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<h1>torch.randn_like<a class="headerlink" href="#torch-randn-like" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="torch.randn_like">
<code class="sig-prename descclassname">torch.</code><code class="sig-name descname">randn_like</code><span class="sig-paren">(</span><em class="sig-param">input</em>, <em class="sig-param">*</em>, <em class="sig-param">dtype=None</em>, <em class="sig-param">layout=None</em>, <em class="sig-param">device=None</em>, <em class="sig-param">requires_grad=False</em>, <em class="sig-param">memory_format=torch.preserve_format</em><span class="sig-paren">)</span> → Tensor<a class="headerlink" href="#torch.randn_like" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a tensor with the same size as <code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code> that is filled with
random numbers from a normal distribution with mean 0 and variance 1.
<code class="docutils literal notranslate"><span class="pre">torch.randn_like(input)</span></code> is equivalent to
<code class="docutils literal notranslate"><span class="pre">torch.randn(input.size(),</span> <span class="pre">dtype=input.dtype,</span> <span class="pre">layout=input.layout,</span> <span class="pre">device=input.device)</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>input</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a>) – the size of <code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code> will determine size of the output tensor.</p>
</dd>
<dt class="field-even">Keyword Arguments</dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>dtype</strong> (<a class="reference internal" href="../tensor_attributes.html#torch.torch.dtype" title="torch.torch.dtype"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.dtype</span></code></a>, optional) – the desired data type of returned Tensor.
Default: if <code class="docutils literal notranslate"><span class="pre">None</span></code>, defaults to the dtype of <code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code>.</p></li>
<li><p><strong>layout</strong> (<a class="reference internal" href="../tensor_attributes.html#torch.torch.layout" title="torch.torch.layout"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.layout</span></code></a>, optional) – the desired layout of returned tensor.
Default: if <code class="docutils literal notranslate"><span class="pre">None</span></code>, defaults to the layout of <code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code>.</p></li>
<li><p><strong>device</strong> (<a class="reference internal" href="../tensor_attributes.html#torch.torch.device" title="torch.torch.device"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.device</span></code></a>, optional) – the desired device of returned tensor.
Default: if <code class="docutils literal notranslate"><span class="pre">None</span></code>, defaults to the device of <code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code>.</p></li>
<li><p><strong>requires_grad</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.9)"><em>bool</em></a><em>, </em><em>optional</em>) – If autograd should record operations on the
returned tensor. Default: <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p></li>
<li><p><strong>memory_format</strong> (<a class="reference internal" href="../tensor_attributes.html#torch.torch.memory_format" title="torch.torch.memory_format"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.memory_format</span></code></a>, optional) – the desired memory format of
returned Tensor. Default: <code class="docutils literal notranslate"><span class="pre">torch.preserve_format</span></code>.</p></li>
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