[GH-PAGES] Updated website
This commit is contained in:
@@ -326,23 +326,23 @@ for different problem sizes.</p>
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size Triton Torch
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</div>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 50.715 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 34.873 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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N Triton Torch (native) Torch (jit)
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@@ -394,7 +394,7 @@ 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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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 30.914 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 27.507 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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|
@@ -567,42 +567,42 @@ 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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1 384.0 7.372800 ... 8.507077 8.507077
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7 1152.0 45.242181 ... 48.161033 47.396572
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6 1024.0 51.150050 ... 53.773130 52.428801
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||||
7 1152.0 45.242181 ... 47.396572 47.396572
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8 1280.0 51.200001 ... 57.690139 57.690139
|
||||
9 1408.0 64.138541 ... 69.009825 67.305878
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10 1536.0 80.430545 ... 80.430545 79.526831
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||||
14 2048.0 73.908442 ... 78.398206 77.314362
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14 2048.0 73.584279 ... 78.398206 77.314362
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|
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19 2688.0 83.737433 ... 91.185232 89.254248
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20 2816.0 79.879498 ... 82.602666 83.392363
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||||
22 3072.0 80.202695 ... 89.170242 87.381335
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||||
23 3200.0 82.474230 ... 96.676741 95.238096
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24 3328.0 82.843841 ... 86.062515 84.795401
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25 3456.0 81.026701 ... 91.200871 87.347312
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26 3584.0 87.381330 ... 95.350361 98.268190
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27 3712.0 85.970176 ... 89.353616 87.552452
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29 3968.0 87.850207 ... 86.449828 89.988156
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30 4096.0 86.509232 ... 92.948562 87.352901
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17 2432.0 71.305746 ... 86.179335 85.653855
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18 2560.0 77.833728 ... 82.331658 81.920002
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19 2688.0 83.552988 ... 91.404957 89.464755
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20 2816.0 79.879498 ... 84.360174 83.873477
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21 2944.0 82.237674 ... 81.431424 83.337844
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22 3072.0 81.589488 ... 89.030036 88.612060
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23 3200.0 84.993363 ... 96.822991 95.808380
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24 3328.0 82.891535 ... 85.602017 84.101981
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||||
25 3456.0 80.300370 ... 91.771848 86.596744
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26 3584.0 85.633710 ... 90.458141 95.451583
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||||
27 3712.0 83.247783 ... 86.829501 87.552452
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||||
28 3840.0 81.019778 ... 88.971840 91.853823
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||||
29 3968.0 85.753071 ... 85.600795 89.988156
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30 4096.0 88.651075 ... 88.768339 89.299883
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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> ( 7 minutes 14.457 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 6 minutes 20.627 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>
|
||||
|
@@ -374,7 +374,7 @@ to explore the <cite>triton/language/random</cite> folder!</p>
|
||||
<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 0.282 seconds)</p>
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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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<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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|
@@ -196,36 +196,36 @@ 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:
|
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N Triton Torch Apex
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1 1536.0 630.153868 323.368435 511.999982
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4 3072.0 702.171410 375.206126 501.551037
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||||
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|
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11 6656.0 700.631610 400.360920 398.861429
|
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12 7168.0 690.891575 382.293315 382.293315
|
||||
6 4096.0 728.177767 383.251446 451.972420
|
||||
7 4608.0 670.254540 396.387087 421.302872
|
||||
8 5120.0 688.403381 397.669909 422.268057
|
||||
9 5632.0 704.000002 398.725657 413.357796
|
||||
10 6144.0 702.171410 402.885254 411.313806
|
||||
11 6656.0 700.631610 400.360920 400.360920
|
||||
12 7168.0 690.891575 383.571898 381.023265
|
||||
13 7680.0 678.895043 392.587863 386.415087
|
||||
14 8192.0 636.271854 392.431125 374.491442
|
||||
15 8704.0 624.502255 392.292962 380.502740
|
||||
16 9216.0 606.814809 403.989025 383.002605
|
||||
17 9728.0 587.350922 407.455499 382.427505
|
||||
18 10240.0 566.920437 407.562184 381.911416
|
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19 10752.0 547.872604 410.577576 380.601764
|
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20 11264.0 533.207081 396.096702 369.311483
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21 11776.0 521.927959 407.826843 377.587162
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22 12288.0 516.031509 413.042029 382.505826
