From 1331c145a353959a4b0d7b7e119a55ae0f4a98a6 Mon Sep 17 00:00:00 2001
From: Ross Wightman <rwightman@gmail.com>
Date: Sun, 23 Jan 2022 14:07:40 -0800
Subject: [PATCH] Add train benchmark results, adjust name scheme for inference
 and train benchmark files.

---
 ...rk-infer-amp-nchw-pt110-cu113-rtx3090.csv} |   0
 ...rk-infer-amp-nhwc-pt110-cu113-rtx3090.csv} |   0
 ...ark-train-amp-nchw-pt110-cu113-rtx3090.csv | 703 ++++++++++++++++++
 ...ark-train-amp-nhwc-pt110-cu113-rtx3090.csv | 699 +++++++++++++++++
 ...adata_in1k.csv => model_metadata-in1k.csv} |   0
 5 files changed, 1402 insertions(+)
 rename results/{model_benchmark_amp_nchw_rtx3090.csv => benchmark-infer-amp-nchw-pt110-cu113-rtx3090.csv} (100%)
 rename results/{model_benchmark_amp_nhwc_rtx3090.csv => benchmark-infer-amp-nhwc-pt110-cu113-rtx3090.csv} (100%)
 create mode 100644 results/benchmark-train-amp-nchw-pt110-cu113-rtx3090.csv
 create mode 100644 results/benchmark-train-amp-nhwc-pt110-cu113-rtx3090.csv
 rename results/{model_metadata_in1k.csv => model_metadata-in1k.csv} (100%)

diff --git a/results/model_benchmark_amp_nchw_rtx3090.csv b/results/benchmark-infer-amp-nchw-pt110-cu113-rtx3090.csv
similarity index 100%
rename from results/model_benchmark_amp_nchw_rtx3090.csv
rename to results/benchmark-infer-amp-nchw-pt110-cu113-rtx3090.csv
diff --git a/results/model_benchmark_amp_nhwc_rtx3090.csv b/results/benchmark-infer-amp-nhwc-pt110-cu113-rtx3090.csv
similarity index 100%
rename from results/model_benchmark_amp_nhwc_rtx3090.csv
rename to results/benchmark-infer-amp-nhwc-pt110-cu113-rtx3090.csv
diff --git a/results/benchmark-train-amp-nchw-pt110-cu113-rtx3090.csv b/results/benchmark-train-amp-nchw-pt110-cu113-rtx3090.csv
new file mode 100644
index 00000000..9337f189
--- /dev/null
+++ b/results/benchmark-train-amp-nchw-pt110-cu113-rtx3090.csv
@@ -0,0 +1,703 @@
+model,train_samples_per_sec,train_step_time,train_batch_size,train_img_size,param_count
+tinynet_e,8788.08,57.613,512,106,2.04
+mobilenetv3_small_050,6451.43,78.69,512,224,1.59
+tf_mobilenetv3_small_minimal_100,6231.46,81.639,512,224,2.04
+levit_128s,5345.65,94.962,512,224,7.78
+lcnet_035,5326.51,95.668,512,224,1.64
+mobilenetv3_small_075,5149.15,98.754,512,224,2.04
+lcnet_050,4879.43,104.466,512,224,1.88
+tf_mobilenetv3_small_075,4839.2,105.1,512,224,2.04
+mobilenetv3_small_100,4741.69,107.315,512,224,2.54
+tf_mobilenetv3_small_100,4474.54,113.738,512,224,2.54
+tinynet_d,4465.05,113.942,512,152,2.34
+mixer_s32_224,3957.52,128.859,512,224,19.1
+levit_128,3868.72,131.359,512,224,9.21
+lcnet_075,3674.09,138.887,512,224,2.36
+vit_small_patch32_224,3657.34,139.252,512,224,22.88
+vit_tiny_r_s16_p8_224,3407.13,149.506,512,224,6.34
+regnetx_002,3372.01,151.204,512,224,2.68
+levit_192,3357.19,151.505,512,224,10.95
+mnasnet_small,3158.42,161.274,512,224,2.03
+regnety_002,3119.2,163.263,512,224,3.16
+lcnet_100,3075.72,165.994,512,224,2.95
+mobilenetv2_035,3007.95,169.496,512,224,1.68
+gernet_s,2901.28,175.82,512,224,8.17
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+ssl_resnet18,2668.71,191.54,512,224,11.69
+resnet18,2662.83,191.947,512,224,11.69
+mobilenetv2_050,2596.25,196.482,512,224,1.97
+levit_256,2559.67,199.033,512,224,18.89
+regnetx_004,2499.65,203.84,512,224,5.16
+mnasnet_050,2494.39,204.524,512,224,2.22
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+tinynet_c,2389.53,213.326,512,184,2.46
+tf_mobilenetv3_large_minimal_100,2278.25,224.06,512,224,3.92
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+tf_mobilenetv3_large_075,2027.78,251.65,512,224,3.99
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+ese_vovnet19b_slim,1970.7,259.464,512,224,3.17
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+mobilenetv3_large_100,1936.66,263.562,512,224,5.48
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+semnasnet_075,1791.94,284.855,512,224,2.91
