From 02b806e00a24fa9c6e34187980700e1af927e817 Mon Sep 17 00:00:00 2001
From: Ross Wightman <rwightman@gmail.com>
Date: Fri, 1 Apr 2022 16:34:23 -0700
Subject: [PATCH] Add PyTorch 1.11 train benchmark numbers

---
 ...ark-train-amp-nchw-pt111-cu113-rtx3090.csv | 756 ++++++++++++++++++
 ...ark-train-amp-nhwc-pt111-cu113-rtx3090.csv | 752 +++++++++++++++++
 2 files changed, 1508 insertions(+)
 create mode 100644 results/benchmark-train-amp-nchw-pt111-cu113-rtx3090.csv
 create mode 100644 results/benchmark-train-amp-nhwc-pt111-cu113-rtx3090.csv

diff --git a/results/benchmark-train-amp-nchw-pt111-cu113-rtx3090.csv b/results/benchmark-train-amp-nchw-pt111-cu113-rtx3090.csv
new file mode 100644
index 00000000..40396925
--- /dev/null
+++ b/results/benchmark-train-amp-nchw-pt111-cu113-rtx3090.csv
@@ -0,0 +1,756 @@
+model,train_samples_per_sec,train_step_time,train_batch_size,train_img_size,param_count
+tinynet_e,9380.97,53.881,512,106,2.04
+mobilenetv3_small_050,7276.68,69.643,512,224,1.59
+tf_mobilenetv3_small_minimal_100,6334.14,80.291,512,224,2.04
+mobilenetv3_small_075,5920.21,85.765,512,224,2.04
+lcnet_035,5760.61,88.397,512,224,1.64
+mobilenetv3_small_100,5583.48,90.99,512,224,2.54
+tf_mobilenetv3_small_075,5569.37,91.204,512,224,2.04
+levit_128s,5426.95,93.402,512,224,7.78
+lcnet_050,5425.23,93.895,512,224,1.88
+tf_mobilenetv3_small_100,5275.47,96.328,512,224,2.54
+tinynet_d,4879.29,104.179,512,152,2.34
+mixer_s32_224,4491.84,113.42,512,224,19.1
+vit_small_patch32_224,4321.32,117.658,512,224,22.88
+lcnet_075,4147.31,122.971,512,224,2.36
+levit_128,3971.6,127.764,512,224,9.21
+vit_tiny_r_s16_p8_224,3957.53,128.516,512,224,6.34
+lcnet_100,3524.02,144.807,512,224,2.95
+mnasnet_small,3488.23,145.878,512,224,2.03
+levit_192,3436.74,147.842,512,224,10.95
+regnetx_002,3423.6,148.87,512,224,2.68
+regnety_002,3178.35,160.128,512,224,3.16
+mobilenetv2_035,3069.55,166.033,512,224,1.68
+gernet_s,2949.06,172.893,512,224,8.17
+mnasnet_050,2821.34,180.673,512,224,2.22
+ssl_resnet18,2720.94,187.823,512,224,11.69
+swsl_resnet18,2720.55,187.842,512,224,11.69
+gluon_resnet18_v1b,2718.42,187.998,512,224,11.69
+resnet18,2711.83,188.459,512,224,11.69
+semnasnet_050,2700.91,188.67,512,224,2.08
+tinynet_c,2654.89,191.851,512,184,2.46
+mobilenetv2_050,2650.81,192.34,512,224,1.97
+levit_256,2620.65,194.218,512,224,18.89
+lcnet_150,2613.69,195.4,512,224,4.5
+regnetx_004,2532.79,201.109,512,224,5.16
+seresnet18,2519.64,202.716,512,224,11.78
+legacy_seresnet18,2461.74,207.479,512,224,11.78
+ese_vovnet19b_slim_dw,2456.97,207.908,512,224,1.9
+mobilenetv3_large_075,2342.92,217.677,512,224,3.99
+tf_mobilenetv3_large_minimal_100,2311.18,220.824,512,224,3.92
+vit_tiny_patch16_224,2249.49,226.757,512,224,5.72
+levit_256d,2248.95,226.128,512,224,26.21
+deit_tiny_patch16_224,2244.74,227.248,512,224,5.72
+tf_mobilenetv3_large_075,2222.25,229.522,512,224,3.99
+deit_tiny_distilled_patch16_224,2207.23,231.107,512,224,5.91
+ghostnet_050,2193.43,232.046,512,224,2.59
+mnasnet_075,2163.05,235.897,512,224,3.17
+mobilenetv3_rw,2147.03,237.6,512,224,5.48
+mobilenetv3_large_100_miil,2135.44,238.882,512,224,5.48
+mobilenetv3_large_100,2134.66,238.979,512,224,5.48
+resnet18d,2086.64,244.99,512,224,11.71
+pit_ti_distilled_224,2085.77,244.59,512,224,5.1
+pit_ti_224,2083.57,244.847,512,224,4.85
+hardcorenas_a,2050.08,249.015,512,224,5.26
+regnetx_006,2048.56,249.103,512,224,6.2
+tf_mobilenetv3_large_100,2046.24,249.335,512,224,5.48
+ese_vovnet19b_slim,1997.73,255.915,512,224,3.17
+mnasnet_100,1996.94,255.609,512,224,4.38
