[GH-PAGES] Updated website
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@@ -244,7 +244,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
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10 4194304.0 780.190482 780.190482
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11 8388608.0 812.429770 812.429770
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12 16777216.0 833.084721 833.084721
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13 33554432.0 842.004273 842.906750
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13 33554432.0 842.004273 843.811163
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14 67108864.0 847.448255 848.362445
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15 134217728.0 849.737435 850.656574
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@@ -254,7 +254,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 1 minutes 46.556 seconds)
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**Total running time of the script:** ( 1 minutes 44.156 seconds)
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.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
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@@ -286,17 +286,17 @@ We will then compare its performance against (1) :code:`torch.softmax` and (2) t
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softmax-performance:
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N Triton Torch (native) Torch (jit)
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0 256.0 512.000001 546.133347 190.511628
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1 384.0 585.142862 585.142862 153.600004
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0 256.0 512.000001 546.133347 186.181817
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1 384.0 614.400016 585.142862 151.703707
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2 512.0 655.360017 606.814814 154.566038
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3 640.0 682.666684 640.000002 160.000000
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4 768.0 722.823517 664.216187 162.754967
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.. ... ... ... ...
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93 12160.0 812.359066 406.179533 198.936606
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94 12288.0 814.111783 415.222812 199.298541
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95 12416.0 812.498981 411.722274 198.854847
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96 12544.0 812.566838 413.396498 199.111113
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97 12672.0 812.633240 412.097543 199.264875
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93 12160.0 814.058574 406.179533 198.733401
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94 12288.0 814.111783 416.101597 198.995960
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95 12416.0 812.498981 412.149375 198.705656
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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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[98 rows x 4 columns]
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@@ -314,7 +314,7 @@ In the above plot, we can see that:
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 3 minutes 23.713 seconds)
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**Total running time of the script:** ( 3 minutes 20.891 seconds)
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.. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:
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@@ -462,37 +462,37 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
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matmul-performance:
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M cuBLAS ... Triton Triton (+ LeakyReLU)
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0 256.0 2.730667 ... 3.276800 2.978909
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0 256.0 2.730667 ... 2.978909 2.978909
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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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2 512.0 14.563555 ... 16.384000 15.420235
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3 640.0 22.260869 ... 24.380953 24.380953
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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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5 896.0 39.025776 ... 39.025776 39.025776
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6 1024.0 49.932191 ... 53.773130 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 ... 62.492442 62.061463
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12 1792.0 72.983276 ... 72.512412 72.047592
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13 1920.0 69.120002 ... 70.530615 70.530615
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14 2048.0 73.908442 ... 76.959706 76.959706
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15 2176.0 83.500614 ... 85.632545 85.632545
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16 2304.0 68.446623 ... 76.563695 76.563695
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17 2432.0 71.305746 ... 74.918570 84.877538
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18 2560.0 77.833728 ... 81.108913 81.108913
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19 2688.0 83.552988 ... 89.254248 89.464755
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20 2816.0 79.587973 ... 82.916747 82.916747
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21 2944.0 81.832567 ... 82.509987 82.509987
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22 3072.0 82.062468 ... 87.651868 88.197981
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23 3200.0 81.424937 ... 93.704243 92.352095
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24 3328.0 84.003845 ... 84.895397 84.298943
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25 3456.0 81.230800 ... 90.790053 87.489490
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26 3584.0 85.633710 ... 96.166193 96.683219
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27 3712.0 82.423549 ... 87.094458 87.706180
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28 3840.0 83.402717 ... 91.134731 87.011801
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29 3968.0 91.301109 ... 86.144680 89.394823
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30 4096.0 86.592080 ... 93.206754 86.313653
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12 1792.0 72.983276 ... 71.588687 71.588687
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13 1920.0 68.776119 ... 70.530615 70.530615
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14 2048.0 73.908442 ... 77.314362 76.959706
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15 2176.0 83.500614 ... 85.998493 85.269692
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16 2304.0 68.251065 ... 76.809875 76.563695
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17 2432.0 71.305746 ... 74.719317 84.877538
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18 2560.0 78.019048 ... 81.310171 81.108913
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19 2688.0 83.552988 ... 89.995386 89.464755
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20 2816.0 79.587973 ... 82.916747 82.602666
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21 2944.0 82.102191 ... 82.646820 83.060049
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22 3072.0 81.707223 ... 87.516392 88.060814
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23 3200.0 80.402009 ... 87.551302 87.189747
