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_sources/getting-started/tutorials/01-vector-add.rst.txt
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_sources/getting-started/tutorials/02-fused-softmax.rst.txt
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_sources/getting-started/tutorials/03-matrix-multiplication.rst.txt
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_sources/getting-started/tutorials/sg_execution_times.rst.txt
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Computation times Computation times
================= =================
**03:51.756** total execution time for **getting-started_tutorials** files: **03:38.920** total execution time for **getting-started_tutorials** files:
+---------------------------------------------------------------------------------------------------------+-----------+--------+ +---------------------------------------------------------------------------------------------------------+-----------+--------+
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getting-started/tutorials/01-vector-add.html
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<p class="sphx-glr-script-out">Out:</p> <p class="sphx-glr-script-out">Out:</p>
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getting-started/tutorials/02-fused-softmax.html
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Note however that the PyTorch <cite>softmax</cite> operation is more general and will works on tensors of any shape.</p></li> Note however that the PyTorch <cite>softmax</cite> operation is more general and will works on tensors of any shape.</p></li>
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getting-started/tutorials/03-matrix-multiplication.html
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@@ -174,7 +174,7 @@
<div class="section" id="computation-times"> <div class="section" id="computation-times">
<span id="sphx-glr-getting-started-tutorials-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline"></a></h1> <span id="sphx-glr-getting-started-tutorials-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline"></a></h1>
<p><strong>03:51.756</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p> <p><strong>03:38.920</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<table class="docutils align-default"> <table class="docutils align-default">
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@@ -183,15 +183,15 @@
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<tr class="row-odd"><td><p><a class="reference internal" href="03-matrix-multiplication.html#sphx-glr-getting-started-tutorials-03-matrix-multiplication-py"><span class="std std-ref">Matrix Multiplication</span></a> (<code class="docutils literal notranslate"><span class="pre">03-matrix-multiplication.py</span></code>)</p></td> <tr class="row-odd"><td><p><a class="reference internal" href="03-matrix-multiplication.html#sphx-glr-getting-started-tutorials-03-matrix-multiplication-py"><span class="std std-ref">Matrix Multiplication</span></a> (<code class="docutils literal notranslate"><span class="pre">03-matrix-multiplication.py</span></code>)</p></td>
<td><p>02:27.957</p></td> <td><p>02:14.737</p></td>
<td><p>0.0 MB</p></td> <td><p>0.0 MB</p></td>
</tr> </tr>
<tr class="row-even"><td><p><a class="reference internal" href="02-fused-softmax.html#sphx-glr-getting-started-tutorials-02-fused-softmax-py"><span class="std std-ref">Fused Softmax</span></a> (<code class="docutils literal notranslate"><span class="pre">02-fused-softmax.py</span></code>)</p></td> <tr class="row-even"><td><p><a class="reference internal" href="02-fused-softmax.html#sphx-glr-getting-started-tutorials-02-fused-softmax-py"><span class="std std-ref">Fused Softmax</span></a> (<code class="docutils literal notranslate"><span class="pre">02-fused-softmax.py</span></code>)</p></td>
<td><p>01:12.770</p></td> <td><p>01:13.131</p></td>
<td><p>0.0 MB</p></td> <td><p>0.0 MB</p></td>
</tr> </tr>
<tr class="row-odd"><td><p><a class="reference internal" href="01-vector-add.html#sphx-glr-getting-started-tutorials-01-vector-add-py"><span class="std std-ref">Vector Addition</span></a> (<code class="docutils literal notranslate"><span class="pre">01-vector-add.py</span></code>)</p></td> <tr class="row-odd"><td><p><a class="reference internal" href="01-vector-add.html#sphx-glr-getting-started-tutorials-01-vector-add-py"><span class="std std-ref">Vector Addition</span></a> (<code class="docutils literal notranslate"><span class="pre">01-vector-add.py</span></code>)</p></td>
<td><p>00:11.028</p></td> <td><p>00:11.053</p></td>
<td><p>0.0 MB</p></td> <td><p>0.0 MB</p></td>
</tr> </tr>
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2
python-api/generated/triton.heuristics.html
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@@ -189,7 +189,7 @@
<span class="sig-prename descclassname"><span class="pre">triton.</span></span><span class="sig-name descname"><span class="pre">heuristics</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">values</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#triton.heuristics" title="Permalink to this definition"></a></dt> <span class="sig-prename descclassname"><span class="pre">triton.</span></span><span class="sig-name descname"><span class="pre">heuristics</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">values</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#triton.heuristics" title="Permalink to this definition"></a></dt>
<dd><p>Decorator for specifying how the values of certain meta-parameters may be computed. <dd><p>Decorator for specifying how the values of certain meta-parameters may be computed.
This is useful for cases where auto-tuning is prohibitevely expensive, or just not applicable.</p> This is useful for cases where auto-tuning is prohibitevely expensive, or just not applicable.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@heuristics</span><span class="p">(</span><span class="n">values</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;BLOCK_SIZE&#39;</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">args</span><span class="p">:</span> <span class="mi">2</span> <span class="o">**</span> <span class="nb">int</span><span class="p">(</span><span class="n">math</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="n">math</span><span class="o">.</span><span class="n">log2</span><span class="p">(</span><span class="n">args</span><span class="p">[</span><span class="mi">1</span><span class="p">])))})</span> <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@triton</span><span class="o">.</span><span class="n">heuristics</span><span class="p">(</span><span class="n">values</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;BLOCK_SIZE&#39;</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">args</span><span class="p">:</span> <span class="mi">2</span> <span class="o">**</span> <span class="nb">int</span><span class="p">(</span><span class="n">math</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="n">math</span><span class="o">.</span><span class="n">log2</span><span class="p">(</span><span class="n">args</span><span class="p">[</span><span class="mi">1</span><span class="p">])))})</span>
<span class="nd">@triton</span><span class="o">.</span><span class="n">jit</span> <span class="nd">@triton</span><span class="o">.</span><span class="n">jit</span>
<span class="k">def</span> <span class="nf">kernel</span><span class="p">(</span><span class="n">x_ptr</span><span class="p">,</span> <span class="n">x_size</span><span class="p">,</span> <span class="o">**</span><span class="n">META</span><span class="p">):</span> <span class="k">def</span> <span class="nf">kernel</span><span class="p">(</span><span class="n">x_ptr</span><span class="p">,</span> <span class="n">x_size</span><span class="p">,</span> <span class="o">**</span><span class="n">META</span><span class="p">):</span>
<span class="n">BLOCK_SIZE</span> <span class="o">=</span> <span class="n">META</span><span class="p">[</span><span class="s1">&#39;BLOCK_SIZE&#39;</span><span class="p">]</span> <span class="c1"># smallest power-of-two &gt;= x_size</span> <span class="n">BLOCK_SIZE</span> <span class="o">=</span> <span class="n">META</span><span class="p">[</span><span class="s1">&#39;BLOCK_SIZE&#39;</span><span class="p">]</span> <span class="c1"># smallest power-of-two &gt;= x_size</span>

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searchindex.js
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