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<div class="section" id="torchvision-utils">
<h1>torchvision.utils<a class="headerlink" href="#torchvision-utils" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="torchvision.utils.make_grid">
<code class="descclassname">torchvision.utils.</code><code class="descname">make_grid</code><span class="sig-paren">(</span><em>tensor</em>, <em>nrow=8</em>, <em>padding=2</em>, <em>normalize=False</em>, <em>range=None</em>, <em>scale_each=False</em>, <em>pad_value=0</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torchvision/utils.html#make_grid"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torchvision.utils.make_grid" title="Permalink to this definition">¶</a></dt>
<dd><p>Make a grid of images.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>tensor</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.7)"><em>list</em></a>) – 4D mini-batch Tensor of shape (B x C x H x W)
or a list of images all of the same size.</li>
<li><strong>nrow</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a><em>, </em><em>optional</em>) – Number of images displayed in each row of the grid.
The Final grid size is (B / nrow, nrow). Default is 8.</li>
<li><strong>padding</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a><em>, </em><em>optional</em>) – amount of padding. Default is 2.</li>
<li><strong>normalize</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.7)"><em>bool</em></a><em>, </em><em>optional</em>) – If True, shift the image to the range (0, 1),
by subtracting the minimum and dividing by the maximum pixel value.</li>
<li><strong>range</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.7)"><em>tuple</em></a><em>, </em><em>optional</em>) – tuple (min, max) where min and max are numbers,
then these numbers are used to normalize the image. By default, min and max
are computed from the tensor.</li>
<li><strong>scale_each</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.7)"><em>bool</em></a><em>, </em><em>optional</em>) – If True, scale each image in the batch of
images separately rather than the (min, max) over all images.</li>
<li><strong>pad_value</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.7)"><em>float</em></a><em>, </em><em>optional</em>) – Value for the padded pixels.</li>
</ul>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Example</p>
<p>See this notebook <a class="reference external" href="https://gist.github.com/anonymous/bf16430f7750c023141c562f3e9f2a91">here</a></p>
</dd></dl>
<dl class="function">
<dt id="torchvision.utils.save_image">
<code class="descclassname">torchvision.utils.</code><code class="descname">save_image</code><span class="sig-paren">(</span><em>tensor</em>, <em>filename</em>, <em>nrow=8</em>, <em>padding=2</em>, <em>normalize=False</em>, <em>range=None</em>, <em>scale_each=False</em>, <em>pad_value=0</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torchvision/utils.html#save_image"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torchvision.utils.save_image" title="Permalink to this definition">¶</a></dt>
<dd><p>Save a given Tensor into an image file.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>tensor</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.7)"><em>list</em></a>) – Image to be saved. If given a mini-batch tensor,
saves the tensor as a grid of images by calling <code class="docutils literal notranslate"><span class="pre">make_grid</span></code>.</li>
<li><strong>**kwargs</strong> – Other arguments are documented in <code class="docutils literal notranslate"><span class="pre">make_grid</span></code>.</li>
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