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<div class="section" id="torch-as-strided">
<h1>torch.as_strided<a class="headerlink" href="#torch-as-strided" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="torch.as_strided">
<code class="sig-prename descclassname">torch.</code><code class="sig-name descname">as_strided</code><span class="sig-paren">(</span><em class="sig-param">input</em>, <em class="sig-param">size</em>, <em class="sig-param">stride</em>, <em class="sig-param">storage_offset=0</em><span class="sig-paren">)</span> → Tensor<a class="headerlink" href="#torch.as_strided" title="Permalink to this definition">¶</a></dt>
<dd><p>Create a view of an existing <cite>torch.Tensor</cite> <code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code> with specified
<code class="xref py py-attr docutils literal notranslate"><span class="pre">size</span></code>, <code class="xref py py-attr docutils literal notranslate"><span class="pre">stride</span></code> and <code class="xref py py-attr docutils literal notranslate"><span class="pre">storage_offset</span></code>.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>More than one element of a created tensor may refer to a single memory
location. As a result, in-place operations (especially ones that are
vectorized) may result in incorrect behavior. If you need to write to
the tensors, please clone them first.</p>
<p>Many PyTorch functions, which return a view of a tensor, are internally
implemented with this function. Those functions, like
<a class="reference internal" href="../tensors.html#torch.Tensor.expand" title="torch.Tensor.expand"><code class="xref py py-meth docutils literal notranslate"><span class="pre">torch.Tensor.expand()</span></code></a>, are easier to read and are therefore more
advisable to use.</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>) – the input tensor.</p></li>
<li><p><strong>size</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.9)"><em>tuple</em></a><em> or </em><em>ints</em>) – the shape of the output tensor</p></li>
<li><p><strong>stride</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.9)"><em>tuple</em></a><em> or </em><em>ints</em>) – the stride of the output tensor</p></li>
<li><p><strong>storage_offset</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)"><em>int</em></a><em>, </em><em>optional</em>) – the offset in the underlying storage of 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">x</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">3</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">x</span>
<span class="go">tensor([[ 0.9039, 0.6291, 1.0795],</span>
<span class="go"> [ 0.1586, 2.1939, -0.4900],</span>
<span class="go"> [-0.1909, -0.7503, 1.9355]])</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">as_strided</span><span class="p">(</span><span class="n">x</span><span class="p">,</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="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">))</span>
<span class="gp">>>> </span><span class="n">t</span>
<span class="go">tensor([[0.9039, 1.0795],</span>
<span class="go"> [0.6291, 0.1586]])</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">as_strided</span><span class="p">(</span><span class="n">x</span><span class="p">,</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="p">(</span><span class="mi">1</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([[0.6291, 0.1586],</span>
<span class="go"> [1.0795, 2.1939]])</span>
</pre></div>
</div>
</dd></dl>
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