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+mnasnet_100,1686.2,302.919,512,224,4.38
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+dpn68b,728.18,526.241,384,224,12.61
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+selecsls84,719.68,710.264,512,224,50.95
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+seresnet33ts,700.84,364.51,256,256,19.78
+eca_resnet33ts,700.22,364.953,256,256,19.68
+resnetblur50,694.99,551.777,384,224,25.56
+cspresnet50d,694.84,551.823,384,256,21.64
+rexnet_200,693.57,275.752,192,224,16.37
+cspresnet50w,686.88,558.19,384,256,28.12
+eca_vovnet39b,683.56,748.398,512,224,22.6
+densenet121,682.9,373.209,256,224,7.98
+dla60,682.79,561.488,384,224,22.04
+efficientnet_b1,682.7,373.555,256,256,7.79
+tv_densenet121,681.14,374.178,256,224,7.98
+gcresnet33ts,680.99,374.966,256,256,19.88
+efficientnet_lite2,680.43,375.329,256,260,6.09
+resnest26d,672.85,570.012,384,224,17.07
+resnetaa50d,669.52,572.758,384,224,25.58
+vgg11_bn,669.19,382.326,256,224,132.87
+gluon_resnet50_v1s,664.71,576.903,384,224,25.68
+nf_ecaresnet50,663.54,577.843,384,224,25.56
+hrnet_w18_small_v2,663.05,769.959,512,224,15.6
+tf_efficientnet_lite2,656.12,389.28,256,260,6.09
+vit_small_r26_s32_224,654.12,390.216,256,224,36.43
+lambda_resnet26rpt_256,650.73,196.144,128,256,10.99
+vit_base_resnet26d_224,650.56,589.099,384,224,101.4
+seresnet50t,645.62,395.439,256,224,28.1
+gluon_resnext50_32x4d,643.1,596.344,384,224,25.03
+ssl_resnext50_32x4d,642.69,596.753,384,224,25.03
+resnext50_32x4d,642.56,596.871,384,224,25.03
+tv_resnext50_32x4d,642.26,597.116,384,224,25.03
+swsl_resnext50_32x4d,642.22,597.166,384,224,25.03
+haloregnetz_b,639.45,398.971,256,224,11.68
+resnetrs50,639.32,599.548,384,224,35.69
+densenet121d,637.87,399.654,256,224,8.0
+regnetx_032,635.48,603.11,384,224,15.3
+resnetblur50d,634.6,402.62,256,224,25.58
+res2net50_26w_4s,625.68,407.946,256,224,25.7
+skresnet50,620.44,411.364,256,224,25.8
+ese_vovnet57b,618.38,620.149,384,224,38.61
+densenetblur121d,611.64,416.815,256,224,8.0
+ecaresnet50d,601.62,424.614,256,224,25.58
+adv_inception_v3,592.83,646.406,384,299,23.83
+resnext50d_32x4d,590.58,432.684,256,224,25.05
+gluon_inception_v3,589.45,650.157,384,299,23.83
+inception_v3,588.55,651.172,384,299,23.83
+tf_inception_v3,588.36,651.336,384,299,23.83
+seresnetaa50d,587.38,434.758,256,224,28.11
+sehalonet33ts,585.23,436.688,256,256,13.69
+coat_lite_tiny,580.33,660.876,384,224,5.72
+gmixer_24_224,577.9,441.611,256,224,24.72
+gcresnet50t,577.25,442.093,256,256,25.9
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+tresnet_l_448,99.64,1281.316,128,448,55.99
+beit_large_patch16_224,98.41,485.874,48,224,304.43
+resnetrs200,97.6,487.799,48,320,93.21
+ig_resnext101_32x16d,96.96,988.697,96,224,194.03
+swsl_resnext101_32x16d,96.88,989.444,96,224,194.03
+ssl_resnext101_32x16d,96.83,989.971,96,224,194.03
+xcit_small_24_p16_384_dist,92.8,514.221,48,384,47.67
+eca_nfnet_l2,92.75,687.481,64,384,56.72
+convnext_base_384_in22ft1k,92.09,519.541,48,384,88.59
+deit_base_patch16_384,90.25,353.802,32,384,86.86
+vit_base_patch16_384,90.2,353.987,32,384,86.86
+deit_base_distilled_patch16_384,88.49,360.855,32,384,87.63
+tf_efficientnetv2_m,88.2,359.811,32,480,54.14
+tf_efficientnetv2_m_in21ft1k,88.09,360.345,32,480,54.14
+xcit_tiny_12_p8_384_dist,87.2,548.793,48,384,6.71
+cait_xxs24_384,86.38,368.153,32,384,12.03
+resnetv2_101x1_bitm,85.15,374.386,32,448,44.54
+resnetv2_152x2_bit_teacher,85.01,374.341,32,224,236.34
+convmixer_768_32,84.46,1135.466,96,224,21.11
+resnest200e,77.86,611.828,48,320,70.2
+crossvit_18_dagger_408,77.59,307.496,24,408,44.61
+beit_base_patch16_384,76.84,311.346,24,384,86.74
+tresnet_xl_448,75.89,1261.775,96,448,78.44
+efficientnet_b5,75.33,422.385,32,456,30.39
+vit_large_r50_s32_384,73.95,430.573,32,384,329.09
