diff --git a/README.md b/README.md index e4c058f1..adb43971 100644 --- a/README.md +++ b/README.md @@ -21,6 +21,24 @@ And a big thanks to all GitHub sponsors who helped with some of my costs before ## What's New +### July 28, 2022 +* Add freshly minted DeiT-III Medium (width=512, depth=12, num_heads=8) model weights. Thanks [Hugo Touvron](https://github.com/TouvronHugo)! + +### July 27, 2022 +* All runtime benchmark and validation result csv files are finally up-to-date! +* A few more weights & model defs added: + * `darknetaa53` - 79.8 @ 256, 80.5 @ 288 + * `convnext_nano` - 80.8 @ 224, 81.5 @ 288 + * `cs3sedarknet_l` - 81.2 @ 256, 81.8 @ 288 + * `cs3darknet_x` - 81.8 @ 256, 82.2 @ 288 + * `cs3sedarknet_x` - 82.2 @ 256, 82.7 @ 288 + * `cs3edgenet_x` - 82.2 @ 256, 82.7 @ 288 + * `cs3se_edgenet_x` - 82.8 @ 256, 83.5 @ 320 +* `cs3*` weights above all trained on TPU w/ `bits_and_tpu` branch. Thanks to TRC program! +* Add output_stride=8 and 16 support to ConvNeXt (dilation) +* deit3 models not being able to resize pos_emb fixed +* Version 0.6.7 PyPi release (/w above bug fixes and new weighs since 0.6.5) + ### July 8, 2022 More models, more fixes * Official research models (w/ weights) added: @@ -178,185 +196,6 @@ More models, more fixes * SGDP and AdamP still won't work with PyTorch XLA but others should (have yet to test Adabelief, Adafactor, Adahessian myself). * EfficientNet-V2 XL TF ported weights added, but they don't validate well in PyTorch (L is better). The pre-processing for the V2 TF training is a bit diff and the fine-tuned 21k -> 1k weights are very sensitive and less robust than the 1k weights. * Added PyTorch trained EfficientNet-V2 'Tiny' w/ GlobalContext attn weights. Only .1-.2 top-1 better than the SE so more of a curiosity for those interested. - -### July 12, 2021 -* Add XCiT models from [official facebook impl](https://github.com/facebookresearch/xcit). Contributed by [Alexander Soare](https://github.com/alexander-soare) - -### July 5-9, 2021 -* Add `efficientnetv2_rw_t` weights, a custom 'tiny' 13.6M param variant that is a bit better than (non NoisyStudent) B3 models. Both faster and better accuracy (at same or lower res) - * top-1 82.34 @ 288x288 and 82.54 @ 320x320 -* Add [SAM pretrained](https://arxiv.org/abs/2106.01548) in1k weight for ViT B/16 (`vit_base_patch16_sam_224`) and B/32 (`vit_base_patch32_sam_224`) models. -* Add 'Aggregating Nested Transformer' (NesT) w/ weights converted from official [Flax impl](https://github.com/google-research/nested-transformer). Contributed by [Alexander Soare](https://github.com/alexander-soare). - * `jx_nest_base` - 83.534, `jx_nest_small` - 83.120, `jx_nest_tiny` - 81.426 - -### June 23, 2021 -* Reproduce gMLP model training, `gmlp_s16_224` trained to 79.6 top-1, matching [paper](https://arxiv.org/abs/2105.08050). Hparams for this and other recent MLP training [here](https://gist.github.com/rwightman/d6c264a9001f9167e06c209f630b2cc6) - -### June 20, 2021 -* Release Vision Transformer 'AugReg' weights from [How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers](https://arxiv.org/abs/2106.10270) - * .npz weight loading support added, can load any of the 50K+ weights from the [AugReg series](https://console.cloud.google.com/storage/browser/vit_models/augreg) - * See [example notebook](https://colab.research.google.com/github/google-research/vision_transformer/blob/master/vit_jax_augreg.ipynb) from [official impl](https://github.com/google-research/vision_transformer/) for navigating the augreg weights - * Replaced all default weights w/ best AugReg variant (if possible). All AugReg 21k classifiers work. - * Highlights: `vit_large_patch16_384` (87.1 top-1), `vit_large_r50_s32_384` (86.2 top-1), `vit_base_patch16_384` (86.0 top-1) - * `vit_deit_*` renamed to just `deit_*` - * Remove my old small model, replace with DeiT compatible small w/ AugReg weights -* Add 1st training of my `gmixer_24_224` MLP /w GLU, 78.1 top-1 w/ 25M params. -* Add weights from official ResMLP release (https://github.com/facebookresearch/deit) -* Add `eca_nfnet_l2` weights from my 'lightweight' series. 84.7 top-1 at 384x384. -* Add distilled BiT 50x1 student and 152x2 Teacher weights from [Knowledge distillation: A good teacher is patient and consistent](https://arxiv.org/abs/2106.05237) -* NFNets and ResNetV2-BiT models work w/ Pytorch XLA now - * weight standardization uses F.batch_norm instead of std_mean (std_mean wasn't lowered) - * eps values adjusted, will be slight differences but should be quite close -* Improve test coverage and classifier interface of non-conv (vision transformer and mlp) models -* Cleanup a few classifier / flatten details for models w/ conv classifiers or early global pool -* Please report any regressions, this PR touched quite a few models. - -### June 8, 2021 -* Add first ResMLP weights, trained in PyTorch XLA on TPU-VM w/ my XLA branch. 24 block variant, 79.2 top-1. -* Add ResNet51-Q model w/ pretrained weights at 82.36 top-1. - * NFNet inspired block layout with quad layer stem and no maxpool - * Same param count (35.7M) and throughput as ResNetRS-50 but +1.5 top-1 @ 224x224 and +2.5 top-1 at 288x288 - -### May 25, 2021 -* Add LeViT, Visformer, ConViT (PR by Aman Arora), Twins (PR by paper authors) transformer models -* Add ResMLP and gMLP MLP vision models to the existing MLP Mixer impl -* Fix a number of torchscript issues with various vision transformer models -* Cleanup input_size/img_size override handling and improve testing / test coverage for all vision transformer and MLP models -* More flexible pos embedding resize (non-square) for ViT and TnT. Thanks [Alexander Soare](https://github.com/alexander-soare) -* Add `efficientnetv2_rw_m` model and weights (started training before official code). 84.8 top-1, 53M params. - -### May 14, 2021 -* Add EfficientNet-V2 official model defs w/ ported weights from official [Tensorflow/Keras](https://github.com/google/automl/tree/master/efficientnetv2) impl. - * 1k trained variants: `tf_efficientnetv2_s/m/l` - * 21k trained variants: `tf_efficientnetv2_s/m/l_in21k` - * 21k pretrained -> 1k fine-tuned: `tf_efficientnetv2_s/m/l_in21ft1k` - * v2 models w/ v1 scaling: `tf_efficientnetv2_b0` through `b3` - * Rename my prev V2 guess `efficientnet_v2s` -> `efficientnetv2_rw_s` - * Some blank `efficientnetv2_*` models in-place for future native PyTorch training - -### May 5, 2021 -* Add MLP-Mixer models and port pretrained weights from [Google JAX impl](https://github.com/google-research/vision_transformer/tree/linen) -* Add CaiT models and pretrained weights from [FB](https://github.com/facebookresearch/deit) -* Add ResNet-RS models and weights from [TF](https://github.com/tensorflow/tpu/tree/master/models/official/resnet/resnet_rs). Thanks [Aman Arora](https://github.com/amaarora) -* Add CoaT models and weights. Thanks [Mohammed Rizin](https://github.com/morizin) -* Add new ImageNet-21k weights & finetuned weights for TResNet, MobileNet-V3, ViT models. Thanks [mrT](https://github.com/mrT23) -* Add GhostNet models and weights. Thanks [Kai Han](https://github.com/iamhankai) -* Update ByoaNet attention modules - * Improve SA module inits - * Hack together experimental stand-alone Swin based attn module and `swinnet` - * Consistent '26t' model defs for experiments. -* Add improved Efficientnet-V2S (prelim model def) weights. 83.8 top-1. -* WandB logging support - -### April 13, 2021 -* Add Swin Transformer models and weights from https://github.com/microsoft/Swin-Transformer - -### April 12, 2021 -* Add ECA-NFNet-L1 (slimmed down F1 w/ SiLU, 41M params) trained with this code. 84% top-1 @ 320x320. Trained at 256x256. -* Add EfficientNet-V2S model (unverified model definition) weights. 83.3 top-1 @ 288x288. Only trained single res 224. Working on progressive training. -* Add ByoaNet model definition (Bring-your-own-attention) w/ SelfAttention block and corresponding SA/SA-like modules and model defs - * Lambda Networks - https://arxiv.org/abs/2102.08602 - * Bottleneck Transformers - https://arxiv.org/abs/2101.11605 - * Halo Nets - https://arxiv.org/abs/2103.12731 -* Adabelief optimizer contributed by Juntang Zhuang - -### April 1, 2021 -* Add snazzy `benchmark.py` script for bulk `timm` model benchmarking of train and/or inference -* Add Pooling-based Vision Transformer (PiT) models (from https://github.com/naver-ai/pit) - * Merged distilled variant into main for torchscript compatibility - * Some `timm` cleanup/style tweaks and weights have hub download support -* Cleanup Vision Transformer (ViT) models - * Merge distilled (DeiT) model into main so that torchscript can work - * Support updated weight init (defaults to old still) that closer matches original JAX impl (possibly better training from scratch) - * Separate hybrid model defs into different file and add several new model defs to fiddle with, support patch_size != 1 for hybrids - * Fix fine-tuning num_class changes (PiT and ViT) and pos_embed resizing (Vit) with distilled variants - * nn.Sequential for block stack (does not break downstream compat) -* TnT (Transformer-in-Transformer) models contributed by author (from https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/TNT) -* Add RegNetY-160 weights from DeiT teacher model -* Add new NFNet-L0 w/ SE attn (rename `nfnet_l0b`->`nfnet_l0`) weights 82.75 top-1 @ 288x288 -* Some fixes/improvements for TFDS dataset wrapper - -### March 17, 2021 -* Add new ECA-NFNet-L0 (rename `nfnet_l0c`->`eca_nfnet_l0`) weights trained by myself. - * 82.6 top-1 @ 288x288, 82.8 @ 320x320, trained at 224x224 - * Uses SiLU activation, approx 2x faster than `dm_nfnet_f0` and 50% faster than `nfnet_f0s` w/ 1/3 param count -* Integrate [Hugging Face model hub](https://huggingface.co/models) into timm create_model and default_cfg handling for pretrained weight and config sharing (more on this soon!) -* Merge HardCoRe NAS models contributed by https://github.com/yoniaflalo -* Merge PyTorch trained EfficientNet-EL and pruned ES/EL variants contributed by [DeGirum](https://github.com/DeGirum) - - -### March 7, 2021 -* First 0.4.x PyPi release w/ NFNets (& related), ByoB (GPU-Efficient, RepVGG, etc). -* Change feature extraction for pre-activation nets (NFNets, ResNetV2) to return features before activation. -* Tested with PyTorch 1.8 release. Updated CI to use 1.8. -* Benchmarked several arch on RTX 3090, Titan RTX, and V100 across 1.7.1, 1.8, NGC 20.12, and 21.02. Some interesting performance variations to take note of https://gist.github.com/rwightman/bb59f9e245162cee0e38bd66bd8cd77f - -### Feb 18, 2021 -* Add pretrained weights and model variants for NFNet-F* models from [DeepMind Haiku impl](https://github.com/deepmind/deepmind-research/tree/master/nfnets). - * Models are prefixed with `dm_`. They require SAME padding conv, skipinit enabled, and activation gains applied in act fn. - * These models are big, expect to run out of GPU memory. With the GELU activiation + other options, they are roughly 1/2 the inference speed of my SiLU PyTorch optimized `s` variants. - * Original model results are based on pre-processing that is not the same as all other models so you'll see different results in the results csv (once updated). - * Matching the original pre-processing as closely as possible I get these results: - * `dm_nfnet_f6` - 86.352 - * `dm_nfnet_f5` - 86.100 - * `dm_nfnet_f4` - 85.834 - * `dm_nfnet_f3` - 85.676 - * `dm_nfnet_f2` - 85.178 - * `dm_nfnet_f1` - 84.696 - * `dm_nfnet_f0` - 83.464 - -### Feb 16, 2021 -* Add Adaptive Gradient Clipping (AGC) as per https://arxiv.org/abs/2102.06171. Integrated w/ PyTorch gradient clipping via mode arg that defaults to prev 'norm' mode. For backward arg compat, clip-grad arg must be specified to enable when using train.py. - * AGC w/ default clipping factor `--clip-grad .01 --clip-mode agc` - * PyTorch global norm of 1.0 (old behaviour, always norm), `--clip-grad 1.0` - * PyTorch value clipping of 10, `--clip-grad 10. --clip-mode value` - * AGC performance is definitely sensitive to the clipping factor. More experimentation needed to determine good values for smaller batch sizes and optimizers besides those in paper. So far I've found .001-.005 is necessary for stable RMSProp training w/ NFNet/NF-ResNet. - -### Feb 12, 2021 -* Update Normalization-Free nets to include new NFNet-F (https://arxiv.org/abs/2102.06171) model defs - -### Feb 10, 2021 -* First Normalization-Free model training experiments done, - * nf_resnet50 - 80.68 top-1 @ 288x288, 80.31 @ 256x256 - * nf_regnet_b1 - 79.30 @ 288x288, 78.75 @ 256x256 -* More model archs, incl a flexible ByobNet backbone ('Bring-your-own-blocks') - * GPU-Efficient-Networks (https://github.com/idstcv/GPU-Efficient-Networks), impl in `byobnet.py` - * RepVGG (https://github.com/DingXiaoH/RepVGG), impl in `byobnet.py` - * classic VGG (from torchvision, impl in `vgg.py`) -* Refinements to normalizer layer arg handling and normalizer+act layer handling in some models -* Default AMP mode changed to native PyTorch AMP instead of APEX. Issues not being fixed with APEX. Native works with `--channels-last` and `--torchscript` model training, APEX does not. -* Fix a few bugs introduced since last pypi release - -### Feb 8, 2021 -* Add several ResNet weights with ECA attention. 26t & 50t trained @ 256, test @ 320. 269d train @ 256, fine-tune @320, test @ 352. - * `ecaresnet26t` - 79.88 top-1 @ 320x320, 79.08 @ 256x256 - * `ecaresnet50t` - 82.35 top-1 @ 320x320, 81.52 @ 256x256 - * `ecaresnet269d` - 84.93 top-1 @ 352x352, 84.87 @ 320x320 -* Remove separate tiered (`t`) vs tiered_narrow (`tn`) ResNet model defs, all `tn` changed to `t` and `t` models removed (`seresnext26t_32x4d` only model w/ weights that was removed). -* Support model default_cfgs with separate train vs test resolution `test_input_size` and remove extra `_320` suffix ResNet model defs that were just for test. - -### Jan 30, 2021 -* Add initial "Normalization Free" NF-RegNet-B* and NF-ResNet model definitions based on [paper](https://arxiv.org/abs/2101.08692) - -### Jan 25, 2021 -* Add ResNetV2 Big Transfer (BiT) models w/ ImageNet-1k and 21k weights from https://github.com/google-research/big_transfer -* Add official R50+ViT-B/16 hybrid models + weights from https://github.com/google-research/vision_transformer -* ImageNet-21k ViT weights are added w/ model defs and representation layer (pre logits) support - * NOTE: ImageNet-21k classifier heads were zero'd in original weights, they are only useful for transfer learning -* Add model defs and weights for DeiT Vision Transformer models from https://github.com/facebookresearch/deit -* Refactor dataset classes into ImageDataset/IterableImageDataset + dataset specific parser classes -* Add Tensorflow-Datasets (TFDS) wrapper to allow use of TFDS image classification sets with train script - * Ex: `train.py /data/tfds --dataset tfds/oxford_iiit_pet --val-split test --model resnet50 -b 256 --amp --num-classes 37 --opt adamw --lr 3e-4 --weight-decay .001 --pretrained -j 2` -* Add improved .tar dataset parser that reads images from .tar, folder of .tar files, or .tar within .tar - * Run validation on full ImageNet-21k directly from tar w/ BiT model: `validate.py /data/fall11_whole.tar --model resnetv2_50x1_bitm_in21k --amp` -* Models in this update should be stable w/ possible exception of ViT/BiT, possibility of some regressions with train/val scripts and dataset handling - -### Jan 3, 2021 -* Add SE-ResNet-152D weights - * 256x256 val, 0.94 crop top-1 - 83.75 - * 320x320 val, 1.0 crop - 84.36 -* Update [results files](results/) - ## Introduction @@ -379,7 +218,8 @@ A full version of the list below with source links can be found in the [document * ConvNeXt - https://arxiv.org/abs/2201.03545 * ConViT (Soft Convolutional Inductive Biases Vision Transformers)- https://arxiv.org/abs/2103.10697 * CspNet (Cross-Stage Partial Networks) - https://arxiv.org/abs/1911.11929 -* DeiT (Vision Transformer) - https://arxiv.org/abs/2012.12877 +* DeiT - https://arxiv.org/abs/2012.12877 +* DeiT-III - https://arxiv.org/pdf/2204.07118.pdf * DenseNet - https://arxiv.org/abs/1608.06993 * DLA - https://arxiv.org/abs/1707.06484 * DPN (Dual-Path Network) - https://arxiv.org/abs/1707.01629 @@ -411,6 +251,7 @@ A full version of the list below with source links can be found in the [document * HardCoRe-NAS - https://arxiv.org/abs/2102.11646 * LCNet - https://arxiv.org/abs/2109.15099 * MobileViT - https://arxiv.org/abs/2110.02178 +* MobileViT-V2 - https://arxiv.org/abs/2206.02680 * NASNet-A - https://arxiv.org/abs/1707.07012 * NesT - https://arxiv.org/abs/2105.12723 * NFNet-F - https://arxiv.org/abs/2102.06171 diff --git a/benchmark.py b/benchmark.py index 23047bb5..4679a009 100755 --- a/benchmark.py +++ b/benchmark.py @@ -21,7 +21,7 @@ import torch.nn.parallel from timm.data import resolve_data_config from timm.models import create_model, is_model, list_models from timm.optim import create_optimizer_v2 -from timm.utils import setup_default_logging, set_jit_fuser +from timm.utils import setup_default_logging, set_jit_fuser, decay_batch_step, check_batch_size_retry has_apex = False try: @@ -506,34 +506,31 @@ class ProfileRunner(BenchmarkRunner): return results -def decay_batch_exp(batch_size, factor=0.5, divisor=16): - out_batch_size = batch_size * factor - if out_batch_size > divisor: - out_batch_size = (out_batch_size + 1) // divisor * divisor - else: - out_batch_size = batch_size - 1 - return max(0, int(out_batch_size)) - - -def _try_run(model_name, bench_fn, bench_kwargs, initial_batch_size, no_batch_size_retry=False): +def _try_run( + model_name, + bench_fn, + bench_kwargs, + initial_batch_size, + no_batch_size_retry=False +): batch_size = initial_batch_size results = dict() error_str = 'Unknown' - while batch_size >= 1: - torch.cuda.empty_cache() + while batch_size: try: + torch.cuda.empty_cache() bench = bench_fn(model_name=model_name, batch_size=batch_size, **bench_kwargs) results = bench.run() return results except RuntimeError as e: error_str = str(e) - if 'channels_last' in error_str: - _logger.error(f'{model_name} not supported in channels_last, skipping.') - break _logger.error(f'"{error_str}" while running benchmark.') + if not check_batch_size_retry(error_str): + _logger.error(f'Unrecoverable error encountered while benchmarking {model_name}, skipping.') + break if no_batch_size_retry: break - batch_size = decay_batch_exp(batch_size) + batch_size = decay_batch_step(batch_size) _logger.warning(f'Reducing batch size to {batch_size} for retry.') results['error'] = error_str return results @@ -586,6 +583,8 @@ def benchmark(args): if prefix and 'error' not in run_results: run_results = {'_'.join([prefix, k]): v for k, v in run_results.items()} model_results.update(run_results) + if 'error' in run_results: + break if 'error' not in model_results: param_count = model_results.pop('infer_param_count', model_results.pop('train_param_count', 0)) model_results.setdefault('param_count', param_count) diff --git a/bulk_runner.py b/bulk_runner.py new file mode 100755 index 00000000..b71d0bb6 --- /dev/null +++ b/bulk_runner.py @@ -0,0 +1,184 @@ +#!/usr/bin/env python3 +""" Bulk Model Script Runner + +Run validation or benchmark script in separate process for each model + +Benchmark all 'vit*' models: +python bulk_runner.py --model-list 'vit*' --results-file vit_bench.csv benchmark.py --amp -b 512 + +Validate all models: +python bulk_runner.py --model-list all --results-file val.csv --pretrained validate.py /imagenet/validation/ --amp -b 512 --retry + +Hacked together by Ross Wightman (https://github.com/rwightman) +""" +import argparse +import os +import sys +import csv +import json +import subprocess +import time +from typing import Callable, List, Tuple, Union + + +from timm.models import is_model, list_models + + +parser = argparse.ArgumentParser(description='Per-model process launcher') + +# model and results args +parser.add_argument( + '--model-list', metavar='NAME', default='', + help='txt file based list of model names to benchmark') +parser.add_argument( + '--results-file', default='', type=str, metavar='FILENAME', + help='Output csv file for validation results (summary)') +parser.add_argument( + '--sort-key', default='', type=str, metavar='COL', + help='Specify sort key for results csv') +parser.add_argument( + "--pretrained", action='store_true', + help="only run models with pretrained weights") + +parser.add_argument( + "--delay", + type=float, + default=0, + help="Interval, in seconds, to delay between model invocations.", +) +parser.add_argument( + "--start_method", type=str, default="spawn", choices=["spawn", "fork", "forkserver"], + help="Multiprocessing start method to use when creating workers.", +) +parser.add_argument( + "--no_python", + help="Skip prepending the script with 'python' - just execute it directly. Useful " + "when the script is not a Python script.", +) +parser.add_argument( + "-m", + "--module", + help="Change each process to interpret the launch script as a Python module, executing " + "with the same behavior as 'python -m'.", +) + +# positional +parser.add_argument( + "script", type=str, + help="Full path to the program/script to be launched for each model config.", +) +parser.add_argument("script_args", nargs=argparse.REMAINDER) + + +def cmd_from_args(args) -> Tuple[Union[Callable, str], List[str]]: + # If ``args`` not passed, defaults to ``sys.argv[:1]`` + with_python = not args.no_python + cmd: Union[Callable, str] + cmd_args = [] + if with_python: + cmd = os.getenv("PYTHON_EXEC", sys.executable) + cmd_args.append("-u") + if args.module: + cmd_args.append("-m") + cmd_args.append(args.script) + else: + if args.module: + raise ValueError( + "Don't use both the '--no_python' flag" + " and the '--module' flag at the same time." + ) + cmd = args.script + cmd_args.extend(args.script_args) + + return cmd, cmd_args + + +def main(): + args = parser.parse_args() + cmd, cmd_args = cmd_from_args(args) + + model_cfgs = [] + model_names = [] + if args.model_list == 'all': + # NOTE should make this config, for validation / benchmark runs the focus is 1k models, + # so we filter out 21/22k and some other unusable heads. This will change in the future... + exclude_model_filters = ['*in21k', '*in22k', '*dino', '*_22k'] + model_names = list_models( + pretrained=args.pretrained, # only include models w/ pretrained checkpoints if set + exclude_filters=exclude_model_filters + ) + model_cfgs = [(n, None) for n in model_names] + elif not is_model(args.model_list): + # model name doesn't exist, try as wildcard filter + model_names = list_models(args.model_list) + model_cfgs = [(n, None) for n in model_names] + + if not model_cfgs and os.path.exists(args.model_list): + with open(args.model_list) as f: + model_names = [line.rstrip() for line in f] + model_cfgs = [(n, None) for n in model_names] + + if len(model_cfgs): + results_file = args.results_file or './results.csv' + results = [] + errors = [] + print('Running script on these models: {}'.format(', '.join(model_names))) + if not args.sort_key: + if 'benchmark' in args.script: + if any(['train' in a for a in args.script_args]): + sort_key = 'train_samples_per_sec' + else: + sort_key = 'infer_samples_per_sec' + else: + sort_key = 'top1' + else: + sort_key = args.sort_key + print(f'Script: {args.script}, Args: {args.script_args}, Sort key: {sort_key}') + + try: + for m, _ in model_cfgs: + if not m: + continue + args_str = (cmd, *[str(e) for e in cmd_args], '--model', m) + try: + o = subprocess.check_output(args=args_str).decode('utf-8').split('--result')[-1] + r = json.loads(o) + results.append(r) + except Exception as e: + # FIXME batch_size retry loop is currently done in either validation.py or benchmark.py + # for further robustness (but more overhead), we may want to manage that by looping here... + errors.append(dict(model=m, error=str(e))) + if args.delay: + time.sleep(args.delay) + except KeyboardInterrupt as e: + pass + + errors.extend(list(filter(lambda x: 'error' in x, results))) + if errors: + print(f'{len(errors)} models had errors during run.') + for e in errors: + print(f"\t {e['model']} ({e.get('error', 'Unknown')})") + results = list(filter(lambda x: 'error' not in x, results)) + + no_sortkey = list(filter(lambda x: sort_key not in x, results)) + if no_sortkey: + print(f'{len(no_sortkey)} results missing sort key, skipping sort.') + else: + results = sorted(results, key=lambda x: x[sort_key], reverse=True) + + if len(results): + print(f'{len(results)} models run successfully. Saving results to {results_file}.') + write_results(results_file, results) + + +def write_results(results_file, results): + with open(results_file, mode='w') as cf: + dw = csv.DictWriter(cf, fieldnames=results[0].keys()) + dw.writeheader() + for r in results: + dw.writerow(r) + cf.flush() + + +if __name__ == '__main__': + main() diff --git a/docs/archived_changes.md b/docs/archived_changes.md index 36b7b9a1..9c2b62b6 100644 --- a/docs/archived_changes.md +++ b/docs/archived_changes.md @@ -1,5 +1,37 @@ # Archived Changes +### July 12, 2021 +* Add XCiT models from [official facebook impl](https://github.com/facebookresearch/xcit). Contributed by [Alexander Soare](https://github.com/alexander-soare) + +### July 5-9, 2021 +* Add `efficientnetv2_rw_t` weights, a custom 'tiny' 13.6M param variant that is a bit better than (non NoisyStudent) B3 models. Both faster and better accuracy (at same or lower res) + * top-1 82.34 @ 288x288 and 82.54 @ 320x320 +* Add [SAM pretrained](https://arxiv.org/abs/2106.01548) in1k weight for ViT B/16 (`vit_base_patch16_sam_224`) and B/32 (`vit_base_patch32_sam_224`) models. +* Add 'Aggregating Nested Transformer' (NesT) w/ weights converted from official [Flax impl](https://github.com/google-research/nested-transformer). Contributed by [Alexander Soare](https://github.com/alexander-soare). + * `jx_nest_base` - 83.534, `jx_nest_small` - 83.120, `jx_nest_tiny` - 81.426 + +### June 23, 2021 +* Reproduce gMLP model training, `gmlp_s16_224` trained to 79.6 top-1, matching [paper](https://arxiv.org/abs/2105.08050). Hparams for this and other recent MLP training [here](https://gist.github.com/rwightman/d6c264a9001f9167e06c209f630b2cc6) + +### June 20, 2021 +* Release Vision Transformer 'AugReg' weights from [How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers](https://arxiv.org/abs/2106.10270) + * .npz weight loading support added, can load any of the 50K+ weights from the [AugReg series](https://console.cloud.google.com/storage/browser/vit_models/augreg) + * See [example notebook](https://colab.research.google.com/github/google-research/vision_transformer/blob/master/vit_jax_augreg.ipynb) from [official impl](https://github.com/google-research/vision_transformer/) for navigating the augreg weights + * Replaced all default weights w/ best AugReg variant (if possible). All AugReg 21k classifiers work. + * Highlights: `vit_large_patch16_384` (87.1 top-1), `vit_large_r50_s32_384` (86.2 top-1), `vit_base_patch16_384` (86.0 top-1) + * `vit_deit_*` renamed to just `deit_*` + * Remove my old small model, replace with DeiT compatible small w/ AugReg weights +* Add 1st training of my `gmixer_24_224` MLP /w GLU, 78.1 top-1 w/ 25M params. +* Add weights from official ResMLP release (https://github.com/facebookresearch/deit) +* Add `eca_nfnet_l2` weights from my 'lightweight' series. 84.7 top-1 at 384x384. +* Add distilled BiT 50x1 student and 152x2 Teacher weights from [Knowledge distillation: A good teacher is patient and consistent](https://arxiv.org/abs/2106.05237) +* NFNets and ResNetV2-BiT models work w/ Pytorch XLA now + * weight standardization uses F.batch_norm instead of std_mean (std_mean wasn't lowered) + * eps values adjusted, will be slight differences but should be quite close +* Improve test coverage and classifier interface of non-conv (vision transformer and mlp) models +* Cleanup a few classifier / flatten details for models w/ conv classifiers or early global pool +* Please report any regressions, this PR touched quite a few models. + ### June 8, 2021 * Add first ResMLP weights, trained in PyTorch XLA on TPU-VM w/ my XLA branch. 24 block variant, 79.2 top-1. * Add ResNet51-Q model w/ pretrained weights at 82.36 top-1. diff --git a/docs/changes.md b/docs/changes.md index d2965e8f..800dc443 100644 --- a/docs/changes.md +++ b/docs/changes.md @@ -1,5 +1,81 @@ # Recent Changes +### July 27, 2022 +* All runtime benchmark and validation result csv files are up-to-date! +* A few more weights & model defs added: + * `darknetaa53` - 79.8 @ 256, 80.5 @ 288 + * `convnext_nano` - 80.8 @ 224, 81.5 @ 288 + * `cs3sedarknet_l` - 81.2 @ 256, 81.8 @ 288 + * `cs3darknet_x` - 81.8 @ 256, 82.2 @ 288 + * `cs3sedarknet_x` - 82.2 @ 256, 82.7 @ 288 + * `cs3edgenet_x` - 82.2 @ 256, 82.7 @ 288 + * `cs3se_edgenet_x` - 82.8 @ 256, 83.5 @ 320 +* `cs3*` weights above all trained on TPU w/ `bits_and_tpu` branch. Thanks to TRC program! +* Add output_stride=8 and 16 support to ConvNeXt (dilation) +* deit3 models not being able to resize pos_emb fixed +* Version 0.6.7 PyPi release (/w above bug fixes and new weighs since 0.6.5) + +### July 8, 2022 +More models, more fixes +* Official research models (w/ weights) added: + * EdgeNeXt from (https://github.com/mmaaz60/EdgeNeXt) + * MobileViT-V2 from (https://github.com/apple/ml-cvnets) + * DeiT III (Revenge of the ViT) from (https://github.com/facebookresearch/deit) +* My own models: + * Small `ResNet` defs added by request with 1 block repeats for both basic and bottleneck (resnet10 and resnet14) + * `CspNet` refactored with dataclass config, simplified CrossStage3 (`cs3`) option. These are closer to YOLO-v5+ backbone defs. + * More relative position vit fiddling. Two `srelpos` (shared relative position) models trained, and a medium w/ class token. + * Add an alternate downsample mode to EdgeNeXt and train a `small` model. Better than original small, but not their new USI trained weights. +* My own model weight results (all ImageNet-1k training) + * `resnet10t` - 66.5 @ 176, 68.3 @ 224 + * `resnet14t` - 71.3 @ 176, 72.3 @ 224 + * `resnetaa50` - 80.6 @ 224 , 81.6 @ 288 + * `darknet53` - 80.0 @ 256, 80.5 @ 288 + * `cs3darknet_m` - 77.0 @ 256, 77.6 @ 288 + * `cs3darknet_focus_m` - 76.7 @ 256, 77.3 @ 288 + * `cs3darknet_l` - 80.4 @ 256, 80.9 @ 288 + * `cs3darknet_focus_l` - 80.3 @ 256, 80.9 @ 288 + * `vit_srelpos_small_patch16_224` - 81.1 @ 224, 82.1 @ 320 + * `vit_srelpos_medium_patch16_224` - 82.3 @ 224, 83.1 @ 320 + * `vit_relpos_small_patch16_cls_224` - 82.6 @ 224, 83.6 @ 320 + * `edgnext_small_rw` - 79.6 @ 224, 80.4 @ 320 +* `cs3`, `darknet`, and `vit_*relpos` weights above all trained on TPU thanks to TRC program! Rest trained on overheating GPUs. +* Hugging Face Hub support fixes verified, demo notebook TBA +* Pretrained weights / configs can be loaded externally (ie from local disk) w/ support for head adaptation. +* Add support to change image extensions scanned by `timm` datasets/parsers. See (https://github.com/rwightman/pytorch-image-models/pull/1274#issuecomment-1178303103) +* Default ConvNeXt LayerNorm impl to use `F.layer_norm(x.permute(0, 2, 3, 1), ...).permute(0, 3, 1, 2)` via `LayerNorm2d` in all cases. + * a bit slower than previous custom impl on some hardware (ie Ampere w/ CL), but overall fewer regressions across wider HW / PyTorch version ranges. + * previous impl exists as `LayerNormExp2d` in `models/layers/norm.py` +* Numerous bug fixes +* Currently testing for imminent PyPi 0.6.x release +* LeViT pretraining of larger models still a WIP, they don't train well / easily without distillation. Time to add distill support (finally)? +* ImageNet-22k weight training + finetune ongoing, work on multi-weight support (slowly) chugging along (there are a LOT of weights, sigh) ... + +### May 13, 2022 +* Official Swin-V2 models and weights added from (https://github.com/microsoft/Swin-Transformer). Cleaned up to support torchscript. +* Some refactoring for existing `timm` Swin-V2-CR impl, will likely do a bit more to bring parts closer to official and decide whether to merge some aspects. +* More Vision Transformer relative position / residual post-norm experiments (all trained on TPU thanks to TRC program) + * `vit_relpos_small_patch16_224` - 81.5 @ 224, 82.5 @ 320 -- rel pos, layer scale, no class token, avg pool + * `vit_relpos_medium_patch16_rpn_224` - 82.3 @ 224, 83.1 @ 320 -- rel pos + res-post-norm, no class token, avg pool + * `vit_relpos_medium_patch16_224` - 82.5 @ 224, 83.3 @ 320 -- rel pos, layer scale, no class token, avg pool + * `vit_relpos_base_patch16_gapcls_224` - 82.8 @ 224, 83.9 @ 320 -- rel pos, layer scale, class token, avg pool (by mistake) +* Bring 512 dim, 8-head 'medium' ViT model variant back to life (after using in a pre DeiT 'small' model for first ViT impl back in 2020) +* Add ViT relative position support for switching btw existing impl and some additions in official Swin-V2 impl for future trials +* Sequencer2D impl (https://arxiv.org/abs/2205.01972), added via PR from author (https://github.com/okojoalg) + +### May 2, 2022 +* Vision Transformer experiments adding Relative Position (Swin-V2 log-coord) (`vision_transformer_relpos.py`) and Residual Post-Norm branches (from Swin-V2) (`vision_transformer*.py`) + * `vit_relpos_base_patch32_plus_rpn_256` - 79.5 @ 256, 80.6 @ 320 -- rel pos + extended width + res-post-norm, no class token, avg pool + * `vit_relpos_base_patch16_224` - 82.5 @ 224, 83.6 @ 320 -- rel pos, layer scale, no class token, avg pool + * `vit_base_patch16_rpn_224` - 82.3 @ 224 -- rel pos + res-post-norm, no class token, avg pool +* Vision Transformer refactor to remove representation layer that was only used in initial vit and rarely used since with newer pretrain (ie `How to Train Your ViT`) +* `vit_*` models support removal of class token, use of global average pool, use of fc_norm (ala beit, mae). + +### April 22, 2022 +* `timm` models are now officially supported in [fast.ai](https://www.fast.ai/)! Just in time for the new Practical Deep Learning course. `timmdocs` documentation link updated to [timm.fast.ai](http://timm.fast.ai/). +* Two more model weights added in the TPU trained [series](https://github.com/rwightman/pytorch-image-models/releases/tag/v0.1-tpu-weights). Some In22k pretrain still in progress. + * `seresnext101d_32x8d` - 83.69 @ 224, 84.35 @ 288 + * `seresnextaa101d_32x8d` (anti-aliased w/ AvgPool2d) - 83.85 @ 224, 84.57 @ 288 ### March 23, 2022 * Add `ParallelBlock` and `LayerScale` option to base vit models to support model configs in [Three things everyone should know about ViT](https://arxiv.org/abs/2203.09795) @@ -96,35 +172,3 @@ * SGDP and AdamP still won't work with PyTorch XLA but others should (have yet to test Adabelief, Adafactor, Adahessian myself). * EfficientNet-V2 XL TF ported weights added, but they don't validate well in PyTorch (L is better). The pre-processing for the V2 TF training is a bit diff and the fine-tuned 21k -> 1k weights are very sensitive and less robust than the 1k weights. * Added PyTorch trained EfficientNet-V2 'Tiny' w/ GlobalContext attn weights. Only .1-.2 top-1 better than the SE so more of a curiosity for those interested. - -### July 12, 2021 -* Add XCiT models from [official facebook impl](https://github.com/facebookresearch/xcit). Contributed by [Alexander Soare](https://github.com/alexander-soare) - -### July 5-9, 2021 -* Add `efficientnetv2_rw_t` weights, a custom 'tiny' 13.6M param variant that is a bit better than (non NoisyStudent) B3 models. Both faster and better accuracy (at same or lower res) - * top-1 82.34 @ 288x288 and 82.54 @ 320x320 -* Add [SAM pretrained](https://arxiv.org/abs/2106.01548) in1k weight for ViT B/16 (`vit_base_patch16_sam_224`) and B/32 (`vit_base_patch32_sam_224`) models. -* Add 'Aggregating Nested Transformer' (NesT) w/ weights converted from official [Flax impl](https://github.com/google-research/nested-transformer). Contributed by [Alexander Soare](https://github.com/alexander-soare). - * `jx_nest_base` - 83.534, `jx_nest_small` - 83.120, `jx_nest_tiny` - 81.426 - -### June 23, 2021 -* Reproduce gMLP model training, `gmlp_s16_224` trained to 79.6 top-1, matching [paper](https://arxiv.org/abs/2105.08050). Hparams for this and other recent MLP training [here](https://gist.github.com/rwightman/d6c264a9001f9167e06c209f630b2cc6) - -### June 20, 2021 -* Release Vision Transformer 'AugReg' weights from [How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers](https://arxiv.org/abs/2106.10270) - * .npz weight loading support added, can load any of the 50K+ weights from the [AugReg series](https://console.cloud.google.com/storage/browser/vit_models/augreg) - * See [example notebook](https://colab.research.google.com/github/google-research/vision_transformer/blob/master/vit_jax_augreg.ipynb) from [official impl](https://github.com/google-research/vision_transformer/) for navigating the augreg weights - * Replaced all default weights w/ best AugReg variant (if possible). All AugReg 21k classifiers work. - * Highlights: `vit_large_patch16_384` (87.1 top-1), `vit_large_r50_s32_384` (86.2 top-1), `vit_base_patch16_384` (86.0 top-1) - * `vit_deit_*` renamed to just `deit_*` - * Remove my old small model, replace with DeiT compatible small w/ AugReg weights -* Add 1st training of my `gmixer_24_224` MLP /w GLU, 78.1 top-1 w/ 25M params. -* Add weights from official ResMLP release (https://github.com/facebookresearch/deit) -* Add `eca_nfnet_l2` weights from my 'lightweight' series. 84.7 top-1 at 384x384. -* Add distilled BiT 50x1 student and 152x2 Teacher weights from [Knowledge distillation: A good teacher is patient and consistent](https://arxiv.org/abs/2106.05237) -* NFNets and ResNetV2-BiT models work w/ Pytorch XLA now - * weight standardization uses F.batch_norm instead of std_mean (std_mean wasn't lowered) - * eps values adjusted, will be slight differences but should be quite close -* Improve test coverage and classifier interface of non-conv (vision transformer and mlp) models -* Cleanup a few classifier / flatten details for models w/ conv classifiers or early global pool -* Please report any regressions, this PR touched quite a few models. diff --git a/docs/feature_extraction.md b/docs/feature_extraction.md index 3d638d65..86a0e28e 100644 --- a/docs/feature_extraction.md +++ b/docs/feature_extraction.md @@ -90,6 +90,7 @@ print(f'Pooled shape: {o.shape}') ``` Output: ```text +Original shape: torch.Size([2, 1000]) Pooled shape: torch.Size([2, 1024]) ``` diff --git a/results/benchmark-infer-amp-nchw-pt110-cu113-rtx3090.csv b/results/benchmark-infer-amp-nchw-pt110-cu113-rtx3090.csv deleted file mode 100644 index d006a42b..00000000 --- a/results/benchmark-infer-amp-nchw-pt110-cu113-rtx3090.csv +++ /dev/null @@ -1,754 +0,0 @@ -model,infer_samples_per_sec,infer_step_time,infer_batch_size,infer_img_size,infer_gmacs,infer_macts,param_count -tinynet_e,45729.13,22.382,1024,106,0.03,0.69,2.04 -mobilenetv3_small_050,36893.28,27.745,1024,224,0.03,0.92,1.59 -lcnet_035,35105.45,29.158,1024,224,0.03,1.04,1.64 -lcnet_050,30263.97,33.825,1024,224,0.05,1.26,1.88 -tf_mobilenetv3_small_minimal_100,27416.94,37.338,1024,224,0.06,1.41,2.04 -mobilenetv3_small_075,26904.17,38.049,1024,224,0.05,1.3,2.04 -tinynet_d,25044.68,40.875,1024,152,0.05,1.42,2.34 -mobilenetv3_small_100,23617.79,43.346,1024,224,0.06,1.42,2.54 -tf_mobilenetv3_small_075,23189.43,44.147,1024,224,0.05,1.3,2.04 -tf_mobilenetv3_small_100,20762.5,49.309,1024,224,0.06,1.42,2.54 -levit_128s,19460.71,52.608,1024,224,0.31,1.88,7.78 -lcnet_075,19432.12,52.685,1024,224,0.1,1.99,2.36 -mnasnet_small,17836.77,57.398,1024,224,0.07,2.16,2.03 -mobilenetv2_035,17430.32,58.737,1024,224,0.07,2.86,1.68 -ghostnet_050,16407.44,62.399,1024,224,0.05,1.77,2.59 -regnetx_002,16261.91,62.957,1024,224,0.2,2.16,2.68 -lcnet_100,15473.86,66.165,1024,224,0.16,2.52,2.95 -regnety_002,15227.36,67.236,1024,224,0.2,2.17,3.16 -mobilenetv2_050,13934.38,73.476,1024,224,0.1,3.64,1.97 -levit_128,13275.72,77.121,1024,224,0.41,2.71,9.21 -mnasnet_050,13141.39,77.91,1024,224,0.11,3.07,2.22 -tinynet_c,12655.67,80.901,1024,184,0.11,2.87,2.46 -semnasnet_050,12612.89,81.175,1024,224,0.11,3.44,2.08 -levit_192,11388.57,89.902,1024,224,0.66,3.2,10.95 -gernet_s,10813.61,94.684,1024,224,0.75,2.65,8.17 -mixer_s32_224,10504.33,97.471,1024,224,1.0,2.28,19.1 -mobilenetv3_large_075,10490.35,97.601,1024,224,0.16,4.0,3.99 -vit_small_patch32_224,10240.88,99.979,1024,224,1.15,2.5,22.88 -regnetx_004,10074.95,101.626,1024,224,0.4,3.14,5.16 -lcnet_150,9963.3,102.765,1024,224,0.34,3.79,4.5 -ese_vovnet19b_slim_dw,9910.83,103.307,1024,224,0.4,5.28,1.9 -tf_mobilenetv3_large_minimal_100,9754.43,104.966,1024,224,0.22,4.4,3.92 -tf_mobilenetv3_large_075,9324.76,109.803,1024,224,0.16,4.0,3.99 -vit_tiny_r_s16_p8_224,9271.21,110.438,1024,224,0.44,2.06,6.34 -mobilenetv3_rw,9237.45,110.841,1024,224,0.23,4.41,5.48 -mobilenetv3_large_100_miil,9122.48,112.239,1024,224,0.23,4.41,5.48 -mobilenetv3_large_100,9113.48,112.349,1024,224,0.23,4.41,5.48 -swsl_resnet18,8964.25,114.22,1024,224,1.82,2.48,11.69 -ssl_resnet18,8954.23,114.347,1024,224,1.82,2.48,11.69 -resnet18,8950.63,114.393,1024,224,1.82,2.48,11.69 -gluon_resnet18_v1b,8904.35,114.988,1024,224,1.82,2.48,11.69 -ghostnet_100,8800.66,116.343,1024,224,0.15,3.55,5.18 -mobilenetv2_075,8784.57,116.556,1024,224,0.22,5.86,2.64 -mnasnet_075,8615.15,118.849,1024,224,0.23,4.77,3.17 -regnety_004,8508.99,120.332,1024,224,0.41,3.89,4.34 -seresnet18,8476.05,120.8,1024,224,1.82,2.49,11.78 -levit_256,8328.46,122.939,1024,224,1.13,4.23,18.89 -legacy_seresnet18,8221.84,124.534,1024,224,1.82,2.49,11.78 -tf_mobilenetv3_large_100,8193.03,124.971,1024,224,0.23,4.41,5.48 -tinynet_b,8097.58,126.445,1024,188,0.21,4.44,3.73 -semnasnet_075,8084.78,126.646,1024,224,0.23,5.54,2.91 -regnetx_006,8071.67,126.849,1024,224,0.61,3.98,6.2 -mobilenetv2_100,7909.09,129.46,1024,224,0.31,6.68,3.5 -hardcorenas_a,7647.53,133.887,1024,224,0.23,4.38,5.26 -hardcorenas_b,7621.16,134.351,1024,224,0.26,5.09,5.18 -mnasnet_b1,7496.38,136.587,1024,224,0.33,5.46,4.38 -resnet18d,7495.1,136.61,1024,224,2.06,3.29,11.71 -mnasnet_100,7464.6,137.169,1024,224,0.33,5.46,4.38 -regnety_006,7283.03,140.589,1024,224,0.61,4.33,6.06 -levit_256d,7198.1,142.247,1024,224,1.4,4.93,26.21 -ghostnet_130,7150.23,143.2,1024,224,0.24,4.6,7.36 -semnasnet_100,7147.27,143.26,1024,224,0.32,6.23,3.89 -mnasnet_a1,7145.4,143.297,1024,224,0.32,6.23,3.89 -hardcorenas_c,7122.02,143.767,1024,224,0.28,5.01,5.52 -spnasnet_100,7064.4,144.94,1024,224,0.35,6.03,4.42 -hardcorenas_d,7022.23,145.809,1024,224,0.3,4.93,7.5 -ese_vovnet19b_slim,7002.56,146.217,1024,224,1.69,3.52,3.17 -tf_efficientnetv2_b0,6802.55,150.52,1024,224,0.73,4.77,7.14 -regnetx_008,6364.35,160.884,1024,224,0.81,5.15,7.26 -tinynet_a,6111.01,167.554,1024,192,0.35,5.41,6.19 -efficientnet_lite0,6045.52,169.367,1024,224,0.4,6.74,4.65 -rexnet_100,6041.15,169.492,1024,224,0.41,7.44,4.8 -rexnetr_100,5996.51,170.755,1024,224,0.43,7.72,4.88 -mobilenetv2_110d,5977.45,171.298,1024,224,0.45,8.71,4.52 -resnetblur18,5956.09,171.912,1024,224,2.34,3.39,11.69 -regnety_008,5950.01,172.087,1024,224,0.81,5.25,6.26 -hardcorenas_f,5941.51,172.335,1024,224,0.35,5.57,8.2 -dla46_c,5913.03,173.163,1024,224,0.58,4.5,1.3 -hardcorenas_e,5713.6,179.209,1024,224,0.35,5.65,8.07 -skresnet18,5591.52,183.122,1024,224,1.82,3.24,11.96 -fbnetc_100,5586.56,183.283,1024,224,0.4,6.51,5.57 -regnetz_005,5486.82,186.617,1024,224,0.52,5.86,7.12 -tf_efficientnet_lite0,5460.79,187.507,1024,224,0.4,6.74,4.65 -efficientnet_b0,5369.25,190.703,1024,224,0.4,6.75,5.29 -efficientnet_b1_pruned,5363.23,190.917,1024,240,0.4,6.21,6.33 -mobilenetv2_140,5279.19,193.957,1024,224,0.6,9.57,6.11 -gluon_resnet34_v1b,5264.52,194.497,1024,224,3.67,3.74,21.8 -resnet34,5261.07,194.625,1024,224,3.67,3.74,21.8 -tv_resnet34,5246.08,195.181,1024,224,3.67,3.74,21.8 -mnasnet_140,5193.79,197.147,1024,224,0.6,7.71,7.12 -ese_vovnet19b_dw,5184.9,197.482,1024,224,1.34,8.25,6.54 -hrnet_w18_small,5155.87,198.596,1024,224,1.61,5.72,13.19 -nf_regnet_b0,5101.72,200.704,1024,256,0.64,5.58,8.76 -visformer_tiny,5101.23,200.723,1024,224,1.27,5.72,10.32 -levit_384,5073.3,201.829,1024,224,2.36,6.26,39.13 -semnasnet_140,4966.63,206.164,1024,224,0.6,8.87,6.11 -seresnet34,4945.0,207.065,1024,224,3.67,3.74,21.96 -tf_efficientnet_b0_ap,4905.52,208.732,1024,224,0.4,6.75,5.29 -gernet_m,4904.45,208.778,1024,224,3.02,5.24,21.14 -tf_efficientnet_b0_ns,4901.28,208.912,1024,224,0.4,6.75,5.29 -tf_efficientnet_b0,4899.3,208.998,1024,224,0.4,6.75,5.29 -deit_tiny_patch16_224,4843.68,211.396,1024,224,1.26,5.97,5.72 -vit_tiny_patch16_224,4826.03,212.17,1024,224,1.26,5.97,5.72 -legacy_seresnet34,4801.6,213.249,1024,224,3.67,3.74,21.96 -selecsls42,4799.44,213.344,1024,224,2.94,4.62,30.35 -selecsls42b,4785.96,213.947,1024,224,2.98,4.62,32.46 -deit_tiny_distilled_patch16_224,4763.87,214.938,1024,224,1.27,6.01,5.91 -dla46x_c,4729.04,216.521,1024,224,0.54,5.66,1.07 -resnet34d,4728.13,216.564,1024,224,3.91,4.54,21.82 -rexnetr_130,4595.96,222.792,1024,224,0.68,9.81,7.61 -mixnet_s,4558.15,224.639,1024,224,0.25,6.25,4.13 -pit_ti_distilled_224,4547.26,225.178,1024,224,0.71,6.23,5.1 -pit_ti_224,4535.39,225.767,1024,224,0.7,6.19,4.85 -tf_efficientnetv2_b1,4510.37,227.021,1024,240,1.21,7.34,8.14 -xcit_nano_12_p16_224_dist,4493.11,227.892,1024,224,0.56,4.17,3.05 -xcit_nano_12_p16_224,4491.7,227.964,1024,224,0.56,4.17,3.05 -dla60x_c,4470.1,229.064,1024,224,0.59,6.01,1.32 -resmlp_12_distilled_224,4434.35,230.91,1024,224,3.01,5.5,15.35 -resmlp_12_224,4433.54,230.952,1024,224,3.01,5.5,15.35 -rexnet_130,4425.14,231.393,1024,224,0.68,9.71,7.56 -vit_base_patch32_224_sam,4321.54,236.941,1024,224,4.41,5.01,88.22 -vit_base_patch32_224,4307.66,237.703,1024,224,4.41,5.01,88.22 -resnet26,4298.32,238.219,1024,224,2.36,7.35,16.0 -mobilenetv2_120d,4284.71,238.978,1024,224,0.69,11.97,5.83 -tf_mixnet_s,4275.28,239.504,1024,224,0.25,6.25,4.13 -repvgg_b0,4225.0,242.355,1024,224,3.41,6.15,15.82 -mixer_b32_224,4147.03,246.913,1024,224,3.24,6.29,60.29 -selecsls60,4126.77,248.123,1024,224,3.59,5.52,30.67 -selecsls60b,4115.88,248.778,1024,224,3.63,5.52,32.77 -efficientnet_b0_g16_evos,3990.44,256.6,1024,224,1.01,7.42,8.11 -rexnetr_150,3952.56,259.06,1024,224,0.89,11.13,9.78 -efficientnet_lite1,3940.91,259.824,1024,240,0.62,10.14,5.42 -resnet26d,3924.1,260.939,1024,224,2.6,8.15,16.01 -dla34,3875.11,264.237,1024,224,3.07,5.02,15.74 -ecaresnet50d_pruned,3865.04,264.927,1024,224,2.53,6.43,19.94 -rexnet_150,3831.29,267.26,1024,224,0.9,11.21,9.73 -nf_resnet26,3793.55,269.919,1024,224,2.41,7.35,16.0 -mobilevit_xxs,3770.57,271.565,1024,256,0.42,8.34,1.27 -pit_xs_224,3681.14,278.161,1024,224,1.4,7.71,10.62 -tf_efficientnet_lite1,3664.91,279.395,1024,240,0.62,10.14,5.42 -pit_xs_distilled_224,3647.86,280.699,1024,224,1.41,7.76,11.0 -regnetx_016,3647.8,280.704,1024,224,1.62,7.93,9.19 -fbnetv3_d,3569.84,286.833,1024,256,0.68,11.1,10.31 -fbnetv3_b,3536.82,289.512,1024,256,0.55,9.1,8.6 -efficientnet_b2_pruned,3476.28,294.556,1024,260,0.73,9.13,8.31 -efficientnet_es_pruned,3448.68,296.913,1024,224,1.81,8.73,5.44 -efficientnet_es,3446.7,297.082,1024,224,1.81,8.73,5.44 -tf_efficientnetv2_b2,3438.51,297.791,1024,260,1.72,9.84,10.1 -efficientnet_cc_b0_4e,3425.03,298.962,1024,224,0.41,9.42,13.31 -efficientnet_cc_b0_8e,3412.18,300.089,1024,224,0.42,9.42,24.01 -poolformer_s12,3407.92,300.463,1024,224,1.82,5.53,11.92 -mixer_s16_224,3404.99,300.723,1024,224,3.79,5.97,18.53 -regnety_016,3352.08,305.469,1024,224,1.63,8.04,11.2 -tf_efficientnet_es,3332.57,307.258,1024,224,1.81,8.73,5.44 -nf_seresnet26,3311.28,309.234,1024,224,2.41,7.36,17.4 -repvgg_a2,3302.08,310.095,1024,224,5.7,6.26,28.21 -nf_ecaresnet26,3298.62,310.42,1024,224,2.41,7.36,16.0 -gernet_l,3272.91,312.859,1024,256,4.57,8.0,31.08 -vit_small_patch32_384,3271.28,313.014,1024,384,3.45,8.25,22.92 -tf_efficientnet_cc_b0_4e,3244.05,315.642,1024,224,0.41,9.42,13.31 -tf_efficientnet_cc_b0_8e,3240.14,316.023,1024,224,0.42,9.42,24.01 -mixnet_m,3205.49,319.438,1024,224,0.36,8.19,5.01 -resnest14d,3201.02,319.884,1024,224,2.76,7.33,10.61 -skresnet34,3189.73,321.016,1024,224,3.67,5.13,22.28 -xcit_tiny_12_p16_224_dist,3156.96,324.349,1024,224,1.24,6.29,6.72 -xcit_tiny_12_p16_224,3156.35,324.412,1024,224,1.24,6.29,6.72 -resnext26ts,3110.32,329.214,1024,256,2.43,10.52,10.3 -gmixer_12_224,3103.83,329.902,1024,224,2.67,7.26,12.7 -legacy_seresnext26_32x4d,3102.65,330.028,1024,224,2.49,9.39,16.79 -tf_mixnet_m,3073.07,333.204,1024,224,0.36,8.19,5.01 -resnet26t,3052.48,335.451,1024,256,3.35,10.52,16.01 -vit_tiny_r_s16_p8_384,3050.47,167.831,512,384,1.34,6.49,6.36 -tf_efficientnet_b1_ns,3049.35,335.796,1024,240,0.71,10.88,7.79 -tf_efficientnet_b1_ap,3043.26,336.469,1024,240,0.71,10.88,7.79 -tf_efficientnet_b1,3043.05,336.492,1024,240,0.71,10.88,7.79 -seresnext26ts,3036.78,337.182,1024,256,2.43,10.52,10.39 -eca_resnext26ts,3034.01,337.495,1024,256,2.43,10.52,10.3 -efficientnet_lite2,3032.0,337.716,1024,260,0.89,12.9,6.09 -nf_regnet_b1,3025.41,338.455,1024,288,1.02,9.2,10.22 -gcresnext26ts,2985.04,343.027,1024,256,2.43,10.53,10.48 -ecaresnet101d_pruned,2955.16,346.499,1024,224,3.48,7.69,24.88 -efficientnet_b1,2953.49,346.695,1024,256,0.77,12.22,7.79 -nf_regnet_b2,2921.49,350.493,1024,272,1.22,9.27,14.31 -seresnext26t_32x4d,2908.45,352.064,1024,224,2.7,10.09,16.81 -seresnext26tn_32x4d,2907.22,352.213,1024,224,2.7,10.09,16.81 -ecaresnext50t_32x4d,2903.25,352.694,1024,224,2.7,10.09,15.41 -ecaresnext26t_32x4d,2897.07,353.448,1024,224,2.7,10.09,15.41 -seresnext26d_32x4d,2889.43,354.382,1024,224,2.73,10.19,16.81 -ecaresnetlight,2885.43,354.874,1024,224,4.11,8.42,30.16 -convnext_nano_hnf,2883.27,355.139,1024,224,2.45,8.37,15.59 -crossvit_tiny_240,2879.48,355.606,1024,240,1.57,9.08,7.01 -tf_efficientnet_lite2,2824.56,362.522,1024,260,0.89,12.9,6.09 -crossvit_9_240,2817.15,363.474,1024,240,1.85,9.52,8.55 -rexnetr_200,2812.94,182.004,512,224,1.59,15.11,16.52 -resnetv2_50,2787.72,367.312,1024,224,4.11,11.11,25.55 -tresnet_m,2773.53,369.19,1024,224,5.74,7.31,31.39 -rexnet_200,2765.2,185.146,512,224,1.56,14.91,16.37 -eca_botnext26ts_256,2754.13,371.793,1024,256,2.46,11.6,10.59 -efficientnet_b3_pruned,2735.66,374.303,1024,300,1.04,11.86,9.86 -botnet26t_256,2735.31,374.35,1024,256,3.32,11.98,12.49 -crossvit_9_dagger_240,2731.57,374.862,1024,240,1.99,9.97,8.78 -eca_halonext26ts,2696.48,379.742,1024,256,2.44,11.46,10.76 -resnet50,2695.53,379.874,1024,224,4.11,11.11,25.56 -tv_resnet50,2695.5,379.879,1024,224,4.11,11.11,25.56 -halonet26t,2694.88,379.966,1024,256,3.19,11.69,12.48 -swsl_resnet50,2694.7,379.993,1024,224,4.11,11.11,25.56 -gluon_resnet50_v1b,2693.21,380.199,1024,224,4.11,11.11,25.56 -ssl_resnet50,2691.71,380.414,1024,224,4.11,11.11,25.56 -convit_tiny,2683.21,381.617,1024,224,1.26,7.94,5.71 -hrnet_w18_small_v2,2645.65,387.038,1024,224,2.62,9.65,15.6 -resnetv2_50d,2626.53,389.852,1024,224,4.35,11.92,25.57 -resnetv2_50t,2624.52,390.152,1024,224,4.32,11.82,25.57 -vovnet39a,2619.13,390.954,1024,224,7.09,6.73,22.6 -vit_small_resnet26d_224,2608.49,392.55,1024,224,5.07,11.12,63.61 -vit_base2_patch32_256,2600.96,393.689,1024,256,7.79,7.76,119.46 -resnet32ts,2596.05,394.433,1024,256,4.63,11.58,17.96 -bat_resnext26ts,2595.92,394.45,1024,256,2.53,12.51,10.73 -cspresnet50,2575.36,397.599,1024,256,4.54,11.5,21.62 -resnet33ts,2567.21,398.865,1024,256,4.76,11.66,19.68 -dpn68b,2553.11,401.065,1024,224,2.35,10.47,12.61 -gluon_resnet50_v1c,2551.88,401.26,1024,224,4.35,11.92,25.58 -ese_vovnet39b,2548.89,401.728,1024,224,7.09,6.74,24.57 -eca_vovnet39b,2541.8,402.85,1024,224,7.09,6.74,22.6 -cspresnext50,2540.21,403.103,1024,224,3.1,12.14,20.57 -gmlp_ti16_224,2538.75,403.335,1024,224,1.34,7.55,5.87 -resnet50t,2537.39,403.552,1024,224,4.32,11.82,25.57 -legacy_seresnet50,2533.72,404.136,1024,224,3.88,10.6,28.09 -gluon_resnet50_v1d,2530.95,404.578,1024,224,4.35,11.92,25.58 -resnet50d,2529.63,404.786,1024,224,4.35,11.92,25.58 -dpn68,2517.34,406.764,1024,224,2.35,10.47,12.61 -vgg11_bn,2508.2,204.119,512,224,7.62,7.44,132.87 -selecsls84,2496.95,410.085,1024,224,5.9,7.57,50.95 -seresnet33ts,2496.28,410.197,1024,256,4.76,11.66,19.78 -eca_resnet33ts,2490.37,411.17,1024,256,4.76,11.66,19.68 -efficientnet_b0_gn,2478.81,413.089,1024,224,0.42,6.75,5.29 -gcresnet33ts,2444.46,418.89,1024,256,4.76,11.68,19.88 -deit_small_patch16_224,2440.46,419.58,1024,224,4.61,11.95,22.05 -vit_small_patch16_224,2439.92,419.672,1024,224,4.61,11.95,22.05 -pit_s_224,2435.64,420.407,1024,224,2.88,11.56,23.46 -mixnet_l,2434.72,210.28,512,224,0.58,10.84,7.33 -lambda_resnet26t,2428.26,421.688,1024,256,3.02,11.87,10.96 -cspresnet50w,2424.86,422.28,1024,256,5.04,12.19,28.12 -pit_s_distilled_224,2412.77,424.396,1024,224,2.9,11.64,24.04 -cspresnet50d,2411.73,424.578,1024,256,4.86,12.55,21.64 -seresnet50,2411.59,424.604,1024,224,4.11,11.13,28.09 -deit_small_distilled_patch16_224,2408.06,425.226,1024,224,4.63,12.02,22.44 -mobilevit_xs,2390.72,214.149,512,256,1.05,16.33,2.32 -dla60,2381.05,430.049,1024,224,4.26,10.16,22.04 -tf_efficientnet_b2,2362.66,433.397,1024,260,1.02,13.83,9.11 -tf_efficientnet_b2_ns,2360.61,433.773,1024,260,1.02,13.83,9.11 -tf_efficientnet_b2_ap,2357.47,434.351,1024,260,1.02,13.83,9.11 -densenet121,2354.51,434.897,1024,224,2.87,6.9,7.98 -tv_densenet121,2349.07,435.903,1024,224,2.87,6.9,7.98 -tf_mixnet_l,2339.37,218.851,512,224,0.58,10.84,7.33 -resnest26d,2327.85,439.878,1024,224,3.64,9.97,17.07 -resnetaa50d,2303.21,444.583,1024,224,5.39,12.44,25.58 -seresnet50t,2290.22,447.107,1024,224,4.32,11.83,28.1 -res2net50_48w_2s,2276.16,449.868,1024,224,4.18,11.72,25.29 -resnetblur50,2275.68,449.961,1024,224,5.16,12.02,25.56 -ecaresnet50d,2271.69,450.753,1024,224,4.35,11.93,25.58 -haloregnetz_b,2267.5,451.584,1024,224,1.97,11.94,11.68 -resmlp_24_224,2261.81,452.72,1024,224,5.96,10.91,30.02 -resmlp_24_distilled_224,2260.86,452.909,1024,224,5.96,10.91,30.02 -densenet121d,2250.37,455.023,1024,224,3.11,7.7,8.0 -resnetrs50,2250.35,455.026,1024,224,4.48,12.14,35.69 -efficientnet_b0_g8_gn,2225.86,460.033,1024,224,0.66,6.75,6.56 -regnetx_032,2206.94,463.978,1024,224,3.2,11.37,15.3 -efficientnet_b2,2203.49,464.703,1024,288,1.12,16.2,9.11 -efficientnet_b2a,2199.86,465.471,1024,288,1.12,16.2,9.11 -gluon_resnet50_v1s,2199.02,465.65,1024,224,5.47,13.52,25.68 -visformer_small,2180.09,469.693,1024,224,4.88,11.43,40.22 -adv_inception_v3,2153.56,475.475,1024,299,5.73,8.97,23.83 -tf_inception_v3,2151.76,475.872,1024,299,5.73,8.97,23.83 -inception_v3,2150.38,476.182,1024,299,5.73,8.97,23.83 -resnetblur50d,2147.4,476.842,1024,224,5.4,12.82,25.58 -gluon_inception_v3,2143.59,477.682,1024,299,5.73,8.97,23.83 -vovnet57a,2143.19,477.778,1024,224,8.95,7.52,36.64 -efficientnet_cc_b1_8e,2141.85,478.078,1024,240,0.75,15.44,39.72 -densenetblur121d,2137.06,479.149,1024,224,3.11,7.9,8.0 -cspresnext50_iabn,2134.77,479.664,1024,256,4.02,15.86,20.57 -efficientnet_em,2126.8,481.463,1024,240,3.04,14.34,6.9 -vit_base_resnet26d_224,2112.13,484.804,1024,224,6.97,13.16,101.4 -cspdarknet53_iabn,2094.24,488.947,1024,256,6.53,16.81,27.64 -seresnetaa50d,2085.24,491.057,1024,224,5.4,12.46,28.11 -ese_vovnet57b,2083.49,491.467,1024,224,8.95,7.52,38.61 -ssl_resnext50_32x4d,2081.05,492.045,1024,224,4.26,14.4,25.03 -swsl_resnext50_32x4d,2080.34,492.214,1024,224,4.26,14.4,25.03 -gluon_resnext50_32x4d,2080.29,492.225,1024,224,4.26,14.4,25.03 -tv_resnext50_32x4d,2079.74,492.355,1024,224,4.26,14.4,25.03 -resnext50_32x4d,2076.82,493.048,1024,224,4.26,14.4,25.03 -tf_efficientnet_em,2070.88,494.462,1024,240,3.04,14.34,6.9 -tf_efficientnet_cc_b1_8e,2062.84,496.39,1024,240,0.75,15.44,39.72 -res2net50_26w_4s,2042.43,501.35,1024,224,4.28,12.61,25.7 -tf_efficientnetv2_b3,2017.91,507.444,1024,300,3.04,15.74,14.36 -skresnet50,2017.85,507.457,1024,224,4.11,12.5,25.8 -nf_seresnet50,2013.68,508.507,1024,224,4.21,11.13,28.09 -regnetx_040,2006.2,510.404,1024,224,3.99,12.2,22.12 -nf_ecaresnet50,2003.47,511.102,1024,224,4.21,11.13,25.56 -efficientnetv2_rw_t,2000.48,511.861,1024,288,3.19,16.42,13.65 -gcresnet50t,1986.86,515.369,1024,256,5.42,14.67,25.9 -dla60x,1985.6,515.699,1024,224,3.54,13.8,17.35 -resnext50d_32x4d,1981.96,516.647,1024,224,4.5,15.2,25.05 -gc_efficientnetv2_rw_t,1932.03,529.997,1024,288,3.2,16.45,13.68 -convnext_tiny_hnf,1928.02,531.1,1024,224,4.47,13.44,28.59 -res2net50_14w_8s,1927.65,531.204,1024,224,4.21,13.28,25.06 -sehalonet33ts,1927.17,265.662,512,256,3.55,14.7,13.69 -skresnet50d,1925.97,531.666,1024,224,4.36,13.31,25.82 -densenet169,1921.61,532.872,1024,224,3.4,7.3,14.15 -gcresnext50ts,1919.22,533.536,1024,256,3.75,15.46,15.67 -dla60_res2net,1910.95,535.844,1024,224,4.15,12.34,20.85 -seresnext50_32x4d,1907.77,536.737,1024,224,4.26,14.42,27.56 -res2next50,1905.88,537.271,1024,224,4.2,13.71,24.67 -gluon_seresnext50_32x4d,1905.67,537.33,1024,224,4.26,14.42,27.56 -legacy_seresnext50_32x4d,1903.73,537.877,1024,224,4.26,14.42,27.56 -lambda_resnet26rpt_256,1903.17,269.013,512,256,3.16,11.87,10.99 -mobilevit_s,1899.79,269.492,512,256,2.03,19.94,5.58 -repvgg_b1g4,1890.54,541.63,1024,224,8.15,10.64,39.97 -resnest50d_1s4x24d,1888.24,542.29,1024,224,4.43,13.57,25.68 -darknet53,1853.82,276.175,512,256,9.31,12.39,41.61 -coat_lite_tiny,1848.83,553.849,1024,224,1.6,11.65,5.72 -nf_regnet_b3,1839.82,556.565,1024,320,2.05,14.61,18.59 -dla60_res2next,1833.06,558.612,1024,224,3.49,13.17,17.03 -cspdarknet53,1812.82,282.421,512,256,6.57,16.81,27.64 -semobilevit_s,1803.13,283.938,512,256,2.03,19.95,5.74 -efficientnet_lite3,1799.71,284.476,512,300,1.65,21.85,8.2 -regnetz_b16,1794.65,570.57,1024,288,2.39,16.43,9.72 -ecaresnet26t,1785.57,573.473,1024,320,5.24,16.44,16.01 -coat_lite_mini,1766.02,579.817,1024,224,2.0,12.25,11.01 -poolformer_s24,1765.88,579.868,1024,224,3.41,10.68,21.39 -mixnet_xl,1734.71,295.138,512,224,0.93,14.57,11.9 -vit_small_r26_s32_224,1732.3,591.11,1024,224,3.56,9.85,36.43 -resnetv2_101,1697.95,603.065,1024,224,7.83,16.23,44.54 -xcit_tiny_24_p16_224_dist,1687.36,606.851,1024,224,2.34,11.82,12.12 -xcit_tiny_24_p16_224,1682.06,608.762,1024,224,2.34,11.82,12.12 -tf_efficientnet_lite3,1679.33,304.873,512,300,1.65,21.85,8.2 -repvgg_b1,1666.24,614.545,1024,224,13.16,10.64,57.42 -sebotnet33ts_256,1660.84,231.195,384,256,3.89,17.46,13.7 -tv_resnet101,1659.62,616.997,1024,224,7.83,16.23,44.55 -gluon_resnet101_v1b,1659.37,617.087,1024,224,7.83,16.23,44.55 -convnext_tiny,1658.71,617.331,1024,224,4.47,13.44,28.59 -resnet101,1655.84,618.405,1024,224,7.83,16.23,44.55 -xcit_small_12_p16_224_dist,1652.32,619.718,1024,224,4.82,12.58,26.25 -xcit_small_12_p16_224,1648.97,620.98,1024,224,4.82,12.58,26.25 -resnetv2_101d,1631.54,627.614,1024,224,8.07,17.04,44.56 -vit_base_resnet50d_224,1631.31,627.703,1024,224,8.73,16.92,110.97 -lambda_resnet50ts,1601.2,639.507,1024,256,5.07,17.48,21.54 -gluon_resnet101_v1c,1600.5,639.785,1024,224,8.08,17.04,44.57 -gluon_resnet101_v1d,1596.44,641.412,1024,224,8.08,17.04,44.57 -dla102,1582.26,647.16,1024,224,7.19,14.18,33.27 -gmixer_24_224,1582.16,647.204,1024,224,5.28,14.45,24.72 -wide_resnet50_2,1579.37,648.345,1024,224,11.43,14.4,68.88 -twins_svt_small,1577.35,649.176,1024,224,2.94,13.75,24.06 -resnest50d,1570.05,652.193,1024,224,5.4,14.36,27.48 -res2net50_26w_6s,1562.92,655.169,1024,224,6.33,15.28,37.05 -regnetx_080,1553.61,659.095,1024,224,8.02,14.06,39.57 -crossvit_small_240,1546.63,662.07,1024,240,5.63,18.17,26.86 -xcit_nano_12_p16_384_dist,1543.06,663.599,1024,384,1.64,12.15,3.05 -resnetv2_50x1_bit_distilled,1541.41,664.315,1024,224,4.23,11.11,25.55 -legacy_seresnet101,1534.0,667.522,1024,224,7.61,15.74,49.33 -resmlp_36_224,1516.69,675.14,1024,224,8.91,16.33,44.69 -resmlp_36_distilled_224,1515.97,675.455,1024,224,8.91,16.33,44.69 -halonet50ts,1506.38,679.762,1024,256,5.3,19.2,22.73 -resnetaa101d,1500.11,682.602,1024,224,9.12,17.56,44.57 -vgg13_bn,1493.45,342.818,512,224,11.33,12.25,133.05 -densenet201,1492.3,686.177,1024,224,4.34,7.85,20.01 -seresnet101,1488.58,687.891,1024,224,7.84,16.27,49.33 -vit_large_patch32_224,1480.53,691.629,1024,224,15.39,13.3,306.54 -fbnetv3_g,1476.24,693.641,1024,288,1.77,21.09,16.62 -ese_vovnet39b_evos,1470.17,696.502,1024,224,7.07,6.74,24.58 -convnext_tiny_hnfd,1463.28,699.785,1024,224,4.78,14.64,28.63 -gluon_resnet101_v1s,1458.5,702.078,1024,224,9.19,18.64,44.67 -regnetx_064,1451.61,352.7,512,224,6.49,16.37,26.21 -nf_resnet101,1444.19,709.036,1024,224,8.01,16.23,44.55 -lamhalobotnet50ts_256,1432.71,714.715,1024,256,5.02,18.44,22.57 -resnetblur101d,1431.35,715.392,1024,224,9.12,17.94,44.57 -ecaresnet101d,1429.1,716.517,1024,224,8.08,17.07,44.57 -nf_resnet50,1421.81,720.193,1024,288,6.88,18.37,25.56 -hrnet_w18,1420.84,720.684,1024,224,4.32,16.31,21.3 -vit_base_r26_s32_224,1419.32,721.457,1024,224,6.81,12.36,101.38 -crossvit_15_240,1416.83,722.727,1024,240,5.81,19.77,27.53 -tresnet_l,1403.47,729.603,1024,224,10.88,11.9,55.99 -gmlp_s16_224,1393.69,734.725,1024,224,4.42,15.1,19.42 -resnetv2_50d_frn,1389.08,737.162,1024,224,4.33,11.92,25.59 -regnety_032,1387.11,738.212,1024,288,5.29,18.61,19.44 -tf_efficientnet_b3_ap,1384.27,369.858,512,300,1.87,23.83,12.23 -tf_efficientnet_b3,1382.58,370.309,512,300,1.87,23.83,12.23 -tf_efficientnet_b3_ns,1381.54,370.587,512,300,1.87,23.83,12.23 -mixer_l32_224,1377.05,743.605,1024,224,11.27,19.86,206.94 -vit_base_patch32_384,1375.53,744.425,1024,384,13.06,16.5,88.3 -crossvit_15_dagger_240,1372.46,746.094,1024,240,6.13,20.43,28.21 -resnet51q,1370.65,747.074,1024,288,8.07,20.94,35.7 -resnet50_gn,1358.57,753.722,1024,224,4.14,11.11,25.56 -cait_xxs24_224,1351.39,757.722,1024,224,2.53,20.29,11.96 -efficientnet_b3,1344.22,380.877,512,320,2.01,26.52,12.23 -efficientnet_b3a,1343.43,381.1,512,320,2.01,26.52,12.23 -xception,1343.1,381.193,512,299,8.4,35.83,22.86 -dla102x,1336.12,766.382,1024,224,5.89,19.42,26.31 -mixer_b16_224,1331.47,769.062,1024,224,12.62,14.53,59.88 -mixer_b16_224_miil,1329.31,770.309,1024,224,12.62,14.53,59.88 -skresnext50_32x4d,1318.82,776.433,1024,224,4.5,17.18,27.48 -botnet50ts_256,1318.29,388.369,512,256,5.54,22.23,22.74 -swsl_resnext101_32x4d,1313.68,779.478,1024,224,8.01,21.23,44.18 -gluon_resnext101_32x4d,1313.37,779.659,1024,224,8.01,21.23,44.18 -resnext101_32x4d,1312.5,780.172,1024,224,8.01,21.23,44.18 -ssl_resnext101_32x4d,1311.93,780.515,1024,224,8.01,21.23,44.18 -resnetv2_50d_evob,1302.41,786.222,1024,224,4.33,11.92,25.59 -repvgg_b2g4,1294.35,791.118,1024,224,12.63,12.9,61.76 -swin_tiny_patch4_window7_224,1284.93,796.915,1024,224,4.51,17.06,28.29 -res2net50_26w_8s,1282.33,798.529,1024,224,8.37,17.95,48.4 -res2net101_26w_4s,1280.42,799.726,1024,224,8.1,18.45,45.21 -halo2botnet50ts_256,1278.73,400.387,512,256,5.02,21.78,22.64 -twins_pcpvt_small,1266.87,808.275,1024,224,3.83,18.08,24.11 -resnest50d_4s2x40d,1247.1,821.089,1024,224,4.4,17.94,30.42 -nf_seresnet101,1245.83,821.925,1024,224,8.02,16.27,49.33 -resnet61q,1239.28,826.269,1024,288,9.87,21.52,36.85 -vgg16_bn,1239.15,413.174,512,224,15.5,13.56,138.37 -nf_ecaresnet101,1239.13,826.374,1024,224,8.01,16.27,44.55 -eca_nfnet_l0,1229.58,832.793,1024,288,7.12,17.29,24.14 -hrnet_w32,1229.04,833.146,1024,224,8.97,22.02,41.23 -xception41p,1223.32,418.518,512,299,9.25,39.86,26.91 -nfnet_l0,1223.17,837.152,1024,288,7.13,17.29,35.07 -ese_vovnet99b_iabn,1219.1,839.947,1024,224,16.49,11.27,63.2 -convit_small,1215.88,842.173,1024,224,5.76,17.87,27.78 -hrnet_w30,1211.94,844.908,1024,224,8.15,21.21,37.71 -regnety_040,1211.74,422.521,512,288,6.61,20.3,20.65 -regnetv_040,1210.32,423.017,512,288,6.6,20.3,20.64 -vit_tiny_patch16_384,1209.55,846.58,1024,384,4.7,25.39,5.79 -dpn92,1207.37,848.107,1024,224,6.54,18.21,37.67 -seresnext101_32x4d,1202.94,851.233,1024,224,8.02,21.26,48.96 -gluon_seresnext101_32x4d,1201.66,852.139,1024,224,8.02,21.26,48.96 -legacy_seresnext101_32x4d,1201.03,852.591,1024,224,8.02,21.26,48.96 -swin_s3_tiny_224,1197.86,854.845,1024,224,4.64,19.13,28.33 -poolformer_s36,1192.85,858.435,1024,224,5.0,15.82,30.86 -ese_vovnet99b,1182.33,866.068,1024,224,16.51,11.27,63.2 -resnetv2_152,1176.91,870.059,1024,224,11.55,22.56,60.19 -xcit_nano_12_p8_224_dist,1168.85,876.058,1024,224,2.16,15.71,3.05 -xcit_nano_12_p8_224,1164.34,879.454,1024,224,2.16,15.71,3.05 -gluon_resnet152_v1b,1158.23,884.096,1024,224,11.56,22.56,60.19 -tv_resnet152,1157.57,884.6,1024,224,11.56,22.56,60.19 -resnet152,1156.18,885.659,1024,224,11.56,22.56,60.19 -resnetv2_152d,1145.88,893.624,1024,224,11.8,23.36,60.2 -regnetz_c16,1139.93,449.135,512,320,3.92,25.88,13.46 -ecaresnet50t,1137.76,900.002,1024,320,8.82,24.13,25.57 -repvgg_b2,1135.04,902.153,1024,224,20.45,12.9,89.02 -gluon_resnet152_v1c,1127.87,907.895,1024,224,11.8,23.36,60.21 -gluon_resnet152_v1d,1126.2,909.24,1024,224,11.8,23.36,60.21 -inception_v4,1102.19,929.046,1024,299,12.28,15.09,42.68 -regnety_040s_gn,1097.43,933.073,1024,224,4.03,12.29,20.65 -swin_v2_cr_tiny_224,1095.67,934.572,1024,224,4.66,30.64,28.33 -convnext_small,1094.72,935.388,1024,224,8.7,21.56,50.22 -xception41,1088.12,470.521,512,299,9.28,39.86,26.97 -convmixer_1024_20_ks9_p14,1086.94,942.076,1024,224,5.55,5.51,24.38 -vit_small_resnet50d_s16_224,1086.45,942.502,1024,224,13.48,24.82,57.53 -xcit_tiny_12_p16_384_dist,1082.39,946.043,1024,384,3.64,18.26,6.72 -densenet161,1080.13,948.016,1024,224,7.79,11.06,28.68 -mixnet_xxl,1077.24,356.453,384,224,2.04,23.43,23.96 -dla169,1074.25,953.209,1024,224,11.6,20.2,53.39 -nfnet_f0,1065.5,961.034,1024,256,12.62,18.05,71.49 -legacy_seresnet152,1057.8,968.029,1024,224,11.33,22.08,66.82 -gluon_resnet152_v1s,1056.41,969.306,1024,224,12.92,24.96,60.32 -vgg19_bn,1055.4,485.111,512,224,19.66,14.86,143.68 -regnetx_120,1050.75,487.26,512,224,12.13,21.37,46.11 -nest_tiny,1050.35,487.443,512,224,5.83,25.48,17.06 -coat_lite_small,1048.4,976.705,1024,224,3.96,22.09,19.84 -vit_base_patch16_224_miil,1045.49,979.427,1024,224,17.58,23.9,86.54 -crossvit_18_240,1039.49,985.088,1024,240,9.05,26.26,43.27 -swin_v2_cr_tiny_ns_224,1039.03,985.521,1024,224,4.66,30.64,28.33 -tresnet_xl,1037.95,986.545,1024,224,15.17,15.34,78.44 -jx_nest_tiny,1035.86,494.265,512,224,5.83,25.48,17.06 -seresnet152,1034.7,989.644,1024,224,11.57,22.61,66.82 -deit_base_patch16_224,1019.44,1004.455,1024,224,17.58,23.9,86.57 -vit_base_patch16_224_sam,1015.42,1008.432,1024,224,17.58,23.9,86.57 -vit_base_patch16_224,1014.98,1008.871,1024,224,17.58,23.9,86.57 -crossvit_18_dagger_240,1009.97,1013.877,1024,240,9.5,27.03,44.27 -deit_base_distilled_patch16_224,1007.07,1016.791,1024,224,17.68,24.05,87.34 -regnety_120,1005.22,509.326,512,224,12.14,21.38,51.82 -repvgg_b3g4,1002.6,1021.328,1024,224,17.89,15.1,83.83 -volo_d1_224,967.03,1058.901,1024,224,6.94,24.43,26.63 -efficientnet_el_pruned,948.42,539.83,512,300,8.0,30.7,10.59 -efficientnet_el,942.13,543.435,512,300,8.0,30.7,10.59 -dm_nfnet_f0,931.91,1098.8,1024,256,12.62,18.05,71.49 -twins_pcpvt_base,930.89,1100.003,1024,224,6.68,25.25,43.83 -beit_base_patch16_224,930.84,1100.061,1024,224,17.58,23.9,86.53 -tf_efficientnet_el,925.74,553.06,512,300,8.0,30.7,10.59 -wide_resnet101_2,916.19,1117.657,1024,224,22.8,21.23,126.89 -twins_svt_base,914.55,1119.66,1024,224,8.59,26.33,56.07 -dla102x2,911.45,561.725,512,224,9.34,29.91,41.28 -cait_xxs36_224,908.72,1126.845,1024,224,3.77,30.34,17.3 -efficientnetv2_s,907.0,1128.974,1024,384,8.44,35.77,21.46 -resnetv2_50d_gn,896.28,1142.488,1024,288,7.24,19.7,25.57 -xception65p,889.27,575.737,512,299,13.91,52.48,39.82 -repvgg_b3,888.16,1152.929,1024,224,29.16,15.1,123.09 -tf_efficientnetv2_s_in21ft1k,886.83,1154.656,1024,384,8.44,35.77,21.46 -tf_efficientnetv2_s,886.38,1155.25,1024,384,8.44,35.77,21.46 -xcit_small_24_p16_224_dist,880.14,1163.431,1024,224,9.1,23.64,47.67 -xcit_small_24_p16_224,879.96,1163.673,1024,224,9.1,23.64,47.67 -resnetrs101,879.92,1163.729,1024,288,13.56,28.53,63.62 -efficientnetv2_rw_s,866.42,1181.861,1024,384,8.72,38.03,23.94 -dpn98,864.11,1185.015,1024,224,11.73,25.2,61.57 -pit_b_224,862.79,593.411,512,224,12.42,32.94,73.76 -ens_adv_inception_resnet_v2,856.99,1194.864,1024,299,13.18,25.06,55.84 -inception_resnet_v2,856.96,1194.905,1024,299,13.18,25.06,55.84 -pit_b_distilled_224,854.69,599.032,512,224,12.5,33.07,74.79 -nf_regnet_b4,850.27,1204.313,1024,384,4.7,28.61,30.21 -regnetx_160,849.7,602.551,512,224,15.99,25.52,54.28 -regnetz_d8,849.19,1205.844,1024,320,6.19,37.08,23.37 -swin_small_patch4_window7_224,843.01,1214.681,1024,224,8.77,27.47,49.61 -gluon_resnext101_64x4d,836.35,1224.352,1024,224,15.52,31.21,83.46 -resnet200,830.77,1232.576,1024,224,15.07,32.19,64.67 -regnetz_040,828.17,463.661,384,320,6.35,37.78,27.12 -regnetz_040h,823.76,466.142,384,320,6.43,37.94,28.94 -efficientnet_lite4,822.06,467.103,384,380,4.04,45.66,13.01 -hrnet_w40,819.73,1249.18,1024,224,12.75,25.29,57.56 -convnext_base,817.5,1252.582,1024,224,15.38,28.75,88.59 -xcit_tiny_12_p8_224,817.02,1253.32,1024,224,4.81,23.6,6.71 -convnext_base_in22ft1k,816.83,1253.608,1024,224,15.38,28.75,88.59 -xcit_tiny_12_p8_224_dist,816.44,1254.214,1024,224,4.81,23.6,6.71 -convnext_small_in22ft1k,815.72,1255.315,1024,224,15.38,28.75,88.59 -convnext_tiny_in22ft1k,814.36,1257.407,1024,224,15.38,28.75,88.59 -regnetz_b16_evos,811.63,630.813,512,288,2.36,16.43,9.74 -swsl_resnext101_32x8d,805.58,1271.112,1024,224,16.48,31.21,88.79 -regnety_064,804.87,636.11,512,288,10.56,27.11,30.58 -ssl_resnext101_32x8d,804.25,1273.227,1024,224,16.48,31.21,88.79 -ig_resnext101_32x8d,804.24,1273.235,1024,224,16.48,31.21,88.79 -resnext101_32x8d,804.11,1273.443,1024,224,16.48,31.21,88.79 -regnetv_064,800.78,639.366,512,288,10.55,27.11,30.58 -gluon_xception65,800.14,639.877,512,299,13.96,52.48,39.92 -poolformer_m36,799.89,1280.164,1024,224,8.8,22.02,56.17 -resnet101d,798.53,1282.345,1024,320,16.48,34.77,44.57 -xception65,794.53,644.391,512,299,13.96,52.48,39.92 -gluon_seresnext101_64x4d,789.66,1296.749,1024,224,15.53,31.25,88.23 -vit_small_patch16_36x1_224,784.3,1305.61,1024,224,13.71,35.69,64.67 -resnest101e,783.74,653.265,512,256,13.38,28.66,48.28 -tf_efficientnet_lite4,778.05,493.528,384,380,4.04,45.66,13.01 -vit_small_patch16_18x2_224,770.15,1329.591,1024,224,13.71,35.69,64.67 -regnety_080,769.02,665.77,512,288,13.22,29.69,39.18 -resnetv2_50d_evos,763.22,670.828,512,288,7.15,19.7,25.59 -hrnet_w44,761.56,1344.592,1024,224,14.94,26.92,67.06 -cait_s24_224,750.62,1364.194,1024,224,9.35,40.58,46.92 -tresnet_m_448,731.85,1399.173,1024,448,22.94,29.21,31.39 -hrnet_w48,731.58,1399.696,1024,224,17.34,28.56,77.47 -coat_tiny,725.92,1410.611,1024,224,4.35,27.2,5.5 -regnetz_d32,725.1,1412.192,1024,320,9.33,37.08,27.58 -swin_v2_cr_small_224,711.79,1438.61,1024,224,9.08,53.85,49.7 -nest_small,704.65,726.593,512,224,10.35,40.04,38.35 -vit_large_r50_s32_224,704.05,1454.417,1024,224,19.58,24.41,328.99 -jx_nest_small,698.33,733.168,512,224,10.35,40.04,38.35 -twins_svt_large,697.37,1468.361,1024,224,15.15,35.1,99.27 -crossvit_base_240,692.97,738.833,512,240,21.22,36.33,105.03 -efficientnet_b4,680.87,563.972,384,384,4.51,50.04,19.34 -twins_pcpvt_large,679.24,1507.549,1024,224,9.84,35.82,60.99 -gmlp_b16_224,668.45,1531.889,1024,224,15.78,30.21,73.08 -swin_s3_small_224,655.58,780.974,512,224,9.43,37.84,49.74 -tf_efficientnet_b4,650.11,590.654,384,380,4.49,49.49,19.34 -tf_efficientnet_b4_ns,650.01,590.745,384,380,4.49,49.49,19.34 -tf_efficientnet_b4_ap,649.91,590.836,384,380,4.49,49.49,19.34 -densenet264d_iabn,648.39,1579.29,1024,224,13.47,14.0,72.74 -xcit_medium_24_p16_224,643.54,1591.196,1024,224,16.13,31.71,84.4 -xcit_medium_24_p16_224_dist,643.46,1591.39,1024,224,16.13,31.71,84.4 -convit_base,640.59,1598.504,1024,224,17.52,31.77,86.54 -swin_base_patch4_window7_224,637.77,1605.59,1024,224,15.47,36.63,87.77 -dpn131,636.07,1609.871,1024,224,16.09,32.97,79.25 -densenet264,630.43,1624.264,1024,224,12.95,12.8,72.69 -vit_small_patch16_384,609.69,839.76,512,384,15.52,50.78,22.2 -coat_mini,609.64,1679.655,1024,224,6.82,33.68,10.34 -poolformer_m48,602.84,1698.613,1024,224,11.59,29.17,73.47 -xception71,601.65,850.98,512,299,18.09,69.92,42.34 -hrnet_w64,601.51,1702.355,1024,224,28.97,35.09,128.06 -efficientnet_b3_gn,590.02,433.867,256,320,2.14,28.83,11.73 -vit_small_r26_s32_384,588.06,652.978,384,384,10.43,29.85,36.47 -senet154,584.6,1751.617,1024,224,20.77,38.69,115.09 -gluon_senet154,583.36,1755.334,1024,224,20.77,38.69,115.09 -legacy_senet154,583.3,1755.507,1024,224,20.77,38.69,115.09 -dpn107,579.63,1766.612,1024,224,18.38,33.46,86.92 -xcit_tiny_24_p16_384_dist,575.62,1778.929,1024,384,6.87,34.29,12.12 -eca_nfnet_l1,574.09,1783.68,1024,320,14.92,34.42,41.41 -vit_base_r50_s16_224,571.98,1790.263,1024,224,21.66,35.29,98.66 -seresnet200d,564.7,1813.347,1024,256,20.01,43.15,71.86 -resnet152d,563.14,1818.348,1024,320,24.08,47.67,60.21 -ecaresnet200d,561.62,1823.283,1024,256,20.0,43.15,64.69 -xcit_small_12_p16_384_dist,554.2,1847.68,1024,384,14.14,36.51,26.25 -volo_d2_224,554.02,1848.29,1024,224,14.34,41.34,58.68 -swin_v2_cr_base_224,537.55,1904.924,1024,224,15.86,64.42,87.88 -regnety_320,535.71,955.723,512,224,32.34,30.26,145.05 -swin_s3_base_224,533.55,1919.195,1024,224,13.69,48.26,71.13 -nest_base,529.87,966.265,512,224,17.96,53.39,67.72 -jx_nest_base,524.97,975.286,512,224,17.96,53.39,67.72 -regnety_160,524.88,731.579,384,288,26.37,38.07,83.59 -regnetz_c16_evos,513.17,997.712,512,320,3.86,25.88,13.49 -efficientnet_b3_g8_gn,512.15,499.838,256,320,3.2,28.83,14.25 -resnext101_64x4d,508.2,1007.467,512,288,25.66,51.59,83.46 -tnt_s_patch16_224,505.05,2027.493,1024,224,5.24,24.37,23.76 -seresnet152d,504.9,2028.105,1024,320,24.09,47.72,66.84 -resnetrs152,501.47,2041.965,1024,320,24.34,48.14,86.62 -convnext_large,487.74,1049.73,512,224,34.4,43.13,197.77 -convnext_large_in22ft1k,486.41,1052.606,512,224,34.4,43.13,197.77 -vit_large_patch32_384,473.23,2163.856,1024,384,45.31,43.86,306.63 -regnetx_320,469.34,818.147,384,224,31.81,36.3,107.81 -halonet_h1,463.9,551.835,256,256,3.0,51.17,8.1 -seresnext101_32x8d,462.9,1106.059,512,288,27.24,51.63,93.57 -regnetz_e8,453.82,1128.184,512,320,15.46,63.94,57.7 -mixer_l16_224,443.19,2310.528,1024,224,44.6,41.69,208.2 -seresnet269d,441.96,2316.951,1024,256,26.59,53.6,113.67 -efficientnetv2_m,441.46,2319.557,1024,416,18.6,67.5,54.14 -xcit_tiny_24_p8_224,429.28,2385.382,1024,224,9.21,45.39,12.11 -xcit_tiny_24_p8_224_dist,428.77,2388.186,1024,224,9.21,45.39,12.11 -xcit_small_12_p8_224,419.27,2442.349,1024,224,18.69,47.21,26.21 -xcit_small_12_p8_224_dist,419.19,2442.766,1024,224,18.69,47.21,26.21 -efficientnetv2_rw_m,406.5,1259.53,512,416,21.49,79.62,53.24 -resnet200d,405.44,2525.643,1024,320,31.25,67.33,64.69 -tnt_b_patch16_224,396.78,2580.753,1024,224,14.09,39.01,65.41 -swin_large_patch4_window7_224,395.25,1295.372,512,224,34.53,54.94,196.53 -resnetv2_50x1_bitm,393.49,975.875,384,448,16.62,44.46,25.55 -xcit_nano_12_p8_384_dist,392.55,2608.577,1024,384,6.34,46.08,3.05 -xcit_large_24_p16_224_dist,389.81,2626.888,1024,224,35.86,47.27,189.1 -xcit_large_24_p16_224,389.64,2628.072,1024,224,35.86,47.27,189.1 -volo_d3_224,388.78,2633.839,1024,224,20.78,60.09,86.33 -ig_resnext101_32x16d,374.93,1365.563,512,224,36.27,51.18,194.03 -swsl_resnext101_32x16d,374.73,1366.289,512,224,36.27,51.18,194.03 -ssl_resnext101_32x16d,374.63,1366.656,512,224,36.27,51.18,194.03 -tresnet_l_448,362.23,2826.92,1024,448,43.5,47.56,55.99 -resnetrs200,359.53,2848.13,1024,320,31.51,67.81,93.21 -regnetz_d8_evos,355.41,1440.558,512,320,7.03,38.92,23.46 -nfnet_f1,354.11,2891.708,1024,320,35.97,46.77,132.63 -tf_efficientnetv2_m,344.99,1484.089,512,480,24.76,89.84,54.14 -tf_efficientnetv2_m_in21ft1k,344.95,1484.253,512,480,24.76,89.84,54.14 -vit_large_patch16_224,341.74,2996.381,1024,224,61.6,63.52,304.33 -efficientnet_b5,336.97,759.686,256,456,10.46,98.86,30.39 -dm_nfnet_f1,336.55,1521.307,512,320,35.97,46.77,132.63 -swin_v2_cr_large_224,336.25,1522.658,512,224,35.1,85.57,196.68 -convnext_xlarge_in22ft1k,332.85,1538.204,512,224,60.97,57.5,350.2 -tf_efficientnet_b5_ap,325.28,786.993,256,456,10.46,98.86,30.39 -tf_efficientnet_b5_ns,325.25,787.076,256,456,10.46,98.86,30.39 -tf_efficientnet_b5,325.02,787.638,256,456,10.46,98.86,30.39 -vit_base_patch16_18x2_224,323.5,3165.374,1024,224,52.51,71.38,256.73 -crossvit_15_dagger_408,314.0,815.262,256,408,21.45,95.05,28.5 -beit_large_patch16_224,313.18,3269.663,1024,224,61.6,63.52,304.43 -xcit_small_24_p16_384_dist,294.97,3471.465,1024,384,26.72,68.58,47.67 -convmixer_768_32,290.4,3526.113,1024,224,19.55,25.95,21.11 -swin_v2_cr_tiny_384,285.22,897.553,256,384,15.36,179.92,28.33 -eca_nfnet_l2,282.5,1812.345,512,384,30.05,68.28,56.72 -convnext_small_384_in22ft1k,278.47,1378.958,384,384,45.2,84.49,88.59 -convnext_tiny_384_in22ft1k,277.61,1383.204,384,384,45.2,84.49,88.59 -resnetv2_152x2_bit_teacher,277.28,1846.482,512,224,46.95,45.11,236.34 -xcit_tiny_12_p8_384_dist,275.28,3719.775,1024,384,14.13,69.14,6.71 -convnext_base_384_in22ft1k,271.21,1415.851,384,384,45.2,84.49,88.59 -tresnet_xl_448,270.27,1894.405,512,448,60.65,61.31,78.44 -deit_base_patch16_384,266.0,1443.615,384,384,55.54,101.56,86.86 -vit_base_patch16_384,265.19,1448.027,384,384,55.54,101.56,86.86 -deit_base_distilled_patch16_384,262.93,1460.437,384,384,55.65,101.82,87.63 -resnest200e,262.48,1950.635,512,320,35.69,82.78,70.2 -volo_d1_384,260.38,1474.743,384,384,22.75,108.55,26.78 -volo_d4_224,257.94,3969.869,1024,224,44.34,80.22,192.96 -vit_large_patch14_224,251.28,4075.168,1024,224,81.08,88.79,304.2 -resnetv2_101x1_bitm,244.68,1569.394,384,448,31.65,64.93,44.54 -cait_xxs24_384,243.88,4198.837,1024,384,9.63,122.66,12.03 -crossvit_18_dagger_408,234.94,1089.639,256,408,32.47,124.87,44.61 -ecaresnet269d,234.24,4371.583,1024,352,50.25,101.25,102.09 -vit_large_r50_s32_384,234.0,1641.018,384,384,57.43,76.52,329.09 -pnasnet5large,228.91,1677.491,384,331,25.04,92.89,86.06 -resnetrs270,228.2,4487.36,1024,352,51.13,105.48,129.86 -nasnetalarge,228.07,1683.676,384,331,23.89,90.56,88.75 -beit_base_patch16_384,227.79,1685.763,384,384,55.54,101.56,86.74 -xcit_small_24_p8_224_dist,219.63,4662.341,1024,224,35.81,90.78,47.63 -xcit_small_24_p8_224,219.33,4668.653,1024,224,35.81,90.78,47.63 -xcit_medium_24_p16_384_dist,218.42,2344.05,512,384,47.39,91.64,84.4 -resmlp_big_24_224,205.71,4977.973,1024,224,100.23,87.31,129.14 -resmlp_big_24_224_in22ft1k,205.53,4982.262,1024,224,100.23,87.31,129.14 -resmlp_big_24_distilled_224,205.53,4982.296,1024,224,100.23,87.31,129.14 -nfnet_f2,199.27,5138.776,1024,352,63.22,79.06,193.78 -efficientnetv2_l,198.39,2580.786,512,480,56.4,157.99,118.52 -tf_efficientnetv2_l_in21ft1k,196.29,2608.374,512,480,56.4,157.99,118.52 -tf_efficientnetv2_l,196.05,2611.552,512,480,56.4,157.99,118.52 -efficientnet_b6,194.31,658.718,128,528,19.4,167.39,43.04 -dm_nfnet_f2,191.21,2677.704,512,352,63.22,79.06,193.78 -tf_efficientnet_b6_ns,188.46,679.176,128,528,19.4,167.39,43.04 -tf_efficientnet_b6_ap,188.11,680.439,128,528,19.4,167.39,43.04 -tf_efficientnet_b6,187.99,680.87,128,528,19.4,167.39,43.04 -swin_v2_cr_small_384,182.11,1405.708,256,384,29.73,328.89,49.7 -swin_base_patch4_window12_384,176.69,1086.618,192,384,47.19,134.78,87.9 -vit_base_patch8_224,174.18,1469.691,256,224,78.22,161.69,86.58 -cait_xs24_384,172.41,2969.69,512,384,19.28,183.98,26.67 -volo_d5_224,172.09,5950.508,1024,224,72.4,118.11,295.46 -vit_base_r50_s16_384,167.12,2297.711,384,384,67.43,135.03,98.95 -vit_base_resnet50_384,167.1,2298.053,384,384,67.43,135.03,98.95 -convnext_large_384_in22ft1k,166.43,1538.202,256,384,101.09,126.74,197.77 -cait_xxs36_384,163.24,6273.131,1024,384,14.35,183.7,17.37 -xcit_medium_24_p8_224_dist,162.77,3145.502,512,224,63.53,121.23,84.32 -xcit_medium_24_p8_224,162.47,3151.38,512,224,63.53,121.23,84.32 -eca_nfnet_l3,159.16,3216.919,512,448,52.55,118.4,72.04 -swin_v2_cr_huge_224,158.05,2429.581,384,224,115.98,130.61,657.83 -resnetrs350,152.47,3358.018,512,384,77.59,154.74,163.96 -volo_d2_384,149.2,1715.757,256,384,46.17,184.51,58.87 -ig_resnext101_32x32d,147.29,1738.089,256,224,87.29,91.12,468.53 -xcit_tiny_24_p8_384_dist,144.29,7096.813,1024,384,27.05,132.95,12.11 -xcit_small_12_p8_384_dist,140.94,3632.686,512,384,54.92,138.29,26.21 -vit_huge_patch14_224,137.14,7467.038,1024,224,167.4,139.41,632.05 -swin_v2_cr_base_384,136.57,1405.886,192,384,50.61,374.82,87.88 -cait_s24_384,132.93,3851.731,512,384,32.17,245.31,47.06 -xcit_large_24_p16_384_dist,132.54,3862.869,512,384,105.35,137.17,189.1 -efficientnetv2_xl,127.7,3007.081,384,512,93.85,247.32,208.12 -tf_efficientnetv2_xl_in21ft1k,126.72,3030.326,384,512,93.85,247.32,208.12 -resnest269e,122.23,3141.713,384,416,77.69,171.98,110.93 -convnext_xlarge_384_in22ft1k,113.66,1689.239,192,384,179.18,168.99,350.2 -efficientnet_b7,111.61,860.145,96,600,38.33,289.94,66.35 -swin_large_patch4_window12_384,111.13,1151.803,128,384,104.08,202.16,196.74 -resnetrs420,109.22,4687.594,512,416,108.45,213.79,191.89 -nfnet_f3,108.69,4710.42,512,416,115.58,141.78,254.92 -tf_efficientnet_b7_ns,108.52,884.628,96,600,38.33,289.94,66.35 -tf_efficientnet_b7,108.51,884.669,96,600,38.33,289.94,66.35 -tf_efficientnet_b7_ap,108.41,885.546,96,600,38.33,289.94,66.35 -convmixer_1536_20,105.15,9738.155,1024,224,48.68,33.03,51.63 -xcit_large_24_p8_224,98.65,5189.87,512,224,141.23,181.56,188.93 -xcit_large_24_p8_224_dist,98.5,5198.076,512,224,141.23,181.56,188.93 -dm_nfnet_f3,97.31,5261.505,512,416,115.58,141.78,254.92 -resnetv2_152x2_bit_teacher_384,96.06,2664.909,256,384,136.16,132.56,236.34 -resnetv2_50x3_bitm,93.55,1368.206,128,448,145.7,133.37,217.32 -vit_large_patch16_384,91.35,2802.38,256,384,191.21,270.24,304.72 -vit_giant_patch14_224,90.49,5658.11,512,224,267.18,192.64,1012.61 -cait_s36_384,89.11,5745.925,512,384,47.99,367.4,68.37 -ig_resnext101_32x48d,87.36,2197.696,192,224,153.57,131.06,828.41 -swin_v2_cr_large_384,86.85,1473.707,128,384,109.02,466.67,196.68 -beit_large_patch16_384,79.29,3228.802,256,384,191.21,270.24,305.0 -xcit_small_24_p8_384_dist,74.05,6914.533,512,384,105.24,265.91,47.63 -resnetv2_152x2_bitm,70.66,2717.055,192,448,184.99,180.43,236.34 -efficientnet_b8,69.61,1379.103,96,672,63.48,442.89,87.41 -tf_efficientnet_b8,68.01,1411.465,96,672,63.48,442.89,87.41 -tf_efficientnet_b8_ap,68.0,1411.838,96,672,63.48,442.89,87.41 -volo_d3_448,66.4,2891.706,192,448,96.33,446.83,86.63 -nfnet_f4,59.8,6420.863,384,512,216.26,262.26,316.07 -dm_nfnet_f4,58.08,4407.375,256,512,216.26,262.26,316.07 -resnetv2_101x3_bitm,57.61,2221.888,128,448,280.33,194.78,387.93 -vit_gigantic_patch14_224,55.06,6974.141,384,224,483.95,275.37,1844.44 -xcit_medium_24_p8_384_dist,55.01,4653.657,256,384,186.67,354.73,84.32 -volo_d4_448,49.32,2595.126,128,448,197.13,527.35,193.41 -swin_v2_cr_giant_224,47.35,2703.11,128,224,483.88,342.95,2598.76 -nfnet_f5,43.8,5844.773,256,544,290.97,349.71,377.21 -swin_v2_cr_huge_384,40.54,1578.782,64,384,352.16,696.31,657.94 -tf_efficientnet_l2_ns_475,39.18,1633.537,64,475,172.11,609.89,480.31 -dm_nfnet_f5,39.13,6543.097,256,544,290.97,349.71,377.21 -nfnet_f6,34.31,7461.788,256,576,378.69,452.2,438.36 -volo_d5_448,34.12,3751.116,128,448,315.06,737.92,295.91 -xcit_large_24_p8_384_dist,33.15,5792.568,192,384,415.0,531.82,188.93 -beit_large_patch16_512,32.17,2983.777,96,512,362.24,656.39,305.67 -dm_nfnet_f6,30.6,8365.588,256,576,378.69,452.2,438.36 -cait_m36_384,30.38,8425.311,256,384,173.11,734.81,271.22 -nfnet_f7,26.68,9596.214,256,608,480.39,570.85,499.5 -volo_d5_512,23.97,4004.478,96,512,425.09,1105.37,296.09 -resnetv2_152x4_bitm,18.45,3469.53,64,480,844.84,414.26,936.53 -efficientnet_l2,14.11,1701.114,24,800,479.12,1707.39,480.31 -tf_efficientnet_l2_ns,13.9,1726.621,24,800,479.12,1707.39,480.31 -cait_m48_448,13.15,9732.974,128,448,329.41,1708.23,356.46 -swin_v2_cr_giant_384,13.09,1833.537,24,384,1451.0,1686.82,2598.76 diff --git a/results/benchmark-infer-amp-nchw-pt112-cu113-rtx3090.csv b/results/benchmark-infer-amp-nchw-pt112-cu113-rtx3090.csv new file mode 100644 index 00000000..479e68d8 --- /dev/null +++ b/results/benchmark-infer-amp-nchw-pt112-cu113-rtx3090.csv @@ -0,0 +1,842 @@ +model,infer_samples_per_sec,infer_step_time,infer_batch_size,infer_img_size,infer_gmacs,infer_macts,param_count +tinynet_e,49285.12,20.767,1024,106,0.03,0.69,2.04 +mobilenetv3_small_050,43905.96,23.312,1024,224,0.03,0.92,1.59 +lcnet_035,40961.84,24.988,1024,224,0.03,1.04,1.64 +lcnet_050,36451.18,28.081,1024,224,0.05,1.26,1.88 +mobilenetv3_small_075,32291.57,31.7,1024,224,0.05,1.3,2.04 +mobilenetv3_small_100,28935.54,35.379,1024,224,0.06,1.42,2.54 +tf_mobilenetv3_small_minimal_100,27926.5,36.657,1024,224,0.06,1.41,2.04 +tinynet_d,27303.88,37.493,1024,152,0.05,1.42,2.34 +tf_mobilenetv3_small_075,26850.04,38.127,1024,224,0.05,1.3,2.04 +tf_mobilenetv3_small_100,24320.21,42.094,1024,224,0.06,1.42,2.54 +lcnet_075,22627.19,45.245,1024,224,0.1,1.99,2.36 +mnasnet_small,20150.91,50.806,1024,224,0.07,2.16,2.03 +levit_128s,19458.78,52.613,1024,224,0.31,1.88,7.78 +lcnet_100,18910.66,54.139,1024,224,0.16,2.52,2.95 +mobilenetv2_035,18047.72,56.728,1024,224,0.07,2.86,1.68 +regnetx_002,17921.55,57.126,1024,224,0.2,2.16,2.68 +regnety_002,16656.92,61.462,1024,224,0.2,2.17,3.16 +ghostnet_050,16494.57,62.071,1024,224,0.05,1.77,2.59 +mnasnet_050,15574.97,65.736,1024,224,0.11,3.07,2.22 +mobilenetv2_050,14533.98,70.445,1024,224,0.1,3.64,1.97 +tinynet_c,14397.76,71.111,1024,184,0.11,2.87,2.46 +semnasnet_050,14065.61,72.79,1024,224,0.11,3.44,2.08 +levit_128,13348.5,76.702,1024,224,0.41,2.71,9.21 +vit_small_patch32_224,12899.41,79.373,1024,224,1.15,2.5,22.88 +mixer_s32_224,12823.61,79.842,1024,224,1.0,2.28,19.1 +lcnet_150,12599.24,81.264,1024,224,0.34,3.79,4.5 +regnetx_004,12314.46,83.141,1024,224,0.4,3.14,5.16 +cs3darknet_focus_s,11852.98,86.381,1024,256,0.69,2.7,3.27 +mobilenetv3_large_075,11687.27,87.605,1024,224,0.16,4.0,3.99 +resnet10t,11549.51,88.651,1024,224,1.1,2.43,5.44 +cs3darknet_s,11540.93,88.716,1024,256,0.72,2.97,3.28 +vit_tiny_r_s16_p8_224,10917.33,93.785,1024,224,0.44,2.06,6.34 +ese_vovnet19b_slim_dw,10530.7,97.229,1024,224,0.4,5.28,1.9 +mobilenetv3_rw,10453.43,97.947,1024,224,0.23,4.41,5.48 +hardcorenas_a,10387.47,98.569,1024,224,0.23,4.38,5.26 +mobilenetv3_large_100_miil,10298.68,99.419,1024,224,0.23,4.41,5.48 +mobilenetv3_large_100,10295.13,99.453,1024,224,0.23,4.41,5.48 +tf_mobilenetv3_large_075,10277.2,99.627,1024,224,0.16,4.0,3.99 +gernet_s,10228.24,100.105,1024,224,0.75,2.65,8.17 +mnasnet_075,10209.23,100.29,1024,224,0.23,4.77,3.17 +levit_192,10099.95,101.375,1024,224,0.66,3.2,10.95 +tf_mobilenetv3_large_minimal_100,10021.88,102.166,1024,224,0.22,4.4,3.92 +hardcorenas_b,9469.88,108.121,1024,224,0.26,5.09,5.18 +regnetx_006,9309.45,109.982,1024,224,0.61,3.98,6.2 +tinynet_b,9298.6,110.113,1024,188,0.21,4.44,3.73 +regnety_004,9296.36,110.137,1024,224,0.41,3.89,4.34 +ghostnet_100,9264.87,110.513,1024,224,0.15,3.55,5.18 +hardcorenas_c,9196.31,111.338,1024,224,0.28,5.01,5.52 +resnet18,9171.4,111.64,1024,224,1.82,2.48,11.69 +tf_mobilenetv3_large_100,9170.64,111.649,1024,224,0.23,4.41,5.48 +mobilenetv2_075,9151.72,111.88,1024,224,0.22,5.86,2.64 +swsl_resnet18,9145.07,111.962,1024,224,1.82,2.48,11.69 +mnasnet_100,9128.95,112.159,1024,224,0.33,5.46,4.38 +mnasnet_b1,9096.68,112.558,1024,224,0.33,5.46,4.38 +gluon_resnet18_v1b,9092.93,112.604,1024,224,1.82,2.48,11.69 +ssl_resnet18,9043.33,113.221,1024,224,1.82,2.48,11.69 +semnasnet_075,8958.16,114.297,1024,224,0.23,5.54,2.91 +hardcorenas_d,8756.1,116.935,1024,224,0.3,4.93,7.5 +seresnet18,8678.54,117.981,1024,224,1.82,2.49,11.78 +regnety_006,8404.01,121.832,1024,224,0.61,4.33,6.06 +mobilenetv2_100,8360.81,122.466,1024,224,0.31,6.68,3.5 +legacy_seresnet18,8318.12,123.094,1024,224,1.82,2.49,11.78 +spnasnet_100,8246.33,124.165,1024,224,0.35,6.03,4.42 +semnasnet_100,8027.18,127.555,1024,224,0.32,6.23,3.89 +mnasnet_a1,8013.14,127.779,1024,224,0.32,6.23,3.89 +levit_256,7862.24,130.228,1024,224,1.13,4.23,18.89 +resnet18d,7721.04,132.614,1024,224,2.06,3.29,11.71 +hardcorenas_f,7642.68,133.973,1024,224,0.35,5.57,8.2 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+twins_svt_base,1307.2,783.34,1024,224,8.59,26.33,56.07 +dpn92,1299.67,787.878,1024,224,6.54,18.21,37.67 +cs3edgenet_x,1289.05,794.37,1024,288,14.59,16.36,47.82 +ese_vovnet99b_iabn,1282.63,798.345,1024,224,16.49,11.27,63.2 +crossvit_18_240,1272.74,804.553,1024,240,9.05,26.26,43.27 +regnety_040s_gn,1271.39,805.405,1024,224,4.03,12.29,20.65 +eca_nfnet_l0,1271.38,805.411,1024,288,7.12,17.29,24.14 +nfnet_l0,1269.37,806.681,1024,288,7.13,17.29,35.07 +seresnext101_32x4d,1268.1,807.494,1024,224,8.02,21.26,48.96 +legacy_seresnext101_32x4d,1267.59,807.817,1024,224,8.02,21.26,48.96 +gluon_seresnext101_32x4d,1265.67,809.045,1024,224,8.02,21.26,48.96 +nf_ecaresnet101,1264.2,809.986,1024,224,8.01,16.27,44.55 +vit_relpos_medium_patch16_rpn_224,1263.66,810.331,1024,224,7.97,17.02,38.73 +nf_seresnet101,1261.42,811.77,1024,224,8.02,16.27,49.33 +mobilevitv2_200,1256.15,305.684,384,256,7.22,32.15,18.45 +mobilevitv2_200_in22ft1k,1255.83,305.762,384,256,7.22,32.15,18.45 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+gluon_resnet152_v1d,1141.31,897.204,1024,224,11.8,23.36,60.21 +sequencer2d_m,1138.06,899.765,1024,224,6.55,14.26,38.31 +vit_base_patch16_224_sam,1132.42,904.242,1024,224,17.58,23.9,86.57 +deit_base_patch16_224,1132.42,904.245,1024,224,17.58,23.9,86.57 +vit_base_patch16_224,1132.21,904.413,1024,224,17.58,23.9,86.57 +dla169,1130.13,906.071,1024,224,11.6,20.2,53.39 +regnetx_120,1129.55,453.263,512,224,12.13,21.37,46.11 +volo_d1_224,1126.62,908.904,1024,224,6.94,24.43,26.63 +vgg19_bn,1122.31,456.189,512,224,19.66,14.86,143.68 +deit_base_distilled_patch16_224,1116.6,917.056,1024,224,17.68,24.05,87.34 +xception41,1110.46,461.057,512,299,9.28,39.86,26.97 +cait_xxs36_224,1104.66,926.97,1024,224,3.77,30.34,17.3 +tf_efficientnet_lite4,1091.59,351.767,384,380,4.04,45.66,13.01 +convmixer_1024_20_ks9_p14,1091.56,938.092,1024,224,5.55,5.51,24.38 +deit3_base_patch16_224,1090.26,939.213,1024,224,17.58,23.9,86.59 +deit3_base_patch16_224_in21ft1k,1088.57,940.667,1024,224,17.58,23.9,86.59 +legacy_seresnet152,1086.41,942.544,1024,224,11.33,22.08,66.82 +tnt_s_patch16_224,1079.54,948.54,1024,224,5.24,24.37,23.76 +regnety_120,1077.58,475.125,512,224,12.14,21.38,51.82 +repvgg_b3g4,1077.28,950.524,1024,224,17.89,15.1,83.83 +vit_relpos_base_patch16_clsgap_224,1077.01,950.767,1024,224,17.6,25.12,86.43 +vit_relpos_base_patch16_cls_224,1076.19,951.489,1024,224,17.6,25.12,86.43 +gluon_resnet152_v1s,1074.28,953.181,1024,224,12.92,24.96,60.32 +twins_pcpvt_large,1061.77,964.416,1024,224,9.84,35.82,60.99 +seresnet152,1047.32,977.721,1024,224,11.57,22.61,66.82 +beit_base_patch16_224,1045.12,979.774,1024,224,17.58,23.9,86.53 +xcit_small_24_p16_224_dist,1038.39,986.125,1024,224,9.1,23.64,47.67 +xcit_small_24_p16_224,1037.69,986.793,1024,224,9.1,23.64,47.67 +coat_tiny,1036.7,987.731,1024,224,4.35,27.2,5.5 +dm_nfnet_f0,1035.11,989.253,1024,256,12.62,18.05,71.49 +nf_regnet_b4,1027.0,997.065,1024,384,4.7,28.61,30.21 +vit_relpos_base_patch16_224,1017.61,1006.263,1024,224,17.51,24.97,86.43 +convnext_base_in22ft1k,1006.85,1017.02,1024,224,15.38,28.75,88.59 +convnext_base,1006.73,1017.126,1024,224,15.38,28.75,88.59 +pit_b_224,993.61,515.277,512,224,12.42,32.94,73.76 +pit_b_distilled_224,985.16,519.696,512,224,12.5,33.07,74.79 +tresnet_xl,983.38,1041.292,1024,224,15.17,15.34,78.44 +efficientnetv2_s,976.0,1049.166,1024,384,8.44,35.77,21.46 +dla102x2,973.1,526.138,512,224,9.34,29.91,41.28 +cs3se_edgenet_x,972.26,1053.196,1024,320,18.01,20.21,50.72 +vit_small_patch16_36x1_224,972.14,1053.329,1024,224,13.71,35.69,64.67 +swinv2_cr_small_224,966.28,1059.712,1024,224,9.07,50.27,49.7 +swinv2_cr_small_ns_224,955.69,1071.465,1024,224,9.08,50.27,49.7 +tf_efficientnetv2_s_in21ft1k,955.24,1071.964,1024,384,8.44,35.77,21.46 +tf_efficientnetv2_s,955.13,1072.086,1024,384,8.44,35.77,21.46 +vit_small_patch16_18x2_224,948.32,1079.793,1024,224,13.71,35.69,64.67 +wide_resnet101_2,939.08,1090.412,1024,224,22.8,21.23,126.89 +regnetx_160,936.53,546.684,512,224,15.99,25.52,54.28 +regnety_080,933.52,548.447,512,288,13.22,29.69,39.18 +regnetz_b16_evos,933.51,822.691,768,288,2.36,16.43,9.74 +efficientnetv2_rw_s,931.24,1099.596,1024,384,8.72,38.03,23.94 +resnetv2_50d_gn,920.9,1111.946,1024,288,7.24,19.7,25.57 +twins_svt_large,918.22,1115.185,1024,224,15.15,35.1,99.27 +efficientnet_b4,917.89,418.339,384,384,4.51,50.04,19.34 +regnetz_040,913.72,420.249,384,320,6.35,37.78,27.12 +xception65p,910.71,562.184,512,299,13.91,52.48,39.82 +regnetz_040h,909.33,422.274,384,320,6.43,37.94,28.94 +dpn98,906.73,1129.316,1024,224,11.73,25.2,61.57 +repvgg_b3,901.67,1135.661,1024,224,29.16,15.1,123.09 +resnetrs101,898.53,1139.62,1024,288,13.56,28.53,63.62 +gluon_resnext101_64x4d,887.37,1153.955,1024,224,15.52,31.21,83.46 +nest_small,885.28,867.51,768,224,10.35,40.04,38.35 +poolformer_m36,879.83,1163.84,1024,224,8.8,22.02,56.17 +regnetz_d8,877.84,1166.489,1024,320,6.19,37.08,23.37 +jx_nest_small,874.11,878.596,768,224,10.35,40.04,38.35 +ssl_resnext101_32x8d,874.01,1171.597,1024,224,16.48,31.21,88.79 +swsl_resnext101_32x8d,873.31,1172.532,1024,224,16.48,31.21,88.79 +resnext101_32x8d,873.01,1172.932,1024,224,16.48,31.21,88.79 +ig_resnext101_32x8d,872.81,1173.211,1024,224,16.48,31.21,88.79 +regnetz_d32,869.58,1177.564,1024,320,9.33,37.08,27.58 +inception_resnet_v2,868.78,1178.653,1024,299,13.18,25.06,55.84 +ens_adv_inception_resnet_v2,868.32,1179.275,1024,299,13.18,25.06,55.84 +xcit_tiny_24_p16_384_dist,866.54,1181.7,1024,384,6.87,34.29,12.12 +cait_s24_224,865.33,1183.354,1024,224,9.35,40.58,46.92 +resnest101e,858.93,894.122,768,256,13.38,28.66,48.28 +tf_efficientnet_b4,858.91,447.067,384,380,4.49,49.49,19.34 +tf_efficientnet_b4_ap,858.7,447.171,384,380,4.49,49.49,19.34 +tf_efficientnet_b4_ns,858.52,447.267,384,380,4.49,49.49,19.34 +swin_s3_small_224,853.54,899.766,768,224,9.43,37.84,49.74 +regnetv_064,852.1,600.857,512,288,10.55,27.11,30.58 +regnety_064,851.33,601.396,512,288,10.56,27.11,30.58 +resnet200,847.44,1208.333,1024,224,15.07,32.19,64.67 +gluon_seresnext101_64x4d,834.87,1226.518,1024,224,15.53,31.25,88.23 +coat_mini,833.41,1228.669,1024,224,6.82,33.68,10.34 +swin_base_patch4_window7_224,832.6,1229.869,1024,224,15.47,36.63,87.77 +resnet101d,816.8,1253.661,1024,320,16.48,34.77,44.57 +gluon_xception65,816.5,627.052,512,299,13.96,52.48,39.92 +xception65,811.16,631.185,512,299,13.96,52.48,39.92 +resnetv2_50d_evos,810.51,947.543,768,288,7.15,19.7,25.59 +convnext_tiny_384_in22ft1k,807.27,634.218,512,384,13.14,39.48,28.59 +gmlp_b16_224,789.84,1296.449,1024,224,15.78,30.21,73.08 +hrnet_w40,787.85,1299.728,1024,224,12.75,25.29,57.56 +crossvit_base_240,787.17,975.639,768,240,21.22,36.33,105.03 +hrnet_w44,771.15,1327.87,1024,224,14.94,26.92,67.06 +swinv2_tiny_window16_256,763.4,670.672,512,256,6.68,39.02,28.35 +mobilevitv2_150_384_in22ft1k,757.55,337.918,256,384,9.2,54.25,10.59 +xcit_medium_24_p16_224_dist,748.7,1367.689,1024,224,16.13,31.71,84.4 +xcit_medium_24_p16_224,748.18,1368.635,1024,224,16.13,31.71,84.4 +tresnet_m_448,743.16,1377.885,1024,448,22.94,29.21,31.39 +vit_large_r50_s32_224,742.19,1379.692,1024,224,19.58,24.41,328.99 +hrnet_w48,738.63,1386.343,1024,224,17.34,28.56,77.47 +vit_base_patch16_plus_240,738.11,1387.321,1024,240,27.41,33.08,117.56 +sequencer2d_l,736.17,1390.978,1024,224,9.74,22.12,54.3 +xcit_small_12_p16_384_dist,715.91,1430.327,1024,384,14.14,36.51,26.25 +swinv2_small_window8_256,710.32,1441.594,1024,256,11.58,40.14,49.73 +swin_s3_base_224,693.67,1476.198,1024,224,13.69,48.26,71.13 +vit_small_patch16_384,692.4,1109.164,768,384,15.52,50.78,22.2 +vit_relpos_base_patch16_plus_240,691.79,1480.194,1024,240,27.3,34.33,117.38 +tnt_b_patch16_224,691.78,1480.223,1024,224,14.09,39.01,65.41 +swinv2_cr_base_224,688.11,1488.125,1024,224,15.86,59.66,87.88 +densenet264d_iabn,687.57,1489.287,1024,224,13.47,14.0,72.74 +convit_base,685.88,1492.962,1024,224,17.52,31.77,86.54 +swinv2_cr_base_ns_224,682.58,1500.17,1024,224,15.86,59.66,87.88 +vit_base_patch16_rpn_224,667.73,1533.544,1024,224,17.49,23.75,86.54 +densenet264,664.62,1540.716,1024,224,12.95,12.8,72.69 +deit3_small_patch16_384,664.03,1156.564,768,384,15.52,50.78,22.21 +poolformer_m48,663.83,1542.547,1024,224,11.59,29.17,73.47 +deit3_small_patch16_384_in21ft1k,663.62,1157.274,768,384,15.52,50.78,22.21 +efficientnet_b3_gn,662.87,386.187,256,320,2.14,28.83,11.73 +dpn131,660.11,1551.238,1024,224,16.09,32.97,79.25 +eca_nfnet_l1,655.87,1561.27,1024,320,14.92,34.42,41.41 +vit_relpos_base_patch16_rpn_224,655.49,1562.186,1024,224,17.51,24.97,86.41 +xcit_tiny_24_p8_224,650.45,1574.283,1024,224,9.21,45.39,12.11 +xcit_tiny_24_p8_224_dist,649.22,1577.262,1024,224,9.21,45.39,12.11 +xcit_nano_12_p8_384_dist,643.06,1592.369,1024,384,6.34,46.08,3.05 +nest_base,629.02,813.95,512,224,17.96,53.39,67.72 +volo_d2_224,627.91,1630.781,1024,224,14.34,41.34,58.68 +mobilevitv2_175_384_in22ft1k,627.52,407.942,256,384,12.47,63.29,14.25 +jx_nest_base,621.88,823.3,512,224,17.96,53.39,67.72 +vit_small_r26_s32_384,619.54,619.804,384,384,10.43,29.85,36.47 +senet154,618.82,1654.743,1024,224,20.77,38.69,115.09 +gluon_senet154,618.51,1655.586,1024,224,20.77,38.69,115.09 +legacy_senet154,618.16,1656.503,1024,224,20.77,38.69,115.09 +xception71,616.97,829.852,512,299,18.09,69.92,42.34 +vit_base_r50_s16_224,613.11,1670.152,1024,224,21.66,35.29,98.66 +hrnet_w64,609.7,1679.491,1024,224,28.97,35.09,128.06 +regnety_320,607.61,842.637,512,224,32.34,30.26,145.05 +dpn107,606.08,1689.539,1024,224,18.38,33.46,86.92 +regnetz_c16_evos,598.89,854.904,512,320,3.86,25.88,13.49 +ecaresnet200d,592.5,1728.248,1024,256,20.0,43.15,64.69 +seresnet200d,591.19,1732.085,1024,256,20.01,43.15,71.86 +resnet152d,576.9,1774.999,1024,320,24.08,47.67,60.21 +convnext_large,559.02,1831.761,1024,224,34.4,43.13,197.77 +convnext_large_in22ft1k,558.96,1831.941,1024,224,34.4,43.13,197.77 +regnety_160,558.21,687.896,384,288,26.37,38.07,83.59 +efficientnet_b3_g8_gn,557.9,458.854,256,320,3.2,28.83,14.25 +xcit_small_12_p8_224,546.6,1873.371,1024,224,18.69,47.21,26.21 +xcit_small_12_p8_224_dist,546.45,1873.905,1024,224,18.69,47.21,26.21 +resnext101_64x4d,541.68,1417.803,768,288,25.66,51.59,83.46 +mobilevitv2_200_384_in22ft1k,527.08,364.262,192,384,16.24,72.34,18.45 +halonet_h1,518.76,493.471,256,256,3.0,51.17,8.1 +vit_large_patch32_384,517.18,1979.967,1024,384,45.31,43.86,306.63 +seresnet152d,516.02,1984.399,1024,320,24.09,47.72,66.84 +resnetrs152,512.78,1996.941,1024,320,24.34,48.14,86.62 +swinv2_base_window8_256,507.32,1513.812,768,256,20.37,52.59,87.92 +seresnext101_32x8d,503.19,1526.235,768,288,27.24,51.63,93.57 +convnext_small_384_in22ft1k,494.64,1035.087,512,384,25.58,63.37,50.22 +seresnext101d_32x8d,494.43,1553.287,768,288,27.64,52.95,93.59 +swin_large_patch4_window7_224,478.67,1604.435,768,224,34.53,54.94,196.53 +swinv2_small_window16_256,476.38,1074.753,512,256,12.82,66.29,49.73 +regnetz_e8,474.49,1618.577,768,320,15.46,63.94,57.7 +regnetx_320,471.27,814.799,384,224,31.81,36.3,107.81 +ssl_resnext101_32x16d,471.02,1086.983,512,224,36.27,51.18,194.03 +swsl_resnext101_32x16d,470.83,1087.428,512,224,36.27,51.18,194.03 +ig_resnext101_32x16d,470.74,1087.624,512,224,36.27,51.18,194.03 +mixer_l16_224,470.73,2175.315,1024,224,44.6,41.69,208.2 +seresnextaa101d_32x8d,463.39,1657.351,768,288,28.51,56.44,93.59 +seresnet269d,463.29,2210.273,1024,256,26.59,53.6,113.67 +nf_regnet_b5,450.96,1135.344,512,456,11.7,61.95,49.74 +efficientnetv2_m,449.82,2276.453,1024,416,18.6,67.5,54.14 +volo_d3_224,439.99,2327.294,1024,224,20.78,60.09,86.33 +efficientnet_b5,425.78,601.238,256,456,10.46,98.86,30.39 +xcit_large_24_p16_224_dist,423.07,2420.403,1024,224,35.86,47.27,189.1 +xcit_large_24_p16_224,422.98,2420.908,1024,224,35.86,47.27,189.1 +xcit_tiny_12_p8_384_dist,419.35,2441.847,1024,384,14.13,69.14,6.71 +resnet200d,417.0,2455.593,1024,320,31.25,67.33,64.69 +efficientnetv2_rw_m,411.82,1864.879,768,416,21.49,79.62,53.24 +tf_efficientnet_b5_ns,408.16,627.186,256,456,10.46,98.86,30.39 +swinv2_cr_tiny_384,408.1,627.286,256,384,15.34,161.01,28.33 +tf_efficientnet_b5,407.78,627.773,256,456,10.46,98.86,30.39 +tf_efficientnet_b5_ap,407.68,627.936,256,456,10.46,98.86,30.39 +swinv2_cr_large_224,405.25,1895.127,768,224,35.1,78.42,196.68 +resnetv2_50x1_bitm,401.93,955.37,384,448,16.62,44.46,25.55 +nfnet_f1,399.69,2561.946,1024,320,35.97,46.77,132.63 +xcit_small_24_p16_384_dist,382.57,2676.633,1024,384,26.72,68.58,47.67 +regnetz_d8_evos,376.87,2037.797,768,320,7.03,38.92,23.46 +tresnet_l_448,371.52,2756.242,1024,448,43.5,47.56,55.99 +vit_large_patch16_224,369.7,2769.802,1024,224,61.6,63.52,304.33 +resnetrs200,368.58,2778.22,1024,320,31.51,67.81,93.21 +convnext_xlarge_in22ft1k,368.02,1391.221,512,224,60.98,57.5,350.2 +crossvit_15_dagger_408,366.37,698.731,256,408,21.45,95.05,28.5 +vit_base_patch16_18x2_224,361.96,2829.064,1024,224,52.51,71.38,256.73 +deit3_large_patch16_224,358.07,2859.733,1024,224,61.6,63.52,304.37 +deit3_large_patch16_224_in21ft1k,357.9,2861.143,1024,224,61.6,63.52,304.37 +dm_nfnet_f1,357.87,2146.026,768,320,35.97,46.77,132.63 +tf_efficientnetv2_m,350.54,2190.896,768,480,24.76,89.84,54.14 +tf_efficientnetv2_m_in21ft1k,350.14,2193.372,768,480,24.76,89.84,54.14 +swinv2_base_window16_256,345.6,1111.087,384,256,22.02,84.71,87.92 +swinv2_base_window12to16_192to256_22kft1k,345.47,1111.525,384,256,22.02,84.71,87.92 +convnext_base_384_in22ft1k,344.56,1485.926,512,384,45.21,84.49,88.59 +beit_large_patch16_224,342.32,2991.347,1024,224,61.6,63.52,304.43 +eca_nfnet_l2,322.02,2384.947,768,384,30.05,68.28,56.72 +volo_d1_384,293.04,1747.159,512,384,22.75,108.55,26.78 +convmixer_768_32,292.83,3496.872,1024,224,19.55,25.95,21.11 +resnetv2_152x2_bit_teacher,291.46,2634.992,768,224,46.95,45.11,236.34 +deit_base_patch16_384,288.65,1330.327,384,384,55.54,101.56,86.86 +vit_base_patch16_384,288.47,1331.141,384,384,55.54,101.56,86.86 +resnest200e,288.19,1776.58,512,320,35.69,82.78,70.2 +xcit_small_24_p8_224,286.12,3578.848,1024,224,35.81,90.78,47.63 +xcit_small_24_p8_224_dist,286.06,3579.677,1024,224,35.81,90.78,47.63 +deit_base_distilled_patch16_384,284.56,1349.413,384,384,55.65,101.82,87.63 +volo_d4_224,282.61,3623.333,1024,224,44.34,80.22,192.96 +deit3_base_patch16_384,277.81,1382.217,384,384,55.54,101.56,86.88 +deit3_base_patch16_384_in21ft1k,277.78,1382.367,384,384,55.54,101.56,86.88 +tresnet_xl_448,277.15,2771.052,768,448,60.65,61.31,78.44 +nasnetalarge,276.88,1386.877,384,331,23.89,90.56,88.75 +vit_large_patch14_224,271.51,3771.489,1024,224,81.08,88.79,304.2 +cait_xxs24_384,269.82,3795.14,1024,384,9.63,122.66,12.03 +crossvit_18_dagger_408,269.4,950.247,256,408,32.47,124.87,44.61 +xcit_medium_24_p16_384_dist,269.2,2852.889,768,384,47.39,91.64,84.4 +pnasnet5large,264.84,1449.925,384,331,25.04,92.89,86.06 +resnetv2_101x1_bitm,252.59,1520.226,384,448,31.65,64.93,44.54 +efficientnet_b6,252.26,507.392,128,528,19.4,167.39,43.04 +swinv2_cr_small_384,250.03,1023.876,256,384,29.7,298.03,49.7 +beit_base_patch16_384,247.68,1550.363,384,384,55.54,101.56,86.74 +vit_large_r50_s32_384,246.17,1559.866,384,384,57.43,76.52,329.09 +tf_efficientnet_b6_ns,242.42,527.986,128,528,19.4,167.39,43.04 +tf_efficientnet_b6,242.34,528.179,128,528,19.4,167.39,43.04 +tf_efficientnet_b6_ap,242.3,528.255,128,528,19.4,167.39,43.04 +ecaresnet269d,241.69,4236.816,1024,352,50.25,101.25,102.09 +resnetrs270,234.11,4373.986,1024,352,51.13,105.48,129.86 +nfnet_f2,224.73,4556.614,1024,352,63.22,79.06,193.78 +swin_base_patch4_window12_384,220.36,871.278,192,384,47.19,134.78,87.9 +xcit_tiny_24_p8_384_dist,219.9,4656.678,1024,384,27.05,132.95,12.11 +resmlp_big_24_224,218.18,4693.363,1024,224,100.23,87.31,129.14 +resmlp_big_24_224_in22ft1k,217.68,4704.164,1024,224,100.23,87.31,129.14 +resmlp_big_24_distilled_224,217.65,4704.831,1024,224,100.23,87.31,129.14 +swinv2_large_window12to16_192to256_22kft1k,211.96,1207.756,256,256,47.81,121.53,196.74 +efficientnetv2_l,206.63,2477.808,512,480,56.4,157.99,118.52 +tf_efficientnetv2_l,204.52,2503.355,512,480,56.4,157.99,118.52 +tf_efficientnetv2_l_in21ft1k,204.48,2503.917,512,480,56.4,157.99,118.52 +ig_resnext101_32x32d,202.59,1263.594,256,224,87.29,91.12,468.53 +xcit_medium_24_p8_224,202.12,5066.293,1024,224,63.53,121.23,84.32 +xcit_medium_24_p8_224_dist,201.88,5072.196,1024,224,63.53,121.23,84.32 +dm_nfnet_f2,200.18,3836.576,768,352,63.22,79.06,193.78 +convnext_large_384_in22ft1k,190.55,1343.472,256,384,101.1,126.74,197.77 +vit_base_patch8_224,188.25,1359.85,256,224,78.22,161.69,86.58 +volo_d5_224,187.56,5459.662,1024,224,72.4,118.11,295.46 +cait_xs24_384,186.33,4121.716,768,384,19.28,183.98,26.67 +xcit_small_12_p8_384_dist,183.57,2091.823,384,384,54.92,138.29,26.21 +eca_nfnet_l3,182.91,2799.141,512,448,52.55,118.4,72.04 +cait_xxs36_384,180.41,5675.791,1024,384,14.35,183.7,17.37 +swinv2_cr_base_384,178.38,1435.085,256,384,50.57,333.68,87.88 +vit_base_resnet50_384,177.85,2159.087,384,384,67.43,135.03,98.95 +vit_base_r50_s16_384,177.6,2162.196,384,384,67.43,135.03,98.95 +swinv2_cr_huge_224,175.47,2188.347,384,224,115.97,121.08,657.83 +convmixer_1536_20,167.1,6128.044,1024,224,48.68,33.03,51.63 +volo_d2_384,164.75,1553.889,256,384,46.17,184.51,58.87 +resnetrs350,156.77,4898.75,768,384,77.59,154.74,163.96 +xcit_large_24_p16_384_dist,154.33,3317.602,512,384,105.35,137.17,189.1 +vit_huge_patch14_224,146.32,6998.359,1024,224,167.4,139.41,632.05 +efficientnet_b7,145.11,661.558,96,600,38.33,289.94,66.35 +cait_s24_384,144.99,3531.336,512,384,32.17,245.31,47.06 +deit3_huge_patch14_224,142.26,7197.843,1024,224,167.4,139.41,632.13 +deit3_huge_patch14_224_in21ft1k,142.17,7202.758,1024,224,167.4,139.41,632.13 +tf_efficientnet_b7_ns,140.64,682.566,96,600,38.33,289.94,66.35 +tf_efficientnet_b7_ap,140.61,682.704,96,600,38.33,289.94,66.35 +tf_efficientnet_b7,140.6,682.756,96,600,38.33,289.94,66.35 +efficientnetv2_xl,139.56,2751.573,384,512,93.85,247.32,208.12 +tf_efficientnetv2_xl_in21ft1k,138.42,2774.117,384,512,93.85,247.32,208.12 +resnest269e,135.65,2830.833,384,416,77.69,171.98,110.93 +swin_large_patch4_window12_384,130.35,981.936,128,384,104.08,202.16,196.74 +convnext_xlarge_384_in22ft1k,125.25,1532.9,192,384,179.2,168.99,350.2 +nfnet_f3,124.74,4104.555,512,416,115.58,141.78,254.92 +ig_resnext101_32x48d,118.28,1623.193,192,224,153.57,131.06,828.41 +xcit_large_24_p8_224,115.22,4443.765,512,224,141.23,181.56,188.93 +xcit_large_24_p8_224_dist,115.18,4445.056,512,224,141.23,181.56,188.93 +resnetrs420,112.12,6849.78,768,416,108.45,213.79,191.89 +dm_nfnet_f3,110.18,4647.097,512,416,115.58,141.78,254.92 +swinv2_cr_large_384,108.04,1184.75,128,384,108.95,404.96,196.68 +resnetv2_50x3_bitm,102.09,1253.798,128,448,145.7,133.37,217.32 +resnetv2_152x2_bit_teacher_384,98.91,2588.163,256,384,136.16,132.56,236.34 +vit_large_patch16_384,97.45,2626.88,256,384,191.21,270.24,304.72 +cait_s36_384,97.05,5275.469,512,384,47.99,367.4,68.37 +xcit_small_24_p8_384_dist,96.34,3985.916,384,384,105.24,265.91,47.63 +vit_giant_patch14_224,95.73,8022.929,768,224,267.18,192.64,1012.61 +deit3_large_patch16_384,94.64,2704.996,256,384,191.21,270.24,304.76 +deit3_large_patch16_384_in21ft1k,94.52,2708.314,256,384,191.21,270.24,304.76 +swinv2_base_window12to24_192to384_22kft1k,94.37,678.174,64,384,55.25,280.36,87.92 +efficientnet_b8,91.29,1051.594,96,672,63.48,442.89,87.41 +tf_efficientnet_b8,88.95,1079.277,96,672,63.48,442.89,87.41 +tf_efficientnet_b8_ap,88.84,1080.533,96,672,63.48,442.89,87.41 +beit_large_patch16_384,84.67,3023.634,256,384,191.21,270.24,305.0 +resnetv2_152x2_bitm,73.09,2626.956,192,448,184.99,180.43,236.34 +volo_d3_448,72.41,2651.496,192,448,96.33,446.83,86.63 +nfnet_f4,69.91,5493.031,384,512,216.26,262.26,316.07 +xcit_medium_24_p8_384_dist,67.93,3768.466,256,384,186.67,354.73,84.32 +dm_nfnet_f4,62.55,4092.528,256,512,216.26,262.26,316.07 +resnetv2_101x3_bitm,61.05,2096.759,128,448,280.33,194.78,387.93 +swinv2_large_window12to24_192to384_22kft1k,59.71,803.821,48,384,116.15,407.83,196.74 +vit_gigantic_patch14_224,57.59,8890.782,512,224,483.95,275.37,1844.44 +tf_efficientnet_l2_ns_475,56.35,1135.833,64,475,172.11,609.89,480.31 +volo_d4_448,52.92,2418.622,128,448,197.13,527.35,193.41 +swinv2_cr_giant_224,50.53,2532.906,128,224,483.85,309.15,2598.76 +nfnet_f5,49.64,5157.064,256,544,290.97,349.71,377.21 +swinv2_cr_huge_384,47.06,1360.056,64,384,352.04,583.18,657.94 +dm_nfnet_f5,44.17,5795.363,256,544,290.97,349.71,377.21 +xcit_large_24_p8_384_dist,38.64,4968.379,192,384,415.0,531.82,188.93 +nfnet_f6,37.99,6738.223,256,576,378.69,452.2,438.36 +volo_d5_448,36.49,3507.831,128,448,315.06,737.92,295.91 +beit_large_patch16_512,33.88,2833.282,96,512,362.24,656.39,305.67 +dm_nfnet_f6,33.83,7567.962,256,576,378.69,452.2,438.36 +cait_m36_384,31.72,8071.786,256,384,173.11,734.81,271.22 +nfnet_f7,30.38,8426.213,256,608,480.39,570.85,499.5 +volo_d5_512,25.58,3752.221,96,512,425.09,1105.37,296.09 +resnetv2_152x4_bitm,22.67,4234.474,96,480,844.84,414.26,936.53 +efficientnet_l2,20.51,1169.975,24,800,479.12,1707.39,480.31 +tf_efficientnet_l2_ns,20.15,1191.261,24,800,479.12,1707.39,480.31 +swinv2_cr_giant_384,14.62,2188.205,32,384,1450.71,1394.86,2598.76 +cait_m48_448,13.47,9503.031,128,448,329.41,1708.23,356.46 diff --git a/results/benchmark-infer-amp-nhwc-pt110-cu113-rtx3090.csv b/results/benchmark-infer-amp-nhwc-pt110-cu113-rtx3090.csv deleted file mode 100644 index 0eb5b865..00000000 --- a/results/benchmark-infer-amp-nhwc-pt110-cu113-rtx3090.csv +++ /dev/null @@ -1,747 +0,0 @@ -model,infer_samples_per_sec,infer_step_time,infer_batch_size,infer_img_size,infer_gmacs,infer_macts,param_count -tinynet_e,67598.74,15.137,1024,106,0.03,0.69,2.04 -mobilenetv3_small_050,48021.33,21.312,1024,224,0.03,0.92,1.59 -lcnet_035,46934.76,21.806,1024,224,0.03,1.04,1.64 -lcnet_050,41338.69,24.759,1024,224,0.05,1.26,1.88 -mobilenetv3_small_075,37600.26,27.223,1024,224,0.05,1.3,2.04 -mobilenetv3_small_100,34647.33,29.544,1024,224,0.06,1.42,2.54 -tinynet_d,34267.93,29.871,1024,152,0.05,1.42,2.34 -tf_mobilenetv3_small_minimal_100,30966.2,33.057,1024,224,0.06,1.41,2.04 -tf_mobilenetv3_small_075,30182.31,33.916,1024,224,0.05,1.3,2.04 -tf_mobilenetv3_small_100,28343.09,36.117,1024,224,0.06,1.42,2.54 -lcnet_075,26938.48,38.001,1024,224,0.1,1.99,2.36 -mnasnet_small,23076.61,44.363,1024,224,0.07,2.16,2.03 -lcnet_100,22762.31,44.976,1024,224,0.16,2.52,2.95 -levit_128s,20755.15,49.325,1024,224,0.31,1.88,7.78 -mobilenetv2_035,19994.44,51.203,1024,224,0.07,2.86,1.68 -ghostnet_050,18471.32,55.424,1024,224,0.05,1.77,2.59 -mnasnet_050,18296.1,55.958,1024,224,0.11,3.07,2.22 -regnetx_002,17879.88,57.26,1024,224,0.2,2.16,2.68 -tinynet_c,17314.92,59.128,1024,184,0.11,2.87,2.46 -regnety_002,16652.24,61.481,1024,224,0.2,2.17,3.16 -mobilenetv2_050,16390.03,62.466,1024,224,0.1,3.64,1.97 -semnasnet_050,16274.49,62.909,1024,224,0.11,3.44,2.08 -lcnet_150,15027.49,68.13,1024,224,0.34,3.79,4.5 -regnetx_004,14443.33,70.887,1024,224,0.4,3.14,5.16 -levit_128,14144.82,72.382,1024,224,0.41,2.71,9.21 -gernet_s,14022.8,73.012,1024,224,0.75,2.65,8.17 -mobilenetv3_large_075,13623.51,75.153,1024,224,0.16,4.0,3.99 -levit_192,12569.09,81.459,1024,224,0.66,3.2,10.95 -mnasnet_075,12484.05,82.013,1024,224,0.23,4.77,3.17 -hardcorenas_a,12417.99,82.45,1024,224,0.23,4.38,5.26 -mobilenetv3_rw,12394.68,82.605,1024,224,0.23,4.41,5.48 -mobilenetv3_large_100,12240.42,83.646,1024,224,0.23,4.41,5.48 -mobilenetv3_large_100_miil,12231.48,83.708,1024,224,0.23,4.41,5.48 -tf_mobilenetv3_large_075,11693.54,87.558,1024,224,0.16,4.0,3.99 -tinynet_b,11575.42,88.451,1024,188,0.21,4.44,3.73 -hardcorenas_b,11309.45,90.531,1024,224,0.26,5.09,5.18 -ese_vovnet19b_slim_dw,11282.98,90.744,1024,224,0.4,5.28,1.9 -hardcorenas_c,11278.74,90.778,1024,224,0.28,5.01,5.52 -tf_mobilenetv3_large_minimal_100,11239.3,91.097,1024,224,0.22,4.4,3.92 -mixer_s32_224,11024.19,92.875,1024,224,1.0,2.28,19.1 -mnasnet_b1,10928.0,93.692,1024,224,0.33,5.46,4.38 -mnasnet_100,10925.28,93.715,1024,224,0.33,5.46,4.38 -ssl_resnet18,10839.84,94.456,1024,224,1.82,2.48,11.69 -swsl_resnet18,10838.47,94.466,1024,224,1.82,2.48,11.69 -resnet18,10801.25,94.792,1024,224,1.82,2.48,11.69 -gluon_resnet18_v1b,10770.37,95.064,1024,224,1.82,2.48,11.69 -tf_mobilenetv3_large_100,10561.44,96.944,1024,224,0.23,4.41,5.48 -semnasnet_075,10534.15,97.196,1024,224,0.23,5.54,2.91 -hardcorenas_d,10497.86,97.532,1024,224,0.3,4.93,7.5 -ghostnet_100,10377.41,98.663,1024,224,0.15,3.55,5.18 -mobilenetv2_075,10371.19,98.722,1024,224,0.22,5.86,2.64 -vit_small_patch32_224,10204.75,100.333,1024,224,1.15,2.5,22.88 -seresnet18,10134.68,101.027,1024,224,1.82,2.49,11.78 -regnety_006,9954.3,102.858,1024,224,0.61,4.33,6.06 -spnasnet_100,9888.24,103.545,1024,224,0.35,6.03,4.42 -legacy_seresnet18,9818.56,104.281,1024,224,1.82,2.49,11.78 -regnety_004,9541.83,107.304,1024,224,0.41,3.89,4.34 -tinynet_a,9384.67,109.102,1024,192,0.35,5.41,6.19 -hardcorenas_f,9332.55,109.711,1024,224,0.35,5.57,8.2 -semnasnet_100,9315.23,109.915,1024,224,0.32,6.23,3.89 -mnasnet_a1,9304.78,110.039,1024,224,0.32,6.23,3.89 -mobilenetv2_100,9258.67,110.587,1024,224,0.31,6.68,3.5 -hardcorenas_e,9198.78,111.307,1024,224,0.35,5.65,8.07 -levit_256,9194.42,111.36,1024,224,1.13,4.23,18.89 -tf_efficientnetv2_b0,9174.7,111.6,1024,224,0.73,4.77,7.14 -fbnetc_100,9062.65,112.98,1024,224,0.4,6.51,5.57 -efficientnet_lite0,8993.41,113.849,1024,224,0.4,6.74,4.65 -resnet18d,8935.88,114.583,1024,224,2.06,3.29,11.71 -vit_tiny_r_s16_p8_224,8745.04,117.083,1024,224,0.44,2.06,6.34 -ese_vovnet19b_slim,8703.47,117.642,1024,224,1.69,3.52,3.17 -regnetx_008,8472.48,120.85,1024,224,0.81,5.15,7.26 -regnetx_006,7966.99,128.519,1024,224,0.61,3.98,6.2 -levit_256d,7831.06,130.75,1024,224,1.4,4.93,26.21 -regnety_008,7830.87,130.751,1024,224,0.81,5.25,6.26 -tf_efficientnet_lite0,7797.89,131.305,1024,224,0.4,6.74,4.65 -ghostnet_130,7607.96,134.583,1024,224,0.24,4.6,7.36 -efficientnet_b0,7607.28,134.597,1024,224,0.4,6.75,5.29 -mnasnet_140,7524.53,136.075,1024,224,0.6,7.71,7.12 -rexnetr_100,7232.49,141.572,1024,224,0.43,7.72,4.88 -mobilenetv2_110d,7028.36,145.684,1024,224,0.45,8.71,4.52 -tf_efficientnet_b0_ap,6725.28,152.249,1024,224,0.4,6.75,5.29 -tf_efficientnet_b0_ns,6722.65,152.307,1024,224,0.4,6.75,5.29 -tf_efficientnet_b0,6714.91,152.484,1024,224,0.4,6.75,5.29 -hrnet_w18_small,6643.57,154.12,1024,224,1.61,5.72,13.19 -regnetz_005,6617.28,154.735,1024,224,0.52,5.86,7.12 -gernet_m,6458.86,158.529,1024,224,3.02,5.24,21.14 -semnasnet_140,6419.24,159.509,1024,224,0.6,8.87,6.11 -tv_resnet34,6315.93,162.117,1024,224,3.67,3.74,21.8 -resnet34,6312.51,162.205,1024,224,3.67,3.74,21.8 -gluon_resnet34_v1b,6269.39,163.321,1024,224,3.67,3.74,21.8 -mobilenetv2_140,6223.46,164.527,1024,224,0.6,9.57,6.11 -ese_vovnet19b_dw,6166.26,166.054,1024,224,1.34,8.25,6.54 -efficientnet_lite1,5999.14,170.68,1024,240,0.62,10.14,5.42 -efficientnet_b1_pruned,5947.73,172.154,1024,240,0.4,6.21,6.33 -selecsls42,5907.3,173.332,1024,224,2.94,4.62,30.35 -selecsls42b,5879.07,174.165,1024,224,2.98,4.62,32.46 -tf_efficientnetv2_b1,5876.94,174.228,1024,240,1.21,7.34,8.14 -fbnetv3_b,5872.22,174.368,1024,256,0.55,9.1,8.6 -seresnet34,5869.49,174.448,1024,224,3.67,3.74,21.96 -skresnet18,5850.83,175.006,1024,224,1.82,3.24,11.96 -rexnet_100,5841.4,175.288,1024,224,0.41,7.44,4.8 -resnet26,5734.75,178.548,1024,224,2.36,7.35,16.0 -efficientnet_es_pruned,5732.72,178.611,1024,224,1.81,8.73,5.44 -efficientnet_es,5729.21,178.72,1024,224,1.81,8.73,5.44 -legacy_seresnet34,5666.19,180.71,1024,224,3.67,3.74,21.96 -resnet34d,5621.93,182.132,1024,224,3.91,4.54,21.82 -levit_384,5524.35,185.349,1024,224,2.36,6.26,39.13 -resnetblur18,5512.12,185.761,1024,224,2.34,3.39,11.69 -nf_regnet_b0,5492.16,186.436,1024,256,0.64,5.58,8.76 -rexnetr_130,5459.44,187.553,1024,224,0.68,9.81,7.61 -tf_efficientnet_es,5422.9,188.816,1024,224,1.81,8.73,5.44 -tf_efficientnet_lite1,5355.71,191.185,1024,240,0.62,10.14,5.42 -selecsls60,5268.65,194.344,1024,224,3.59,5.52,30.67 -selecsls60b,5252.65,194.936,1024,224,3.63,5.52,32.77 -mobilenetv2_120d,5162.92,198.325,1024,224,0.69,11.97,5.83 -repvgg_b0,5052.09,202.677,1024,224,3.41,6.15,15.82 -resnet26d,4922.38,208.017,1024,224,2.6,8.15,16.01 -fbnetv3_d,4802.31,213.218,1024,256,0.68,11.1,10.31 -xcit_nano_12_p16_224,4773.0,214.528,1024,224,0.56,4.17,3.05 -rexnetr_150,4769.15,214.701,1024,224,0.89,11.13,9.78 -xcit_nano_12_p16_224_dist,4764.08,214.929,1024,224,0.56,4.17,3.05 -vit_tiny_patch16_224,4754.4,215.366,1024,224,1.26,5.97,5.72 -deit_tiny_patch16_224,4742.21,215.918,1024,224,1.26,5.97,5.72 -nf_resnet26,4720.75,216.903,1024,224,2.41,7.35,16.0 -visformer_tiny,4686.07,218.507,1024,224,1.27,5.72,10.32 -deit_tiny_distilled_patch16_224,4682.4,218.676,1024,224,1.27,6.01,5.91 -efficientnet_lite2,4622.9,221.493,1024,260,0.89,12.9,6.09 -pit_ti_distilled_224,4461.94,229.484,1024,224,0.71,6.23,5.1 -pit_ti_224,4451.07,230.044,1024,224,0.7,6.19,4.85 -resmlp_12_distilled_224,4424.39,231.432,1024,224,3.01,5.5,15.35 -resmlp_12_224,4422.97,231.507,1024,224,3.01,5.5,15.35 -tf_efficientnetv2_b2,4364.43,234.612,1024,260,1.72,9.84,10.1 -efficientnet_b0_g16_evos,4258.95,240.422,1024,224,1.01,7.42,8.11 -tf_efficientnet_b1_ap,4209.48,243.247,1024,240,0.71,10.88,7.79 -tf_efficientnet_b1,4206.94,243.394,1024,240,0.71,10.88,7.79 -tf_efficientnet_b1_ns,4206.45,243.423,1024,240,0.71,10.88,7.79 -gernet_l,4203.4,243.6,1024,256,4.57,8.0,31.08 -legacy_seresnext26_32x4d,4195.67,244.05,1024,224,2.49,9.39,16.79 -tf_efficientnet_lite2,4152.0,246.616,1024,260,0.89,12.9,6.09 -resnext26ts,4093.42,250.143,1024,256,2.43,10.52,10.3 -efficientnet_b1,4070.65,251.545,1024,256,0.77,12.22,7.79 -mixer_b32_224,4051.68,252.722,1024,224,3.24,6.29,60.29 -vit_base_patch32_224_sam,4039.13,253.507,1024,224,4.41,5.01,88.22 -vit_base_patch32_224,4032.31,253.936,1024,224,4.41,5.01,88.22 -rexnet_130,3995.13,256.299,1024,224,0.68,9.71,7.56 -nf_seresnet26,3989.88,256.637,1024,224,2.41,7.36,17.4 -nf_ecaresnet26,3979.77,257.29,1024,224,2.41,7.36,16.0 -seresnext26ts,3962.63,258.399,1024,256,2.43,10.52,10.39 -eca_resnext26ts,3962.0,258.443,1024,256,2.43,10.52,10.3 -repvgg_a2,3879.7,263.924,1024,224,5.7,6.26,28.21 -resnet26t,3812.96,268.545,1024,256,3.35,10.52,16.01 -regnetx_016,3789.45,270.213,1024,224,1.62,7.93,9.19 -gcresnext26ts,3774.22,271.302,1024,256,2.43,10.53,10.48 -efficientnet_b2_pruned,3765.97,271.895,1024,260,0.73,9.13,8.31 -mobilevit_xxs,3756.03,272.615,1024,256,0.42,8.34,1.27 -seresnext26t_32x4d,3753.45,272.802,1024,224,2.7,10.09,16.81 -rexnet_150,3752.67,272.86,1024,224,0.9,11.21,9.73 -seresnext26tn_32x4d,3752.12,272.899,1024,224,2.7,10.09,16.81 -seresnext26d_32x4d,3746.32,273.322,1024,224,2.73,10.19,16.81 -ecaresnext50t_32x4d,3742.01,273.637,1024,224,2.7,10.09,15.41 -ecaresnext26t_32x4d,3741.38,273.685,1024,224,2.7,10.09,15.41 -resnetv2_50,3727.11,274.73,1024,224,4.11,11.11,25.55 -ecaresnet50d_pruned,3716.52,275.512,1024,224,2.53,6.43,19.94 -eca_botnext26ts_256,3657.01,279.998,1024,256,2.46,11.6,10.59 -pit_xs_224,3649.08,280.606,1024,224,1.4,7.71,10.62 -mixer_s16_224,3636.18,281.601,1024,224,3.79,5.97,18.53 -pit_xs_distilled_224,3615.14,283.241,1024,224,1.41,7.76,11.0 -ecaresnetlight,3578.86,286.112,1024,224,4.11,8.42,30.16 -gluon_resnet50_v1b,3553.85,288.125,1024,224,4.11,11.11,25.56 -eca_halonext26ts,3546.67,288.71,1024,256,2.44,11.46,10.76 -swsl_resnet50,3546.19,288.748,1024,224,4.11,11.11,25.56 -tv_resnet50,3545.52,288.801,1024,224,4.11,11.11,25.56 -ssl_resnet50,3545.14,288.833,1024,224,4.11,11.11,25.56 -resnet50,3544.26,288.904,1024,224,4.11,11.11,25.56 -poolformer_s12,3517.37,291.113,1024,224,1.82,5.53,11.92 -rexnetr_200,3507.94,145.944,512,224,1.59,15.11,16.52 -dla46_c,3470.52,295.04,1024,224,0.58,4.5,1.3 -efficientnet_em,3446.66,297.086,1024,240,3.04,14.34,6.9 -resnet32ts,3441.99,297.489,1024,256,4.63,11.58,17.96 -dpn68,3441.53,297.53,1024,224,2.35,10.47,12.61 -dpn68b,3424.64,298.997,1024,224,2.35,10.47,12.61 -botnet26t_256,3414.09,299.918,1024,256,3.32,11.98,12.49 -regnety_016,3396.79,301.447,1024,224,1.63,8.04,11.2 -xcit_tiny_12_p16_224_dist,3391.79,301.892,1024,224,1.24,6.29,6.72 -resnet33ts,3389.22,302.122,1024,256,4.76,11.66,19.68 -xcit_tiny_12_p16_224,3388.8,302.158,1024,224,1.24,6.29,6.72 -nf_regnet_b1,3376.64,303.248,1024,288,1.02,9.2,10.22 -resnetv2_50t,3372.1,303.654,1024,224,4.32,11.82,25.57 -resnetv2_50d,3370.23,303.824,1024,224,4.35,11.92,25.57 -gluon_resnet50_v1c,3357.28,304.996,1024,224,4.35,11.92,25.58 -nf_regnet_b2,3357.15,305.008,1024,272,1.22,9.27,14.31 -halonet26t,3341.01,306.482,1024,256,3.19,11.69,12.48 -gmixer_12_224,3331.74,307.335,1024,224,2.67,7.26,12.7 -tf_efficientnet_em,3315.19,308.867,1024,240,3.04,14.34,6.9 -skresnet34,3309.87,309.366,1024,224,3.67,5.13,22.28 -seresnet33ts,3273.95,312.759,1024,256,4.76,11.66,19.78 -tf_efficientnet_b2,3269.65,313.17,1024,260,1.02,13.83,9.11 -eca_resnet33ts,3266.95,313.43,1024,256,4.76,11.66,19.68 -tf_efficientnet_b2_ns,3265.96,313.524,1024,260,1.02,13.83,9.11 -tf_efficientnet_b2_ap,3265.24,313.594,1024,260,1.02,13.83,9.11 -vit_small_patch32_384,3261.97,313.907,1024,384,3.45,8.25,22.92 -resnet50t,3224.3,317.574,1024,224,4.32,11.82,25.57 -gluon_resnet50_v1d,3223.07,317.695,1024,224,4.35,11.92,25.58 -bat_resnext26ts,3219.21,318.076,1024,256,2.53,12.51,10.73 -resnet50d,3219.13,318.085,1024,224,4.35,11.92,25.58 -legacy_seresnet50,3183.45,321.65,1024,224,3.88,10.6,28.09 -convnext_nano_hnf,3142.93,325.795,1024,224,2.45,8.37,15.59 -gcresnet33ts,3109.78,329.272,1024,256,4.76,11.68,19.88 -vovnet39a,3106.34,329.636,1024,224,7.09,6.73,22.6 -efficientnet_b2,3086.88,331.715,1024,288,1.12,16.2,9.11 -efficientnet_b2a,3085.38,331.876,1024,288,1.12,16.2,9.11 -seresnet50,3063.5,334.246,1024,224,4.11,11.13,28.09 -efficientnet_b3_pruned,3061.51,334.462,1024,300,1.04,11.86,9.86 -vit_small_resnet26d_224,3015.3,339.587,1024,224,5.07,11.12,63.61 -ese_vovnet39b,2994.81,341.913,1024,224,7.09,6.74,24.57 -res2net50_48w_2s,2988.95,342.583,1024,224,4.18,11.72,25.29 -cspresnext50,2987.05,342.799,1024,224,3.1,12.14,20.57 -haloregnetz_b,2983.57,343.199,1024,224,1.97,11.94,11.68 -eca_vovnet39b,2981.18,343.475,1024,224,7.09,6.74,22.6 -selecsls84,2979.85,343.628,1024,224,5.9,7.57,50.95 -tv_resnext50_32x4d,2888.51,354.496,1024,224,4.26,14.4,25.03 -swsl_resnext50_32x4d,2887.95,354.564,1024,224,4.26,14.4,25.03 -gluon_resnext50_32x4d,2886.69,354.718,1024,224,4.26,14.4,25.03 -resnetaa50d,2886.21,354.778,1024,224,5.39,12.44,25.58 -resnext50_32x4d,2882.66,355.215,1024,224,4.26,14.4,25.03 -ssl_resnext50_32x4d,2874.35,356.241,1024,224,4.26,14.4,25.03 -mixnet_s,2870.58,356.71,1024,224,0.25,6.25,4.13 -tv_densenet121,2868.5,356.969,1024,224,2.87,6.9,7.98 -densenet121,2859.93,358.034,1024,224,2.87,6.9,7.98 -crossvit_tiny_240,2844.98,359.92,1024,240,1.57,9.08,7.01 -gluon_resnet50_v1s,2839.32,360.638,1024,224,5.47,13.52,25.68 -resnetrs50,2835.76,361.089,1024,224,4.48,12.14,35.69 -ecaresnet101d_pruned,2830.74,361.73,1024,224,3.48,7.69,24.88 -seresnet50t,2823.21,362.695,1024,224,4.32,11.83,28.1 -ecaresnet50d,2805.68,364.961,1024,224,4.35,11.93,25.58 -rexnet_200,2798.14,182.968,512,224,1.56,14.91,16.37 -dla34,2784.38,367.75,1024,224,3.07,5.02,15.74 -crossvit_9_240,2767.15,370.043,1024,240,1.85,9.52,8.55 -dla46x_c,2763.35,370.549,1024,224,0.54,5.66,1.07 -hrnet_w18_small_v2,2753.44,371.885,1024,224,2.62,9.65,15.6 -cspresnet50,2747.09,372.74,1024,256,4.54,11.5,21.62 -densenet121d,2731.42,374.878,1024,224,3.11,7.7,8.0 -tf_mixnet_s,2728.95,375.223,1024,224,0.25,6.25,4.13 -crossvit_9_dagger_240,2727.58,375.412,1024,240,1.99,9.97,8.78 -convit_tiny,2724.97,375.771,1024,224,1.26,7.94,5.71 -efficientnet_lite3,2724.75,187.896,512,300,1.65,21.85,8.2 -regnetz_b16,2699.0,379.388,1024,288,2.39,16.43,9.72 -dla60x_c,2695.93,379.816,1024,224,0.59,6.01,1.32 -resnext50d_32x4d,2662.94,384.525,1024,224,4.5,15.2,25.05 -resnetblur50,2614.02,391.72,1024,224,5.16,12.02,25.56 -vgg11_bn,2605.49,196.497,512,224,7.62,7.44,132.87 -gmlp_ti16_224,2595.56,394.507,1024,224,1.34,7.55,5.87 -cspresnet50d,2589.51,395.427,1024,256,4.86,12.55,21.64 -cspresnet50w,2569.03,398.577,1024,256,5.04,12.19,28.12 -legacy_seresnext50_32x4d,2559.94,399.996,1024,224,4.26,14.42,27.56 -seresnext50_32x4d,2557.01,400.454,1024,224,4.26,14.42,27.56 -seresnetaa50d,2555.76,400.65,1024,224,5.4,12.46,28.11 -gluon_seresnext50_32x4d,2554.83,400.796,1024,224,4.26,14.42,27.56 -vovnet57a,2541.91,402.835,1024,224,8.95,7.52,36.64 -res2net50_26w_4s,2528.48,404.972,1024,224,4.28,12.61,25.7 -fbnetv3_g,2526.11,405.353,1024,288,1.77,21.09,16.62 -gcresnet50t,2519.53,406.409,1024,256,5.42,14.67,25.9 -mobilevit_xs,2517.79,203.342,512,256,1.05,16.33,2.32 -efficientnetv2_rw_t,2509.76,407.994,1024,288,3.19,16.42,13.65 -tf_efficientnetv2_b3,2477.2,413.357,1024,300,3.04,15.74,14.36 -ese_vovnet57b,2451.87,417.628,1024,224,8.95,7.52,38.61 -vit_base2_patch32_256,2444.79,418.837,1024,256,7.79,7.76,119.46 -densenetblur121d,2444.27,418.923,1024,224,3.11,7.9,8.0 -tf_efficientnet_lite3,2442.3,209.627,512,300,1.65,21.85,8.2 -vit_tiny_r_s16_p8_384,2438.04,209.992,512,384,1.34,6.49,6.36 -vit_small_patch16_224,2432.98,420.87,1024,224,4.61,11.95,22.05 -resnetblur50d,2432.25,420.996,1024,224,5.4,12.82,25.58 -deit_small_patch16_224,2428.96,421.564,1024,224,4.61,11.95,22.05 -nf_seresnet50,2416.51,423.739,1024,224,4.21,11.13,28.09 -nf_ecaresnet50,2408.03,425.23,1024,224,4.21,11.13,25.56 -inception_v3,2407.94,425.243,1024,299,5.73,8.97,23.83 -tf_inception_v3,2403.0,426.12,1024,299,5.73,8.97,23.83 -pit_s_224,2400.22,426.615,1024,224,2.88,11.56,23.46 -adv_inception_v3,2396.39,427.291,1024,299,5.73,8.97,23.83 -deit_small_distilled_patch16_224,2393.24,427.856,1024,224,4.63,12.02,22.44 -gluon_inception_v3,2390.99,428.257,1024,299,5.73,8.97,23.83 -pit_s_distilled_224,2380.56,430.136,1024,224,2.9,11.64,24.04 -vit_base_resnet26d_224,2375.02,431.141,1024,224,6.97,13.16,101.4 -resnest14d,2369.9,432.072,1024,224,2.76,7.33,10.61 -lambda_resnet26rpt_256,2366.95,216.301,512,256,3.16,11.87,10.99 -densenet169,2363.13,433.308,1024,224,3.4,7.3,14.15 -skresnet50,2341.67,437.282,1024,224,4.11,12.5,25.8 -gc_efficientnetv2_rw_t,2301.92,444.832,1024,288,3.2,16.45,13.68 -res2net50_14w_8s,2274.27,450.241,1024,224,4.21,13.28,25.06 -gcresnext50ts,2273.63,450.365,1024,256,3.75,15.46,15.67 -sehalonet33ts,2269.0,225.638,512,256,3.55,14.7,13.69 -resmlp_24_224,2264.75,452.133,1024,224,5.96,10.91,30.02 -resmlp_24_distilled_224,2264.4,452.202,1024,224,5.96,10.91,30.02 -darknet53,2257.9,226.743,512,256,9.31,12.39,41.61 -resnetv2_101,2240.07,457.113,1024,224,7.83,16.23,44.54 -skresnet50d,2193.77,466.762,1024,224,4.36,13.31,25.82 -gluon_resnet101_v1b,2175.78,470.623,1024,224,7.83,16.23,44.55 -tv_resnet101,2173.0,471.223,1024,224,7.83,16.23,44.55 -resnet101,2169.86,471.907,1024,224,7.83,16.23,44.55 -res2next50,2165.07,472.951,1024,224,4.2,13.71,24.67 -nf_regnet_b3,2142.11,478.019,1024,320,2.05,14.61,18.59 -ecaresnet26t,2130.22,480.685,1024,320,5.24,16.44,16.01 -resnetv2_101d,2102.02,487.136,1024,224,8.07,17.04,44.56 -gluon_resnet101_v1c,2099.96,487.615,1024,224,8.08,17.04,44.57 -dla60,2086.09,490.853,1024,224,4.26,10.16,22.04 -gluon_resnet101_v1d,2048.54,499.853,1024,224,8.08,17.04,44.57 -vgg13,2036.07,502.915,1024,224,11.31,12.25,133.05 -convnext_tiny_hnf,2032.23,503.867,1024,224,4.47,13.44,28.59 -mobilevit_s,2031.79,251.983,512,256,2.03,19.94,5.58 -wide_resnet50_2,2003.76,511.025,1024,224,11.43,14.4,68.88 -efficientnet_b0_gn,1990.83,257.167,512,224,0.42,6.75,5.29 -repvgg_b1,1937.46,528.514,1024,224,13.16,10.64,57.42 -sebotnet33ts_256,1925.17,199.45,384,256,3.89,17.46,13.7 -legacy_seresnet101,1920.98,533.049,1024,224,7.61,15.74,49.33 -resnetaa101d,1902.88,538.118,1024,224,9.12,17.56,44.57 -semobilevit_s,1901.2,269.292,512,256,2.03,19.95,5.74 -dla60x,1896.63,539.888,1024,224,3.54,13.8,17.35 -vit_base_resnet50d_224,1891.44,541.372,1024,224,8.73,16.92,110.97 -gluon_resnet101_v1s,1885.09,543.196,1024,224,9.19,18.64,44.67 -resnet51q,1880.5,544.522,1024,288,8.07,20.94,35.7 -seresnet101,1876.16,545.782,1024,224,7.84,16.27,49.33 -tf_efficientnet_b3_ns,1869.48,273.862,512,300,1.87,23.83,12.23 -tf_efficientnet_b3,1867.21,274.194,512,300,1.87,23.83,12.23 -tf_efficientnet_b3_ap,1867.02,274.222,512,300,1.87,23.83,12.23 -coat_lite_tiny,1852.39,552.786,1024,224,1.6,11.65,5.72 -efficientnet_b3,1838.85,278.423,512,320,2.01,26.52,12.23 -efficientnet_b3a,1837.41,278.642,512,320,2.01,26.52,12.23 -poolformer_s24,1826.45,560.637,1024,224,3.41,10.68,21.39 -densenet201,1819.15,562.883,1024,224,4.34,7.85,20.01 -xcit_tiny_24_p16_224_dist,1814.23,564.411,1024,224,2.34,11.82,12.12 -nf_resnet101,1807.6,566.485,1024,224,8.01,16.23,44.55 -xcit_tiny_24_p16_224,1806.45,566.843,1024,224,2.34,11.82,12.12 -cspdarknet53,1800.59,284.34,512,256,6.57,16.81,27.64 -resnext101_32x4d,1797.78,569.576,1024,224,8.01,21.23,44.18 -ssl_resnext101_32x4d,1797.66,569.615,1024,224,8.01,21.23,44.18 -swsl_resnext101_32x4d,1795.39,570.337,1024,224,8.01,21.23,44.18 -gluon_resnext101_32x4d,1793.08,571.07,1024,224,8.01,21.23,44.18 -xcit_small_12_p16_224_dist,1789.93,572.076,1024,224,4.82,12.58,26.25 -xcit_small_12_p16_224,1789.28,572.284,1024,224,4.82,12.58,26.25 -halonet50ts,1788.45,572.549,1024,256,5.3,19.2,22.73 -res2net50_26w_6s,1775.31,576.783,1024,224,6.33,15.28,37.05 -coat_lite_mini,1771.74,577.95,1024,224,2.0,12.25,11.01 -ecaresnet101d,1771.55,578.01,1024,224,8.08,17.07,44.57 -convnext_tiny_hnfd,1758.43,582.323,1024,224,4.78,14.64,28.63 -regnetz_c16,1753.5,291.974,512,320,3.92,25.88,13.46 -nf_resnet50,1751.0,584.795,1024,288,6.88,18.37,25.56 -dla60_res2net,1735.18,590.122,1024,224,4.15,12.34,20.85 -convnext_tiny,1731.03,591.541,1024,224,4.47,13.44,28.59 -resnest26d,1730.95,591.569,1024,224,3.64,9.97,17.07 -vit_small_r26_s32_224,1710.8,598.536,1024,224,3.56,9.85,36.43 -gmixer_24_224,1701.15,601.933,1024,224,5.28,14.45,24.72 -resnetblur101d,1698.79,602.767,1024,224,9.12,17.94,44.57 -resnet61q,1686.77,607.063,1024,288,9.87,21.52,36.85 -vgg13_bn,1654.93,309.368,512,224,11.33,12.25,133.05 -vgg16,1643.23,623.151,1024,224,15.47,13.56,138.36 -xcit_nano_12_p16_384_dist,1641.55,623.788,1024,384,1.64,12.15,3.05 -efficientnet_b0_g8_gn,1622.56,315.54,512,224,0.66,6.75,6.56 -repvgg_b1g4,1617.36,633.118,1024,224,8.15,10.64,39.97 -regnetx_032,1612.7,634.945,1024,224,3.2,11.37,15.3 -resnetv2_50d_frn,1611.81,635.295,1024,224,4.33,11.92,25.59 -res2net101_26w_4s,1600.73,639.694,1024,224,8.1,18.45,45.21 -regnetx_040,1592.21,643.119,1024,224,3.99,12.2,22.12 -legacy_seresnext101_32x4d,1591.58,643.374,1024,224,8.02,21.26,48.96 -seresnext101_32x4d,1590.99,643.61,1024,224,8.02,21.26,48.96 -gluon_seresnext101_32x4d,1588.09,644.785,1024,224,8.02,21.26,48.96 -twins_svt_small,1586.89,645.273,1024,224,2.94,13.75,24.06 -ese_vovnet39b_evos,1567.33,653.327,1024,224,7.07,6.74,24.58 -xception41p,1557.52,328.715,512,299,9.25,39.86,26.91 -visformer_small,1553.17,659.284,1024,224,4.88,11.43,40.22 -hrnet_w32,1550.18,660.555,1024,224,8.97,22.02,41.23 -resnetv2_152,1549.71,660.755,1024,224,11.55,22.56,60.19 -dla60_res2next,1549.6,660.797,1024,224,3.49,13.17,17.03 -resnetv2_50d_evob,1548.76,661.162,1024,224,4.33,11.92,25.59 -resnest50d_1s4x24d,1548.3,661.358,1024,224,4.43,13.57,25.68 -xception,1544.37,331.513,512,299,8.4,35.83,22.86 -botnet50ts_256,1543.72,331.651,512,256,5.54,22.23,22.74 -dla102,1543.56,663.384,1024,224,7.19,14.18,33.27 -resnetv2_50x1_bit_distilled,1536.12,666.602,1024,224,4.23,11.11,25.55 -crossvit_small_240,1535.71,666.778,1024,240,5.63,18.17,26.86 -gluon_resnet152_v1b,1521.2,673.136,1024,224,11.56,22.56,60.19 -resmlp_36_224,1519.99,673.674,1024,224,8.91,16.33,44.69 -tv_resnet152,1519.51,673.886,1024,224,11.56,22.56,60.19 -resmlp_36_distilled_224,1519.32,673.971,1024,224,8.91,16.33,44.69 -resnet152,1516.8,675.093,1024,224,11.56,22.56,60.19 -efficientnet_el_pruned,1511.43,338.74,512,300,8.0,30.7,10.59 -efficientnet_el,1502.87,340.669,512,300,8.0,30.7,10.59 -res2net50_26w_8s,1500.5,682.425,1024,224,8.37,17.95,48.4 -nf_seresnet101,1495.3,684.796,1024,224,8.02,16.27,49.33 -nf_ecaresnet101,1488.87,687.754,1024,224,8.01,16.27,44.55 -resnetv2_152d,1485.92,689.12,1024,224,11.8,23.36,60.2 -gluon_resnet152_v1c,1482.34,690.787,1024,224,11.8,23.36,60.21 -halo2botnet50ts_256,1478.01,692.809,1024,256,5.02,21.78,22.64 -tf_efficientnet_el,1462.97,349.96,512,300,8.0,30.7,10.59 -gluon_resnet152_v1d,1456.19,703.189,1024,224,11.8,23.36,60.21 -mixnet_m,1441.42,710.398,1024,224,0.36,8.19,5.01 -gmlp_s16_224,1435.92,713.117,1024,224,4.42,15.1,19.42 -hrnet_w18,1435.25,713.441,1024,224,4.32,16.31,21.3 -vit_large_patch32_224,1434.56,713.791,1024,224,15.39,13.3,306.54 -dla102x,1422.48,719.854,1024,224,5.89,19.42,26.31 -tf_mixnet_m,1407.14,727.704,1024,224,0.36,8.19,5.01 -vit_base_r26_s32_224,1405.74,728.426,1024,224,6.81,12.36,101.38 -crossvit_15_240,1405.36,728.622,1024,240,5.81,19.77,27.53 -mixer_b16_224,1393.37,734.893,1024,224,12.62,14.53,59.88 -cait_xxs24_224,1391.6,735.832,1024,224,2.53,20.29,11.96 -mixer_b16_224_miil,1391.59,735.836,1024,224,12.62,14.53,59.88 -mixer_l32_224,1381.87,741.013,1024,224,11.27,19.86,206.94 -vgg19,1378.09,743.046,1024,224,19.63,14.86,143.67 -ecaresnet50t,1376.72,743.784,1024,320,8.82,24.13,25.57 -crossvit_15_dagger_240,1372.92,745.84,1024,240,6.13,20.43,28.21 -gluon_resnet152_v1s,1372.05,746.315,1024,224,12.92,24.96,60.32 -vgg16_bn,1370.07,373.69,512,224,15.5,13.56,138.37 -regnety_032,1366.08,749.575,1024,288,5.29,18.61,19.44 -skresnext50_32x4d,1361.83,751.915,1024,224,4.5,17.18,27.48 -ese_vovnet99b,1355.58,755.384,1024,224,16.51,11.27,63.2 -xception41,1339.87,382.115,512,299,9.28,39.86,26.97 -legacy_seresnet152,1328.26,770.919,1024,224,11.33,22.08,66.82 -dpn92,1311.48,780.784,1024,224,6.54,18.21,37.67 -seresnet152,1304.92,784.709,1024,224,11.57,22.61,66.82 -vit_base_patch32_384,1292.62,792.174,1024,384,13.06,16.5,88.3 -efficientnet_lite4,1290.99,297.435,384,380,4.04,45.66,13.01 -inception_v4,1286.59,795.889,1024,299,12.28,15.09,42.68 -swin_tiny_patch4_window7_224,1284.81,796.991,1024,224,4.51,17.06,28.29 -tresnet_m,1280.32,799.79,1024,224,5.74,7.31,31.39 -densenet161,1276.37,802.258,1024,224,7.79,11.06,28.68 -twins_pcpvt_small,1273.73,803.927,1024,224,3.83,18.08,24.11 -regnetx_080,1262.29,811.211,1024,224,8.02,14.06,39.57 -convit_small,1252.96,817.253,1024,224,5.76,17.87,27.78 -repvgg_b2,1245.13,822.392,1024,224,20.45,12.9,89.02 -xcit_nano_12_p8_224_dist,1241.05,825.093,1024,224,2.16,15.71,3.05 -xcit_nano_12_p8_224,1238.63,826.705,1024,224,2.16,15.71,3.05 -poolformer_s36,1233.24,830.321,1024,224,5.0,15.82,30.86 -hrnet_w30,1225.12,835.817,1024,224,8.15,21.21,37.71 -swin_s3_tiny_224,1200.23,853.151,1024,224,4.64,19.13,28.33 -vit_tiny_patch16_384,1196.63,855.72,1024,384,4.7,25.39,5.79 -vit_small_resnet50d_s16_224,1187.59,862.229,1024,224,13.48,24.82,57.53 -tf_efficientnet_lite4,1185.79,323.823,384,380,4.04,45.66,13.01 -resnest50d,1179.24,868.341,1024,224,5.4,14.36,27.48 -vgg19_bn,1171.24,437.132,512,224,19.66,14.86,143.68 -regnetx_064,1170.17,437.532,512,224,6.49,16.37,26.21 -nf_regnet_b4,1167.32,877.209,1024,384,4.7,28.61,30.21 -xcit_tiny_12_p16_384_dist,1163.91,879.777,1024,384,3.64,18.26,6.72 -efficientnetv2_s,1144.22,894.92,1024,384,8.44,35.77,21.46 -dla169,1134.2,902.821,1024,224,11.6,20.2,53.39 -regnetz_d8,1133.56,903.33,1024,320,6.19,37.08,23.37 -wide_resnet101_2,1128.84,907.11,1024,224,22.8,21.23,126.89 -gluon_resnext101_64x4d,1125.42,909.866,1024,224,15.52,31.21,83.46 -convnext_small,1123.49,911.428,1024,224,8.7,21.56,50.22 -xception65p,1116.94,458.382,512,299,13.91,52.48,39.82 -mixnet_l,1114.32,459.458,512,224,0.58,10.84,7.33 -resnet50_gn,1113.26,919.804,1024,224,4.14,11.11,25.56 -eca_nfnet_l0,1110.51,922.082,1024,288,7.12,17.29,24.14 -tf_efficientnetv2_s_in21ft1k,1107.38,924.691,1024,384,8.44,35.77,21.46 -nfnet_l0,1107.03,924.983,1024,288,7.13,17.29,35.07 -tf_efficientnetv2_s,1106.17,925.705,1024,384,8.44,35.77,21.46 -resnet200,1102.75,928.576,1024,224,15.07,32.19,64.67 -dpn98,1102.66,928.653,1024,224,11.73,25.2,61.57 -swin_v2_cr_tiny_224,1099.27,931.506,1024,224,4.66,30.64,28.33 -tf_mixnet_l,1097.03,466.699,512,224,0.58,10.84,7.33 -resnetrs101,1091.82,937.873,1024,288,13.56,28.53,63.62 -efficientnetv2_rw_s,1077.94,949.947,1024,384,8.72,38.03,23.94 -ens_adv_inception_resnet_v2,1069.64,957.319,1024,299,13.18,25.06,55.84 -inception_resnet_v2,1067.04,959.647,1024,299,13.18,25.06,55.84 -volo_d1_224,1051.19,974.121,1024,224,6.94,24.43,26.63 -coat_lite_small,1050.15,975.08,1024,224,3.96,22.09,19.84 -nest_tiny,1050.07,487.574,512,224,5.83,25.48,17.06 -dla102x2,1042.76,490.987,512,224,9.34,29.91,41.28 -swin_v2_cr_tiny_ns_224,1041.51,983.175,1024,224,4.66,30.64,28.33 -gluon_seresnext101_64x4d,1039.57,985.01,1024,224,15.53,31.25,88.23 -jx_nest_tiny,1035.76,494.311,512,224,5.83,25.48,17.06 -ssl_resnext101_32x8d,1034.73,989.616,1024,224,16.48,31.21,88.79 -ig_resnext101_32x8d,1034.2,990.121,1024,224,16.48,31.21,88.79 -regnetz_040,1033.76,371.447,384,320,6.35,37.78,27.12 -swsl_resnext101_32x8d,1032.69,991.574,1024,224,16.48,31.21,88.79 -crossvit_18_240,1032.44,991.813,1024,240,9.05,26.26,43.27 -resnext101_32x8d,1032.2,992.04,1024,224,16.48,31.21,88.79 -vit_base_patch16_224_miil,1029.44,994.703,1024,224,17.58,23.9,86.54 -regnetz_040h,1028.74,373.26,384,320,6.43,37.94,28.94 -crossvit_18_dagger_240,1009.42,1014.425,1024,240,9.5,27.03,44.27 -deit_base_patch16_224,1007.07,1016.797,1024,224,17.58,23.9,86.57 -repvgg_b3,1006.51,1017.356,1024,224,29.16,15.1,123.09 -regnetz_d32,1003.93,1019.976,1024,320,9.33,37.08,27.58 -resnet101d,1003.08,1020.84,1024,320,16.48,34.77,44.57 -vit_base_patch16_224,1001.4,1022.55,1024,224,17.58,23.9,86.57 -vit_base_patch16_224_sam,1001.03,1022.936,1024,224,17.58,23.9,86.57 -deit_base_distilled_patch16_224,991.69,1032.561,1024,224,17.68,24.05,87.34 -hrnet_w40,985.45,1039.098,1024,224,12.75,25.29,57.56 -resnest50d_4s2x40d,982.63,1042.082,1024,224,4.4,17.94,30.42 -gluon_xception65,976.14,524.501,512,299,13.96,52.48,39.92 -xception65,967.24,529.329,512,299,13.96,52.48,39.92 -efficientnet_b4,965.42,397.741,384,384,4.51,50.04,19.34 -xcit_small_24_p16_224_dist,951.37,1076.325,1024,224,9.1,23.64,47.67 -xcit_small_24_p16_224,950.22,1077.629,1024,224,9.1,23.64,47.67 -cait_xxs36_224,935.04,1095.127,1024,224,3.77,30.34,17.3 -twins_pcpvt_base,931.12,1099.735,1024,224,6.68,25.25,43.83 -beit_base_patch16_224,922.95,1109.472,1024,224,17.58,23.9,86.53 -twins_svt_base,918.68,1114.635,1024,224,8.59,26.33,56.07 -regnetz_b16_evos,915.33,559.349,512,288,2.36,16.43,9.74 -tf_efficientnet_b4,914.19,420.029,384,380,4.49,49.49,19.34 -tf_efficientnet_b4_ap,913.49,420.352,384,380,4.49,49.49,19.34 -tf_efficientnet_b4_ns,913.14,420.511,384,380,4.49,49.49,19.34 -hrnet_w48,884.3,1157.963,1024,224,17.34,28.56,77.47 -xcit_tiny_12_p8_224_dist,876.78,1167.888,1024,224,4.81,23.6,6.71 -xcit_tiny_12_p8_224,875.61,1169.457,1024,224,4.81,23.6,6.71 -pit_b_224,856.55,597.735,512,224,12.42,32.94,73.76 -pit_b_distilled_224,853.55,599.838,512,224,12.5,33.07,74.79 -poolformer_m36,851.1,1203.131,1024,224,8.8,22.02,56.17 -regnetv_040,850.32,602.11,512,288,6.6,20.3,20.64 -regnety_040,849.8,602.48,512,288,6.61,20.3,20.65 -nfnet_f0,847.6,1208.099,1024,256,12.62,18.05,71.49 -swin_small_patch4_window7_224,843.82,1213.517,1024,224,8.77,27.47,49.61 -convnext_base,830.25,1233.341,1024,224,15.38,28.75,88.59 -convnext_small_in22ft1k,830.17,1233.46,1024,224,15.38,28.75,88.59 -convnext_tiny_in22ft1k,829.7,1234.165,1024,224,15.38,28.75,88.59 -convnext_base_in22ft1k,829.03,1235.157,1024,224,15.38,28.75,88.59 -repvgg_b2g4,814.15,1257.742,1024,224,12.63,12.9,61.76 -dpn131,812.55,1260.217,1024,224,16.09,32.97,79.25 -resnetv2_50d_evos,809.41,1265.096,1024,288,7.15,19.7,25.59 -hrnet_w44,795.23,1287.667,1024,224,14.94,26.92,67.06 -vit_small_patch16_36x1_224,784.17,1305.822,1024,224,13.71,35.69,64.67 -regnetx_120,781.81,654.877,512,224,12.13,21.37,46.11 -cait_s24_224,780.6,1311.795,1024,224,9.35,40.58,46.92 -vit_small_patch16_18x2_224,769.43,1330.841,1024,224,13.71,35.69,64.67 -dm_nfnet_f0,760.88,1345.793,1024,256,12.62,18.05,71.49 -densenet264,753.79,1358.443,1024,224,12.95,12.8,72.69 -regnety_120,753.56,679.427,512,224,12.14,21.38,51.82 -mixnet_xl,753.01,679.926,512,224,0.93,14.57,11.9 -xception71,742.19,689.834,512,299,18.09,69.92,42.34 -hrnet_w64,727.09,1408.333,1024,224,28.97,35.09,128.06 -resnetv2_50d_gn,725.28,705.917,512,288,7.24,19.7,25.57 -coat_tiny,723.65,1415.036,1024,224,4.35,27.2,5.5 -resnet152d,715.97,1430.207,1024,320,24.08,47.67,60.21 -swin_v2_cr_small_224,712.21,1437.764,1024,224,9.08,53.85,49.7 -seresnet200d,707.7,1446.92,1024,256,20.01,43.15,71.86 -regnety_040s_gn,707.19,723.977,512,224,4.03,12.29,20.65 -dpn107,704.9,1452.679,1024,224,18.38,33.46,86.92 -ecaresnet200d,704.84,1452.788,1024,256,20.0,43.15,64.69 -nest_small,704.83,726.402,512,224,10.35,40.04,38.35 -vit_large_r50_s32_224,700.71,1461.355,1024,224,19.58,24.41,328.99 -twins_svt_large,699.68,1463.514,1024,224,15.15,35.1,99.27 -jx_nest_small,698.3,733.197,512,224,10.35,40.04,38.35 -cspresnext50_iabn,694.07,1475.332,1024,256,4.02,15.86,20.57 -xcit_medium_24_p16_224_dist,693.66,1476.222,1024,224,16.13,31.71,84.4 -xcit_medium_24_p16_224,693.5,1476.544,1024,224,16.13,31.71,84.4 -gmlp_b16_224,692.91,1477.808,1024,224,15.78,30.21,73.08 -legacy_senet154,690.74,1482.459,1024,224,20.77,38.69,115.09 -senet154,689.84,1484.377,1024,224,20.77,38.69,115.09 -gluon_senet154,689.77,1484.531,1024,224,20.77,38.69,115.09 -crossvit_base_240,684.4,748.083,512,240,21.22,36.33,105.03 -twins_pcpvt_large,680.47,1504.817,1024,224,9.84,35.82,60.99 -resnext101_64x4d,666.45,768.234,512,288,25.66,51.59,83.46 -swin_s3_small_224,656.61,779.751,512,224,9.43,37.84,49.74 -convit_base,655.73,1561.612,1024,224,17.52,31.77,86.54 -repvgg_b3g4,646.31,1584.364,1024,224,17.89,15.1,83.83 -poolformer_m48,642.41,1593.977,1024,224,11.59,29.17,73.47 -tresnet_l,639.72,1600.689,1024,224,10.88,11.9,55.99 -swin_base_patch4_window7_224,639.26,1601.834,1024,224,15.47,36.63,87.77 -regnetx_160,626.06,817.797,512,224,15.99,25.52,54.28 -resnetrs152,625.1,1638.117,1024,320,24.34,48.14,86.62 -xcit_tiny_24_p16_384_dist,621.13,1648.58,1024,384,6.87,34.29,12.12 -seresnet152d,620.78,1649.515,1024,320,24.09,47.72,66.84 -coat_mini,608.71,1682.243,1024,224,6.82,33.68,10.34 -ese_vovnet99b_iabn,608.1,1683.926,1024,224,16.49,11.27,63.2 -vit_small_patch16_384,607.86,842.292,512,384,15.52,50.78,22.2 -regnetz_e8,602.95,849.151,512,320,15.46,63.94,57.7 -xcit_small_12_p16_384_dist,602.09,1700.725,1024,384,14.14,36.51,26.25 -volo_d2_224,597.09,1714.97,1024,224,14.34,41.34,58.68 -regnetz_c16_evos,580.2,882.442,512,320,3.86,25.88,13.49 -convmixer_768_32,576.37,1776.613,1024,224,19.55,25.95,21.11 -resnest101e,575.52,889.616,512,256,13.38,28.66,48.28 -cspdarknet53_iabn,573.47,1785.619,1024,256,6.53,16.81,27.64 -seresnext101_32x8d,572.07,894.988,512,288,27.24,51.63,93.57 -vit_base_r50_s16_224,569.41,1798.351,1024,224,21.66,35.29,98.66 -vit_small_r26_s32_384,560.76,913.03,512,384,10.43,29.85,36.47 -seresnet269d,554.23,1847.585,1024,256,26.59,53.6,113.67 -swin_v2_cr_base_224,538.29,1902.296,1024,224,15.86,64.42,87.88 -regnety_080,536.66,954.035,512,288,13.22,29.69,39.18 -swin_s3_base_224,533.85,1918.136,1024,224,13.69,48.26,71.13 -nest_base,530.0,966.015,512,224,17.96,53.39,67.72 -resnet200d,526.88,1943.493,1024,320,31.25,67.33,64.69 -jx_nest_base,525.35,974.569,512,224,17.96,53.39,67.72 -tnt_s_patch16_224,505.53,2025.583,1024,224,5.24,24.37,23.76 -mixnet_xxl,492.29,780.014,384,224,2.04,23.43,23.96 -convnext_large,490.59,1043.624,512,224,34.4,43.13,197.77 -eca_nfnet_l1,490.41,2088.053,1024,320,14.92,34.42,41.41 -convnext_large_in22ft1k,490.13,1044.606,512,224,34.4,43.13,197.77 -efficientnetv2_m,477.19,2145.885,1024,416,18.6,67.5,54.14 -regnety_064,472.22,1084.235,512,288,10.56,27.11,30.58 -tresnet_xl,472.15,2168.776,1024,224,15.17,15.34,78.44 -regnetv_064,468.26,1093.388,512,288,10.55,27.11,30.58 -efficientnet_b5,463.45,552.358,256,456,10.46,98.86,30.39 -mixer_l16_224,463.3,2210.217,1024,224,44.6,41.69,208.2 -xcit_tiny_24_p8_224,462.46,2214.217,1024,224,9.21,45.39,12.11 -xcit_tiny_24_p8_224_dist,462.21,2215.442,1024,224,9.21,45.39,12.11 -vit_large_patch32_384,459.15,2230.179,1024,384,45.31,43.86,306.63 -halonet_h1,457.28,559.821,256,256,3.0,51.17,8.1 -xcit_small_12_p8_224,455.91,2246.02,1024,224,18.69,47.21,26.21 -xcit_small_12_p8_224_dist,455.51,2247.996,1024,224,18.69,47.21,26.21 -resnetrs200,453.26,2259.149,1024,320,31.51,67.81,93.21 -efficientnet_b3_gn,449.21,427.404,192,320,2.14,28.83,11.73 -tf_efficientnet_b5_ap,441.14,580.297,256,456,10.46,98.86,30.39 -tf_efficientnet_b5_ns,441.05,580.416,256,456,10.46,98.86,30.39 -tf_efficientnet_b5,440.89,580.636,256,456,10.46,98.86,30.39 -xcit_large_24_p16_224,417.51,2452.617,1024,224,35.86,47.27,189.1 -xcit_nano_12_p8_384_dist,417.42,2453.137,1024,384,6.34,46.08,3.05 -xcit_large_24_p16_224_dist,417.4,2453.255,1024,224,35.86,47.27,189.1 -volo_d3_224,417.39,2453.347,1024,224,20.78,60.09,86.33 -regnety_320,414.44,1235.374,512,224,32.34,30.26,145.05 -regnety_160,414.17,927.145,384,288,26.37,38.07,83.59 -tnt_b_patch16_224,396.88,2580.105,1024,224,14.09,39.01,65.41 -swin_large_patch4_window7_224,396.25,1292.106,512,224,34.53,54.94,196.53 -efficientnetv2_rw_m,389.13,1315.733,512,416,21.49,79.62,53.24 -efficientnet_b3_g8_gn,378.11,507.779,192,320,3.2,28.83,14.25 -regnetz_d8_evos,373.7,1370.081,512,320,7.03,38.92,23.46 -tf_efficientnetv2_m,353.46,1448.525,512,480,24.76,89.84,54.14 -tf_efficientnetv2_m_in21ft1k,352.72,1451.565,512,480,24.76,89.84,54.14 -ssl_resnext101_32x16d,347.36,1473.959,512,224,36.27,51.18,194.03 -swsl_resnext101_32x16d,347.19,1474.669,512,224,36.27,51.18,194.03 -ig_resnext101_32x16d,347.17,1474.756,512,224,36.27,51.18,194.03 -vit_large_patch16_224,339.67,3014.653,1024,224,61.6,63.52,304.33 -swin_v2_cr_large_224,336.96,1519.449,512,224,35.1,85.57,196.68 -convnext_xlarge_in22ft1k,334.18,1532.115,512,224,60.97,57.5,350.2 -vit_base_patch16_18x2_224,321.9,3181.054,1024,224,52.51,71.38,256.73 -tresnet_m_448,321.34,3186.673,1024,448,22.94,29.21,31.39 -xcit_small_24_p16_384_dist,319.79,3202.041,1024,384,26.72,68.58,47.67 -crossvit_15_dagger_408,313.07,817.69,256,408,21.45,95.05,28.5 -beit_large_patch16_224,311.42,3288.141,1024,224,61.6,63.52,304.43 -pnasnet5large,298.92,1284.602,384,331,25.04,92.89,86.06 -xcit_tiny_12_p8_384_dist,295.94,3460.2,1024,384,14.13,69.14,6.71 -ecaresnet269d,292.16,3504.88,1024,352,50.25,101.25,102.09 -nasnetalarge,292.11,1314.567,384,331,23.89,90.56,88.75 -nfnet_f1,287.25,3564.832,1024,320,35.97,46.77,132.63 -swin_v2_cr_tiny_384,285.61,896.314,256,384,15.36,179.92,28.33 -resnetrs270,285.53,3586.279,1024,352,51.13,105.48,129.86 -convnext_small_384_in22ft1k,283.44,1354.767,384,384,45.2,84.49,88.59 -convnext_tiny_384_in22ft1k,283.35,1355.207,384,384,45.2,84.49,88.59 -convnext_base_384_in22ft1k,283.27,1355.587,384,384,45.2,84.49,88.59 -volo_d4_224,276.66,3701.277,1024,224,44.34,80.22,192.96 -resnetv2_152x2_bit_teacher,275.55,1858.104,512,224,46.95,45.11,236.34 -volo_d1_384,274.17,1400.584,384,384,22.75,108.55,26.78 -efficientnet_b6,265.63,481.865,128,528,19.4,167.39,43.04 -regnetx_320,263.46,1457.527,384,224,31.81,36.3,107.81 -deit_base_patch16_384,263.34,1458.17,384,384,55.54,101.56,86.86 -vit_base_patch16_384,262.84,1460.977,384,384,55.54,101.56,86.86 -dm_nfnet_f1,261.73,3912.436,1024,320,35.97,46.77,132.63 -deit_base_distilled_patch16_384,259.59,1479.254,384,384,55.65,101.82,87.63 -tf_efficientnet_b6,254.04,503.851,128,528,19.4,167.39,43.04 -tf_efficientnet_b6_ap,253.95,504.02,128,528,19.4,167.39,43.04 -tf_efficientnet_b6_ns,253.88,504.17,128,528,19.4,167.39,43.04 -vit_large_patch14_224,249.95,4096.733,1024,224,81.08,88.79,304.2 -cait_xxs24_384,247.45,4138.198,1024,384,9.63,122.66,12.03 -xcit_small_24_p8_224,239.07,4283.263,1024,224,35.81,90.78,47.63 -xcit_small_24_p8_224_dist,239.0,4284.476,1024,224,35.81,90.78,47.63 -xcit_medium_24_p16_384_dist,238.18,2149.659,512,384,47.39,91.64,84.4 -eca_nfnet_l2,234.53,2183.088,512,384,30.05,68.28,56.72 -crossvit_18_dagger_408,234.0,820.485,192,408,32.47,124.87,44.61 -vit_large_r50_s32_384,229.73,1671.515,384,384,57.43,76.52,329.09 -beit_base_patch16_384,226.15,1697.971,384,384,55.54,101.56,86.74 -resmlp_big_24_224,204.41,5009.412,1024,224,100.23,87.31,129.14 -resmlp_big_24_224_in22ft1k,204.19,5014.99,1024,224,100.23,87.31,129.14 -resmlp_big_24_distilled_224,204.14,5016.18,1024,224,100.23,87.31,129.14 -resnest200e,198.33,2581.599,512,320,35.69,82.78,70.2 -resnetrs350,188.33,2718.619,512,384,77.59,154.74,163.96 -efficientnetv2_l,185.45,2760.873,512,480,56.4,157.99,118.52 -volo_d5_224,183.53,5579.332,1024,224,72.4,118.11,295.46 -tf_efficientnetv2_l,183.5,2790.123,512,480,56.4,157.99,118.52 -tf_efficientnetv2_l_in21ft1k,183.34,2792.665,512,480,56.4,157.99,118.52 -swin_v2_cr_small_384,182.55,1402.341,256,384,29.73,328.89,49.7 -swin_base_patch4_window12_384,176.96,1085.005,192,384,47.19,134.78,87.9 -xcit_medium_24_p8_224_dist,176.61,5798.18,1024,224,63.53,121.23,84.32 -xcit_medium_24_p8_224,176.56,5799.802,1024,224,63.53,121.23,84.32 -cait_xs24_384,175.88,2911.134,512,384,19.28,183.98,26.67 -vit_base_patch8_224,173.92,1471.961,256,224,78.22,161.69,86.58 -convnext_large_384_in22ft1k,167.45,1528.836,256,384,101.09,126.74,197.77 -cait_xxs36_384,165.77,6177.386,1024,384,14.35,183.7,17.37 -vit_base_resnet50_384,164.81,2329.882,384,384,67.43,135.03,98.95 -vit_base_r50_s16_384,164.76,2330.691,384,384,67.43,135.03,98.95 -densenet264d_iabn,164.43,6227.497,1024,224,13.47,14.0,72.74 -nfnet_f2,161.44,6342.864,1024,352,63.22,79.06,193.78 -efficientnet_b7,159.81,600.7,96,600,38.33,289.94,66.35 -swin_v2_cr_huge_224,158.24,2426.623,384,224,115.98,130.61,657.83 -volo_d2_384,157.29,1627.556,256,384,46.17,184.51,58.87 -xcit_tiny_24_p8_384_dist,155.86,6569.908,1024,384,27.05,132.95,12.11 -xcit_small_12_p8_384_dist,155.07,3301.621,512,384,54.92,138.29,26.21 -tf_efficientnet_b7,154.05,623.167,96,600,38.33,289.94,66.35 -tf_efficientnet_b7_ap,154.01,623.324,96,600,38.33,289.94,66.35 -tf_efficientnet_b7_ns,153.96,623.512,96,600,38.33,289.94,66.35 -tresnet_l_448,152.46,6716.506,1024,448,43.5,47.56,55.99 -dm_nfnet_f2,147.56,3469.794,512,352,63.22,79.06,193.78 -xcit_large_24_p16_384_dist,142.96,3581.333,512,384,105.35,137.17,189.1 -efficientnetv2_xl,140.5,2733.05,384,512,93.85,247.32,208.12 -tf_efficientnetv2_xl_in21ft1k,139.84,2745.956,384,512,93.85,247.32,208.12 -swin_v2_cr_base_384,136.74,1404.102,192,384,50.61,374.82,87.88 -vit_huge_patch14_224,136.63,7494.593,1024,224,167.4,139.41,632.05 -cait_s24_384,136.25,3757.768,512,384,32.17,245.31,47.06 -resnetrs420,133.09,3846.971,512,416,108.45,213.79,191.89 -eca_nfnet_l3,123.63,4141.303,512,448,52.55,118.4,72.04 -convnext_xlarge_384_in22ft1k,114.1,1682.671,192,384,179.18,168.99,350.2 -tresnet_xl_448,113.35,9034.224,1024,448,60.65,61.31,78.44 -swin_large_patch4_window12_384,111.26,1150.4,128,384,104.08,202.16,196.74 -efficientnet_cc_b0_4e,107.9,9.259,1,224,0.41,9.42,13.31 -xcit_large_24_p8_224,106.51,4807.053,512,224,141.23,181.56,188.93 -xcit_large_24_p8_224_dist,106.39,4812.62,512,224,141.23,181.56,188.93 -tf_efficientnet_cc_b0_4e,105.13,9.503,1,224,0.41,9.42,13.31 -tf_efficientnet_cc_b0_8e,101.03,9.888,1,224,0.42,9.42,24.01 -efficientnet_cc_b0_8e,100.58,9.933,1,224,0.42,9.42,24.01 -efficientnet_b8,97.89,980.672,96,672,63.48,442.89,87.41 -resnetv2_152x2_bit_teacher_384,95.58,2678.506,256,384,136.16,132.56,236.34 -tf_efficientnet_b8,94.94,1011.165,96,672,63.48,442.89,87.41 -tf_efficientnet_b8_ap,94.88,1011.773,96,672,63.48,442.89,87.41 -resnest269e,92.66,4144.14,384,416,77.69,171.98,110.93 -resnetv2_50x3_bitm,91.89,1392.952,128,448,145.7,133.37,217.32 -cait_s36_384,91.13,5618.401,512,384,47.99,367.4,68.37 -vit_large_patch16_384,91.02,2812.461,256,384,191.21,270.24,304.72 -vit_giant_patch14_224,90.41,5663.146,512,224,267.18,192.64,1012.61 -swin_v2_cr_large_384,87.0,1471.203,128,384,109.02,466.67,196.68 -nfnet_f3,83.54,6128.872,512,416,115.58,141.78,254.92 -convmixer_1024_20_ks9_p14,82.81,12365.256,1024,224,5.55,5.51,24.38 -xcit_small_24_p8_384_dist,81.31,6296.644,512,384,105.24,265.91,47.63 -beit_large_patch16_384,78.92,3243.632,256,384,191.21,270.24,305.0 -dm_nfnet_f3,76.98,6650.815,512,416,115.58,141.78,254.92 -efficientnet_cc_b1_8e,74.31,13.446,1,240,0.75,15.44,39.72 -tf_efficientnet_cc_b1_8e,71.55,13.966,1,240,0.75,15.44,39.72 -resnetv2_152x2_bitm,70.29,2731.662,192,448,184.99,180.43,236.34 -volo_d3_448,69.5,2762.392,192,448,96.33,446.83,86.63 -xcit_medium_24_p8_384_dist,60.36,4241.495,256,384,186.67,354.73,84.32 -resnetv2_101x3_bitm,56.99,2245.848,128,448,280.33,194.78,387.93 -vit_gigantic_patch14_224,54.97,6985.565,384,224,483.95,275.37,1844.44 -volo_d4_448,52.04,3689.433,192,448,197.13,527.35,193.41 -swin_v2_cr_giant_224,47.35,2703.077,128,224,483.88,342.95,2598.76 -nfnet_f4,45.03,8527.847,384,512,216.26,262.26,316.07 -dm_nfnet_f4,41.28,9302.917,384,512,216.26,262.26,316.07 -swin_v2_cr_huge_384,40.59,1576.755,64,384,352.16,696.31,657.94 -xcit_large_24_p8_384_dist,36.24,5297.999,192,384,415.0,531.82,188.93 -volo_d5_448,36.04,3551.639,128,448,315.06,737.92,295.91 -nfnet_f5,33.24,11553.271,384,544,290.97,349.71,377.21 -beit_large_patch16_512,32.09,2991.564,96,512,362.24,656.39,305.67 -dm_nfnet_f5,31.46,8137.719,256,544,290.97,349.71,377.21 -cait_m36_384,30.85,8298.098,256,384,173.11,734.81,271.22 -nfnet_f6,25.52,10030.043,256,576,378.69,452.2,438.36 -volo_d5_512,25.24,5072.088,128,512,425.09,1105.37,296.09 -dm_nfnet_f6,23.36,10959.027,256,576,378.69,452.2,438.36 -nfnet_f7,20.08,9559.462,192,608,480.39,570.85,499.5 -resnetv2_152x4_bitm,18.1,3536.743,64,480,844.84,414.26,936.53 -convmixer_1536_20,13.52,75763.376,1024,224,48.68,33.03,51.63 -cait_m48_448,13.31,9617.788,128,448,329.41,1708.23,356.46 -swin_v2_cr_giant_384,13.19,2426.875,32,384,1451.0,1686.82,2598.76 diff --git a/results/benchmark-infer-amp-nhwc-pt112-cu113-rtx3090.csv b/results/benchmark-infer-amp-nhwc-pt112-cu113-rtx3090.csv new file mode 100644 index 00000000..fbf7e583 --- /dev/null +++ b/results/benchmark-infer-amp-nhwc-pt112-cu113-rtx3090.csv @@ -0,0 +1,839 @@ +model,infer_samples_per_sec,infer_step_time,infer_batch_size,infer_img_size,infer_gmacs,infer_macts,param_count +tinynet_e,70939.06,14.424,1024,106,0.03,0.69,2.04 +mobilenetv3_small_050,53363.87,19.179,1024,224,0.03,0.92,1.59 +lcnet_035,39908.29,25.648,1024,224,0.03,1.04,1.64 +mobilenetv3_small_075,38048.72,26.902,1024,224,0.05,1.3,2.04 +tinynet_d,35634.7,28.724,1024,152,0.05,1.42,2.34 +lcnet_050,35231.0,29.055,1024,224,0.05,1.26,1.88 +mobilenetv3_small_100,34913.55,29.319,1024,224,0.06,1.42,2.54 +tf_mobilenetv3_small_minimal_100,31288.96,32.716,1024,224,0.06,1.41,2.04 +tf_mobilenetv3_small_075,30676.85,33.368,1024,224,0.05,1.3,2.04 +lcnet_075,30088.74,34.022,1024,224,0.1,1.99,2.36 +tf_mobilenetv3_small_100,28547.5,35.858,1024,224,0.06,1.42,2.54 +lcnet_100,23945.91,42.753,1024,224,0.16,2.52,2.95 +mnasnet_small,22244.35,46.024,1024,224,0.07,2.16,2.03 +levit_128s,22002.58,46.529,1024,224,0.31,1.88,7.78 +mobilenetv2_035,20937.19,48.897,1024,224,0.07,2.86,1.68 +mnasnet_050,18984.06,53.93,1024,224,0.11,3.07,2.22 +ghostnet_050,18415.88,55.593,1024,224,0.05,1.77,2.59 +tinynet_c,17846.73,57.365,1024,184,0.11,2.87,2.46 +mobilenetv2_050,16928.19,60.48,1024,224,0.1,3.64,1.97 +semnasnet_050,16394.61,62.449,1024,224,0.11,3.44,2.08 +lcnet_150,15508.0,66.02,1024,224,0.34,3.79,4.5 +gernet_s,15282.73,66.993,1024,224,0.75,2.65,8.17 +levit_128,14929.05,68.581,1024,224,0.41,2.71,9.21 +cs3darknet_focus_s,14654.05,69.868,1024,256,0.69,2.7,3.27 +cs3darknet_s,14422.34,70.991,1024,256,0.72,2.97,3.28 +mobilenetv3_large_075,14412.2,71.04,1024,224,0.16,4.0,3.99 +mixer_s32_224,13576.58,75.414,1024,224,1.0,2.28,19.1 +resnet10t,13509.21,75.789,1024,224,1.1,2.43,5.44 +mobilenetv3_rw,13202.47,77.551,1024,224,0.23,4.41,5.48 +levit_192,13174.02,77.717,1024,224,0.66,3.2,10.95 +mobilenetv3_large_100,12955.77,79.027,1024,224,0.23,4.41,5.48 +mobilenetv3_large_100_miil,12954.49,79.035,1024,224,0.23,4.41,5.48 +vit_small_patch32_224,12913.76,79.284,1024,224,1.15,2.5,22.88 +hardcorenas_a,12748.25,80.313,1024,224,0.23,4.38,5.26 +mnasnet_075,12700.79,80.614,1024,224,0.23,4.77,3.17 +tf_mobilenetv3_large_075,12296.64,83.262,1024,224,0.16,4.0,3.99 +tinynet_b,12104.09,84.587,1024,188,0.21,4.44,3.73 +tf_mobilenetv3_large_minimal_100,11915.92,85.923,1024,224,0.22,4.4,3.92 +hardcorenas_b,11667.78,87.752,1024,224,0.26,5.09,5.18 +hardcorenas_c,11602.35,88.247,1024,224,0.28,5.01,5.52 +ese_vovnet19b_slim_dw,11450.49,89.417,1024,224,0.4,5.28,1.9 +mnasnet_b1,11305.32,90.567,1024,224,0.33,5.46,4.38 +mnasnet_100,11303.72,90.578,1024,224,0.33,5.46,4.38 +tf_mobilenetv3_large_100,11165.87,91.695,1024,224,0.23,4.41,5.48 +gluon_resnet18_v1b,11046.16,92.691,1024,224,1.82,2.48,11.69 +ssl_resnet18,11027.01,92.852,1024,224,1.82,2.48,11.69 +resnet18,11023.6,92.881,1024,224,1.82,2.48,11.69 +swsl_resnet18,11003.86,93.048,1024,224,1.82,2.48,11.69 +semnasnet_075,10953.15,93.479,1024,224,0.23,5.54,2.91 +regnetx_004,10946.78,93.533,1024,224,0.4,3.14,5.16 +hardcorenas_d,10898.13,93.95,1024,224,0.3,4.93,7.5 +mobilenetv2_075,10779.36,94.985,1024,224,0.22,5.86,2.64 +ghostnet_100,10498.38,97.527,1024,224,0.15,3.55,5.18 +seresnet18,10333.85,99.081,1024,224,1.82,2.49,11.78 +vit_tiny_r_s16_p8_224,10273.23,99.666,1024,224,0.44,2.06,6.34 +spnasnet_100,10240.55,99.983,1024,224,0.35,6.03,4.42 +legacy_seresnet18,10026.58,102.118,1024,224,1.82,2.49,11.78 +mnasnet_a1,9730.7,105.223,1024,224,0.32,6.23,3.89 +semnasnet_100,9728.29,105.249,1024,224,0.32,6.23,3.89 +tf_efficientnetv2_b0,9714.68,105.397,1024,224,0.73,4.77,7.14 +tinynet_a,9706.17,105.487,1024,192,0.35,5.41,6.19 +hardcorenas_f,9654.05,106.058,1024,224,0.35,5.57,8.2 +mobilenetv2_100,9591.46,106.751,1024,224,0.31,6.68,3.5 +levit_256,9580.42,106.874,1024,224,1.13,4.23,18.89 +regnetx_002,9551.99,107.191,1024,224,0.2,2.16,2.68 +hardcorenas_e,9521.78,107.531,1024,224,0.35,5.65,8.07 +efficientnet_lite0,9415.07,108.751,1024,224,0.4,6.74,4.65 +regnety_002,9227.09,110.966,1024,224,0.2,2.17,3.16 +fbnetc_100,9182.63,111.504,1024,224,0.4,6.51,5.57 +resnet18d,9153.04,111.864,1024,224,2.06,3.29,11.71 +regnety_006,9048.64,113.154,1024,224,0.61,4.33,6.06 +ese_vovnet19b_slim,8822.42,116.057,1024,224,1.69,3.52,3.17 +ghostnet_130,8402.81,121.852,1024,224,0.24,4.6,7.36 +regnetx_006,8395.84,121.954,1024,224,0.61,3.98,6.2 +levit_256d,8131.84,125.914,1024,224,1.4,4.93,26.21 +tf_efficientnet_lite0,8115.07,126.174,1024,224,0.4,6.74,4.65 +regnetz_005,8104.32,126.341,1024,224,0.52,5.86,7.12 +efficientnet_b0,8015.36,127.743,1024,224,0.4,6.75,5.29 +xcit_nano_12_p16_224_dist,7700.28,132.971,1024,224,0.56,4.17,3.05 +xcit_nano_12_p16_224,7692.58,133.102,1024,224,0.56,4.17,3.05 +mnasnet_140,7484.35,136.808,1024,224,0.6,7.71,7.12 +rexnetr_100,7414.06,138.105,1024,224,0.43,7.72,4.88 +resnet14t,7298.17,140.296,1024,224,1.69,5.8,10.08 +mobilenetv2_110d,7233.3,141.556,1024,224,0.45,8.71,4.52 +regnetx_008,7112.68,143.957,1024,224,0.81,5.15,7.26 +tf_efficientnet_b0_ns,7058.22,145.067,1024,224,0.4,6.75,5.29 +tf_efficientnet_b0_ap,7055.15,145.131,1024,224,0.4,6.75,5.29 +tf_efficientnet_b0,7052.24,145.19,1024,224,0.4,6.75,5.29 +edgenext_xx_small,6998.78,146.298,1024,256,0.33,4.21,1.33 +dla46_c,6933.78,147.671,1024,224,0.58,4.5,1.3 +deit_tiny_patch16_224,6855.38,149.36,1024,224,1.26,5.97,5.72 +vit_tiny_patch16_224,6844.8,149.592,1024,224,1.26,5.97,5.72 +regnety_008,6827.19,149.977,1024,224,0.81,5.25,6.26 +gernet_m,6753.27,151.619,1024,224,3.02,5.24,21.14 +deit_tiny_distilled_patch16_224,6720.97,152.347,1024,224,1.27,6.01,5.91 +efficientnet_b1_pruned,6608.04,154.952,1024,240,0.4,6.21,6.33 +hrnet_w18_small,6603.38,155.061,1024,224,1.61,5.72,13.19 +gluon_resnet34_v1b,6434.28,159.136,1024,224,3.67,3.74,21.8 +semnasnet_140,6428.21,159.287,1024,224,0.6,8.87,6.11 +tv_resnet34,6406.04,159.838,1024,224,3.67,3.74,21.8 +resnet34,6404.45,159.878,1024,224,3.67,3.74,21.8 +ese_vovnet19b_dw,6353.89,161.15,1024,224,1.34,8.25,6.54 +rexnet_100,6291.85,162.738,1024,224,0.41,7.44,4.8 +mobilenetv2_140,6258.1,163.617,1024,224,0.6,9.57,6.11 +mobilevitv2_050,6228.2,164.403,1024,256,0.48,8.04,1.37 +efficientnet_lite1,6215.56,164.736,1024,240,0.62,10.14,5.42 +tf_efficientnetv2_b1,6143.78,166.661,1024,240,1.21,7.34,8.14 +visformer_tiny,6090.13,168.13,1024,224,1.27,5.72,10.32 +fbnetv3_b,6012.29,170.307,1024,256,0.55,9.1,8.6 +seresnet34,5988.65,170.978,1024,224,3.67,3.74,21.96 +resnet26,5923.37,172.863,1024,224,2.36,7.35,16.0 +efficientnet_es,5871.09,174.403,1024,224,1.81,8.73,5.44 +efficientnet_es_pruned,5866.42,174.542,1024,224,1.81,8.73,5.44 +selecsls42,5796.58,176.643,1024,224,2.94,4.62,30.35 +pit_ti_distilled_224,5792.34,176.773,1024,224,0.71,6.23,5.1 +legacy_seresnet34,5780.67,177.13,1024,224,3.67,3.74,21.96 +selecsls42b,5766.92,177.544,1024,224,2.98,4.62,32.46 +pit_ti_224,5764.0,177.643,1024,224,0.7,6.19,4.85 +resnet34d,5748.0,178.138,1024,224,3.91,4.54,21.82 +levit_384,5659.16,180.934,1024,224,2.36,6.26,39.13 +tf_efficientnet_es,5608.15,182.58,1024,224,1.81,8.73,5.44 +resnetblur18,5572.02,183.764,1024,224,2.34,3.39,11.69 +tf_efficientnet_lite1,5541.93,184.761,1024,240,0.62,10.14,5.42 +rexnetr_130,5487.71,186.587,1024,224,0.68,9.81,7.61 +cs3darknet_m,5481.96,186.783,1024,288,2.63,6.69,9.31 +mixnet_s,5402.43,189.533,1024,224,0.25,6.25,4.13 +regnety_004,5382.71,190.227,1024,224,0.41,3.89,4.34 +skresnet18,5371.9,190.61,1024,224,1.82,3.24,11.96 +darknet17,5347.86,143.598,768,256,3.26,7.18,14.3 +mobilevit_xxs,5306.36,192.964,1024,256,0.42,8.34,1.27 +cs3darknet_focus_m,5289.88,193.566,1024,288,2.51,6.19,9.3 +mobilenetv2_120d,5178.64,197.724,1024,224,0.69,11.97,5.83 +repvgg_b0,5161.18,198.394,1024,224,3.41,6.15,15.82 +xcit_tiny_12_p16_224_dist,5107.76,200.467,1024,224,1.24,6.29,6.72 +xcit_tiny_12_p16_224,5104.48,200.597,1024,224,1.24,6.29,6.72 +resnet26d,5093.48,201.03,1024,224,2.6,8.15,16.01 +tf_mixnet_s,4981.9,205.528,1024,224,0.25,6.25,4.13 +vit_base_patch32_224_sam,4925.79,207.875,1024,224,4.41,5.01,88.22 +vit_base_patch32_224,4923.14,207.986,1024,224,4.41,5.01,88.22 +selecsls60,4922.02,208.033,1024,224,3.59,5.52,30.67 +mixer_b32_224,4909.46,208.566,1024,224,3.24,6.29,60.29 +selecsls60b,4902.59,208.858,1024,224,3.63,5.52,32.77 +rexnetr_150,4887.15,209.518,1024,224,0.89,11.13,9.78 +nf_resnet26,4834.78,211.787,1024,224,2.41,7.35,16.0 +darknet21,4804.05,159.854,768,256,3.93,7.47,20.86 +resmlp_12_distilled_224,4801.62,213.251,1024,224,3.01,5.5,15.35 +resmlp_12_224,4801.47,213.257,1024,224,3.01,5.5,15.35 +efficientnet_lite2,4791.14,213.716,1024,260,0.89,12.9,6.09 +pit_xs_224,4790.75,213.733,1024,224,1.4,7.71,10.62 +fbnetv3_d,4788.83,213.819,1024,256,0.68,11.1,10.31 +pit_xs_distilled_224,4740.73,215.989,1024,224,1.41,7.76,11.0 +dla34,4712.5,217.283,1024,224,3.07,5.02,15.74 +sedarknet21,4615.23,166.394,768,256,3.93,7.47,20.95 +resnext26ts,4512.74,226.902,1024,256,2.43,10.52,10.3 +tf_efficientnetv2_b2,4506.54,227.212,1024,260,1.72,9.84,10.1 +mixer_s16_224,4471.0,229.021,1024,224,3.79,5.97,18.53 +legacy_seresnext26_32x4d,4467.81,229.184,1024,224,2.49,9.39,16.79 +edgenext_x_small,4458.42,229.664,1024,256,0.68,7.5,2.34 +gernet_l,4450.89,230.055,1024,256,4.57,8.0,31.08 +tf_efficientnet_b1,4403.29,232.542,1024,240,0.71,10.88,7.79 +tf_efficientnet_b1_ns,4402.75,232.57,1024,240,0.71,10.88,7.79 +tf_efficientnet_b1_ap,4402.24,232.597,1024,240,0.71,10.88,7.79 +eca_resnext26ts,4354.84,235.13,1024,256,2.43,10.52,10.3 +seresnext26ts,4350.24,235.378,1024,256,2.43,10.52,10.39 +tf_efficientnet_lite2,4300.72,238.087,1024,260,0.89,12.9,6.09 +gcresnext26ts,4295.78,238.361,1024,256,2.43,10.53,10.48 +rexnet_130,4282.77,239.085,1024,224,0.68,9.71,7.56 +efficientnet_b1,4273.32,239.615,1024,256,0.77,12.22,7.79 +gmlp_ti16_224,4143.15,247.143,1024,224,1.34,7.55,5.87 +efficientnet_b0_g16_evos,4127.77,248.064,1024,224,1.01,7.42,8.11 +crossvit_tiny_240,4122.07,248.408,1024,240,1.57,9.08,7.01 +nf_ecaresnet26,4104.24,249.486,1024,224,2.41,7.36,16.0 +efficientnet_b2_pruned,4103.05,249.558,1024,260,0.73,9.13,8.31 +nf_seresnet26,4102.39,249.599,1024,224,2.41,7.36,17.4 +mobilevitv2_075,4066.07,251.829,1024,256,1.05,12.06,2.87 +vit_small_patch32_384,4025.63,254.359,1024,384,3.45,8.25,22.92 +ecaresnext50t_32x4d,4000.29,255.97,1024,224,2.7,10.09,15.41 +ecaresnext26t_32x4d,3998.13,256.108,1024,224,2.7,10.09,15.41 +seresnext26tn_32x4d,3995.56,256.274,1024,224,2.7,10.09,16.81 +seresnext26t_32x4d,3993.92,256.378,1024,224,2.7,10.09,16.81 +seresnext26d_32x4d,3982.98,257.083,1024,224,2.73,10.19,16.81 +resnet26t,3922.56,261.042,1024,256,3.35,10.52,16.01 +dla46x_c,3917.72,261.363,1024,224,0.54,5.66,1.07 +rexnet_150,3870.49,264.554,1024,224,0.9,11.21,9.73 +resnetv2_50,3868.33,264.701,1024,224,4.11,11.11,25.55 +crossvit_9_240,3865.11,264.922,1024,240,1.85,9.52,8.55 +convnext_nano_ols,3859.14,265.333,1024,224,2.5,8.37,15.6 +nf_regnet_b0,3819.49,268.086,1024,256,0.64,5.58,8.76 +ecaresnet50d_pruned,3812.92,268.549,1024,224,2.53,6.43,19.94 +regnetx_016,3808.7,268.846,1024,224,1.62,7.93,9.19 +crossvit_9_dagger_240,3792.18,270.018,1024,240,1.99,9.97,8.78 +dla60x_c,3787.69,270.337,1024,224,0.59,6.01,1.32 +convnext_nano_hnf,3786.83,270.399,1024,224,2.46,8.37,15.59 +ecaresnetlight,3729.3,274.57,1024,224,4.11,8.42,30.16 +poolformer_s12,3722.39,275.081,1024,224,1.82,5.53,11.92 +gmixer_12_224,3686.02,277.795,1024,224,2.67,7.26,12.7 +gluon_resnet50_v1b,3677.5,278.438,1024,224,4.11,11.11,25.56 +resnet50,3676.35,278.526,1024,224,4.11,11.11,25.56 +ssl_resnet50,3674.86,278.638,1024,224,4.11,11.11,25.56 +tv_resnet50,3673.31,278.756,1024,224,4.11,11.11,25.56 +swsl_resnet50,3672.81,278.794,1024,224,4.11,11.11,25.56 +dpn68,3650.67,280.484,1024,224,2.35,10.47,12.61 +dpn68b,3606.63,283.907,1024,224,2.35,10.47,12.61 +botnet26t_256,3555.59,287.983,1024,256,3.32,11.98,12.49 +regnety_016,3516.07,291.222,1024,224,1.63,8.04,11.2 +repvgg_a2,3514.85,291.324,1024,224,5.7,6.26,28.21 +resnetv2_50t,3513.08,291.47,1024,224,4.32,11.82,25.57 +efficientnet_em,3504.92,292.149,1024,240,3.04,14.34,6.9 +mixnet_m,3496.31,292.868,1024,224,0.36,8.19,5.01 +resnetv2_50d,3496.21,292.876,1024,224,4.35,11.92,25.57 +rexnetr_200,3492.0,219.921,768,224,1.59,15.11,16.52 +halonet26t,3480.88,294.167,1024,256,3.19,11.69,12.48 +gluon_resnet50_v1c,3476.97,294.498,1024,224,4.35,11.92,25.58 +resnet32ts,3465.97,295.433,1024,256,4.63,11.58,17.96 +bat_resnext26ts,3457.26,296.173,1024,256,2.53,12.51,10.73 +resnet33ts,3415.09,299.834,1024,256,4.76,11.66,19.68 +tf_efficientnet_b2_ns,3414.14,299.918,1024,260,1.02,13.83,9.11 +tf_efficientnet_b2,3412.6,300.052,1024,260,1.02,13.83,9.11 +tf_efficientnet_b2_ap,3412.15,300.092,1024,260,1.02,13.83,9.11 +tf_efficientnet_em,3389.12,302.132,1024,240,3.04,14.34,6.9 +resnet50t,3345.79,306.045,1024,224,4.32,11.82,25.57 +gluon_resnet50_v1d,3337.44,306.809,1024,224,4.35,11.92,25.58 +resnet50d,3336.65,306.882,1024,224,4.35,11.92,25.58 +vit_tiny_r_s16_p8_384,3314.06,154.482,512,384,1.34,6.49,6.36 +legacy_seresnet50,3311.17,309.245,1024,224,3.88,10.6,28.09 +seresnet33ts,3304.6,309.859,1024,256,4.76,11.66,19.78 +tf_mixnet_m,3303.11,309.997,1024,224,0.36,8.19,5.01 +eca_resnet33ts,3297.96,310.484,1024,256,4.76,11.66,19.68 +convit_tiny,3289.83,311.251,1024,224,1.26,7.94,5.71 +gcresnet33ts,3263.32,313.778,1024,256,4.76,11.68,19.88 +vit_small_resnet26d_224,3252.42,314.83,1024,224,5.07,11.12,63.61 +vovnet39a,3229.96,317.018,1024,224,7.09,6.73,22.6 +efficientnet_b2a,3221.33,317.868,1024,288,1.12,16.2,9.11 +efficientnet_b2,3221.08,317.894,1024,288,1.12,16.2,9.11 +efficientnet_b3_pruned,3195.08,320.48,1024,300,1.04,11.86,9.86 +seresnet50,3183.22,321.675,1024,224,4.11,11.13,28.09 +cs3darknet_l,3171.55,322.859,1024,288,6.16,10.83,21.16 +cs3darknet_focus_l,3146.07,325.473,1024,288,5.9,10.16,21.15 +res2net50_48w_2s,3141.04,325.995,1024,224,4.18,11.72,25.29 +eca_vovnet39b,3123.78,327.796,1024,224,7.09,6.74,22.6 +ese_vovnet39b,3117.85,328.419,1024,224,7.09,6.74,24.57 +mobilevit_xs,3095.24,248.113,768,256,1.05,16.33,2.32 +resnext50_32x4d,3092.67,331.094,1024,224,4.26,14.4,25.03 +ssl_resnext50_32x4d,3089.61,331.422,1024,224,4.26,14.4,25.03 +gluon_resnext50_32x4d,3087.43,331.656,1024,224,4.26,14.4,25.03 +swsl_resnext50_32x4d,3086.28,331.779,1024,224,4.26,14.4,25.03 +tv_resnext50_32x4d,3085.42,331.872,1024,224,4.26,14.4,25.03 +hrnet_w18_small_v2,3075.57,332.934,1024,224,2.62,9.65,15.6 +eca_botnext26ts_256,3069.01,333.646,1024,256,2.46,11.6,10.59 +dla60,3049.62,335.767,1024,224,4.26,10.16,22.04 +vgg11,3048.59,167.933,512,224,7.61,7.44,132.86 +skresnet34,3035.0,337.386,1024,224,3.67,5.13,22.28 +mobilevitv2_100,3028.13,253.611,768,256,1.84,16.08,4.9 +vit_small_patch16_224,3005.65,340.679,1024,224,4.61,11.95,22.05 +deit_small_patch16_224,3005.16,340.735,1024,224,4.61,11.95,22.05 +eca_halonext26ts,2980.4,343.567,1024,256,2.44,11.46,10.76 +resnetaa50d,2972.16,344.518,1024,224,5.39,12.44,25.58 +ecaresnet101d_pruned,2963.47,345.529,1024,224,3.48,7.69,24.88 +coat_lite_tiny,2957.59,346.216,1024,224,1.6,11.65,5.72 +cs3sedarknet_l,2955.87,346.418,1024,288,6.16,10.83,21.91 +deit_small_distilled_patch16_224,2950.21,347.082,1024,224,4.63,12.02,22.44 +gluon_resnet50_v1s,2947.99,347.343,1024,224,5.47,13.52,25.68 +resnetrs50,2945.06,347.688,1024,224,4.48,12.14,35.69 +seresnet50t,2939.07,348.397,1024,224,4.32,11.83,28.1 +densenet121,2936.15,348.744,1024,224,2.87,6.9,7.98 +pit_s_224,2935.87,348.777,1024,224,2.88,11.56,23.46 +ecaresnet50d,2934.67,348.92,1024,224,4.35,11.93,25.58 +tv_densenet121,2927.3,349.799,1024,224,2.87,6.9,7.98 +selecsls84,2927.1,349.822,1024,224,5.9,7.57,50.95 +pit_s_distilled_224,2909.88,351.892,1024,224,2.9,11.64,24.04 +vit_relpos_base_patch32_plus_rpn_256,2858.63,358.203,1024,256,7.68,8.01,119.42 +deit3_small_patch16_224_in21ft1k,2858.2,358.255,1024,224,4.61,11.95,22.06 +deit3_small_patch16_224,2853.97,358.786,1024,224,4.61,11.95,22.06 +resnext50d_32x4d,2849.78,359.313,1024,224,4.5,15.2,25.05 +vit_relpos_small_patch16_rpn_224,2814.18,363.86,1024,224,4.59,13.05,21.97 +densenet121d,2808.28,364.624,1024,224,3.11,7.7,8.0 +cspresnet50,2805.19,365.024,1024,256,4.54,11.5,21.62 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+vgg11_bn,2701.91,189.486,512,224,7.62,7.44,132.87 +visformer_small,2695.9,379.825,1024,224,4.88,11.43,40.22 +lambda_resnet26rpt_256,2689.85,380.679,1024,256,3.16,11.87,10.99 +mixnet_l,2682.98,286.237,768,224,0.58,10.84,7.33 +resnetblur50,2682.32,381.746,1024,224,5.16,12.02,25.56 +vovnet57a,2674.97,382.797,1024,224,8.95,7.52,36.64 +efficientnet_lite3,2659.04,192.54,512,300,1.65,21.85,8.2 +cspresnet50d,2649.78,386.434,1024,256,4.86,12.55,21.64 +seresnetaa50d,2644.86,387.154,1024,224,5.4,12.46,28.11 +efficientnetv2_rw_t,2633.28,388.856,1024,288,3.19,16.42,13.65 +cspresnet50w,2624.25,390.195,1024,256,5.04,12.19,28.12 +twins_svt_small,2599.22,393.951,1024,224,2.94,13.75,24.06 +tf_efficientnetv2_b3,2587.08,395.8,1024,300,3.04,15.74,14.36 +nf_regnet_b2,2583.08,396.413,1024,272,1.22,9.27,14.31 +vit_base_resnet26d_224,2575.01,397.656,1024,224,6.97,13.16,101.4 +ese_vovnet57b,2572.63,398.024,1024,224,8.95,7.52,38.61 +fbnetv3_g,2570.51,398.353,1024,288,1.77,21.09,16.62 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+seresnextaa101d_32x8d,521.71,1472.057,768,288,28.51,56.44,93.59 +vit_large_patch32_384,517.33,1979.373,1024,384,45.31,43.86,306.63 +swinv2_base_window8_256,509.01,2011.746,1024,256,20.37,52.59,87.92 +eca_nfnet_l1,497.06,2060.113,1024,320,14.92,34.42,41.41 +convnext_small_384_in22ft1k,496.5,1031.206,512,384,25.58,63.37,50.22 +mixer_l16_224,495.85,2065.122,1024,224,44.6,41.69,208.2 +efficientnet_b5,493.19,519.054,256,456,10.46,98.86,30.39 +halonet_h1,492.19,520.115,256,256,3.0,51.17,8.1 +regnety_320,483.53,1058.87,512,224,32.34,30.26,145.05 +swin_large_patch4_window7_224,480.21,1599.271,768,224,34.53,54.94,196.53 +swinv2_small_window16_256,477.23,1072.842,512,256,12.82,66.29,49.73 +volo_d3_224,474.32,2158.852,1024,224,20.78,60.09,86.33 +resnetrs200,471.22,2173.072,1024,320,31.51,67.81,93.21 +tf_efficientnet_b5_ns,469.35,545.419,256,456,10.46,98.86,30.39 +tf_efficientnet_b5_ap,469.08,545.738,256,456,10.46,98.86,30.39 +tf_efficientnet_b5,468.97,545.864,256,456,10.46,98.86,30.39 +xcit_tiny_12_p8_384_dist,468.35,2186.374,1024,384,14.13,69.14,6.71 +tresnet_xl,466.16,2196.648,1024,224,15.17,15.34,78.44 +efficientnet_b3_gn,464.67,550.914,256,320,2.14,28.83,11.73 +xcit_large_24_p16_224_dist,454.83,2251.393,1024,224,35.86,47.27,189.1 +xcit_large_24_p16_224,454.8,2251.543,1024,224,35.86,47.27,189.1 +tf_efficientnetv2_m_in21ft1k,444.81,1726.544,768,480,24.76,89.84,54.14 +tf_efficientnetv2_m,444.79,1726.633,768,480,24.76,89.84,54.14 +xcit_small_24_p16_384_dist,426.37,2401.669,1024,384,26.72,68.58,47.67 +regnety_160,422.88,908.045,384,288,26.37,38.07,83.59 +nf_regnet_b5,413.3,1238.797,512,456,11.7,61.95,49.74 +swinv2_cr_tiny_384,408.94,625.992,256,384,15.34,161.01,28.33 +swinv2_cr_large_224,406.2,1890.673,768,224,35.1,78.42,196.68 +resnetv2_50x1_bitm,400.73,958.233,384,448,16.62,44.46,25.55 +regnetz_d8_evos,392.85,1954.947,768,320,7.03,38.92,23.46 +convmixer_1024_20_ks9_p14,390.62,2621.469,1024,224,5.55,5.51,24.38 +efficientnet_b3_g8_gn,373.24,685.874,256,320,3.2,28.83,14.25 +vit_large_patch16_224,370.72,2762.206,1024,224,61.6,63.52,304.33 +convnext_xlarge_in22ft1k,368.8,1388.275,512,224,60.98,57.5,350.2 +crossvit_15_dagger_408,368.65,694.421,256,408,21.45,95.05,28.5 +vit_base_patch16_18x2_224,361.92,2829.305,1024,224,52.51,71.38,256.73 +deit3_large_patch16_224_in21ft1k,358.3,2857.929,1024,224,61.6,63.52,304.37 +deit3_large_patch16_224,357.82,2861.791,1024,224,61.6,63.52,304.37 +swinv2_base_window16_256,346.22,1109.109,384,256,22.02,84.71,87.92 +swinv2_base_window12to16_192to256_22kft1k,345.97,1109.898,384,256,22.02,84.71,87.92 +nasnetalarge,345.75,1110.628,384,331,23.89,90.56,88.75 +convnext_base_384_in22ft1k,345.74,1110.63,384,384,45.21,84.49,88.59 +beit_large_patch16_224,343.01,2985.299,1024,224,61.6,63.52,304.43 +ssl_resnext101_32x16d,338.92,1510.65,512,224,36.27,51.18,194.03 +ig_resnext101_32x16d,338.75,1511.419,512,224,36.27,51.18,194.03 +swsl_resnext101_32x16d,338.52,1512.441,512,224,36.27,51.18,194.03 +tresnet_m_448,325.14,3149.347,1024,448,22.94,29.21,31.39 +pnasnet5large,323.98,1185.25,384,331,25.04,92.89,86.06 +regnetx_320,320.95,1196.437,384,224,31.81,36.3,107.81 +xcit_small_24_p8_224,319.26,3207.434,1024,224,35.81,90.78,47.63 +xcit_small_24_p8_224_dist,319.16,3208.44,1024,224,35.81,90.78,47.63 +volo_d1_384,315.83,1621.098,512,384,22.75,108.55,26.78 +nfnet_f1,306.71,3338.679,1024,320,35.97,46.77,132.63 +ecaresnet269d,304.87,3358.754,1024,352,50.25,101.25,102.09 +volo_d4_224,303.38,3375.331,1024,224,44.34,80.22,192.96 +xcit_medium_24_p16_384_dist,297.67,2580.013,768,384,47.39,91.64,84.4 +resnetrs270,296.93,3448.599,1024,352,51.13,105.48,129.86 +resnetv2_152x2_bit_teacher,290.64,2642.472,768,224,46.95,45.11,236.34 +vit_base_patch16_384,289.22,1327.696,384,384,55.54,101.56,86.86 +deit_base_patch16_384,289.04,1328.502,384,384,55.54,101.56,86.86 +deit_base_distilled_patch16_384,285.12,1346.806,384,384,55.65,101.82,87.63 +dm_nfnet_f1,282.58,3623.721,1024,320,35.97,46.77,132.63 +deit3_base_patch16_384,281.04,1366.341,384,384,55.54,101.56,86.88 +deit3_base_patch16_384_in21ft1k,280.92,1366.918,384,384,55.54,101.56,86.88 +efficientnet_b6,279.71,457.611,128,528,19.4,167.39,43.04 +cait_xxs24_384,275.0,3723.573,1024,384,9.63,122.66,12.03 +vit_large_patch14_224,271.58,3770.566,1024,224,81.08,88.79,304.2 +crossvit_18_dagger_408,269.56,712.259,192,408,32.47,124.87,44.61 +tf_efficientnet_b6_ap,267.5,478.495,128,528,19.4,167.39,43.04 +tf_efficientnet_b6,267.48,478.534,128,528,19.4,167.39,43.04 +tf_efficientnet_b6_ns,267.38,478.715,128,528,19.4,167.39,43.04 +efficientnetv2_l,254.55,2011.402,512,480,56.4,157.99,118.52 +resnetv2_101x1_bitm,252.46,1521.025,384,448,31.65,64.93,44.54 +tf_efficientnetv2_l,251.41,2036.496,512,480,56.4,157.99,118.52 +tf_efficientnetv2_l_in21ft1k,251.09,2039.122,512,480,56.4,157.99,118.52 +swinv2_cr_small_384,250.5,1021.951,256,384,29.7,298.03,49.7 +beit_base_patch16_384,248.36,1546.143,384,384,55.54,101.56,86.74 +xcit_tiny_24_p8_384_dist,246.6,4152.437,1024,384,27.05,132.95,12.11 +vit_large_r50_s32_384,246.12,2080.308,512,384,57.43,76.52,329.09 +eca_nfnet_l2,237.09,3239.214,768,384,30.05,68.28,56.72 +resmlp_big_24_224,228.25,4486.35,1024,224,100.23,87.31,129.14 +resmlp_big_24_224_in22ft1k,227.96,4491.908,1024,224,100.23,87.31,129.14 +resmlp_big_24_distilled_224,227.94,4492.471,1024,224,100.23,87.31,129.14 +xcit_medium_24_p8_224_dist,222.27,3455.29,768,224,63.53,121.23,84.32 +xcit_medium_24_p8_224,222.27,3455.239,768,224,63.53,121.23,84.32 +swin_base_patch4_window12_384,221.01,868.732,192,384,47.19,134.78,87.9 +swinv2_large_window12to16_192to256_22kft1k,212.32,1205.699,256,256,47.81,121.53,196.74 +xcit_small_12_p8_384_dist,207.32,1852.22,384,384,54.92,138.29,26.21 +resnest200e,201.89,2536.056,512,320,35.69,82.78,70.2 +volo_d5_224,200.39,5110.009,1024,224,72.4,118.11,295.46 +resnetrs350,194.78,3942.989,768,384,77.59,154.74,163.96 +convnext_large_384_in22ft1k,191.43,1337.313,256,384,101.1,126.74,197.77 +cait_xs24_384,190.0,4042.088,768,384,19.28,183.98,26.67 +vit_base_patch8_224,188.23,1360.04,256,224,78.22,161.69,86.58 +cait_xxs36_384,183.87,5569.221,1024,384,14.35,183.7,17.37 +swinv2_cr_base_384,178.69,1432.608,256,384,50.57,333.68,87.88 +vit_base_r50_s16_384,176.73,1448.509,256,384,67.43,135.03,98.95 +vit_base_resnet50_384,176.72,1448.639,256,384,67.43,135.03,98.95 +volo_d2_384,176.17,2179.696,384,384,46.17,184.51,58.87 +swinv2_cr_huge_224,175.72,2185.293,384,224,115.97,121.08,657.83 +nfnet_f2,172.68,5929.942,1024,352,63.22,79.06,193.78 +xcit_large_24_p16_384_dist,168.33,3041.628,512,384,105.35,137.17,189.1 +densenet264d_iabn,166.37,6155.083,1024,224,13.47,14.0,72.74 +efficientnet_b7,161.46,594.574,96,600,38.33,289.94,66.35 +efficientnetv2_xl,159.28,2410.894,384,512,93.85,247.32,208.12 +dm_nfnet_f2,159.16,4825.445,768,352,63.22,79.06,193.78 +tf_efficientnetv2_xl_in21ft1k,158.05,2429.572,384,512,93.85,247.32,208.12 +tf_efficientnet_b7,155.86,615.938,96,600,38.33,289.94,66.35 +tf_efficientnet_b7_ap,155.83,616.029,96,600,38.33,289.94,66.35 +tf_efficientnet_b7_ns,155.78,616.248,96,600,38.33,289.94,66.35 +tresnet_l_448,151.99,6737.079,1024,448,43.5,47.56,55.99 +cait_s24_384,148.32,3451.871,512,384,32.17,245.31,47.06 +vit_huge_patch14_224,146.38,6995.606,1024,224,167.4,139.41,632.05 +ig_resnext101_32x32d,143.03,1789.868,256,224,87.29,91.12,468.53 +resnetrs420,142.89,5374.778,768,416,108.45,213.79,191.89 +deit3_huge_patch14_224,142.28,7197.12,1024,224,167.4,139.41,632.13 +deit3_huge_patch14_224_in21ft1k,142.06,7208.264,1024,224,167.4,139.41,632.13 +eca_nfnet_l3,132.47,3864.977,512,448,52.55,118.4,72.04 +swin_large_patch4_window12_384,130.79,978.633,128,384,104.08,202.16,196.74 +convnext_xlarge_384_in22ft1k,126.14,2029.4,256,384,179.2,168.99,350.2 +xcit_large_24_p8_224,125.6,4076.305,512,224,141.23,181.56,188.93 +xcit_large_24_p8_224_dist,125.51,4079.48,512,224,141.23,181.56,188.93 +tresnet_xl_448,111.87,9153.659,1024,448,60.65,61.31,78.44 +xcit_small_24_p8_384_dist,108.62,3535.115,384,384,105.24,265.91,47.63 +swinv2_cr_large_384,108.25,1182.395,128,384,108.95,404.96,196.68 +efficientnet_b8,101.79,943.075,96,672,63.48,442.89,87.41 +resnetv2_50x3_bitm,101.1,1266.075,128,448,145.7,133.37,217.32 +cait_s36_384,99.17,5162.791,512,384,47.99,367.4,68.37 +tf_efficientnet_b8,98.82,971.416,96,672,63.48,442.89,87.41 +tf_efficientnet_b8_ap,98.81,971.518,96,672,63.48,442.89,87.41 +resnetv2_152x2_bit_teacher_384,98.49,2599.208,256,384,136.16,132.56,236.34 +vit_large_patch16_384,97.65,2621.481,256,384,191.21,270.24,304.72 +vit_giant_patch14_224,95.7,8025.142,768,224,267.18,192.64,1012.61 +deit3_large_patch16_384,94.92,2697.101,256,384,191.21,270.24,304.76 +deit3_large_patch16_384_in21ft1k,94.92,2697.083,256,384,191.21,270.24,304.76 +swinv2_base_window12to24_192to384_22kft1k,94.52,677.087,64,384,55.25,280.36,87.92 +nfnet_f3,93.84,8184.276,768,416,115.58,141.78,254.92 +resnest269e,93.31,4115.183,384,416,77.69,171.98,110.93 +dm_nfnet_f3,86.56,5914.801,512,416,115.58,141.78,254.92 +beit_large_patch16_384,84.77,3019.757,256,384,191.21,270.24,305.0 +volo_d3_448,76.33,2515.269,192,448,96.33,446.83,86.63 +xcit_medium_24_p8_384_dist,75.97,3369.835,256,384,186.67,354.73,84.32 +ig_resnext101_32x48d,74.47,2578.247,192,224,153.57,131.06,828.41 +resnetv2_152x2_bitm,72.95,2631.902,192,448,184.99,180.43,236.34 +tf_efficientnet_l2_ns_475,63.13,1013.713,64,475,172.11,609.89,480.31 +resnetv2_101x3_bitm,60.06,2131.166,128,448,280.33,194.78,387.93 +swinv2_large_window12to24_192to384_22kft1k,59.82,802.459,48,384,116.15,407.83,196.74 +vit_gigantic_patch14_224,57.64,8883.342,512,224,483.95,275.37,1844.44 +volo_d4_448,56.09,3423.322,192,448,197.13,527.35,193.41 +convmixer_1536_20,53.95,18979.912,1024,224,48.68,33.03,51.63 +swinv2_cr_giant_224,50.56,2531.46,128,224,483.85,309.15,2598.76 +nfnet_f4,49.93,10254.329,512,512,216.26,262.26,316.07 +swinv2_cr_huge_384,47.13,1357.909,64,384,352.04,583.18,657.94 +dm_nfnet_f4,45.97,8353.673,384,512,216.26,262.26,316.07 +xcit_large_24_p8_384_dist,42.84,4481.402,192,384,415.0,531.82,188.93 +volo_d5_448,38.62,3314.317,128,448,315.06,737.92,295.91 +nfnet_f5,37.03,10370.994,384,544,290.97,349.71,377.21 +dm_nfnet_f5,33.93,11318.026,384,544,290.97,349.71,377.21 +beit_large_patch16_512,33.87,2834.401,96,512,362.24,656.39,305.67 +cait_m36_384,32.22,7945.944,256,384,173.11,734.81,271.22 +nfnet_f6,28.33,13554.319,384,576,378.69,452.2,438.36 +volo_d5_512,26.99,4742.789,128,512,425.09,1105.37,296.09 +dm_nfnet_f6,26.14,9792.719,256,576,378.69,452.2,438.36 +resnetv2_152x4_bitm,24.34,2629.892,64,480,844.84,414.26,936.53 +efficientnet_l2,23.12,1037.889,24,800,479.12,1707.39,480.31 +tf_efficientnet_l2_ns,22.7,1057.422,24,800,479.12,1707.39,480.31 +nfnet_f7,22.34,11460.175,256,608,480.39,570.85,499.5 +swinv2_cr_giant_384,14.63,2187.208,32,384,1450.71,1394.86,2598.76 +cait_m48_448,13.64,9385.159,128,448,329.41,1708.23,356.46 diff --git a/results/benchmark-train-amp-nchw-pt110-cu113-rtx3090.csv b/results/benchmark-train-amp-nchw-pt110-cu113-rtx3090.csv deleted file mode 100644 index f13f2980..00000000 --- a/results/benchmark-train-amp-nchw-pt110-cu113-rtx3090.csv +++ /dev/null @@ -1,756 +0,0 @@ -model,train_samples_per_sec,train_step_time,train_batch_size,train_img_size,param_count -tinynet_e,8879.06,56.99,512,106,2.04 -mobilenetv3_small_050,6486.16,78.215,512,224,1.59 -tf_mobilenetv3_small_minimal_100,6286.95,80.898,512,224,2.04 -lcnet_035,5388.39,94.526,512,224,1.64 -levit_128s,5340.79,94.942,512,224,7.78 -mobilenetv3_small_075,5188.12,97.983,512,224,2.04 -lcnet_050,4931.51,103.34,512,224,1.88 -tf_mobilenetv3_small_075,4918.54,103.391,512,224,2.04 -mobilenetv3_small_100,4776.47,106.481,512,224,2.54 -tf_mobilenetv3_small_100,4548.9,111.828,512,224,2.54 -tinynet_d,4535.94,112.125,512,152,2.34 -mixer_s32_224,4002.68,127.361,512,224,19.1 -levit_128,3906.35,129.937,512,224,9.21 -vit_small_patch32_224,3720.28,136.814,512,224,22.88 -lcnet_075,3708.14,137.591,512,224,2.36 -vit_tiny_r_s16_p8_224,3450.55,147.535,512,224,6.34 -regnetx_002,3409.48,149.489,512,224,2.68 -levit_192,3369.4,150.83,512,224,10.95 -mnasnet_small,3194.94,159.346,512,224,2.03 -regnety_002,3152.93,161.41,512,224,3.16 -lcnet_100,3112.12,164.023,512,224,2.95 -mobilenetv2_035,3034.35,167.951,512,224,1.68 -gernet_s,2945.06,173.156,512,224,8.17 -gluon_resnet18_v1b,2722.13,187.746,512,224,11.69 -resnet18,2720.28,187.878,512,224,11.69 -swsl_resnet18,2718.44,187.99,512,224,11.69 -ssl_resnet18,2711.89,188.46,512,224,11.69 -mobilenetv2_050,2618.63,194.751,512,224,1.97 -levit_256,2590.96,196.476,512,224,18.89 -semnasnet_050,2528.95,201.569,512,224,2.08 -regnetx_004,2522.75,201.894,512,224,5.16 -mnasnet_050,2522.58,202.188,512,224,2.22 -seresnet18,2507.84,203.663,512,224,11.78 -ese_vovnet19b_slim_dw,2471.49,206.677,512,224,1.9 -legacy_seresnet18,2441.93,209.163,512,224,11.78 -tinynet_c,2430.81,209.624,512,184,2.46 -tf_mobilenetv3_large_minimal_100,2297.77,222.108,512,224,3.92 -lcnet_150,2274.7,224.596,512,224,4.5 -levit_256d,2246.11,226.444,512,224,26.21 -ghostnet_050,2164.08,235.253,512,224,2.59 -mobilenetv3_large_075,2163.25,235.816,512,224,3.99 -resnet18d,2077.18,246.121,512,224,11.71 -tf_mobilenetv3_large_075,2064.86,247.051,512,224,3.99 -regnetx_006,2039.62,250.217,512,224,6.2 -ese_vovnet19b_slim,2002.06,255.364,512,224,3.17 -mobilenetv3_rw,1974.38,258.462,512,224,5.48 -mobilenetv3_large_100_miil,1968.34,259.245,512,224,5.48 -mobilenetv3_large_100,1965.11,259.678,512,224,5.48 -mnasnet_075,1898.08,268.968,512,224,3.17 -mobilenetv2_075,1880.91,271.408,512,224,2.64 -tf_mobilenetv3_large_100,1872.32,272.582,512,224,5.48 -tf_efficientnetv2_b0,1868.24,272.852,512,224,7.14 -resnetblur18,1851.92,276.12,512,224,11.69 -regnety_004,1839.55,277.22,512,224,4.34 -semnasnet_075,1812.64,281.537,512,224,2.91 -regnety_006,1807.53,282.196,512,224,6.06 -skresnet18,1781.57,286.76,512,224,11.96 -mobilenetv2_100,1759.59,290.188,512,224,3.5 -mnasnet_b1,1711.38,298.386,512,224,4.38 -mnasnet_100,1703.75,299.741,512,224,4.38 -vit_tiny_patch16_224,1703.5,299.738,512,224,5.72 -deit_tiny_patch16_224,1700.58,300.234,512,224,5.72 -tinynet_b,1695.36,300.958,512,188,3.73 -hardcorenas_a,1688.73,302.486,512,224,5.26 -hardcorenas_b,1681.38,303.598,512,224,5.18 -deit_tiny_distilled_patch16_224,1676.33,304.592,512,224,5.91 -regnetx_008,1660.21,307.58,512,224,7.26 -semnasnet_100,1660.21,307.494,512,224,3.89 -mnasnet_a1,1660.16,307.488,512,224,3.89 -levit_384,1645.5,310.035,512,224,39.13 -visformer_tiny,1629.45,313.55,512,224,10.32 -gluon_resnet34_v1b,1628.8,313.768,512,224,21.8 -tv_resnet34,1628.63,313.804,512,224,21.8 -resnet34,1618.43,315.788,512,224,21.8 -mixer_b32_224,1614.41,316.375,512,224,60.29 -hardcorenas_c,1606.09,317.82,512,224,5.52 -spnasnet_100,1581.9,322.7,512,224,4.42 -hardcorenas_d,1573.64,324.168,512,224,7.5 -pit_ti_distilled_224,1567.79,325.678,512,224,5.1 -pit_ti_224,1567.05,325.843,512,224,4.85 -vit_base_patch32_224,1566.16,326.106,512,224,88.22 -vit_base_patch32_224_sam,1565.94,326.137,512,224,88.22 -ghostnet_100,1561.28,326.61,512,224,5.18 -regnety_008,1549.78,329.38,512,224,6.26 -resmlp_12_distilled_224,1540.69,331.527,512,224,15.35 -resmlp_12_224,1540.68,331.535,512,224,15.35 -seresnet34,1491.24,342.456,512,224,21.96 -nf_regnet_b0,1463.76,348.603,512,256,8.76 -gernet_m,1452.99,351.696,512,224,21.14 -legacy_seresnet34,1444.09,353.657,512,224,21.96 -ese_vovnet19b_dw,1432.57,356.897,512,224,6.54 -nf_resnet26,1427.35,358.203,512,224,16.0 -tinynet_a,1409.24,362.071,512,192,6.19 -dla46_c,1404.15,363.911,512,224,1.3 -rexnetr_100,1384.43,276.261,384,224,4.88 -mobilenetv2_110d,1383.76,276.51,384,224,4.52 -efficientnet_lite0,1382.82,369.515,512,224,4.65 -rexnet_100,1378.22,277.499,384,224,4.8 -resnet34d,1368.6,373.438,512,224,21.82 -hardcorenas_f,1363.96,374.257,512,224,8.2 -xcit_nano_12_p16_224_dist,1357.57,375.351,512,224,3.05 -xcit_nano_12_p16_224,1356.26,375.722,512,224,3.05 -selecsls42,1352.83,377.829,512,224,30.35 -ghostnet_130,1348.59,378.322,512,224,7.36 -selecsls42b,1347.97,379.197,512,224,32.46 -mixer_s16_224,1328.86,384.74,512,224,18.53 -tf_efficientnet_lite0,1326.3,385.288,512,224,4.65 -regnetz_005,1322.96,385.624,512,224,7.12 -resnet26,1320.55,387.258,512,224,16.0 -hardcorenas_e,1317.58,387.482,512,224,8.07 -hrnet_w18_small,1302.47,391.734,512,224,13.19 -pit_xs_distilled_224,1268.5,402.739,512,224,11.0 -pit_xs_224,1268.42,402.775,512,224,10.62 -fbnetc_100,1266.68,403.231,512,224,5.57 -mnasnet_140,1263.67,404.387,512,224,7.12 -mobilenetv2_140,1253.56,305.536,384,224,6.11 -vit_small_patch32_384,1234.94,413.769,512,384,22.92 -efficientnet_b0,1229.26,311.326,384,224,5.29 -poolformer_s12,1218.66,419.43,512,224,11.92 -semnasnet_140,1213.3,421.085,512,224,6.11 -nf_seresnet26,1200.27,425.903,512,224,17.4 -vit_tiny_r_s16_p8_384,1194.12,320.732,384,384,6.36 -tf_efficientnetv2_b1,1189.33,321.432,384,240,8.14 -gmixer_12_224,1181.89,432.408,512,224,12.7 -repvgg_b0,1180.49,432.688,512,224,15.82 -tf_efficientnet_b0_ap,1177.13,325.127,384,224,5.29 -tf_efficientnet_b0,1176.58,325.256,384,224,5.29 -tf_efficientnet_b0_ns,1176.09,325.406,384,224,5.29 -efficientnet_b1_pruned,1160.78,439.616,512,240,6.33 -selecsls60,1153.95,442.796,512,224,30.67 -selecsls60b,1150.77,444.044,512,224,32.77 -resnet26d,1125.05,454.584,512,224,16.01 -nf_ecaresnet26,1118.2,457.322,512,224,16.0 -mixnet_s,1099.59,464.39,512,224,4.13 -rexnetr_130,1097.48,232.14,256,224,7.61 -dla34,1070.28,477.798,512,224,15.74 -dla46x_c,1057.9,483.219,512,224,1.07 -rexnet_130,1047.2,243.344,256,224,7.56 -regnetx_016,1042.62,490.182,512,224,9.19 -tf_mixnet_s,1040.0,491.07,512,224,4.13 -mobilenetv2_120d,1039.92,245.01,256,224,5.83 -skresnet34,1030.78,495.577,512,224,22.28 -dla60x_c,1018.3,501.873,512,224,1.32 -ecaresnet50d_pruned,1010.79,505.611,512,224,19.94 -gernet_l,1008.74,506.703,512,256,31.08 -mobilevit_xxs,994.64,384.944,384,256,1.27 -xcit_tiny_12_p16_224,994.0,513.339,512,224,6.72 -xcit_tiny_12_p16_224_dist,993.15,513.793,512,224,6.72 -efficientnet_b0_g16_evos,992.08,385.991,384,224,8.11 -rexnetr_150,974.49,261.552,256,224,9.78 -convnext_nano_hnf,957.8,400.126,384,224,15.59 -crossvit_tiny_240,953.54,401.134,384,240,7.01 -crossvit_9_240,948.17,403.562,384,240,8.55 -rexnet_150,931.33,273.747,256,224,9.73 -vit_base2_patch32_256,930.69,549.32,512,256,119.46 -repvgg_a2,930.45,549.419,512,224,28.21 -legacy_seresnext26_32x4d,924.87,552.965,512,224,16.79 -regnety_016,921.92,553.59,512,224,11.2 -efficientnet_lite1,920.32,277.193,256,240,5.42 -gmlp_ti16_224,915.04,418.12,384,224,5.87 -convit_tiny,914.83,418.772,384,224,5.71 -efficientnet_es_pruned,914.62,559.049,512,224,5.44 -crossvit_9_dagger_240,914.01,418.663,384,240,8.78 -efficientnet_es,913.84,559.524,512,224,5.44 -resnest14d,902.54,566.834,512,224,10.61 -tf_efficientnet_es,895.9,570.736,512,224,5.44 -vit_small_patch16_224,886.44,432.354,384,224,22.05 -deit_small_patch16_224,886.38,432.371,384,224,22.05 -resnetv2_50,885.9,577.167,512,224,25.55 -tf_efficientnet_lite1,884.99,288.297,256,240,5.42 -resnext26ts,882.6,434.57,384,256,10.3 -resnet26t,880.32,581.109,512,256,16.01 -nf_regnet_b1,876.86,582.443,512,288,10.22 -tf_efficientnetv2_b2,873.82,291.458,256,260,10.1 -nf_regnet_b2,872.25,585.395,512,272,14.31 -deit_small_distilled_patch16_224,870.96,440.043,384,224,22.44 -eca_resnext26ts,854.22,299.135,256,256,10.3 -seresnext26ts,848.06,301.208,256,256,10.39 -gluon_resnet50_v1b,836.3,458.36,384,224,25.56 -swsl_resnet50,836.28,458.365,384,224,25.56 -tv_resnet50,835.63,458.72,384,224,25.56 -resnet50,833.11,460.106,384,224,25.56 -botnet26t_256,831.36,461.332,384,256,12.49 -ssl_resnet50,830.95,461.318,384,224,25.56 -gcresnext26ts,830.68,307.354,256,256,10.48 -seresnext26tn_32x4d,830.61,461.636,384,224,16.81 -seresnext26t_32x4d,830.27,461.827,384,224,16.81 -seresnext26d_32x4d,828.27,462.949,384,224,16.81 -pit_s_224,823.52,309.982,256,224,23.46 -vgg11,823.03,621.921,512,224,132.86 -pit_s_distilled_224,820.99,310.896,256,224,24.04 -halonet26t,808.46,474.411,384,256,12.48 -eca_botnext26ts_256,804.84,317.488,256,256,10.59 -vit_small_resnet26d_224,799.3,479.391,384,224,63.61 -resnetv2_50t,795.78,642.594,512,224,25.57 -ecaresnext26t_32x4d,794.24,482.933,384,224,15.41 -resnetv2_50d,793.28,644.617,512,224,25.57 -ecaresnext50t_32x4d,791.08,484.877,384,224,15.41 -tresnet_m,787.35,647.607,512,224,31.39 -vovnet39a,782.12,654.018,512,224,22.6 -efficientnet_b0_gn,780.55,326.912,256,224,5.29 -fbnetv3_d,780.39,326.274,256,256,10.31 -eca_halonext26ts,780.25,327.496,256,256,10.76 -fbnetv3_b,780.18,490.58,384,256,8.6 -cspresnet50,779.41,491.838,384,256,21.62 -ecaresnet101d_pruned,774.28,659.497,512,224,24.88 -efficientnet_cc_b0_8e,770.73,497.068,384,224,24.01 -gluon_resnet50_v1c,770.17,497.757,384,224,25.58 -efficientnet_cc_b0_4e,768.45,498.536,384,224,13.31 -ecaresnetlight,767.52,666.18,512,224,30.16 -cspresnext50,767.32,499.601,384,224,20.57 -mixnet_m,767.21,499.005,384,224,5.01 -efficientnet_b2_pruned,763.33,333.903,256,260,8.31 -resnet50t,754.86,507.852,384,224,25.57 -gluon_resnet50_v1d,754.57,508.055,384,224,25.58 -resnet50d,753.37,508.854,384,224,25.58 -resmlp_24_224,752.46,338.709,256,224,30.02 -resmlp_24_distilled_224,751.46,339.201,256,224,30.02 -ese_vovnet39b,748.27,512.528,384,224,24.57 -tf_efficientnet_cc_b0_8e,747.26,512.722,384,224,24.01 -tf_efficientnet_cc_b0_4e,746.74,513.086,384,224,13.31 -resnet32ts,744.48,343.29,256,256,17.96 -visformer_small,743.67,515.696,384,224,40.22 -legacy_seresnet50,743.56,515.327,384,224,28.09 -dpn68b,738.91,518.504,384,224,12.61 -selecsls84,736.93,693.544,512,224,50.95 -resnet33ts,736.41,347.04,256,256,19.68 -tf_mixnet_m,730.05,524.465,384,224,5.01 -nf_seresnet50,727.19,526.873,384,224,28.09 -rexnetr_200,725.21,263.618,192,224,16.52 -res2net50_48w_2s,723.44,529.975,384,224,25.29 -dpn68,721.43,531.156,384,224,12.61 -lambda_resnet26t,720.18,532.596,384,256,10.96 -seresnet50,719.22,532.776,384,224,28.09 -tf_efficientnet_b1_ns,717.68,355.196,256,240,7.79 -tf_efficientnet_b1,717.65,355.204,256,240,7.79 -tf_efficientnet_b1_ap,717.6,355.242,256,240,7.79 -eca_resnet33ts,713.27,358.233,256,256,19.68 -bat_resnext26ts,709.94,359.448,256,256,10.73 -seresnet33ts,708.46,360.554,256,256,19.78 -resnetblur50,706.03,543.087,384,224,25.56 -cspresnet50d,704.69,544.074,384,256,21.64 -rexnet_200,702.3,272.253,192,224,16.37 -eca_vovnet39b,698.49,732.369,512,224,22.6 -cspresnet50w,698.43,548.944,384,256,28.12 -dla60,695.38,551.258,384,224,22.04 -efficientnet_b1,694.5,367.105,256,256,7.79 -efficientnet_lite2,691.09,369.477,256,260,6.09 -tv_densenet121,688.36,370.145,256,224,7.98 -vgg11_bn,688.31,371.701,256,224,132.87 -gcresnet33ts,687.54,371.346,256,256,19.88 -densenet121,686.73,371.056,256,224,7.98 -resnest26d,682.74,561.689,384,224,17.07 -resnetaa50d,680.45,563.474,384,224,25.58 -gluon_resnet50_v1s,673.44,569.389,384,224,25.68 -hrnet_w18_small_v2,669.83,761.985,512,224,15.6 -nf_ecaresnet50,669.55,572.548,384,224,25.56 -tf_efficientnet_lite2,667.12,382.773,256,260,6.09 -vit_base_resnet26d_224,663.97,577.082,384,224,101.4 -vit_small_r26_s32_224,661.78,385.595,256,224,36.43 -lambda_resnet26rpt_256,660.67,193.152,128,256,10.99 -efficientnet_b0_g8_gn,657.99,387.987,256,224,6.56 -seresnet50t,654.75,389.823,256,224,28.1 -resnext50_32x4d,651.94,588.217,384,224,25.03 -swsl_resnext50_32x4d,651.54,588.552,384,224,25.03 -gluon_resnext50_32x4d,651.5,588.601,384,224,25.03 -ssl_resnext50_32x4d,651.06,588.971,384,224,25.03 -tv_resnext50_32x4d,651.04,589.025,384,224,25.03 -haloregnetz_b,649.9,392.411,256,224,11.68 -resnetrs50,647.82,591.571,384,224,35.69 -regnetx_032,644.99,594.128,384,224,15.3 -resnetblur50d,643.36,397.048,256,224,25.58 -densenet121d,640.21,398.026,256,224,8.0 -mobilevit_xs,636.32,300.601,192,256,2.32 -res2net50_26w_4s,636.08,401.175,256,224,25.7 -ese_vovnet57b,632.89,605.833,384,224,38.61 -convnext_tiny_hnf,631.3,404.531,256,224,28.59 -skresnet50,629.62,405.227,256,224,25.8 -densenetblur121d,620.91,410.489,256,224,8.0 -poolformer_s24,618.55,412.632,256,224,21.39 -ecaresnet50d,617.9,413.387,256,224,25.58 -gluon_inception_v3,602.04,636.443,384,299,23.83 -tf_inception_v3,601.78,636.737,384,299,23.83 -resnext50d_32x4d,599.81,425.968,256,224,25.05 -adv_inception_v3,598.91,639.776,384,299,23.83 -inception_v3,597.68,641.096,384,299,23.83 -seresnetaa50d,595.51,428.742,256,224,28.11 -sehalonet33ts,593.18,430.755,256,256,13.69 -coat_lite_tiny,588.45,651.687,384,224,5.72 -efficientnet_b3_pruned,588.04,433.698,256,300,9.86 -mixnet_l,587.47,434.23,256,224,7.33 -gmixer_24_224,586.46,435.043,256,224,24.72 -gcresnet50t,584.74,436.344,256,256,25.9 -vovnet57a,583.53,876.573,512,224,36.64 -skresnet50d,581.8,438.63,256,224,25.82 -resnetv2_50x1_bit_distilled,579.51,330.493,192,224,25.55 -res2next50,576.25,443.0,256,224,24.67 -seresnext50_32x4d,575.09,444.01,256,224,27.56 -cspresnext50_iabn,574.6,666.024,384,256,20.57 -legacy_seresnext50_32x4d,573.45,445.299,256,224,27.56 -res2net50_14w_8s,572.23,445.23,256,224,25.06 -gluon_seresnext50_32x4d,572.14,446.313,256,224,27.56 -repvgg_b1g4,571.09,895.496,512,224,39.97 -convnext_tiny,568.67,449.214,256,224,28.59 -resnest50d_1s4x24d,568.37,449.124,256,224,25.68 -vgg13,565.29,679.111,384,224,133.05 -densenet169,564.44,451.109,256,224,14.15 -coat_lite_mini,560.18,684.613,384,224,11.01 -tf_mixnet_l,559.29,456.201,256,224,7.33 -dla60_res2net,558.91,456.605,256,224,20.85 -darknet53,555.4,460.146,256,256,41.61 -dla60x,553.72,461.36,256,224,17.35 -efficientnet_em,553.62,692.657,384,240,6.9 -regnetx_040,551.95,694.615,384,224,22.12 -tf_efficientnet_em,550.96,463.679,256,240,6.9 -nf_resnet101,550.06,696.472,384,224,44.55 -nf_regnet_b3,545.32,467.686,256,320,18.59 -tf_efficientnet_b2_ns,542.89,352.148,192,260,9.11 -tf_efficientnet_b2_ap,542.72,352.279,192,260,9.11 -tf_efficientnet_b2,542.33,352.563,192,260,9.11 -resnetv2_101,541.77,470.948,256,224,44.54 -tf_efficientnetv2_b3,537.24,355.668,192,300,14.36 -gcresnext50ts,536.7,356.26,192,256,15.67 -nf_resnet50,535.99,715.561,384,288,25.56 -xcit_small_12_p16_224_dist,535.18,476.598,256,224,26.25 -xcit_small_12_p16_224,535.12,476.63,256,224,26.25 -sebotnet33ts_256,533.03,239.342,128,256,13.7 -efficientnetv2_rw_t,527.89,361.618,192,288,13.65 -resnet101,526.2,484.988,256,224,44.55 -twins_svt_small,526.18,484.993,256,224,24.06 -tv_resnet101,525.84,485.332,256,224,44.55 -resnet50_gn,525.26,364.696,192,224,25.56 -gluon_resnet101_v1b,524.51,486.543,256,224,44.55 -mobilevit_s,521.06,367.349,192,256,5.58 -crossvit_small_240,519.76,367.784,192,240,26.86 -xcit_tiny_24_p16_224,519.69,489.334,256,224,12.12 -xcit_tiny_24_p16_224_dist,519.36,489.596,256,224,12.12 -vit_base_r26_s32_224,518.41,369.094,192,224,101.38 -mixer_b16_224,512.16,499.054,256,224,59.88 -mixer_b16_224_miil,512.15,499.069,256,224,59.88 -gmlp_s16_224,510.63,374.487,192,224,19.42 -resnetv2_101d,506.75,503.627,256,224,44.56 -vit_base_resnet50d_224,506.41,503.941,256,224,110.97 -dla60_res2next,504.89,505.645,256,224,17.03 -vit_base_patch32_384,503.41,507.725,256,384,88.3 -repvgg_b1,499.68,1023.594,512,224,57.42 -resmlp_36_distilled_224,499.65,382.104,192,224,44.69 -resmlp_36_224,499.61,382.157,192,224,44.69 -gluon_resnet101_v1c,499.33,511.143,256,224,44.57 -vit_large_patch32_224,498.76,511.726,256,224,306.54 -efficientnet_b2a,498.46,383.699,192,288,9.11 -efficientnet_b2,498.23,383.892,192,288,9.11 -semobilevit_s,498.08,384.196,192,256,5.74 -wide_resnet50_2,492.85,518.616,256,224,68.88 -gluon_resnet101_v1d,492.69,518.053,256,224,44.57 -mixer_l32_224,486.84,392.903,192,224,206.94 -efficientnet_cc_b1_8e,485.45,525.706,256,240,39.72 -cspdarknet53,485.41,526.351,256,256,27.64 -gc_efficientnetv2_rw_t,484.77,393.323,192,288,13.68 -cait_xxs24_224,483.07,527.475,256,224,11.96 -resnest50d,481.14,530.778,256,224,27.48 -res2net50_26w_6s,478.7,533.037,256,224,37.05 -crossvit_15_240,477.76,400.069,192,240,27.53 -dla102,477.62,534.469,256,224,33.27 -ecaresnet26t,476.78,536.378,256,320,16.01 -regnetz_b16,474.17,403.475,192,288,9.72 -tf_efficientnet_cc_b1_8e,473.85,538.615,256,240,39.72 -xcit_nano_12_p16_384_dist,473.63,538.718,256,384,3.05 -cspdarknet53_iabn,473.06,809.288,384,256,27.64 -convnext_tiny_hnfd,470.51,543.084,256,224,28.63 -vgg13_bn,465.58,549.581,256,224,133.05 -vgg16,464.87,825.812,384,224,138.36 -regnetx_080,463.41,827.528,384,224,39.57 -crossvit_15_dagger_240,461.34,414.345,192,240,28.21 -resnetaa101d,460.14,554.755,256,224,44.57 -lambda_resnet50ts,459.6,416.745,192,256,21.54 -halonet50ts,459.3,417.05,192,256,22.73 -legacy_seresnet101,458.51,556.133,256,224,49.33 -gluon_resnet101_v1s,457.44,558.089,256,224,44.67 -densenet201,452.47,421.386,192,224,20.01 -swin_tiny_patch4_window7_224,451.01,566.618,256,224,28.29 -seresnet101,447.55,569.776,256,224,49.33 -resnetblur101d,441.76,577.918,256,224,44.57 -nf_seresnet101,440.27,579.119,256,224,49.33 -mixnet_xl,435.11,586.493,256,224,11.9 -twins_pcpvt_small,428.18,596.275,256,224,24.11 -nfnet_l0,422.47,604.781,256,288,35.07 -skresnext50_32x4d,418.8,609.905,256,224,27.48 -swin_s3_tiny_224,418.5,457.809,192,224,28.33 -gluon_resnext101_32x4d,418.3,610.447,256,224,44.18 -swsl_resnext101_32x4d,418.28,610.459,256,224,44.18 -ssl_resnext101_32x4d,418.21,610.626,256,224,44.18 -resnext101_32x4d,418.12,610.73,256,224,44.18 -vit_tiny_patch16_384,415.69,307.09,128,384,5.79 -botnet50ts_256,415.68,306.991,128,256,22.74 -poolformer_s36,413.64,462.249,192,224,30.86 -ese_vovnet39b_evos,408.73,312.204,128,224,24.58 -convit_small,408.52,468.993,192,224,27.78 -res2net101_26w_4s,406.07,470.321,192,224,45.21 -eca_nfnet_l0,404.15,632.409,256,288,24.14 -efficientnet_lite3,403.71,315.975,128,300,8.2 -halo2botnet50ts_256,403.26,316.425,128,256,22.64 -tresnet_l,403.06,1266.831,512,224,55.99 -resnet51q,399.11,480.193,192,288,35.7 -nf_ecaresnet101,394.48,647.098,256,224,44.55 -dla102x,393.78,486.022,192,224,26.31 -vgg19,393.77,974.937,384,224,143.67 -res2net50_26w_8s,393.74,485.439,192,224,48.4 -lamhalobotnet50ts_256,392.54,325.068,128,256,22.57 -regnetx_064,392.18,651.888,256,224,26.21 -regnety_032,391.93,651.749,256,288,19.44 -tf_efficientnet_lite3,390.65,326.582,128,300,8.2 -vgg16_bn,389.79,656.438,256,224,138.37 -xception,385.34,331.396,128,299,22.86 -resnetv2_152,380.13,671.312,256,224,60.19 -swin_v2_cr_tiny_224,379.43,504.758,192,224,28.33 -ecaresnet101d,378.93,673.854,256,224,44.57 -resnest50d_4s2x40d,378.25,675.481,256,224,30.42 -repvgg_b2g4,377.89,1353.806,512,224,61.76 -ese_vovnet99b,373.42,684.063,256,224,63.2 -tv_resnet152,371.1,515.112,192,224,60.19 -resnet152,371.02,515.239,192,224,60.19 -convnext_small,370.63,516.315,192,224,50.22 -xcit_nano_12_p8_224,370.09,689.984,256,224,3.05 -xcit_nano_12_p8_224_dist,369.33,691.413,256,224,3.05 -gluon_resnet152_v1b,369.24,517.744,192,224,60.19 -nfnet_f0,367.34,695.748,256,256,71.49 -gluon_seresnext101_32x4d,366.5,521.688,192,224,48.96 -seresnext101_32x4d,366.15,522.18,192,224,48.96 -legacy_seresnext101_32x4d,365.14,523.663,192,224,48.96 -vit_base_patch16_224_miil,364.71,350.199,128,224,86.54 -nest_tiny,363.32,351.416,128,224,17.06 -resnetv2_152d,361.72,528.569,192,224,60.2 -vit_small_resnet50d_s16_224,361.26,530.264,192,224,57.53 -resnet61q,360.88,353.672,128,288,36.85 -jx_nest_tiny,360.53,354.122,128,224,17.06 -swin_v2_cr_tiny_ns_224,360.48,531.298,192,224,28.33 -vit_base_patch16_224,359.03,355.693,128,224,86.57 -vit_base_patch16_224_sam,358.97,355.726,128,224,86.57 -ese_vovnet99b_iabn,358.47,1068.125,384,224,63.2 -gluon_resnet152_v1c,358.0,534.017,192,224,60.21 -deit_base_patch16_224,356.65,358.076,128,224,86.57 -regnety_040,355.37,538.804,192,288,20.65 -gluon_resnet152_v1d,353.37,541.005,192,224,60.21 -regnety_040s_gn,351.45,362.7,128,224,20.65 -deit_base_distilled_patch16_224,351.33,363.49,128,224,87.34 -resnetv2_50d_frn,347.92,366.764,128,224,25.59 -crossvit_18_240,347.71,366.132,128,240,43.27 -xcit_tiny_12_p16_384_dist,343.61,557.009,192,384,6.72 -xception41p,343.15,372.168,128,299,26.91 -volo_d1_224,342.86,371.99,128,224,26.63 -regnetv_040,340.89,374.038,128,288,20.64 -hrnet_w18,340.14,747.884,256,224,21.3 -repvgg_b2,339.58,1506.684,512,224,89.02 -fbnetv3_g,338.81,375.801,128,288,16.62 -crossvit_18_dagger_240,336.48,378.386,128,240,44.27 -vgg19_bn,336.38,760.656,256,224,143.68 -gluon_resnet152_v1s,335.54,569.962,192,224,60.32 -dla169,331.7,576.335,192,224,53.39 -densenet161,329.95,385.629,128,224,28.68 -dm_nfnet_f0,329.15,776.517,256,256,71.49 -coat_lite_small,327.59,584.625,192,224,19.84 -resnetv2_50d_gn,326.94,390.7,128,288,25.57 -beit_base_patch16_224,326.19,391.317,128,224,86.53 -repvgg_b3g4,321.01,1195.136,384,224,83.83 -tf_efficientnet_b3_ns,318.86,399.788,128,300,12.23 -tf_efficientnet_b3,318.7,399.98,128,300,12.23 -tf_efficientnet_b3_ap,318.42,400.336,128,300,12.23 -legacy_seresnet152,315.73,604.891,192,224,66.82 -dpn92,314.66,812.131,256,224,37.67 -inception_v4,312.7,611.827,192,299,42.68 -efficientnet_b3,312.0,408.597,128,320,12.23 -efficientnet_b3a,311.95,408.654,128,320,12.23 -twins_pcpvt_base,311.39,613.825,192,224,43.83 -convmixer_1024_20_ks9_p14,310.04,824.873,256,224,24.38 -regnetx_120,309.97,824.929,256,224,46.11 -cait_xxs36_224,308.02,411.825,128,224,17.3 -ecaresnet50t,306.62,416.516,128,320,25.57 -hrnet_w32,305.43,623.994,192,224,41.23 -seresnet152,303.38,418.64,128,224,66.82 -twins_svt_base,303.13,420.211,128,224,56.07 -regnetz_c16,302.01,422.387,128,320,13.46 -hrnet_w30,301.1,845.453,256,224,37.71 -tresnet_xl,294.8,1299.032,384,224,78.44 -swin_small_patch4_window7_224,294.09,433.317,128,224,49.61 -pit_b_224,291.77,328.073,96,224,73.76 -xception41,291.75,437.519,128,299,26.97 -regnety_120,291.47,657.427,192,224,51.82 -pit_b_distilled_224,289.77,330.344,96,224,74.79 -wide_resnet101_2,288.45,664.093,192,224,126.89 -nf_regnet_b4,286.33,444.906,128,384,30.21 -mixnet_xxl,281.29,453.113,128,224,23.96 -poolformer_m36,278.5,457.747,128,224,56.17 -xcit_small_24_p16_224_dist,276.84,459.031,128,224,47.67 -repvgg_b3,276.53,1387.56,384,224,123.09 -xcit_small_24_p16_224,275.37,461.371,128,224,47.67 -convnext_small_in22ft1k,274.88,463.928,128,224,88.59 -convnext_base,274.83,464.011,128,224,88.59 -convnext_tiny_in22ft1k,273.31,466.623,128,224,88.59 -convnext_base_in22ft1k,272.88,467.352,128,224,88.59 -gluon_resnext101_64x4d,268.43,475.336,128,224,83.46 -dla102x2,266.91,478.025,128,224,41.28 -cait_s24_224,265.32,479.979,128,224,46.92 -resnet200,265.02,479.979,128,224,64.67 -vit_small_patch16_18x2_224,263.71,482.808,128,224,64.67 -regnetx_160,261.64,732.791,192,224,54.28 -xcit_tiny_12_p8_224_dist,261.1,488.495,128,224,6.71 -xcit_tiny_12_p8_224,260.74,489.138,128,224,6.71 -vit_small_patch16_36x1_224,259.32,367.632,96,224,64.67 -xception65p,258.71,493.479,128,299,39.82 -ens_adv_inception_resnet_v2,255.7,747.458,192,299,55.84 -resnetv2_50d_evob,254.24,376.389,96,224,25.59 -inception_resnet_v2,254.09,752.309,192,299,55.84 -efficientnet_el,253.35,504.154,128,300,10.59 -efficientnet_el_pruned,253.34,504.171,128,300,10.59 -resnext101_32x8d,252.02,506.385,128,224,88.79 -swsl_resnext101_32x8d,252.02,506.295,128,224,88.79 -ssl_resnext101_32x8d,251.67,507.107,128,224,88.79 -resnetrs101,251.09,507.486,128,288,63.62 -ig_resnext101_32x8d,250.58,509.299,128,224,88.79 -dpn98,249.31,511.881,128,224,61.57 -tf_efficientnet_el,249.14,512.694,128,300,10.59 -efficientnetv2_s,245.1,389.491,96,384,21.46 -gluon_seresnext101_64x4d,243.69,523.04,128,224,88.23 -tf_efficientnetv2_s,243.67,391.823,96,384,21.46 -tf_efficientnetv2_s_in21ft1k,242.75,393.147,96,384,21.46 -gmlp_b16_224,241.6,395.795,96,224,73.08 -resnet101d,240.1,531.541,128,320,44.57 -nest_small,238.81,400.33,96,224,38.35 -resnest101e,237.62,536.114,128,256,48.28 -jx_nest_small,237.34,402.863,96,224,38.35 -swin_v2_cr_small_224,234.05,407.737,96,224,49.7 -twins_svt_large,233.44,546.209,128,224,99.27 -efficientnetv2_rw_s,232.97,272.53,64,384,23.94 -regnety_064,232.53,548.809,128,288,30.58 -crossvit_base_240,232.11,411.966,96,240,105.03 -coat_tiny,230.73,552.729,128,224,5.5 -swin_s3_small_224,227.28,420.551,96,224,49.74 -swin_base_patch4_window7_224,225.83,564.975,128,224,87.77 -vit_large_r50_s32_224,224.13,425.968,96,224,328.99 -gluon_xception65,224.07,426.586,96,299,39.92 -regnetv_064,223.77,570.349,128,288,30.58 -xception65,222.29,429.965,96,299,39.92 -hrnet_w40,221.98,860.248,192,224,57.56 -twins_pcpvt_large,221.53,573.857,128,224,60.99 -regnety_080,221.41,576.9,128,288,39.18 -vit_small_r26_s32_384,217.53,292.946,64,384,36.47 -convit_base,213.7,448.233,96,224,86.54 -resnetv2_50d_evos,211.36,301.609,64,288,25.59 -vit_small_patch16_384,211.21,302.185,64,384,22.2 -tresnet_m_448,207.11,924.362,192,448,31.39 -hrnet_w44,206.62,924.469,192,224,67.06 -hrnet_w48,203.91,623.058,128,224,77.47 -xcit_medium_24_p16_224_dist,201.77,472.474,96,224,84.4 -efficientnet_lite4,201.72,315.945,64,380,13.01 -regnetz_040,200.93,316.724,64,320,27.12 -xcit_medium_24_p16_224,200.38,475.726,96,224,84.4 -regnetz_040h,199.32,319.288,64,320,28.94 -vit_base_r50_s16_224,198.49,320.852,64,224,98.66 -volo_d2_224,198.45,481.736,96,224,58.68 -regnetz_d8,197.22,322.887,64,320,23.37 -regnetz_b16_evos,196.95,323.135,64,288,9.74 -densenet264,196.71,484.156,96,224,72.69 -coat_mini,196.35,649.865,128,224,10.34 -tf_efficientnet_lite4,196.17,324.922,64,380,13.01 -eca_nfnet_l1,189.49,673.644,128,320,41.41 -dpn131,186.08,685.82,128,224,79.25 -xcit_small_12_p16_384_dist,185.19,516.612,96,384,26.25 -regnetz_d32,185.07,344.194,64,320,27.58 -poolformer_m48,184.64,517.502,96,224,73.47 -efficientnet_b3_gn,183.63,346.864,64,320,11.73 -nest_base,179.17,355.564,64,224,67.72 -jx_nest_base,178.25,357.393,64,224,67.72 -xcit_tiny_24_p16_384_dist,178.08,535.75,96,384,12.12 -swin_s3_base_224,176.4,360.127,64,224,71.13 -swin_v2_cr_base_224,175.64,361.983,64,224,87.88 -dpn107,174.69,731.058,128,224,86.92 -resnet152d,172.77,553.323,96,320,60.21 -efficientnet_b4,170.77,372.707,64,384,19.34 -hrnet_w64,170.07,747.892,128,224,128.06 -xception71,168.48,377.772,64,299,42.34 -regnety_320,166.84,765.843,128,224,145.05 -densenet264d_iabn,165.34,1156.78,192,224,72.74 -halonet_h1,164.36,387.985,64,256,8.1 -convnext_large_in22ft1k,162.57,588.815,96,224,197.77 -convnext_large,162.19,590.164,96,224,197.77 -tnt_s_patch16_224,160.48,795.734,128,224,23.76 -tf_efficientnet_b4_ap,160.07,397.797,64,380,19.34 -tf_efficientnet_b4,160.05,397.861,64,380,19.34 -tf_efficientnet_b4_ns,159.86,398.285,64,380,19.34 -mixer_l16_224,158.98,602.398,96,224,208.2 -seresnet200d,156.82,607.841,96,256,71.86 -efficientnet_b3_g8_gn,153.08,416.422,64,320,14.25 -vit_large_patch32_384,148.01,430.862,64,384,306.63 -regnetx_320,147.1,869.066,128,224,107.81 -ecaresnet200d,146.51,433.421,64,256,64.69 -seresnet152d,142.71,445.143,64,320,66.84 -senet154,141.47,675.227,96,224,115.09 -gluon_senet154,140.33,680.825,96,224,115.09 -resnetrs152,140.22,453.07,64,320,86.62 -resnetv2_50x1_bitm,140.19,341.567,48,448,25.55 -xcit_small_12_p8_224,140.1,455.06,64,224,26.21 -legacy_senet154,139.98,682.498,96,224,115.09 -xcit_small_12_p8_224_dist,139.68,456.467,64,224,26.21 -volo_d3_224,136.64,465.978,64,224,86.33 -regnety_160,136.33,702.93,96,288,83.59 -xcit_tiny_24_p8_224,135.22,706.664,96,224,12.11 -xcit_tiny_24_p8_224_dist,135.04,707.588,96,224,12.11 -swin_large_patch4_window7_224,134.46,474.195,64,224,196.53 -tnt_b_patch16_224,128.28,746.509,96,224,65.41 -seresnext101_32x8d,126.87,502.256,64,288,93.57 -resnet200d,125.03,508.876,64,320,64.69 -nfnet_f1,124.83,766.912,96,320,132.63 -xcit_nano_12_p8_384_dist,124.74,511.323,64,384,3.05 -resnext101_64x4d,122.53,781.921,96,288,83.46 -xcit_large_24_p16_224,121.81,522.038,64,224,189.1 -xcit_large_24_p16_224_dist,121.62,522.935,64,224,189.1 -regnetz_c16_evos,121.42,393.457,48,320,13.49 -efficientnetv2_m,119.95,397.043,48,416,54.14 -seresnet269d,115.73,547.311,64,256,113.67 -dm_nfnet_f1,111.52,571.621,64,320,132.63 -nf_regnet_b5,111.52,571.237,64,456,49.74 -swin_v2_cr_large_224,108.24,441.046,48,224,196.68 -vit_large_patch16_224,107.89,443.324,48,224,304.33 -convnext_xlarge_in22ft1k,105.95,602.3,64,224,350.2 -vit_base_patch16_18x2_224,104.22,457.937,48,224,256.73 -crossvit_15_dagger_408,103.66,306.843,32,408,28.5 -efficientnetv2_rw_m,103.03,307.229,32,416,53.24 -regnetz_e8,102.71,465.407,48,320,57.7 -tresnet_l_448,102.02,1251.242,128,448,55.99 -beit_large_patch16_224,100.02,477.913,48,224,304.43 -ssl_resnext101_32x16d,99.42,964.104,96,224,194.03 -ig_resnext101_32x16d,99.34,964.822,96,224,194.03 -swsl_resnext101_32x16d,99.31,965.114,96,224,194.03 -resnetrs200,98.78,481.487,48,320,93.21 -xcit_small_24_p16_384_dist,94.29,505.743,48,384,47.67 -convnext_small_384_in22ft1k,94.25,507.598,48,384,88.59 -eca_nfnet_l2,93.98,678.342,64,384,56.72 -convnext_tiny_384_in22ft1k,93.69,510.615,48,384,88.59 -convnext_base_384_in22ft1k,93.6,511.079,48,384,88.59 -vit_base_patch16_384,91.38,349.381,32,384,86.86 -deit_base_patch16_384,91.25,349.874,32,384,86.86 -swin_v2_cr_tiny_384,89.93,354.59,32,384,28.33 -deit_base_distilled_patch16_384,89.45,356.909,32,384,87.63 -tf_efficientnetv2_m,89.24,355.387,32,480,54.14 -tf_efficientnetv2_m_in21ft1k,89.11,356.006,32,480,54.14 -volo_d4_224,89.0,536.865,48,224,192.96 -xcit_tiny_12_p8_384_dist,88.71,539.341,48,384,6.71 -volo_d1_384,87.94,271.566,24,384,26.78 -convmixer_768_32,87.33,1098.007,96,224,21.11 -cait_xxs24_384,86.9,365.799,32,384,12.03 -resnetv2_152x2_bit_teacher,86.51,367.584,32,224,236.34 -resnetv2_101x1_bitm,85.93,370.849,32,448,44.54 -regnetz_d8_evos,81.9,388.68,32,320,23.46 -resnest200e,78.86,603.644,48,320,70.2 -crossvit_18_dagger_408,78.2,304.877,24,408,44.61 -beit_base_patch16_384,77.31,309.414,24,384,86.74 -tresnet_xl_448,77.31,1238.041,96,448,78.44 -efficientnet_b5,76.38,416.454,32,456,30.39 -vit_large_patch14_224,76.22,418.295,32,224,304.2 -tf_efficientnet_b5_ns,75.17,423.294,32,456,30.39 -tf_efficientnet_b5,75.06,423.89,32,456,30.39 -tf_efficientnet_b5_ap,74.91,424.757,32,456,30.39 -vit_large_r50_s32_384,74.62,426.461,32,384,329.09 -nfnet_f2,71.13,671.634,48,352,193.78 -xcit_small_24_p8_224,70.93,447.831,32,224,47.63 -xcit_small_24_p8_224_dist,70.82,448.457,32,224,47.63 -xcit_medium_24_p16_384_dist,68.86,461.356,32,384,84.4 -resmlp_big_24_distilled_224,67.63,471.604,32,224,129.14 -resmlp_big_24_224,66.97,476.343,32,224,129.14 -resmlp_big_24_224_in22ft1k,66.96,476.41,32,224,129.14 -dm_nfnet_f2,63.38,754.059,48,352,193.78 -ecaresnet269d,62.55,506.999,32,352,102.09 -swin_base_patch4_window12_384,61.26,389.996,24,384,87.9 -pnasnet5large,60.8,522.503,32,331,86.06 -cait_xs24_384,60.18,396.29,24,384,26.67 -resnetrs270,59.41,532.629,32,352,129.86 -vit_base_patch8_224,58.54,272.507,16,224,86.58 -nasnetalarge,58.23,544.595,32,331,88.75 -volo_d5_224,57.67,551.667,32,224,295.46 -cait_xxs36_384,57.1,416.606,24,384,17.37 -convnext_large_384_in22ft1k,55.31,576.804,32,384,197.77 -vit_base_resnet50_384,55.13,288.662,16,384,98.95 -vit_base_r50_s16_384,55.08,288.922,16,384,98.95 -swin_v2_cr_small_384,54.02,293.773,16,384,49.7 -xcit_medium_24_p8_224,52.96,600.968,32,224,84.32 -xcit_medium_24_p8_224_dist,52.91,601.478,32,224,84.32 -ig_resnext101_32x32d,52.61,606.726,32,224,468.53 -volo_d2_384,50.75,313.547,16,384,58.87 -eca_nfnet_l3,50.5,630.136,32,448,72.04 -convmixer_1536_20,49.92,960.799,48,224,51.63 -xcit_small_12_p8_384_dist,47.77,500.692,24,384,26.21 -tf_efficientnetv2_l_in21ft1k,47.35,333.533,16,480,118.52 -efficientnetv2_l,47.16,334.995,16,480,118.52 -tf_efficientnetv2_l,47.07,335.523,16,480,118.52 -xcit_tiny_24_p8_384_dist,45.79,695.564,32,384,12.11 -cait_s24_384,44.86,354.226,16,384,47.06 -swin_v2_cr_huge_224,44.05,360.723,16,224,657.83 -efficientnet_b6,42.26,375.764,16,528,43.04 -xcit_large_24_p16_384_dist,41.96,568.582,24,384,189.1 -tf_efficientnet_b6_ap,41.84,379.635,16,528,43.04 -tf_efficientnet_b6,41.78,380.157,16,528,43.04 -tf_efficientnet_b6_ns,41.7,380.74,16,528,43.04 -swin_v2_cr_base_384,41.43,383.765,16,384,87.88 -vit_huge_patch14_224,38.82,410.089,16,224,632.05 -swin_large_patch4_window12_384,37.36,426.362,16,384,196.74 -resnetrs350,37.22,637.051,24,384,163.96 -nfnet_f3,35.3,675.657,24,416,254.92 -convnext_xlarge_384_in22ft1k,34.59,460.906,16,384,350.2 -resnest269e,33.49,709.738,24,416,110.93 -dm_nfnet_f3,32.11,742.967,24,416,254.92 -resnetv2_50x3_bitm,31.49,507.203,16,448,217.32 -xcit_large_24_p8_224,31.1,511.188,16,224,188.93 -xcit_large_24_p8_224_dist,31.08,511.4,16,224,188.93 -resnetv2_152x2_bit_teacher_384,29.72,401.405,12,384,236.34 -cait_s36_384,29.53,402.581,12,384,68.37 -efficientnetv2_xl,28.84,410.429,12,512,208.12 -tf_efficientnetv2_xl_in21ft1k,28.76,411.641,12,512,208.12 -ig_resnext101_32x48d,27.57,578.926,16,224,828.41 -vit_large_patch16_384,26.83,296.63,8,384,304.72 -efficientnet_b7,25.65,308.317,8,600,66.35 -tf_efficientnet_b7_ns,25.54,309.843,8,600,66.35 -tf_efficientnet_b7,25.52,309.949,8,600,66.35 -tf_efficientnet_b7_ap,25.49,310.429,8,600,66.35 -resnetrs420,25.06,628.984,16,416,191.89 -swin_v2_cr_large_384,24.48,324.319,8,384,196.68 -xcit_small_24_p8_384_dist,24.12,494.319,12,384,47.63 -beit_large_patch16_384,22.92,347.104,8,384,305.0 -vit_giant_patch14_224,21.77,364.805,8,224,1012.61 -resnetv2_152x2_bitm,21.5,369.846,8,448,236.34 -volo_d3_448,21.39,278.066,6,448,86.63 -nfnet_f4,18.65,638.182,12,512,316.07 -resnetv2_101x3_bitm,17.49,455.806,8,448,387.93 -xcit_medium_24_p8_384_dist,17.39,456.608,8,384,84.32 -dm_nfnet_f4,16.87,705.913,12,512,316.07 -volo_d4_448,15.85,376.008,6,448,193.41 -tf_efficientnet_b8_ap,13.05,456.145,6,672,87.41 -tf_efficientnet_b8,13.04,456.234,6,672,87.41 -efficientnet_b8,13.01,457.314,6,672,87.41 -nfnet_f5,12.16,651.359,8,544,377.21 -cait_m36_384,11.39,523.115,6,384,271.22 -dm_nfnet_f5,11.14,711.506,8,544,377.21 -xcit_large_24_p8_384_dist,10.6,562.64,6,384,188.93 -volo_d5_448,10.46,379.155,4,448,295.91 -swin_v2_cr_huge_384,9.68,307.346,3,384,657.94 -nfnet_f6,9.19,645.361,6,576,438.36 -tf_efficientnet_l2_ns_475,9.01,438.204,4,475,480.31 -beit_large_patch16_512,8.44,353.416,3,512,305.67 -dm_nfnet_f6,8.42,705.117,6,576,438.36 -volo_d5_512,6.78,291.864,2,512,296.09 -nfnet_f7,6.51,605.721,4,608,499.5 -cait_m48_448,4.62,428.106,2,448,356.46 -resnetv2_152x4_bitm,4.47,445.366,2,480,936.53 -tf_efficientnet_l2_ns,2.56,385.525,1,800,480.31 -efficientnet_l2,2.55,385.937,1,800,480.31 diff --git a/results/benchmark-train-amp-nchw-pt112-cu113-rtx3090.csv b/results/benchmark-train-amp-nchw-pt112-cu113-rtx3090.csv new file mode 100644 index 00000000..de3025b1 --- /dev/null +++ b/results/benchmark-train-amp-nchw-pt112-cu113-rtx3090.csv @@ -0,0 +1,839 @@ +model,train_samples_per_sec,train_step_time,train_batch_size,train_img_size,param_count +tinynet_e,10001.12,50.423,512,106,2.04 +mobilenetv3_small_050,7406.47,68.392,512,224,1.59 +tf_mobilenetv3_small_minimal_100,6438.14,78.983,512,224,2.04 +mobilenetv3_small_075,6186.83,82.006,512,224,2.04 +tf_mobilenetv3_small_075,5783.46,87.782,512,224,2.04 +mobilenetv3_small_100,5749.13,88.315,512,224,2.54 +lcnet_035,5673.53,89.75,512,224,1.64 +tf_mobilenetv3_small_100,5383.9,94.36,512,224,2.54 +levit_128s,5298.88,95.701,512,224,7.78 +lcnet_050,5280.37,96.452,512,224,1.88 +tinynet_d,5161.83,98.416,512,152,2.34 +mixer_s32_224,4696.33,108.475,512,224,19.1 +resnet10t,4669.46,109.393,512,176,5.44 +vit_small_patch32_224,4447.28,114.289,512,224,22.88 +lcnet_075,4278.23,119.175,512,224,2.36 +vit_tiny_r_s16_p8_224,4137.87,122.895,512,224,6.34 +levit_128,3895.0,130.318,512,224,9.21 +regnetx_002,3718.05,137.026,512,224,2.68 +lcnet_100,3569.0,142.969,512,224,2.95 +mnasnet_small,3450.28,147.453,512,224,2.03 +regnety_002,3414.18,149.006,512,224,3.16 +cs3darknet_focus_s,3251.91,156.949,512,256,3.27 +mobilenetv2_035,3160.04,161.202,512,224,1.68 +levit_192,3046.5,166.9,512,224,10.95 +gernet_s,3034.31,168.028,512,224,8.17 +tinynet_c,2919.98,174.314,512,184,2.46 +mnasnet_050,2847.14,179.025,512,224,2.22 +cs3darknet_s,2821.27,180.951,512,256,3.28 +resnet18,2764.22,184.877,512,224,11.69 +ssl_resnet18,2760.71,185.109,512,224,11.69 +mobilenetv2_050,2751.58,185.257,512,224,1.97 +swsl_resnet18,2742.47,186.338,512,224,11.69 +semnasnet_050,2741.67,185.816,512,224,2.08 +gluon_resnet18_v1b,2741.53,186.395,512,224,11.69 +lcnet_150,2713.5,188.193,512,224,4.5 +regnetx_004,2695.23,188.875,512,224,5.16 +ese_vovnet19b_slim_dw,2588.37,197.313,512,224,1.9 +seresnet18,2562.51,199.293,512,224,11.78 +nf_regnet_b0,2561.76,198.646,512,192,8.76 +legacy_seresnet18,2500.8,204.207,512,224,11.78 +tf_efficientnetv2_b0,2483.22,204.949,512,192,7.14 +levit_256,2482.39,205.091,512,224,18.89 +mobilenetv3_large_075,2392.41,213.119,512,224,3.99 +resnet14t,2385.69,214.281,512,176,10.08 +tf_mobilenetv3_large_minimal_100,2347.68,217.368,512,224,3.92 +vit_tiny_patch16_224,2293.54,222.408,512,224,5.72 +regnetx_006,2293.09,222.433,512,224,6.2 +deit_tiny_patch16_224,2290.53,222.68,512,224,5.72 +tf_mobilenetv3_large_075,2259.6,225.688,512,224,3.99 +deit_tiny_distilled_patch16_224,2253.36,226.358,512,224,5.91 +edgenext_xx_small,2231.33,228.598,512,256,1.33 +ghostnet_050,2189.91,232.414,512,224,2.59 +mobilenetv3_rw,2184.31,233.512,512,224,5.48 +mnasnet_075,2176.02,234.492,512,224,3.17 +mobilenetv3_large_100,2167.29,235.344,512,224,5.48 +mobilenetv3_large_100_miil,2165.63,235.504,512,224,5.48 +levit_256d,2159.5,235.516,512,224,26.21 +resnet18d,2129.12,240.084,512,224,11.71 +hardcorenas_a,2118.32,240.968,512,224,5.26 +regnety_004,2100.99,242.536,512,224,4.34 +pit_ti_distilled_224,2086.5,244.504,512,224,5.1 +pit_ti_224,2079.54,245.311,512,224,4.85 +ese_vovnet19b_slim,2066.1,247.446,512,224,3.17 +mnasnet_100,2053.84,248.477,512,224,4.38 +tf_mobilenetv3_large_100,2053.63,248.437,512,224,5.48 +mnasnet_b1,2053.54,248.485,512,224,4.38 +semnasnet_075,2008.51,253.986,512,224,2.91 +hardcorenas_b,2008.46,253.96,512,224,5.18 +mobilenetv2_075,1983.69,257.32,512,224,2.64 +hardcorenas_c,1977.37,257.94,512,224,5.52 +xcit_nano_12_p16_224_dist,1970.62,258.036,512,224,3.05 +xcit_nano_12_p16_224,1969.78,258.084,512,224,3.05 +tinynet_b,1965.95,259.368,512,188,3.73 +hardcorenas_d,1880.3,271.085,512,224,7.5 +tf_efficientnetv2_b1,1876.23,271.395,512,192,8.14 +resnetblur18,1872.21,273.11,512,224,11.69 +spnasnet_100,1862.13,273.955,512,224,4.42 +mnasnet_a1,1859.21,274.476,512,224,3.89 +semnasnet_100,1857.75,274.693,512,224,3.89 +mobilenetv2_100,1832.14,278.633,512,224,3.5 +regnety_006,1809.24,281.912,512,224,6.06 +visformer_tiny,1802.41,283.384,512,224,10.32 +mixer_b32_224,1784.58,286.101,512,224,60.29 +skresnet18,1730.13,295.275,512,224,11.96 +tinynet_a,1710.13,298.117,512,192,6.19 +vit_base_patch32_224_sam,1703.64,299.668,512,224,88.22 +vit_base_patch32_224,1703.57,299.695,512,224,88.22 +efficientnet_lite0,1674.68,304.971,512,224,4.65 +cs3darknet_focus_m,1668.48,306.209,512,256,9.3 +hardcorenas_e,1650.74,309.021,512,224,8.07 +hardcorenas_f,1646.88,309.777,512,224,8.2 +gluon_resnet34_v1b,1634.03,312.731,512,224,21.8 +regnetx_008,1632.2,312.851,512,224,7.26 +tv_resnet34,1630.02,313.513,512,224,21.8 +resnet34,1622.41,314.992,512,224,21.8 +ghostnet_100,1601.5,318.319,512,224,5.18 +tf_efficientnet_lite0,1591.79,320.884,512,224,4.65 +fbnetc_100,1567.77,325.605,512,224,5.57 +pit_xs_distilled_224,1551.83,329.02,512,224,11.0 +pit_xs_224,1549.02,329.642,512,224,10.62 +mixer_s16_224,1543.23,331.197,512,224,18.53 +dla46_c,1532.94,333.18,512,224,1.3 +mnasnet_140,1525.17,334.879,512,224,7.12 +seresnet34,1505.77,339.147,512,224,21.96 +cs3darknet_m,1499.82,340.716,512,256,9.31 +regnety_008,1498.63,340.596,512,224,6.26 +levit_384,1491.26,342.207,512,224,39.13 +edgenext_x_small,1481.71,344.446,512,256,2.34 +ese_vovnet19b_dw,1466.46,348.623,512,224,6.54 +legacy_seresnet34,1465.81,348.38,512,224,21.96 +efficientnet_b0,1459.11,262.1,384,224,5.29 +gernet_m,1456.76,350.74,512,224,21.14 +vit_small_patch32_384,1448.56,352.604,512,384,22.92 +regnetz_005,1448.06,352.165,512,224,7.12 +rexnet_100,1447.81,264.049,384,224,4.8 +rexnetr_100,1441.71,265.216,384,224,4.88 +nf_resnet26,1422.76,359.346,512,224,16.0 +hrnet_w18_small,1410.43,361.614,512,224,13.19 +selecsls42,1405.04,363.736,512,224,30.35 +selecsls42b,1401.22,364.735,512,224,32.46 +mobilenetv2_110d,1400.15,273.199,384,224,4.52 +tf_efficientnet_b0_ap,1398.67,273.43,384,224,5.29 +mobilevitv2_050,1396.45,365.664,512,256,1.37 +tf_efficientnet_b0_ns,1395.54,274.064,384,224,5.29 +tf_efficientnet_b0,1395.32,274.114,384,224,5.29 +tf_efficientnetv2_b2,1392.9,365.948,512,208,10.1 +vit_tiny_r_s16_p8_384,1392.75,274.873,384,384,6.36 +resnet34d,1379.64,370.514,512,224,21.82 +ghostnet_130,1364.55,373.824,512,224,7.36 +gmixer_12_224,1352.72,377.701,512,224,12.7 +crossvit_tiny_240,1349.19,377.902,512,240,7.01 +gmlp_ti16_224,1340.6,284.894,384,224,5.87 +semnasnet_140,1340.57,380.992,512,224,6.11 +dla46x_c,1338.33,381.81,512,224,1.07 +xcit_tiny_12_p16_224,1323.84,384.926,512,224,6.72 +xcit_tiny_12_p16_224_dist,1317.19,386.895,512,224,6.72 +resnetrs50,1317.01,387.565,512,160,35.69 +mobilevit_xxs,1316.84,290.489,384,256,1.27 +resnet26,1312.7,389.566,512,224,16.0 +efficientnet_b1_pruned,1301.95,391.798,512,240,6.33 +mobilenetv2_140,1267.4,302.189,384,224,6.11 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+regnetx_016,1139.3,448.473,512,224,9.19 +fbnetv3_d,1138.14,335.598,384,224,10.31 +tf_efficientnet_es,1136.29,449.83,512,224,5.44 +rexnetr_130,1133.04,224.76,256,224,7.61 +dla34,1132.96,451.315,512,224,15.74 +resnet26d,1119.56,456.822,512,224,16.01 +tf_mixnet_s,1118.11,456.605,512,224,4.13 +tf_efficientnet_lite1,1110.94,229.444,256,240,5.42 +edgenext_small,1109.37,460.388,512,256,5.59 +convit_tiny,1095.04,466.531,512,224,5.71 +rexnet_130,1094.78,232.699,256,224,7.56 +mobilenetv2_120d,1078.49,236.158,256,224,5.83 +darknet21,1073.87,476.43,512,256,20.86 +ecaresnet50d_pruned,1067.01,478.899,512,224,19.94 +deit_small_patch16_224,1053.64,363.563,384,224,22.05 +vit_small_patch16_224,1052.92,363.872,384,224,22.05 +deit_small_distilled_patch16_224,1032.61,370.971,384,224,22.44 +sedarknet21,1031.46,495.893,512,256,20.95 +gernet_l,1030.31,496.058,512,256,31.08 +efficientnet_b1,1030.3,246.963,256,224,7.79 +rexnetr_150,1022.06,249.288,256,224,9.78 +repvgg_a2,1010.18,506.008,512,224,28.21 +edgenext_small_rw,1009.52,506.183,512,256,7.83 +skresnet34,1008.96,506.323,512,224,22.28 +resnest14d,979.06,522.497,512,224,10.61 +cs3darknet_focus_l,977.57,391.957,384,256,21.15 +deit3_small_patch16_224,977.26,391.961,384,224,22.06 +deit3_small_patch16_224_in21ft1k,976.5,392.276,384,224,22.06 +rexnet_150,965.2,264.04,256,224,9.73 +regnety_016,954.26,534.657,512,224,11.2 +vit_base_patch32_plus_256,951.64,537.091,512,256,119.48 +mobilevitv2_075,947.54,269.157,256,256,2.87 +legacy_seresnext26_32x4d,946.21,405.17,384,224,16.79 +pit_s_224,942.8,270.615,256,224,23.46 +pit_s_distilled_224,939.97,271.455,256,224,24.04 +vit_srelpos_small_patch16_224,922.29,415.451,384,224,21.97 +vit_relpos_small_patch16_224,921.7,415.439,384,224,21.98 +efficientnet_b0_g16_evos,909.42,421.149,384,224,8.11 +resnext26ts,905.09,423.733,384,256,10.3 +cs3darknet_l,902.18,282.891,256,256,21.16 +coat_lite_tiny,893.97,428.624,384,224,5.72 +resnet26t,890.89,574.188,512,256,16.01 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+gluon_seresnext50_32x4d,613.35,416.206,256,224,27.56 +sehalonet33ts,613.13,416.664,256,256,13.69 +legacy_seresnext50_32x4d,612.89,416.52,256,224,27.56 +dla60x,612.79,416.731,256,224,17.35 +gcresnet50t,611.79,626.12,384,256,25.9 +xcit_nano_12_p16_384_dist,611.55,416.81,256,384,3.05 +resmlp_24_224,609.69,418.351,256,224,30.02 +resmlp_24_distilled_224,609.51,418.474,256,224,30.02 +gcresnext50ts,606.82,314.923,192,256,15.67 +tf_inception_v3,603.29,635.057,384,299,23.83 +gluon_inception_v3,603.22,635.143,384,299,23.83 +adv_inception_v3,603.01,635.347,384,299,23.83 +inception_v3,602.27,636.205,384,299,23.83 +tf_mixnet_l,600.24,424.956,256,224,7.33 +dm_nfnet_f0,600.1,638.573,384,192,71.49 +xcit_small_12_p16_224,598.44,425.955,256,224,26.25 +xcit_small_12_p16_224_dist,598.22,426.013,256,224,26.25 +semobilevit_s,597.07,320.258,192,256,5.74 +densenet169,592.78,429.221,256,224,14.15 +res2next50,591.98,431.144,256,224,24.67 +resnetv2_101,590.74,431.806,256,224,44.54 +darknet53,590.64,432.606,256,256,41.61 +resnetv2_50x1_bit_distilled,587.0,326.262,192,224,25.55 +res2net50_14w_8s,586.94,433.992,256,224,25.06 +swin_s3_tiny_224,586.39,435.576,256,224,28.33 +repvgg_b1g4,584.26,875.234,512,224,39.97 +dla60_res2net,583.07,437.618,256,224,20.85 +crossvit_15_240,576.62,331.16,192,240,27.53 +cait_xxs24_224,576.52,441.46,256,224,11.96 +cs3darknet_focus_x,569.86,448.292,256,256,35.02 +resnet101,568.98,448.321,256,224,44.55 +gluon_resnet101_v1b,568.4,448.834,256,224,44.55 +tv_resnet101,566.24,450.547,256,224,44.55 +resnetrs101,564.72,451.1,256,192,63.62 +efficientnet_cc_b1_8e,564.18,452.061,256,240,39.72 +crossvit_15_dagger_240,558.23,342.033,192,240,28.21 +vit_base_resnet50d_224,557.61,457.501,256,224,110.97 +mobilevitv2_125,557.38,343.473,192,256,7.48 +xcit_nano_12_p8_224_dist,555.43,459.069,256,224,3.05 +xcit_nano_12_p8_224,555.18,459.311,256,224,3.05 +sebotnet33ts_256,554.49,230.012,128,256,13.7 +resnet51q,551.31,463.504,256,256,35.7 +resnetv2_101d,548.02,465.6,256,224,44.56 +tf_efficientnet_cc_b1_8e,547.16,466.173,256,240,39.72 +resnetv2_50d_gn,546.54,350.469,192,224,25.57 +nf_resnet101,543.9,704.337,384,224,44.55 +vit_base_patch32_384,542.76,470.804,256,384,88.3 +gluon_resnet101_v1c,537.15,475.0,256,224,44.57 +cspdarknet53,537.1,475.617,256,256,27.64 +cs3darknet_x,534.86,477.64,256,256,35.05 +vit_base_r26_s32_224,534.67,357.767,192,224,101.38 +resnest50d,534.66,477.434,256,224,27.48 +resnet50_gn,531.78,360.235,192,224,25.56 +regnetz_c16,530.35,360.552,192,256,13.46 +gluon_resnet101_v1d,528.59,482.76,256,224,44.57 +mixer_b16_224,528.02,484.004,256,224,59.88 +mixer_l32_224,527.33,362.504,192,224,206.94 +mixer_b16_224_miil,526.58,485.347,256,224,59.88 +vit_large_patch32_224,521.73,489.021,256,224,306.54 +dla60_res2next,520.31,490.572,256,224,17.03 +ecaresnet50t,516.29,494.896,256,256,25.57 +cs3sedarknet_xdw,516.24,246.008,128,256,21.6 +lambda_resnet50ts,515.16,371.658,192,256,21.54 +vit_tiny_patch16_384,512.2,249.072,128,384,5.79 +resnet61q,510.55,375.027,192,256,36.85 +swinv2_cr_tiny_224,505.83,504.823,256,224,28.33 +halonet50ts,503.76,380.122,192,256,22.73 +repvgg_b1,503.57,1015.623,512,224,57.42 +swinv2_cr_tiny_ns_224,502.5,508.144,256,224,28.33 +cs3sedarknet_x,501.96,508.547,256,256,35.4 +dla102,497.28,513.14,256,224,33.27 +wide_resnet50_2,495.68,773.85,384,224,68.88 +res2net50_26w_6s,493.57,516.914,256,224,37.05 +resnetaa101d,490.51,520.338,256,224,44.57 +convnext_small,489.81,390.224,192,224,50.22 +convnext_small_in22ft1k,489.45,390.576,192,224,50.22 +legacy_seresnet101,487.73,522.616,256,224,49.33 +vit_relpos_medium_patch16_rpn_224,485.5,526.221,256,224,38.73 +efficientnet_lite3,484.47,263.098,128,300,8.2 +gluon_resnet101_v1s,483.47,527.891,256,224,44.67 +seresnet101,480.65,530.38,256,224,49.33 +cs3edgenet_x,477.59,535.019,256,256,47.82 +nest_tiny,476.68,267.593,128,224,17.06 +nf_seresnet101,474.46,537.213,256,224,49.33 +mobilevitv2_150_in22ft1k,473.86,269.132,128,256,10.59 +mobilevitv2_150,473.84,269.144,128,256,10.59 +resnetblur101d,472.23,540.497,256,224,44.57 +jx_nest_tiny,472.22,270.163,128,224,17.06 +nf_ecaresnet101,469.53,543.375,256,224,44.55 +vgg13_bn,468.37,546.3,256,224,133.05 +twins_pcpvt_base,466.47,408.848,192,224,43.83 +tf_efficientnet_lite3,465.4,273.895,128,300,8.2 +vgg16,465.36,824.954,384,224,138.36 +sequencer2d_s,462.43,412.819,192,224,27.65 +mixnet_xl,460.21,554.308,256,224,11.9 +coat_lite_small,457.06,418.568,192,224,19.84 +efficientnet_b3a,456.95,278.403,128,288,12.23 +efficientnet_b3,456.81,278.448,128,288,12.23 +regnetx_080,454.56,843.629,384,224,39.57 +regnetx_064,452.43,564.953,256,224,26.21 +halo2botnet50ts_256,451.35,424.392,192,256,22.64 +ecaresnet101d,447.44,570.33,256,224,44.57 +densenet201,447.44,425.987,192,224,20.01 +nf_regnet_b4,445.8,428.533,192,320,30.21 +convit_small,443.63,431.737,192,224,27.78 +efficientnetv2_s,433.27,293.157,128,288,21.46 +skresnext50_32x4d,432.3,590.802,256,224,27.48 +cs3se_edgenet_x,431.68,443.324,192,256,50.72 +botnet50ts_256,428.8,297.529,128,256,22.74 +ssl_resnext101_32x4d,427.28,447.74,192,224,44.18 +resnext101_32x4d,427.18,447.921,192,224,44.18 +swsl_resnext101_32x4d,427.16,447.915,192,224,44.18 +gluon_resnext101_32x4d,427.13,447.97,192,224,44.18 +poolformer_s36,425.0,449.906,192,224,30.86 +ese_vovnet39b_evos,421.31,302.862,128,224,24.58 +resnet101d,418.0,457.739,192,256,44.57 +dla102x,417.16,458.658,192,224,26.31 +res2net101_26w_4s,416.51,612.121,256,224,45.21 +lamhalobotnet50ts_256,413.09,463.774,192,256,22.57 +twins_svt_base,411.8,464.138,192,224,56.07 +crossvit_18_240,406.79,312.611,128,240,43.27 +tresnet_l,404.84,1261.389,512,224,55.99 +efficientnetv2_rw_s,402.34,315.806,128,288,23.94 +volo_d1_224,401.47,476.8,192,224,26.63 +resmlp_36_224,401.06,476.505,192,224,44.69 +res2net50_26w_8s,400.52,636.999,256,224,48.4 +resmlp_36_distilled_224,400.14,477.557,192,224,44.69 +swin_small_patch4_window7_224,399.67,478.499,192,224,49.61 +resnest50d_4s2x40d,396.0,645.092,256,224,30.42 +vit_base_patch16_224_miil,395.78,484.311,192,224,86.54 +crossvit_18_dagger_240,394.08,322.72,128,240,44.27 +deit_base_patch16_224,390.88,490.307,192,224,86.57 +vit_base_patch16_224,390.86,490.391,192,224,86.57 +vit_base_patch16_224_sam,390.67,490.608,192,224,86.57 +mobilevitv2_175_in22ft1k,389.97,327.241,128,256,14.25 +mobilevitv2_175,389.95,327.23,128,256,14.25 +tf_efficientnetv2_s_in21ft1k,389.66,326.288,128,300,21.46 +tf_efficientnetv2_s,389.1,326.713,128,300,21.46 +vgg16_bn,388.69,658.276,256,224,138.37 +regnety_064,388.46,657.256,256,224,30.58 +regnety_080,385.84,662.273,256,224,39.18 +deit_base_distilled_patch16_224,385.62,497.03,192,224,87.34 +xception,385.56,331.194,128,299,22.86 +regnety_040s_gn,384.97,330.927,128,224,20.65 +repvgg_b2g4,379.42,1348.329,512,224,61.76 +resnetv2_152,379.4,503.868,192,224,60.19 +regnetz_d8,378.76,336.282,128,256,23.37 +hrnet_w18,378.26,671.883,256,224,21.3 +ese_vovnet99b,377.27,677.036,256,224,63.2 +vit_small_resnet50d_s16_224,376.52,508.654,192,224,57.53 +cait_xxs36_224,375.8,507.032,192,224,17.3 +gluon_seresnext101_32x4d,375.02,509.78,192,224,48.96 +regnetz_040,374.91,339.544,128,256,27.12 +seresnext101_32x4d,374.73,510.176,192,224,48.96 +regnetv_064,372.69,513.522,192,224,30.58 +regnetz_040h,372.64,341.593,128,256,28.94 +legacy_seresnext101_32x4d,372.06,513.705,192,224,48.96 +deit3_base_patch16_224_in21ft1k,371.79,515.431,192,224,86.59 +deit3_base_patch16_224,371.73,515.464,192,224,86.59 +tf_efficientnet_b3,370.15,344.089,128,300,12.23 +tf_efficientnet_b3_ap,370.14,344.111,128,300,12.23 +tf_efficientnet_b3_ns,370.1,344.134,128,300,12.23 +resnet152,370.08,516.516,192,224,60.19 +vit_relpos_base_patch16_clsgap_224,369.76,518.105,192,224,86.43 +vit_relpos_base_patch16_cls_224,369.34,518.67,192,224,86.43 +resnetv2_50d_frn,369.16,345.594,128,224,25.59 +gluon_resnet152_v1b,369.02,517.998,192,224,60.19 +tv_resnet152,369.0,518.088,192,224,60.19 +regnetz_b16_evos,365.3,348.518,128,224,9.74 +sequencer2d_m,363.12,525.505,192,224,38.31 +ese_vovnet99b_iabn,362.9,1055.043,384,224,63.2 +resnetv2_152d,360.99,529.48,192,224,60.2 +beit_base_patch16_224,358.29,534.776,192,224,86.53 +xcit_tiny_12_p16_384_dist,357.91,534.55,192,384,6.72 +vit_relpos_base_patch16_224,355.33,539.194,192,224,86.43 +gluon_resnet152_v1c,354.77,538.797,192,224,60.21 +regnetz_d32,354.52,359.397,128,256,27.58 +swinv2_tiny_window8_256,354.35,540.569,192,256,28.35 +resnetv2_50d_evos,353.36,270.506,96,224,25.59 +dpn92,353.0,723.617,256,224,37.67 +vgg19,352.0,1090.655,384,224,143.67 +gluon_resnet152_v1d,351.06,544.563,192,224,60.21 +densenet161,346.02,367.416,128,224,28.68 +xception41p,344.85,370.318,128,299,26.91 +gluon_resnet152_v1s,344.7,368.96,128,224,60.32 +mobilevitv2_200,342.4,372.843,128,256,18.45 +tnt_s_patch16_224,342.25,559.037,192,224,23.76 +mobilevitv2_200_in22ft1k,342.08,373.147,128,256,18.45 +eca_nfnet_l1,341.07,561.084,192,256,41.41 +hrnet_w32,340.54,747.043,256,224,41.23 +dla169,338.11,565.259,192,224,53.39 +convnext_base_in22ft1k,337.76,377.102,128,224,88.59 +convnext_base,336.98,378.091,128,224,88.59 +repvgg_b2,335.01,1527.215,512,224,89.02 +repvgg_b3g4,334.01,1148.557,384,224,83.83 +vgg13,331.37,1544.923,512,224,133.05 +pit_b_224,331.17,385.577,128,224,73.76 +vgg19_bn,330.96,773.109,256,224,143.68 +pit_b_distilled_224,329.46,387.568,128,224,74.79 +regnetx_120,327.41,780.952,256,224,46.11 +twins_pcpvt_large,322.96,392.17,128,224,60.99 +hrnet_w30,321.86,790.607,256,224,37.71 +legacy_seresnet152,319.56,397.245,128,224,66.82 +inception_v4,316.87,603.734,192,299,42.68 +seresnet152,313.75,608.677,192,224,66.82 +vit_small_patch16_36x1_224,310.56,409.448,128,224,64.67 +dla102x2,309.09,412.537,128,224,41.28 +xcit_small_24_p16_224_dist,307.83,412.466,128,224,47.67 +convmixer_1024_20_ks9_p14,307.81,830.813,256,224,24.38 +vit_small_patch16_18x2_224,307.61,413.3,128,224,64.67 +xcit_small_24_p16_224,307.46,412.867,128,224,47.67 +regnety_120,307.05,623.971,192,224,51.82 +poolformer_m36,303.34,420.132,128,224,56.17 +efficientnet_el_pruned,301.49,423.464,128,300,10.59 +efficientnet_el,301.45,423.5,128,300,10.59 +swinv2_cr_small_ns_224,300.41,423.619,128,224,49.7 +swinv2_cr_small_224,297.65,427.521,128,224,49.7 +mixnet_xxl,297.33,428.503,128,224,23.96 +cait_s24_224,296.96,428.341,128,224,46.92 +nest_small,296.72,321.888,96,224,38.35 +coat_tiny,296.44,429.708,128,224,5.5 +tf_efficientnet_el,295.51,432.07,128,300,10.59 +jx_nest_small,294.83,323.932,96,224,38.35 +efficientnet_b4,293.1,325.442,96,320,19.34 +xception41,293.07,435.505,128,299,26.97 +xcit_tiny_12_p8_224_dist,291.52,437.287,128,224,6.71 +tresnet_xl,291.4,875.028,256,224,78.44 +resnext101_64x4d,291.33,437.816,128,224,83.46 +gluon_resnext101_64x4d,291.25,437.881,128,224,83.46 +swin_s3_small_224,289.76,439.818,128,224,49.74 +wide_resnet101_2,289.62,661.356,192,224,126.89 +xcit_tiny_12_p8_224,289.33,440.549,128,224,6.71 +twins_svt_large,289.11,440.647,128,224,99.27 +resnet152d,281.47,452.46,128,256,60.21 +swin_base_patch4_window7_224,279.66,455.817,128,224,87.77 +convnext_tiny_384_in22ft1k,278.8,343.389,96,384,28.59 +resnet200,276.62,459.688,128,224,64.67 +ssl_resnext101_32x8d,276.52,461.341,128,224,88.79 +ig_resnext101_32x8d,276.39,461.582,128,224,88.79 +resnext101_32x8d,276.22,461.854,128,224,88.79 +swsl_resnext101_32x8d,276.22,461.764,128,224,88.79 +repvgg_b3,271.93,1411.039,384,224,123.09 +nfnet_f1,271.43,705.161,192,224,132.63 +resnetv2_50d_evob,268.92,355.729,96,224,25.59 +gmlp_b16_224,268.22,356.298,96,224,73.08 +dpn98,267.62,476.602,128,224,61.57 +regnetx_160,266.55,719.244,192,224,54.28 +regnety_160,264.44,724.758,192,224,83.59 +gluon_seresnext101_64x4d,264.12,482.344,128,224,88.23 +ens_adv_inception_resnet_v2,261.47,730.952,192,299,55.84 +inception_resnet_v2,261.44,730.919,192,299,55.84 +xception65p,259.32,492.32,128,299,39.82 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+xcit_medium_24_p16_224_dist,227.91,558.239,128,224,84.4 +deit3_small_patch16_384_in21ft1k,227.77,280.008,64,384,22.21 +deit3_small_patch16_384,227.76,280.015,64,384,22.21 +xcit_medium_24_p16_224,227.75,558.491,128,224,84.4 +vit_small_r26_s32_384,227.25,280.302,64,384,36.47 +convit_base,224.86,568.198,128,224,86.54 +gluon_xception65,224.1,426.474,96,299,39.92 +swin_s3_base_224,223.36,426.944,96,224,71.13 +tnt_b_patch16_224,222.94,572.213,128,224,65.41 +xception65,222.93,428.728,96,299,39.92 +coat_mini,222.88,572.209,128,224,10.34 +volo_d2_224,222.28,430.111,96,224,58.68 +xcit_small_12_p16_384_dist,221.79,430.984,96,384,26.25 +poolformer_m48,220.53,432.741,96,224,73.47 +hrnet_w40,219.45,869.959,192,224,57.56 +vit_base_r50_s16_224,215.41,443.988,96,224,98.66 +swinv2_cr_base_ns_224,213.88,446.428,96,224,87.88 +sequencer2d_l,213.86,444.098,96,224,54.3 +swinv2_small_window8_256,212.59,449.01,96,256,49.73 +swinv2_cr_base_224,211.39,451.682,96,224,87.88 +mobilevitv2_150_384_in22ft1k,210.38,303.23,64,384,10.59 +nest_base,210.2,302.774,64,224,67.72 +tresnet_m_448,209.55,913.447,192,448,31.39 +efficientnetv2_m,207.96,304.545,64,320,54.14 +jx_nest_base,207.78,306.371,64,224,67.72 +regnetz_c16_evos,207.35,306.824,64,256,13.49 +hrnet_w44,206.45,925.026,192,224,67.06 +resnet200d,204.47,623.017,128,256,64.69 +efficientnet_b3_g8_gn,203.44,312.836,64,288,14.25 +hrnet_w48,202.15,628.427,128,224,77.47 +densenet264,202.1,470.789,96,224,72.69 +dpn131,198.25,643.486,128,224,79.25 +tf_efficientnet_b4,194.83,326.399,64,380,19.34 +tf_efficientnet_b4_ap,194.65,326.738,64,380,19.34 +tf_efficientnet_b4_ns,194.23,327.375,64,380,19.34 +xcit_nano_12_p8_384_dist,187.76,338.965,64,384,3.05 +efficientnetv2_rw_m,187.31,338.14,64,320,53.24 +dpn107,187.14,682.151,128,224,86.92 +convnext_large_in22ft1k,187.05,511.402,96,224,197.77 +convnext_large,187.01,511.523,96,224,197.77 +nf_regnet_b5,186.49,512.09,96,384,49.74 +xcit_tiny_24_p8_224_dist,183.21,520.533,96,224,12.11 +xcit_tiny_24_p8_224,183.21,520.609,96,224,12.11 +halonet_h1,177.48,359.151,64,256,8.1 +hrnet_w64,176.04,722.362,128,224,128.06 +mobilevitv2_175_384_in22ft1k,175.76,363.135,64,384,14.25 +senet154,174.83,545.792,96,224,115.09 +regnety_320,174.41,732.528,128,224,145.05 +gluon_senet154,174.03,548.162,96,224,115.09 +regnetz_e8,173.89,365.999,64,256,57.7 +legacy_senet154,170.27,560.493,96,224,115.09 +xception71,168.81,376.911,64,299,42.34 +xcit_small_12_p8_224,168.52,377.961,64,224,26.21 +xcit_small_12_p8_224_dist,168.32,378.375,64,224,26.21 +vit_large_patch32_384,168.05,569.595,96,384,306.63 +convnext_small_384_in22ft1k,164.94,386.292,64,384,50.22 +mixer_l16_224,164.43,582.335,96,224,208.2 +ecaresnet200d,161.74,392.334,64,256,64.69 +seresnet200d,161.56,391.892,64,256,71.86 +resnetrs200,160.52,394.222,64,256,93.21 +densenet264d_iabn,158.12,804.924,128,224,72.74 +regnetx_320,155.94,819.702,128,224,107.81 +swin_large_patch4_window7_224,153.79,414.255,64,224,196.53 +volo_d3_224,152.73,416.584,64,224,86.33 +mobilevitv2_200_384_in22ft1k,150.68,317.559,48,384,18.45 +swinv2_base_window8_256,150.28,423.39,64,256,87.92 +resnetv2_50x1_bitm,149.04,321.21,48,448,25.55 +nfnet_f2,148.92,641.446,96,256,193.78 +swinv2_small_window16_256,142.83,445.591,64,256,49.73 +tf_efficientnetv2_m,142.41,333.833,48,384,54.14 +eca_nfnet_l2,142.2,672.291,96,320,56.72 +tf_efficientnetv2_m_in21ft1k,141.35,336.246,48,384,54.14 +regnetz_d8_evos,132.2,360.995,48,256,23.46 +swinv2_cr_tiny_384,131.5,485.388,64,384,28.33 +ig_resnext101_32x16d,130.47,734.203,96,224,194.03 +ssl_resnext101_32x16d,130.4,734.63,96,224,194.03 +swsl_resnext101_32x16d,130.37,734.771,96,224,194.03 +xcit_large_24_p16_224,126.98,500.577,64,224,189.1 +xcit_large_24_p16_224_dist,126.97,500.662,64,224,189.1 +seresnet269d,125.7,503.318,64,256,113.67 +dm_nfnet_f2,125.2,507.681,64,256,193.78 +swinv2_cr_large_224,124.7,510.736,64,224,196.68 +xcit_tiny_12_p8_384_dist,122.38,390.412,48,384,6.71 +resnetrs270,121.5,520.761,64,256,129.86 +crossvit_15_dagger_408,117.57,270.29,32,408,28.5 +vit_large_patch16_224,117.08,544.981,64,224,304.33 +vit_base_patch16_18x2_224,116.55,546.378,64,224,256.73 +convnext_base_384_in22ft1k,115.97,412.084,48,384,88.59 +convnext_xlarge_in22ft1k,115.91,550.445,64,224,350.2 +deit3_large_patch16_224_in21ft1k,113.19,563.501,64,224,304.37 +deit3_large_patch16_224,113.17,563.634,64,224,304.37 +xcit_small_24_p16_384_dist,112.88,421.839,48,384,47.67 +beit_large_patch16_224,107.8,591.544,64,224,304.43 +swinv2_base_window16_256,103.68,460.461,48,256,87.92 +swinv2_base_window12to16_192to256_22kft1k,103.56,461.021,48,256,87.92 +tresnet_l_448,103.2,1236.839,128,448,55.99 +volo_d1_384,99.39,320.613,32,384,26.78 +cait_xxs24_384,97.83,488.033,48,384,12.03 +vit_base_patch16_384,96.96,329.192,32,384,86.86 +deit_base_patch16_384,96.37,331.171,32,384,86.86 +volo_d4_224,95.75,498.748,48,224,192.96 +deit_base_distilled_patch16_384,94.83,336.556,32,384,87.63 +efficientnet_b5,93.71,338.901,32,456,30.39 +deit3_base_patch16_384,93.22,342.328,32,384,86.88 +deit3_base_patch16_384_in21ft1k,92.68,344.327,32,384,86.88 +tf_efficientnet_b5,92.16,344.785,32,456,30.39 +tf_efficientnet_b5_ns,92.11,344.939,32,456,30.39 +tf_efficientnet_b5_ap,91.98,345.405,32,456,30.39 +resnetv2_152x2_bit_teacher,89.37,355.711,32,224,236.34 +crossvit_18_dagger_408,88.76,358.492,32,408,44.61 +xcit_small_24_p8_224,87.25,546.829,48,224,47.63 +xcit_small_24_p8_224_dist,86.87,549.24,48,224,47.63 +convmixer_768_32,85.53,1121.025,96,224,21.11 +vit_large_patch14_224,85.27,561.239,48,224,304.2 +eca_nfnet_l3,84.61,563.702,48,352,72.04 +resnetv2_101x1_bitm,84.61,187.399,16,448,44.54 +beit_base_patch16_384,83.67,381.291,32,384,86.74 +resnest200e,83.33,570.802,48,320,70.2 +tf_efficientnetv2_l_in21ft1k,83.27,379.678,32,384,118.52 +efficientnetv2_l,83.27,379.867,32,384,118.52 +tf_efficientnetv2_l,82.74,382.367,32,384,118.52 +ecaresnet269d,82.15,579.477,48,320,102.09 +tresnet_xl_448,78.31,1222.487,96,448,78.44 +xcit_medium_24_p16_384_dist,77.9,407.346,32,384,84.4 +vit_large_r50_s32_384,77.49,410.426,32,384,329.09 +swinv2_cr_small_384,76.31,416.793,32,384,49.7 +swin_base_patch4_window12_384,74.03,430.327,32,384,87.9 +pnasnet5large,68.77,461.392,32,331,86.06 +resnetrs350,68.24,460.967,32,288,163.96 +nfnet_f3,67.87,703.087,48,320,254.92 +nasnetalarge,67.38,469.785,32,331,88.75 +resmlp_big_24_distilled_224,67.03,475.867,32,224,129.14 +resmlp_big_24_224_in22ft1k,67.03,475.857,32,224,129.14 +resmlp_big_24_224,67.02,475.97,32,224,129.14 +cait_xs24_384,65.59,485.229,32,384,26.67 +convnext_large_384_in22ft1k,63.62,501.159,32,384,197.77 +vit_base_patch8_224,63.42,377.591,24,224,86.58 +cait_xxs36_384,63.23,502.345,32,384,17.37 +ig_resnext101_32x32d,62.72,508.666,32,224,468.53 +xcit_tiny_24_p8_384_dist,62.14,511.676,32,384,12.11 +volo_d5_224,61.58,516.467,32,224,295.46 +vit_base_resnet50_384,61.06,391.43,24,384,98.95 +vit_base_r50_s16_384,61.0,391.773,24,384,98.95 +swinv2_large_window12to16_192to256_22kft1k,60.93,391.352,24,256,196.74 +xcit_medium_24_p8_224,60.43,526.111,32,224,84.32 +xcit_medium_24_p8_224_dist,60.03,529.652,32,224,84.32 +xcit_small_12_p8_384_dist,57.75,413.763,24,384,26.21 +dm_nfnet_f3,57.26,554.375,32,320,254.92 +volo_d2_384,55.56,286.247,16,384,58.87 +efficientnet_b6,54.98,288.003,16,528,43.04 +swinv2_cr_base_384,54.71,436.265,24,384,87.88 +tf_efficientnet_b6,54.38,291.338,16,528,43.04 +tf_efficientnet_b6_ns,54.21,292.241,16,528,43.04 +tf_efficientnet_b6_ap,54.17,292.479,16,528,43.04 +efficientnetv2_xl,53.77,291.666,16,384,208.12 +tf_efficientnetv2_xl_in21ft1k,53.07,295.611,16,384,208.12 +convmixer_1536_20,50.1,957.271,48,224,51.63 +swinv2_cr_huge_224,49.51,482.114,24,224,657.83 +cait_s24_384,49.37,483.331,24,384,47.06 +resnetrs420,48.12,489.4,24,320,191.89 +xcit_large_24_p16_384_dist,45.6,522.909,24,384,189.1 +swin_large_patch4_window12_384,41.65,382.145,16,384,196.74 +convnext_xlarge_384_in22ft1k,40.18,595.51,24,384,350.2 +vit_huge_patch14_224,39.94,398.436,16,224,632.05 +deit3_huge_patch14_224_in21ft1k,38.36,414.578,16,224,632.13 +deit3_huge_patch14_224,38.33,414.855,16,224,632.13 +nfnet_f4,36.85,646.047,24,384,316.07 +resnest269e,35.75,664.499,24,416,110.93 +resnetv2_50x3_bitm,34.88,457.822,16,448,217.32 +xcit_large_24_p8_224_dist,33.7,471.344,16,224,188.93 +xcit_large_24_p8_224,33.68,471.512,16,224,188.93 +resnetv2_152x2_bit_teacher_384,32.69,487.138,16,384,236.34 +ig_resnext101_32x48d,32.39,492.417,16,224,828.41 +swinv2_cr_large_384,32.36,491.839,16,384,196.68 +cait_s36_384,31.92,497.404,16,384,68.37 +efficientnet_b7,31.74,248.492,8,600,66.35 +dm_nfnet_f4,31.4,758.349,24,384,316.07 +tf_efficientnet_b7,31.4,251.12,8,600,66.35 +tf_efficientnet_b7_ns,31.37,251.394,8,600,66.35 +tf_efficientnet_b7_ap,31.35,251.548,8,600,66.35 +xcit_small_24_p8_384_dist,29.2,544.65,16,384,47.63 +vit_large_patch16_384,29.07,411.127,12,384,304.72 +deit3_large_patch16_384,28.22,423.365,12,384,304.76 +deit3_large_patch16_384_in21ft1k,28.19,423.825,12,384,304.76 +swinv2_base_window12to24_192to384_22kft1k,28.14,423.938,12,384,87.92 +beit_large_patch16_384,25.12,475.56,12,384,305.0 +volo_d3_448,23.79,333.686,8,448,86.63 +nfnet_f5,22.84,694.067,16,416,377.21 +resnetv2_152x2_bitm,22.69,350.236,8,448,236.34 +vit_giant_patch14_224,22.29,356.113,8,224,1012.61 +dm_nfnet_f5,20.95,756.72,16,416,377.21 +xcit_medium_24_p8_384_dist,19.97,397.272,8,384,84.32 +efficientnet_b8,19.9,297.659,6,672,87.41 +tf_efficientnet_b8_ap,19.66,301.198,6,672,87.41 +tf_efficientnet_b8,19.65,301.246,6,672,87.41 +nfnet_f6,18.5,641.193,12,448,438.36 +resnetv2_101x3_bitm,18.0,442.742,8,448,387.93 +volo_d4_448,16.87,353.154,6,448,193.41 +swinv2_large_window12to24_192to384_22kft1k,16.59,359.187,6,384,196.74 +dm_nfnet_f6,15.07,522.261,8,448,438.36 +swinv2_cr_huge_384,12.92,461.964,6,384,657.94 +nfnet_f7,12.67,622.861,8,480,499.5 +cait_m36_384,11.76,506.439,6,384,271.22 +xcit_large_24_p8_384_dist,11.53,516.755,6,384,188.93 +volo_d5_448,11.08,357.783,4,448,295.91 +tf_efficientnet_l2_ns_475,10.91,360.832,4,475,480.31 +beit_large_patch16_512,9.42,422.333,4,512,305.67 +volo_d5_512,7.72,385.462,3,512,296.09 +resnetv2_152x4_bitm,4.91,404.529,2,480,936.53 +cait_m48_448,4.71,419.69,2,448,356.46 +efficientnet_l2,3.43,285.826,1,800,480.31 +tf_efficientnet_l2_ns,3.42,287.247,1,800,480.31 diff --git a/results/benchmark-train-amp-nhwc-pt110-cu113-rtx3090.csv b/results/benchmark-train-amp-nhwc-pt110-cu113-rtx3090.csv deleted file mode 100644 index e1c7a27b..00000000 --- a/results/benchmark-train-amp-nhwc-pt110-cu113-rtx3090.csv +++ /dev/null @@ -1,752 +0,0 @@ -model,train_samples_per_sec,train_step_time,train_batch_size,train_img_size,param_count -tinynet_e,11865.58,41.98,512,106,2.04 -mobilenetv3_small_050,9629.08,51.965,512,224,1.59 -lcnet_035,9606.99,52.813,512,224,1.64 -lcnet_050,8308.1,61.144,512,224,1.88 -tf_mobilenetv3_small_minimal_100,8177.36,62.078,512,224,2.04 -tinynet_d,7868.57,64.271,512,152,2.34 -mobilenetv3_small_075,7711.11,65.691,512,224,2.04 -mobilenetv3_small_100,7460.55,67.914,512,224,2.54 -tf_mobilenetv3_small_075,7072.94,71.668,512,224,2.04 -tf_mobilenetv3_small_100,6822.85,74.336,512,224,2.54 -levit_128s,6307.22,80.265,512,224,7.78 -lcnet_075,5771.69,88.22,512,224,2.36 -lcnet_100,5340.01,95.349,512,224,2.95 -mnasnet_small,4625.32,109.825,512,224,2.03 -mnasnet_050,4551.97,111.686,512,224,2.22 -levit_128,4410.33,114.704,512,224,9.21 -mixer_s32_224,4217.66,120.85,512,224,19.1 -mobilenetv2_035,4180.28,121.712,512,224,1.68 -gernet_s,4116.78,123.681,512,224,8.17 -tinynet_c,4103.49,123.752,512,184,2.46 -semnasnet_050,4028.68,126.209,512,224,2.08 -levit_192,3811.4,133.194,512,224,10.95 -vit_small_patch32_224,3700.17,137.556,512,224,22.88 -lcnet_150,3681.41,138.606,512,224,4.5 -gluon_resnet18_v1b,3581.02,142.641,512,224,11.69 -resnet18,3574.82,142.871,512,224,11.69 -ssl_resnet18,3574.64,142.896,512,224,11.69 -swsl_resnet18,3565.29,143.268,512,224,11.69 -mobilenetv2_050,3526.73,144.403,512,224,1.97 -vit_tiny_r_s16_p8_224,3365.24,151.299,512,224,6.34 -mobilenetv3_large_075,3334.18,152.721,512,224,3.99 -ese_vovnet19b_slim_dw,3240.01,157.539,512,224,1.9 -seresnet18,3217.3,158.65,512,224,11.78 -tf_mobilenetv3_large_minimal_100,3209.68,158.819,512,224,3.92 -legacy_seresnet18,3142.19,162.435,512,224,11.78 -mnasnet_075,3119.09,163.378,512,224,3.17 -tf_mobilenetv3_large_075,3090.56,164.803,512,224,3.99 -ghostnet_050,3063.05,165.85,512,224,2.59 -mobilenetv3_rw,3014.78,168.962,512,224,5.48 -mobilenetv3_large_100,2992.21,170.226,512,224,5.48 -mobilenetv3_large_100_miil,2990.87,170.323,512,224,5.48 -levit_256,2894.46,175.762,512,224,18.89 -hardcorenas_a,2868.48,177.792,512,224,5.26 -resnet18d,2834.12,180.284,512,224,11.71 -mnasnet_100,2827.14,180.334,512,224,4.38 -mnasnet_b1,2827.02,180.326,512,224,4.38 -tf_mobilenetv3_large_100,2779.62,183.335,512,224,5.48 -tinynet_b,2747.1,185.348,512,188,3.73 -hardcorenas_b,2668.69,190.927,512,224,5.18 -semnasnet_075,2655.76,191.892,512,224,2.91 -hardcorenas_c,2631.09,193.667,512,224,5.52 -ese_vovnet19b_slim,2599.09,196.628,512,224,3.17 -mobilenetv2_075,2533.52,201.317,512,224,2.64 -spnasnet_100,2511.06,202.936,512,224,4.42 -tf_efficientnetv2_b0,2494.41,204.074,512,224,7.14 -hardcorenas_d,2465.48,206.526,512,224,7.5 -levit_256d,2462.33,206.435,512,224,26.21 -mnasnet_a1,2405.65,211.939,512,224,3.89 -semnasnet_100,2399.02,212.51,512,224,3.89 -mobilenetv2_100,2378.23,214.513,512,224,3.5 -regnetx_002,2343.58,217.787,512,224,2.68 -tinynet_a,2256.09,225.69,512,192,6.19 -ghostnet_100,2255.1,225.72,512,224,5.18 -fbnetc_100,2254.08,226.169,512,224,5.57 -regnety_002,2253.77,226.257,512,224,3.16 -efficientnet_lite0,2211.3,230.81,512,224,4.65 -hardcorenas_f,2190.03,232.713,512,224,8.2 -hardcorenas_e,2162.31,235.693,512,224,8.07 -tv_resnet34,2075.27,246.161,512,224,21.8 -resnet34,2068.19,246.986,512,224,21.8 -gluon_resnet34_v1b,2067.71,247.057,512,224,21.8 -skresnet18,2066.34,247.158,512,224,11.96 -tf_efficientnet_lite0,2054.44,248.465,512,224,4.65 -resnetblur18,1969.59,259.6,512,224,11.69 -resnet26,1968.95,259.579,512,224,16.0 -gernet_m,1919.3,266.068,512,224,21.14 -ese_vovnet19b_dw,1895.91,269.566,512,224,6.54 -nf_resnet26,1892.25,270.084,512,224,16.0 -hrnet_w18_small,1887.88,269.862,512,224,13.19 -seresnet34,1853.44,275.372,512,224,21.96 -mnasnet_140,1845.29,276.683,512,224,7.12 -legacy_seresnet34,1806.55,282.531,512,224,21.96 -resnet34d,1806.5,282.837,512,224,21.82 -efficientnet_b0,1788.38,213.649,384,224,5.29 -levit_384,1780.35,286.471,512,224,39.13 -mobilenetv2_110d,1767.81,216.252,384,224,4.52 -rexnetr_100,1752.61,217.959,384,224,4.88 -selecsls42,1747.75,292.316,512,224,30.35 -selecsls42b,1738.89,293.814,512,224,32.46 -deit_tiny_patch16_224,1689.9,302.152,512,224,5.72 -tf_efficientnet_b0_ap,1684.9,226.862,384,224,5.29 -tf_efficientnet_b0_ns,1683.36,227.058,384,224,5.29 -tf_efficientnet_b0,1683.23,227.077,384,224,5.29 -vit_tiny_patch16_224,1683.04,303.395,512,224,5.72 -deit_tiny_distilled_patch16_224,1666.5,306.386,512,224,5.91 -semnasnet_140,1636.74,311.892,512,224,6.11 -efficientnet_es,1623.57,314.604,512,224,5.44 -efficientnet_es_pruned,1623.07,314.728,512,224,5.44 -mixer_b32_224,1621.79,314.927,512,224,60.29 -tf_efficientnet_es,1614.49,316.384,512,224,5.44 -resnet26d,1611.26,317.273,512,224,16.01 -ghostnet_130,1598.03,319.078,512,224,7.36 -tf_efficientnetv2_b1,1597.89,238.836,384,240,8.14 -repvgg_b0,1575.31,323.975,512,224,15.82 -pit_ti_224,1548.89,329.683,512,224,4.85 -pit_ti_distilled_224,1548.6,329.749,512,224,5.1 -resmlp_12_224,1545.21,330.553,512,224,15.35 -resmlp_12_distilled_224,1540.69,331.552,512,224,15.35 -mobilenetv2_140,1540.03,248.569,384,224,6.11 -vit_base_patch32_224,1513.69,337.426,512,224,88.22 -vit_base_patch32_224_sam,1513.5,337.457,512,224,88.22 -selecsls60,1477.69,345.619,512,224,30.67 -selecsls60b,1473.48,346.601,512,224,32.77 -nf_seresnet26,1470.65,347.478,512,224,17.4 -xcit_nano_12_p16_224,1446.71,352.118,512,224,3.05 -xcit_nano_12_p16_224_dist,1446.49,352.205,512,224,3.05 -mixer_s16_224,1421.1,359.737,512,224,18.53 -efficientnet_lite1,1418.43,179.546,256,240,5.42 -efficientnet_b1_pruned,1373.85,371.198,512,240,6.33 -dla46_c,1358.21,376.236,512,224,1.3 -nf_ecaresnet26,1357.53,376.618,512,224,16.0 -poolformer_s12,1347.4,379.311,512,224,11.92 -rexnetr_130,1344.64,189.254,256,224,7.61 -tf_efficientnet_lite1,1343.17,189.621,256,240,5.42 -mobilenetv2_120d,1310.43,194.218,256,224,5.83 -resnetv2_50,1297.38,393.874,512,224,25.55 -gernet_l,1283.43,398.072,512,256,31.08 -rexnet_100,1272.36,300.69,384,224,4.8 -pit_xs_distilled_224,1254.74,407.184,512,224,11.0 -pit_xs_224,1254.0,407.428,512,224,10.62 -gmixer_12_224,1249.86,408.85,512,224,12.7 -resnet26t,1229.42,415.965,512,256,16.01 -vit_small_patch32_384,1222.24,418.08,512,384,22.92 -gluon_resnet50_v1b,1211.76,316.088,384,224,25.56 -resnet50,1209.87,316.583,384,224,25.56 -swsl_resnet50,1207.82,317.131,384,224,25.56 -ssl_resnet50,1206.46,317.499,384,224,25.56 -tv_resnet50,1206.19,317.554,384,224,25.56 -fbnetv3_b,1183.98,322.691,384,256,8.6 -rexnetr_150,1180.6,215.678,256,224,9.78 -skresnet34,1172.64,435.505,512,224,22.28 -botnet26t_256,1165.39,328.958,384,256,12.49 -regnetx_004,1156.64,441.6,512,224,5.16 -tf_efficientnetv2_b2,1153.57,220.384,256,260,10.1 -mobilevit_xxs,1138.13,336.274,384,256,1.27 -repvgg_a2,1135.99,449.884,512,224,28.21 -fbnetv3_d,1135.22,223.716,256,256,10.31 -resnetv2_50t,1134.34,450.569,512,224,25.57 -resnetv2_50d,1133.08,451.042,512,224,25.57 -gluon_resnet50_v1c,1130.59,338.824,384,224,25.58 -halonet26t,1113.35,344.34,384,256,12.48 -efficientnet_lite2,1098.34,232.132,256,260,6.09 -dla34,1084.57,471.49,512,224,15.74 -mixnet_s,1077.24,474.033,512,224,4.13 -resnet50d,1072.54,357.199,384,224,25.58 -gluon_resnet50_v1d,1071.22,357.651,384,224,25.58 -resnet50t,1070.87,357.75,384,224,25.57 -xcit_tiny_12_p16_224,1059.54,481.47,512,224,6.72 -xcit_tiny_12_p16_224_dist,1056.83,482.712,512,224,6.72 -vit_tiny_r_s16_p8_384,1051.35,364.401,384,384,6.36 -convnext_nano_hnf,1047.46,365.815,384,224,15.59 -tf_efficientnet_lite2,1043.72,244.303,256,260,6.09 -legacy_seresnext26_32x4d,1042.93,490.306,512,224,16.79 -regnety_004,1025.72,498.016,512,224,4.34 -resnet32ts,1024.45,249.318,256,256,17.96 -res2net50_48w_2s,1015.98,377.161,384,224,25.29 -tf_efficientnet_b1,1013.9,251.028,256,240,7.79 -tf_efficientnet_b1_ap,1013.6,251.079,256,240,7.79 -tf_efficientnet_b1_ns,1013.45,251.129,256,240,7.79 -resnet33ts,1011.87,252.405,256,256,19.68 -vit_small_resnet26d_224,1011.11,378.737,384,224,63.61 -vovnet39a,996.22,513.329,512,224,22.6 -seresnext26d_32x4d,992.71,386.155,384,224,16.81 -seresnext26tn_32x4d,991.03,386.816,384,224,16.81 -seresnext26t_32x4d,990.93,386.864,384,224,16.81 -legacy_seresnet50,981.61,390.065,384,224,28.09 -efficientnet_em,977.99,260.806,256,240,6.9 -dla46x_c,974.57,524.617,512,224,1.07 -tf_efficientnet_em,973.77,261.927,256,240,6.9 -tf_mixnet_s,968.67,527.275,512,224,4.13 -eca_resnet33ts,964.37,264.809,256,256,19.68 -crossvit_tiny_240,956.47,399.879,384,240,7.01 -seresnet33ts,956.02,266.975,256,256,19.78 -crossvit_9_240,952.71,401.653,384,240,8.55 -efficientnet_b1,949.11,268.27,256,256,7.79 -seresnet50,945.63,404.935,384,224,28.09 -resnetaa50d,943.45,406.185,384,224,25.58 -gluon_resnet50_v1s,943.41,406.213,384,224,25.68 -ecaresnetlight,941.44,542.944,512,224,30.16 -ese_vovnet39b,941.23,543.33,512,224,24.57 -ecaresnext26t_32x4d,941.0,407.528,384,224,15.41 -dla60,940.59,407.297,384,224,22.04 -ecaresnext50t_32x4d,939.56,408.147,384,224,15.41 -eca_vovnet39b,935.89,546.442,512,224,22.6 -convit_tiny,932.74,410.683,384,224,5.71 -gcresnet33ts,930.55,274.114,256,256,19.88 -gmlp_ti16_224,928.92,411.858,384,224,5.87 -crossvit_9_dagger_240,926.84,412.865,384,240,8.78 -cspresnet50,926.15,413.781,384,256,21.62 -vgg11,923.83,554.05,512,224,132.86 -dla60x_c,916.37,557.77,512,224,1.32 -resnetblur50,915.4,418.683,384,224,25.56 -vit_base2_patch32_256,908.46,562.788,512,256,119.46 -ecaresnet50d_pruned,905.82,564.295,512,224,19.94 -rexnetr_200,893.29,213.797,192,224,16.52 -deit_small_patch16_224,893.26,429.034,384,224,22.05 -lambda_resnet26rpt_256,890.56,215.0,192,256,10.99 -vit_small_patch16_224,886.7,432.227,384,224,22.05 -cspresnext50,880.67,435.197,384,224,20.57 -nf_seresnet50,879.83,435.274,384,224,28.09 -cspresnet50w,877.16,436.915,384,256,28.12 -dpn68b,876.72,436.795,384,224,12.61 -selecsls84,869.46,587.629,512,224,50.95 -cspresnet50d,864.94,443.102,384,256,21.64 -hrnet_w18_small_v2,863.89,590.316,512,224,15.6 -deit_small_distilled_patch16_224,862.29,296.032,256,224,22.44 -resnetrs50,858.46,446.055,384,224,35.69 -densenet121,847.31,300.374,256,224,7.98 -seresnet50t,845.39,301.672,256,224,28.1 -tv_densenet121,843.62,301.628,256,224,7.98 -gluon_resnext50_32x4d,836.83,458.055,384,224,25.03 -rexnet_150,836.6,304.881,256,224,9.73 -tv_resnext50_32x4d,834.19,459.519,384,224,25.03 -swsl_resnext50_32x4d,834.14,459.541,384,224,25.03 -ssl_resnext50_32x4d,832.93,460.219,384,224,25.03 -resnext50_32x4d,832.41,460.523,384,224,25.03 -dpn68,829.49,461.803,384,224,12.61 -res2net50_26w_4s,828.02,307.899,256,224,25.7 -vovnet57a,825.25,464.451,384,224,36.64 -resnetblur50d,824.95,309.477,256,224,25.58 -pit_s_224,821.86,310.612,256,224,23.46 -efficientnet_b2_pruned,819.89,310.747,256,260,8.31 -pit_s_distilled_224,815.65,312.988,256,224,24.04 -skresnet50,813.96,313.131,256,224,25.8 -vgg11_bn,808.62,474.647,384,224,132.87 -densenet121d,807.2,315.378,256,224,8.0 -vit_base_resnet26d_224,803.08,476.892,384,224,101.4 -nf_ecaresnet50,802.77,477.356,384,224,25.56 -rexnet_130,798.18,319.593,256,224,7.56 -tf_efficientnet_b2_ap,795.21,239.963,192,260,9.11 -tf_efficientnet_b2,794.4,240.207,192,260,9.11 -regnetx_006,793.57,644.37,512,224,6.2 -tf_efficientnet_b2_ns,792.71,240.732,192,260,9.11 -gcresnet50t,789.8,322.677,256,256,25.9 -regnety_006,787.34,649.188,512,224,6.06 -ese_vovnet57b,786.57,487.301,384,224,38.61 -ecaresnet50d,779.07,327.677,256,224,25.58 -gluon_inception_v3,773.52,495.019,384,299,23.83 -inception_v3,772.81,495.53,384,299,23.83 -tf_inception_v3,770.52,496.982,384,299,23.83 -resnext50d_32x4d,766.06,333.341,256,224,25.05 -res2net50_14w_8s,764.36,332.765,256,224,25.06 -seresnetaa50d,763.26,334.261,256,224,28.11 -resnetv2_101,757.08,336.665,256,224,44.54 -mobilevit_xs,756.94,252.56,192,256,2.32 -resmlp_24_224,756.42,336.919,256,224,30.02 -resmlp_24_distilled_224,756.42,336.97,256,224,30.02 -adv_inception_v3,750.25,510.458,384,299,23.83 -skresnet50d,748.96,340.43,256,224,25.82 -dla60_res2net,743.7,342.834,256,224,20.85 -sehalonet33ts,741.65,344.36,256,256,13.69 -densenetblur121d,741.17,343.605,256,224,8.0 -resnet101,732.48,347.987,256,224,44.55 -gluon_resnet101_v1b,731.78,348.301,256,224,44.55 -efficientnet_b0_gn,728.3,350.425,256,224,5.29 -tv_resnet101,727.94,350.179,256,224,44.55 -efficientnet_b2a,716.29,266.588,192,288,9.11 -nf_resnet50,716.15,535.346,384,288,25.56 -nf_resnet101,716.05,534.647,384,224,44.55 -efficientnet_b2,714.18,267.365,192,288,9.11 -ecaresnet101d_pruned,711.06,718.295,512,224,24.88 -darknet53,702.74,363.511,256,256,41.61 -gluon_resnet101_v1c,701.82,363.226,256,224,44.57 -resnetv2_101d,700.7,363.831,256,224,44.56 -densenet169,700.47,362.977,256,224,14.15 -gluon_seresnext50_32x4d,700.46,364.36,256,224,27.56 -seresnext50_32x4d,699.23,365.027,256,224,27.56 -legacy_seresnext50_32x4d,697.76,365.743,256,224,27.56 -nf_regnet_b0,696.64,733.751,512,256,8.76 -dla60x,692.36,368.785,256,224,17.35 -poolformer_s24,685.09,372.431,256,224,21.39 -gluon_resnet101_v1d,678.31,375.898,256,224,44.57 -efficientnetv2_rw_t,675.19,282.266,192,288,13.65 -vgg13,667.6,575.009,384,224,133.05 -tf_efficientnetv2_b3,665.51,286.721,192,300,14.36 -convnext_tiny_hnf,664.96,384.0,256,224,28.59 -rexnet_200,662.14,288.822,192,224,16.37 -regnety_008,658.96,775.979,512,224,6.26 -wide_resnet50_2,657.26,583.464,384,224,68.88 -vit_small_r26_s32_224,656.89,388.437,256,224,36.43 -sebotnet33ts_256,656.8,194.107,128,256,13.7 -dla102,653.13,390.463,256,224,33.27 -vit_base_resnet50d_224,630.21,404.636,256,224,110.97 -mobilevit_s,629.43,303.928,192,256,5.58 -repvgg_b1,626.12,816.692,512,224,57.42 -gluon_resnet101_v1s,625.12,407.966,256,224,44.67 -resnetaa101d,624.52,408.356,256,224,44.57 -gmixer_24_224,623.55,409.084,256,224,24.72 -ecaresnet26t,622.79,410.514,256,320,16.01 -eca_botnext26ts_256,616.5,414.654,256,256,10.59 -resnext26ts,613.16,625.751,384,256,10.3 -eca_halonext26ts,603.84,423.35,256,256,10.76 -gc_efficientnetv2_rw_t,602.6,315.856,192,288,13.68 -eca_resnext26ts,600.19,425.981,256,256,10.3 -convnext_tiny,596.38,428.309,256,224,28.59 -seresnext26ts,596.22,428.706,256,256,10.39 -coat_lite_tiny,594.48,645.068,384,224,5.72 -regnetx_008,592.44,863.401,512,224,7.26 -semobilevit_s,588.43,325.035,192,256,5.74 -gcresnext26ts,588.04,434.525,256,256,10.48 -mixnet_m,587.11,652.551,384,224,5.01 -resnetv2_50x1_bit_distilled,582.57,328.74,192,224,25.55 -legacy_seresnet101,581.9,437.758,256,224,49.33 -cspdarknet53,581.74,439.027,256,256,27.64 -halonet50ts,578.04,331.194,192,256,22.73 -convnext_tiny_hnfd,577.71,442.141,256,224,28.63 -res2net50_26w_6s,575.17,443.355,256,224,37.05 -vgg13_bn,572.41,446.96,256,224,133.05 -resnetblur101d,571.53,446.389,256,224,44.57 -seresnet101,569.61,447.279,256,224,49.33 -xcit_small_12_p16_224,569.05,448.106,256,224,26.25 -coat_lite_mini,568.16,675.001,384,224,11.01 -xcit_small_12_p16_224_dist,566.71,449.975,256,224,26.25 -efficientnet_lite3,563.82,225.962,128,300,8.2 -tf_efficientnet_lite3,561.43,226.92,128,300,8.2 -tf_mixnet_m,548.78,698.227,384,224,5.01 -gluon_resnext101_32x4d,548.42,465.243,256,224,44.18 -swsl_resnext101_32x4d,547.31,466.21,256,224,44.18 -xcit_tiny_24_p16_224_dist,547.0,464.738,256,224,12.12 -ssl_resnext101_32x4d,546.67,466.798,256,224,44.18 -resnext101_32x4d,545.9,467.45,256,224,44.18 -xcit_tiny_24_p16_224,544.31,466.994,256,224,12.12 -densenet201,543.07,350.641,192,224,20.01 -vgg16,540.58,710.12,384,224,138.36 -twins_svt_small,538.2,474.088,256,224,24.06 -bat_resnext26ts,534.44,477.847,256,256,10.73 -mixer_b16_224_miil,533.51,479.062,256,224,59.88 -mixer_b16_224,533.49,479.056,256,224,59.88 -nf_seresnet101,527.72,482.805,256,224,49.33 -resnetv2_152,524.88,485.535,256,224,60.19 -gmlp_s16_224,524.3,364.698,192,224,19.42 -crossvit_small_240,523.32,365.287,192,240,26.86 -res2net101_26w_4s,521.59,365.626,192,224,45.21 -botnet50ts_256,517.93,246.212,128,256,22.74 -efficientnet_b3_pruned,516.58,493.917,256,300,9.86 -vit_base_r26_s32_224,515.2,371.411,192,224,101.38 -nf_regnet_b3,513.91,496.324,256,320,18.59 -res2next50,505.83,504.834,256,224,24.67 -dla102x,504.27,379.22,192,224,26.31 -xcit_nano_12_p16_384_dist,504.22,505.947,256,384,3.05 -resnet50_gn,503.53,380.489,192,224,25.56 -mixnet_l,503.2,507.181,256,224,7.33 -resnet152,499.49,382.202,192,224,60.19 -gluon_resnet152_v1b,499.26,382.341,192,224,60.19 -resmlp_36_224,498.84,382.725,192,224,44.69 -tv_resnet152,497.88,383.389,192,224,60.19 -mixer_l32_224,496.73,385.058,192,224,206.94 -resmlp_36_distilled_224,495.13,385.629,192,224,44.69 -visformer_tiny,493.66,1036.466,512,224,10.32 -halo2botnet50ts_256,493.38,258.451,128,256,22.64 -cait_xxs24_224,493.27,516.559,256,224,11.96 -xception,492.05,259.342,128,299,22.86 -vit_base_patch32_384,491.11,520.434,256,384,88.3 -vit_large_patch32_224,490.76,520.06,256,224,306.54 -gluon_resnet152_v1c,485.71,393.072,192,224,60.21 -resnetv2_152d,485.01,393.607,192,224,60.2 -res2net50_26w_8s,477.37,400.062,192,224,48.4 -crossvit_15_240,477.11,400.634,192,240,27.53 -gluon_resnet152_v1d,473.85,402.963,192,224,60.21 -tf_mixnet_l,473.66,538.956,256,224,7.33 -ecaresnet101d,472.0,540.618,256,224,44.57 -vgg16_bn,467.67,547.066,256,224,138.37 -crossvit_15_dagger_240,464.95,411.108,192,240,28.21 -nf_ecaresnet101,463.81,550.107,256,224,44.55 -efficientnet_el,455.11,280.196,128,300,10.59 -poolformer_s36,454.99,420.116,192,224,30.86 -efficientnet_el_pruned,454.4,280.625,128,300,10.59 -swin_tiny_patch4_window7_224,453.0,564.154,256,224,28.29 -gluon_resnet152_v1s,449.55,424.842,192,224,60.32 -vgg19,448.89,855.203,384,224,143.67 -fbnetv3_g,446.79,284.505,128,288,16.62 -ese_vovnet99b,446.63,571.682,256,224,63.2 -gluon_seresnext101_32x4d,445.56,428.728,192,224,48.96 -legacy_seresnext101_32x4d,443.64,430.564,192,224,48.96 -seresnext101_32x4d,442.87,431.396,192,224,48.96 -tf_efficientnet_el,442.83,287.962,128,300,10.59 -skresnext50_32x4d,441.31,578.719,256,224,27.48 -twins_pcpvt_small,440.34,579.752,256,224,24.11 -dla60_res2next,439.19,581.507,256,224,17.03 -ese_vovnet39b_evos,437.95,291.344,128,224,24.58 -dla169,436.27,437.707,192,224,53.39 -hrnet_w32,434.6,437.22,192,224,41.23 -hrnet_w18,419.74,605.263,256,224,21.3 -swin_s3_tiny_224,418.05,458.308,192,224,28.33 -convit_small,417.6,458.784,192,224,27.78 -vit_tiny_patch16_384,413.0,309.097,128,384,5.79 -vit_small_resnet50d_s16_224,412.12,464.661,192,224,57.53 -vgg19_bn,402.52,635.599,256,224,143.68 -inception_v4,396.8,481.741,192,299,42.68 -ecaresnet50t,394.31,323.698,128,320,25.57 -tf_efficientnet_b3,389.49,327.004,128,300,12.23 -legacy_seresnet152,389.45,489.771,192,224,66.82 -tf_efficientnet_b3_ap,388.84,327.542,128,300,12.23 -tf_efficientnet_b3_ns,388.78,327.565,128,300,12.23 -xcit_nano_12_p8_224_dist,387.21,659.394,256,224,3.05 -convnext_small,384.54,497.552,192,224,50.22 -xcit_nano_12_p8_224,384.13,664.719,256,224,3.05 -regnetx_016,380.23,1345.67,512,224,9.19 -swin_v2_cr_tiny_224,379.31,504.955,192,224,28.33 -repvgg_b2,378.58,1351.362,512,224,89.02 -densenet161,378.04,336.272,128,224,28.68 -haloregnetz_b,373.44,684.066,256,224,11.68 -seresnet152,368.67,343.988,128,224,66.82 -volo_d1_224,368.14,346.356,128,224,26.63 -dla102x2,362.23,351.833,128,224,41.28 -swin_v2_cr_tiny_ns_224,361.82,529.379,192,224,28.33 -vit_base_patch16_224_miil,361.72,353.077,128,224,86.54 -nest_tiny,360.72,353.977,128,224,17.06 -gluon_resnext101_64x4d,360.58,353.482,128,224,83.46 -jx_nest_tiny,360.01,354.671,128,224,17.06 -wide_resnet101_2,358.04,534.717,192,224,126.89 -deit_base_patch16_224,356.6,358.132,128,224,86.57 -vit_base_patch16_224,355.86,358.875,128,224,86.57 -vit_base_patch16_224_sam,355.66,359.078,128,224,86.57 -resnet200,355.09,357.637,128,224,64.67 -regnety_016,353.22,1447.724,512,224,11.2 -xception41p,353.13,361.611,128,299,26.91 -deit_base_distilled_patch16_224,352.06,362.734,128,224,87.34 -efficientnet_b3a,350.83,363.194,128,320,12.23 -efficientnet_b3,350.78,363.262,128,320,12.23 -resnest14d,349.46,1464.67,512,224,10.61 -crossvit_18_240,347.41,366.517,128,240,43.27 -hrnet_w30,347.21,732.586,256,224,37.71 -inception_resnet_v2,342.0,558.107,192,299,55.84 -ens_adv_inception_resnet_v2,341.96,558.12,192,299,55.84 -crossvit_18_dagger_240,338.55,376.059,128,240,44.27 -efficientnet_lite4,334.77,189.845,64,380,13.01 -dpn92,332.74,767.899,256,224,37.67 -nf_regnet_b1,332.08,1540.325,512,288,10.22 -coat_lite_small,330.21,579.992,192,224,19.84 -resnet101d,329.64,386.792,128,320,44.57 -mixnet_xl,327.95,583.611,192,224,11.9 -beit_base_patch16_224,326.86,390.577,128,224,86.53 -tf_efficientnet_lite4,322.3,197.262,64,380,13.01 -resnetrs101,319.8,398.042,128,288,63.62 -twins_pcpvt_base,319.06,599.001,192,224,43.83 -cait_xxs36_224,317.98,398.889,128,224,17.3 -gcresnext50ts,316.46,605.234,192,256,15.67 -resnetv2_50d_gn,315.97,404.249,128,288,25.57 -repvgg_b3,314.46,1220.096,384,224,123.09 -gluon_seresnext101_64x4d,311.54,408.706,128,224,88.23 -twins_svt_base,310.17,410.642,128,224,56.07 -regnetz_d8,308.13,206.12,64,320,23.37 -poolformer_m36,305.55,417.03,128,224,56.17 -xception41,305.2,418.184,128,299,26.97 -resnetv2_50d_frn,299.55,426.215,128,224,25.59 -efficientnetv2_s,298.13,319.843,96,384,21.46 -efficientnetv2_rw_s,294.35,215.203,64,384,23.94 -swin_small_patch4_window7_224,293.69,434.018,128,224,49.61 -tf_efficientnetv2_s,292.33,326.193,96,384,21.46 -hrnet_w40,292.01,652.817,192,224,57.56 -tf_efficientnetv2_s_in21ft1k,290.7,328.02,96,384,21.46 -pit_b_224,290.65,329.366,96,224,73.76 -xcit_small_24_p16_224_dist,289.62,438.649,128,224,47.67 -xcit_small_24_p16_224,289.57,438.594,128,224,47.67 -regnetz_005,289.37,1767.969,512,224,7.12 -pit_b_distilled_224,289.24,330.966,96,224,74.79 -nf_regnet_b2,283.49,1804.47,512,272,14.31 -dpn98,282.57,451.401,128,224,61.57 -gluon_xception65,280.65,340.128,96,299,39.92 -convnext_base,280.05,455.331,128,224,88.59 -convnext_base_in22ft1k,278.55,457.745,128,224,88.59 -convnext_small_in22ft1k,278.52,457.835,128,224,88.59 -resnet51q,278.38,688.843,192,288,35.7 -convnext_tiny_in22ft1k,278.23,458.306,128,224,88.59 -xception65,278.17,343.202,96,299,39.92 -nf_regnet_b4,276.19,461.347,128,384,30.21 -xcit_tiny_12_p8_224,275.08,463.559,128,224,6.71 -xcit_tiny_12_p8_224_dist,274.14,465.135,128,224,6.71 -xception65p,273.65,466.496,128,299,39.82 -cait_s24_224,273.57,465.435,128,224,46.92 -hrnet_w48,266.71,475.16,128,224,77.47 -vit_small_patch16_18x2_224,263.99,482.238,128,224,64.67 -vit_small_patch16_36x1_224,259.67,367.102,96,224,64.67 -resnest50d_1s4x24d,257.47,992.99,256,224,25.68 -resnest26d,255.39,1502.806,384,224,17.07 -regnetz_c16,250.02,510.536,128,320,13.46 -gmlp_b16_224,249.07,383.895,96,224,73.08 -hrnet_w44,242.27,787.905,192,224,67.06 -twins_svt_large,238.88,533.776,128,224,99.27 -efficientnet_b4,238.09,266.775,64,384,19.34 -nest_small,237.16,403.167,96,224,38.35 -jx_nest_small,237.15,403.154,96,224,38.35 -swin_v2_cr_small_224,235.88,404.597,96,224,49.7 -resnetv2_50d_evob,235.37,406.693,96,224,25.59 -crossvit_base_240,233.19,410.026,96,240,105.03 -visformer_small,233.03,1647.198,384,224,40.22 -tf_efficientnet_b4_ns,232.84,272.816,64,380,19.34 -nfnet_l0,232.69,1098.999,256,288,35.07 -tf_efficientnet_b4_ap,232.56,273.059,64,380,19.34 -tresnet_m,232.35,2200.869,512,224,31.39 -tf_efficientnet_b4,232.32,273.464,64,380,19.34 -coat_tiny,232.24,549.137,128,224,5.5 -swin_s3_small_224,226.56,421.928,96,224,49.74 -twins_pcpvt_large,226.38,561.433,128,224,60.99 -eca_nfnet_l0,225.65,1133.48,256,288,24.14 -swin_base_patch4_window7_224,225.24,566.471,128,224,87.77 -vit_large_r50_s32_224,223.42,427.305,96,224,328.99 -densenet264,221.03,430.404,96,224,72.69 -resnetv2_50d_evos,220.72,288.818,64,288,25.59 -hrnet_w64,220.46,575.895,128,224,128.06 -convit_base,218.2,438.93,96,224,86.54 -resnet152d,215.82,442.51,96,320,60.21 -resnext101_64x4d,215.79,443.36,96,288,83.46 -xception71,214.33,296.52,64,299,42.34 -vit_small_r26_s32_384,213.14,298.982,64,384,36.47 -volo_d2_224,211.05,453.161,96,224,58.68 -vit_small_patch16_384,211.02,302.439,64,384,22.2 -dpn131,210.85,605.028,128,224,79.25 -xcit_medium_24_p16_224_dist,210.73,452.215,96,224,84.4 -xcit_medium_24_p16_224,210.37,452.835,96,224,84.4 -resnet61q,208.57,612.704,128,288,36.85 -mixnet_xxl,207.05,616.266,128,224,23.96 -vit_base_r50_s16_224,197.64,322.234,64,224,98.66 -coat_mini,197.23,646.961,128,224,10.34 -xcit_small_12_p16_384_dist,195.15,490.178,96,384,26.25 -poolformer_m48,192.74,495.644,96,224,73.47 -xcit_tiny_24_p16_384_dist,188.23,506.657,96,384,12.12 -seresnet200d,187.28,508.352,96,256,71.86 -ecaresnet200d,180.23,529.288,96,256,64.69 -regnetz_b16,180.04,1064.958,192,288,9.72 -convmixer_768_32,179.96,532.189,96,224,21.11 -repvgg_b1g4,179.05,2858.541,512,224,39.97 -regnetx_032,178.17,2153.981,384,224,15.3 -nest_base,178.06,357.8,64,224,67.72 -regnety_032,177.84,1438.077,256,288,19.44 -jx_nest_base,177.82,358.268,64,224,67.72 -resnest50d,177.64,1439.759,256,224,27.48 -gluon_senet154,176.66,540.173,96,224,115.09 -legacy_senet154,176.51,540.595,96,224,115.09 -swin_v2_cr_base_224,176.18,360.924,64,224,87.88 -senet154,175.91,542.436,96,224,115.09 -swin_s3_base_224,175.78,361.468,64,224,71.13 -dpn107,172.56,554.611,96,224,86.92 -seresnet152d,171.73,369.416,64,320,66.84 -resnetrs152,170.84,371.345,64,320,86.62 -halonet_h1,170.19,374.644,64,256,8.1 -resnet200d,166.41,381.713,64,320,64.69 -resnest50d_4s2x40d,165.16,1548.618,256,224,30.42 -efficientnet_b3_gn,165.05,386.066,64,320,11.73 -convnext_large_in22ft1k,165.0,580.132,96,224,197.77 -mixer_l16_224,164.87,580.828,96,224,208.2 -convnext_large,164.55,581.706,96,224,197.77 -regnetx_040,161.41,2377.974,384,224,22.12 -tnt_s_patch16_224,160.55,795.443,128,224,23.76 -regnety_040s_gn,150.6,848.376,128,224,20.65 -regnetx_080,149.33,2570.458,384,224,39.57 -efficientnetv2_m,148.8,319.462,48,416,54.14 -vit_large_patch32_384,148.01,430.873,64,384,306.63 -xcit_small_12_p8_224,147.15,433.155,64,224,26.21 -xcit_small_12_p8_224_dist,147.09,433.349,64,224,26.21 -ssl_resnext101_32x8d,147.0,869.242,128,224,88.79 -ig_resnext101_32x8d,146.08,874.69,128,224,88.79 -resnext101_32x8d,145.7,876.913,128,224,88.79 -swsl_resnext101_32x8d,145.58,877.666,128,224,88.79 -regnetz_e8,145.15,328.705,48,320,57.7 -volo_d3_224,144.0,442.004,64,224,86.33 -xcit_tiny_24_p8_224,141.24,676.422,96,224,12.11 -xcit_tiny_24_p8_224_dist,141.08,677.134,96,224,12.11 -resnetv2_50x1_bitm,139.17,344.083,48,448,25.55 -seresnet269d,135.41,466.832,64,256,113.67 -swin_large_patch4_window7_224,135.03,472.167,64,224,196.53 -xcit_nano_12_p8_384_dist,130.74,487.752,64,384,3.05 -tnt_b_patch16_224,128.41,745.748,96,224,65.41 -xcit_large_24_p16_224,126.55,502.346,64,224,189.1 -xcit_large_24_p16_224_dist,126.43,502.798,64,224,189.1 -efficientnetv2_rw_m,125.71,251.147,32,416,53.24 -regnetx_064,124.66,2052.691,256,224,26.21 -resnetrs200,122.11,388.798,48,320,93.21 -dm_nfnet_f0,120.79,1588.27,192,256,71.49 -regnety_040,120.68,1589.481,192,288,20.65 -nfnet_f0,120.42,2124.657,256,256,71.49 -regnetv_040,118.46,1079.092,128,288,20.64 -ese_vovnet99b_iabn,118.26,3243.909,384,224,63.2 -regnetz_b16_evos,116.8,546.096,64,288,9.74 -efficientnet_b0_g8_gn,116.53,2195.74,256,224,6.56 -regnetz_c16_evos,114.31,418.055,48,320,13.49 -swin_v2_cr_large_224,108.78,438.885,48,224,196.68 -tf_efficientnetv2_m_in21ft1k,108.7,291.236,32,480,54.14 -tf_efficientnetv2_m,108.35,292.175,32,480,54.14 -vit_large_patch16_224,108.17,442.193,48,224,304.33 -convnext_xlarge_in22ft1k,107.24,595.043,64,224,350.2 -crossvit_15_dagger_408,104.58,304.132,32,408,28.5 -tresnet_l,104.32,4904.502,512,224,55.99 -vit_base_patch16_18x2_224,104.09,458.533,48,224,256.73 -repvgg_b2g4,101.53,5041.523,512,224,61.76 -eca_nfnet_l1,100.88,1267.001,128,320,41.41 -beit_large_patch16_224,100.32,476.403,48,224,304.43 -xcit_small_24_p16_384_dist,99.8,477.482,48,384,47.67 -cspdarknet53_iabn,98.78,3885.053,384,256,27.64 -efficientnet_b5,96.37,329.642,32,456,30.39 -convnext_tiny_384_in22ft1k,96.12,497.65,48,384,88.59 -convnext_small_384_in22ft1k,96.06,497.96,48,384,88.59 -convnext_base_384_in22ft1k,95.88,498.886,48,384,88.59 -tf_efficientnet_b5,94.64,335.672,32,456,30.39 -tf_efficientnet_b5_ns,94.45,336.36,32,456,30.39 -tf_efficientnet_b5_ap,94.33,336.768,32,456,30.39 -regnetz_d8_evos,94.31,337.348,32,320,23.46 -xcit_tiny_12_p8_384_dist,94.1,508.387,48,384,6.71 -volo_d4_224,93.96,508.449,48,224,192.96 -regnetz_040h,93.67,681.392,64,320,28.94 -regnetz_040,93.38,683.596,64,320,27.12 -volo_d1_384,93.34,341.484,32,384,26.78 -deit_base_patch16_384,91.68,348.207,32,384,86.86 -tresnet_xl,91.43,4196.241,384,224,78.44 -vit_base_patch16_384,91.19,350.061,32,384,86.86 -swin_v2_cr_tiny_384,90.49,352.393,32,384,28.33 -cspresnext50_iabn,90.44,4243.373,384,256,20.57 -deit_base_distilled_patch16_384,89.77,355.647,32,384,87.63 -resnest101e,89.04,1435.031,128,256,48.28 -cait_xxs24_384,87.86,361.779,32,384,12.03 -resnetv2_152x2_bit_teacher,86.24,368.749,32,224,236.34 -nf_regnet_b5,85.98,741.696,64,456,49.74 -resnetv2_101x1_bitm,85.74,371.65,32,448,44.54 -repvgg_b3g4,84.87,4523.286,384,224,83.83 -seresnext101_32x8d,82.05,777.804,64,288,93.57 -crossvit_18_dagger_408,78.89,302.153,24,408,44.61 -regnetx_120,77.59,3298.519,256,224,46.11 -beit_base_patch16_384,77.5,308.622,24,384,86.74 -ecaresnet269d,77.22,409.805,32,352,102.09 -vit_large_patch14_224,76.42,417.211,32,224,304.2 -pnasnet5large,76.37,415.337,32,331,86.06 -regnety_120,76.06,2523.147,192,224,51.82 -xcit_small_24_p8_224_dist,74.34,427.129,32,224,47.63 -xcit_small_24_p8_224,74.3,427.381,32,224,47.63 -vit_large_r50_s32_384,74.29,428.354,32,384,329.09 -resnetrs270,73.96,426.877,32,352,129.86 -regnety_064,72.72,1758.529,128,288,30.58 -xcit_medium_24_p16_384_dist,72.0,441.154,32,384,84.4 -regnetv_064,71.99,1776.312,128,288,30.58 -regnetz_d32,71.61,892.143,64,320,27.58 -resmlp_big_24_224,67.65,471.502,32,224,129.14 -resmlp_big_24_distilled_224,67.55,472.229,32,224,129.14 -resmlp_big_24_224_in22ft1k,67.54,472.283,32,224,129.14 -regnety_320,67.39,1897.989,128,224,145.05 -nasnetalarge,66.66,475.073,32,331,88.75 -regnetx_160,64.8,2961.678,192,224,54.28 -regnety_080,64.56,1981.56,128,288,39.18 -efficientnet_b3_g8_gn,62.22,1026.855,64,320,14.25 -convmixer_1024_20_ks9_p14,61.3,4175.375,256,224,24.38 -swin_base_patch4_window12_384,61.18,390.429,24,384,87.9 -cait_xs24_384,60.88,391.766,24,384,26.67 -efficientnetv2_l,60.88,258.466,16,480,118.52 -efficientnet_b0_g16_evos,60.54,6341.858,384,224,8.11 -volo_d5_224,60.14,529.003,32,224,295.46 -tf_efficientnetv2_l_in21ft1k,59.38,265.08,16,480,118.52 -tf_efficientnetv2_l,59.33,265.325,16,480,118.52 -vit_base_patch8_224,58.77,271.439,16,224,86.58 -cait_xxs36_384,57.81,411.427,24,384,17.37 -convnext_large_384_in22ft1k,56.3,566.668,32,384,197.77 -xcit_medium_24_p8_224,55.39,574.459,32,224,84.32 -xcit_medium_24_p8_224_dist,55.37,574.617,32,224,84.32 -vit_base_r50_s16_384,54.43,292.359,16,384,98.95 -vit_base_resnet50_384,54.42,292.382,16,384,98.95 -swin_v2_cr_small_384,54.01,293.873,16,384,49.7 -tresnet_m_448,53.37,3595.072,192,448,31.39 -volo_d2_384,52.96,300.372,16,384,58.87 -xcit_small_12_p8_384_dist,50.48,473.643,24,384,26.21 -regnety_160,48.6,1974.142,96,288,83.59 -xcit_tiny_24_p8_384_dist,47.78,666.46,32,384,12.11 -swsl_resnext101_32x16d,47.43,2022.519,96,224,194.03 -ig_resnext101_32x16d,47.42,2022.744,96,224,194.03 -ssl_resnext101_32x16d,47.33,2027.008,96,224,194.03 -resnetrs350,46.92,503.827,24,384,163.96 -regnetx_320,46.0,2781.369,128,224,107.81 -cait_s24_384,45.47,349.358,16,384,47.06 -eca_nfnet_l2,44.85,1424.203,64,384,56.72 -swin_v2_cr_huge_224,44.03,360.964,16,224,657.83 -xcit_large_24_p16_384_dist,43.83,544.238,24,384,189.1 -efficientnet_b6,42.4,374.556,16,528,43.04 -swin_v2_cr_base_384,41.62,382.084,16,384,87.88 -tf_efficientnet_b6,41.4,383.615,16,528,43.04 -tf_efficientnet_b6_ns,41.39,383.737,16,528,43.04 -tf_efficientnet_b6_ap,41.38,383.814,16,528,43.04 -nfnet_f1,40.44,2371.983,96,320,132.63 -dm_nfnet_f1,38.48,1661.038,64,320,132.63 -vit_huge_patch14_224,38.43,414.258,16,224,632.05 -swin_large_patch4_window12_384,37.29,427.283,16,384,196.74 -efficientnet_b7,36.33,216.757,8,600,66.35 -tf_efficientnetv2_xl_in21ft1k,36.25,325.472,12,512,208.12 -tf_efficientnet_b7_ap,35.67,220.798,8,600,66.35 -tf_efficientnet_b7_ns,35.48,221.953,8,600,66.35 -tf_efficientnet_b7,35.47,221.939,8,600,66.35 -efficientnetv2_xl,35.3,334.216,12,512,208.12 -convnext_xlarge_384_in22ft1k,34.93,456.323,16,384,350.2 -xcit_large_24_p8_224_dist,32.32,491.645,16,224,188.93 -xcit_large_24_p8_224,32.31,491.872,16,224,188.93 -densenet264d_iabn,32.2,3970.866,128,224,72.74 -resnetrs420,31.96,491.372,16,416,191.89 -resnetv2_50x3_bitm,31.49,507.255,16,448,217.32 -resnest200e,31.48,1519.686,48,320,70.2 -cait_s36_384,29.84,398.239,12,384,68.37 -resnetv2_152x2_bit_teacher_384,29.48,404.769,12,384,236.34 -vit_large_patch16_384,26.9,295.811,8,384,304.72 -xcit_small_24_p8_384_dist,25.67,620.053,16,384,47.63 -tresnet_l_448,25.26,5063.842,128,448,55.99 -swin_v2_cr_large_384,24.64,322.332,8,384,196.68 -eca_nfnet_l3,24.27,1315.168,32,448,72.04 -beit_large_patch16_384,23.0,345.85,8,384,305.0 -tresnet_xl_448,22.99,4172.388,96,448,78.44 -efficientnet_cc_b0_8e,22.43,42.825,1,224,24.01 -nfnet_f2,22.22,2156.946,48,352,193.78 -volo_d3_448,22.16,268.408,6,448,86.63 -vit_giant_patch14_224,21.83,363.834,8,224,1012.61 -dm_nfnet_f2,21.64,1475.547,32,352,193.78 -resnetv2_152x2_bitm,21.52,369.432,8,448,236.34 -efficientnet_cc_b0_4e,20.51,46.86,1,224,13.31 -tf_efficientnet_cc_b0_4e,19.96,48.206,1,224,13.31 -xcit_medium_24_p8_384_dist,18.25,434.872,8,384,84.32 -ig_resnext101_32x32d,18.09,1767.053,32,224,468.53 -tf_efficientnet_cc_b0_8e,17.78,54.484,1,224,24.01 -efficientnet_cc_b1_8e,17.74,54.107,1,240,39.72 -resnetv2_101x3_bitm,17.38,458.802,8,448,387.93 -tf_efficientnet_cc_b1_8e,17.01,56.332,1,240,39.72 -volo_d4_448,16.53,360.493,6,448,193.41 -resnest269e,13.1,1825.366,24,416,110.93 -efficientnet_b8,12.26,485.693,6,672,87.41 -nfnet_f3,12.1,1978.567,24,416,254.92 -tf_efficientnet_b8,11.89,500.911,6,672,87.41 -tf_efficientnet_b8_ap,11.89,500.858,6,672,87.41 -dm_nfnet_f3,11.77,2034.476,24,416,254.92 -cait_m36_384,11.53,516.589,6,384,271.22 -xcit_large_24_p8_384_dist,11.09,537.486,6,384,188.93 -volo_d5_448,10.86,365.099,4,448,295.91 -swin_v2_cr_huge_384,9.72,306.157,3,384,657.94 -convmixer_1536_20,9.61,4992.24,48,224,51.63 -tf_efficientnet_l2_ns_475,8.93,330.392,3,475,480.31 -ig_resnext101_32x48d,8.5,1880.833,16,224,828.41 -beit_large_patch16_512,8.47,351.949,3,512,305.67 -volo_d5_512,6.98,283.446,2,512,296.09 -nfnet_f4,6.43,1861.542,12,512,316.07 -dm_nfnet_f4,6.21,1926.442,12,512,316.07 -cait_m48_448,4.67,423.202,2,448,356.46 -nfnet_f5,4.64,1718.999,8,544,377.21 -dm_nfnet_f5,4.45,1789.915,8,544,377.21 -nfnet_f6,3.52,1695.187,6,576,438.36 -dm_nfnet_f6,3.37,1774.692,6,576,438.36 -resnetv2_152x4_bitm,3.2,310.383,1,480,936.53 -nfnet_f7,2.65,1499.45,4,608,499.5 -efficientnet_l2,2.12,466.427,1,800,480.31 -tf_efficientnet_l2_ns,2.09,472.26,1,800,480.31 diff --git a/results/benchmark-train-amp-nhwc-pt112-cu113-rtx3090.csv b/results/benchmark-train-amp-nhwc-pt112-cu113-rtx3090.csv new file mode 100644 index 00000000..3c0025c8 --- /dev/null +++ b/results/benchmark-train-amp-nhwc-pt112-cu113-rtx3090.csv @@ -0,0 +1,835 @@ +model,train_samples_per_sec,train_step_time,train_batch_size,train_img_size,param_count +tinynet_e,11915.85,41.681,512,106,2.04 +mobilenetv3_small_050,11290.99,44.293,512,224,1.59 +lcnet_035,10015.98,50.125,512,224,1.64 +lcnet_050,9286.37,54.37,512,224,1.88 +tf_mobilenetv3_small_minimal_100,9042.22,55.986,512,224,2.04 +mobilenetv3_small_075,8679.98,58.254,512,224,2.04 +mobilenetv3_small_100,8035.08,62.981,512,224,2.54 +tinynet_d,7990.69,63.223,512,152,2.34 +tf_mobilenetv3_small_075,7930.1,63.8,512,224,2.04 +tf_mobilenetv3_small_100,7330.24,69.047,512,224,2.54 +lcnet_075,6950.91,73.156,512,224,2.36 +levit_128s,6539.16,77.346,512,224,7.78 +resnet10t,6318.63,80.774,512,176,5.44 +mnasnet_small,5607.09,90.422,512,224,2.03 +lcnet_100,5354.67,95.126,512,224,2.95 +mixer_s32_224,4943.04,103.013,512,224,19.1 +mobilenetv2_035,4789.43,106.101,512,224,1.68 +mnasnet_050,4680.08,108.62,512,224,2.22 +levit_128,4558.28,111.213,512,224,9.21 +cs3darknet_focus_s,4469.48,114.041,512,256,3.27 +vit_small_patch32_224,4445.76,114.324,512,224,22.88 +tinynet_c,4167.16,121.826,512,184,2.46 +gernet_s,4165.03,122.198,512,224,8.17 +cs3darknet_s,4110.51,124.007,512,256,3.28 +regnetx_002,4105.04,124.027,512,224,2.68 +mobilenetv2_050,4051.14,125.606,512,224,1.97 +vit_tiny_r_s16_p8_224,4025.23,126.328,512,224,6.34 +semnasnet_050,3904.91,130.185,512,224,2.08 +regnety_002,3777.81,134.562,512,224,3.16 +levit_192,3727.29,136.213,512,224,10.95 +ghostnet_050,3670.99,138.144,512,224,2.59 +ese_vovnet19b_slim_dw,3629.92,140.575,512,224,1.9 +lcnet_150,3576.28,142.665,512,224,4.5 +gluon_resnet18_v1b,3482.17,146.691,512,224,11.69 +resnet18,3481.78,146.713,512,224,11.69 +swsl_resnet18,3480.5,146.765,512,224,11.69 +ssl_resnet18,3477.04,146.904,512,224,11.69 +resnet14t,3472.37,147.102,512,176,10.08 +tf_efficientnetv2_b0,3428.08,148.143,512,192,7.14 +tf_mobilenetv3_large_minimal_100,3366.45,151.356,512,224,3.92 +mnasnet_075,3238.88,157.273,512,224,3.17 +tf_mobilenetv3_large_075,3189.08,159.67,512,224,3.99 +seresnet18,3138.91,162.608,512,224,11.78 +mobilenetv3_large_075,3095.0,164.56,512,224,3.99 +legacy_seresnet18,3076.04,165.928,512,224,11.78 +hardcorenas_a,2971.63,171.576,512,224,5.26 +levit_256,2956.43,172.043,512,224,18.89 +mnasnet_b1,2930.02,173.933,512,224,4.38 +mnasnet_100,2929.31,173.976,512,224,4.38 +tf_mobilenetv3_large_100,2907.93,175.204,512,224,5.48 +resnet18d,2875.3,177.69,512,224,11.71 +tinynet_b,2851.82,178.435,512,188,3.73 +hardcorenas_b,2772.42,183.73,512,224,5.18 +hardcorenas_c,2763.94,184.272,512,224,5.52 +mobilenetv3_rw,2754.46,184.981,512,224,5.48 +nf_regnet_b0,2740.89,185.595,512,192,8.76 +mobilenetv3_large_100_miil,2733.62,186.4,512,224,5.48 +mobilenetv3_large_100,2732.43,186.472,512,224,5.48 +ese_vovnet19b_slim,2684.58,190.344,512,224,3.17 +spnasnet_100,2610.47,195.171,512,224,4.42 +mobilenetv2_075,2609.91,195.379,512,224,2.64 +semnasnet_075,2603.1,195.762,512,224,2.91 +hardcorenas_d,2566.48,198.271,512,224,7.5 +tf_efficientnetv2_b1,2548.95,199.349,512,192,8.14 +levit_256d,2522.09,201.424,512,224,26.21 +fbnetc_100,2397.58,212.548,512,224,5.57 +tinynet_a,2334.41,218.035,512,192,6.19 +mobilenetv2_100,2313.1,220.563,512,224,3.5 +vit_tiny_patch16_224,2299.56,221.804,512,224,5.72 +mnasnet_a1,2291.94,222.453,512,224,3.89 +deit_tiny_patch16_224,2290.33,222.697,512,224,5.72 +semnasnet_100,2279.15,223.737,512,224,3.89 +edgenext_xx_small,2271.04,224.572,512,256,1.33 +dla46_c,2266.89,225.115,512,224,1.3 +hardcorenas_f,2252.64,226.141,512,224,8.2 +deit_tiny_distilled_patch16_224,2248.67,226.799,512,224,5.91 +hardcorenas_e,2245.94,226.861,512,224,8.07 +xcit_nano_12_p16_224_dist,2177.52,233.052,512,224,3.05 +xcit_nano_12_p16_224,2170.17,234.054,512,224,3.05 +tf_efficientnet_lite0,2134.89,239.057,512,224,4.65 +ghostnet_100,2129.82,239.0,512,224,5.18 +hrnet_w18_small,2121.96,239.906,512,224,13.19 +regnety_004,2085.76,244.311,512,224,4.34 +efficientnet_lite0,2079.28,245.485,512,224,4.65 +cs3darknet_focus_m,2062.98,247.547,512,256,9.3 +pit_ti_distilled_224,2061.94,247.414,512,224,5.1 +mnasnet_140,2060.59,247.645,512,224,7.12 +pit_ti_224,2057.02,247.989,512,224,4.85 +gluon_resnet34_v1b,2039.68,250.446,512,224,21.8 +tv_resnet34,2038.39,250.573,512,224,21.8 +resnet34,2036.51,250.813,512,224,21.8 +ese_vovnet19b_dw,1999.58,255.562,512,224,6.54 +resnet26,1962.0,260.488,512,224,16.0 +tf_efficientnetv2_b2,1951.52,260.748,512,208,10.1 +skresnet18,1943.81,262.753,512,224,11.96 +cs3darknet_m,1940.79,263.122,512,256,9.31 +regnetz_005,1916.17,265.765,512,224,7.12 +resnetblur18,1897.99,269.406,512,224,11.69 +rexnetr_100,1893.12,201.724,384,224,4.88 +nf_resnet26,1869.64,273.344,512,224,16.0 +mobilenetv2_110d,1868.27,204.505,384,224,4.52 +visformer_tiny,1861.63,274.356,512,224,10.32 +mixer_b32_224,1856.75,274.965,512,224,60.29 +seresnet34,1837.21,277.783,512,224,21.96 +fbnetv3_b,1825.5,278.744,512,224,8.6 +mobilevitv2_050,1824.87,279.552,512,256,1.37 +gernet_m,1822.12,280.293,512,224,21.14 +resnet34d,1813.16,281.758,512,224,21.82 +levit_384,1801.0,283.153,512,224,39.13 +legacy_seresnet34,1781.32,286.529,512,224,21.96 +regnetx_004,1780.61,286.47,512,224,5.16 +tf_efficientnet_b0_ns,1779.24,214.77,384,224,5.29 +tf_efficientnet_b0,1779.02,214.765,384,224,5.29 +tf_efficientnet_b0_ap,1777.73,214.898,384,224,5.29 +efficientnet_b0,1751.72,291.183,512,224,5.29 +selecsls42,1718.76,297.231,512,224,30.35 +selecsls42b,1710.18,298.726,512,224,32.46 +vit_base_patch32_224,1708.63,298.818,512,224,88.22 +vit_base_patch32_224_sam,1707.5,298.997,512,224,88.22 +efficientnet_es_pruned,1687.32,302.688,512,224,5.44 +resnetrs50,1686.45,302.42,512,160,35.69 +efficientnet_es,1686.11,302.906,512,224,5.44 +mixer_s16_224,1660.76,307.737,512,224,18.53 +darknet17,1654.01,309.253,512,256,14.3 +mobilenetv2_140,1637.57,233.691,384,224,6.11 +fbnetv3_d,1634.54,233.136,384,224,10.31 +tf_efficientnet_es,1623.9,314.542,512,224,5.44 +resnet26d,1623.31,314.899,512,224,16.01 +mobilevit_xxs,1602.81,238.427,384,256,1.27 +resmlp_12_distilled_224,1577.54,323.769,512,224,15.35 +resmlp_12_224,1577.31,323.803,512,224,15.35 +pit_xs_224,1555.66,328.198,512,224,10.62 +pit_xs_distilled_224,1555.48,328.255,512,224,11.0 +semnasnet_140,1546.19,330.184,512,224,6.11 +ghostnet_130,1542.47,330.535,512,224,7.36 +repvgg_b0,1538.07,331.828,512,224,15.82 +efficientnet_lite1,1530.99,166.26,256,240,5.42 +dla34,1524.02,335.337,512,224,15.74 +edgenext_x_small,1512.48,337.399,512,256,2.34 +darknet21,1486.14,344.159,512,256,20.86 +selecsls60,1482.76,344.397,512,224,30.67 +selecsls60b,1478.62,345.378,512,224,32.77 +nf_seresnet26,1473.71,346.754,512,224,17.4 +vit_small_patch32_384,1455.89,350.818,512,384,22.92 +gmixer_12_224,1448.32,352.721,512,224,12.7 +efficientnet_b1_pruned,1446.82,352.35,512,240,6.33 +tf_efficientnet_lite1,1443.47,176.394,256,240,5.42 +nf_ecaresnet26,1440.41,354.896,512,224,16.0 +xcit_tiny_12_p16_224_dist,1426.36,357.157,512,224,6.72 +xcit_tiny_12_p16_224,1426.18,357.168,512,224,6.72 +sedarknet21,1401.98,364.696,512,256,20.95 +rexnetr_130,1388.84,183.199,256,224,7.61 +dla46x_c,1388.59,367.953,512,224,1.07 +gmlp_ti16_224,1381.11,276.449,384,224,5.87 +mixnet_s,1365.54,373.667,512,224,4.13 +rexnet_100,1364.31,280.319,384,224,4.8 +regnety_006,1361.43,374.963,512,224,6.06 +mobilenetv2_120d,1352.9,188.013,256,224,5.83 +legacy_seresnext26_32x4d,1349.26,378.798,512,224,16.79 +crossvit_tiny_240,1348.01,378.219,512,240,7.01 +vit_tiny_r_s16_p8_384,1345.31,284.562,384,384,6.36 +poolformer_s12,1342.54,380.659,512,224,11.92 +dla60x_c,1341.77,380.621,512,224,1.32 +efficientnet_b1,1325.85,191.544,256,224,7.79 +resnetv2_50,1288.61,396.553,512,224,25.55 +regnetx_006,1286.44,397.176,512,224,6.2 +crossvit_9_240,1258.73,303.637,384,240,8.55 +convnext_nano_ols,1252.33,408.151,512,224,15.6 +convnext_nano,1249.89,408.864,512,224,15.59 +convnext_nano_hnf,1249.05,409.138,512,224,15.59 +resnet26t,1237.34,413.275,512,256,16.01 +tf_mixnet_s,1236.15,412.905,512,224,4.13 +nf_regnet_b2,1229.56,414.759,512,240,14.31 +rexnetr_150,1224.57,207.878,256,224,9.78 +gluon_resnet50_v1b,1219.23,419.12,512,224,25.56 +tv_resnet50,1218.99,419.17,512,224,25.56 +crossvit_9_dagger_240,1218.38,313.701,384,240,8.78 +resnet50,1218.01,419.528,512,224,25.56 +swsl_resnet50,1217.39,419.737,512,224,25.56 +ssl_resnet50,1217.38,419.757,512,224,25.56 +cs3darknet_focus_l,1216.61,314.788,384,256,21.15 +repvgg_a2,1214.87,420.579,512,224,28.21 +cs3darknet_l,1203.14,318.267,384,256,21.16 +gernet_l,1201.09,425.379,512,256,31.08 +efficientnet_lite2,1191.67,213.855,256,260,6.09 +nf_regnet_b1,1181.15,431.966,512,256,10.22 +seresnext26d_32x4d,1178.86,325.051,384,224,16.81 +botnet26t_256,1178.34,325.281,384,256,12.49 +seresnext26tn_32x4d,1177.85,325.355,384,224,16.81 +seresnext26t_32x4d,1176.65,325.669,384,224,16.81 +mobilevitv2_075,1174.29,217.001,256,256,2.87 +ecaresnext50t_32x4d,1159.52,330.605,384,224,15.41 +ecaresnext26t_32x4d,1158.26,330.961,384,224,15.41 +gluon_resnet50_v1c,1147.86,333.697,384,224,25.58 +halonet26t,1136.15,337.402,384,256,12.48 +resnetv2_50d,1134.86,450.316,512,224,25.57 +resnetv2_50t,1132.89,451.133,512,224,25.57 +edgenext_small,1127.71,452.849,512,256,5.59 +tf_efficientnet_lite2,1121.02,227.403,256,260,6.09 +convit_tiny,1118.98,456.53,512,224,5.71 +skresnet34,1113.08,458.799,512,224,22.28 +tf_efficientnet_b1,1099.77,231.299,256,240,7.79 +tf_efficientnet_b1_ap,1099.37,231.402,256,240,7.79 +efficientnetv2_rw_t,1098.86,230.78,256,224,13.65 +tf_efficientnet_b1_ns,1098.29,231.567,256,240,7.79 +ecaresnetlight,1091.16,468.275,512,224,30.16 +gluon_resnet50_v1d,1084.38,353.226,384,224,25.58 +dpn68b,1083.77,353.123,384,224,12.61 +cs3sedarknet_l,1083.42,353.12,384,256,21.91 +resnet50d,1078.0,355.348,384,224,25.58 +resnet50t,1076.81,355.721,384,224,25.57 +resnet32ts,1075.86,237.337,256,256,17.96 +resnet33ts,1061.36,240.599,256,256,19.68 +vit_small_patch16_224,1057.92,362.157,384,224,22.05 +resnetaa50,1057.73,362.204,384,224,25.56 +vit_small_resnet26d_224,1057.57,362.04,384,224,63.61 +deit_small_patch16_224,1050.7,364.638,384,224,22.05 +cspresnet50,1042.19,367.617,384,256,21.62 +tf_efficientnetv2_b3,1041.71,243.94,256,240,14.36 +regnetx_008,1034.73,493.971,512,224,7.26 +ecaresnet26t,1033.34,371.048,384,256,16.01 +deit_small_distilled_patch16_224,1028.8,372.398,384,224,22.44 +vit_relpos_base_patch32_plus_rpn_256,1021.86,499.989,512,256,119.42 +dla60,1020.05,375.488,384,224,22.04 +res2net50_48w_2s,1018.83,376.079,384,224,25.29 +gc_efficientnetv2_rw_t,1014.65,249.524,256,224,13.68 +vit_relpos_small_patch16_rpn_224,1013.69,377.786,384,224,21.97 +edgenext_small_rw,1011.18,505.339,512,256,7.83 +pit_s_224,1010.83,378.943,384,224,23.46 +seresnet33ts,1007.26,253.362,256,256,19.78 +efficientnet_em,1007.19,253.179,256,240,6.9 +vovnet39a,1006.62,507.995,512,224,22.6 +legacy_seresnet50,1003.5,381.52,384,224,28.09 +gluon_resnext50_32x4d,1001.3,382.689,384,224,25.03 +tv_resnext50_32x4d,1001.18,382.711,384,224,25.03 +resnext50_32x4d,1001.03,382.776,384,224,25.03 +ssl_resnext50_32x4d,1000.68,382.908,384,224,25.03 +eca_resnet33ts,999.77,255.368,256,256,19.68 +swsl_resnext50_32x4d,997.37,384.186,384,224,25.03 +regnety_008,993.3,514.408,512,224,6.26 +dpn68,992.27,385.859,384,224,12.61 +deit3_small_patch16_224,987.86,387.777,384,224,22.06 +deit3_small_patch16_224_in21ft1k,987.15,388.058,384,224,22.06 +gcresnet33ts,985.12,258.855,256,256,19.88 +efficientnet_b2a,980.29,259.63,256,256,9.11 +tf_efficientnet_em,980.0,260.253,256,240,6.9 +efficientnet_b2,978.68,260.092,256,256,9.11 +seresnet50,971.79,394.011,384,224,28.09 +gluon_resnet50_v1s,970.71,394.714,384,224,25.68 +vit_srelpos_small_patch16_224,969.18,395.281,384,224,21.97 +vit_relpos_small_patch16_224,965.13,396.742,384,224,21.98 +ecaresnet50d_pruned,964.18,530.07,512,224,19.94 +cspresnet50d,956.82,266.672,256,256,21.64 +vgg11,954.03,536.508,512,224,132.86 +cspresnet50w,952.27,267.927,256,256,28.12 +ese_vovnet39b,951.93,537.173,512,224,24.57 +vit_base_patch32_plus_256,951.5,537.138,512,256,119.48 +resnetaa50d,950.79,403.026,384,224,25.58 +eca_vovnet39b,948.4,539.184,512,224,22.6 +lambda_resnet26rpt_256,942.15,203.17,192,256,10.99 +pit_s_distilled_224,934.29,273.079,256,224,24.04 +mobilevit_xs,924.5,275.792,256,256,2.32 +tv_densenet121,917.93,277.067,256,224,7.98 +densenet121,913.65,278.353,256,224,7.98 +resnetblur50,911.91,420.254,384,224,25.56 +hrnet_w18_small_v2,910.26,559.998,512,224,15.6 +coat_lite_tiny,909.29,421.406,384,224,5.72 +mobilevitv2_100,907.45,281.094,256,256,4.9 +nf_resnet50,900.11,425.722,384,256,25.56 +resnext50d_32x4d,894.57,285.293,256,224,25.05 +nf_seresnet50,892.73,428.967,384,224,28.09 +rexnetr_200,890.57,214.407,192,224,16.52 +efficientnet_cc_b0_4e,890.34,430.073,384,224,13.31 +efficientnet_cc_b0_8e,889.37,430.553,384,224,24.01 +dla60x,886.5,287.775,256,224,17.35 +twins_svt_small,885.48,432.048,384,224,24.06 +seresnet50t,879.71,435.29,384,224,28.1 +mixnet_m,878.04,581.529,512,224,5.01 +nf_ecaresnet50,875.38,437.674,384,224,25.56 +efficientnet_b2_pruned,873.9,291.355,256,260,8.31 +densenet121d,873.44,291.238,256,224,8.0 +cspresnext50,868.23,294.006,256,256,20.57 +rexnet_150,866.26,294.391,256,224,9.73 +ecaresnet50d,862.65,444.205,384,224,25.58 +fbnetv3_g,862.32,220.642,192,240,16.62 +regnetz_b16,862.05,295.457,256,224,9.72 +tf_efficientnet_cc_b0_4e,861.1,444.691,384,224,13.31 +tf_efficientnet_cc_b0_8e,857.16,446.822,384,224,24.01 +gcresnet50t,854.99,447.633,384,256,25.9 +res2net50_26w_4s,851.03,449.921,384,224,25.7 +coat_lite_mini,849.82,450.985,384,224,11.01 +tf_efficientnet_b2_ap,849.52,224.466,192,260,9.11 +tf_efficientnet_b2,848.58,224.736,192,260,9.11 +tf_efficientnet_b2_ns,847.86,224.983,192,260,9.11 +vit_base_resnet26d_224,844.62,453.315,384,224,101.4 +vgg11_bn,832.74,460.889,384,224,132.87 +vovnet57a,832.06,614.449,512,224,36.64 +selecsls84,830.17,615.492,512,224,50.95 +resnetblur50d,826.31,308.964,256,224,25.58 +convnext_tiny_hnfd,820.9,310.941,256,224,28.59 +convnext_tiny_hnf,819.46,311.471,256,224,28.59 +convnext_tiny,819.24,311.536,256,224,28.59 +convnext_tiny_in22ft1k,818.81,311.724,256,224,28.59 +rexnet_130,816.78,312.226,256,224,7.56 +seresnext50_32x4d,814.69,313.102,256,224,27.56 +legacy_seresnext50_32x4d,813.61,313.477,256,224,27.56 +gluon_seresnext50_32x4d,813.13,313.678,256,224,27.56 +skresnet50,808.8,473.357,384,224,25.8 +visformer_small,806.27,475.588,384,224,40.22 +res2net50_14w_8s,794.56,319.93,256,224,25.06 +densenetblur121d,789.33,322.521,256,224,8.0 +seresnetaa50d,785.32,324.779,256,224,28.11 +gluon_inception_v3,782.59,489.263,384,299,23.83 +inception_v3,782.35,489.427,384,299,23.83 +adv_inception_v3,778.18,491.976,384,299,23.83 +resmlp_24_distilled_224,777.24,327.895,256,224,30.02 +resmlp_24_224,776.95,327.972,256,224,30.02 +tf_inception_v3,775.41,493.776,384,299,23.83 +ese_vovnet57b,774.18,495.058,384,224,38.61 +tf_mixnet_m,773.08,495.127,384,224,5.01 +resnetv2_101,772.45,329.834,256,224,44.54 +dla60_res2net,767.35,332.099,256,224,20.85 +nf_regnet_b3,766.23,499.321,384,288,18.59 +sehalonet33ts,763.66,334.4,256,256,13.69 +ecaresnet101d_pruned,754.9,676.449,512,224,24.88 +darknet53,753.16,339.081,256,256,41.61 +densenet169,752.52,337.551,256,224,14.15 +resnet101,747.89,340.74,256,224,44.55 +gluon_resnet101_v1b,747.04,341.055,256,224,44.55 +tv_resnet101,746.84,341.219,256,224,44.55 +skresnet50d,739.17,344.891,256,224,25.82 +twins_pcpvt_small,738.11,345.194,256,224,24.11 +vit_small_r26_s32_224,733.9,347.477,256,224,36.43 +mobilevit_s,733.0,260.821,192,256,5.58 +darknetaa53,732.7,348.577,256,256,36.02 +xcit_tiny_24_p16_224_dist,727.98,348.335,256,224,12.12 +xcit_tiny_24_p16_224,727.1,348.63,256,224,12.12 +efficientnet_b0_gn,724.56,352.174,256,224,5.29 +efficientnet_b3_pruned,722.23,352.701,256,300,9.86 +gluon_resnet101_v1c,717.66,355.143,256,224,44.57 +resnext26ts,717.15,534.946,384,256,10.3 +resnetv2_101d,715.45,356.238,256,224,44.56 +gmixer_24_224,714.67,356.582,256,224,24.72 +resnetrs101,714.37,356.071,256,192,63.62 +nf_resnet101,712.1,537.603,384,224,44.55 +efficientnet_lite3,702.44,181.104,128,300,8.2 +mixnet_l,702.18,545.327,384,224,7.33 +eca_resnext26ts,694.05,368.289,256,256,10.3 +semobilevit_s,692.92,368.16,256,256,5.74 +seresnext26ts,691.18,369.699,256,256,10.39 +poolformer_s24,689.84,369.792,256,224,21.39 +gluon_resnet101_v1d,688.26,370.323,256,224,44.57 +dla102,688.03,370.524,256,224,33.27 +vit_relpos_medium_patch16_rpn_224,687.13,371.514,256,224,38.73 +sebotnet33ts_256,686.07,279.058,192,256,13.7 +gcresnext26ts,683.09,373.929,256,256,10.48 +regnetx_016,682.73,749.012,512,224,9.19 +haloregnetz_b,680.78,374.495,256,224,11.68 +cspdarknet53,679.01,375.961,256,256,27.64 +vgg13,677.45,566.653,384,224,133.05 +xcit_nano_12_p16_384_dist,671.72,379.231,256,384,3.05 +wide_resnet50_2,668.78,573.358,384,224,68.88 +tf_efficientnet_lite3,665.78,191.165,128,300,8.2 +vit_relpos_medium_patch16_cls_224,661.77,385.665,256,224,38.76 +vit_srelpos_medium_patch16_224,659.88,386.996,256,224,38.74 +rexnet_200,659.06,290.146,192,224,16.37 +vit_base_resnet50d_224,658.84,386.945,256,224,110.97 +ecaresnet50t,657.78,388.237,256,256,25.57 +gmlp_s16_224,657.63,290.408,192,224,19.42 +vit_relpos_medium_patch16_224,657.05,388.484,256,224,38.75 +tf_efficientnet_cc_b1_8e,654.82,389.25,256,240,39.72 +regnety_016,650.07,785.757,512,224,11.2 +swin_tiny_patch4_window7_224,648.69,393.641,256,224,28.29 +xcit_small_12_p16_224,640.82,397.688,256,224,26.25 +gluon_resnet101_v1s,640.79,397.908,256,224,44.67 +xcit_small_12_p16_224_dist,639.99,398.193,256,224,26.25 +crossvit_small_240,638.8,399.076,256,240,26.86 +efficientnet_cc_b1_8e,637.42,399.94,256,240,39.72 +resnetaa101d,634.86,401.619,256,224,44.57 +cs3sedarknet_xdw,630.82,302.41,192,256,21.6 +repvgg_b1,623.55,820.034,512,224,57.42 +mobilevitv2_125,620.51,308.406,192,256,7.48 +bat_resnext26ts,613.61,415.954,256,256,10.73 +gluon_resnext101_32x4d,609.67,418.333,256,224,44.18 +swsl_resnext101_32x4d,609.02,418.731,256,224,44.18 +resnext101_32x4d,609.01,418.74,256,224,44.18 +tf_mixnet_l,606.88,420.297,256,224,7.33 +ssl_resnext101_32x4d,606.28,420.718,256,224,44.18 +legacy_seresnet101,601.55,423.316,256,224,49.33 +cs3darknet_focus_x,600.02,425.715,256,256,35.02 +dla102x,598.42,319.231,192,224,26.31 +halonet50ts,597.8,320.205,192,256,22.73 +xcit_nano_12_p8_224,595.07,428.358,256,224,3.05 +xcit_nano_12_p8_224_dist,593.27,429.695,256,224,3.05 +cait_xxs24_224,593.22,428.92,256,224,11.96 +seresnet101,590.42,431.41,256,224,49.33 +swin_s3_tiny_224,588.57,433.98,256,224,28.33 +resnetv2_50x1_bit_distilled,585.83,326.889,192,224,25.55 +efficientnet_b0_g8_gn,582.67,438.264,256,224,6.56 +crossvit_15_240,580.46,328.975,192,240,27.53 +resnetblur101d,576.87,442.155,256,224,44.57 +res2net50_26w_6s,573.8,444.339,256,224,37.05 +vgg13_bn,573.47,446.125,256,224,133.05 +efficientnet_b3a,572.29,221.925,128,288,12.23 +efficientnet_b3,572.18,221.941,128,288,12.23 +cs3darknet_x,571.12,447.259,256,256,35.05 +densenet201,562.52,338.221,192,224,20.01 +crossvit_15_dagger_240,562.49,339.489,192,240,28.21 +efficientnetv2_s,559.15,226.702,128,288,21.46 +eca_botnext26ts_256,558.6,457.666,256,256,10.59 +mixer_b16_224,556.6,459.152,256,224,59.88 +mixer_b16_224_miil,556.5,459.202,256,224,59.88 +eca_halonext26ts,547.96,466.574,256,256,10.76 +ecaresnet101d,546.58,466.555,256,224,44.57 +vgg16,546.06,702.994,384,224,138.36 +mixer_l32_224,543.38,351.819,192,224,206.94 +vit_base_patch32_384,543.37,470.294,256,384,88.3 +nf_seresnet101,540.53,471.014,256,224,49.33 +resnetv2_152,536.63,474.697,256,224,60.19 +botnet50ts_256,534.71,238.412,128,256,22.74 +mobilevitv2_150,533.38,238.97,128,256,10.59 +vit_base_r26_s32_224,533.28,358.697,192,224,101.38 +mobilevitv2_150_in22ft1k,532.99,239.183,128,256,10.59 +cs3sedarknet_x,531.85,479.872,256,256,35.4 +nf_ecaresnet101,531.3,479.947,256,224,44.55 +cs3edgenet_x,529.37,482.632,256,256,47.82 +res2next50,528.59,483.023,256,224,24.67 +res2net101_26w_4s,527.01,483.179,256,224,45.21 +vit_large_patch32_224,524.74,486.172,256,224,306.54 +resnet101d,523.85,364.964,192,256,44.57 +efficientnetv2_rw_s,520.77,243.564,128,288,23.94 +halo2botnet50ts_256,517.51,369.975,192,256,22.64 +resmlp_36_distilled_224,513.23,371.84,192,224,44.69 +vit_tiny_patch16_384,510.99,249.657,128,384,5.79 +resmlp_36_224,509.53,374.55,192,224,44.69 +swinv2_cr_tiny_224,506.82,503.861,256,224,28.33 +mixnet_xl,505.67,504.387,256,224,11.9 +resnetv2_50d_gn,505.25,379.149,192,224,25.57 +swinv2_cr_tiny_ns_224,504.1,506.527,256,224,28.33 +gluon_resnet152_v1b,502.02,380.204,192,224,60.19 +regnetz_d8,501.8,253.463,128,256,23.37 +resnet152,501.44,380.547,192,224,60.19 +tv_resnet152,501.12,380.811,192,224,60.19 +xception,497.64,256.367,128,299,22.86 +regnety_032,496.85,771.405,384,224,19.44 +tf_efficientnet_b3_ap,496.0,256.348,128,300,12.23 +tf_efficientnet_b3,494.58,257.101,128,300,12.23 +tf_efficientnet_b3_ns,492.45,258.213,128,300,12.23 +convnext_small_in22ft1k,490.79,389.411,192,224,50.22 +res2net50_26w_8s,489.22,520.921,256,224,48.4 +tf_efficientnetv2_s_in21ft1k,488.77,259.622,128,300,21.46 +tf_efficientnetv2_s,488.25,259.918,128,300,21.46 +gluon_resnet152_v1c,488.2,390.894,192,224,60.21 +convnext_small,487.15,392.394,192,224,50.22 +twins_pcpvt_base,487.13,391.314,192,224,43.83 +resnetv2_152d,486.82,392.059,192,224,60.2 +legacy_seresnext101_32x4d,484.7,393.829,192,224,48.96 +resnet50_gn,482.45,397.141,192,224,25.56 +gluon_seresnext101_32x4d,480.63,397.197,192,224,48.96 +hrnet_w32,480.24,528.215,256,224,41.23 +sequencer2d_s,480.16,264.213,128,224,27.65 +seresnext101_32x4d,479.03,398.526,192,224,48.96 +nest_tiny,477.97,266.889,128,224,17.06 +dla60_res2next,477.74,534.408,256,224,17.03 +gluon_resnet152_v1d,476.32,400.788,192,224,60.21 +regnetz_c16,475.79,402.061,192,256,13.46 +hrnet_w18,473.42,535.867,256,224,21.3 +jx_nest_tiny,472.84,269.807,128,224,17.06 +regnetz_d32,471.85,269.596,128,256,27.58 +regnetz_040,471.81,269.412,128,256,27.12 +xception41p,471.79,270.424,128,299,26.91 +vgg16_bn,470.3,543.999,256,224,138.37 +regnetz_040h,469.27,270.846,128,256,28.94 +poolformer_s36,467.39,408.832,192,224,30.86 +resnet51q,463.81,551.102,256,256,35.7 +efficientnet_el_pruned,461.98,275.957,128,300,10.59 +efficientnet_el,461.97,275.94,128,300,10.59 +coat_lite_small,461.36,414.606,192,224,19.84 +nf_regnet_b4,457.97,417.049,192,320,30.21 +vgg19,457.37,839.347,384,224,143.67 +cs3se_edgenet_x,457.05,418.615,192,256,50.72 +dla169,455.51,419.044,192,224,53.39 +convit_small,454.72,421.197,192,224,27.78 +gluon_resnet152_v1s,452.53,421.917,192,224,60.32 +tf_efficientnet_el,449.8,283.446,128,300,10.59 +gcresnext50ts,445.12,429.834,192,256,15.67 +regnetx_040,442.35,866.937,384,224,22.12 +vit_small_resnet50d_s16_224,437.26,437.826,192,224,57.53 +volo_d1_224,437.04,437.842,192,224,26.63 +mobilevitv2_175_in22ft1k,434.9,293.339,128,256,14.25 +mobilevitv2_175,434.88,293.341,128,256,14.25 +resnet61q,433.95,441.405,192,256,36.85 +ese_vovnet99b,433.24,589.371,256,224,63.2 +ese_vovnet39b_evos,430.54,296.328,128,224,24.58 +twins_svt_base,425.02,449.64,192,224,56.07 +resnest14d,411.87,1242.634,512,224,10.61 +dla102x2,405.87,313.766,128,224,41.28 +mobilevitv2_200_in22ft1k,405.83,314.414,128,256,18.45 +mobilevitv2_200,405.76,314.447,128,256,18.45 +inception_v4,405.43,471.399,192,299,42.68 +crossvit_18_240,404.58,314.332,128,240,43.27 +swin_small_patch4_window7_224,400.37,477.632,192,224,49.61 +densenet161,399.17,318.189,128,224,28.68 +vgg19_bn,398.5,642.012,256,224,143.68 +legacy_seresnet152,398.4,478.588,192,224,66.82 +vit_base_patch16_224_miil,397.86,481.79,192,224,86.54 +sequencer2d_m,396.83,480.626,192,224,38.31 +crossvit_18_dagger_240,396.31,320.926,128,240,44.27 +resnetv2_50d_frn,394.18,323.553,128,224,25.59 +vit_base_patch16_224,392.99,487.729,192,224,86.57 +vit_base_patch16_224_sam,392.92,487.774,192,224,86.57 +vit_base_patch16_rpn_224,391.32,489.846,192,224,86.54 +xception41,391.05,326.045,128,299,26.97 +deit_base_patch16_224,390.04,491.437,192,224,86.57 +cait_xxs36_224,387.24,492.066,192,224,17.3 +efficientnet_b0_g16_evos,386.23,993.13,384,224,8.11 +deit_base_distilled_patch16_224,384.06,499.086,192,224,87.34 +xcit_tiny_12_p16_384_dist,383.09,499.371,192,384,6.72 +vit_relpos_base_patch16_rpn_224,382.95,500.328,192,224,86.41 +seresnet152,379.38,334.127,128,224,66.82 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+regnetz_b16_evos,347.19,366.83,128,224,9.74 +tnt_s_patch16_224,342.71,558.25,192,224,23.76 +xception65p,341.43,373.588,128,299,39.82 +convnext_base_in22ft1k,339.67,374.996,128,224,88.59 +convnext_base,338.68,376.119,128,224,88.59 +efficientnet_lite4,338.39,187.783,64,380,13.01 +twins_pcpvt_large,333.52,379.633,128,224,60.99 +pit_b_224,331.08,385.636,128,224,73.76 +pit_b_distilled_224,328.87,388.208,128,224,74.79 +xcit_small_24_p16_224_dist,326.41,388.817,128,224,47.67 +xcit_small_24_p16_224,326.38,388.806,128,224,47.67 +tf_efficientnet_lite4,324.6,195.748,64,380,13.01 +eca_nfnet_l0,319.84,1599.745,512,224,24.14 +nfnet_l0,319.69,1600.317,512,224,35.07 +gluon_seresnext101_64x4d,319.51,398.398,128,224,88.23 +repvgg_b3,316.57,1211.922,384,224,123.09 +skresnext50_32x4d,315.84,809.121,256,224,27.48 +poolformer_m36,315.69,403.496,128,224,56.17 +ssl_resnext101_32x8d,313.35,406.924,128,224,88.79 +resnext101_32x8d,312.8,407.622,128,224,88.79 +swsl_resnext101_32x8d,312.76,407.724,128,224,88.79 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+tnt_b_patch16_224,223.52,570.669,128,224,65.41 +hrnet_w64,223.29,568.417,128,224,128.06 +sequencer2d_l,220.03,286.022,64,224,54.3 +dpn131,216.53,588.962,128,224,79.25 +vit_base_r50_s16_224,215.49,443.851,96,224,98.66 +swinv2_cr_base_ns_224,214.73,444.647,96,224,87.88 +xception71,214.09,296.77,64,299,42.34 +swinv2_cr_base_224,213.21,447.81,96,224,87.88 +swinv2_small_window8_256,213.06,448.048,96,256,49.73 +nest_base,210.25,302.717,64,224,67.72 +jx_nest_base,209.06,304.441,64,224,67.72 +seresnet200d,203.53,467.209,96,256,71.86 +resnetrs200,201.84,471.293,96,256,93.21 +resnest50d,201.6,1268.493,256,224,27.48 +ecaresnet200d,201.55,472.938,96,256,64.69 +xcit_nano_12_p8_384_dist,201.45,315.854,64,384,3.05 +efficientnet_b3_gn,197.65,322.123,64,288,11.73 +xcit_tiny_24_p8_224_dist,195.37,488.075,96,224,12.11 +xcit_tiny_24_p8_224,195.11,488.622,96,224,12.11 +dpn107,194.08,492.913,96,224,86.92 +regnetz_c16_evos,193.89,328.188,64,256,13.49 +regnety_040,190.14,2017.916,384,224,20.65 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+swin_large_patch4_window7_224,153.79,414.289,64,224,196.53 +swinv2_base_window8_256,151.21,420.663,64,256,87.92 +convmixer_1024_20_ks9_p14,149.3,1713.726,256,224,24.38 +resnetv2_50x1_bitm,147.75,215.764,32,448,25.55 +seresnet269d,145.59,433.61,64,256,113.67 +resnetrs270,144.14,437.83,64,256,129.86 +swinv2_small_window16_256,143.52,443.487,64,256,49.73 +regnety_040s_gn,142.58,896.132,128,224,20.65 +repvgg_b2g4,133.72,3827.892,512,224,61.76 +eca_nfnet_l1,133.59,1435.413,192,256,41.41 +xcit_large_24_p16_224,132.6,479.222,64,224,189.1 +swinv2_cr_tiny_384,131.94,483.86,64,384,28.33 +xcit_large_24_p16_224_dist,131.66,482.65,64,224,189.1 +xcit_tiny_12_p8_384_dist,131.64,362.75,48,384,6.71 +regnetx_064,129.82,1970.916,256,224,26.21 +swinv2_cr_large_224,124.15,513.018,64,224,196.68 +xcit_small_24_p16_384_dist,120.64,394.328,48,384,47.67 +regnety_064,119.44,2141.523,256,224,30.58 +regnety_080,117.88,2170.37,256,224,39.18 +crossvit_15_dagger_408,117.86,269.618,32,408,28.5 +vit_large_patch16_224,117.2,544.512,64,224,304.33 +regnetv_064,117.03,1638.944,192,224,30.58 +ese_vovnet99b_iabn,117.02,3278.167,384,224,63.2 +convnext_xlarge_in22ft1k,116.37,548.167,64,224,350.2 +vit_base_patch16_18x2_224,116.0,548.972,64,224,256.73 +convnext_base_384_in22ft1k,115.58,413.454,48,384,88.59 +efficientnet_b5,113.63,279.129,32,456,30.39 +deit3_large_patch16_224_in21ft1k,112.51,567.041,64,224,304.37 +deit3_large_patch16_224,112.48,567.139,64,224,304.37 +tf_efficientnet_b5,111.42,284.665,32,456,30.39 +tf_efficientnet_b5_ap,111.14,285.451,32,456,30.39 +tf_efficientnet_b5_ns,111.14,285.33,32,456,30.39 +legacy_senet154,110.98,861.567,96,224,115.09 +senet154,110.82,862.828,96,224,115.09 +gluon_senet154,110.77,863.12,96,224,115.09 +beit_large_patch16_224,109.02,584.818,64,224,304.43 +repvgg_b3g4,108.77,3529.239,384,224,83.83 +regnetx_160,107.6,1783.261,192,224,54.28 +nfnet_f1,107.01,1791.907,192,224,132.63 +volo_d1_384,105.69,301.347,32,384,26.78 +swinv2_base_window16_256,103.88,459.56,48,256,87.92 +swinv2_base_window12to16_192to256_22kft1k,103.79,460.002,48,256,87.92 +tresnet_l,102.82,4975.916,512,224,55.99 +dm_nfnet_f1,101.59,1257.525,128,224,132.63 +volo_d4_224,101.08,472.359,48,224,192.96 +cait_xxs24_384,99.39,480.268,48,384,12.03 +ecaresnet269d,99.06,479.988,48,320,102.09 +efficientnetv2_l,98.76,319.521,32,384,118.52 +tf_efficientnetv2_l_in21ft1k,98.35,320.759,32,384,118.52 +tf_efficientnetv2_l,97.56,323.47,32,384,118.52 +deit_base_patch16_384,97.3,328.042,32,384,86.86 +vit_base_patch16_384,97.1,328.712,32,384,86.86 +resnest101e,96.09,1329.413,128,256,48.28 +deit_base_distilled_patch16_384,94.63,337.315,32,384,87.63 +regnetx_120,94.03,2721.558,256,224,46.11 +deit3_base_patch16_384,93.5,341.294,32,384,86.88 +deit3_base_patch16_384_in21ft1k,93.49,341.309,32,384,86.88 +xcit_small_24_p8_224_dist,92.61,514.968,48,224,47.63 +xcit_small_24_p8_224,92.51,515.466,48,224,47.63 +regnety_120,92.07,2083.952,192,224,51.82 +tresnet_xl,91.15,4209.119,384,224,78.44 +crossvit_18_dagger_408,89.17,356.787,32,408,44.61 +resnetv2_152x2_bit_teacher,89.16,356.538,32,224,236.34 +vit_large_patch14_224,85.06,562.673,48,224,304.2 +resnetv2_101x1_bitm,84.72,187.286,16,448,44.54 +resnetrs350,84.14,372.211,32,288,163.96 +beit_base_patch16_384,83.87,380.424,32,384,86.74 +regnety_160,83.24,2305.144,192,224,83.59 +pnasnet5large,83.16,380.801,32,331,86.06 +xcit_medium_24_p16_384_dist,82.74,383.266,32,384,84.4 +vit_large_r50_s32_384,77.34,411.186,32,384,329.09 +nasnetalarge,77.32,408.633,32,331,88.75 +swinv2_cr_small_384,76.42,416.277,32,384,49.7 +swin_base_patch4_window12_384,74.73,426.327,32,384,87.9 +resmlp_big_24_distilled_224,70.88,449.95,32,224,129.14 +resmlp_big_24_224_in22ft1k,70.88,449.933,32,224,129.14 +resmlp_big_24_224,70.41,452.99,32,224,129.14 +regnety_320,66.33,1928.357,128,224,145.05 +xcit_tiny_24_p8_384_dist,66.29,479.361,32,384,12.11 +cait_xs24_384,66.24,480.525,32,384,26.67 +ig_resnext101_32x16d,65.9,1455.165,96,224,194.03 +ssl_resnext101_32x16d,65.74,1458.688,96,224,194.03 +swsl_resnext101_32x16d,65.74,1458.738,96,224,194.03 +volo_d5_224,64.41,493.535,32,224,295.46 +cait_xxs36_384,64.34,493.602,32,384,17.37 +efficientnet_b6,64.08,246.77,16,528,43.04 +xcit_medium_24_p8_224,63.96,496.86,32,224,84.32 +xcit_medium_24_p8_224_dist,63.93,497.194,32,224,84.32 +convnext_large_384_in22ft1k,63.85,499.388,32,384,197.77 +vit_base_patch8_224,63.45,377.425,24,224,86.58 +tf_efficientnet_b6_ns,63.1,250.577,16,528,43.04 +tf_efficientnet_b6,62.84,251.669,16,528,43.04 +tf_efficientnet_b6_ap,62.76,252.073,16,528,43.04 +efficientnetv2_xl,62.18,251.438,16,384,208.12 +tf_efficientnetv2_xl_in21ft1k,62.14,251.721,16,384,208.12 +xcit_small_12_p8_384_dist,61.84,386.224,24,384,26.21 +vit_base_r50_s16_384,61.01,391.67,24,384,98.95 +vit_base_resnet50_384,60.98,391.903,24,384,98.95 +swinv2_large_window12to16_192to256_22kft1k,60.98,391.098,24,256,196.74 +eca_nfnet_l2,58.72,1632.112,96,320,56.72 +volo_d2_384,58.5,271.766,16,384,58.87 +resnetrs420,56.49,415.629,24,320,191.89 +swinv2_cr_base_384,55.08,433.269,24,384,87.88 +nfnet_f2,54.73,1750.573,96,256,193.78 +tresnet_m_448,53.52,3584.333,192,448,31.39 +dm_nfnet_f2,51.26,1245.084,64,256,193.78 +cait_s24_384,50.14,476.064,24,384,47.06 +swinv2_cr_huge_224,49.63,481.092,24,224,657.83 +regnetx_320,48.06,2662.024,128,224,107.81 +xcit_large_24_p16_384_dist,48.02,496.416,24,384,189.1 +swin_large_patch4_window12_384,41.75,381.31,16,384,196.74 +convnext_xlarge_384_in22ft1k,40.45,591.485,24,384,350.2 +deit3_huge_patch14_224_in21ft1k,38.41,414.036,16,224,632.13 +deit3_huge_patch14_224,38.4,414.103,16,224,632.13 +efficientnet_b7,37.97,207.232,8,600,66.35 +tf_efficientnet_b7_ap,37.27,210.986,8,600,66.35 +tf_efficientnet_b7_ns,37.25,211.249,8,600,66.35 +tf_efficientnet_b7,37.22,211.329,8,600,66.35 +eca_nfnet_l3,35.61,1344.526,48,352,72.04 +xcit_large_24_p8_224_dist,35.32,449.68,16,224,188.93 +xcit_large_24_p8_224,35.06,452.952,16,224,188.93 +resnetv2_50x3_bitm,34.68,460.605,16,448,217.32 +swinv2_cr_large_384,32.56,488.949,16,384,196.68 +cait_s36_384,32.3,491.641,16,384,68.37 +densenet264d_iabn,32.11,3982.48,128,224,72.74 +resnetv2_152x2_bit_teacher_384,31.17,382.508,12,384,236.34 +xcit_small_24_p8_384_dist,31.12,510.761,16,384,47.63 +resnest200e,30.3,1579.149,48,320,70.2 +vit_large_patch16_384,29.14,410.147,12,384,304.72 +deit3_large_patch16_384,28.26,422.768,12,384,304.76 +deit3_large_patch16_384_in21ft1k,28.25,422.94,12,384,304.76 +swinv2_base_window12to24_192to384_22kft1k,28.19,423.281,12,384,87.92 +nfnet_f3,26.1,1834.868,48,320,254.92 +beit_large_patch16_384,25.3,472.219,12,384,305.0 +tresnet_l_448,25.28,5060.321,128,448,55.99 +volo_d3_448,24.7,321.403,8,448,86.63 +dm_nfnet_f3,24.56,1297.967,32,320,254.92 +tresnet_xl_448,23.27,4122.323,96,448,78.44 +efficientnet_b8,22.93,257.589,6,672,87.41 +tf_efficientnet_b8,22.71,260.18,6,672,87.41 +tf_efficientnet_b8_ap,22.69,260.555,6,672,87.41 +resnetv2_152x2_bitm,22.58,351.774,8,448,236.34 +vit_giant_patch14_224,22.32,355.766,8,224,1012.61 +ig_resnext101_32x32d,21.03,1519.993,32,224,468.53 +xcit_medium_24_p8_384_dist,21.03,376.997,8,384,84.32 +convmixer_1536_20,20.83,2303.059,48,224,51.63 +resnetv2_101x3_bitm,18.05,441.706,8,448,387.93 +volo_d4_448,17.57,338.789,6,448,193.41 +swinv2_large_window12to24_192to384_22kft1k,16.62,358.548,6,384,196.74 +resnest269e,16.0,1493.085,24,416,110.93 +nfnet_f4,14.17,1687.74,24,384,316.07 +swinv2_cr_huge_384,13.13,454.627,6,384,657.94 +dm_nfnet_f4,12.96,1229.019,16,384,316.07 +xcit_large_24_p8_384_dist,12.19,488.758,6,384,188.93 +cait_m36_384,11.91,500.148,6,384,271.22 +volo_d5_448,11.43,346.654,4,448,295.91 +ig_resnext101_32x48d,11.2,1427.437,16,224,828.41 +tf_efficientnet_l2_ns_475,10.96,267.912,3,475,480.31 +dm_nfnet_f5,9.76,1222.345,12,416,377.21 +beit_large_patch16_512,9.42,422.548,4,512,305.67 +volo_d5_512,8.0,371.847,3,512,296.09 +nfnet_f5,8.0,1992.337,16,416,377.21 +dm_nfnet_f6,7.45,1065.231,8,448,438.36 +nfnet_f6,5.82,2052.248,12,448,438.36 +nfnet_f7,5.73,1387.07,8,480,499.5 +resnetv2_152x4_bitm,4.89,406.668,2,480,936.53 +cait_m48_448,4.76,414.936,2,448,356.46 +efficientnet_l2,3.95,247.515,1,800,480.31 +tf_efficientnet_l2_ns,3.93,248.975,1,800,480.31 diff --git a/results/generate_csv_results.py b/results/generate_csv_results.py index 04cf710a..70fd4588 100644 --- a/results/generate_csv_results.py +++ b/results/generate_csv_results.py @@ -62,13 +62,13 @@ def diff(base_df, test_csv): test_df['rank_diff'] = rank_diff test_df['param_count'] = test_df['param_count'].map('{:,.2f}'.format) - test_df.sort_values('top1', ascending=False, inplace=True) + test_df.sort_values(['top1', 'top5', 'model'], ascending=[False, False, True], inplace=True) test_df.to_csv(test_csv, index=False, float_format='%.3f') for base_results, test_results in results.items(): base_df = pd.read_csv(base_results) - base_df.sort_values('top1', ascending=False, inplace=True) + base_df.sort_values(['top1', 'top5', 'model'], ascending=[False, False, True], inplace=True) for test_csv in test_results: diff(base_df, test_csv) base_df['param_count'] = base_df['param_count'].map('{:,.2f}'.format) diff --git a/results/results-imagenet-a-clean.csv b/results/results-imagenet-a-clean.csv index c24d3768..68822bd8 100644 --- a/results/results-imagenet-a-clean.csv +++ b/results/results-imagenet-a-clean.csv @@ -1,42 +1,53 @@ -model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation +model,top1,top1_err,top5,top5_err,param_count,img_size,crop_pct,interpolation beit_large_patch16_512,98.560,1.440,99.840,0.160,305.67,512,1.000,bicubic tf_efficientnet_l2_ns,98.550,1.450,99.820,0.180,480.31,800,0.960,bicubic beit_large_patch16_384,98.520,1.480,99.820,0.180,305.00,384,1.000,bicubic tf_efficientnet_l2_ns_475,98.500,1.500,99.830,0.170,480.31,475,0.936,bicubic +deit3_large_patch16_384_in21ft1k,98.460,1.540,99.760,0.240,304.76,384,1.000,bicubic convnext_xlarge_384_in22ft1k,98.350,1.650,99.800,0.200,350.20,384,1.000,bicubic -convnext_large_384_in22ft1k,98.220,1.780,99.730,0.270,197.77,384,1.000,bicubic vit_large_patch16_384,98.220,1.780,99.800,0.200,304.72,384,1.000,bicubic +convnext_large_384_in22ft1k,98.220,1.780,99.730,0.270,197.77,384,1.000,bicubic beit_large_patch16_224,98.180,1.820,99.760,0.240,304.43,224,0.900,bicubic +deit3_large_patch16_224_in21ft1k,98.170,1.830,99.760,0.240,304.37,224,1.000,bicubic +deit3_huge_patch14_224_in21ft1k,98.170,1.830,99.730,0.270,632.13,224,1.000,bicubic +swinv2_large_window12to24_192to384_22kft1k,98.150,1.850,99.690,0.310,196.74,384,1.000,bicubic +swinv2_base_window12to24_192to384_22kft1k,98.140,1.860,99.780,0.220,87.92,384,1.000,bicubic swin_large_patch4_window12_384,98.040,1.960,99.690,0.310,196.74,384,1.000,bicubic convnext_base_384_in22ft1k,97.950,2.050,99.650,0.350,88.59,384,1.000,bicubic +tf_efficientnet_b7_ns,97.920,2.080,99.720,0.280,66.35,600,0.949,bicubic convnext_xlarge_in22ft1k,97.920,2.080,99.680,0.320,350.20,224,0.875,bicubic -tf_efficientnet_b7_ns,97.910,2.090,99.720,0.280,66.35,600,0.949,bicubic swin_base_patch4_window12_384,97.890,2.110,99.710,0.290,87.90,384,1.000,bicubic vit_large_r50_s32_384,97.860,2.140,99.670,0.330,329.09,384,1.000,bicubic +swinv2_large_window12to16_192to256_22kft1k,97.860,2.140,99.650,0.350,196.74,256,0.900,bicubic vit_base_patch16_384,97.840,2.160,99.670,0.330,86.86,384,1.000,bicubic convnext_large_in22ft1k,97.830,2.170,99.690,0.310,197.77,224,0.875,bicubic -beit_base_patch16_384,97.810,2.190,99.700,0.300,86.74,384,1.000,bicubic +deit3_base_patch16_384_in21ft1k,97.830,2.170,99.680,0.320,86.88,384,1.000,bicubic +beit_base_patch16_384,97.820,2.180,99.700,0.300,86.74,384,1.000,bicubic volo_d5_512,97.770,2.230,99.670,0.330,296.09,512,1.150,bicubic volo_d5_448,97.760,2.240,99.620,0.380,295.91,448,1.150,bicubic tf_efficientnetv2_l_in21ft1k,97.700,2.300,99.670,0.330,118.52,480,1.000,bicubic volo_d4_448,97.670,2.330,99.610,0.390,193.41,448,1.150,bicubic +tf_efficientnetv2_xl_in21ft1k,97.660,2.340,99.490,0.510,208.12,512,1.000,bicubic +swinv2_base_window12to16_192to256_22kft1k,97.650,2.350,99.720,0.280,87.92,256,0.900,bicubic swin_large_patch4_window7_224,97.650,2.350,99.580,0.420,196.53,224,0.900,bicubic -tf_efficientnetv2_xl_in21ft1k,97.650,2.350,99.490,0.510,208.12,512,1.000,bicubic vit_large_patch16_224,97.640,2.360,99.590,0.410,304.33,224,0.900,bicubic tf_efficientnet_b6_ns,97.630,2.370,99.580,0.420,43.04,528,0.942,bicubic -ig_resnext101_32x48d,97.620,2.380,99.710,0.290,828.41,224,0.875,bilinear +ig_resnext101_32x48d,97.620,2.380,99.700,0.300,828.41,224,0.875,bilinear dm_nfnet_f6,97.600,2.400,99.550,0.450,438.36,576,0.956,bicubic -dm_nfnet_f4,97.580,2.420,99.510,0.490,316.07,512,0.951,bicubic vit_base_patch8_224,97.580,2.420,99.670,0.330,86.58,224,0.900,bicubic +dm_nfnet_f4,97.580,2.420,99.510,0.490,316.07,512,0.951,bicubic volo_d3_448,97.550,2.450,99.550,0.450,86.63,448,1.000,bicubic dm_nfnet_f5,97.540,2.460,99.570,0.430,377.21,544,0.954,bicubic xcit_large_24_p8_384_dist,97.520,2.480,99.540,0.460,188.93,384,1.000,bicubic xcit_large_24_p16_384_dist,97.520,2.480,99.480,0.520,189.10,384,1.000,bicubic tf_efficientnet_b5_ns,97.500,2.500,99.630,0.370,30.39,456,0.934,bicubic resnetv2_152x4_bitm,97.490,2.510,99.610,0.390,936.53,480,1.000,bilinear -tf_efficientnetv2_m_in21ft1k,97.480,2.520,99.530,0.470,54.14,480,1.000,bicubic +deit3_base_patch16_224_in21ft1k,97.490,2.510,99.600,0.400,86.59,224,1.000,bicubic cait_m48_448,97.480,2.520,99.550,0.450,356.46,448,1.000,bicubic +tf_efficientnetv2_m_in21ft1k,97.480,2.520,99.530,0.470,54.14,480,1.000,bicubic convnext_base_in22ft1k,97.470,2.530,99.600,0.400,88.59,224,0.875,bicubic +convnext_small_384_in22ft1k,97.460,2.540,99.580,0.420,50.22,384,1.000,bicubic +deit3_large_patch16_384,97.420,2.580,99.620,0.380,304.76,384,1.000,bicubic cait_m36_384,97.400,2.600,99.510,0.490,271.22,384,1.000,bicubic volo_d5_224,97.390,2.610,99.570,0.430,295.46,224,0.960,bicubic ig_resnext101_32x32d,97.370,2.630,99.680,0.320,468.53,224,0.875,bilinear @@ -50,35 +61,42 @@ xcit_medium_24_p16_384_dist,97.280,2.720,99.460,0.540,84.40,384,1.000,bicubic swin_base_patch4_window7_224,97.250,2.750,99.530,0.470,87.77,224,0.900,bicubic xcit_small_24_p8_384_dist,97.240,2.760,99.610,0.390,47.63,384,1.000,bicubic xcit_small_12_p8_384_dist,97.230,2.770,99.480,0.520,26.21,384,1.000,bicubic -tf_efficientnet_b7_ap,97.200,2.800,99.540,0.460,66.35,600,0.949,bicubic -tf_efficientnet_b8,97.200,2.800,99.500,0.500,87.41,672,0.954,bicubic swsl_resnext101_32x8d,97.200,2.800,99.570,0.430,88.79,224,0.875,bilinear +tf_efficientnet_b7_ap,97.200,2.800,99.540,0.460,66.35,600,0.949,bicubic regnetz_e8,97.200,2.800,99.500,0.500,57.70,320,1.000,bicubic +tf_efficientnet_b8,97.200,2.800,99.500,0.500,87.41,672,0.954,bicubic vit_base_r50_s16_384,97.180,2.820,99.560,0.440,98.95,384,1.000,bicubic tf_efficientnetv2_m,97.140,2.860,99.410,0.590,54.14,480,1.000,bicubic -xcit_small_24_p16_384_dist,97.120,2.880,99.460,0.540,47.67,384,1.000,bicubic +deit3_small_patch16_384_in21ft1k,97.130,2.870,99.500,0.500,22.21,384,1.000,bicubic +xcit_small_24_p16_384_dist,97.120,2.880,99.450,0.550,47.67,384,1.000,bicubic tf_efficientnet_b8_ap,97.110,2.890,99.660,0.340,87.41,672,0.954,bicubic beit_base_patch16_224,97.090,2.910,99.610,0.390,86.53,224,0.900,bicubic eca_nfnet_l2,97.090,2.910,99.510,0.490,56.72,384,1.000,bicubic volo_d3_224,97.090,2.910,99.470,0.530,86.33,224,0.960,bicubic tf_efficientnet_b6_ap,97.080,2.920,99.620,0.380,43.04,528,0.942,bicubic ecaresnet269d,97.080,2.920,99.470,0.530,102.09,352,1.000,bicubic -cait_s24_384,97.080,2.920,99.430,0.570,47.06,384,1.000,bicubic +cait_s24_384,97.070,2.930,99.430,0.570,47.06,384,1.000,bicubic xcit_large_24_p8_224_dist,97.070,2.930,99.420,0.580,188.93,224,1.000,bicubic -dm_nfnet_f2,97.030,2.970,99.440,0.560,193.78,352,0.920,bicubic +dm_nfnet_f2,97.020,2.980,99.440,0.560,193.78,352,0.920,bicubic +deit3_base_patch16_384,97.020,2.980,99.390,0.610,86.88,384,1.000,bicubic resnetv2_152x2_bitm,97.010,2.990,99.590,0.410,236.34,448,1.000,bilinear tf_efficientnet_b7,97.010,2.990,99.520,0.480,66.35,600,0.949,bicubic volo_d2_224,97.000,3.000,99.390,0.610,58.68,224,0.960,bicubic resnetv2_101x3_bitm,96.990,3.010,99.490,0.510,387.93,448,1.000,bilinear -efficientnetv2_rw_m,96.980,3.020,99.530,0.470,53.24,416,1.000,bicubic +convnext_small_in22ft1k,96.990,3.010,99.410,0.590,50.22,224,0.875,bicubic +efficientnetv2_rw_m,96.980,3.020,99.540,0.460,53.24,416,1.000,bicubic deit_base_distilled_patch16_384,96.960,3.040,99.480,0.520,87.63,384,1.000,bicubic tf_efficientnet_b4_ns,96.950,3.050,99.580,0.420,19.34,380,0.922,bicubic +seresnextaa101d_32x8d,96.950,3.050,99.390,0.610,93.59,288,1.000,bicubic +deit3_large_patch16_224,96.940,3.060,99.340,0.660,304.37,224,0.900,bicubic xcit_small_12_p16_384_dist,96.930,3.070,99.400,0.600,26.25,384,1.000,bicubic -resnetrs420,96.920,3.080,99.460,0.540,191.89,416,1.000,bicubic -volo_d1_384,96.920,3.080,99.520,0.480,26.78,384,1.000,bicubic xcit_medium_24_p8_224_dist,96.920,3.080,99.390,0.610,84.32,224,1.000,bicubic +volo_d1_384,96.910,3.090,99.520,0.480,26.78,384,1.000,bicubic +resnetrs420,96.910,3.090,99.460,0.540,191.89,416,1.000,bicubic dm_nfnet_f1,96.910,3.090,99.410,0.590,132.63,320,0.910,bicubic +deit3_huge_patch14_224,96.890,3.110,99.480,0.520,632.13,224,0.900,bicubic vit_base_patch16_224,96.880,3.120,99.530,0.470,86.57,224,0.900,bicubic +convnext_tiny_384_in22ft1k,96.880,3.120,99.470,0.530,28.59,384,1.000,bicubic xcit_small_24_p8_224_dist,96.870,3.130,99.480,0.520,47.63,224,1.000,bicubic resnetv2_152x2_bit_teacher_384,96.830,3.170,99.450,0.550,236.34,384,1.000,bicubic ig_resnext101_32x16d,96.810,3.190,99.600,0.400,194.03,224,0.875,bilinear @@ -86,46 +104,52 @@ xcit_large_24_p16_224_dist,96.800,3.200,99.350,0.650,189.10,224,1.000,bicubic vit_large_r50_s32_224,96.790,3.210,99.350,0.650,328.99,224,0.900,bicubic seresnet152d,96.770,3.230,99.450,0.550,66.84,320,1.000,bicubic seresnext101_32x8d,96.770,3.230,99.350,0.650,93.57,288,1.000,bicubic -convnext_large,96.760,3.240,99.300,0.700,197.77,224,0.875,bicubic resnetrs350,96.760,3.240,99.370,0.630,163.96,384,1.000,bicubic -tf_efficientnetv2_s_in21ft1k,96.730,3.270,99.420,0.580,21.46,384,1.000,bicubic +swinv2_base_window16_256,96.760,3.240,99.350,0.650,87.92,256,0.900,bicubic +convnext_large,96.760,3.240,99.300,0.700,197.77,224,0.875,bicubic +tf_efficientnetv2_s_in21ft1k,96.720,3.280,99.420,0.580,21.46,384,1.000,bicubic resnet200d,96.720,3.280,99.330,0.670,64.69,320,1.000,bicubic resnetv2_50x3_bitm,96.710,3.290,99.550,0.450,217.32,448,1.000,bilinear regnetz_040h,96.710,3.290,99.500,0.500,28.94,320,1.000,bicubic regnetz_040,96.710,3.290,99.470,0.530,27.12,320,1.000,bicubic -eca_nfnet_l1,96.700,3.300,99.290,0.710,41.41,320,1.000,bicubic -resnetrs200,96.700,3.300,99.370,0.630,93.21,320,1.000,bicubic +seresnext101d_32x8d,96.710,3.290,99.360,0.640,93.59,288,1.000,bicubic vit_small_patch16_384,96.700,3.300,99.480,0.520,22.20,384,1.000,bicubic -xcit_small_12_p8_224_dist,96.700,3.300,99.390,0.610,26.21,224,1.000,bicubic +resnetrs200,96.700,3.300,99.370,0.630,93.21,320,1.000,bicubic +eca_nfnet_l1,96.700,3.300,99.290,0.710,41.41,320,1.000,bicubic +xcit_small_12_p8_224_dist,96.690,3.310,99.390,0.610,26.21,224,1.000,bicubic resnetrs270,96.690,3.310,99.350,0.650,129.86,352,1.000,bicubic vit_small_r26_s32_384,96.680,3.320,99.580,0.420,36.47,384,1.000,bicubic +tf_efficientnet_b5_ap,96.680,3.320,99.460,0.540,30.39,456,0.934,bicubic tf_efficientnet_b6,96.670,3.330,99.370,0.630,43.04,528,0.942,bicubic -tf_efficientnet_b5_ap,96.670,3.330,99.460,0.540,30.39,456,0.934,bicubic pit_b_distilled_224,96.670,3.330,99.350,0.650,74.79,224,0.900,bicubic -regnetz_d8,96.620,3.380,99.450,0.550,23.37,320,1.000,bicubic +deit3_small_patch16_224_in21ft1k,96.660,3.340,99.330,0.670,22.06,224,1.000,bicubic resmlp_big_24_224_in22ft1k,96.620,3.380,99.510,0.490,129.14,224,0.875,bicubic +regnetz_d8,96.620,3.380,99.450,0.550,23.37,320,1.000,bicubic regnetz_d8_evos,96.610,3.390,99.440,0.560,23.46,320,0.950,bicubic resnest200e,96.610,3.390,99.350,0.650,70.20,320,0.909,bicubic -regnetz_d32,96.600,3.400,99.380,0.620,27.58,320,0.950,bicubic swsl_resnext101_32x16d,96.600,3.400,99.530,0.470,194.03,224,0.875,bilinear +regnetz_d32,96.600,3.400,99.380,0.620,27.58,320,0.950,bicubic xcit_medium_24_p16_224_dist,96.590,3.410,99.270,0.730,84.40,224,1.000,bicubic resnetrs152,96.580,3.420,99.240,0.760,86.62,320,1.000,bicubic -cait_xs24_384,96.550,3.450,99.420,0.580,26.67,384,1.000,bicubic -xcit_tiny_24_p8_384_dist,96.540,3.460,99.320,0.680,12.11,384,1.000,bicubic +xcit_tiny_24_p8_384_dist,96.550,3.450,99.320,0.680,12.11,384,1.000,bicubic +cait_xs24_384,96.540,3.460,99.420,0.580,26.67,384,1.000,bicubic efficientnetv2_rw_s,96.540,3.460,99.360,0.640,23.94,384,1.000,bicubic -crossvit_18_dagger_408,96.530,3.470,99.260,0.740,44.61,408,1.000,bicubic +swinv2_base_window8_256,96.540,3.460,99.270,0.730,87.92,256,0.900,bicubic regnety_080,96.530,3.470,99.320,0.680,39.18,288,1.000,bicubic +crossvit_18_dagger_408,96.530,3.470,99.260,0.740,44.61,408,1.000,bicubic resnest269e,96.520,3.480,99.350,0.650,110.93,416,0.928,bicubic vit_base_patch32_384,96.490,3.510,99.410,0.590,88.30,384,1.000,bicubic convnext_base,96.470,3.530,99.230,0.770,88.59,224,0.875,bicubic +swinv2_small_window16_256,96.460,3.540,99.200,0.800,49.73,256,0.900,bicubic resmlp_big_24_distilled_224,96.450,3.550,99.310,0.690,129.14,224,0.875,bicubic vit_base_patch16_224_miil,96.450,3.550,99.300,0.700,86.54,224,0.875,bilinear +cs3se_edgenet_x,96.440,3.560,99.400,0.600,50.72,320,1.000,bicubic swsl_resnext101_32x4d,96.430,3.570,99.470,0.530,44.18,224,0.875,bilinear regnetv_064,96.410,3.590,99.360,0.640,30.58,288,1.000,bicubic xcit_large_24_p8_224,96.410,3.590,98.980,1.020,188.93,224,1.000,bicubic xcit_small_24_p8_224,96.400,3.600,99.150,0.850,47.63,224,1.000,bicubic -crossvit_15_dagger_408,96.390,3.610,99.160,0.840,28.50,408,1.000,bicubic tf_efficientnet_b3_ns,96.390,3.610,99.350,0.650,12.23,300,0.904,bicubic +crossvit_15_dagger_408,96.390,3.610,99.160,0.840,28.50,408,1.000,bicubic cait_s24_224,96.380,3.620,99.150,0.850,46.92,224,1.000,bicubic resnet152d,96.360,3.640,99.390,0.610,60.21,320,1.000,bicubic regnety_064,96.360,3.640,99.230,0.770,30.58,288,1.000,bicubic @@ -136,237 +160,281 @@ tf_efficientnetv2_s,96.340,3.660,99.200,0.800,21.46,384,1.000,bicubic volo_d1_224,96.330,3.670,99.310,0.690,26.63,224,0.960,bicubic ig_resnext101_32x8d,96.310,3.690,99.430,0.570,88.79,224,0.875,bilinear resnet101d,96.300,3.700,99.230,0.770,44.57,320,1.000,bicubic +deit3_base_patch16_224,96.300,3.700,99.180,0.820,86.59,224,0.900,bicubic +swinv2_small_window8_256,96.290,3.710,99.210,0.790,49.73,256,0.900,bicubic twins_svt_large,96.270,3.730,99.170,0.830,99.27,224,0.900,bicubic +jx_nest_base,96.250,3.750,99.210,0.790,67.72,224,0.875,bicubic swin_s3_base_224,96.250,3.750,99.140,0.860,71.13,224,0.900,bicubic -jx_nest_base,96.240,3.760,99.210,0.790,67.72,224,0.875,bicubic swin_s3_small_224,96.230,3.770,99.090,0.910,49.74,224,0.900,bicubic -xcit_small_24_p16_224_dist,96.220,3.780,99.210,0.790,47.67,224,1.000,bicubic -xception65p,96.200,3.800,99.180,0.820,39.82,299,0.940,bicubic +convnext_tiny_in22ft1k,96.220,3.780,99.340,0.660,28.59,224,0.875,bicubic +xcit_small_24_p16_224_dist,96.210,3.790,99.210,0.790,47.67,224,1.000,bicubic +xception65p,96.210,3.790,99.180,0.820,39.82,299,0.940,bicubic +deit3_small_patch16_384,96.200,3.800,99.290,0.710,22.21,384,1.000,bicubic regnetv_040,96.190,3.810,99.330,0.670,20.64,288,1.000,bicubic +swinv2_cr_small_ns_224,96.180,3.820,99.140,0.860,49.70,224,0.900,bicubic +mobilevitv2_175_384_in22ft1k,96.180,3.820,99.130,0.870,14.25,384,1.000,bicubic convnext_small,96.170,3.830,99.100,0.900,50.22,224,0.875,bicubic -tf_efficientnet_b4_ap,96.170,3.830,99.280,0.720,19.34,380,0.922,bicubic +tf_efficientnet_b4_ap,96.160,3.840,99.280,0.720,19.34,380,0.922,bicubic twins_svt_base,96.160,3.840,99.060,0.940,56.07,224,0.900,bicubic -deit_base_patch16_384,96.150,3.850,99.140,0.860,86.86,384,1.000,bicubic -twins_pcpvt_large,96.150,3.850,99.180,0.820,60.99,224,0.900,bicubic dm_nfnet_f0,96.150,3.850,99.250,0.750,71.49,256,0.900,bicubic efficientnet_b4,96.150,3.850,99.190,0.810,19.34,384,1.000,bicubic +twins_pcpvt_large,96.150,3.850,99.180,0.820,60.99,224,0.900,bicubic +deit_base_patch16_384,96.150,3.850,99.140,0.860,86.86,384,1.000,bicubic +sequencer2d_l,96.140,3.860,99.160,0.840,54.30,224,0.875,bicubic regnetz_c16_evos,96.130,3.870,99.360,0.640,13.49,320,0.950,bicubic -nfnet_l0,96.120,3.880,99.240,0.760,35.07,288,1.000,bicubic resnetv2_50x1_bit_distilled,96.120,3.880,99.280,0.720,25.55,224,0.875,bicubic -xcit_medium_24_p8_224,96.110,3.890,98.890,1.110,84.32,224,1.000,bicubic +nfnet_l0,96.120,3.880,99.240,0.760,35.07,288,1.000,bicubic xcit_small_12_p8_224,96.110,3.890,99.160,0.840,26.21,224,1.000,bicubic +xcit_medium_24_p8_224,96.110,3.890,98.890,1.110,84.32,224,1.000,bicubic resnetv2_101x1_bitm,96.100,3.900,99.280,0.720,44.54,448,1.000,bilinear resnetv2_152x2_bit_teacher,96.100,3.900,99.270,0.730,236.34,224,0.875,bicubic deit_base_distilled_patch16_224,96.090,3.910,99.190,0.810,87.34,224,0.900,bicubic resnext101_64x4d,96.080,3.920,99.240,0.760,83.46,288,1.000,bicubic xcit_tiny_12_p8_384_dist,96.080,3.920,99.140,0.860,6.71,384,1.000,bicubic -xcit_small_12_p16_224_dist,96.030,3.970,99.140,0.860,26.25,224,1.000,bicubic -regnety_040,96.020,3.980,99.190,0.810,20.65,288,1.000,bicubic +swinv2_cr_small_224,96.060,3.940,98.870,1.130,49.70,224,0.900,bicubic +cs3edgenet_x,96.050,3.950,99.140,0.860,47.82,288,1.000,bicubic +cs3sedarknet_x,96.040,3.960,99.110,0.890,35.40,288,1.000,bicubic +mobilevitv2_200_384_in22ft1k,96.040,3.960,99.080,0.920,18.45,384,1.000,bicubic +xcit_small_12_p16_224_dist,96.020,3.980,99.130,0.870,26.25,224,1.000,bicubic +regnety_040,96.010,3.990,99.180,0.820,20.65,288,1.000,bicubic +sequencer2d_s,95.990,4.010,99.050,0.950,27.65,224,0.875,bicubic regnety_032,95.970,4.030,99.190,0.810,19.44,288,1.000,bicubic tresnet_xl_448,95.970,4.030,99.130,0.870,78.44,448,0.875,bilinear -jx_nest_small,95.970,4.030,99.030,0.970,38.35,224,0.875,bicubic +jx_nest_small,95.960,4.040,99.030,0.970,38.35,224,0.875,bicubic eca_nfnet_l0,95.950,4.050,99.210,0.790,24.14,288,1.000,bicubic -xcit_tiny_24_p16_384_dist,95.930,4.070,99.220,0.780,12.12,384,1.000,bicubic +swinv2_tiny_window16_256,95.940,4.060,99.140,0.860,28.35,256,0.900,bicubic +xcit_tiny_24_p16_384_dist,95.920,4.080,99.220,0.780,12.12,384,1.000,bicubic swin_small_patch4_window7_224,95.910,4.090,99.020,0.980,49.61,224,0.900,bicubic -resnet152,95.900,4.100,99.080,0.920,60.19,224,0.950,bicubic tf_efficientnet_b4,95.900,4.100,99.170,0.830,19.34,380,0.922,bicubic -resnet51q,95.870,4.130,99.120,0.880,35.70,288,1.000,bilinear -swsl_resnext50_32x4d,95.870,4.130,99.250,0.750,25.03,224,0.875,bilinear -tresnet_l_448,95.860,4.140,99.120,0.880,55.99,448,0.875,bilinear +resnet152,95.900,4.100,99.080,0.920,60.19,224,0.950,bicubic +resnet51q,95.870,4.130,99.130,0.870,35.70,288,1.000,bilinear +swsl_resnext50_32x4d,95.860,4.140,99.250,0.750,25.03,224,0.875,bilinear resnest101e,95.860,4.140,99.210,0.790,48.28,256,0.875,bilinear +cs3darknet_x,95.860,4.140,99.180,0.820,35.05,288,1.000,bicubic +tresnet_l_448,95.860,4.140,99.120,0.880,55.99,448,0.875,bilinear cait_xxs36_384,95.840,4.160,99.090,0.910,17.37,384,1.000,bicubic vit_large_patch32_384,95.830,4.170,99.150,0.850,306.63,384,1.000,bicubic xcit_tiny_24_p8_224_dist,95.810,4.190,99.210,0.790,12.11,224,1.000,bicubic +sequencer2d_m,95.810,4.190,99.110,0.890,38.31,224,0.875,bicubic regnetz_c16,95.800,4.200,99.100,0.900,13.46,320,0.940,bicubic ssl_resnext101_32x16d,95.790,4.210,99.180,0.820,194.03,224,0.875,bilinear twins_pcpvt_base,95.790,4.210,99.130,0.870,43.83,224,0.900,bicubic resnet61q,95.780,4.220,98.990,1.010,36.85,288,1.000,bicubic -tf_efficientnet_b2_ns,95.770,4.230,99.120,0.880,9.11,260,0.890,bicubic +tf_efficientnet_b2_ns,95.760,4.240,99.120,0.880,9.11,260,0.890,bicubic +vit_relpos_base_patch16_clsgap_224,95.760,4.240,99.040,0.960,86.43,224,0.900,bicubic gc_efficientnetv2_rw_t,95.740,4.260,99.020,0.980,13.68,288,1.000,bicubic efficientnet_b3,95.710,4.290,99.040,0.960,12.23,320,1.000,bicubic tresnet_m,95.710,4.290,99.030,0.970,31.39,224,0.875,bilinear pnasnet5large,95.710,4.290,98.920,1.080,86.06,331,0.911,bicubic +mobilevitv2_150_384_in22ft1k,95.700,4.300,99.140,0.860,10.59,384,1.000,bicubic crossvit_15_dagger_240,95.690,4.310,98.830,1.170,28.21,240,0.875,bicubic nasnetalarge,95.680,4.320,98.930,1.070,88.75,331,0.911,bicubic xcit_tiny_24_p8_224,95.670,4.330,99.050,0.950,12.11,224,1.000,bicubic -poolformer_m48,95.640,4.360,98.940,1.060,73.47,224,0.950,bicubic vit_small_r26_s32_224,95.640,4.360,99.190,0.810,36.43,224,0.900,bicubic +poolformer_m48,95.640,4.360,98.940,1.060,73.47,224,0.950,bicubic pit_b_224,95.640,4.360,98.670,1.330,73.76,224,0.900,bicubic -resnetv2_101,95.630,4.370,98.990,1.010,44.54,224,0.950,bicubic -efficientnetv2_rw_t,95.610,4.390,99.070,0.930,13.65,288,1.000,bicubic +resnetv2_101,95.620,4.380,98.990,1.010,44.54,224,0.950,bicubic resnetv2_50d_evos,95.610,4.390,99.030,0.970,25.59,288,0.950,bicubic +efficientnetv2_rw_t,95.600,4.400,99.070,0.930,13.65,288,1.000,bicubic crossvit_18_dagger_240,95.570,4.430,99.060,0.940,44.27,240,0.875,bicubic -convit_base,95.550,4.450,98.870,1.130,86.54,224,0.875,bicubic +vit_relpos_base_patch16_224,95.570,4.430,99.030,0.970,86.43,224,0.900,bicubic convnext_tiny,95.550,4.450,99.000,1.000,28.59,224,0.875,bicubic +convit_base,95.550,4.450,98.870,1.130,86.54,224,0.875,bicubic coat_lite_small,95.540,4.460,98.860,1.140,19.84,224,0.900,bicubic -xcit_small_24_p16_224,95.530,4.470,98.760,1.240,47.67,224,1.000,bicubic -xcit_medium_24_p16_224,95.530,4.470,98.740,1.260,84.40,224,1.000,bicubic -levit_384,95.530,4.470,99.050,0.950,39.13,224,0.900,bicubic ecaresnet101d,95.530,4.470,99.130,0.870,44.57,224,0.875,bicubic +levit_384,95.530,4.470,99.050,0.950,39.13,224,0.900,bicubic +xcit_small_24_p16_224,95.530,4.470,98.770,1.230,47.67,224,1.000,bicubic +xcit_medium_24_p16_224,95.530,4.470,98.740,1.260,84.40,224,1.000,bicubic crossvit_base_240,95.520,4.480,98.820,1.180,105.03,240,0.875,bicubic -xception41p,95.520,4.480,98.910,1.090,26.91,299,0.940,bicubic -convnext_tiny_hnf,95.510,4.490,99.020,0.980,28.59,224,0.950,bicubic ecaresnet50t,95.510,4.490,99.120,0.880,25.57,320,0.950,bicubic +vit_relpos_medium_patch16_rpn_224,95.510,4.490,99.080,0.920,38.73,224,0.900,bicubic +convnext_tiny_hnf,95.510,4.490,99.020,0.980,28.59,224,0.950,bicubic fbnetv3_g,95.510,4.490,98.990,1.010,16.62,288,0.950,bilinear +xception41p,95.510,4.490,98.910,1.090,26.91,299,0.940,bicubic +swinv2_tiny_window8_256,95.500,4.500,99.120,0.880,28.35,256,0.900,bicubic ssl_resnext101_32x8d,95.490,4.510,99.120,0.880,88.79,224,0.875,bilinear -visformer_small,95.490,4.510,98.900,1.100,40.22,224,0.900,bicubic +vit_relpos_medium_patch16_cls_224,95.480,4.520,98.950,1.050,38.76,224,0.900,bicubic +visformer_small,95.470,4.530,98.900,1.100,40.22,224,0.900,bicubic +vit_relpos_medium_patch16_224,95.460,4.540,98.960,1.040,38.75,224,0.900,bicubic ssl_resnext101_32x4d,95.440,4.560,99.130,0.870,44.18,224,0.875,bilinear tresnet_xl,95.440,4.560,99.050,0.950,78.44,224,0.875,bilinear -crossvit_18_240,95.440,4.560,98.790,1.210,43.27,240,0.875,bicubic deit_base_patch16_224,95.440,4.560,98.840,1.160,86.57,224,0.900,bicubic -resnetrs101,95.430,4.570,99.030,0.970,63.62,288,0.940,bicubic +crossvit_18_240,95.440,4.560,98.790,1.210,43.27,240,0.875,bicubic resnetv2_50d_gn,95.430,4.570,99.040,0.960,25.57,288,0.950,bicubic -xcit_large_24_p16_224,95.420,4.580,98.620,1.380,189.10,224,1.000,bicubic +resnetrs101,95.430,4.570,99.030,0.970,63.62,288,0.940,bicubic +halo2botnet50ts_256,95.420,4.580,99.010,0.990,22.64,256,0.950,bicubic