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<h1>torch.Tensor.add<a class="headerlink" href="#torch-tensor-add" title="Permalink to this heading">¶</a></h1>
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<span class="sig-prename descclassname"><span class="pre">Tensor.</span></span><span class="sig-name descname"><span class="pre">add</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">other</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><span class="pre">Tensor</span></a></span></span><a class="headerlink" href="#torch.Tensor.add" title="Permalink to this definition">¶</a></dt>
<dd><p>Add a scalar or tensor to <code class="xref py py-attr docutils literal notranslate"><span class="pre">self</span></code> tensor. If both <code class="xref py py-attr docutils literal notranslate"><span class="pre">alpha</span></code>
and <code class="xref py py-attr docutils literal notranslate"><span class="pre">other</span></code> are specified, each element of <code class="xref py py-attr docutils literal notranslate"><span class="pre">other</span></code> is scaled by
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<p>When <code class="xref py py-attr docutils literal notranslate"><span class="pre">other</span></code> is a tensor, the shape of <code class="xref py py-attr docutils literal notranslate"><span class="pre">other</span></code> must be
<a class="reference internal" href="../notes/broadcasting.html#broadcasting-semantics"><span class="std std-ref">broadcastable</span></a> with the shape of the underlying
tensor</p>
<p>See <a class="reference internal" href="torch.add.html#torch.add" title="torch.add"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.add()</span></code></a></p>
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