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<div class="section" id="torch-amin">
<h1>torch.amin<a class="headerlink" href="#torch-amin" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="torch.amin">
<code class="sig-prename descclassname">torch.</code><code class="sig-name descname">amin</code><span class="sig-paren">(</span><em class="sig-param">input</em>, <em class="sig-param">dim</em>, <em class="sig-param">keepdim=False</em>, <em class="sig-param">*</em>, <em class="sig-param">out=None</em><span class="sig-paren">)</span> → Tensor<a class="headerlink" href="#torch.amin" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns the minimum value of each slice of the <code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code> tensor in the given
dimension(s) <code class="xref py py-attr docutils literal notranslate"><span class="pre">dim</span></code>.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<dl class="simple">
<dt>The difference between <code class="docutils literal notranslate"><span class="pre">max</span></code>/<code class="docutils literal notranslate"><span class="pre">min</span></code> and <code class="docutils literal notranslate"><span class="pre">amax</span></code>/<code class="docutils literal notranslate"><span class="pre">amin</span></code> is:</dt><dd><ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">amax</span></code>/<code class="docutils literal notranslate"><span class="pre">amin</span></code> supports reducing on multiple dimensions,</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">amax</span></code>/<code class="docutils literal notranslate"><span class="pre">amin</span></code> does not return indices,</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">amax</span></code>/<code class="docutils literal notranslate"><span class="pre">amin</span></code> evenly distributes gradient between equal values,
while <code class="docutils literal notranslate"><span class="pre">max(dim)</span></code>/<code class="docutils literal notranslate"><span class="pre">min(dim)</span></code> propagates gradient only to a single
index in the source tensor.</p></li>
</ul>
</dd>
</dl>
</div>
<p>If <code class="xref py py-attr docutils literal notranslate"><span class="pre">keepdim</span></code> is <code class="docutils literal notranslate"><span class="pre">True</span></code>, the output tensors are of the same size as
<code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code> except in the dimension(s) <code class="xref py py-attr docutils literal notranslate"><span class="pre">dim</span></code> where they are of size 1.
Otherwise, <code class="xref py py-attr docutils literal notranslate"><span class="pre">dim`s</span> <span class="pre">are</span> <span class="pre">squeezed</span> <span class="pre">(see</span> <span class="pre">:func:`torch.squeeze</span></code>), resulting in
the output tensors having fewer dimensions than <code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code>.</p>
<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>dim</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> or </em><em>tuple of python:ints</em>) – the dimension or dimensions to reduce.</p></li>
<li><p><strong>keepdim</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.9)"><em>bool</em></a>) – whether the output tensor has <code class="xref py py-attr docutils literal notranslate"><span class="pre">dim</span></code> retained or not.</p></li>
</ul>
</dd>
<dt class="field-even">Keyword Arguments</dt>
<dd class="field-even"><p><strong>out</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a><em>, </em><em>optional</em>) – the output tensor.</p>
</dd>
</dl>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">a</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">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">a</span>
<span class="go">tensor([[ 0.6451, -0.4866, 0.2987, -1.3312],</span>
<span class="go"> [-0.5744, 1.2980, 1.8397, -0.2713],</span>
<span class="go"> [ 0.9128, 0.9214, -1.7268, -0.2995],</span>
<span class="go"> [ 0.9023, 0.4853, 0.9075, -1.6165]])</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">amin</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="go">tensor([-1.3312, -0.5744, -1.7268, -1.6165])</span>
</pre></div>
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</dd></dl>
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