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Philippe Tillet
2021-09-14 00:21:56 +00:00
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Computation times
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<p>Note that, if llvm-11 is not present on your system, the setup.py script will download the official LLVM11 static libraries link against that.</p>
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getting-started/tutorials/04-low-memory-dropout.html
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@@ -370,7 +370,7 @@ to explore the <cite>triton/language/random</cite> folder!</p>
<dd><p>Nitish Srivastava and Geoffrey Hinton and Alex Krizhevsky and Ilya Sutskever and Ruslan Salakhutdinov, “Dropout: A Simple Way to Prevent Neural Networks from Overfitting”, JMLR 2014</p>
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<h1>triton.testing.do_bench<a class="headerlink" href="#triton-testing-do-bench" title="Permalink to this headline"></a></h1>
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<dt class="sig sig-object py" id="triton.testing.do_bench">
<span class="sig-prename descclassname"><span class="pre">triton.testing.</span></span><span class="sig-name descname"><span class="pre">do_bench</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fn</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">warmup</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rep</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grad_to_none</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percentiles</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[0.2,</span> <span class="pre">0.8]</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#triton.testing.do_bench" title="Permalink to this definition"></a></dt>
<span class="sig-prename descclassname"><span class="pre">triton.testing.</span></span><span class="sig-name descname"><span class="pre">do_bench</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fn</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">warmup</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rep</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">grad_to_none</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percentiles</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[0.2,</span> <span class="pre">0.8]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">record_clocks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#triton.testing.do_bench" title="Permalink to this definition"></a></dt>
<dd><p>Benchmark the runtime of the provided function. By default, return the median runtime of <code class="code docutils literal notranslate"><span class="pre">fn</span></code> along with
the 20-th and 80-th performance percentile.</p>
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