[GH-PAGES] Updated website
This commit is contained in:
@@ -323,7 +323,7 @@ for different problem sizes.</p>
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size Triton Torch
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@@ -339,7 +339,7 @@ for different problem sizes.</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 45.289 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 43.459 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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@@ -375,16 +375,16 @@ We will then compare its performance against (1) <code class="code docutils lite
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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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[98 rows x 4 columns]
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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 23.318 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 23.196 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 2.978909 ... 2.978909 2.978909
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1 384.0 7.372800 ... 7.899428 7.899428
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6 1024.0 49.932191 ... 52.428801 52.428801
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5 896.0 37.971025 ... 40.140799 39.025776
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6 1024.0 49.932191 ... 53.773130 52.428801
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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 69.467336 ... 70.172588 70.172588
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14 2048.0 73.908442 ... 76.959706 76.608294
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15 2176.0 83.155572 ... 85.998493 85.269692
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16 2304.0 68.056616 ... 76.809875 76.563695
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17 2432.0 71.305746 ... 85.653855 84.367759
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18 2560.0 77.833728 ... 81.310171 80.511054
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19 2688.0 83.737433 ... 90.102270 89.044730
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20 2816.0 83.074685 ... 83.873477 82.759409
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21 2944.0 82.237674 ... 83.337844 83.060049
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22 3072.0 81.121923 ... 88.750943 87.787755
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23 3200.0 84.321474 ... 96.096095 95.952022
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24 3328.0 83.516586 ... 84.052885 84.795401
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25 3456.0 82.604067 ... 91.407671 91.097818
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26 3584.0 85.633710 ... 92.600816 95.350361
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27 3712.0 84.159518 ... 86.867254 88.640059
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28 3840.0 81.138664 ... 90.723546 91.930177
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29 3968.0 91.885495 ... 80.120775 82.700061
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30 4096.0 91.741443 ... 85.434583 87.211002
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11 1664.0 63.150256 ... 62.492442 62.061463
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12 1792.0 72.983276 ... 59.154861 71.135597
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13 1920.0 69.120002 ... 70.172588 70.172588
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16 2304.0 68.251065 ... 76.809875 76.563695
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17 2432.0 71.215370 ... 74.918570 84.877538
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18 2560.0 77.833728 ... 81.310171 80.908642
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19 2688.0 83.186525 ... 90.102270 89.254248
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20 2816.0 81.674548 ... 83.552120 82.602666
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21 2944.0 81.967162 ... 82.237674 82.102191
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22 3072.0 81.943708 ... 89.310890 88.681451
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23 3200.0 84.880639 ... 89.761569 94.955488
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24 3328.0 83.468170 ... 84.895397 84.795401
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25 3456.0 82.519518 ... 91.407671 90.586029
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26 3584.0 86.540320 ... 94.349836 93.564405
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27 3712.0 86.341700 ... 87.094458 87.322855
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28 3840.0 83.402717 ... 92.545605 85.201850
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29 3968.0 92.793868 ... 87.913500 86.788006
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30 4096.0 91.397840 ... 92.372834 87.324485
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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 53.278 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 56.098 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 0.109 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.110 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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3 2560.0 461.954908 182.857144 330.322572
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4 3072.0 511.999982 191.501303 320.556515
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5 3584.0 551.384634 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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9 5632.0 536.380957 243.107920 290.683877
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10 6144.0 544.118087 248.661056 285.767458
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11 6656.0 527.207907 256.410903 286.279570
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12 7168.0 505.976473 261.844750 288.644296
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13 7680.0 482.513091 260.707203 277.590365
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15 8704.0 416.958106 267.815384 285.377055
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16 9216.0 428.651187 273.066667 289.507855
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18 10240.0 446.836366 286.767793 290.840246
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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 2048.0 420.102553 162.217818 325.509933
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3 2560.0 461.954908 182.314537 325.079368
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6 4096.0 568.231237 220.412561 298.796351
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7 4608.0 495.928261 231.849059 286.507772
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8 5120.0 522.893618 242.845844 283.787523
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9 5632.0 536.380957 243.545956 290.683877
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10 6144.0 542.117638 248.661056 285.214712
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11 6656.0 525.473708 256.410903 286.793541
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12 7168.0 505.976473 261.844750 288.160801
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13 7680.0 481.253256 260.707203 277.590365
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14 8192.0 460.440290 268.957600 286.600589
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15 8704.0 416.958106 267.815384 284.987724
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16 9216.0 428.651187 272.729961 289.507855
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17 9728.0 438.857162 279.942444 288.950501
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18 10240.0 446.836366 286.767793 290.496460
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19 10752.0 429.364408 246.464170 290.267711
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20 11264.0 429.104745 245.313973 285.767446
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||||
21 11776.0 421.826879 249.227509 288.686414
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||||
20 11264.0 429.104745 245.091565 285.767446
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||||
21 11776.0 421.198220 249.227509 288.686414
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||||
22 12288.0 420.102570 254.453844 294.911986
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||||
23 12800.0 415.135142 253.465340 288.721817
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||||
24 13312.0 412.242569 252.559690 289.916513
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||||
25 13824.0 405.098897 257.390218 292.571423
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||||
26 14336.0 397.761846 254.673567 286.242939
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||||
27 14848.0 383.999990 257.108233 289.246765
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||||
28 15360.0 374.634130 257.610071 287.550706
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||||
29 15872.0 366.982663 262.890274 291.229369
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||||
23 12800.0 415.135142 253.256381 289.811310
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||||
24 13312.0 412.242569 252.559690 290.179836
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||||
25 13824.0 404.604870 257.190689 292.571423
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||||
26 14336.0 397.761846 254.673567 286.481278
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||||
27 14848.0 384.207000 257.293872 289.012175
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||||
28 15360.0 374.253788 257.610071 287.326580
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29 15872.0 366.982663 262.708969 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 13.046 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 12.651 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">
|
||||
<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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||||
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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>13:15.039</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<p><strong>13:15.515</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
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<table class="docutils align-default">
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<colgroup>
|
||||
<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>05:53.278</p></td>
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<td><p>05:56.098</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>03:23.318</p></td>
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||||
<td><p>03:23.196</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>02:13.046</p></td>
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<td><p>02:12.651</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>01:45.289</p></td>
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<td><p>01:43.459</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>00:00.109</p></td>
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<td><p>00:00.110</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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