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update the baseline data for the operator benchmark (#162693)
According to the results of the last four operator benchmark runs, we found that five models achieved more than a 30% improvement compared to the baseline. Therefore, we will update the operator benchmark baseline data. We use the average results from the four runs as the new baseline for the five models. And add a pull request trigger for the operator benchmark workflow Benchmarking Framework | Benchmarking Module Name | Case Name | tag | run_backward | baseline old | r1 | r2 | r3 | r4 | avg | speedup -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- PyTorch | add | add_M1_N1_K1_cpu | short | FALSE | 3.9497 | 2.57 | 2.54 | 2.38 | 2.31 | 2.45 | 1.61 PyTorch | functional.hardtanh | functional.hardtanh_dims(512 512)_contigFalse_inplaceFalse_dtypetorch.quint8 | short | FALSE | 67.118 | 50.02 | 49.80 | 46.78 | 48.94 | 48.88 | 1.37 PyTorch | relu6 | relu6_dims(512 512)_contigFalse_inplaceFalse_dtypetorch.quint8 | short | FALSE | 68.739 | 51.17 | 51.19 | 48.07 | 50.42 | 50.21 | 1.37 PyTorch | relu6 | relu6_dims(256 1024)_contigFalse_inplaceFalse_dtypetorch.quint8 | short | FALSE | 69.1875 | 51.97 | 52.77 | 50.00 | 51.24 | 51.50 | 1.34 PyTorch | functional.hardtanh | functional.hardtanh_dims(256 1024)_contigFalse_inplaceFalse_dtypetorch.quint8 | short | FALSE | 67.436 | 50.98 | 51.69 | 49.06 | 49.87 | 50.40 | 1.34 @chuanqi129 @huydhn @desertfire @jainapurva Pull Request resolved: https://github.com/pytorch/pytorch/pull/162693 Approved by: https://github.com/huydhn
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@ -1,5 +1,5 @@
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Benchmarking Framework,Benchmarking Module Name,Case Name,tag,run_backward,Execution Time
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PyTorch,add,add_M1_N1_K1_cpu,short,FALSE,3.9497
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PyTorch,add,add_M1_N1_K1_cpu,short,FALSE,2.459
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PyTorch,add,add_M64_N64_K64_cpu,short,FALSE,14.3181
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PyTorch,add,add_M64_N64_K128_cpu,short,FALSE,14.6826
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PyTorch,add,add_M1_N1_K1_cpu_bwdall_BACKWARD,short,TRUE,58.1449
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@ -376,10 +376,10 @@ PyTorch,relu6,"relu6_dims(3,4,5)_contigFalse_inplaceFalse_dtypetorch.qint32",sho
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PyTorch,relu6,"relu6_dims(2,3,4,5)_contigFalse_inplaceFalse_dtypetorch.quint8",short,FALSE,9.6588
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PyTorch,relu6,"relu6_dims(2,3,4,5)_contigFalse_inplaceFalse_dtypetorch.qint8",short,FALSE,9.5969
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PyTorch,relu6,"relu6_dims(2,3,4,5)_contigFalse_inplaceFalse_dtypetorch.qint32",short,FALSE,9.547
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PyTorch,relu6,"relu6_dims(512,512)_contigFalse_inplaceFalse_dtypetorch.quint8",short,FALSE,68.739
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PyTorch,relu6,"relu6_dims(512,512)_contigFalse_inplaceFalse_dtypetorch.quint8",short,FALSE,50.21375
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PyTorch,relu6,"relu6_dims(512,512)_contigFalse_inplaceFalse_dtypetorch.qint8",short,FALSE,45.14133333
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PyTorch,relu6,"relu6_dims(512,512)_contigFalse_inplaceFalse_dtypetorch.qint32",short,FALSE,52.6664
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PyTorch,relu6,"relu6_dims(256,1024)_contigFalse_inplaceFalse_dtypetorch.quint8",short,FALSE,69.1875
