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<div class="section" id="torch-tensor-repeat">
<h1>torch.Tensor.repeat<a class="headerlink" href="#torch-tensor-repeat" title="Permalink to this headline">¶</a></h1>
<dl class="py method">
<dt id="torch.Tensor.repeat">
<code class="sig-prename descclassname"><span class="pre">Tensor.</span></code><code class="sig-name descname"><span class="pre">repeat</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">sizes</span></span></em><span class="sig-paren">)</span> → <a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><span class="pre">Tensor</span></a><a class="headerlink" href="#torch.Tensor.repeat" title="Permalink to this definition">¶</a></dt>
<dd><p>Repeats this tensor along the specified dimensions.</p>
<p>Unlike <a class="reference internal" href="torch.Tensor.expand.html#torch.Tensor.expand" title="torch.Tensor.expand"><code class="xref py py-meth docutils literal notranslate"><span class="pre">expand()</span></code></a>, this function copies the tensor’s data.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p><a class="reference internal" href="#torch.Tensor.repeat" title="torch.Tensor.repeat"><code class="xref py py-meth docutils literal notranslate"><span class="pre">repeat()</span></code></a> behaves differently from
<a class="reference external" href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.repeat.html">numpy.repeat</a>,
but is more similar to
<a class="reference external" href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.tile.html">numpy.tile</a>.
For the operator similar to <cite>numpy.repeat</cite>, see <a class="reference internal" href="torch.repeat_interleave.html#torch.repeat_interleave" title="torch.repeat_interleave"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.repeat_interleave()</span></code></a>.</p>
</div>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>sizes</strong> (<em>torch.Size</em><em> or </em><em>int...</em>) – The number of times to repeat this tensor along each
dimension</p>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">x</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="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">repeat</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
<span class="go">tensor([[ 1, 2, 3, 1, 2, 3],</span>
<span class="go"> [ 1, 2, 3, 1, 2, 3],</span>
<span class="go"> [ 1, 2, 3, 1, 2, 3],</span>
<span class="go"> [ 1, 2, 3, 1, 2, 3]])</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">repeat</span><span class="p">(</span><span class="mi">4</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="o">.</span><span class="n">size</span><span class="p">()</span>
<span class="go">torch.Size([4, 2, 3])</span>
</pre></div>
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