+mnasnet_b1,1993.53,256.025,512,224,4.38
+xcit_nano_12_p16_224_dist,1946.62,261.255,512,224,3.05
+xcit_nano_12_p16_224,1946.1,261.308,512,224,3.05
+semnasnet_075,1927.77,264.67,512,224,2.91
+hardcorenas_b,1912.19,266.758,512,224,5.18
+mobilenetv2_075,1888.29,270.368,512,224,2.64
+hardcorenas_c,1885.12,270.645,512,224,5.52
+tf_efficientnetv2_b0,1880.38,271.08,512,224,7.14
+tinynet_b,1857.15,274.614,512,188,3.73
+regnety_004,1855.83,274.756,512,224,4.34
+resnetblur18,1846.1,276.978,512,224,11.69
+regnety_006,1808.76,282.043,512,224,6.06
+hardcorenas_d,1808.52,281.873,512,224,7.5
+mnasnet_a1,1796.84,284.044,512,224,3.89
+semnasnet_100,1784.41,286.019,512,224,3.89
+spnasnet_100,1782.41,286.288,512,224,4.42
+skresnet18,1776.65,287.57,512,224,11.96
+mobilenetv2_100,1761.25,289.902,512,224,3.5
+mixer_b32_224,1711.23,298.43,512,224,60.29
+regnetx_008,1669.43,305.887,512,224,7.26
+levit_384,1662.81,306.81,512,224,39.13
+vit_base_patch32_224,1658.09,307.969,512,224,88.22
+vit_base_patch32_224_sam,1657.82,308.015,512,224,88.22
+efficientnet_lite0,1636.56,312.086,512,224,4.65
+visformer_tiny,1629.51,313.524,512,224,10.32
+gluon_resnet34_v1b,1626.25,314.261,512,224,21.8
+resnet34,1624.32,314.625,512,224,21.8
+tv_resnet34,1622.42,314.985,512,224,21.8
+ghostnet_100,1610.26,316.618,512,224,5.18
+hardcorenas_f,1606.37,317.568,512,224,8.2
+pit_xs_distilled_224,1596.23,319.885,512,224,11.0
+pit_xs_224,1595.39,320.023,512,224,10.62
+hardcorenas_e,1595.11,319.841,512,224,8.07
+tinynet_a,1592.8,320.187,512,192,6.19
+resmlp_12_distilled_224,1562.43,326.888,512,224,15.35
+resmlp_12_224,1562.2,326.933,512,224,15.35
+regnety_008,1550.03,329.315,512,224,6.26
+tf_efficientnet_lite0,1547.08,330.18,512,224,4.65
+mixer_s16_224,1538.34,332.27,512,224,18.53
+fbnetc_100,1532.35,333.142,512,224,5.57
+seresnet34,1494.24,341.776,512,224,21.96
+mnasnet_140,1493.96,341.916,512,224,7.12
+nf_regnet_b0,1481.15,344.453,512,256,8.76
+legacy_seresnet34,1458.06,350.271,512,224,21.96
+gmixer_12_224,1449.53,352.403,512,224,12.7
+gernet_m,1442.79,354.129,512,224,21.14
+ese_vovnet19b_dw,1440.24,354.984,512,224,6.54
+vit_small_patch32_384,1423.05,358.931,512,384,22.92
+nf_resnet26,1422.6,359.386,512,224,16.0
+efficientnet_b0,1413.79,270.572,384,224,5.29
+dla46_c,1408.04,362.893,512,224,1.3
+rexnetr_100,1385.71,275.935,384,224,4.88
+mobilenetv2_110d,1384.57,276.313,384,224,4.52
+rexnet_100,1381.06,276.903,384,224,4.8
+vit_tiny_r_s16_p8_384,1371.38,279.143,384,384,6.36
+ghostnet_130,1367.64,372.982,512,224,7.36
+resnet34d,1367.17,373.876,512,224,21.82
+tf_efficientnet_b0,1353.9,282.522,384,224,5.29
+tf_efficientnet_b0_ap,1353.18,282.683,384,224,5.29
+tf_efficientnet_b0_ns,1352.63,282.744,384,224,5.29
+selecsls42,1349.71,378.706,512,224,30.35
+selecsls42b,1347.34,379.337,512,224,32.46
+gmlp_ti16_224,1340.35,284.915,384,224,5.87
+regnetz_005,1326.54,384.587,512,224,7.12
+crossvit_tiny_240,1322.74,385.447,512,240,7.01
+resnet26,1321.4,386.974,512,224,16.0
+semnasnet_140,1315.96,388.179,512,224,6.11
+xcit_tiny_12_p16_224,1309.91,389.1,512,224,6.72
+xcit_tiny_12_p16_224_dist,1303.81,390.894,512,224,6.72
+hrnet_w18_small,1302.26,391.765,512,224,13.19
+efficientnet_b1_pruned,1277.21,399.368,512,240,6.33
+mobilevit_xxs,1270.89,301.046,384,256,1.27
+mobilenetv2_140,1250.7,306.236,384,224,6.11
+poolformer_s12,1245.33,410.466,512,224,11.92
+crossvit_9_240,1236.49,309.127,384,240,8.55
+nf_seresnet26,1207.14,423.49,512,224,17.4
+tf_efficientnetv2_b1,1198.02,319.027,384,240,8.14
+repvgg_b0,1184.29,431.28,512,224,15.82
+crossvit_9_dagger_240,1177.9,324.572,384,240,8.78