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PyTorch,relu6,"relu6_dims(256,1024)_contigFalse_inplaceFalse_dtypetorch.quint8",short,FALSE,51.49525
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PyTorch,relu6,"relu6_dims(256,1024)_contigFalse_inplaceFalse_dtypetorch.qint8",short,FALSE,48.3458
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PyTorch,relu6,"relu6_dims(256,1024)_contigFalse_inplaceFalse_dtypetorch.qint32",short,FALSE,62.0719
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PyTorch,functional.hardtanh,"functional.hardtanh_dims(3,4,5)_contigFalse_inplaceFalse_dtypetorch.quint8",short,FALSE,7.5728
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@ -388,10 +388,10 @@ PyTorch,functional.hardtanh,"functional.hardtanh_dims(3,4,5)_contigFalse_inplace
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PyTorch,functional.hardtanh,"functional.hardtanh_dims(2,3,4,5)_contigFalse_inplaceFalse_dtypetorch.quint8",short,FALSE,8.1647
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PyTorch,functional.hardtanh,"functional.hardtanh_dims(2,3,4,5)_contigFalse_inplaceFalse_dtypetorch.qint8",short,FALSE,8.1768
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PyTorch,functional.hardtanh,"functional.hardtanh_dims(2,3,4,5)_contigFalse_inplaceFalse_dtypetorch.qint32",short,FALSE,8.0619
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PyTorch,functional.hardtanh,"functional.hardtanh_dims(512,512)_contigFalse_inplaceFalse_dtypetorch.quint8",short,FALSE,67.118
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PyTorch,functional.hardtanh,"functional.hardtanh_dims(512,512)_contigFalse_inplaceFalse_dtypetorch.quint8",short,FALSE,48.88475
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PyTorch,functional.hardtanh,"functional.hardtanh_dims(512,512)_contigFalse_inplaceFalse_dtypetorch.qint8",short,FALSE,43.702
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PyTorch,functional.hardtanh,"functional.hardtanh_dims(512,512)_contigFalse_inplaceFalse_dtypetorch.qint32",short,FALSE,50.3613
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PyTorch,functional.hardtanh,"functional.hardtanh_dims(256,1024)_contigFalse_inplaceFalse_dtypetorch.quint8",short,FALSE,67.436
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PyTorch,functional.hardtanh,"functional.hardtanh_dims(256,1024)_contigFalse_inplaceFalse_dtypetorch.quint8",short,FALSE,50.3995
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PyTorch,functional.hardtanh,"functional.hardtanh_dims(256,1024)_contigFalse_inplaceFalse_dtypetorch.qint8",short,FALSE,46.9813
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PyTorch,functional.hardtanh,"functional.hardtanh_dims(256,1024)_contigFalse_inplaceFalse_dtypetorch.qint32",short,FALSE,59.2295
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PyTorch,functional.hardsigmoid,"functional.hardsigmoid_dims(3,4,5)_contigFalse_inplaceFalse_dtypetorch.quint8",short,FALSE,6.5189
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@ -1316,4 +1316,4 @@ PyTorch,where,"where_cond_shape(8,16,1)_input_shape(1,)_other_shape(1,)_cpu_dtyp
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PyTorch,where,"where_cond_shape(8,16,1)_input_shape(16,1)_other_shape(8,16,1)_cpu_dtypetorch.float32",short,FALSE,5.763
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PyTorch,where,"where_cond_shape(8,16,1)_input_shape(8,1,1)_other_shape(1,)_cpu_dtypetorch.float32",short,FALSE,5.744666667
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PyTorch,clamp,clamp_M512_N512_cpu,short,FALSE,15.26233333
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PyTorch,gelu,gelu_M512_N512_cpu,short,FALSE,31.33166667
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PyTorch,gelu,gelu_M512_N512_cpu,short,FALSE,31.33166667
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