[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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</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 42.563 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 41.931 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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@@ -374,17 +374,17 @@ 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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1 384.0 614.400016 585.142862 153.600004
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2 512.0 655.360017 585.142849 154.566038
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.. ... ... ... ...
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96 12544.0 812.566838 412.971190 199.111113
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93 12160.0 812.359066 406.179533 198.936606
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[98 rows x 4 columns]
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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 22.469 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 21.826 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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0 256.0 2.730667 ... 2.978909 2.978909
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1 384.0 7.372800 ... 8.507077 7.899428
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0 256.0 2.978909 ... 2.978909 2.978909
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1 384.0 7.372800 ... 8.507077 8.507077
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5 896.0 39.025776 ... 40.140799 39.025776
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6 1024.0 49.932191 ... 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 56.109587
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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 ... 71.588687 71.588687
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13 1920.0 68.776119 ... 70.172588 70.530615
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14 2048.0 73.908442 ... 77.314362 76.959706
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15 2176.0 83.155572 ... 86.367588 85.269692
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5 896.0 39.025776 ... 39.025776 39.025776
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6 1024.0 51.150050 ... 52.428801 52.428801
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7 1152.0 45.242181 ... 47.396572 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 63.372618 ... 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 ... 70.172588 70.172588
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14 2048.0 73.908442 ... 76.959706 76.959706
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15 2176.0 83.500614 ... 85.998493 85.269692
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16 2304.0 68.446623 ... 76.809875 76.563695
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17 2432.0 71.305746 ... 74.918570 84.877538
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18 2560.0 77.833728 ... 81.310171 81.108913
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19 2688.0 83.552988 ... 90.102270 88.732296
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20 2816.0 82.602666 ... 83.712490 82.759409
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21 2944.0 81.967162 ... 82.578347 82.646820
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22 3072.0 82.062468 ... 87.651868 86.579673
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23 3200.0 84.544253 ... 89.887639 94.674553
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24 3328.0 83.226931 ... 81.346098 83.710812
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25 3456.0 82.688790 ... 90.180725 91.097818
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26 3584.0 85.430303 ... 92.505546 97.522120
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27 3712.0 85.528545 ... 85.672957 87.552452
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28 3840.0 84.292684 ... 87.148936 91.022218
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29 3968.0 86.973584 ... 90.656713 84.856701
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30 4096.0 93.531519 ... 83.416859 87.267706
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18 2560.0 77.833728 ... 81.310171 80.313727
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19 2688.0 83.922689 ... 89.676257 88.422041
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20 2816.0 80.617762 ... 83.392363 83.233226
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21 2944.0 82.373605 ... 82.373605 81.298583
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22 3072.0 82.540970 ... 88.335577 88.060814
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23 3200.0 83.769634 ... 95.096582 94.674553
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24 3328.0 84.003845 ... 83.516586 84.003845
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25 3456.0 82.015834 ... 89.183149 84.597660
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26 3584.0 86.043434 ... 97.416461 96.579370
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27 3712.0 81.548851 ... 88.797643 84.946722
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28 3840.0 83.908951 ... 91.097196 85.930069
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29 3968.0 91.301109 ... 86.175099 89.068569
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30 4096.0 88.534120 ... 93.206754 89.240508
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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 27.557 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 21.527 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 0.010 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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0 1024.0 311.088617 99.497980 307.200008
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1 1536.0 351.085717 135.032961 344.523365
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2 2048.0 427.408686 159.584422 323.368435
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3 2560.0 461.954908 182.857144 326.808501
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4 3072.0 515.580429 192.501302 316.429186
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5 3584.0 554.941930 208.271186 308.301075
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6 4096.0 568.231237 219.919464 297.890900
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7 4608.0 500.416301 233.316456 291.031570
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8 5120.0 527.381977 240.941184 285.104413
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9 5632.0 538.517949 243.985547 289.438969
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10 6144.0 546.133354 249.081070 286.322318
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11 6656.0 525.473708 256.000009 285.767438
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12 7168.0 512.000004 259.475119 284.821192
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13 7680.0 485.052616 263.690977 277.172933
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14 8192.0 463.698115 266.406514 284.939124
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15 8704.0 417.791980 267.472468 285.767450
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16 9216.0 431.157889 272.059034 289.507855
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17 9728.0 439.683593 280.278512 290.027323
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18 10240.0 446.836366 287.102804 290.496460
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19 10752.0 430.797982 246.229020 290.594591
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20 11264.0 429.786952 246.882202 288.204696
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21 11776.0 422.457417 248.788725 287.804473
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22 12288.0 420.701865 254.453844 294.029924
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23 12800.0 416.260178 253.256381 287.910035
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24 13312.0 411.711355 252.161013 289.916513
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25 13824.0 406.588243 256.991469 292.313649
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26 14336.0 396.387109 254.673567 287.919661
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27 14848.0 383.380322 257.479779 289.246765
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28 15360.0 376.547496 258.332158 286.656296
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29 15872.0 366.982663 262.527914 290.562936
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0 1024.0 311.088617 98.303995 303.407414
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1 1536.0 351.085717 134.540150 338.201833
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2 2048.0 423.724127 161.154101 323.368435
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3 2560.0 465.454542 180.705883 326.808501
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4 3072.0 515.580429 191.999993 320.556515
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5 3584.0 554.941930 208.271186 311.652167
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||||
6 4096.0 568.231237 220.412561 298.796351
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||||
7 4608.0 500.416301 232.825259 286.507772
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||||
8 5120.0 527.381977 241.889751 283.133649
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||||
9 5632.0 540.671974 243.107920 290.683877
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10 6144.0 544.118087 248.661056 286.322318
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||||
11 6656.0 532.479975 256.000009 286.279570
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||||
12 7168.0 507.469040 259.867079 285.767449
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||||
13 7680.0 481.253256 262.564106 276.341823
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||||
14 8192.0 463.698115 264.970349 284.115618
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||||
15 8704.0 416.958106 267.815384 284.987724
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||||
16 9216.0 430.319054 270.727053 287.251954
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||||
17 9728.0 438.857162 280.278512 289.667485
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||||
18 10240.0 447.650282 286.100109 288.112552
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||||
19 10752.0 432.241202 246.229020 289.941565
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||||
20 11264.0 429.786952 245.760001 286.980888
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||||
21 11776.0 423.089806 248.788725 288.391833
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22 12288.0 419.504980 254.453844 294.764603
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23 12800.0 414.016170 253.047766 288.450715
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24 13312.0 411.711355 252.161013 290.443638
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25 13824.0 406.090579 256.792581 292.056329
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26 14336.0 394.116833 254.485198 287.198654
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27 14848.0 384.414233 257.665934 290.188916
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28 15360.0 375.015246 257.790220 285.104419
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29 15872.0 366.629453 261.986243 290.784741
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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 11.866 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 11.478 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>
|
||||
<p><strong>12:44.465</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<p><strong>12:36.772</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>05:27.557</p></td>
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<td><p>05:21.527</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>03:22.469</p></td>
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||||
<td><p>03:21.826</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>02:11.866</p></td>
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<td><p>02:11.478</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>01:42.563</p></td>
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<td><p>01:41.931</p></td>
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<td><p>0.0 MB</p></td>
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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>00:00.010</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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|
Reference in New Issue
Block a user