Add update NCHW and NHWC inference benchmark numbers for current models. Flip name of 'sam' vit models in results files

Author: rwightman

results/model_benchmark_amp_nchw_rtx3090.csv

@@ -452,10 +452,10 @@ visformer_small,in1k
 vit_base_patch16_224,in21k
 vit_base_patch16_224_miil,in21k
 vit_base_patch16_384,in21k
-vit_base_patch16_sam_224,in1k
+vit_base_patch16_224_sam,in1k
 vit_base_patch32_224,in21k
 vit_base_patch32_384,in21k
-vit_base_patch32_sam_224,in1k
+vit_base_patch32_224_sam,in1k
 vit_base_r50_s16_384,in21k
 vit_large_patch16_224,in21k
 vit_large_patch16_384,in21k

results/model_benchmark_amp_nhwc_rtx3090.csv

@@ -309,7 +309,7 @@ gluon_resnet152_v1c,94.160,5.840,98.640,1.360,60.21,224,0.875,bicubic
 gmlp_s16_224,94.150,5.850,98.500,1.500,19.42,224,0.875,bicubic
 efficientnet_b2_pruned,94.140,5.860,98.530,1.470,8.31,260,0.890,bicubic
 regnety_064,94.140,5.860,98.730,1.270,30.58,224,0.875,bicubic
-vit_base_patch16_sam_224,94.140,5.860,98.670,1.330,86.57,224,0.900,bicubic
+vit_base_patch16_224_sam,94.140,5.860,98.670,1.330,86.57,224,0.900,bicubic
 regnetx_160,94.120,5.880,98.740,1.260,54.28,224,0.875,bicubic
 nf_regnet_b1,94.120,5.880,98.630,1.370,10.22,288,0.900,bicubic
 dpn98,94.110,5.890,98.580,1.420,61.57,224,0.875,bicubic
@@ -513,7 +513,7 @@ semnasnet_075,90.080,9.920,97.430,2.570,2.91,224,0.875,bicubic
 ghostnet_100,90.030,9.970,97.370,2.630,5.18,224,0.875,bilinear
 pit_ti_224,89.950,10.050,97.450,2.550,4.85,224,0.900,bicubic
 tv_resnet34,89.930,10.070,97.340,2.660,21.80,224,0.875,bilinear
-vit_base_patch32_sam_224,89.750,10.250,97.000,3.000,88.22,224,0.900,bicubic
+vit_base_patch32_224_sam,89.750,10.250,97.000,3.000,88.22,224,0.900,bicubic
 tf_mobilenetv3_large_075,89.680,10.320,97.210,2.790,3.99,224,0.875,bilinear
 xcit_nano_12_p16_224_dist,89.680,10.320,97.090,2.910,3.05,224,1.000,bicubic
 deit_tiny_patch16_224,89.670,10.330,97.440,2.560,5.72,224,0.900,bicubic

results/model_metadata_in1k.csv

@@ -373,7 +373,7 @@ crossvit_tiny_240,9.107,90.893,34.587,65.413,7.01,240,0.875,bicubic,-81.143,-63.
 resnest26d,9.080,90.920,37.840,62.160,17.07,224,0.875,bilinear,-84.240,-60.190,+10
 vit_tiny_patch16_224,9.067,90.933,34.600,65.400,5.72,224,0.900,bicubic,-82.693,-63.440,+98
 regnety_040,9.013,90.987,37.040,62.960,20.65,224,0.875,bicubic,-84.847,-61.610,-40
-vit_base_patch16_sam_224,8.987,91.013,36.160,63.840,86.57,224,0.900,bicubic,-85.153,-62.510,-64
+vit_base_patch16_224_sam,8.987,91.013,36.160,63.840,86.57,224,0.900,bicubic,-85.153,-62.510,-64
 gluon_resnext50_32x4d,8.973,91.027,36.307,63.693,25.03,224,0.875,bicubic,-84.837,-62.103,-36
 rexnet_100,8.907,91.093,36.373,63.627,4.80,224,0.875,bicubic,-84.123,-62.017,+21
 seresnext26t_32x4d,8.893,91.107,36.920,63.080,16.81,224,0.875,bicubic,-83.927,-61.450,+34
@@ -476,7 +476,7 @@ resnext26ts,4.680,95.320,29.013,70.987,10.30,256,0.900,bicubic,-87.190,-68.907,-
 selecsls42b,4.667,95.333,28.587,71.413,32.46,224,0.875,bicubic,-87.613,-69.553,-30
 tf_efficientnet_lite1,4.613,95.387,28.387,71.613,5.42,240,0.882,bicubic,-88.007,-69.683,-49
 mobilenetv2_120d,4.533,95.467,29.280,70.720,5.83,224,0.875,bicubic,-87.867,-68.770,-37
-vit_base_patch32_sam_224,4.333,95.667,24.387,75.613,88.22,224,0.900,bicubic,-85.417,-72.613,+37
+vit_base_patch32_224_sam,4.333,95.667,24.387,75.613,88.22,224,0.900,bicubic,-85.417,-72.613,+37
 efficientnet_es_pruned,4.213,95.787,26.533,73.467,5.44,224,0.875,bicubic,-86.967,-71.217,+5
 tinynet_b,4.187,95.813,26.707,73.293,3.73,188,0.875,bicubic,-86.743,-70.963,+13
 fbnetc_100,4.133,95.867,25.933,74.067,5.57,224,0.875,bilinear,-86.577,-71.277,+18

