[GH-PAGES] Updated website
This commit is contained in:
@@ -324,10 +324,10 @@ for different problem sizes.</p>
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@@ -339,7 +339,7 @@ for different problem sizes.</p>
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</pre></div>
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</div>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 40.240 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 41.226 seconds)</p>
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-01-vector-add-py">
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<div class="sphx-glr-download sphx-glr-download-python docutils container">
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<p><a class="reference download internal" download="" href="../../_downloads/62d97d49a32414049819dd8bb8378080/01-vector-add.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">01-vector-add.py</span></code></a></p>
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@@ -380,11 +380,11 @@ We will then compare its performance against (1) <code class="code docutils lite
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</pre></div>
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@@ -397,7 +397,7 @@ We will then compare its performance against (1) <code class="code docutils lite
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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>
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</ul>
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</div></blockquote>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 22.452 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 20.998 seconds)</p>
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-02-fused-softmax-py">
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<div class="sphx-glr-download sphx-glr-download-python docutils container">
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<p><a class="reference download internal" download="" href="../../_downloads/d91442ac2982c4e0cc3ab0f43534afbc/02-fused-softmax.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">02-fused-softmax.py</span></code></a></p>
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@@ -568,42 +568,42 @@ torch_output=tensor([[ 1.1045, -36.9688, 31.4688, ..., -11.3906, 24.4531, -3
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<p class="sphx-glr-script-out">Out:</p>
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<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>matmul-performance:
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M cuBLAS ... Triton Triton (+ LeakyReLU)
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5 896.0 39.025776 ... 40.140799 39.025776
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9 1408.0 64.138541 ... 67.305878 67.305878
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10 1536.0 80.430545 ... 79.526831 79.526831
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11 1664.0 63.372618 ... 62.492442 62.061463
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12 1792.0 72.983276 ... 72.047592 71.588687
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13 1920.0 69.120002 ... 70.172588 70.530615
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14 2048.0 73.908442 ... 77.314362 76.959706
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15 2176.0 83.500614 ... 85.998493 85.269692
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8 1280.0 51.200001 ... 56.888887 56.109587
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9 1408.0 64.138541 ... 67.305878 66.485074
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10 1536.0 80.430545 ... 79.526831 78.643199
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11 1664.0 62.929456 ... 62.061463 62.061463
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12 1792.0 72.512412 ... 72.047592 71.588687
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13 1920.0 69.120002 ... 70.530615 70.530615
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14 2048.0 73.908442 ... 76.959706 76.959706
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15 2176.0 83.500614 ... 86.367588 85.632545
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16 2304.0 68.251065 ... 76.809875 76.563695
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17 2432.0 71.305746 ... 85.134737 84.877538
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22 3072.0 81.825298 ... 88.542777 86.579673
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23 3200.0 79.701121 ... 91.822093 92.352095
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24 3328.0 80.707733 ... 84.895397 84.596116
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26 3584.0 85.633710 ... 91.610178 95.502274
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27 3712.0 84.372753 ... 87.170458 86.716441
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29 3968.0 92.372393 ... 89.068569 84.915752
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30 4096.0 91.553703 ... 83.468735 86.844210
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17 2432.0 71.305746 ... 85.393507 84.367759
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19 2688.0 83.737433 ... 89.254248 89.464755
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20 2816.0 82.759409 ... 82.916747 82.759409
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21 2944.0 81.967162 ... 82.373605 82.102191
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22 3072.0 80.316458 ... 84.197924 89.240511
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23 3200.0 84.880639 ... 95.952022 94.674553
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25 3456.0 81.849303 ... 91.097818 90.790053
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26 3584.0 84.865870 ... 87.211821 94.548254
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27 3712.0 85.455380 ... 86.192706 89.473662
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28 3840.0 80.197243 ... 89.839159 88.438226
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29 3968.0 85.810547 ... 84.214331 87.787005
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30 4096.0 92.820009 ... 93.206754 86.313653
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[31 rows x 5 columns]
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</div>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 24.923 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 21.530 seconds)</p>
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-03-matrix-multiplication-py">
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<div class="sphx-glr-download sphx-glr-download-python docutils container">
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<p><a class="reference download internal" download="" href="../../_downloads/d5fee5b55a64e47f1b5724ec39adf171/03-matrix-multiplication.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">03-matrix-multiplication.py</span></code></a></p>
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@@ -371,7 +371,7 @@ to explore the <cite>triton/language/random</cite> folder!</p>
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<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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</dd>
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</dl>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.012 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.011 seconds)</p>
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-04-low-memory-dropout-py">
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<div class="sphx-glr-download sphx-glr-download-python docutils container">
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<p><a class="reference download internal" download="" href="../../_downloads/c9aed78977a4c05741d675a38dde3d7d/04-low-memory-dropout.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">04-low-memory-dropout.py</span></code></a></p>
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|
@@ -194,36 +194,36 @@ to download the full example code</p>
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<p class="sphx-glr-script-out">Out:</p>