+selecsls60,1152.93,443.193,512,224,30.67
+mixnet_s,1150.64,443.717,512,224,4.13
+selecsls60b,1149.12,444.678,512,224,32.77
+efficientnet_es,1142.77,447.293,512,224,5.44
+efficientnet_es_pruned,1141.22,447.892,512,224,5.44
+nf_ecaresnet26,1137.4,449.596,512,224,16.0
+resnet26d,1125.5,454.383,512,224,16.01
+tf_efficientnet_es,1120.47,456.18,512,224,5.44
+efficientnet_lite1,1109.69,229.723,256,240,5.42
+rexnetr_130,1097.15,232.191,256,224,7.61
+tf_mixnet_s,1090.03,468.412,512,224,4.13
+convit_tiny,1087.94,469.614,512,224,5.71
+convnext_nano_hnf,1075.51,356.223,384,224,15.59
+dla34,1072.51,476.787,512,224,15.74
+tf_efficientnet_lite1,1061.0,240.288,256,240,5.42
+dla46x_c,1058.5,482.972,512,224,1.07
+rexnet_130,1051.04,242.43,256,224,7.56
+regnetx_016,1042.11,490.415,512,224,9.19
+mobilenetv2_120d,1036.53,245.787,256,224,5.83
+skresnet34,1033.13,494.425,512,224,22.28
+vit_small_patch16_224,1032.86,370.943,384,224,22.05
+deit_small_patch16_224,1031.61,371.386,384,224,22.05
+deit_small_distilled_patch16_224,1011.7,378.721,384,224,22.44
+dla60x_c,1011.12,505.401,512,224,1.32
+ecaresnet50d_pruned,1009.57,506.231,512,224,19.94
+gernet_l,1007.43,507.303,512,256,31.08
+efficientnet_b0_g16_evos,992.51,385.814,384,224,8.11
+rexnetr_150,973.93,261.684,256,224,9.78
+vit_base2_patch32_256,970.35,526.818,512,256,119.46
+pit_s_distilled_224,963.9,264.693,256,224,24.04
+pit_s_224,963.25,264.885,256,224,23.46
+fbnetv3_b,936.5,408.4,384,256,8.6
+rexnet_150,934.54,272.774,256,224,9.73
+repvgg_a2,931.84,548.616,512,224,28.21
+legacy_seresnext26_32x4d,930.69,411.955,384,224,16.79
+regnety_016,921.99,553.558,512,224,11.2
+resnest14d,909.12,562.716,512,224,10.61
+efficientnet_cc_b0_4e,892.75,428.931,384,224,13.31
+efficientnet_cc_b0_8e,889.3,430.599,384,224,24.01
+coat_lite_tiny,885.61,432.738,384,224,5.72
+nf_regnet_b1,883.44,578.138,512,288,10.22
+resnetv2_50,883.05,579.001,512,224,25.55
+resnext26ts,882.89,434.405,384,256,10.3
+resnet26t,880.13,581.227,512,256,16.01
+tf_efficientnetv2_b2,877.18,290.276,256,260,10.1
+fbnetv3_d,875.63,290.586,256,256,10.31
+nf_regnet_b2,875.24,583.366,512,272,14.31
+tf_efficientnet_cc_b0_4e,872.5,438.913,384,224,13.31
+tf_efficientnet_cc_b0_8e,867.49,441.45,384,224,24.01
+efficientnet_b0_gn,860.35,296.448,256,224,5.29
+eca_resnext26ts,852.81,299.643,256,256,10.3
+seresnext26ts,848.06,301.17,256,256,10.39
+botnet26t_256,835.32,459.139,384,256,12.49
+gluon_resnet50_v1b,835.19,458.946,384,224,25.56
+twins_svt_small,835.02,458.264,384,224,24.06
+swsl_resnet50,834.38,459.391,384,224,25.56
+resnet50,833.17,460.051,384,224,25.56
+tf_efficientnet_b1_ap,832.71,305.903,256,240,7.79
+tf_efficientnet_b1,832.37,306.044,256,240,7.79
+tf_efficientnet_b1_ns,831.62,306.366,256,240,7.79
+tv_resnet50,831.54,460.947,384,224,25.56
+efficientnet_b2_pruned,831.45,306.38,256,260,8.31
+seresnext26tn_32x4d,831.09,461.371,384,224,16.81
+seresnext26d_32x4d,830.66,461.598,384,224,16.81
+gcresnext26ts,830.6,307.372,256,256,10.48
+seresnext26t_32x4d,830.1,461.943,384,224,16.81
+ssl_resnet50,828.96,462.397,384,224,25.56
+coat_lite_mini,825.96,464.063,384,224,11.01
+vgg11,818.58,625.301,512,224,132.86
+halonet26t,813.08,471.69,384,256,12.48
+vit_small_resnet26d_224,812.32,471.613,384,224,63.61
+eca_botnext26ts_256,804.88,317.468,256,256,10.59
+efficientnet_lite2,800.14,318.978,256,260,6.09
+efficientnet_b1,797.8,319.366,256,256,7.79
+resnetv2_50t,793.9,644.111,512,224,25.57
+ecaresnext26t_32x4d,792.87,483.752,384,224,15.41
+ecaresnext50t_32x4d,790.88,484.99,384,224,15.41
