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table.md

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executable file
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108 lines (108 loc) · 5.91 KB
name Parameters Size (MB)
cse_resnet101 49,326,872 188.17
cse_resnet152 66,821,848 254.91
cse_resnet18 11,778,592 44.93
cse_resnet34 21,958,868 83.77
cse_resnet50 28,088,024 107.15
deit_base_patch16_224 87,184,592 332.58
deit_base_patch16_384 87,186,128 357.63
deit_small_patch16_224 22,359,632 85.3
deit_tiny_patch16_224 5,872,400 22.4
densenet121 7,978,856 30.44
densenet161 28,681,000 109.41
densenet169 14,149,480 53.98
densenet201 20,013,928 76.35
eca_resnet101d 44,568,563 212.62
eca_resnet101t 44,566,027 228.65
eca_resnet18d 16,014,452 98.41
eca_resnet18t 1,415,684 37.91
eca_resnet26d 16,014,452 98.41
eca_resnet26t 16,011,916 114.44
eca_resnet50d 25,576,350 136.65
eca_resnet50t 25,573,814 152.68
efficientnet_b0 5,288,548 20.17
efficientnet_b1 7,794,184 29.73
efficientnet_b2 9,109,994 34.75
efficientnet_b3 12,233,232 46.67
efficientnet_b4 19,341,616 73.78
efficientnet_b5 30,389,784 115.93
efficientnet_b6 43,040,704 164.19
efficientnet_b7 66,347,960 253.1
efficientnet_b8 87,413,142 505.01
efficientnet_l2 480,309,308 2332.13
efficientnet_lite0 4,652,008 17.75
efficientnet_lite1 5,416,680 20.66
efficientnet_lite2 6,092,072 23.24
efficientnet_lite3 8,197,096 31.27
efficientnet_lite4 13,006,568 49.62
fishnet150 24,960,808 95.22
fishnet99 16,630,312 63.44
mobilenet_v2 3,504,872 24.51
mobilenetv2 3,504,872 13.37
regnetx_002 2,684,792 10.24
regnetx_004 5,157,512 19.67
regnetx_006 6,196,040 23.64
regnetx_008 7,259,656 27.69
regnetx_016 9,190,136 35.06
regnetx_032 15,296,552 58.35
regnetx_040 22,118,248 97.66
regnetx_064 26,209,256 114.02
regnetx_080 34,561,448 147.43
regnety_002 3,162,996 12.07
regnety_004 4,344,144 16.57
regnety_006 6,055,160 23.1
regnety_008 6,263,168 23.89
regnety_016 11,202,430 42.73
regnety_032 19,436,338 74.14
regnety_040 20,646,656 91.77
regnety_064 30,583,252 131.52
regnety_080 39,180,068 165.9
resnest101e 48,275,016 184.15
resnest14d 10,611,688 40.48
resnest200e 70,201,544 267.8
resnest269e 7,551,112 28.81
resnest26d 17,069,448 65.11
resnest50d 27,483,240 104.84
resnest50d_1s4x24d 25,677,000 97.95
resnest50d_4s2x40d 30,417,592 116.03
resnet101 44,549,160 169.94
resnet152 60,192,808 229.62
resnet18 11,689,512 44.59
resnet200 64,673,832 246.71
resnet26 15,995,176 61.02
resnet26d 16,014,408 61.09
resnet34 21,797,672 83.15
resnet34d 21,816,904 83.22
resnet50 25,557,032 97.49
resnet50d 25,576,264 97.57
resnext101_32x16d 194,026,792 740.15
resnext101_32x32d 468,530,472 1787.3
resnext101_32x48d 828,411,176 3160.14
resnext101_32x8d 88,791,336 338.71
resnext50_32x4d 25,028,904 95.48
se_resnet101 49,292,328 188.04
se_resnet152 66,770,984 254.71
se_resnet18 11,776,552 44.92
se_resnet34 21,954,856 83.75
se_resnet50 28,071,976 107.09
unet 23,202,530 88.51
vgg11 132,863,336 506.83
vgg11_bn 132,868,840 506.85
vgg13 133,047,848 507.54
vgg13_bn 133,053,736 507.56
vgg16 138,357,544 527.79
vgg16_bn 138,365,992 527.82
vgg19 143,667,240 548.05
vgg19_bn 143,678,248 548.09
vit_base_patch16_224 86,415,592 329.65
vit_base_patch16_384 86,415,592 329.65
vit_base_patch32_384 88,185,064 336.4
vit_huge_patch16_224 631,823,080 2410.21
vit_huge_patch32_384 634,772,200 2421.46
vit_large_patch16_224 304,123,880 1160.14
vit_large_patch16_384 304,123,880 1160.14
vit_large_patch32_384 306,483,176 1169.14
vit_small_patch16_224 48,602,344 185.4
wide_resnet101_2 126,886,696 484.03
wide_resnet50_2 68,883,240 262.77