results/results-imagenet-a-clean.csv

@@ -304,7 +304,7 @@ dpn98,93.920,6.080,98.920,1.080,61.57,224,0.875,bicubic
 gluon_resnet152_v1c,93.890,6.110,98.800,1.200,60.21,224,0.875,bicubic
 regnetx_160,93.890,6.110,99.090,0.910,54.28,224,0.875,bicubic
 regnety_080,93.890,6.110,99.000,1.000,39.18,224,0.875,bicubic
-vit_base_patch16_sam_224,93.890,6.110,98.890,1.110,86.57,224,0.900,bicubic
+vit_base_patch16_224_sam,93.890,6.110,98.890,1.110,86.57,224,0.900,bicubic
 nf_regnet_b1,93.880,6.120,98.740,1.260,10.22,288,0.900,bicubic
 xception71,93.880,6.120,98.950,1.050,42.34,299,0.903,bicubic
 cspresnet50,93.860,6.140,98.860,1.140,21.62,256,0.887,bilinear
@@ -518,7 +518,7 @@ skresnet18,90.170,9.830,97.780,2.220,11.96,224,0.875,bicubic
 xcit_nano_12_p16_224_dist,90.170,9.830,97.760,2.240,3.05,224,1.000,bicubic
 resnet18d,89.990,10.010,97.830,2.170,11.71,224,0.875,bicubic
 hrnet_w18_small,89.880,10.120,97.900,2.100,13.19,224,0.875,bilinear
-vit_base_patch32_sam_224,89.860,10.140,97.600,2.400,88.22,224,0.900,bicubic
+vit_base_patch32_224_sam,89.860,10.140,97.600,2.400,88.22,224,0.900,bicubic
 mobilenetv2_100,89.830,10.170,97.830,2.170,3.50,224,0.875,bicubic
 vgg19,89.680,10.320,97.550,2.450,143.67,224,0.875,bilinear
 deit_tiny_patch16_224,89.620,10.380,97.960,2.040,5.72,224,0.900,bicubic