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<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>layer-norm-backward:
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N Triton Torch Apex
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4 3072.0 515.580429 191.501303 320.556515
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5 3584.0 554.941930 208.271186 309.410081
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0 1024.0 311.088617 99.096776 307.200008
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1 1536.0 351.085717 133.083026 338.201833
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2 2048.0 423.724127 161.684218 336.657521
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3 2560.0 461.954908 182.314537 328.556154
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4 3072.0 511.999982 191.501303 320.556515
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5 3584.0 554.941930 208.271186 308.301075
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6 4096.0 568.231237 220.412561 297.890900
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7 4608.0 498.162157 231.849059 287.251954
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8 5120.0 527.381977 242.845844 283.787523
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12 7168.0 505.976473 262.243907 288.644296
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13 7680.0 482.513091 260.338991 276.756754
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17 9728.0 438.857162 280.615388 288.950501
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22 12288.0 420.102570 254.673582 295.207195
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23 12800.0 415.696898 253.465340 288.180121
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24 13312.0 412.242569 252.959629 290.179836
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25 13824.0 405.098897 257.390218 292.829653
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19 10752.0 429.364408 246.464170 290.267711
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20 11264.0 429.786952 245.313973 285.767446
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21 11776.0 421.198220 249.447482 288.686414
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22 12288.0 420.102570 254.673582 294.911986
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23 12800.0 415.135142 253.674644 289.811310
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24 13312.0 412.242569 252.659556 290.179836
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25 13824.0 405.098897 257.390218 292.571423
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26 14336.0 398.222222 254.862216 286.481278
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27 14848.0 384.414233 257.108233 289.246765
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28 15360.0 374.634130 257.790220 287.775181
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29 15872.0 366.982663 262.890274 291.229369
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27 14848.0 383.999990 257.293872 289.246765
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28 15360.0 374.634130 257.610071 288.000007
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29 15872.0 367.336555 262.890274 291.229369
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||||
</pre></div>
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</div>
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<div class="line-block">
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||||
@@ -477,7 +477,7 @@ to download the full example code</p>
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||||
<span class="n">bench_layer_norm</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">save_path</span><span class="o">=</span><span class="s1">'.'</span><span class="p">,</span> <span class="n">print_data</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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</pre></div>
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</div>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 9.732 seconds)</p>
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||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 12.291 seconds)</p>
|
||||
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-05-layer-norm-py">
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<div class="sphx-glr-download sphx-glr-download-python docutils container">
|
||||
<p><a class="reference download internal" download="" href="../../_downloads/935c0dd0fbeb4b2e69588471cbb2d4b2/05-layer-norm.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">05-layer-norm.py</span></code></a></p>
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@@ -174,7 +174,7 @@
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<div class="section" id="computation-times">
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<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>
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<p><strong>12:37.359</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<p><strong>12:36.056</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<table class="docutils align-default">
|
||||
<colgroup>
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<col style="width: 85%" />
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@@ -183,23 +183,23 @@
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</colgroup>
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<tbody>
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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>
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<td><p>05:24.923</p></td>
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<td><p>05:21.530</p></td>
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<td><p>0.0 MB</p></td>
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<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>
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<td><p>03:22.452</p></td>
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<td><p>03:20.998</p></td>
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<td><p>0.0 MB</p></td>
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</tr>
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<tr class="row-odd"><td><p><a class="reference internal" href="05-layer-norm.html#sphx-glr-getting-started-tutorials-05-layer-norm-py"><span class="std std-ref">Layer Normalization</span></a> (<code class="docutils literal notranslate"><span class="pre">05-layer-norm.py</span></code>)</p></td>
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<td><p>02:09.732</p></td>
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<td><p>02:12.291</p></td>
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<td><p>0.0 MB</p></td>
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</tr>
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<tr class="row-even"><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>
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<td><p>01:40.240</p></td>
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<td><p>01:41.226</p></td>
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<td><p>0.0 MB</p></td>
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</tr>
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<tr class="row-odd"><td><p><a class="reference internal" href="04-low-memory-dropout.html#sphx-glr-getting-started-tutorials-04-low-memory-dropout-py"><span class="std std-ref">Low-Memory Dropout</span></a> (<code class="docutils literal notranslate"><span class="pre">04-low-memory-dropout.py</span></code>)</p></td>
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<td><p>00:00.012</p></td>
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<td><p>00:00.011</p></td>
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<td><p>0.0 MB</p></td>
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</tr>
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</tbody>
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|
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