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23 12800.0 504.433489 408.782457 376.470582
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24 13312.0 494.180982 401.871683 375.647260
|
||||
25 13824.0 482.934503 409.600016 378.092325
|
||||
26 14336.0 471.967074 398.914774 372.969090
|
||||
27 14848.0 461.297068 403.341254 374.712936
|
||||
28 15360.0 454.269882 406.887417 378.092307
|
||||
29 15872.0 447.887117 406.974373 376.225175
|
||||
14 8192.0 636.271854 390.095241 375.564460
|
||||
15 8704.0 627.315309 392.292962 380.502740
|
||||
16 9216.0 609.322328 403.989025 381.023249
|
||||
17 9728.0 587.350922 408.524944 382.427505
|
||||
18 10240.0 566.920437 408.578556 382.803739
|
||||
19 10752.0 547.872604 412.546760 379.761601
|
||||
20 11264.0 531.634232 396.096702 369.311483
|
||||
21 11776.0 521.927959 408.711507 378.345375
|
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22 12288.0 514.007840 413.911572 383.251457
|
||||
23 12800.0 504.433489 410.420828 377.163903
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24 13312.0 494.180982 404.159395 376.310952
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||||
25 13824.0 481.882350 409.600016 378.739711
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||||
26 14336.0 471.967074 400.307157 369.961287
|
||||
27 14848.0 461.297068 404.027214 375.304904
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||||
28 15360.0 454.269882 406.214870 378.092307
|
||||
29 15872.0 447.098578 408.940410 376.783377
|
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</pre></div>
|
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</div>
|
||||
<div class="line-block">
|
||||
@@ -543,7 +543,7 @@ to download the full example code</p>
|
||||
<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>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 38.714 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 29.729 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">
|
||||
<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>
|
||||
|
@@ -543,7 +543,7 @@ to download the full example code</p>
|
||||
<span class="c1"># bench_flash_attention.run(save_path='.', print_data=True)</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.074 seconds)</p>
|
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.072 seconds)</p>
|
||||
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-06-fused-attention-py">
|
||||
<div class="sphx-glr-download sphx-glr-download-python docutils container">
|
||||
<p><a class="reference download internal" download="" href="../../_downloads/54a35f6ec55f9746935b9566fb6bb1df/06-fused-attention.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">06-fused-attention.py</span></code></a></p>
|
||||
|
@@ -276,7 +276,7 @@ tensor([0.4105, 0.5430, 0.0249, ..., 0.0424, 0.5351, 0.8149], device='cuda:
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The maximum difference between torch and triton is 2.384185791015625e-07
|
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</pre></div>
|
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</div>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.250 seconds)</p>
|
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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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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-07-libdevice-function-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/3ff29f967ace7985da24aab10352fc76/07-libdevice-function.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">07-libdevice-function.py</span></code></a></p>
|
||||
|
@@ -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>18:15.408</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<p><strong>16:52.830</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>
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<col style="width: 85%" />
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@@ -183,31 +183,31 @@
|
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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>07:14.457</p></td>
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<td><p>06:20.627</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="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>
|
||||
<td><p>05:38.714</p></td>
|
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<td><p>05:29.729</p></td>
|
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<td><p>0.0 MB</p></td>
|
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</tr>
|
||||
<tr class="row-odd"><td><p><a class="reference internal" href="02-fused-softmax.html#sphx-glr-getting-started-tutorials-02-fused-softmax-py"><span class="std std-ref">Fused Softmax</span></a> (<code class="docutils literal notranslate"><span class="pre">02-fused-softmax.py</span></code>)</p></td>
|
||||
<td><p>03:30.914</p></td>
|
||||
<td><p>03:27.507</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
<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>
|
||||
<td><p>01:50.715</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
<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>
|
||||
<td><p>00:00.282</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
<tr class="row-even"><td><p><a class="reference internal" href="07-libdevice-function.html#sphx-glr-getting-started-tutorials-07-libdevice-function-py"><span class="std std-ref">Libdevice function</span></a> (<code class="docutils literal notranslate"><span class="pre">07-libdevice-function.py</span></code>)</p></td>
|
||||
<td><p>00:00.250</p></td>
|
||||
<td><p>01:34.873</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
<tr class="row-odd"><td><p><a class="reference internal" href="06-fused-attention.html#sphx-glr-getting-started-tutorials-06-fused-attention-py"><span class="std std-ref">Fused Attention</span></a> (<code class="docutils literal notranslate"><span class="pre">06-fused-attention.py</span></code>)</p></td>
|
||||
<td><p>00:00.074</p></td>
|
||||
<td><p>00:00.072</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
<tr class="row-even"><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>
|
||||
<td><p>00:00.012</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
<tr class="row-odd"><td><p><a class="reference internal" href="07-libdevice-function.html#sphx-glr-getting-started-tutorials-07-libdevice-function-py"><span class="std std-ref">Libdevice function</span></a> (<code class="docutils literal notranslate"><span class="pre">07-libdevice-function.py</span></code>)</p></td>
|
||||
<td><p>00:00.010</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
</tbody>
|
||||
|
Reference in New Issue
Block a user