results/results-imagenet-a.csv

@@ -341,7 +341,7 @@ xception65,40.270,59.730,55.277,44.723,39.92,299,0.903,bicubic,-53.490,-43.583,-
 densenet201,40.267,59.733,56.700,43.300,20.01,224,0.875,bicubic,-52.423,-41.950,+84
 resnext50d_32x4d,40.163,59.837,55.487,44.513,25.05,224,0.875,bicubic,-53.647,-43.253,-23
 eca_resnet33ts,40.130,59.870,56.997,43.003,19.68,256,0.900,bicubic,-53.730,-41.893,-32
-vit_base_patch16_sam_224,40.103,59.897,55.430,44.570,86.57,224,0.900,bicubic,-53.787,-43.460,-37
+vit_base_patch16_224_sam,40.103,59.897,55.430,44.570,86.57,224,0.900,bicubic,-53.787,-43.460,-37
 hrnet_w48,40.097,59.903,56.640,43.360,77.47,224,0.875,bilinear,-53.933,-42.400,-53
 legacy_seresnet152,40.050,59.950,55.813,44.187,66.82,224,0.875,bilinear,-53.390,-43.037,+21
 hrnet_w30,40.030,59.970,57.117,42.883,37.71,224,0.875,bilinear,-53.360,-41.713,+29
@@ -452,7 +452,7 @@ eca_botnext26ts_256,36.670,63.330,52.477,47.523,10.59,256,0.950,bicubic,-56.690,
 hardcorenas_a,36.643,63.357,54.910,45.090,5.26,224,0.875,bilinear,-54.977,-43.260,+25
 levit_128s,36.623,63.377,53.137,46.863,7.78,224,0.900,bicubic,-54.877,-45.263,+27
 efficientnet_b0,36.603,63.397,53.487,46.513,5.29,224,0.875,bicubic,-55.877,-45.193,-14
-vit_base_patch32_sam_224,36.547,63.453,53.043,46.957,88.22,224,0.900,bicubic,-53.313,-44.557,+66
+vit_base_patch32_224_sam,36.547,63.453,53.043,46.957,88.22,224,0.900,bicubic,-53.313,-44.557,+66
 xcit_nano_12_p8_224_dist,36.540,63.460,52.883,47.117,3.05,224,1.000,bicubic,-55.880,-45.647,-10
 tf_efficientnet_em,36.370,63.630,52.843,47.157,6.90,240,0.882,bicubic,-56.810,-45.827,-66
 skresnet18,36.320,63.680,54.193,45.807,11.96,224,0.875,bicubic,-53.850,-43.587,+59

results/results-imagenet-r-clean.csv

@@ -275,7 +275,7 @@ vit_large_patch32_384,85.911,14.089,97.368,2.632,306.63,384,1.000,bicubic,+4.401
 tf_efficientnetv2_b2,85.900,14.100,96.889,3.111,10.10,260,0.890,bicubic,+5.694,+1.847,+5
 tf_efficientnet_b2,85.898,14.102,96.862,3.139,9.11,260,0.890,bicubic,+5.818,+1.954,+11
 resnet50_gn,85.883,14.117,96.849,3.151,25.56,224,0.940,bicubic,+5.831,+1.903,+12
-vit_base_patch16_sam_224,85.877,14.123,96.697,3.303,86.57,224,0.900,bicubic,+5.635,+1.941,-2
+vit_base_patch16_224_sam,85.877,14.123,96.697,3.303,86.57,224,0.900,bicubic,+5.635,+1.941,-2
 seresnet50,85.853,14.147,97.009,2.991,28.09,224,0.875,bicubic,+5.589,+1.937,-5
 repvgg_b2g4,85.849,14.151,96.812,3.188,61.76,224,0.875,bilinear,+6.479,+2.126,+47
 gluon_resnet101_v1d,85.847,14.153,96.663,3.337,44.57,224,0.875,bicubic,+5.431,+1.647,-18
@@ -516,7 +516,7 @@ tv_resnet34,80.389,19.611,94.438,5.562,21.80,224,0.875,bilinear,+7.081,+3.014,-3
 resnet18d,80.385,19.615,94.246,5.754,11.71,224,0.875,bicubic,+8.135,+3.558,+8
 mobilenetv2_100,80.255,19.745,94.197,5.803,3.50,224,0.875,bicubic,+7.289,+3.179,0
 xcit_nano_12_p16_224_dist,80.216,19.784,94.357,5.643,3.05,224,1.000,bicubic,+7.914,+3.495,+5
-vit_base_patch32_sam_224,80.210,19.790,93.823,6.177,88.22,224,0.900,bicubic,+6.518,+2.811,-11
+vit_base_patch32_224_sam,80.210,19.790,93.823,6.177,88.22,224,0.900,bicubic,+6.518,+2.811,-11
 ssl_resnet18,80.101,19.899,94.590,5.410,11.69,224,0.875,bilinear,+7.495,+3.166,-1
 tf_mobilenetv3_large_075,80.088,19.912,94.182,5.818,3.99,224,0.875,bilinear,+6.648,+2.834,-12
 deit_tiny_patch16_224,80.011,19.988,94.449,5.551,5.72,224,0.900,bicubic,+7.846,+3.329,+4