+tf_efficientnet_b5_ap,73.87,430.874,32,456,30.39
+tf_efficientnet_b5_ns,73.84,431.06,32,456,30.39
+tf_efficientnet_b5,73.76,431.443,32,456,30.39
+regnetz_d8_evob,69.9,684.907,48,320,23.41
+nfnet_f2,69.7,685.799,48,352,193.78
+xcit_small_24_p8_224,69.53,457.315,32,224,47.63
+xcit_small_24_p8_224_dist,69.49,457.517,32,224,47.63
+nfnet_f2s,69.09,691.894,48,352,193.78
+xcit_medium_24_p16_384_dist,67.17,473.231,32,384,84.4
+resmlp_big_24_distilled_224,65.96,483.773,32,224,129.14
+resmlp_big_24_224,65.95,483.848,32,224,129.14
+resmlp_big_24_224_in22ft1k,65.95,483.866,32,224,129.14
+regnetz_d8_evos,64.24,496.339,32,320,23.46
+dm_nfnet_f2,62.49,765.031,48,352,193.78
+ecaresnet269d,60.75,522.332,32,352,102.09
+swin_base_patch4_window12_384,60.1,397.741,24,384,87.9
+cait_xs24_384,59.89,398.428,24,384,26.67
+pnasnet5large,59.35,535.626,32,331,86.06
+resnetrs270,58.4,542.338,32,352,129.86
+vit_base_patch8_224,58.07,274.782,16,224,86.58
+nasnetalarge,57.07,556.194,32,331,88.75
+cait_xxs36_384,56.42,422.115,24,384,17.37
+convnext_large_384_in22ft1k,54.47,585.847,32,384,197.77
+vit_base_r50_s16_384,54.27,293.3,16,384,98.95
+vit_base_resnet50_384,54.19,293.736,16,384,98.95
+xcit_medium_24_p8_224,51.72,615.776,32,224,84.32
+xcit_medium_24_p8_224_dist,51.69,616.066,32,224,84.32
+ig_resnext101_32x32d,51.67,617.889,32,224,468.53
+eca_nfnet_l3,49.71,640.359,32,448,72.04
+convmixer_1536_20,48.09,997.399,48,224,51.63
+xcit_small_12_p8_384_dist,46.72,512.057,24,384,26.21
+efficientnetv2_l,46.55,339.739,16,480,118.52
+tf_efficientnetv2_l_in21ft1k,46.43,340.391,16,480,118.52
+tf_efficientnetv2_l,46.41,340.685,16,480,118.52
+xcit_tiny_24_p8_384_dist,44.75,712.159,32,384,12.11
+cait_s24_384,44.7,355.627,16,384,47.06
+efficientnet_b6,41.67,381.28,16,528,43.04
+tf_efficientnet_b6_ap,41.13,386.3,16,528,43.04
+tf_efficientnet_b6,41.11,386.574,16,528,43.04
+tf_efficientnet_b6_ns,40.99,387.676,16,528,43.04
+xcit_large_24_p16_384_dist,40.96,582.937,24,384,189.1
+vit_huge_patch14_224,37.91,420.175,16,224,632.05
+resnetrs350,36.74,646.103,24,384,163.96
+swin_large_patch4_window12_384,36.6,435.55,16,384,196.74
+nfnet_f3,34.36,694.502,24,416,254.92
+nfnet_f3s,34.26,696.883,24,416,254.92
+convnext_xlarge_384_in22ft1k,34.01,468.853,16,384,350.2
+resnest269e,32.96,721.9,24,416,110.93
+dm_nfnet_f3,31.6,755.444,24,416,254.92
+resnetv2_50x3_bitm,31.14,513.017,16,448,217.32
+xcit_large_24_p8_224_dist,30.37,523.887,16,224,188.93
+xcit_large_24_p8_224,30.32,524.75,16,224,188.93
+cait_s36_384,29.46,404.043,12,384,68.37
+resnetv2_152x2_bit_teacher_384,29.25,408.083,12,384,236.34
+tf_efficientnetv2_xl_in21ft1k,28.52,415.17,12,512,208.12
+efficientnetv2_xl,28.5,415.628,12,512,208.12
+ig_resnext101_32x48d,27.26,585.456,16,224,828.41
+vit_large_patch16_384,26.62,299.076,8,384,304.72
+efficientnet_b7,25.52,310.186,8,600,66.35
+tf_efficientnet_b7,25.25,313.569,8,600,66.35
+tf_efficientnet_b7_ap,25.18,314.571,8,600,66.35
+tf_efficientnet_b7_ns,25.12,315.222,8,600,66.35
+resnetrs420,24.94,632.993,16,416,191.89
+xcit_small_24_p8_384_dist,23.58,505.912,12,384,47.63
+beit_large_patch16_384,22.66,351.145,8,384,305.0
+vit_giant_patch14_224,21.59,368.118,8,224,1012.61
+resnetv2_152x2_bitm,21.27,373.944,8,448,236.34
+nfnet_f4,18.45,645.682,12,512,316.07
+nfnet_f4s,18.35,649.188,12,512,316.07
+resnetv2_101x3_bitm,17.19,464.077,8,448,387.93
+xcit_medium_24_p8_384_dist,17.03,466.878,8,384,84.32
+dm_nfnet_f4,16.71,713.246,12,512,316.07
+efficientnet_b8,12.85,463.389,6,672,87.41
+tf_efficientnet_b8_ap,12.75,466.866,6,672,87.41
+tf_efficientnet_b8,12.73,467.671,6,672,87.41
+nfnet_f5,12.01,660.317,8,544,377.21
+nfnet_f5s,11.94,664.267,8,544,377.21
+cait_m36_384,11.32,526.589,6,384,271.22
+dm_nfnet_f5,10.99,722.011,8,544,377.21
+xcit_large_24_p8_384_dist,10.37,575.649,6,384,188.93
+nfnet_f6,9.06,655.713,6,576,438.36