+resnetv2_50d,790.5,646.873,512,224,25.57
+tresnet_m,787.27,647.568,512,224,31.39
+convnext_tiny,782.73,326.109,256,224,28.59
+eca_halonext26ts,781.32,327.03,256,256,10.76
+vovnet39a,779.14,656.53,512,224,22.6
+ecaresnet101d_pruned,778.75,655.702,512,224,24.88
+mixnet_m,778.63,491.619,384,224,5.01
+cspresnet50,774.32,495.068,384,256,21.62
+tf_efficientnet_lite2,771.04,331.043,256,260,6.09
+gluon_resnet50_v1c,769.5,498.184,384,224,25.58
+ecaresnetlight,767.59,666.098,512,224,30.16
+resmlp_24_224,766.31,332.575,256,224,30.02
+resmlp_24_distilled_224,766.21,332.58,256,224,30.02
+cspresnext50,765.28,500.93,384,224,20.57
+resnet50t,753.13,509.003,384,224,25.57
+resnet50d,752.95,509.12,384,224,25.58
+gluon_resnet50_v1d,752.94,509.122,384,224,25.58
+legacy_seresnet50,751.28,510.001,384,224,28.09
+mobilevit_xs,751.23,339.638,256,256,2.32
+tf_mixnet_m,748.19,511.684,384,224,5.01
+ese_vovnet39b,748.06,683.786,512,224,24.57
+resnet32ts,744.11,343.453,256,256,17.96
+visformer_small,743.29,515.928,384,224,40.22
+dpn68b,737.5,519.461,384,224,12.61
+selecsls84,735.99,694.378,512,224,50.95
+resnet33ts,732.63,348.809,256,256,19.68
+nf_seresnet50,732.06,523.375,384,224,28.09
+rexnetr_200,724.64,263.786,192,224,16.52
+lambda_resnet26t,724.61,529.342,384,256,10.96
+seresnet50,722.32,530.5,384,224,28.09
+dpn68,721.48,531.095,384,224,12.61
+res2net50_48w_2s,717.64,534.245,384,224,25.29
+gmixer_24_224,717.31,355.331,256,224,24.72
+eca_resnet33ts,712.11,358.824,256,256,19.68
+seresnet33ts,709.27,360.12,256,256,19.78
+bat_resnext26ts,708.45,360.137,256,256,10.73
+rexnet_200,703.57,271.754,192,224,16.37
+resnetblur50,702.19,546.026,384,224,25.56
+cspresnet50d,701.76,546.305,384,256,21.64
+vgg11_bn,698.67,549.368,384,224,132.87
+twins_pcpvt_small,698.21,364.986,256,224,24.11
+eca_vovnet39b,697.82,733.074,512,224,22.6
+efficientnet_em,694.64,551.807,384,240,6.9
+dla60,693.8,552.499,384,224,22.04
+tf_efficientnet_em,692.96,368.419,256,240,6.9
+cspresnet50w,692.76,553.433,384,256,28.12
+resnest26d,688.5,556.976,384,224,17.07
+gcresnet33ts,687.02,371.584,256,256,19.88
+tv_densenet121,686.65,371.007,256,224,7.98
+densenet121,686.51,371.091,256,224,7.98
+vit_small_r26_s32_224,685.79,371.994,256,224,36.43
+convnext_tiny_hnf,683.74,373.449,256,224,28.59
+xcit_nano_12_p16_384_dist,682.7,373.202,256,384,3.05
+xcit_tiny_24_p16_224_dist,681.26,372.348,256,224,12.12
+lambda_resnet26rpt_256,679.63,281.896,192,256,10.99
+xcit_tiny_24_p16_224,679.38,373.443,256,224,12.12
+vit_base_resnet26d_224,679.21,563.967,384,224,101.4
+resnetaa50d,678.8,564.84,384,224,25.58
+nf_ecaresnet50,673.73,568.984,384,224,25.56
+hrnet_w18_small_v2,672.52,758.874,512,224,15.6
+gluon_resnet50_v1s,671.98,570.574,384,224,25.68
+efficientnet_b0_g8_gn,661.67,385.796,256,224,6.56
+seresnet50t,659.6,581.03,384,224,28.1
+efficientnet_b3_pruned,657.34,387.781,256,300,9.86
+haloregnetz_b,656.48,388.419,256,224,11.68
+tv_resnext50_32x4d,651.27,588.791,384,224,25.03
+swsl_resnext50_32x4d,651.11,588.925,384,224,25.03
+gluon_resnext50_32x4d,650.97,589.059,384,224,25.03
+ssl_resnext50_32x4d,650.9,589.136,384,224,25.03
+resnext50_32x4d,649.99,589.957,384,224,25.03
+resnetrs50,648.71,590.781,384,224,35.69
+densenet121d,646.33,394.275,256,224,8.0
+regnetx_032,643.77,595.296,384,224,15.3
+resnetblur50d,642.77,397.429,256,224,25.58
+res2net50_26w_4s,636.71,601.86,384,224,25.7
+swin_tiny_patch4_window7_224,635.13,402.044,256,224,28.29
+skresnet50,634.96,603.369,384,224,25.8
+poolformer_s24,634.53,402.132,256,224,21.39
+gmlp_s16_224,632.58,301.939,192,224,19.42
