├── .github └── framework.png ├── .gitignore ├── LICENSE ├── README.md ├── stitching_deit ├── .gitignore ├── LICENSE ├── README.md ├── config │ └── deit_stitching.json ├── datasets.py ├── engine.py ├── hubconf.py ├── logger.py ├── losses.py ├── main.py ├── models.py ├── params.py ├── pretrained │ └── readme.txt ├── results │ ├── deit_res.jpg │ └── stitches_res.txt ├── run_with_submitit.py ├── samplers.py ├── scripts │ ├── eval.sh │ └── train.sh ├── snnet.py ├── tox.ini ├── utils.py └── visualize_stitches.py ├── stitching_levit ├── .gitignore ├── LICENSE ├── README.md ├── datasets.py ├── engine.py ├── hubconf.py ├── levit.py ├── levit_c.py ├── losses.py ├── main.py ├── pretrained │ └── readme.txt ├── results │ └── stitches_res.txt ├── run_with_submitit.py ├── samplers.py ├── snnet.py └── utils.py ├── stitching_resnet_swin ├── .gitattributes ├── .gitignore ├── LICENSE ├── README.md ├── configs │ ├── resnet18_resnet50.json │ └── resnet18_swin_ti.json ├── distributed_train.sh ├── logs │ ├── log-20230327-195119.txt │ └── log-20230327-195714.txt ├── requirements.txt ├── results │ ├── stitches_res_resnet_18_50.txt │ └── stitches_res_resnet_18_swin_ti.txt ├── setup.cfg ├── setup.py ├── timm │ ├── __init__.py │ ├── data │ │ ├── __init__.py │ │ ├── auto_augment.py │ │ ├── config.py │ │ ├── constants.py │ │ ├── dataset.py │ │ ├── dataset_factory.py │ │ ├── distributed_sampler.py │ │ ├── loader.py │ │ ├── mixup.py │ │ ├── random_erasing.py │ │ ├── readers │ │ │ ├── __init__.py │ │ │ ├── class_map.py │ │ │ ├── img_extensions.py │ │ │ ├── reader.py │ │ │ ├── reader_factory.py │ │ │ ├── reader_hfds.py │ │ │ ├── reader_image_folder.py │ │ │ ├── reader_image_in_tar.py │ │ │ ├── reader_image_tar.py │ │ │ ├── reader_tfds.py │ │ │ ├── reader_wds.py │ │ │ └── shared_count.py │ │ ├── real_labels.py │ │ ├── tf_preprocessing.py │ │ ├── transforms.py │ │ └── transforms_factory.py │ ├── loss │ │ ├── __init__.py │ │ ├── asymmetric_loss.py │ │ ├── binary_cross_entropy.py │ │ ├── cross_entropy.py │ │ ├── jsd.py │ │ └── stitch_loss.py │ ├── models │ │ ├── __init__.py │ │ ├── beit.py │ │ ├── byoanet.py │ │ ├── byobnet.py │ │ ├── cait.py │ │ ├── coat.py │ │ ├── convit.py │ │ ├── convmixer.py │ │ ├── convnext.py │ │ ├── crossvit.py │ │ ├── cspnet.py │ │ ├── deit.py │ │ ├── densenet.py │ │ ├── dla.py │ │ ├── dpn.py │ │ ├── edgenext.py │ │ ├── efficientformer.py │ │ ├── efficientnet.py │ │ ├── efficientnet_blocks.py │ │ ├── efficientnet_builder.py │ │ ├── factory.py │ │ ├── features.py │ │ ├── fx_features.py │ │ ├── gcvit.py │ │ ├── ghostnet.py │ │ ├── gluon_resnet.py │ │ ├── gluon_xception.py │ │ ├── hardcorenas.py │ │ ├── helpers.py │ │ ├── hrnet.py │ │ ├── hub.py │ │ ├── inception_resnet_v2.py │ │ ├── inception_v3.py │ │ ├── inception_v4.py │ │ ├── layers │ │ │ ├── __init__.py │ │ │ ├── activations.py │ │ │ ├── activations_jit.py │ │ │ ├── activations_me.py │ │ │ ├── adaptive_avgmax_pool.py │ │ │ ├── attention_pool2d.py │ │ │ ├── blur_pool.py │ │ │ ├── bottleneck_attn.py │ │ │ ├── cbam.py │ │ │ ├── classifier.py │ │ │ ├── cond_conv2d.py │ │ │ ├── config.py │ │ │ ├── conv2d_same.py │ │ │ ├── conv_bn_act.py │ │ │ ├── create_act.py │ │ │ ├── create_attn.py │ │ │ ├── create_conv2d.py │ │ │ ├── create_norm.py │ │ │ ├── create_norm_act.py │ │ │ ├── drop.py │ │ │ ├── eca.py │ │ │ ├── evo_norm.py │ │ │ ├── fast_norm.py │ │ │ ├── filter_response_norm.py │ │ │ ├── gather_excite.py │ │ │ ├── global_context.py │ │ │ ├── halo_attn.py │ │ │ ├── helpers.py │ │ │ ├── inplace_abn.py │ │ │ ├── lambda_layer.py │ │ │ ├── linear.py │ │ │ ├── median_pool.py │ │ │ ├── mixed_conv2d.py │ │ │ ├── ml_decoder.py │ │ │ ├── mlp.py │ │ │ ├── non_local_attn.py │ │ │ ├── norm.py │ │ │ ├── norm_act.py │ │ │ ├── padding.py │ │ │ ├── patch_embed.py │ │ │ ├── pool2d_same.py │ │ │ ├── pos_embed.py │ │ │ ├── selective_kernel.py │ │ │ ├── separable_conv.py │ │ │ ├── space_to_depth.py │ │ │ ├── split_attn.py │ │ │ ├── split_batchnorm.py │ │ │ ├── squeeze_excite.py │ │ │ ├── std_conv.py │ │ │ ├── test_time_pool.py │ │ │ ├── trace_utils.py │ │ │ └── weight_init.py │ │ ├── levit.py │ │ ├── maxxvit.py │ │ ├── mlp_mixer.py │ │ ├── mobilenetv3.py │ │ ├── mobilevit.py │ │ ├── mvitv2.py │ │ ├── nasnet.py │ │ ├── nest.py │ │ ├── nfnet.py │ │ ├── pit.py │ │ ├── pnasnet.py │ │ ├── poolformer.py │ │ ├── pruned │ │ │ ├── ecaresnet101d_pruned.txt │ │ │ ├── ecaresnet50d_pruned.txt │ │ │ ├── efficientnet_b1_pruned.txt │ │ │ ├── efficientnet_b2_pruned.txt │ │ │ └── efficientnet_b3_pruned.txt │ │ ├── pvt_v2.py │ │ ├── registry.py │ │ ├── regnet.py │ │ ├── res2net.py │ │ ├── resnest.py │ │ ├── resnet.py │ │ ├── resnetv2.py │ │ ├── rexnet.py │ │ ├── selecsls.py │ │ ├── senet.py │ │ ├── sequencer.py │ │ ├── sknet.py │ │ ├── snnet.py │ │ ├── swin_transformer.py │ │ ├── swin_transformer_v2.py │ │ ├── swin_transformer_v2_cr.py │ │ ├── tnt.py │ │ ├── tresnet.py │ │ ├── twins.py │ │ ├── vgg.py │ │ ├── visformer.py │ │ ├── vision_transformer.py │ │ ├── vision_transformer_hybrid.py │ │ ├── vision_transformer_relpos.py │ │ ├── volo.py │ │ ├── vovnet.py │ │ ├── xception.py │ │ ├── xception_aligned.py │ │ └── xcit.py │ ├── optim │ │ ├── __init__.py │ │ ├── adabelief.py │ │ ├── adafactor.py │ │ ├── adahessian.py │ │ ├── adamp.py │ │ ├── adamw.py │ │ ├── adan.py │ │ ├── lamb.py │ │ ├── lars.py │ │ ├── lookahead.py │ │ ├── madgrad.py │ │ ├── nadam.py │ │ ├── nvnovograd.py │ │ ├── optim_factory.py │ │ ├── radam.py │ │ ├── rmsprop_tf.py │ │ └── sgdp.py │ ├── scheduler │ │ ├── __init__.py │ │ ├── cosine_lr.py │ │ ├── multistep_lr.py │ │ ├── plateau_lr.py │ │ ├── poly_lr.py │ │ ├── scheduler.py │ │ ├── scheduler_factory.py │ │ ├── step_lr.py │ │ └── tanh_lr.py │ ├── utils │ │ ├── __init__.py │ │ ├── agc.py │ │ ├── checkpoint_saver.py │ │ ├── clip_grad.py │ │ ├── cuda.py │ │ ├── decay_batch.py │ │ ├── distributed.py │ │ ├── jit.py │ │ ├── log.py │ │ ├── metrics.py │ │ ├── misc.py │ │ ├── model.py │ │ ├── model_ema.py │ │ ├── random.py │ │ └── summary.py │ └── version.py └── train.py └── stitching_swin ├── .gitignore ├── CODE_OF_CONDUCT.md ├── LICENSE ├── MODELHUB.md ├── README.md ├── SECURITY.md ├── SUPPORT.md ├── config.py ├── configs ├── simmim │ ├── simmim_finetune__swin_base__img224_window7__800ep.yaml │ ├── simmim_finetune__swinv2_base__img224_window14__800ep.yaml │ ├── simmim_pretrain__swin_base__img192_window6__800ep.yaml │ └── simmim_pretrain__swinv2_base__img192_window12__800ep.yaml ├── snnet │ └── stitch_swin_ti_s_b.yaml ├── swin │ ├── swin_base_patch4_window12_384_22kto1k_finetune.yaml │ ├── swin_base_patch4_window12_384_finetune.yaml │ ├── swin_base_patch4_window7_224.yaml │ ├── swin_base_patch4_window7_224_22k.yaml │ ├── swin_base_patch4_window7_224_22kto1k_finetune.yaml │ ├── swin_large_patch4_window12_384_22kto1k_finetune.yaml │ ├── swin_large_patch4_window7_224_22k.yaml │ ├── swin_large_patch4_window7_224_22kto1k_finetune.yaml │ ├── swin_small_patch4_window7_224.yaml │ ├── swin_small_patch4_window7_224_22k.yaml │ ├── swin_small_patch4_window7_224_22kto1k_finetune.yaml │ ├── swin_tiny_c24_patch4_window8_256.yaml │ ├── swin_tiny_patch4_window7_224.yaml │ ├── swin_tiny_patch4_window7_224_22k.yaml │ └── swin_tiny_patch4_window7_224_22kto1k_finetune.yaml ├── swinmlp │ ├── swin_mlp_base_patch4_window7_224.yaml │ ├── swin_mlp_tiny_c12_patch4_window8_256.yaml │ ├── swin_mlp_tiny_c24_patch4_window8_256.yaml │ └── swin_mlp_tiny_c6_patch4_window8_256.yaml ├── swinmoe │ ├── swin_moe_base_patch4_window12_192_16expert_32gpu_22k.yaml │ ├── swin_moe_base_patch4_window12_192_32expert_32gpu_22k.yaml │ ├── swin_moe_base_patch4_window12_192_8expert_32gpu_22k.yaml │ ├── swin_moe_base_patch4_window12_192_cosine_router_32expert_32gpu_22k.yaml │ ├── swin_moe_base_patch4_window12_192_densebaseline_22k.yaml │ ├── swin_moe_small_patch4_window12_192_16expert_32gpu_22k.yaml │ ├── swin_moe_small_patch4_window12_192_32expert_32gpu_22k.yaml │ ├── swin_moe_small_patch4_window12_192_64expert_64gpu_22k.yaml │ ├── swin_moe_small_patch4_window12_192_8expert_32gpu_22k.yaml │ ├── swin_moe_small_patch4_window12_192_cosine_router_32expert_32gpu_22k.yaml │ └── swin_moe_small_patch4_window12_192_densebaseline_22k.yaml └── swinv2 │ ├── swinv2_base_patch4_window12_192_22k.yaml │ ├── swinv2_base_patch4_window12to16_192to256_22kto1k_ft.yaml │ ├── swinv2_base_patch4_window12to24_192to384_22kto1k_ft.yaml │ ├── swinv2_base_patch4_window16_256.yaml │ ├── swinv2_base_patch4_window8_256.yaml │ ├── swinv2_large_patch4_window12_192_22k.yaml │ ├── swinv2_large_patch4_window12to16_192to256_22kto1k_ft.yaml │ ├── swinv2_large_patch4_window12to24_192to384_22kto1k_ft.yaml │ ├── swinv2_small_patch4_window16_256.yaml │ ├── swinv2_small_patch4_window8_256.yaml │ ├── swinv2_tiny_patch4_window16_256.yaml │ └── swinv2_tiny_patch4_window8_256.yaml ├── data ├── __init__.py ├── build.py ├── cached_image_folder.py ├── data_simmim_ft.py ├── data_simmim_pt.py ├── imagenet22k_dataset.py ├── map22kto1k.txt ├── samplers.py └── 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