[GH-PAGES] Updated website
This commit is contained in:
@@ -324,7 +324,7 @@ for different problem sizes.</p>
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@@ -339,7 +339,7 @@ for different problem sizes.</p>
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15 134217728.0 849.737435 850.656574
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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 46.577 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 45.106 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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@@ -374,15 +374,15 @@ We will then compare its performance against (1) <code class="code docutils lite
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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>softmax-performance:
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N Triton Torch (native) Torch (jit)
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0 256.0 512.000001 546.133347 188.321838
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0 256.0 512.000001 546.133347 190.511628
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.. ... ... ... ...
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94 12288.0 814.111783 415.661740 198.995960
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96 12544.0 812.566838 412.971190 198.913776
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97 12672.0 812.633240 412.097543 199.069228
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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 23.717 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 23.481 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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@@ -569,41 +569,41 @@ torch_output=tensor([[ 1.1045, -36.9688, 31.4688, ..., -11.3906, 24.4531, -3
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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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0 256.0 2.730667 ... 2.978909 2.978909
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1 384.0 7.372800 ... 7.899428 7.899428
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1 384.0 7.372800 ... 8.507077 8.507077
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2 512.0 14.563555 ... 16.384000 16.384000
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3 640.0 22.260869 ... 24.380953 24.380953
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4 768.0 32.768000 ... 35.389441 34.028308
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4 768.0 32.768000 ... 34.028308 34.028308
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5 896.0 39.025776 ... 40.140799 39.025776
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6 1024.0 51.150050 ... 53.773130 52.428801
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7 1152.0 45.242181 ... 46.656000 46.656000
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8 1280.0 51.200001 ... 56.888887 56.888887
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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 62.929456 ... 62.492442 62.061463
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12 1792.0 72.512412 ... 72.512412 71.588687
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13 1920.0 68.776119 ... 70.172588 70.172588
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14 2048.0 73.584279 ... 76.608294 76.608294
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15 2176.0 83.155572 ... 85.998493 85.632545
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16 2304.0 68.446623 ... 77.057651 76.563695
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17 2432.0 71.305746 ... 85.134737 83.614477
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18 2560.0 77.833728 ... 81.108913 80.313727
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19 2688.0 83.369354 ... 89.044730 88.216412
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20 2816.0 82.916747 ... 83.074685 83.074685
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21 2944.0 80.640830 ... 82.509987 81.832567
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22 3072.0 82.301023 ... 88.473602 88.335577
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23 3200.0 83.769634 ... 95.380032 94.955488
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24 3328.0 83.130825 ... 84.298943 83.613586
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25 3456.0 81.271743 ... 91.304157 85.676480
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26 3584.0 85.552231 ... 89.557167 94.548254
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27 3712.0 85.601834 ... 86.716441 86.905039
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28 3840.0 79.305843 ... 84.419358 91.587578
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29 3968.0 85.932350 ... 91.062642 85.660888
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30 4096.0 93.206754 ... 86.369197 85.325956
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9 1408.0 64.138541 ... 67.305878 66.485074
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10 1536.0 79.526831 ... 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 68.776119 ... 69.994940 70.172588
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14 2048.0 73.908442 ... 76.608294 76.260072
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15 2176.0 83.155572 ... 85.632545 85.269692
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16 2304.0 68.446623 ... 76.809875 76.563695
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17 2432.0 71.305746 ... 83.119713 84.877538
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18 2560.0 78.019048 ... 80.709358 80.908642
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19 2688.0 83.186525 ... 89.676257 89.254248
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20 2816.0 83.233226 ... 83.552120 83.233226
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21 2944.0 82.237674 ... 82.237674 82.102191
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22 3072.0 81.943708 ... 87.381335 86.845249
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23 3200.0 84.768213 ... 95.025983 94.674553
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24 3328.0 83.034941 ... 82.181847 82.939284
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25 3456.0 81.600781 ... 89.579522 91.097818
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26 3584.0 87.211821 ... 89.918204 95.654673
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27 3712.0 85.748791 ... 86.641231 86.942857
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28 3840.0 81.079177 ... 91.701494 86.063813
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29 3968.0 92.407370 ... 78.170362 84.504108
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30 4096.0 86.426548 ... 86.536250 89.478485
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[31 rows x 5 columns]