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+senet154,141.16,676.729,96,224,115.09
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diff --git a/results/benchmark-train-amp-nhwc-pt111-cu113-rtx3090.csv b/results/benchmark-train-amp-nhwc-pt111-cu113-rtx3090.csv
new file mode 100644
index 00000000..8f7186d1
--- /dev/null
+++ b/results/benchmark-train-amp-nhwc-pt111-cu113-rtx3090.csv
@@ -0,0 +1,752 @@
+model,train_samples_per_sec,train_step_time,train_batch_size,train_img_size,param_count
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+resnet26t,1227.85,416.475,512,256,16.01
+ssl_resnet50,1223.5,417.643,512,224,25.56
+resnet50,1222.61,417.956,512,224,25.56
+tv_resnet50,1222.03,418.147,512,224,25.56
+swsl_resnet50,1222.0,418.189,512,224,25.56
+gluon_resnet50_v1b,1221.97,418.181,512,224,25.56
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+vit_tiny_r_s16_p8_384,1193.45,320.912,384,384,6.36
+rexnetr_150,1185.63,214.799,256,224,9.78
+fbnetv3_b,1184.86,322.487,384,256,8.6
+botnet26t_256,1168.73,327.971,384,256,12.49
+tf_efficientnetv2_b2,1157.41,219.649,256,260,10.1
+regnetx_004,1150.82,443.834,512,224,5.16
+repvgg_a2,1142.14,447.42,512,224,28.21
+skresnet34,1140.48,447.803,512,224,22.28
+resnetv2_50t,1134.35,450.541,512,224,25.57
+fbnetv3_d,1133.65,223.966,256,256,10.31
+resnetv2_50d,1131.93,451.499,512,224,25.57
+gluon_resnet50_v1c,1131.41,338.54,384,224,25.58
+halonet26t,1122.34,341.57,384,256,12.48
+convit_tiny,1108.09,461.02,512,224,5.71
+efficientnet_lite2,1096.26,232.544,256,260,6.09
+dla34,1094.33,467.287,512,224,15.74
+convnext_nano_hnf,1075.54,356.227,384,224,15.59
+resnet50d,1070.21,357.929,384,224,25.58
+gluon_resnet50_v1d,1070.13,357.997,384,224,25.58
+resnet50t,1068.62,358.508,384,224,25.57
+mixnet_s,1051.2,485.837,512,224,4.13
+legacy_seresnext26_32x4d,1051.18,486.414,512,224,16.79
+tf_efficientnet_lite2,1045.58,243.879,256,260,6.09
+vit_small_resnet26d_224,1042.37,367.395,384,224,63.61
+deit_small_patch16_224,1032.62,371.017,384,224,22.05
+vit_small_patch16_224,1027.63,372.823,384,224,22.05
+regnety_004,1027.25,497.255,512,224,4.34
+tf_efficientnet_b1_ns,1026.16,247.955,256,240,7.79
+tf_efficientnet_b1_ap,1026.11,248.006,256,240,7.79
+tf_efficientnet_b1,1025.11,248.193,256,240,7.79
+resnet32ts,1021.77,249.96,256,256,17.96
+deit_small_distilled_patch16_224,1010.79,379.058,384,224,22.44
+resnet33ts,1009.39,252.998,256,256,19.68
+res2net50_48w_2s,1006.25,380.82,384,224,25.29
+vovnet39a,1004.46,509.092,512,224,22.6
+seresnext26d_32x4d,1002.27,382.471,384,224,16.81
+seresnext26t_32x4d,1001.74,382.665,384,224,16.81
+seresnext26tn_32x4d,1001.47,382.779,384,224,16.81
+legacy_seresnet50,993.86,385.256,384,224,28.09
+tf_efficientnet_em,979.63,260.356,256,240,6.9
+efficientnet_em,978.46,260.687,256,240,6.9
+dla46x_c,973.77,525.047,512,224,1.07
+eca_resnet33ts,964.39,264.788,256,256,19.68
+pit_s_224,961.0,265.507,256,224,23.46
+pit_s_distilled_224,960.14,265.718,256,224,24.04
+tf_mixnet_s,958.59,532.877,512,224,4.13
+seresnet50,956.87,400.165,384,224,28.09
+efficientnet_b1,954.91,266.596,256,256,7.79
+seresnet33ts,954.85,267.313,256,256,19.78
+ecaresnetlight,952.86,536.422,512,224,30.16
+vit_base2_patch32_256,950.48,537.853,512,256,119.46
+ese_vovnet39b,947.73,539.578,512,224,24.57
+ecaresnext50t_32x4d,947.69,404.65,384,224,15.41
+ecaresnext26t_32x4d,947.22,404.844,384,224,15.41
+dla60,945.45,405.196,384,224,22.04
+gluon_resnet50_v1s,943.31,406.227,384,224,25.68
+resnetaa50d,941.94,406.82,384,224,25.58
+eca_vovnet39b,939.18,544.514,512,224,22.6