+nfnet_f6s,9.04,657.589,6,576,438.36
+tf_efficientnet_l2_ns_475,8.8,449.624,4,475,480.31
+beit_large_patch16_512,8.36,356.829,3,512,305.67
+dm_nfnet_f6,8.32,713.582,6,576,438.36
+nfnet_f7,6.44,613.323,4,608,499.5
+nfnet_f7s,6.38,619.793,4,608,499.5
+cait_m48_448,4.6,430.517,2,448,356.46
+resnetv2_152x4_bitm,4.42,450.22,2,480,936.53
+tf_efficientnet_l2_ns,2.55,387.178,1,800,480.31
+efficientnet_l2,2.52,391.57,1,800,480.31
diff --git a/results/benchmark-train-amp-nhwc-pt110-cu113-rtx3090.csv b/results/benchmark-train-amp-nhwc-pt110-cu113-rtx3090.csv
new file mode 100644
index 00000000..82689dc1
--- /dev/null
+++ b/results/benchmark-train-amp-nhwc-pt110-cu113-rtx3090.csv
@@ -0,0 +1,699 @@
+model,train_samples_per_sec,train_step_time,train_batch_size,train_img_size,param_count
+mobilenetv3_small_050,10124.2,49.732,512,224,1.59
+lcnet_035,9556.39,53.122,512,224,1.64
+tinynet_e,9259.87,53.163,512,106,2.04
+lcnet_050,8204.13,61.959,512,224,1.88
+tf_mobilenetv3_small_minimal_100,8115.25,62.582,512,224,2.04
+tinynet_d,7842.33,64.591,512,152,2.34
+mobilenetv3_small_075,7645.76,66.298,512,224,2.04
+mobilenetv3_small_100,7391.62,68.594,512,224,2.54
+tf_mobilenetv3_small_075,7004.36,72.432,512,224,2.04
+tf_mobilenetv3_small_100,6775.26,74.902,512,224,2.54
+levit_128s,6249.41,81.115,512,224,7.78
+lcnet_075,5706.1,89.275,512,224,2.36
+lcnet_100,5288.36,96.356,512,224,2.95
+mnasnet_small,4565.41,111.287,512,224,2.03
+mnasnet_050,4479.4,113.569,512,224,2.22
+levit_128,4339.94,116.946,512,224,9.21
+mobilenetv2_035,4152.95,122.551,512,224,1.68
+mixer_s32_224,4131.98,123.414,512,224,19.1
+tinynet_c,4071.23,124.835,512,184,2.46
+gernet_s,4039.7,126.102,512,224,8.17
+semnasnet_050,3974.04,127.989,512,224,2.08
+levit_192,3756.95,135.269,512,224,10.95
+vit_small_patch32_224,3671.47,138.697,512,224,22.88
+lcnet_150,3645.88,139.972,512,224,4.5
+ssl_resnet18,3513.72,145.398,512,224,11.69
+gluon_resnet18_v1b,3512.34,145.445,512,224,11.69
+swsl_resnet18,3508.0,145.642,512,224,11.69
+mobilenetv2_050,3501.31,145.498,512,224,1.97
+resnet18,3496.86,146.104,512,224,11.69
+vit_tiny_r_s16_p8_224,3335.03,152.754,512,224,6.34
+mobilenetv3_large_075,3296.24,154.517,512,224,3.99
+ese_vovnet19b_slim_dw,3204.84,159.295,512,224,1.9
+tf_mobilenetv3_large_minimal_100,3175.97,160.546,512,224,3.92
+seresnet18,3165.67,161.261,512,224,11.78
+legacy_seresnet18,3081.19,165.707,512,224,11.78
+mnasnet_075,3078.06,165.602,512,224,3.17
+tf_mobilenetv3_large_075,3052.6,166.905,512,224,3.99
+ghostnet_050,2997.88,169.549,512,224,2.59
+mobilenetv3_rw,2978.91,171.068,512,224,5.48
+mobilenetv3_large_100_miil,2954.41,172.485,512,224,5.48
+mobilenetv3_large_100,2949.17,172.802,512,224,5.48
+levit_256,2853.53,178.318,512,224,18.89
+hardcorenas_a,2833.05,180.061,512,224,5.26
+mnasnet_100,2794.45,182.489,512,224,4.38
+mnasnet_b1,2793.42,182.553,512,224,4.38
+resnet18d,2767.22,184.677,512,224,11.71
+tf_mobilenetv3_large_100,2745.99,185.646,512,224,5.48
+tinynet_b,2724.35,186.966,512,188,3.73
+hardcorenas_b,2641.84,192.939,512,224,5.18
+semnasnet_075,2627.64,193.989,512,224,2.91
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+ese_vovnet19b_slim,2546.07,200.754,512,224,3.17
+mobilenetv2_075,2520.15,202.421,512,224,2.64
+spnasnet_100,2483.13,205.29,512,224,4.42
+tf_efficientnetv2_b0,2462.53,206.791,512,224,7.14
+hardcorenas_d,2435.65,209.09,512,224,7.5
+mnasnet_a1,2380.33,214.252,512,224,3.89
+semnasnet_100,2377.81,214.477,512,224,3.89
+mobilenetv2_100,2363.97,215.837,512,224,3.5
+regnetx_002,2307.34,221.263,512,224,2.68
+tinynet_a,2237.07,227.684,512,192,6.19
+fbnetc_100,2225.25,229.187,512,224,5.57
+ghostnet_100,2211.89,230.191,512,224,5.18
+regnety_002,2204.25,231.393,512,224,3.16
+efficientnet_lite0,2189.09,233.188,512,224,4.65
+hardcorenas_f,2163.36,235.624,512,224,8.2
+hardcorenas_e,2139.96,238.217,512,224,8.07
