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import timm.models as tmm
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import torchvision.models as tm
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# input shape: (batch_size, 3, 224, 224)
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tm_models = [
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tm.alexnet,
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tm.convnext_base,
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tm.densenet121,
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# tm.efficientnet_v2_s,
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# tm.googlenet, # output bad case
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# tm.inception_v3, # bad case
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tm.mobilenet_v2,
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tm.mobilenet_v3_small,
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tm.mnasnet0_5,
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tm.resnet18,
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tm.regnet_x_16gf,
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tm.resnext50_32x4d,
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tm.shufflenet_v2_x0_5,
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tm.squeezenet1_0,
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# tm.swin_s, # fx bad case
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tm.vgg11,
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tm.vit_b_16,
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tm.wide_resnet50_2,
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]
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tmm_models = [
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tmm.beit_base_patch16_224,
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tmm.beitv2_base_patch16_224,
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tmm.cait_s24_224,
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tmm.coat_lite_mini,
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tmm.convit_base,
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tmm.deit3_base_patch16_224,
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tmm.dm_nfnet_f0,
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tmm.eca_nfnet_l0,
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tmm.efficientformer_l1,
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# tmm.ese_vovnet19b_dw,
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tmm.gmixer_12_224,
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tmm.gmlp_b16_224,
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# tmm.hardcorenas_a,
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tmm.hrnet_w18_small,
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tmm.inception_v3,
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tmm.mixer_b16_224,
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tmm.nf_ecaresnet101,
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tmm.nf_regnet_b0,
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# tmm.pit_b_224, # pretrained only
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# tmm.regnetv_040,
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# tmm.skresnet18,
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# tmm.swin_base_patch4_window7_224, # fx bad case
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# tmm.tnt_b_patch16_224, # bad case
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tmm.vgg11,
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tmm.vit_base_patch16_18x2_224,
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tmm.wide_resnet50_2,
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]
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