+vgg11,930.6,550.023,512,224,132.86
+gcresnet33ts,927.58,274.995,256,256,19.88
+lambda_resnet26rpt_256,921.55,207.755,192,256,10.99
+dla60x_c,921.01,554.951,512,224,1.32
+ecaresnet50d_pruned,911.85,560.565,512,224,19.94
+resnetblur50,909.58,421.362,384,224,25.56
+mobilevit_xs,909.51,210.0,192,256,2.32
+cspresnet50,906.79,422.612,384,256,21.62
+rexnetr_200,896.75,212.966,192,224,16.52
+coat_lite_tiny,890.79,430.193,384,224,5.72
+nf_seresnet50,886.81,431.807,384,224,28.09
+dpn68b,878.29,436.039,384,224,12.61
+selecsls84,872.56,585.545,512,224,50.95
+twins_svt_small,868.85,440.366,384,224,24.06
+hrnet_w18_small_v2,867.42,587.948,512,224,15.6
+seresnet50t,865.51,442.504,384,224,28.1
+cspresnext50,862.61,444.309,384,224,20.57
+resnetrs50,861.96,444.354,384,224,35.69
+cspresnet50w,860.12,445.567,384,256,28.12
+cspresnet50d,849.09,451.363,384,256,21.64
+densenet121,845.28,301.077,256,224,7.98
+tv_densenet121,845.28,301.063,256,224,7.98
+rexnet_150,842.23,302.82,256,224,9.73
+tv_resnext50_32x4d,836.18,458.41,384,224,25.03
+swsl_resnext50_32x4d,836.09,458.464,384,224,25.03
+res2net50_26w_4s,835.77,458.208,384,224,25.7
+coat_lite_mini,833.77,459.672,384,224,11.01
+vit_base_resnet26d_224,833.37,459.491,384,224,101.4
+resnext50_32x4d,832.87,460.244,384,224,25.03
+ssl_resnext50_32x4d,832.34,460.521,384,224,25.03
+dpn68,831.95,460.44,384,224,12.61
+gluon_resnext50_32x4d,831.77,460.799,384,224,25.03
+vovnet57a,828.64,616.994,512,224,36.64
+efficientnet_b2_pruned,825.77,308.457,256,260,8.31
+resnetblur50d,818.48,311.928,256,224,25.58
+skresnet50,810.12,472.628,384,224,25.8
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+tf_efficientnet_b2_ns,809.32,235.717,192,260,9.11
+tf_efficientnet_b2,809.06,235.843,192,260,9.11
+vgg11_bn,805.38,476.555,384,224,132.87
+densenet121d,805.31,316.045,256,224,8.0
+nf_ecaresnet50,804.89,476.102,384,224,25.56
+rexnet_130,801.42,318.304,256,224,7.56
+ecaresnet50d,793.07,483.245,384,224,25.58
+ese_vovnet57b,790.94,484.567,384,224,38.61
+regnetx_006,790.56,646.782,512,224,6.2
+gcresnet50t,788.09,323.372,256,256,25.9
+regnety_006,787.76,648.873,512,224,6.06
+convnext_tiny,781.17,326.737,256,224,28.59
+tf_inception_v3,774.78,494.217,384,299,23.83
+gluon_inception_v3,774.48,494.404,384,299,23.83
+seresnetaa50d,773.82,329.682,256,224,28.11
+inception_v3,772.99,495.38,384,299,23.83
+adv_inception_v3,769.85,497.351,384,299,23.83
+resmlp_24_distilled_224,767.92,331.893,256,224,30.02
+resnext50d_32x4d,765.61,333.516,256,224,25.05
+resmlp_24_224,762.25,334.383,256,224,30.02
+gmixer_24_224,759.72,335.461,256,224,24.72
+resnetv2_101,757.49,336.449,256,224,44.54
+res2net50_14w_8s,756.34,336.303,256,224,25.06
+xcit_nano_12_p16_384_dist,754.95,337.338,256,384,3.05
+sehalonet33ts,749.52,340.746,256,256,13.69
+densenetblur121d,739.98,344.167,256,224,8.0
+dla60_res2net,736.45,346.205,256,224,20.85
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+gluon_resnet101_v1b,731.02,348.601,256,224,44.55
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+resnet101,727.5,350.369,256,224,44.55
+xcit_tiny_24_p16_224,726.25,349.143,256,224,12.12
+xcit_tiny_24_p16_224_dist,725.28,349.489,256,224,12.12
+efficientnet_b2,724.21,263.654,192,288,9.11
+twins_pcpvt_small,724.17,351.883,256,224,24.11
+efficientnet_b2a,723.56,263.856,192,288,9.11
+ecaresnet101d_pruned,714.19,715.116,512,224,24.88
+nf_resnet50,710.87,539.322,384,288,25.56
+nf_resnet101,707.69,540.968,384,224,44.55
+seresnext50_32x4d,706.91,361.01,256,224,27.56
+gluon_seresnext50_32x4d,706.58,361.114,256,224,27.56