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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> ( 5 minutes 34.643 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 48.488 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 0.011 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.114 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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0 1024.0 311.088617 99.497980 311.088617
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1 1536.0 351.085717 133.083026 344.523365
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2 2048.0 427.408686 158.554837 332.108094
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3 2560.0 461.954908 182.857144 328.556154
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4 3072.0 519.211251 191.999993 320.556515
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0 1024.0 311.088617 99.902435 311.088617
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1 1536.0 354.461542 133.083026 341.333333
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2 2048.0 427.408686 158.554837 321.254900
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3 2560.0 461.954908 182.857144 323.368411
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4 3072.0 515.580429 191.999993 319.168834
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5 3584.0 551.384634 208.271186 309.410081
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6 4096.0 568.231237 220.412561 298.796351
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7 4608.0 498.162157 232.825259 287.251954
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8 5120.0 529.655159 244.294240 286.433562
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9 5632.0 540.671974 245.313973 291.939522
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10 6144.0 548.163546 251.202731 288.000001
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11 6656.0 536.053693 255.590406 286.279570
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6 4096.0 568.231237 219.919464 299.707322
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7 4608.0 500.416301 232.825259 287.251954
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8 5120.0 529.655159 243.809526 289.811322
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9 5632.0 540.671974 244.869560 291.310338
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10 6144.0 548.163546 251.631408 288.000001
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11 6656.0 534.260858 256.000009 286.279570
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12 7168.0 516.612607 254.485198 278.820105
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13 7680.0 487.619051 266.743841 284.884090
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14 8192.0 467.002371 257.003920 276.912679
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15 8704.0 415.300208 267.815384 286.158893
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16 9216.0 430.319054 273.742580 289.887291
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17 9728.0 438.857162 280.615388 289.667485
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18 10240.0 447.650282 287.102804 290.496460
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19 10752.0 433.694125 246.699797 289.616170
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20 11264.0 429.104745 246.432094 286.980888
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14 8192.0 468.114289 257.003920 276.912679
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15 8704.0 416.958106 267.815384 285.767450
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16 9216.0 430.319054 274.081793 289.887291
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18 10240.0 446.025405 287.102804 290.153487
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19 10752.0 430.797982 246.699797 289.291486
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20 11264.0 429.104745 246.656943 286.980888
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21 11776.0 422.457417 250.109737 288.981596
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22 12288.0 418.909088 254.893699 294.617366
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23 12800.0 414.574901 253.674644 288.721817
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24 13312.0 411.711355 252.559690 289.391298
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25 13824.0 406.090579 257.390218 292.056329
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26 14336.0 396.387109 255.619613 289.129416
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27 14848.0 386.080180 257.108233 287.844912
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28 15360.0 374.634130 258.332158 288.450715
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29 15872.0 367.691129 261.986243 290.341468
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22 12288.0 419.504980 254.893699 294.323369
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23 12800.0 414.574901 254.094291 288.993430
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24 13312.0 413.309181 252.759501 289.653667
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25 13824.0 407.587209 257.390218 292.056329
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26 14336.0 395.930964 255.429842 288.644296
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27 14848.0 386.918555 257.293872 287.380642
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28 15360.0 375.015246 258.513318 286.656296
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29 15872.0 368.046389 261.267482 289.679087
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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 12.765 seconds)</p>
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||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 12.791 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-05-layer-norm-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/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>12:57.713</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<p><strong>13:09.980</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<table class="docutils align-default">
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||||
<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>05:34.643</p></td>
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<td><p>05:48.488</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="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>03:23.717</p></td>
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<td><p>03:23.481</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>02:12.765</p></td>
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<td><p>02:12.791</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>01:46.577</p></td>
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<td><p>01:45.106</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>00:00.011</p></td>
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<td><p>00:00.114</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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