+tf_efficientnet_lite0,2037.27,250.609,512,224,4.65
+resnet34,2037.12,250.805,512,224,21.8
+tv_resnet34,2035.85,250.969,512,224,21.8
+gluon_resnet34_v1b,2035.71,250.984,512,224,21.8
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+gernet_m,1870.52,273.071,512,224,21.14
+ese_vovnet19b_dw,1864.29,274.174,512,224,6.54
+nf_resnet26,1859.82,274.839,512,224,16.0
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+selecsls60,1450.31,352.185,512,224,30.67
+selecsls60b,1447.33,352.935,512,224,32.77
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+resnet26t,1208.16,423.321,512,256,16.01
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+crossvit_tiny_240,940.57,406.823,384,240,7.01
+crossvit_9_240,937.22,408.452,384,240,8.55
+efficientnet_b1,935.15,272.379,256,256,7.79
+seresnet50,934.74,409.786,384,224,28.09
+regnety_004,931.71,548.466,512,224,4.34
+gluon_resnet50_v1s,928.8,412.664,384,224,25.68
+ecaresnetlight,928.23,550.753,512,224,30.16
+resnetaa50d,926.64,413.614,384,224,25.58
+dla60,926.01,413.77,384,224,22.04
+ecaresnext26t_32x4d,925.94,414.209,384,224,15.41
+ecaresnext50t_32x4d,924.8,414.714,384,224,15.41
+ese_vovnet39b,919.92,555.952,512,224,24.57
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+crossvit_9_dagger_240,912.87,419.313,384,240,8.78
+gcresnet33ts,912.73,279.541,256,256,19.88
+eca_vovnet39b,910.35,561.796,512,224,22.6
+gmlp_ti16_224,908.97,421.011,384,224,5.87
+dla60x_c,908.47,562.709,512,224,1.32
+cspresnet50,908.32,421.991,384,256,21.62
+vgg11,905.72,565.146,512,224,132.86
+resnetblur50,901.02,425.435,384,224,25.56
+ecaresnet50d_pruned,892.5,572.812,512,224,19.94
+rexnetr_200,885.64,215.704,192,224,16.52
+lambda_resnet26rpt_256,881.41,217.279,192,256,10.99
+vit_small_patch16_224,879.33,435.939,384,224,22.05
+deit_small_patch16_224,876.6,437.293,384,224,22.05
+nf_seresnet50,866.69,441.953,384,224,28.09
+dpn68b,864.02,443.325,384,224,12.61
+cspresnext50,863.58,443.862,384,224,20.57
+cspresnet50w,858.14,446.674,384,256,28.12
+selecsls84,852.15,599.694,512,224,50.95
+hrnet_w18_small_v2,849.12,600.799,512,224,15.6
+cspresnet50d,847.29,452.406,384,256,21.64
+deit_small_distilled_patch16_224,846.66,301.609,256,224,22.44
+seresnet50t,844.69,453.54,384,224,28.1
+resnetrs50,843.24,454.312,384,224,35.69
+densenet121,835.01,304.929,256,224,7.98
+tv_densenet121,832.77,305.766,256,224,7.98
+rexnet_150,829.93,307.376,256,224,9.73
+gluon_resnext50_32x4d,824.86,464.778,384,224,25.03
+tv_resnext50_32x4d,824.06,465.237,384,224,25.03
+ssl_resnext50_32x4d,823.91,465.298,384,224,25.03
+swsl_resnext50_32x4d,823.16,465.728,384,224,25.03
+resnext50_32x4d,823.01,465.815,384,224,25.03
+dpn68,816.18,469.476,384,224,12.61
+res2net50_26w_4s,812.07,314.023,256,224,25.7
+efficientnet_b2_pruned,811.6,314.06,256,260,8.31
+resnetblur50d,810.86,314.915,256,224,25.58
+pit_s_224,809.09,315.601,256,224,23.46
+pit_s_distilled_224,808.91,315.694,256,224,24.04
+vovnet57a,808.86,473.9,384,224,36.64
+skresnet50,802.36,317.782,256,224,25.8
+densenet121d,795.36,320.183,256,224,8.0
+vit_base_resnet26d_224,792.88,483.157,384,224,101.4
+rexnet_130,792.23,322.087,256,224,7.56
+tf_efficientnet_b2_ns,791.33,241.259,192,260,9.11
+tf_efficientnet_b2_ap,790.24,241.588,192,260,9.11
+regnetx_006,788.72,648.389,512,224,6.2
+tf_efficientnet_b2,788.26,242.2,192,260,9.11
+vgg11_bn,788.01,487.085,384,224,132.87
+nf_ecaresnet50,787.45,486.772,384,224,25.56
+regnety_006,779.2,656.099,512,224,6.06
+gcresnet50t,776.26,328.367,256,256,25.9
+ese_vovnet57b,765.66,500.673,384,224,38.61
+ecaresnet50d,761.68,335.218,256,224,25.58
+resnext50d_32x4d,757.82,337.002,256,224,25.05
+adv_inception_v3,756.25,506.326,384,299,23.83
+tf_inception_v3,754.65,507.545,384,299,23.83
+gluon_inception_v3,754.57,507.572,384,299,23.83
+inception_v3,753.64,508.224,384,299,23.83
+seresnetaa50d,751.96,339.385,256,224,28.11
