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<h1>torch.Tensor.bernoulli<a class="headerlink" href="#torch-tensor-bernoulli" title="Permalink to this headline">¶</a></h1>
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<dt id="torch.Tensor.bernoulli">
<code class="sig-prename descclassname">Tensor.</code><code class="sig-name descname">bernoulli</code><span class="sig-paren">(</span><em class="sig-param">*</em>, <em class="sig-param">generator=None</em><span class="sig-paren">)</span> → Tensor<a class="headerlink" href="#torch.Tensor.bernoulli" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a result tensor where each <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext mathvariant="monospace">result[i]</mtext></mrow><annotation encoding="application/x-tex">\texttt{result[i]}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.77777em;vertical-align:-0.08333em;"></span><span class="mord text"><span class="mord texttt">result[i]</span></span></span></span></span></span> is independently
sampled from <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext>Bernoulli</mtext><mo stretchy="false">(</mo><mtext mathvariant="monospace">self[i]</mtext><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">\text{Bernoulli}(\texttt{self[i]})</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord text"><span class="mord">Bernoulli</span></span><span class="mopen">(</span><span class="mord text"><span class="mord texttt">self[i]</span></span><span class="mclose">)</span></span></span></span></span>. <code class="xref py py-attr docutils literal notranslate"><span class="pre">self</span></code> must have
floating point <code class="docutils literal notranslate"><span class="pre">dtype</span></code>, and the result will have the same <code class="docutils literal notranslate"><span class="pre">dtype</span></code>.</p>
<p>See <a class="reference internal" href="torch.bernoulli.html#torch.bernoulli" title="torch.bernoulli"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.bernoulli()</span></code></a></p>
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