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additional-exp.sh
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#python calc_metrics.py
#
#python calc_metrics.py --metrics=mixermlp_fid50k_full --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/match_inception_ffhq.zip --save_name mixermlp_fid50k_full_match_inception
#
python calc_metrics.py --metrics=moco_vit_i_cka50k_full,moco_vit_i_fid50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/pytorch-CycleGAN-and-pix2pix/datasets/horse2zebra/testB --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=120 --num_gen=120 --save_name=CUT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/results/horse2zebra_cut_pretrained/test_latest/images/fake_B --save_res ./results/CUT
#python calc_metrics.py --metrics=vitcls_base_fid50k_full,vitcls_base_cka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/pytorch-CycleGAN-and-pix2pix/datasets/horse2zebra/testB --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=120 --num_gen=120 --save_name=CUT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/results/horse2zebra_cut_pretrained/test_latest/images/fake_B --save_res ./results/CUT-Cat2Dog
#
python calc_metrics.py --metrics=moco_vit_i_cka50k_full,moco_vit_i_fid50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/pytorch-CycleGAN-and-pix2pix/datasets/horse2zebra/testB --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=120 --num_gen=120 --save_name=AttentionGAN --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/AttentionGAN-master/results/horse2zebra_pretrained/test_latest/fakeB --save_res ./results/AttentionGAN
#python calc_metrics.py --metrics=vitcls_base_fid50k_full,vitcls_base_cka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/pytorch-CycleGAN-and-pix2pix/datasets/horse2zebra/testB --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=120 --num_gen=120 --save_name=AttentionGAN --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/AttentionGAN-master/results/horse2zebra_pretrained/test_latest/fakeB --save_res ./results/AttentionGAN
#
python calc_metrics.py --metrics=moco_vit_i_cka50k_full,moco_vit_i_fid50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/pytorch-CycleGAN-and-pix2pix/datasets/horse2zebra/testB --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=120 --num_gen=120 --save_name=CycleGAN --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/pytorch-CycleGAN-and-pix2pix/results/horse2zebra_pretrained/test_latest/fake --save_res ./results/CycleGAN
#python calc_metrics.py --metrics=vitcls_base_fid50k_full,vitcls_base_cka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/pytorch-CycleGAN-and-pix2pix/datasets/horse2zebra/testB --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=120 --num_gen=120 --save_name=CycleGAN --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/pytorch-CycleGAN-and-pix2pix/results/horse2zebra_pretrained/test_latest/fake --save_res ./results/CycleGAN
#
python calc_metrics.py --metrics=moco_vit_i_cka50k_full,moco_vit_i_fid50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testB256.zip --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=CUT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/results/cat2dog_cut_pretrained/test_latest/images/fake_B --save_res ./results/CUT-Cat2Dog
#python calc_metrics.py --metrics=vitcls_base_fid50k_full,vitcls_base_cka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testB256.zip --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=CUT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/results/cat2dog_cut_pretrained/test_latest/images/fake_B --save_res ./results/CUT-Cat2Dog
#
python calc_metrics.py --metrics=moco_vit_i_cka50k_full,moco_vit_i_fid50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testB256.zip --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=GP-UNIT-Cat2Dog --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/GP-UNIT/results_cat2dog --save_res ./results/GP-UNIT-Cat2Dog
#python calc_metrics.py --metrics=vitcls_base_fid50k_full,vitcls_base_cka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testB256.zip --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=GP-UNIT-Cat2Dog --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/GP-UNIT/results_cat2dog --save_res ./results/GP-UNIT-Cat2Dog
#
python calc_metrics.py --metrics=moco_vit_i_cka50k_full,moco_vit_i_fid50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testA256.zip --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=MUNIT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/imaginaire/output --save_res ./results/MUNIT
#python calc_metrics.py --metrics=vitcls_base_fid50k_full,vitcls_base_cka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testA256.zip --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=MUNIT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/imaginaire/output --save_res ./results/MUNIT
#
python calc_metrics.py --metrics=moco_vit_i_cka50k_full,moco_vit_i_fid50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testA256.zip --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=GP-UNIT-Dog2Cat --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/GP-UNIT/results_dog2cat --save_res ./results/GP-UNIT-Dog2Cat
#python calc_metrics.py --metrics=vitcls_base_fid50k_full,vitcls_base_cka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testA256.zip --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=GP-UNIT-Dog2Cat --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/GP-UNIT/results_dog2cat --save_res ./results/GP-UNIT-Dog2Cat
python calc_metrics.py --metrics=mixermlp_fid50k_full,mixermlp_cka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testB256.zip --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=CUT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/results/cat2dog_cut_pretrained/test_latest/images/fake_B --save_res ./results/CUT-Cat2Dog
python calc_metrics.py --metrics=gmlp_fid50k_full,gmlp_cka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testB256.zip --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=CUT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/results/cat2dog_cut_pretrained/test_latest/images/fake_B --save_res ./results/CUT-Cat2Dog
python calc_metrics.py --metrics=convnext_base_fid50k_full,convnext_base_cka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testB256.zip --eval_bs=1000 --layers=stages.0,stages.1,stages.2,stages.3 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=CUT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/results/cat2dog_cut_pretrained/test_latest/images/fake_B --save_res ./results/CUT-Cat2Dog
python calc_metrics.py --metrics=repvgg_fid50k_full,repvgg_cka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testB256.zip --eval_bs=1000 --layers=stages.0,stages.1,stages.2,stages.3 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=CUT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/results/cat2dog_cut_pretrained/test_latest/images/fake_B --save_res ./results/CUT-Cat2Dog
python calc_metrics.py --metrics=swavfid50k_full,swavcka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testB256.zip --eval_bs=1000 --layers=layer1,layer2,layer3,layer4 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=CUT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/results/cat2dog_cut_pretrained/test_latest/images/fake_B --save_res ./results/CUT-Cat2Dog
python calc_metrics.py --metrics=moco_vit_i_fid50k_full,moco_vit_i_cka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testB256.zip --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=CUT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/results/cat2dog_cut_pretrained/test_latest/images/fake_B --save_res ./results/CUT-Cat2Dog
python calc_metrics.py --metrics=clip_vit_B16_cka50k_full,clip_vit_B16_fid50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testB256.zip --eval_bs=1000 --layers=transformer.resblocks.2,transformer.resblocks.5,transformer.resblocks.8,transformer.resblocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=CUT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/results/cat2dog_cut_pretrained/test_latest/images/fake_B --save_res ./results/CUT-Cat2Dog
python calc_metrics.py --metrics=vitcls_base_fid50k_full,vitcls_base_cka50k_full --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testB256.zip --eval_bs=1000 --layers=blocks.0,blocks.1,blocks.2,blocks.3,blocks.4,blocks.5,blocks.6,blocks.7,blocks.8,blocks.9,blocks.10,blocks.11 --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=CUT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/results/cat2dog_cut_pretrained/test_latest/images/fake_B --save_res ./results/CUT-Cat2Dog
python calc_metrics.py --metrics=fid50k_full,cka_full_torch --data D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/datasets/afhq/cat2dog/testB256.zip --eval_bs=1000 --layers=Conv2d_4a_3x3,Mixed_5d,Mixed_6e,Mixed_7c --mirror=1 --cache=1 --cfg=stylegan2 --random=0 --feature_save_flag=0 --feature_save='./features' --max_real=500 --num_gen=500 --save_name=CUT --generate D:/Z-kobeshegu/NeurIPS2023-rebuttal/contrastive-unpaired-translation/results/cat2dog_cut_pretrained/test_latest/images/fake_B --save_res ./results/CUT-Cat2Dog