+res2net50_14w_8s,748.86,339.851,256,224,25.06
+resmlp_24_distilled_224,743.59,342.912,256,224,30.02
+resmlp_24_224,743.53,342.937,256,224,30.02
+resnetv2_101,742.52,343.363,256,224,44.54
+skresnet50d,738.05,345.557,256,224,25.82
+sehalonet33ts,731.23,349.345,256,256,13.69
+dla60_res2net,730.56,349.091,256,224,20.85
+densenetblur121d,729.66,349.185,256,224,8.0
+resnet101,719.46,354.412,256,224,44.55
+tv_resnet101,719.29,354.488,256,224,44.55
+gluon_resnet101_v1b,719.28,354.459,256,224,44.55
+efficientnet_b2a,707.95,269.81,192,288,9.11
+efficientnet_b2,707.16,270.111,192,288,9.11
+nf_resnet50,703.13,545.338,384,288,25.56
+nf_resnet101,702.76,544.906,384,224,44.55
+ecaresnet101d_pruned,698.97,730.858,512,224,24.88
+densenet169,691.74,367.774,256,224,14.15
+gluon_resnet101_v1c,690.21,369.47,256,224,44.57
+gluon_seresnext50_32x4d,689.84,370.073,256,224,27.56
+legacy_seresnext50_32x4d,688.18,370.947,256,224,27.56
+seresnext50_32x4d,688.18,370.943,256,224,27.56
+resnetv2_101d,686.94,371.274,256,224,44.56
+darknet53,683.71,373.676,256,256,41.61
+dla60x,680.87,375.081,256,224,17.35
+nf_regnet_b0,680.47,751.331,512,256,8.76
+efficientnetv2_rw_t,669.58,284.789,192,288,13.65
+gluon_resnet101_v1d,666.43,382.723,256,224,44.57
+regnety_008,657.21,778.104,512,224,6.26
+rexnet_200,656.53,291.353,192,224,16.37
+tf_efficientnetv2_b3,655.17,291.405,192,300,14.36
+vit_small_r26_s32_224,652.39,391.27,256,224,36.43
+sebotnet33ts_256,650.1,196.14,128,256,13.7
+wide_resnet50_2,646.12,593.536,384,224,68.88
+vgg13,645.37,594.836,384,224,133.05
+dla102,640.56,398.166,256,224,33.27
+vit_base_resnet50d_224,619.99,411.439,256,224,110.97
+gluon_resnet101_v1s,614.53,415.124,256,224,44.67
+resnext26ts,613.38,625.548,384,256,10.3
+resnetaa101d,612.93,416.224,256,224,44.57
+ecaresnet26t,610.98,418.477,256,320,16.01
+gmixer_24_224,610.59,417.896,256,224,24.72
+repvgg_b1,609.77,838.686,512,224,57.42
+eca_botnext26ts_256,609.21,419.672,256,256,10.59
+eca_halonext26ts,598.72,427.016,256,256,10.76
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+eca_resnext26ts,593.02,431.168,256,256,10.3
+seresnext26ts,592.35,431.553,256,256,10.39
+regnetx_008,587.44,870.811,512,224,7.26
+convnext_tiny,584.52,437.049,256,224,28.59
+coat_lite_tiny,583.0,657.845,384,224,5.72
+convnext_tiny_hnf,582.18,438.813,256,224,28.59
+gcresnext26ts,581.42,439.532,256,256,10.48
+mixnet_m,576.71,664.443,384,224,5.01
+resnetv2_50x1_bit_distilled,575.65,332.777,192,224,25.55
+cspdarknet53,570.42,447.825,256,256,27.64
+legacy_seresnet101,570.04,447.058,256,224,49.33
+halonet50ts,568.71,336.701,192,256,22.73
+res2net50_26w_6s,565.22,451.306,256,224,37.05
+resnetblur101d,562.81,453.413,256,224,44.57
+seresnet101,560.51,454.74,256,224,49.33
+coat_lite_mini,559.21,685.884,384,224,11.01
+xcit_small_12_p16_224,558.21,456.962,256,224,26.25
+xcit_small_12_p16_224_dist,557.95,457.219,256,224,26.25
+vgg13_bn,555.55,460.55,256,224,133.05
+tf_efficientnet_lite3,555.29,229.476,128,300,8.2
+efficientnet_lite3,554.26,229.924,128,300,8.2
+tf_mixnet_m,541.25,708.06,384,224,5.01
+ssl_resnext101_32x4d,539.66,472.944,256,224,44.18
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+xcit_tiny_24_p16_224,538.48,472.477,256,224,12.12
+swsl_resnext101_32x4d,538.39,474.037,256,224,44.18
+densenet201,535.33,355.953,192,224,20.01
+bat_resnext26ts,534.3,478.021,256,256,10.73
+twins_svt_small,529.33,482.243,256,224,24.06
+mixer_b16_224,521.89,489.791,256,224,59.88
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+vgg16,519.79,738.569,384,224,138.36
+nf_seresnet101,519.55,490.612,256,224,49.33
+gmlp_s16_224,514.57,371.708,192,224,19.42
+crossvit_small_240,514.25,371.914,192,240,26.86
+resnetv2_152,514.07,495.927,256,224,60.19
+res2net101_26w_4s,512.94,372.022,192,224,45.21
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+botnet50ts_256,511.02,249.57,128,256,22.74
