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<div class="section" id="torch-count-nonzero">
<h1>torch.count_nonzero<a class="headerlink" href="#torch-count-nonzero" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="torch.count_nonzero">
<code class="sig-prename descclassname">torch.</code><code class="sig-name descname">count_nonzero</code><span class="sig-paren">(</span><em class="sig-param">input</em>, <em class="sig-param">dim=None</em><span class="sig-paren">)</span> → Tensor<a class="headerlink" href="#torch.count_nonzero" title="Permalink to this definition">¶</a></dt>
<dd><p>Counts the number of non-zero values in the tensor <code class="xref py py-attr docutils literal notranslate"><span class="pre">input</span></code> along the given <code class="xref py py-attr docutils literal notranslate"><span class="pre">dim</span></code>.
If no dim is specified then all non-zeros in the tensor are counted.</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><em>, </em><em>optional</em>) – Dim or tuple of dims along which to count non-zeros.</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">zeros</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="p">[</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="o">></span> <span class="mf">0.5</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
<span class="gp">>>> </span><span class="n">x</span>
<span class="go">tensor([[0., 1., 1.],</span>
<span class="go"> [0., 0., 0.],</span>
<span class="go"> [0., 0., 1.]])</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">count_nonzero</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="go">tensor(3)</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">count_nonzero</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="go">tensor([0, 1, 2])</span>
</pre></div>
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