> (<em>Number</em><em>, </em><em>optional</em>) – multiplier for <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext>tensor1</mtext><mi mathvariant="normal">/</mi><mtext>tensor2</mtext></mrow><annotation encoding="application/x-tex">\text{tensor1} / \text{tensor2}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord text"><span class="mord">tensor1</span></span><span class="mord">/</span><span class="mord text"><span class="mord">tensor2</span></span></span></span></span>
</span></p></li>
<li><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></li>
</ul>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">t</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">t1</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">t2</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">addcdiv</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">t1</span><span class="p">,</span> <span class="n">t2</span><span class="p">,</span> <span class="n">value</span><span class="o">=</span><span class="mf">0.1</span><span class="p">)</span>
<span class="go">tensor([[-0.2312, -3.6496, 0.1312],</span>
<span class="go"> [-1.0428, 3.4292, -0.1030],</span>
<span class="go"> [-0.5369, -0.9829, 0.0430]])</span>
</pre></div>
</div>
</dd></dl>
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