+efficientnet_b0_gn,705.84,361.599,256,224,5.29
+legacy_seresnext50_32x4d,704.96,362.028,256,224,27.56
+nf_regnet_b0,703.19,726.933,512,256,8.76
+darknet53,701.97,363.892,256,256,41.61
+resnetv2_101d,699.92,364.177,256,224,44.56
+densenet169,698.35,364.121,256,224,14.15
+gluon_resnet101_v1c,697.85,365.313,256,224,44.57
+dla60x,694.54,367.645,256,224,17.35
+poolformer_s24,690.11,369.675,256,224,21.39
+semobilevit_s,684.71,279.143,192,256,5.74
+efficientnetv2_rw_t,684.48,278.424,192,288,13.65
+vit_small_r26_s32_224,682.34,373.878,256,224,36.43
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+gluon_resnet101_v1d,674.08,378.237,256,224,44.57
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+xcit_small_12_p16_224,670.22,380.208,256,224,26.25
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+sebotnet33ts_256,666.38,191.3,128,256,13.7
+rexnet_200,665.99,287.162,192,224,16.37
+vgg13,663.21,578.818,384,224,133.05
+regnety_008,661.82,772.637,512,224,6.26
+wide_resnet50_2,661.04,580.088,384,224,68.88
+dla102,650.38,392.047,256,224,33.27
+gmlp_s16_224,648.9,294.316,192,224,19.42
+vit_base_resnet50d_224,646.39,394.444,256,224,110.97
+swin_tiny_patch4_window7_224,639.35,399.428,256,224,28.29
+ecaresnet26t,628.75,406.586,256,320,16.01
+repvgg_b1,627.31,815.089,512,224,57.42
+gluon_resnet101_v1s,624.3,408.497,256,224,44.67
+crossvit_small_240,624.04,408.587,256,240,26.86
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+eca_botnext26ts_256,618.03,413.613,256,256,10.59
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+eca_halonext26ts,604.41,422.932,256,256,10.76
+seresnext26ts,598.53,427.051,256,256,10.39
+eca_resnext26ts,598.25,427.346,256,256,10.3
+convnext_tiny_hnfd,592.58,430.992,256,224,28.63
+regnetx_008,591.8,864.35,512,224,7.26
+resnetv2_50x1_bit_distilled,589.64,324.794,192,224,25.55
+legacy_seresnet101,588.41,432.899,256,224,49.33
+gcresnext26ts,585.17,436.656,256,256,10.48
+halonet50ts,584.39,327.573,192,256,22.73
+xcit_nano_12_p8_224,583.42,437.05,256,224,3.05
+cait_xxs24_224,582.93,436.673,256,224,11.96
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+mixer_b16_224,580.44,440.268,256,224,59.88
+mixer_b16_224_miil,579.94,440.653,256,224,59.88
+swin_s3_tiny_224,578.76,441.339,256,224,28.33
+seresnet101,574.05,443.691,256,224,49.33
+mixnet_m,573.23,891.634,512,224,5.01
+res2net50_26w_6s,569.28,447.908,256,224,37.05
+vgg13_bn,568.79,449.813,256,224,133.05
+crossvit_15_240,568.46,335.957,192,240,27.53
+resnetblur101d,567.71,449.352,256,224,44.57
+cspdarknet53,565.64,451.547,256,256,27.64
+efficientnet_lite3,563.01,226.244,128,300,8.2
+tf_efficientnet_lite3,561.05,227.067,128,300,8.2
+crossvit_15_dagger_240,549.96,347.22,192,240,28.21
+resnext101_32x4d,548.6,465.031,256,224,44.18
+tf_mixnet_m,547.03,700.438,384,224,5.01
+swsl_resnext101_32x4d,546.13,467.192,256,224,44.18
+gluon_resnext101_32x4d,545.31,467.899,256,224,44.18
+ssl_resnext101_32x4d,545.31,467.944,256,224,44.18
+densenet201,539.32,353.029,192,224,20.01
+vgg16,536.49,715.548,384,224,138.36
+bat_resnext26ts,533.44,478.688,256,256,10.73
+nf_seresnet101,532.2,478.733,256,224,49.33
+vit_base_r26_s32_224,528.57,361.981,192,224,101.38
+resnetv2_152,524.49,485.916,256,224,60.19
+botnet50ts_256,524.41,243.109,128,256,22.74
+res2net101_26w_4s,523.46,486.536,256,224,45.21
+efficientnet_b3_pruned,519.43,491.117,256,300,9.86
+vit_base_patch32_384,517.32,494.013,256,384,88.3
+vit_large_patch32_224,511.41,498.976,256,224,306.54
+halo2botnet50ts_256,510.64,375.017,192,256,22.64
+mixer_l32_224,510.1,374.908,192,224,206.94