results/results-imagenet-r.csv

@@ -273,7 +273,7 @@ gluon_resnet101_v1s,80.302,19.698,95.160,4.840,44.67,224,0.875,bicubic
 tf_efficientnet_b2_ap,80.302,19.698,95.028,4.972,9.11,260,0.890,bicubic
 seresnet50,80.264,19.736,95.072,4.928,28.09,224,0.875,bicubic
 tf_efficientnet_el,80.250,19.750,95.130,4.870,10.59,300,0.904,bicubic
-vit_base_patch16_sam_224,80.242,19.758,94.756,5.244,86.57,224,0.900,bicubic
+vit_base_patch16_224_sam,80.242,19.758,94.756,5.244,86.57,224,0.900,bicubic
 regnetx_320,80.240,19.760,95.022,4.978,107.81,224,0.875,bicubic
 legacy_seresnext101_32x4d,80.228,19.772,95.014,4.986,48.96,224,0.875,bilinear
 repvgg_b3g4,80.212,19.788,95.106,4.894,83.83,224,0.875,bilinear
@@ -505,7 +505,7 @@ ghostnet_100,73.978,26.022,91.458,8.542,5.18,224,0.875,bilinear
 crossvit_9_240,73.970,26.030,91.964,8.036,8.55,240,0.875,bicubic
 xcit_nano_12_p8_224,73.918,26.082,92.170,7.830,3.05,224,1.000,bicubic
 regnetx_006,73.852,26.148,91.674,8.326,6.20,224,0.875,bicubic
-vit_base_patch32_sam_224,73.692,26.308,91.012,8.988,88.22,224,0.900,bicubic
+vit_base_patch32_224_sam,73.692,26.308,91.012,8.988,88.22,224,0.900,bicubic
 tf_mobilenetv3_large_075,73.440,26.560,91.348,8.652,3.99,224,0.875,bilinear
 vgg16_bn,73.350,26.650,91.504,8.496,138.37,224,0.875,bilinear
 crossvit_tiny_240,73.336,26.664,91.916,8.084,7.01,240,0.875,bicubic

results/results-imagenet-real.csv

@@ -314,7 +314,7 @@ fbnetv3_d,68.340,31.660,88.450,11.550,10.31,256,0.950,bilinear,-11.342,-6.500,-2
 resmlp_big_24_224,68.320,31.680,87.530,12.470,129.14,224,0.875,bicubic,-12.712,-7.490,-85
 efficientnet_b2_pruned,68.320,31.680,88.100,11.900,8.31,260,0.890,bicubic,-11.596,-6.754,-21
 gluon_resnext50_32x4d,68.300,31.700,87.290,12.710,25.03,224,0.875,bicubic,-11.068,-7.136,+12
-vit_base_patch16_sam_224,68.260,31.740,87.720,12.280,86.57,224,0.900,bicubic,-11.982,-7.036,-41
+vit_base_patch16_224_sam,68.260,31.740,87.720,12.280,86.57,224,0.900,bicubic,-11.982,-7.036,-41
 ecaresnet26t,68.230,31.770,88.800,11.200,16.01,320,0.950,bicubic,-11.618,-6.284,-18
 tf_efficientnet_lite3,68.230,31.770,87.740,12.260,8.20,300,0.904,bilinear,-11.588,-7.174,-15
 ese_vovnet39b,68.200,31.800,88.260,11.740,24.57,224,0.875,bicubic,-11.110,-6.456,+10
@@ -518,7 +518,7 @@ tf_mobilenetv3_large_075,60.400,39.600,81.950,18.050,3.99,224,0.875,bilinear,-13
 xcit_nano_12_p16_224_dist,60.240,39.760,82.500,17.500,3.05,224,1.000,bicubic,-12.062,-8.362,+5
 mobilenetv2_100,60.190,39.810,82.240,17.760,3.50,224,0.875,bicubic,-12.776,-8.778,-2
 resnet18d,60.180,39.820,82.310,17.690,11.71,224,0.875,bicubic,-12.070,-8.378,+4
-vit_base_patch32_sam_224,60.010,39.990,81.230,18.770,88.22,224,0.900,bicubic,-13.682,-9.782,-13
+vit_base_patch32_224_sam,60.010,39.990,81.230,18.770,88.22,224,0.900,bicubic,-13.682,-9.782,-13
 deit_tiny_patch16_224,59.830,40.170,82.660,17.340,5.72,224,0.900,bicubic,-12.336,-8.460,+4
 legacy_seresnet18,59.810,40.190,81.690,18.310,11.78,224,0.875,bicubic,-11.932,-8.642,+7
 vgg19,59.710,40.290,81.450,18.550,143.67,224,0.875,bilinear,-12.656,-9.420,-3