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24 3328.0 80.798314 ... 83.905938 84.596116
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25 3456.0 82.688790 ... 91.252485 90.994998
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26 3584.0 86.540320 ... 91.563533 95.350361
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27 3712.0 82.491612 ... 86.867254 86.791782
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28 3840.0 82.592983 ... 92.390975 86.400002
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29 3968.0 93.254827 ... 85.093402 91.130650
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30 4096.0 86.202781 ... 87.982773 89.210850
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[31 rows x 5 columns]
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@@ -502,7 +502,7 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 5 minutes 23.466 seconds)
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**Total running time of the script:** ( 5 minutes 26.818 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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@@ -38,36 +38,36 @@ Layer Normalization
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layer-norm-backward:
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N Triton Torch Apex
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0 1024.0 311.088617 99.497980 315.076934
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1 1536.0 354.461542 134.050910 338.201833
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2 2048.0 423.724127 159.067963 321.254900
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3 2560.0 465.454542 181.238943 326.808501
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4 3072.0 515.580429 191.501303 315.076914
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5 3584.0 551.384634 207.267476 307.199992
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6 4096.0 568.231237 218.939860 299.707322
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7 4608.0 500.416301 233.316456 290.267724
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8 5120.0 529.655159 240.469672 285.104413
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9 5632.0 542.843364 244.426754 290.683877
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10 6144.0 546.133354 250.349744 286.322318
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11 6656.0 532.479975 255.590406 286.793541
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12 7168.0 513.528374 256.764187 281.558103
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13 7680.0 486.332448 264.068761 283.133636
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14 8192.0 464.794337 262.143998 282.077471
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15 8704.0 416.958106 267.472468 285.767450
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16 9216.0 430.319054 272.729961 289.129410
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17 9728.0 438.857162 280.278512 289.667485
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25 13824.0 404.604870 257.190689 292.056329
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26 14336.0 397.302533 254.485198 288.402346
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27 14848.0 381.942121 257.108233 289.246765
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28 15360.0 374.253788 258.151252 287.775181
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29 15872.0 366.982663 262.527914 290.562936
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0 1024.0 311.088617 99.096776 307.200008
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1 1536.0 351.085717 133.083026 341.333333
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2 2048.0 423.724127 161.684218 338.979315
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3 2560.0 461.954908 182.857144 330.322572
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4 3072.0 511.999982 191.501303 316.429186
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5 3584.0 554.941930 208.271186 310.527060
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6 4096.0 568.231237 220.412561 296.990947
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7 4608.0 498.162157 231.849059 289.507855
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8 5120.0 525.128191 242.845844 286.433562
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9 5632.0 538.517949 243.107920 290.683877
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10 6144.0 544.118087 248.451567 286.322318
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11 6656.0 527.207907 256.000009 286.536325
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12 7168.0 507.469040 262.243907 288.160801
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13 7680.0 482.513091 260.338991 276.756754
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14 8192.0 460.440290 268.957600 286.600589
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15 8704.0 416.958106 267.472468 284.987724
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16 9216.0 428.651187 272.729961 289.507855
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17 9728.0 438.857162 280.278512 288.950501
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18 10240.0 447.650282 286.433562 288.112552
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19 10752.0 430.079980 246.464170 290.267711
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20 11264.0 429.104745 245.091565 285.767446
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21 11776.0 421.198220 249.447482 288.686414
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22 12288.0 420.102570 254.453844 294.911986
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23 12800.0 415.696898 253.465340 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 254.862216 286.481278
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27 14848.0 384.414233 257.293872 289.012175
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28 15360.0 374.253788 257.610071 288.000007
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29 15872.0 367.336555 262.708969 291.229369
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@@ -329,7 +329,7 @@ Layer Normalization
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 2 minutes 11.996 seconds)
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**Total running time of the script:** ( 2 minutes 7.366 seconds)
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.. _sphx_glr_download_getting-started_tutorials_05-layer-norm.py:
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@@ -5,16 +5,16 @@
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Computation times
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=================
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**12:45.742** total execution time for **getting-started_tutorials** files:
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**12:39.242** total execution time for **getting-started_tutorials** files:
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 05:23.466 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 05:26.818 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 03:23.713 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 03:20.891 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``) | 02:11.996 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``) | 02:07.366 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 01:46.556 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 01:44.156 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``) | 00:00.011 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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