+swin_v2_cr_tiny_224,506.89,377.55,192,224,28.33
+resmlp_36_distilled_224,505.72,377.435,192,224,44.69
+resmlp_36_224,505.39,377.735,192,224,44.69
+vit_tiny_patch16_384,503.94,253.174,128,384,5.79
+res2next50,502.84,507.818,256,224,24.67
+dla102x,501.98,380.938,192,224,26.31
+swin_v2_cr_tiny_ns_224,501.36,381.688,192,224,28.33
+resnet152,499.83,381.783,192,224,60.19
+gluon_resnet152_v1b,499.79,381.933,192,224,60.19
+tv_resnet152,496.47,384.401,192,224,60.19
+xception,494.06,258.29,128,299,22.86
+visformer_tiny,491.83,1040.332,512,224,10.32
+mixnet_l,488.23,784.993,384,224,7.33
+gluon_resnet152_v1c,485.58,393.139,192,224,60.21
+resnet50_gn,484.73,395.256,192,224,25.56
+resnetv2_152d,484.59,393.938,192,224,60.2
+twins_pcpvt_base,480.18,397.102,192,224,43.83
+nest_tiny,477.31,267.267,128,224,17.06
+res2net50_26w_8s,476.93,534.581,256,224,48.4
+ecaresnet101d,475.58,536.508,256,224,44.57
+convnext_small,473.89,403.445,192,224,50.22
+gluon_resnet152_v1d,473.52,403.216,192,224,60.21
+tf_mixnet_l,470.86,542.123,256,224,7.33
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+vgg16_bn,469.97,544.386,256,224,138.37
+nf_ecaresnet101,465.87,547.628,256,224,44.55
+coat_lite_small,463.34,412.922,192,224,19.84
+poolformer_s36,458.24,417.134,192,224,30.86
+efficientnet_el,455.42,279.993,128,300,10.59
+efficientnet_el_pruned,454.32,280.643,128,300,10.59
+vgg19,451.86,849.574,384,224,143.67
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+ese_vovnet99b,448.97,568.658,256,224,63.2
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+nf_regnet_b3,442.03,577.378,256,320,18.59
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+dla60_res2next,437.89,583.208,256,224,17.03
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+dla169,436.98,436.866,192,224,53.39
+skresnext50_32x4d,435.09,586.972,256,224,27.48
+hrnet_w32,433.46,438.263,192,224,41.23
+vit_small_resnet50d_s16_224,432.94,442.239,192,224,57.53
+twins_svt_base,429.83,444.617,192,224,56.07
+hrnet_w18,419.32,605.846,256,224,21.3
+crossvit_18_240,400.15,317.858,128,240,43.27
+vgg19_bn,399.74,640.035,256,224,143.68
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+inception_v4,397.78,480.469,192,299,42.68
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+swin_small_patch4_window7_224,393.38,486.272,192,224,49.61
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+cait_xxs36_224,380.29,501.012,192,224,17.3
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+deit_base_distilled_patch16_224,378.28,506.739,192,224,87.34
+densenet161,376.13,337.907,128,224,28.68
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+efficientnet_b3a,354.6,359.335,128,320,12.23
+resnet200,354.57,357.998,128,224,64.67
+xception41p,353.88,360.846,128,299,26.91
+regnety_016,353.36,1447.082,512,224,11.2
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+beit_base_patch16_224,352.29,543.93,192,224,86.53
+resnest14d,349.84,1463.045,512,224,10.61
+hrnet_w30,346.82,733.381,256,224,37.71
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+ig_resnext101_32x48d,8.5,1880.808,16,224,828.41
+volo_d5_512,8.05,369.448,3,512,296.09
+nfnet_f4,6.47,1849.874,12,512,316.07
+dm_nfnet_f4,6.2,1929.065,12,512,316.07
+cait_m48_448,4.75,415.897,2,448,356.46
+nfnet_f5,4.63,1719.792,8,544,377.21
+resnetv2_152x4_bitm,4.49,443.185,2,480,936.53
+dm_nfnet_f5,4.47,1782.137,8,544,377.21
+nfnet_f6,3.5,1707.387,6,576,438.36
+dm_nfnet_f6,3.39,1759.608,6,576,438.36
+nfnet_f7,2.67,1489.771,4,608,499.5
+efficientnet_l2,2.09,473.733,1,800,480.31
+tf_efficientnet_l2_ns,2.09,474.031,1,800,480.31