+vit_base_r26_s32_224,509.73,375.506,192,224,101.38
+efficientnet_b3_pruned,508.52,501.852,256,300,9.86
+nf_regnet_b3,507.41,502.895,256,320,18.59
+res2next50,500.31,510.5,256,224,24.67
+xcit_nano_12_p16_384_dist,497.26,513.197,256,384,3.05
+dla102x,495.72,385.887,192,224,26.31
+resnet50_gn,494.95,387.141,192,224,25.56
+mixnet_l,494.74,516.045,256,224,7.33
+resnet152,490.44,389.409,192,224,60.19
+gluon_resnet152_v1b,490.37,389.44,192,224,60.19
+tv_resnet152,490.23,389.552,192,224,60.19
+resmlp_36_224,489.84,389.965,192,224,44.69
+resmlp_36_distilled_224,489.66,390.129,192,224,44.69
+cait_xxs24_224,487.15,523.231,256,224,11.96
+mixer_l32_224,486.19,393.553,192,224,206.94
+halo2botnet50ts_256,485.95,262.504,128,256,22.64
+xception,485.66,262.809,128,299,22.86
+visformer_tiny,484.78,1055.527,512,224,10.32
+vit_large_patch32_224,484.04,527.472,256,224,306.54
+vit_base_patch32_384,478.93,533.779,256,384,88.3
+gluon_resnet152_v1c,476.8,400.507,192,224,60.21
+resnetv2_152d,475.38,401.77,192,224,60.2
+crossvit_15_240,472.73,404.523,192,240,27.53
+res2net50_26w_8s,468.77,407.558,192,224,48.4
+tf_mixnet_l,466.85,546.936,256,224,7.33
+gluon_resnet152_v1d,465.06,410.759,192,224,60.21
+ecaresnet101d,462.22,552.191,256,224,44.57
+crossvit_15_dagger_240,459.76,415.927,192,240,28.21
+vgg16_bn,457.66,559.065,256,224,138.37
+nf_ecaresnet101,455.3,560.589,256,224,44.55
+efficientnet_el,446.2,285.844,128,300,10.59
+efficientnet_el_pruned,445.59,286.28,128,300,10.59
+swin_tiny_patch4_window7_224,445.53,573.708,256,224,28.29
+fbnetv3_g,442.28,287.506,128,288,16.62
+gluon_resnet152_v1s,441.14,433.129,192,224,60.32
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+tf_efficientnet_el,436.28,292.36,128,300,10.59
+vgg19,436.15,880.196,384,224,143.67
+seresnext101_32x4d,435.91,438.42,192,224,48.96
+legacy_seresnext101_32x4d,435.08,439.246,192,224,48.96
+ese_vovnet99b,434.62,587.614,256,224,63.2
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+dla60_res2next,431.53,591.928,256,224,17.03
+dla169,427.18,447.18,192,224,53.39
+hrnet_w32,426.75,445.609,192,224,41.23
+hrnet_w18,413.83,614.275,256,224,21.3
+convit_small,409.81,467.592,192,224,27.78
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+vit_small_resnet50d_s16_224,407.06,470.553,192,224,57.53
+vgg19_bn,388.74,658.182,256,224,143.68
+ecaresnet50t,388.23,328.837,128,320,25.57
+inception_v4,387.4,493.551,192,299,42.68
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+legacy_seresnet152,382.75,498.635,192,224,66.82
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+densenet161,371.62,342.252,128,224,28.68
+repvgg_b2,368.23,1389.47,512,224,89.02
+seresnet152,362.95,349.646,128,224,66.82
+nest_tiny,356.9,357.853,128,224,17.06
+dla102x2,355.19,358.924,128,224,41.28
+vit_base_patch16_224_miil,354.79,360.089,128,224,86.54
+jx_nest_tiny,353.97,360.795,128,224,17.06
+gluon_resnext101_64x4d,352.72,361.493,128,224,83.46
+resnext101_64x4d,352.52,361.632,128,224,83.46
+wide_resnet101_2,350.85,545.834,192,224,126.89
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+vit_base_patch16_224,349.4,365.598,128,224,86.57
+deit_base_patch16_224,349.3,365.691,128,224,86.57
+vit_base_patch16_224_sam,349.14,365.832,128,224,86.57
+resnet200,348.81,364.208,128,224,64.67
+resnest14d,348.25,1469.78,512,224,10.61
+efficientnet_b3a,345.42,368.96,128,320,12.23
+efficientnet_b3,345.06,369.413,128,320,12.23
+deit_base_distilled_patch16_224,344.74,370.536,128,224,87.34
+crossvit_18_240,343.92,370.408,128,240,43.27
+hrnet_w30,341.47,745.312,256,224,37.71
+crossvit_18_dagger_240,335.19,380.045,128,240,44.27
+ens_adv_inception_resnet_v2,334.4,571.029,192,299,55.84
+inception_resnet_v2,334.03,571.741,192,299,55.84
+efficientnet_lite4,332.63,191.154,64,380,13.01
+nf_regnet_b1,327.56,1561.741,512,288,10.22
