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<div class="section" id="torch-tensor-unfold">
<h1>torch.Tensor.unfold<a class="headerlink" href="#torch-tensor-unfold" title="Permalink to this headline">¶</a></h1>
<dl class="py method">
<dt id="torch.Tensor.unfold">
<code class="sig-prename descclassname"><span class="pre">Tensor.</span></code><code class="sig-name descname"><span class="pre">unfold</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dimension</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">step</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.unfold" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a view of the original tensor which contains all slices of size <a class="reference internal" href="torch.Tensor.size.html#torch.Tensor.size" title="torch.Tensor.size"><code class="xref py py-attr docutils literal notranslate"><span class="pre">size</span></code></a> from
<code class="xref py py-attr docutils literal notranslate"><span class="pre">self</span></code> tensor in the dimension <code class="xref py py-attr docutils literal notranslate"><span class="pre">dimension</span></code>.</p>
<p>Step between two slices is given by <code class="xref py py-attr docutils literal notranslate"><span class="pre">step</span></code>.</p>
<p>If <cite>sizedim</cite> is the size of dimension <code class="xref py py-attr docutils literal notranslate"><span class="pre">dimension</span></code> for <code class="xref py py-attr docutils literal notranslate"><span class="pre">self</span></code>, the size of
dimension <code class="xref py py-attr docutils literal notranslate"><span class="pre">dimension</span></code> in the returned tensor will be
<cite>(sizedim - size) / step + 1</cite>.</p>
<p>An additional dimension of size <a class="reference internal" href="torch.Tensor.size.html#torch.Tensor.size" title="torch.Tensor.size"><code class="xref py py-attr docutils literal notranslate"><span class="pre">size</span></code></a> is appended in the returned tensor.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>dimension</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) – dimension in which unfolding happens</p></li>
<li><p><strong>size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) – the size of each slice that is unfolded</p></li>
<li><p><strong>step</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) – the step between each slice</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">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mf">1.</span><span class="p">,</span> <span class="mi">8</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">x</span>
<span class="go">tensor([ 1., 2., 3., 4., 5., 6., 7.])</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">unfold</span><span class="p">(</span><span class="mi">0</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([[ 1., 2.],</span>
<span class="go"> [ 2., 3.],</span>
<span class="go"> [ 3., 4.],</span>
<span class="go"> [ 4., 5.],</span>
<span class="go"> [ 5., 6.],</span>
<span class="go"> [ 6., 7.]])</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">unfold</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
<span class="go">tensor([[ 1., 2.],</span>
<span class="go"> [ 3., 4.],</span>
<span class="go"> [ 5., 6.]])</span>
</pre></div>
</div>
</dd></dl>
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