+coat_lite_small,324.96,589.506,192,224,19.84
+dpn92,324.94,786.493,256,224,37.67
+resnet101d,323.43,394.33,128,320,44.57
+mixnet_xl,322.47,593.686,192,224,11.9
+beit_base_patch16_224,320.26,398.682,128,224,86.53
+tf_efficientnet_lite4,319.09,199.328,64,380,13.01
+gcresnext50ts,314.79,608.558,192,256,15.67
+resnetrs101,314.59,404.798,128,288,63.62
+twins_pcpvt_base,313.15,610.712,192,224,43.83
+cait_xxs36_224,311.89,407.079,128,224,17.3
+gluon_seresnext101_64x4d,306.13,416.102,128,224,88.23
+twins_svt_base,305.99,416.477,128,224,56.07
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+regnetz_d8,301.65,210.668,64,320,23.37
+xception41,300.49,424.83,128,299,26.97
+efficientnetv2_s,292.99,325.601,96,384,21.46
+ese_vovnet39b_evos,292.82,436.279,128,224,24.58
+efficientnetv2_rw_s,289.9,218.715,64,384,23.94
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+swin_small_patch4_window7_224,289.15,441.029,128,224,49.61
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+xcit_small_24_p16_224_dist,286.23,444.237,128,224,47.67
+xcit_small_24_p16_224,286.12,444.416,128,224,47.67
+hrnet_w40,285.91,667.227,192,224,57.56
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+pit_b_distilled_224,284.45,336.631,96,224,74.79
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+dpn98,275.63,462.928,128,224,61.57
+xception65,275.32,346.928,96,299,39.92
+resnet51q,274.2,699.442,192,288,35.7
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+convnext_base,272.92,467.434,128,224,88.59
+nf_regnet_b4,271.03,470.306,128,384,30.21
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+cait_s24_224,268.53,474.373,128,224,46.92
+hrnet_w48,262.05,484.085,128,224,77.47
+resnest26d,254.99,1505.218,384,224,17.07
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+resnetv2_50d_evob,247.25,775.496,192,224,25.59
+regnetz_c16,246.47,517.947,128,320,13.46
+gmlp_b16_224,243.4,392.966,96,224,73.08
+hrnet_w44,236.76,806.557,192,224,67.06
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+efficientnet_b4,234.85,270.618,64,384,19.34
+nest_small,234.57,407.797,96,224,38.35
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+nfnet_l0,228.47,1119.415,256,288,35.07
+coat_tiny,228.08,559.427,128,224,5.5
+twins_pcpvt_large,223.01,570.431,128,224,60.99
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+tresnet_l,102.9,4972.484,512,224,55.99
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+beit_large_patch16_224,98.03,487.815,48,224,304.43
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+vit_base_patch16_384,89.9,355.185,32,384,86.86
+deit_base_patch16_384,89.87,355.331,32,384,86.86
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+deit_base_distilled_patch16_384,88.07,362.54,32,384,87.63
+cait_xxs24_384,87.17,364.76,32,384,12.03
+nf_regnet_b5,85.26,748.171,64,456,49.74
+resnetv2_101x1_bitm,84.86,375.607,32,448,44.54
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+repvgg_b3g4,83.61,4591.876,384,224,83.83
+crossvit_18_dagger_408,77.92,306.154,24,408,44.61
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+pnasnet5large,75.01,423.127,32,331,86.06
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+resnetrs270,73.04,432.615,32,352,129.86
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+nasnetalarge,65.99,480.339,32,331,88.75
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+resmlp_big_24_224,65.94,483.953,32,224,129.14
+resmlp_big_24_224_in22ft1k,65.9,484.194,32,224,129.14
+regnetx_160,65.04,2951.208,192,224,54.28
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+vit_base_patch8_224,57.86,275.754,16,224,86.58
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diff --git a/results/model_metadata_in1k.csv b/results/model_metadata-in1k.csv
similarity index 100%
rename from results/model_metadata_in1k.csv
rename to results/model_metadata-in1k.csv