xcit_small_12_p16_224,95.420,4.580,98.840,1.160,26.25,224,1.000,bicubic -halo2botnet50ts_256,95.410,4.590,99.010,0.990,22.64,256,0.950,bicubic -swsl_resnet50,95.400,4.600,99.300,0.700,25.56,224,0.875,bilinear +xcit_large_24_p16_224,95.420,4.580,98.620,1.380,189.10,224,1.000,bicubic +swsl_resnet50,95.410,4.590,99.300,0.700,25.56,224,0.875,bilinear +edgenext_small,95.410,4.590,99.100,0.900,5.59,320,1.000,bicubic +vit_base_patch16_rpn_224,95.380,4.620,98.930,1.070,86.54,224,0.900,bicubic poolformer_m36,95.380,4.620,98.850,1.150,56.17,224,0.950,bicubic vit_small_patch16_224,95.370,4.630,99.150,0.850,22.05,224,0.900,bicubic +swinv2_cr_tiny_ns_224,95.370,4.630,98.940,1.060,28.33,224,0.900,bicubic resnet101,95.360,4.640,98.860,1.140,44.55,224,0.950,bicubic +convnext_nano,95.360,4.640,98.850,1.150,15.59,288,1.000,bicubic tf_efficientnet_b3_ap,95.320,4.680,98.900,1.100,12.23,300,0.904,bicubic -mixer_b16_224_miil,95.310,4.690,98.870,1.130,59.88,224,0.875,bilinear +cs3sedarknet_l,95.310,4.690,99.130,0.870,21.91,288,0.950,bicubic +mixer_b16_224_miil,95.300,4.700,98.880,1.120,59.88,224,0.875,bilinear tresnet_l,95.290,4.710,99.010,0.990,55.99,224,0.875,bilinear -cait_xxs24_384,95.270,4.730,98.960,1.040,12.03,384,1.000,bicubic +cait_xxs24_384,95.280,4.720,98.960,1.040,12.03,384,1.000,bicubic pit_s_distilled_224,95.240,4.760,99.050,0.950,24.04,224,0.900,bicubic jx_nest_tiny,95.240,4.760,98.980,1.020,17.06,224,0.875,bicubic +vit_srelpos_medium_patch16_224,95.230,4.770,98.990,1.010,38.74,224,0.900,bicubic +mobilevitv2_175_in22ft1k,95.230,4.770,98.790,1.210,14.25,256,0.888,bicubic +resnetaa50,95.210,4.790,98.930,1.070,25.56,288,1.000,bicubic twins_pcpvt_small,95.210,4.790,98.880,1.120,24.11,224,0.900,bicubic convit_small,95.200,4.800,98.900,1.100,27.78,224,0.875,bicubic twins_svt_small,95.200,4.800,98.880,1.120,24.06,224,0.900,bicubic -tf_efficientnet_b1_ns,95.170,4.830,99.120,0.880,7.79,240,0.882,bicubic +tf_efficientnet_b1_ns,95.180,4.820,99.110,0.890,7.79,240,0.882,bicubic +cs3darknet_focus_l,95.170,4.830,98.960,1.040,21.15,288,0.950,bicubic +mobilevitv2_200_in22ft1k,95.160,4.840,98.950,1.050,18.45,256,0.888,bicubic +vit_relpos_small_patch16_224,95.160,4.840,98.950,1.050,21.98,224,0.900,bicubic swin_s3_tiny_224,95.160,4.840,98.940,1.060,28.33,224,0.900,bicubic tf_efficientnetv2_b3,95.160,4.840,98.820,1.180,14.36,300,0.904,bicubic -halonet50ts,95.150,4.850,98.770,1.230,22.73,256,0.940,bicubic +crossvit_15_240,95.150,4.850,98.930,1.070,27.53,240,0.875,bicubic lamhalobotnet50ts_256,95.150,4.850,98.880,1.120,22.57,256,0.950,bicubic -swin_tiny_patch4_window7_224,95.140,4.860,98.850,1.150,28.29,224,0.900,bicubic -crossvit_15_240,95.140,4.860,98.930,1.070,27.53,240,0.875,bicubic +mobilevitv2_150_in22ft1k,95.140,4.860,98.860,1.140,10.59,256,0.888,bicubic +halonet50ts,95.140,4.860,98.770,1.230,22.73,256,0.940,bicubic xcit_tiny_12_p16_384_dist,95.130,4.870,99.020,0.980,6.72,384,1.000,bicubic +swin_tiny_patch4_window7_224,95.130,4.870,98.850,1.150,28.29,224,0.900,bicubic +cs3darknet_l,95.120,4.880,98.980,1.020,21.16,288,0.950,bicubic efficientnet_el,95.120,4.880,98.980,1.020,10.59,300,0.904,bicubic -gernet_l,95.100,4.900,98.900,1.100,31.08,256,0.875,bilinear +xcit_tiny_12_p8_224_dist,95.100,4.900,98.910,1.090,6.71,224,1.000,bicubic poolformer_s36,95.090,4.910,98.910,1.090,30.86,224,0.900,bicubic -xcit_tiny_12_p8_224_dist,95.090,4.910,98.910,1.090,6.71,224,1.000,bicubic +gernet_l,95.090,4.910,98.900,1.100,31.08,256,0.875,bilinear ecaresnet101d_pruned,95.080,4.920,98.980,1.020,24.88,224,0.875,bicubic +wide_resnet50_2,95.080,4.920,98.970,1.030,68.88,224,0.875,bicubic +convmixer_1536_20,95.070,4.930,99.030,0.970,51.63,224,0.960,bicubic legacy_senet154,95.070,4.930,98.830,1.170,115.09,224,0.875,bilinear -wide_resnet50_2,95.070,4.930,98.970,1.030,68.88,224,0.875,bicubic -vit_small_patch32_384,95.060,4.940,98.990,1.010,22.92,384,1.000,bicubic -convmixer_1536_20,95.060,4.940,99.030,0.970,51.63,224,0.960,bicubic regnetz_b16,95.060,4.940,99.050,0.950,9.72,288,0.940,bicubic +vit_small_patch32_384,95.050,4.950,98.990,1.010,22.92,384,1.000,bicubic gluon_resnet152_v1s,95.040,4.960,98.930,1.070,60.32,224,0.875,bicubic -tnt_s_patch16_224,95.040,4.960,98.840,1.160,23.76,224,0.900,bicubic +tnt_s_patch16_224,95.040,4.960,98.830,1.170,23.76,224,0.900,bicubic +vit_srelpos_small_patch16_224,95.030,4.970,98.960,1.040,21.97,224,0.900,bicubic seresnext50_32x4d,95.030,4.970,98.880,1.120,27.56,224,0.875,bicubic -levit_256,95.020,4.980,98.890,1.110,18.89,224,0.900,bicubic -tf_efficientnet_b3,95.020,4.980,98.910,1.090,12.23,300,0.904,bicubic resnetv2_50x1_bitm,95.010,4.990,99.060,0.940,25.55,448,1.000,bilinear +tf_efficientnet_b3,95.010,4.990,98.910,1.090,12.23,300,0.904,bicubic +levit_256,95.010,4.990,98.890,1.110,18.89,224,0.900,bicubic vit_base_patch32_224,95.000,5.000,99.030,0.970,88.22,224,0.900,bicubic +deit3_small_patch16_224,95.000,5.000,98.460,1.540,22.06,224,0.900,bicubic tresnet_m_448,94.990,5.010,98.980,1.020,31.39,448,0.875,bilinear coat_mini,94.970,5.030,98.780,1.220,10.34,224,0.900,bicubic resnest50d_4s2x40d,94.960,5.040,99.070,0.930,30.42,224,0.875,bicubic rexnet_200,94.950,5.050,99.010,0.990,16.37,224,0.875,bicubic -gluon_senet154,94.920,5.080,98.760,1.240,115.09,224,0.875,bicubic -gluon_seresnext101_32x4d,94.920,5.080,98.810,1.190,48.96,224,0.875,bicubic gluon_seresnext101_64x4d,94.920,5.080,98.830,1.170,88.23,224,0.875,bicubic -tf_efficientnet_lite4,94.890,5.110,99.020,0.980,13.01,380,0.920,bilinear +gluon_seresnext101_32x4d,94.920,5.080,98.810,1.190,48.96,224,0.875,bicubic +gluon_senet154,94.920,5.080,98.760,1.240,115.09,224,0.875,bicubic +mobilevitv2_175,94.890,5.110,98.860,1.140,14.25,256,0.888,bicubic +tf_efficientnet_lite4,94.880,5.120,99.020,0.980,13.01,380,0.920,bilinear resmlp_36_distilled_224,94.880,5.120,98.840,1.160,44.69,224,0.875,bicubic ssl_resnext50_32x4d,94.870,5.130,98.890,1.110,25.03,224,0.875,bilinear -gcresnet50t,94.850,5.150,98.790,1.210,25.90,256,0.900,bicubic +seresnet33ts,94.860,5.140,98.790,1.210,19.78,256,0.900,bicubic resnest50d,94.850,5.150,98.880,1.120,27.48,224,0.875,bilinear -seresnet33ts,94.850,5.150,98.790,1.210,19.78,256,0.900,bicubic +gcresnet50t,94.850,5.150,98.790,1.210,25.90,256,0.900,bicubic crossvit_small_240,94.830,5.170,99.020,0.980,26.86,240,0.875,bicubic -lambda_resnet50ts,94.790,5.210,98.460,1.540,21.54,256,0.950,bicubic +cspresnext50,94.830,5.170,98.770,1.230,20.57,256,0.887,bilinear +mobilevitv2_200,94.830,5.170,98.710,1.290,18.45,256,0.888,bicubic +sehalonet33ts,94.780,5.220,98.570,1.430,13.69,256,0.940,bicubic +lambda_resnet50ts,94.780,5.220,98.460,1.540,21.54,256,0.950,bicubic ecaresnetlight,94.770,5.230,98.800,1.200,30.16,224,0.875,bicubic -sehalonet33ts,94.770,5.230,98.570,1.430,13.69,256,0.940,bicubic -resnest50d_1s4x24d,94.760,5.240,98.980,1.020,25.68,224,0.875,bicubic +resnest50d_1s4x24d,94.750,5.250,98.980,1.020,25.68,224,0.875,bicubic gluon_resnet152_v1d,94.740,5.260,98.740,1.260,60.21,224,0.875,bicubic gluon_resnet101_v1s,94.720,5.280,98.820,1.180,44.67,224,0.875,bicubic deit_small_distilled_patch16_224,94.710,5.290,99.030,0.970,22.44,224,0.900,bicubic haloregnetz_b,94.700,5.300,98.660,1.340,11.68,224,0.940,bicubic xcit_tiny_12_p8_224,94.690,5.310,98.830,1.170,6.71,224,1.000,bicubic -resmlp_big_24_224,94.670,5.330,98.480,1.520,129.14,224,0.875,bicubic cspdarknet53,94.660,5.340,98.800,1.200,27.64,256,0.887,bilinear +edgenext_small_rw,94.660,5.340,98.790,1.210,7.83,320,1.000,bicubic gluon_resnext101_64x4d,94.660,5.340,98.650,1.350,83.46,224,0.875,bicubic +resmlp_big_24_224,94.660,5.340,98.480,1.520,129.14,224,0.875,bicubic +darknet53,94.630,5.370,98.890,1.110,41.61,288,1.000,bicubic efficientnet_b3_pruned,94.630,5.370,98.760,1.240,9.86,300,0.904,bicubic -ecaresnet50d,94.630,5.370,98.890,1.110,25.58,224,0.875,bicubic +ecaresnet50d,94.620,5.380,98.890,1.110,25.58,224,0.875,bicubic gernet_m,94.620,5.380,98.860,1.140,21.14,224,0.875,bilinear efficientnet_b2,94.610,5.390,98.710,1.290,9.11,288,1.000,bicubic pit_s_224,94.590,5.410,98.700,1.300,23.46,224,0.900,bicubic +sebotnet33ts_256,94.580,5.420,98.500,1.500,13.70,256,0.940,bicubic repvgg_b3,94.570,5.430,98.780,1.220,123.09,224,0.875,bilinear -sebotnet33ts_256,94.570,5.430,98.500,1.500,13.70,256,0.940,bicubic poolformer_s24,94.550,5.450,98.880,1.120,21.39,224,0.900,bicubic -resnext50_32x4d,94.550,5.450,98.610,1.390,25.03,224,0.950,bicubic -seresnet50,94.550,5.450,98.750,1.250,28.09,224,0.875,bicubic nf_resnet50,94.550,5.450,98.790,1.210,25.56,288,0.940,bicubic -inception_resnet_v2,94.550,5.450,98.780,1.220,55.84,299,0.897,bicubic +seresnet50,94.550,5.450,98.750,1.250,28.09,224,0.875,bicubic +mobilevitv2_150,94.550,5.450,98.710,1.290,10.59,256,0.888,bicubic +regnety_320,94.540,5.460,98.860,1.140,145.05,224,0.875,bicubic gluon_resnext101_32x4d,94.540,5.460,98.630,1.370,44.18,224,0.875,bicubic -regnety_320,94.540,5.460,98.850,1.150,145.05,224,0.875,bicubic -xcit_tiny_24_p16_224_dist,94.540,5.460,98.780,1.220,12.12,224,1.000,bicubic +resnext50_32x4d,94.540,5.460,98.610,1.390,25.03,224,0.950,bicubic +inception_resnet_v2,94.530,5.470,98.780,1.220,55.84,299,0.897,bicubic +xcit_tiny_24_p16_224_dist,94.530,5.470,98.780,1.220,12.12,224,1.000,bicubic repvgg_b3g4,94.520,5.480,98.970,1.030,83.83,224,0.875,bilinear convmixer_768_32,94.500,5.500,98.850,1.150,21.11,224,0.960,bicubic gcresnext50ts,94.490,5.510,98.670,1.330,15.67,256,0.900,bicubic tf_efficientnet_b2_ap,94.490,5.510,98.620,1.380,9.11,260,0.890,bicubic regnety_120,94.480,5.520,98.810,1.190,51.82,224,0.875,bicubic rexnet_150,94.480,5.520,98.790,1.210,9.73,224,0.875,bicubic -cspresnext50,94.470,5.530,98.680,1.320,20.57,224,0.875,bilinear gcresnet33ts,94.470,5.530,98.770,1.230,19.88,256,0.900,bicubic -regnetx_320,94.460,5.540,98.740,1.260,107.81,224,0.875,bicubic +darknetaa53,94.470,5.530,98.760,1.240,36.02,288,1.000,bilinear resmlp_24_distilled_224,94.460,5.540,98.770,1.230,30.02,224,0.875,bicubic -ssl_resnet50,94.450,5.550,98.920,1.080,25.56,224,0.875,bilinear -resnetv2_50,94.430,5.570,98.740,1.260,25.55,224,0.950,bicubic +regnetx_320,94.460,5.540,98.740,1.260,107.81,224,0.875,bicubic +ssl_resnet50,94.440,5.560,98.920,1.080,25.56,224,0.875,bilinear +resnetv2_50,94.430,5.570,98.730,1.270,25.55,224,0.950,bicubic tf_efficientnetv2_b2,94.420,5.580,98.570,1.430,10.10,260,0.890,bicubic -tf_efficientnet_el,94.400,5.600,98.710,1.290,10.59,300,0.904,bicubic efficientnet_el_pruned,94.400,5.600,98.740,1.260,10.59,300,0.904,bicubic +tf_efficientnet_el,94.400,5.600,98.710,1.290,10.59,300,0.904,bicubic deit_small_patch16_224,94.390,5.610,98.690,1.310,22.05,224,0.900,bicubic inception_v4,94.380,5.620,98.580,1.420,42.68,299,0.875,bicubic -legacy_seresnext101_32x4d,94.360,5.640,98.650,1.350,48.96,224,0.875,bilinear +legacy_seresnext101_32x4d,94.370,5.630,98.650,1.350,48.96,224,0.875,bilinear tf_efficientnet_b2,94.360,5.640,98.610,1.390,9.11,260,0.890,bicubic resnet50_gn,94.350,5.650,98.710,1.290,25.56,224,0.940,bicubic resnet50,94.340,5.660,98.440,1.560,25.56,224,0.950,bicubic gluon_seresnext50_32x4d,94.330,5.670,98.610,1.390,27.56,224,0.875,bicubic -ecaresnet26t,94.310,5.690,98.720,1.280,16.01,320,0.950,bicubic -dpn107,94.300,5.700,98.470,1.530,86.92,224,0.875,bicubic +ecaresnet26t,94.320,5.680,98.720,1.280,16.01,320,0.950,bicubic +dpn107,94.310,5.690,98.470,1.530,86.92,224,0.875,bicubic resnetrs50,94.300,5.700,98.640,1.360,35.69,224,0.910,bicubic xception71,94.280,5.720,98.640,1.360,42.34,299,0.903,bicubic cait_xxs36_224,94.260,5.740,98.720,1.280,17.30,224,1.000,bicubic -gluon_xception65,94.260,5.740,98.570,1.430,39.92,299,0.903,bicubic resnet50d,94.260,5.740,98.720,1.280,25.58,224,0.875,bicubic -skresnext50_32x4d,94.260,5.740,98.460,1.540,27.48,224,0.875,bicubic +gluon_xception65,94.260,5.740,98.570,1.430,39.92,299,0.903,bicubic +skresnext50_32x4d,94.250,5.750,98.460,1.540,27.48,224,0.875,bicubic regnetx_120,94.240,5.760,98.650,1.350,46.11,224,0.875,bicubic -gluon_resnet101_v1d,94.230,5.770,98.560,1.440,44.57,224,0.875,bicubic dpn92,94.230,5.770,98.730,1.270,37.67,224,0.875,bicubic +gluon_resnet101_v1d,94.230,5.770,98.550,1.450,44.57,224,0.875,bicubic ecaresnet50d_pruned,94.220,5.780,98.730,1.270,19.94,224,0.875,bicubic +tf_efficientnet_lite3,94.210,5.790,98.640,1.360,8.20,300,0.904,bilinear resmlp_36_224,94.200,5.800,98.660,1.340,44.69,224,0.875,bicubic -tf_efficientnet_lite3,94.200,5.800,98.640,1.360,8.20,300,0.904,bilinear -eca_resnet33ts,94.190,5.810,98.770,1.230,19.68,256,0.900,bicubic +eca_resnet33ts,94.190,5.810,98.760,1.240,19.68,256,0.900,bicubic +resnext50d_32x4d,94.190,5.810,98.560,1.440,25.05,224,0.875,bicubic mixnet_xl,94.190,5.810,98.340,1.660,11.90,224,0.875,bicubic -resnext50d_32x4d,94.180,5.820,98.570,1.430,25.05,224,0.875,bicubic -levit_192,94.170,5.830,98.550,1.450,10.95,224,0.900,bicubic -ens_adv_inception_resnet_v2,94.160,5.840,98.600,1.400,55.84,299,0.897,bicubic +levit_192,94.180,5.820,98.540,1.460,10.95,224,0.900,bicubic gluon_resnet152_v1c,94.160,5.840,98.640,1.360,60.21,224,0.875,bicubic -gmlp_s16_224,94.150,5.850,98.500,1.500,19.42,224,0.875,bicubic -efficientnet_b2_pruned,94.140,5.860,98.530,1.470,8.31,260,0.890,bicubic +ens_adv_inception_resnet_v2,94.160,5.840,98.600,1.400,55.84,299,0.897,bicubic +gmlp_s16_224,94.160,5.840,98.500,1.500,19.42,224,0.875,bicubic +efficientnet_b2_pruned,94.150,5.850,98.530,1.470,8.31,260,0.890,bicubic vit_base_patch16_224_sam,94.140,5.860,98.670,1.330,86.57,224,0.900,bicubic regnetx_160,94.130,5.870,98.740,1.260,54.28,224,0.875,bicubic -nf_regnet_b1,94.120,5.880,98.620,1.380,10.22,288,0.900,bicubic -dpn98,94.110,5.890,98.580,1.420,61.57,224,0.875,bicubic +dpn98,94.120,5.880,98.580,1.420,61.57,224,0.875,bicubic +nf_regnet_b1,94.110,5.890,98.630,1.370,10.22,288,0.900,bicubic ese_vovnet39b,94.090,5.910,98.660,1.340,24.57,224,0.875,bicubic -xcit_tiny_24_p16_224,94.070,5.930,98.510,1.490,12.12,224,1.000,bicubic +xcit_tiny_24_p16_224,94.070,5.930,98.530,1.470,12.12,224,1.000,bicubic gluon_resnet152_v1b,94.070,5.930,98.460,1.540,60.19,224,0.875,bicubic coat_lite_mini,94.050,5.950,98.560,1.440,11.01,224,0.900,bicubic -eca_halonext26ts,94.050,5.950,98.490,1.510,10.76,256,0.940,bicubic -halonet26t,94.020,5.980,98.500,1.500,12.48,256,0.950,bicubic +eca_halonext26ts,94.040,5.960,98.490,1.510,10.76,256,0.940,bicubic +hrnet_w64,94.020,5.980,98.620,1.380,128.06,224,0.875,bilinear resmlp_24_224,94.020,5.980,98.330,1.670,30.02,224,0.875,bicubic -hrnet_w64,94.010,5.990,98.610,1.390,128.06,224,0.875,bilinear +halonet26t,94.010,5.990,98.500,1.500,12.48,256,0.950,bicubic dpn131,93.990,6.010,98.720,1.280,79.25,224,0.875,bicubic fbnetv3_b,93.970,6.030,98.630,1.370,8.60,256,0.950,bilinear -dla102x2,93.960,6.040,98.490,1.510,41.28,224,0.875,bilinear -resnetblur50,93.940,6.060,98.580,1.420,25.56,224,0.875,bicubic +mobilevitv2_125,93.970,6.030,98.560,1.440,7.48,256,0.888,bicubic +dla102x2,93.970,6.030,98.500,1.500,41.28,224,0.875,bilinear tf_efficientnetv2_b1,93.940,6.060,98.620,1.380,8.14,240,0.882,bicubic +resnetblur50,93.940,6.060,98.580,1.420,25.56,224,0.875,bicubic fbnetv3_d,93.930,6.070,98.740,1.260,10.31,256,0.950,bilinear hrnet_w48,93.920,6.080,98.610,1.390,77.47,224,0.875,bilinear tf_efficientnet_cc_b1_8e,93.910,6.090,98.260,1.740,39.72,240,0.882,bicubic rexnet_130,93.900,6.100,98.400,1.600,7.56,224,0.875,bicubic regnetx_064,93.890,6.110,98.630,1.370,26.21,224,0.875,bicubic regnetx_080,93.870,6.130,98.520,1.480,39.57,224,0.875,bicubic -repvgg_b2g4,93.840,6.160,98.590,1.410,61.76,224,0.875,bilinear efficientnet_em,93.840,6.160,98.810,1.190,6.90,240,0.882,bicubic +repvgg_b2g4,93.840,6.160,98.590,1.410,61.76,224,0.875,bilinear lambda_resnet26t,93.830,6.170,98.650,1.350,10.96,256,0.940,bicubic pit_xs_distilled_224,93.820,6.180,98.670,1.330,11.00,224,0.900,bicubic resnext101_32x8d,93.820,6.180,98.580,1.420,88.79,224,0.875,bilinear @@ -375,217 +443,227 @@ eca_botnext26ts_256,93.780,6.220,98.500,1.500,10.59,256,0.950,bicubic gluon_resnet50_v1d,93.770,6.230,98.390,1.610,25.58,224,0.875,bicubic gluon_resnet101_v1b,93.750,6.250,98.380,1.620,44.55,224,0.875,bicubic res2net101_26w_4s,93.750,6.250,98.310,1.690,45.21,224,0.875,bilinear -cspresnet50,93.740,6.260,98.640,1.360,21.62,256,0.887,bilinear +cspresnet50,93.730,6.270,98.640,1.360,21.62,256,0.887,bilinear legacy_seresnext50_32x4d,93.730,6.270,98.580,1.420,27.56,224,0.875,bilinear -wide_resnet101_2,93.720,6.280,98.540,1.460,126.89,224,0.875,bilinear -lambda_resnet26rpt_256,93.710,6.290,98.510,1.490,10.99,256,0.940,bicubic +vit_relpos_base_patch32_plus_rpn_256,93.730,6.270,98.070,1.930,119.42,256,0.900,bicubic +lambda_resnet26rpt_256,93.720,6.280,98.520,1.480,10.99,256,0.940,bicubic +wide_resnet101_2,93.710,6.290,98.540,1.460,126.89,224,0.875,bilinear dpn68b,93.690,6.310,98.520,1.480,12.61,224,0.875,bicubic -tf_efficientnet_b1_ap,93.690,6.310,98.360,1.640,7.79,240,0.882,bicubic +tf_efficientnet_b1_ap,93.680,6.320,98.360,1.640,7.79,240,0.882,bicubic gluon_resnet101_v1c,93.670,6.330,98.420,1.580,44.57,224,0.875,bicubic -vit_tiny_patch16_384,93.660,6.340,98.600,1.400,5.79,384,1.000,bicubic -tf_efficientnet_b0_ns,93.640,6.360,98.640,1.360,5.29,224,0.875,bicubic +vit_tiny_patch16_384,93.650,6.350,98.600,1.400,5.79,384,1.000,bicubic +tf_efficientnet_b0_ns,93.630,6.370,98.640,1.360,5.29,224,0.875,bicubic gluon_resnet50_v1s,93.620,6.380,98.460,1.540,25.68,224,0.875,bicubic -cait_xxs24_224,93.600,6.400,98.450,1.550,11.96,224,1.000,bicubic -resnet33ts,93.600,6.400,98.540,1.460,19.68,256,0.900,bicubic +resnet33ts,93.600,6.400,98.530,1.470,19.68,256,0.900,bicubic +cait_xxs24_224,93.600,6.400,98.440,1.560,11.96,224,1.000,bicubic coat_tiny,93.590,6.410,98.420,1.580,5.50,224,0.900,bicubic +regnetx_040,93.560,6.440,98.550,1.450,22.12,224,0.875,bicubic hrnet_w44,93.550,6.450,98.700,1.300,67.06,224,0.875,bilinear -regnetx_040,93.550,6.450,98.550,1.450,22.12,224,0.875,bicubic hrnet_w32,93.530,6.470,98.460,1.540,41.23,224,0.875,bilinear +xcit_nano_12_p8_384_dist,93.520,6.480,98.540,1.460,3.05,384,1.000,bicubic +dla102x,93.520,6.480,98.500,1.500,26.31,224,0.875,bilinear botnet26t_256,93.510,6.490,98.300,1.700,12.49,256,0.950,bicubic -dla102x,93.510,6.490,98.510,1.490,26.31,224,0.875,bilinear -xcit_nano_12_p8_384_dist,93.500,6.500,98.540,1.460,3.05,384,1.000,bicubic -repvgg_b2,93.500,6.500,98.730,1.270,89.02,224,0.875,bilinear +tf_efficientnet_b1,93.500,6.500,98.360,1.640,7.79,240,0.882,bicubic +repvgg_b2,93.490,6.510,98.730,1.270,89.02,224,0.875,bilinear hrnet_w40,93.490,6.510,98.580,1.420,57.56,224,0.875,bilinear -tf_efficientnet_b1,93.490,6.510,98.360,1.640,7.79,240,0.882,bicubic -resnet32ts,93.470,6.530,98.490,1.510,17.96,256,0.900,bicubic xception,93.470,6.530,98.530,1.470,22.86,299,0.897,bicubic +resnet32ts,93.460,6.540,98.490,1.510,17.96,256,0.900,bicubic gluon_inception_v3,93.450,6.550,98.570,1.430,23.83,299,0.875,bicubic mixnet_l,93.450,6.550,98.220,1.780,7.33,224,0.875,bicubic xception41,93.430,6.570,98.430,1.570,26.97,299,0.903,bicubic -res2net50_26w_8s,93.410,6.590,98.180,1.820,48.40,224,0.875,bilinear +res2net50_26w_8s,93.420,6.580,98.170,1.830,48.40,224,0.875,bilinear res2net50_26w_6s,93.410,6.590,98.280,1.720,37.05,224,0.875,bilinear xcit_tiny_12_p16_224_dist,93.400,6.600,98.480,1.520,6.72,224,1.000,bicubic -legacy_seresnet152,93.400,6.600,98.350,1.650,66.82,224,0.875,bilinear +legacy_seresnet152,93.390,6.610,98.340,1.660,66.82,224,0.875,bilinear +cs3darknet_m,93.360,6.640,98.600,1.400,9.31,288,0.950,bicubic dla169,93.340,6.660,98.590,1.410,53.39,224,0.875,bilinear +resnest26d,93.330,6.670,98.630,1.370,17.07,224,0.875,bilinear +levit_128,93.330,6.670,98.380,1.620,9.21,224,0.900,bicubic bat_resnext26ts,93.330,6.670,98.350,1.650,10.73,256,0.900,bicubic -repvgg_b1,93.330,6.670,98.510,1.490,57.42,224,0.875,bilinear +repvgg_b1,93.320,6.680,98.510,1.490,57.42,224,0.875,bilinear tf_inception_v3,93.320,6.680,98.030,1.970,23.83,299,0.875,bicubic -tv_resnet152,93.320,6.680,98.390,1.610,60.19,224,0.875,bilinear tf_mixnet_l,93.320,6.680,98.030,1.970,7.33,224,0.875,bicubic -resnest26d,93.320,6.680,98.630,1.370,17.07,224,0.875,bilinear -levit_128,93.320,6.680,98.380,1.620,9.21,224,0.900,bicubic -legacy_seresnet101,93.300,6.700,98.510,1.490,49.33,224,0.875,bilinear +tv_resnet152,93.310,6.690,98.390,1.610,60.19,224,0.875,bilinear +mobilevitv2_100,93.300,6.700,98.280,1.720,4.90,256,0.888,bicubic +legacy_seresnet101,93.290,6.710,98.510,1.490,49.33,224,0.875,bilinear selecsls60b,93.290,6.710,98.280,1.720,32.77,224,0.875,bicubic -efficientnet_b1,93.250,6.750,98.290,1.710,7.79,256,1.000,bicubic +efficientnet_b1,93.240,6.760,98.300,1.700,7.79,256,1.000,bicubic coat_lite_tiny,93.230,6.770,98.260,1.740,5.72,224,0.900,bicubic -hrnet_w30,93.190,6.810,98.410,1.590,37.71,224,0.875,bilinear -dla60_res2net,93.180,6.820,98.420,1.580,20.85,224,0.875,bilinear -dla60_res2next,93.180,6.820,98.410,1.590,17.03,224,0.875,bilinear -mobilevit_s,93.170,6.830,98.440,1.560,5.58,256,0.900,bicubic +hrnet_w30,93.200,6.800,98.410,1.590,37.71,224,0.875,bilinear +mobilevit_s,93.180,6.820,98.440,1.560,5.58,256,0.900,bicubic +dla60_res2next,93.170,6.830,98.400,1.600,17.03,224,0.875,bilinear +dla60_res2net,93.160,6.840,98.400,1.600,20.85,224,0.875,bilinear efficientnet_es,93.140,6.860,98.420,1.580,5.44,224,0.875,bicubic +dla60x,93.120,6.880,98.510,1.490,17.35,224,0.875,bilinear regnetx_032,93.120,6.880,98.390,1.610,15.30,224,0.875,bicubic -dla60x,93.110,6.890,98.510,1.490,17.35,224,0.875,bilinear -pit_xs_224,93.110,6.890,98.330,1.670,10.62,224,0.900,bicubic +pit_xs_224,93.120,6.880,98.330,1.670,10.62,224,0.900,bicubic tf_efficientnetv2_b0,93.110,6.890,98.390,1.610,7.14,224,0.875,bicubic -dla102,93.060,6.940,98.540,1.460,33.27,224,0.875,bilinear +dla102,93.060,6.940,98.550,1.450,33.27,224,0.875,bilinear gluon_resnet50_v1c,93.030,6.970,98.390,1.610,25.58,224,0.875,bicubic -regnety_016,93.030,6.970,98.360,1.640,11.20,224,0.875,bicubic +regnety_016,93.030,6.970,98.350,1.650,11.20,224,0.875,bicubic rexnet_100,93.030,6.970,98.190,1.810,4.80,224,0.875,bicubic -selecsls60,93.020,6.980,98.310,1.690,30.67,224,0.875,bicubic +selecsls60,93.020,6.980,98.300,1.700,30.67,224,0.875,bicubic repvgg_b1g4,92.980,7.020,98.430,1.570,39.97,224,0.875,bilinear -legacy_seresnet50,92.960,7.040,98.180,1.820,28.09,224,0.875,bilinear -hardcorenas_f,92.950,7.050,98.160,1.840,8.20,224,0.875,bilinear +cs3darknet_focus_m,92.970,7.030,98.390,1.610,9.30,288,0.950,bicubic +legacy_seresnet50,92.970,7.030,98.190,1.810,28.09,224,0.875,bilinear +hardcorenas_f,92.960,7.040,98.160,1.840,8.20,224,0.875,bilinear tf_efficientnet_em,92.930,7.070,98.200,1.800,6.90,240,0.882,bicubic -adv_inception_v3,92.890,7.110,98.140,1.860,23.83,299,0.875,bicubic crossvit_9_dagger_240,92.890,7.110,98.250,1.750,8.78,240,0.875,bicubic +adv_inception_v3,92.880,7.120,98.140,1.860,23.83,299,0.875,bicubic res2next50,92.860,7.140,98.190,1.810,24.67,224,0.875,bilinear -resmlp_12_distilled_224,92.830,7.170,98.140,1.860,15.35,224,0.875,bicubic +resmlp_12_distilled_224,92.840,7.160,98.140,1.860,15.35,224,0.875,bicubic tf_efficientnet_cc_b0_8e,92.830,7.170,98.180,1.820,24.01,224,0.875,bicubic gmixer_24_224,92.830,7.170,97.880,2.120,24.72,224,0.875,bicubic seresnext26t_32x4d,92.820,7.180,98.370,1.630,16.81,224,0.875,bicubic tv_resnet101,92.820,7.180,98.250,1.750,44.55,224,0.875,bilinear +gcresnext26ts,92.780,7.220,98.260,1.740,10.48,256,0.900,bicubic efficientnet_b1_pruned,92.770,7.230,98.040,1.960,6.33,240,0.882,bicubic -gcresnext26ts,92.770,7.230,98.260,1.740,10.48,256,0.900,bicubic -densenet201,92.750,7.250,98.230,1.770,20.01,224,0.875,bicubic +tv_resnext50_32x4d,92.750,7.250,98.280,1.720,25.03,224,0.875,bilinear resnet26t,92.750,7.250,98.230,1.770,16.01,256,0.940,bicubic -tv_resnext50_32x4d,92.750,7.250,98.270,1.730,25.03,224,0.875,bilinear +densenet201,92.740,7.260,98.230,1.770,20.01,224,0.875,bicubic res2net50_14w_8s,92.740,7.260,98.180,1.820,25.06,224,0.875,bilinear inception_v3,92.720,7.280,97.970,2.030,23.83,299,0.875,bicubic -seresnext26d_32x4d,92.700,7.300,98.150,1.850,16.81,224,0.875,bicubic -efficientnet_b0,92.690,7.310,98.070,1.930,5.29,224,0.875,bicubic seresnext26ts,92.690,7.310,98.290,1.710,10.39,256,0.900,bicubic +seresnext26d_32x4d,92.690,7.310,98.150,1.850,16.81,224,0.875,bicubic +efficientnet_b0,92.690,7.310,98.070,1.930,5.29,224,0.875,bicubic resnet34d,92.680,7.320,98.310,1.690,21.82,224,0.875,bicubic tf_efficientnet_lite2,92.650,7.350,98.230,1.770,6.09,260,0.890,bicubic legacy_seresnext26_32x4d,92.640,7.360,98.130,1.870,16.79,224,0.875,bicubic -poolformer_s12,92.620,7.380,98.200,1.800,11.92,224,0.900,bicubic +poolformer_s12,92.630,7.370,98.200,1.800,11.92,224,0.900,bicubic tf_efficientnet_lite1,92.620,7.380,98.080,1.920,5.42,240,0.882,bicubic eca_resnext26ts,92.610,7.390,98.260,1.740,10.30,256,0.900,bicubic -tf_efficientnet_cc_b0_4e,92.600,7.400,98.080,1.920,13.31,224,0.875,bicubic -hardcorenas_e,92.580,7.420,98.110,1.890,8.07,224,0.875,bilinear -res2net50_48w_2s,92.550,7.450,98.080,1.920,25.29,224,0.875,bilinear +tf_efficientnet_cc_b0_4e,92.590,7.410,98.080,1.920,13.31,224,0.875,bicubic +hardcorenas_e,92.570,7.430,98.100,1.900,8.07,224,0.875,bilinear gluon_resnet50_v1b,92.540,7.460,98.170,1.830,25.56,224,0.875,bicubic +res2net50_48w_2s,92.540,7.460,98.080,1.920,25.29,224,0.875,bilinear densenet161,92.500,7.500,98.290,1.710,28.68,224,0.875,bicubic xcit_tiny_12_p16_224,92.500,7.500,98.240,1.760,6.72,224,1.000,bicubic res2net50_26w_4s,92.490,7.510,98.060,1.940,25.70,224,0.875,bilinear tinynet_a,92.440,7.560,98.080,1.920,6.19,192,0.875,bicubic -mixnet_m,92.430,7.570,97.870,2.130,5.01,224,0.875,bicubic -convmixer_1024_20_ks9_p14,92.420,7.580,98.270,1.730,24.38,224,0.960,bicubic -hardcorenas_d,92.400,7.600,98.070,1.930,7.50,224,0.875,bilinear +convmixer_1024_20_ks9_p14,92.430,7.570,98.270,1.730,24.38,224,0.960,bicubic +mixnet_m,92.430,7.570,97.860,2.140,5.01,224,0.875,bicubic mobilenetv2_120d,92.400,7.600,98.050,1.950,5.83,224,0.875,bicubic skresnet34,92.390,7.610,98.150,1.850,22.28,224,0.875,bicubic -tf_mixnet_m,92.330,7.670,97.890,2.110,5.01,224,0.875,bicubic +hardcorenas_d,92.390,7.610,98.080,1.920,7.50,224,0.875,bilinear hrnet_w18,92.320,7.680,98.250,1.750,21.30,224,0.875,bilinear +tf_mixnet_m,92.320,7.680,97.890,2.110,5.01,224,0.875,bicubic +selecsls42b,92.280,7.720,98.140,1.860,32.46,224,0.875,bicubic ese_vovnet19b_dw,92.280,7.720,98.090,1.910,6.54,224,0.875,bicubic -selecsls42b,92.280,7.720,98.130,1.870,32.46,224,0.875,bicubic mobilenetv3_large_100_miil,92.270,7.730,97.640,2.360,5.48,224,0.875,bilinear -tf_efficientnet_b0,92.250,7.750,98.000,2.000,5.29,224,0.875,bicubic -dla60,92.230,7.770,98.110,1.890,22.04,224,0.875,bilinear +tf_efficientnet_b0,92.250,7.750,97.990,2.010,5.29,224,0.875,bicubic resmlp_12_224,92.210,7.790,98.160,1.840,15.35,224,0.875,bicubic +dla60,92.210,7.790,98.100,1.900,22.04,224,0.875,bilinear tf_efficientnet_b0_ap,92.200,7.800,98.020,1.980,5.29,224,0.875,bicubic -regnetx_016,92.160,7.840,98.210,1.790,9.19,224,0.875,bicubic -gernet_s,92.140,7.860,98.190,1.810,8.17,224,0.875,bilinear -xcit_nano_12_p8_224_dist,92.100,7.900,98.160,1.840,3.05,224,1.000,bicubic +regnetx_016,92.160,7.840,98.200,1.800,9.19,224,0.875,bicubic +gernet_s,92.140,7.860,98.200,1.800,8.17,224,0.875,bilinear +xcit_nano_12_p8_224_dist,92.100,7.900,98.150,1.850,3.05,224,1.000,bicubic resnet26d,92.070,7.930,97.970,2.030,16.01,224,0.875,bicubic vit_tiny_r_s16_p8_384,92.040,7.960,98.290,1.710,6.36,384,1.000,bicubic -vit_small_patch32_224,92.040,7.960,98.230,1.770,22.88,224,0.900,bicubic +vit_small_patch32_224,92.030,7.970,98.230,1.770,22.88,224,0.900,bicubic dpn68,92.030,7.970,98.050,1.950,12.61,224,0.875,bicubic -hardcorenas_c,92.020,7.980,97.840,2.160,5.52,224,0.875,bilinear +hardcorenas_c,92.030,7.970,97.840,2.160,5.52,224,0.875,bilinear tf_efficientnet_es,91.980,8.020,97.860,2.140,5.44,224,0.875,bicubic -levit_128s,91.950,8.050,98.070,1.930,7.78,224,0.900,bicubic repvgg_a2,91.940,8.060,98.150,1.850,28.21,224,0.875,bilinear -densenet169,91.930,8.070,98.100,1.900,14.15,224,0.875,bicubic +levit_128s,91.930,8.070,98.070,1.930,7.78,224,0.900,bicubic +densenet169,91.920,8.080,98.100,1.900,14.15,224,0.875,bicubic densenetblur121d,91.910,8.090,98.070,1.930,8.00,224,0.875,bicubic -tv_resnet50,91.890,8.110,98.040,1.960,25.56,224,0.875,bilinear +tv_resnet50,91.900,8.100,98.040,1.960,25.56,224,0.875,bilinear resnext26ts,91.870,8.130,97.920,2.080,10.30,256,0.900,bicubic mixer_b16_224,91.870,8.130,97.250,2.750,59.88,224,0.875,bicubic -mobilenetv2_140,91.840,8.160,97.850,2.150,6.11,224,0.875,bicubic -mixnet_s,91.830,8.170,97.690,2.310,4.13,224,0.875,bicubic xcit_nano_12_p16_384_dist,91.830,8.170,98.020,1.980,3.05,384,1.000,bicubic -hardcorenas_b,91.780,8.220,97.780,2.220,5.18,224,0.875,bilinear +mobilenetv2_140,91.830,8.170,97.850,2.150,6.11,224,0.875,bicubic +mixnet_s,91.820,8.180,97.690,2.310,4.13,224,0.875,bicubic vit_tiny_patch16_224,91.770,8.230,98.040,1.960,5.72,224,0.900,bicubic +mobilevitv2_075,91.760,8.240,97.860,2.140,2.87,256,0.888,bicubic +hardcorenas_b,91.760,8.240,97.780,2.220,5.18,224,0.875,bilinear regnety_008,91.720,8.280,98.180,1.820,6.26,224,0.875,bicubic resnest14d,91.720,8.280,97.870,2.130,10.61,224,0.875,bilinear densenet121,91.580,8.420,98.030,1.970,7.98,224,0.875,bicubic -tf_mixnet_s,91.510,8.490,97.620,2.380,4.13,224,0.875,bicubic -repvgg_b0,91.430,8.570,97.990,2.010,15.82,224,0.875,bilinear -regnety_006,91.380,8.620,97.710,2.290,6.06,224,0.875,bicubic +tf_mixnet_s,91.510,8.490,97.610,2.390,4.13,224,0.875,bicubic +repvgg_b0,91.400,8.600,97.990,2.010,15.82,224,0.875,bilinear +regnety_006,91.370,8.630,97.710,2.290,6.06,224,0.875,bicubic hardcorenas_a,91.350,8.650,97.860,2.140,5.26,224,0.875,bilinear -mobilenetv3_large_100,91.330,8.670,97.710,2.290,5.48,224,0.875,bicubic -semnasnet_100,91.270,8.730,97.560,2.440,3.89,224,0.875,bicubic -tf_mobilenetv3_large_100,91.240,8.760,97.660,2.340,5.48,224,0.875,bilinear +mobilenetv3_large_100,91.330,8.670,97.720,2.280,5.48,224,0.875,bicubic +semnasnet_100,91.280,8.720,97.560,2.440,3.89,224,0.875,bicubic +tf_mobilenetv3_large_100,91.220,8.780,97.660,2.340,5.48,224,0.875,bilinear mobilenetv3_rw,91.210,8.790,97.660,2.340,5.48,224,0.875,bicubic hrnet_w18_small_v2,91.190,8.810,97.900,2.100,15.60,224,0.875,bilinear efficientnet_es_pruned,91.180,8.820,97.750,2.250,5.44,224,0.875,bicubic resnet34,91.130,8.870,97.620,2.380,21.80,224,0.875,bilinear -efficientnet_lite0,91.120,8.880,97.620,2.380,4.65,224,0.875,bicubic resnet26,91.120,8.880,97.750,2.250,16.00,224,0.875,bicubic +efficientnet_lite0,91.110,8.890,97.630,2.370,4.65,224,0.875,bicubic +edgenext_x_small,91.090,8.910,97.550,2.450,2.34,256,0.900,bicubic regnetx_008,91.050,8.950,97.710,2.290,7.26,224,0.875,bicubic -tf_efficientnet_lite0,91.050,8.950,97.590,2.410,4.65,224,0.875,bicubic +tf_efficientnet_lite0,91.040,8.960,97.590,2.410,4.65,224,0.875,bicubic xcit_nano_12_p8_224,91.020,8.980,97.790,2.210,3.05,224,1.000,bicubic gluon_resnet34_v1b,90.960,9.040,97.640,2.360,21.80,224,0.875,bicubic mobilenetv2_110d,90.960,9.040,97.560,2.440,4.52,224,0.875,bicubic -tinynet_b,90.930,9.070,97.670,2.330,3.73,188,0.875,bicubic -legacy_seresnet34,90.900,9.100,97.580,2.420,21.96,224,0.875,bilinear +tinynet_b,90.920,9.080,97.670,2.330,3.73,188,0.875,bicubic pit_ti_distilled_224,90.900,9.100,97.720,2.280,5.10,224,0.900,bicubic +legacy_seresnet34,90.900,9.100,97.580,2.420,21.96,224,0.875,bilinear tv_densenet121,90.890,9.110,97.710,2.290,7.98,224,0.875,bicubic -mobilevit_xs,90.840,9.160,97.920,2.080,2.32,256,0.900,bicubic -dla34,90.770,9.230,97.660,2.340,15.74,224,0.875,bilinear +mobilevit_xs,90.820,9.180,97.920,2.080,2.32,256,0.900,bicubic +dla34,90.780,9.220,97.660,2.340,15.74,224,0.875,bilinear deit_tiny_distilled_patch16_224,90.710,9.290,97.570,2.430,5.91,224,0.900,bicubic fbnetc_100,90.710,9.290,97.210,2.790,5.57,224,0.875,bilinear swsl_resnet18,90.690,9.310,97.700,2.300,11.69,224,0.875,bilinear -crossvit_9_240,90.650,9.350,97.740,2.260,8.55,240,0.875,bicubic -convit_tiny,90.650,9.350,97.740,2.260,5.71,224,0.875,bicubic +convit_tiny,90.640,9.360,97.740,2.260,5.71,224,0.875,bicubic +crossvit_9_240,90.630,9.370,97.740,2.260,8.55,240,0.875,bicubic +regnety_004,90.510,9.490,97.540,2.460,4.34,224,0.875,bicubic mnasnet_100,90.510,9.490,97.470,2.530,4.38,224,0.875,bicubic -regnety_004,90.490,9.510,97.540,2.460,4.34,224,0.875,bicubic -regnetx_006,90.350,9.650,97.440,2.560,6.20,224,0.875,bicubic -spnasnet_100,90.350,9.650,97.190,2.810,4.42,224,0.875,bilinear +regnetx_006,90.360,9.640,97.430,2.570,6.20,224,0.875,bicubic +spnasnet_100,90.340,9.660,97.190,2.810,4.42,224,0.875,bilinear crossvit_tiny_240,90.240,9.760,97.590,2.410,7.01,240,0.875,bicubic -ssl_resnet18,90.220,9.780,97.550,2.450,11.69,224,0.875,bilinear +ssl_resnet18,90.210,9.790,97.550,2.450,11.69,224,0.875,bilinear vgg16_bn,90.090,9.910,97.370,2.630,138.37,224,0.875,bilinear vgg19_bn,90.080,9.920,97.580,2.420,143.68,224,0.875,bilinear -semnasnet_075,90.070,9.930,97.430,2.570,2.91,224,0.875,bicubic +semnasnet_075,90.060,9.940,97.430,2.570,2.91,224,0.875,bicubic ghostnet_100,90.030,9.970,97.370,2.630,5.18,224,0.875,bilinear -pit_ti_224,89.950,10.050,97.450,2.550,4.85,224,0.900,bicubic +pit_ti_224,89.950,10.050,97.440,2.560,4.85,224,0.900,bicubic tv_resnet34,89.930,10.070,97.340,2.660,21.80,224,0.875,bilinear vit_base_patch32_224_sam,89.750,10.250,97.000,3.000,88.22,224,0.900,bicubic -deit_tiny_patch16_224,89.680,10.320,97.450,2.550,5.72,224,0.900,bicubic +xcit_nano_12_p16_224_dist,89.690,10.310,97.100,2.900,3.05,224,1.000,bicubic tf_mobilenetv3_large_075,89.680,10.320,97.210,2.790,3.99,224,0.875,bilinear -xcit_nano_12_p16_224_dist,89.680,10.320,97.090,2.910,3.05,224,1.000,bicubic -skresnet18,89.660,10.340,97.230,2.770,11.96,224,0.875,bicubic +deit_tiny_patch16_224,89.660,10.340,97.450,2.550,5.72,224,0.900,bicubic +skresnet18,89.660,10.340,97.240,2.760,11.96,224,0.875,bicubic mobilenetv2_100,89.610,10.390,97.150,2.850,3.50,224,0.875,bicubic -resnet18d,89.270,10.730,97.140,2.860,11.71,224,0.875,bicubic +resnet18d,89.280,10.720,97.140,2.860,11.71,224,0.875,bicubic vit_tiny_r_s16_p8_224,89.180,10.820,97.230,2.770,6.34,224,0.900,bicubic -hrnet_w18_small,89.050,10.950,97.110,2.890,13.19,224,0.875,bilinear vgg19,89.040,10.960,96.870,3.130,143.67,224,0.875,bilinear -tf_mobilenetv3_large_minimal_100,88.960,11.040,96.860,3.140,3.92,224,0.875,bilinear +resnet14t,89.040,10.960,96.600,3.400,10.08,224,0.950,bilinear +hrnet_w18_small,89.030,10.970,97.110,2.890,13.19,224,0.875,bilinear +tf_mobilenetv3_large_minimal_100,88.970,11.030,96.850,3.150,3.92,224,0.875,bilinear regnetx_004,88.900,11.100,97.120,2.880,5.16,224,0.875,bicubic legacy_seresnet18,88.880,11.120,96.980,3.020,11.78,224,0.875,bicubic -lcnet_100,88.800,11.200,96.730,3.270,2.95,224,0.875,bicubic +lcnet_100,88.790,11.210,96.730,3.270,2.95,224,0.875,bicubic vgg13_bn,88.760,11.240,96.970,3.030,133.05,224,0.875,bilinear xcit_nano_12_p16_224,88.610,11.390,96.790,3.210,3.05,224,1.000,bicubic vgg16,88.550,11.450,96.790,3.210,138.36,224,0.875,bilinear gluon_resnet18_v1b,88.400,11.600,96.680,3.320,11.69,224,0.875,bicubic -tinynet_c,87.770,12.230,96.370,3.630,2.46,184,0.875,bicubic +edgenext_xx_small,88.350,11.650,96.520,3.480,1.33,256,0.900,bicubic +mobilevitv2_050,88.230,11.770,96.990,3.010,1.37,256,0.888,bicubic +tinynet_c,87.780,12.220,96.370,3.630,2.46,184,0.875,bicubic vgg11_bn,87.500,12.500,96.820,3.180,132.87,224,0.875,bilinear resnet18,87.390,12.610,96.290,3.710,11.69,224,0.875,bilinear regnety_002,87.380,12.620,96.590,3.410,3.16,224,0.875,bicubic mobilevit_xxs,87.190,12.810,96.100,3.900,1.27,256,0.900,bicubic -mixer_l16_224,87.150,12.850,93.510,6.490,208.20,224,0.875,bicubic +mixer_l16_224,87.140,12.860,93.520,6.480,208.20,224,0.875,bicubic vgg13,87.050,12.950,96.320,3.680,133.05,224,0.875,bilinear vgg11,86.550,13.450,96.280,3.720,132.86,224,0.875,bilinear -dla60x_c,86.290,13.710,96.160,3.840,1.32,224,0.875,bilinear -regnetx_002,86.190,13.810,95.980,4.020,2.68,224,0.875,bicubic -lcnet_075,85.990,14.010,95.680,4.320,2.36,224,0.875,bicubic -mobilenetv3_small_100,85.220,14.780,95.620,4.380,2.54,224,0.875,bicubic -tf_mobilenetv3_small_100,85.210,14.790,95.770,4.230,2.54,224,0.875,bilinear -tinynet_d,84.750,15.250,95.180,4.820,2.34,152,0.875,bicubic +dla60x_c,86.270,13.730,96.170,3.830,1.32,224,0.875,bilinear +resnet10t,86.210,13.790,95.660,4.340,5.44,224,0.950,bilinear +regnetx_002,86.200,13.800,95.980,4.020,2.68,224,0.875,bicubic +lcnet_075,85.990,14.010,95.690,4.310,2.36,224,0.875,bicubic +mobilenetv3_small_100,85.220,14.780,95.630,4.370,2.54,224,0.875,bicubic +tf_mobilenetv3_small_100,85.190,14.810,95.770,4.230,2.54,224,0.875,bilinear +tinynet_d,84.760,15.240,95.180,4.820,2.34,152,0.875,bicubic mnasnet_small,84.440,15.560,95.180,4.820,2.03,224,0.875,bicubic -dla46x_c,84.250,15.750,95.270,4.730,1.07,224,0.875,bilinear -mobilenetv2_050,83.890,16.110,94.710,5.290,1.97,224,0.875,bicubic -dla46_c,83.650,16.350,94.920,5.080,1.30,224,0.875,bilinear -tf_mobilenetv3_small_075,83.510,16.490,94.800,5.200,2.04,224,0.875,bilinear -mobilenetv3_small_075,83.040,16.960,94.090,5.910,2.04,224,0.875,bicubic -lcnet_050,81.780,18.220,93.710,6.290,1.88,224,0.875,bicubic -tf_mobilenetv3_small_minimal_100,81.380,18.620,93.670,6.330,2.04,224,0.875,bilinear +dla46x_c,84.250,15.750,95.260,4.740,1.07,224,0.875,bilinear +mobilenetv2_050,83.890,16.110,94.720,5.280,1.97,224,0.875,bicubic +dla46_c,83.640,16.360,94.920,5.080,1.30,224,0.875,bilinear +tf_mobilenetv3_small_075,83.520,16.480,94.800,5.200,2.04,224,0.875,bilinear +mobilenetv3_small_075,83.040,16.960,94.100,5.900,2.04,224,0.875,bicubic +lcnet_050,81.780,18.220,93.720,6.280,1.88,224,0.875,bicubic +tf_mobilenetv3_small_minimal_100,81.400,18.600,93.680,6.320,2.04,224,0.875,bilinear tinynet_e,78.900,21.100,92.560,7.440,2.04,106,0.875,bicubic mobilenetv3_small_050,76.990,23.010,91.300,8.700,1.59,224,0.875,bicubic diff --git a/results/results-imagenet-a.csv b/results/results-imagenet-a.csv index e6fd3f72..4e306fba 100644 --- a/results/results-imagenet-a.csv +++ b/results/results-imagenet-a.csv @@ -1,591 +1,669 @@ -model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation,top1_diff,top5_diff,rank_diff +model,top1,top1_err,top5,top5_err,param_count,img_size,crop_pct,interpolation,top1_diff,top5_diff,rank_diff tf_efficientnet_l2_ns,84.760,15.240,96.147,3.853,480.31,800,0.960,bicubic,-13.790,-3.673,+1 tf_efficientnet_l2_ns_475,83.400,16.600,95.453,4.547,480.31,475,0.936,bicubic,-15.100,-4.377,+2 -beit_large_patch16_512,81.627,18.373,94.880,5.120,305.67,512,1.000,bicubic,-16.933,-4.960,-2 -beit_large_patch16_384,79.120,20.880,94.280,5.720,305.00,384,1.000,bicubic,-19.400,-5.540,-1 -vit_large_patch16_384,71.240,28.760,89.853,10.147,304.72,384,1.000,bicubic,-26.980,-9.947,+2 -convnext_xlarge_384_in22ft1k,70.787,29.213,90.400,9.600,350.20,384,1.000,bicubic,-27.563,-9.400,-1 -volo_d5_512,69.653,30.347,90.413,9.587,296.09,512,1.150,bicubic,-28.117,-9.257,+11 -swin_large_patch4_window12_384,69.600,30.400,89.560,10.440,196.74,384,1.000,bicubic,-28.440,-10.130,+1 -beit_large_patch16_224,68.507,31.493,89.560,10.440,304.43,224,0.900,bicubic,-29.673,-10.200,-1 -volo_d5_448,68.107,31.893,89.707,10.293,295.91,448,1.150,bicubic,-29.653,-9.913,+9 -convnext_large_384_in22ft1k,67.947,32.053,89.200,10.800,197.77,384,1.000,bicubic,-30.273,-10.530,-5 -tf_efficientnet_b7_ns,67.040,32.960,88.667,11.333,66.35,600,0.949,bicubic,-30.870,-11.053,0 -tf_efficientnetv2_xl_in21ft1k,67.000,33.000,86.867,13.133,208.12,512,1.000,bicubic,-30.650,-12.623,+10 -volo_d4_448,66.653,33.347,89.000,11.000,193.41,448,1.150,bicubic,-31.017,-10.610,+7 +beit_large_patch16_512,81.653,18.347,94.880,5.120,305.67,512,1.000,bicubic,-16.907,-4.960,-2 +deit3_large_patch16_384_in21ft1k,79.213,20.787,93.627,6.373,304.76,384,1.000,bicubic,-19.247,-6.133,+1 +beit_large_patch16_384,79.120,20.880,94.280,5.720,305.00,384,1.000,bicubic,-19.400,-5.540,-2 +swinv2_large_window12to24_192to384_22kft1k,73.867,26.133,91.747,8.253,196.74,384,1.000,bicubic,-24.283,-7.943,+6 +deit3_base_patch16_384_in21ft1k,71.280,28.720,89.947,10.053,86.88,384,1.000,bicubic,-26.550,-9.733,+16 +swinv2_base_window12to24_192to384_22kft1k,71.267,28.733,91.280,8.720,87.92,384,1.000,bicubic,-26.873,-8.500,+5 +vit_large_patch16_384,71.227,28.773,89.853,10.147,304.72,384,1.000,bicubic,-26.993,-9.947,-2 +convnext_xlarge_384_in22ft1k,70.787,29.213,90.400,9.600,350.20,384,1.000,bicubic,-27.563,-9.400,-4 +deit3_huge_patch14_224_in21ft1k,70.227,29.773,90.720,9.280,632.13,224,1.000,bicubic,-27.943,-9.010,0 +volo_d5_512,69.653,30.347,90.413,9.587,296.09,512,1.150,bicubic,-28.117,-9.257,+13 +swin_large_patch4_window12_384,69.613,30.387,89.573,10.427,196.74,384,1.000,bicubic,-28.427,-10.117,+1 +deit3_large_patch16_224_in21ft1k,68.707,31.293,90.013,9.987,304.37,224,1.000,bicubic,-29.463,-9.747,-4 +beit_large_patch16_224,68.507,31.493,89.573,10.427,304.43,224,0.900,bicubic,-29.673,-10.187,-6 +volo_d5_448,68.107,31.893,89.707,10.293,295.91,448,1.150,bicubic,-29.653,-9.913,+10 +convnext_large_384_in22ft1k,67.947,32.053,89.200,10.800,197.77,384,1.000,bicubic,-30.273,-10.530,-9 +swinv2_large_window12to16_192to256_22kft1k,67.280,32.720,88.013,11.987,196.74,256,0.900,bicubic,-30.580,-11.637,+2 +tf_efficientnet_b7_ns,67.080,32.920,88.640,11.360,66.35,600,0.949,bicubic,-30.840,-11.080,-3 +tf_efficientnetv2_xl_in21ft1k,67.000,33.000,86.867,13.133,208.12,512,1.000,bicubic,-30.660,-12.623,+9 +volo_d4_448,66.680,33.320,88.987,11.013,193.41,448,1.150,bicubic,-30.990,-10.623,+7 tf_efficientnetv2_l_in21ft1k,66.320,33.680,87.840,12.160,118.52,480,1.000,bicubic,-31.380,-11.830,+5 -beit_base_patch16_384,65.880,34.120,88.507,11.493,86.74,384,1.000,bicubic,-31.930,-11.193,+1 -volo_d3_448,65.440,34.560,87.560,12.440,86.63,448,1.000,bicubic,-32.110,-11.990,+13 -convnext_base_384_in22ft1k,65.000,35.000,87.867,12.133,88.59,384,1.000,bicubic,-32.950,-11.783,-8 -swin_base_patch4_window12_384,64.467,35.533,87.507,12.493,87.90,384,1.000,bicubic,-33.423,-12.203,-6 -vit_base_patch16_384,63.693,36.307,86.707,13.293,86.86,384,1.000,bicubic,-34.147,-12.963,-5 -convnext_xlarge_in22ft1k,62.613,37.387,86.000,14.000,350.20,224,0.875,bicubic,-35.307,-13.680,-10 -cait_m48_448,62.333,37.667,86.440,13.560,356.46,448,1.000,bicubic,-35.147,-13.090,+15 +beit_base_patch16_384,65.880,34.120,88.507,11.493,86.74,384,1.000,bicubic,-31.940,-11.193,+1 +volo_d3_448,65.427,34.573,87.560,12.440,86.63,448,1.000,bicubic,-32.123,-11.990,+14 +convnext_base_384_in22ft1k,65.000,35.000,87.867,12.133,88.59,384,1.000,bicubic,-32.950,-11.783,-10 +swin_base_patch4_window12_384,64.467,35.533,87.493,12.507,87.90,384,1.000,bicubic,-33.423,-12.217,-8 +vit_base_patch16_384,63.693,36.307,86.707,13.293,86.86,384,1.000,bicubic,-34.147,-12.963,-6 +swinv2_base_window12to16_192to256_22kft1k,63.227,36.773,87.493,12.507,87.92,256,0.900,bicubic,-34.423,-12.227,+2 +convnext_xlarge_in22ft1k,62.627,37.373,86.000,14.000,350.20,224,0.875,bicubic,-35.293,-13.680,-12 +cait_m48_448,62.347,37.653,86.453,13.547,356.46,448,1.000,bicubic,-35.133,-13.097,+15 tf_efficientnet_b6_ns,62.267,37.733,85.173,14.827,43.04,528,0.942,bicubic,-35.363,-14.407,+2 -vit_large_r50_s32_384,61.507,38.493,83.973,16.027,329.09,384,1.000,bicubic,-36.353,-15.697,-10 -tf_efficientnetv2_m_in21ft1k,61.373,38.627,85.413,14.587,54.14,480,1.000,bicubic,-36.107,-14.137,+11 -ig_resnext101_32x48d,61.053,38.947,83.320,16.680,828.41,224,0.875,bilinear,-36.567,-16.390,0 -swin_large_patch4_window7_224,60.907,39.093,85.867,14.133,196.53,224,0.900,bicubic,-36.743,-13.713,-5 +vit_large_r50_s32_384,61.493,38.507,83.960,16.040,329.09,384,1.000,bicubic,-36.367,-15.710,-13 +tf_efficientnetv2_m_in21ft1k,61.387,38.613,85.413,14.587,54.14,480,1.000,bicubic,-36.093,-14.117,+13 +ig_resnext101_32x48d,61.013,38.987,83.333,16.667,828.41,224,0.875,bilinear,-36.607,-16.367,0 +swin_large_patch4_window7_224,60.907,39.093,85.867,14.133,196.53,224,0.900,bicubic,-36.743,-13.713,-4 resnetv2_152x4_bitm,60.787,39.213,83.560,16.440,936.53,480,1.000,bilinear,-36.703,-16.050,+7 -tf_efficientnet_b5_ns,60.307,39.693,84.467,15.533,30.39,456,0.934,bicubic,-37.193,-15.163,+5 -xcit_large_24_p8_384_dist,59.880,40.120,85.480,14.520,188.93,384,1.000,bicubic,-37.640,-14.060,+2 -convnext_large_in22ft1k,59.773,40.227,84.040,15.960,197.77,224,0.875,bicubic,-38.057,-15.650,-15 -dm_nfnet_f6,59.173,40.827,82.333,17.667,438.36,576,0.956,bicubic,-38.427,-17.217,-5 -vit_base_patch8_224,58.920,41.080,82.733,17.267,86.58,224,0.900,bicubic,-38.660,-16.937,-4 -volo_d2_384,58.600,41.400,84.253,15.747,58.87,384,1.000,bicubic,-38.710,-15.347,+10 -dm_nfnet_f5,58.560,41.440,82.773,17.227,377.21,544,0.954,bicubic,-38.980,-16.797,-4 -dm_nfnet_f4,58.107,41.893,81.973,18.027,316.07,512,0.951,bicubic,-39.473,-17.537,-8 -ig_resnext101_32x32d,58.053,41.947,80.600,19.400,468.53,224,0.875,bilinear,-39.317,-19.080,+4 -cait_m36_384,57.813,42.187,84.813,15.187,271.22,384,1.000,bicubic,-39.587,-14.697,+1 -volo_d5_224,57.120,42.880,82.720,17.280,295.46,224,0.960,bicubic,-40.270,-16.850,+1 -xcit_medium_24_p8_384_dist,56.680,43.320,83.400,16.600,84.32,384,1.000,bicubic,-40.610,-16.110,+6 -dm_nfnet_f3,55.827,44.173,80.933,19.067,254.92,416,0.940,bicubic,-41.523,-18.627,+1 -vit_large_patch16_224,55.627,44.373,80.080,19.920,304.33,224,0.900,bicubic,-42.013,-19.510,-18 -convnext_base_in22ft1k,54.640,45.360,82.173,17.827,88.59,224,0.875,bicubic,-42.830,-17.427,-5 -vit_base_r50_s16_384,54.627,45.373,81.227,18.773,98.95,384,1.000,bicubic,-42.553,-18.333,+12 -cait_s36_384,54.413,45.587,81.360,18.640,68.37,384,1.000,bicubic,-42.917,-18.170,-2 -volo_d1_384,54.333,45.667,80.973,19.027,26.78,384,1.000,bicubic,-42.587,-18.547,+31 -xcit_small_24_p8_384_dist,54.253,45.747,81.533,18.467,47.63,384,1.000,bicubic,-42.987,-18.077,+3 -resnetv2_101x3_bitm,54.027,45.973,81.027,18.973,387.93,448,1.000,bilinear,-42.963,-18.463,+23 +deit3_large_patch16_384,60.507,39.493,85.707,14.293,304.76,384,1.000,bicubic,-36.913,-13.913,+12 +tf_efficientnet_b5_ns,60.293,39.707,84.480,15.520,30.39,456,0.934,bicubic,-37.207,-15.150,+4 +xcit_large_24_p8_384_dist,59.880,40.120,85.480,14.520,188.93,384,1.000,bicubic,-37.640,-14.060,+1 +convnext_large_in22ft1k,59.773,40.227,84.040,15.960,197.77,224,0.875,bicubic,-38.057,-15.650,-18 +dm_nfnet_f6,59.173,40.827,82.333,17.667,438.36,576,0.956,bicubic,-38.427,-17.217,-6 +vit_base_patch8_224,58.920,41.080,82.733,17.267,86.58,224,0.900,bicubic,-38.660,-16.937,-6 +volo_d2_384,58.600,41.400,84.253,15.747,58.87,384,1.000,bicubic,-38.710,-15.347,+12 +dm_nfnet_f5,58.560,41.440,82.773,17.227,377.21,544,0.954,bicubic,-38.980,-16.797,-5 +dm_nfnet_f4,58.133,41.867,81.973,18.027,316.07,512,0.951,bicubic,-39.447,-17.537,-8 +ig_resnext101_32x32d,58.040,41.960,80.613,19.387,468.53,224,0.875,bilinear,-39.330,-19.067,+6 +cait_m36_384,57.813,42.187,84.827,15.173,271.22,384,1.000,bicubic,-39.587,-14.683,+3 +deit3_base_patch16_224_in21ft1k,57.253,42.747,83.520,16.480,86.59,224,1.000,bicubic,-40.237,-16.080,-4 +volo_d5_224,57.120,42.880,82.720,17.280,295.46,224,0.960,bicubic,-40.270,-16.850,+2 +deit3_small_patch16_384_in21ft1k,57.067,42.933,83.080,16.920,22.21,384,1.000,bicubic,-40.063,-16.420,+19 +xcit_medium_24_p8_384_dist,56.693,43.307,83.400,16.600,84.32,384,1.000,bicubic,-40.597,-16.110,+6 +convnext_small_384_in22ft1k,56.187,43.813,83.760,16.240,50.22,384,1.000,bicubic,-41.273,-15.820,-4 +dm_nfnet_f3,55.827,44.173,80.947,19.053,254.92,416,0.940,bicubic,-41.523,-18.613,0 +vit_large_patch16_224,55.627,44.373,80.080,19.920,304.33,224,0.900,bicubic,-42.013,-19.510,-22 +convnext_base_in22ft1k,54.627,45.373,82.173,17.827,88.59,224,0.875,bicubic,-42.843,-17.427,-8 +vit_base_r50_s16_384,54.627,45.373,81.213,18.787,98.95,384,1.000,bicubic,-42.553,-18.347,+11 +cait_s36_384,54.387,45.613,81.360,18.640,68.37,384,1.000,bicubic,-42.943,-18.170,-3 +volo_d1_384,54.333,45.667,80.973,19.027,26.78,384,1.000,bicubic,-42.577,-18.547,+35 +deit3_huge_patch14_224,54.320,45.680,82.093,17.907,632.13,224,0.900,bicubic,-42.570,-17.387,+37 +xcit_small_24_p8_384_dist,54.267,45.733,81.533,18.467,47.63,384,1.000,bicubic,-42.973,-18.077,+1 +resnetv2_101x3_bitm,54.027,45.973,81.040,18.960,387.93,448,1.000,bilinear,-42.963,-18.450,+23 resnetv2_152x2_bitm,54.013,45.987,82.013,17.987,236.34,448,1.000,bilinear,-42.997,-17.577,+19 -tf_efficientnetv2_l,53.173,46.827,79.147,20.853,118.52,480,1.000,bicubic,-44.107,-20.403,-3 -ig_resnext101_32x16d,53.080,46.920,76.933,23.067,194.03,224,0.875,bilinear,-43.730,-22.667,+32 -volo_d4_224,52.933,47.067,80.453,19.547,192.96,224,0.960,bicubic,-44.367,-19.067,-7 -xcit_large_24_p16_384_dist,52.827,47.173,81.827,18.173,189.10,384,1.000,bicubic,-44.693,-17.653,-20 -swin_base_patch4_window7_224,51.427,48.573,79.973,20.027,87.77,224,0.900,bicubic,-45.823,-19.557,-5 -swsl_resnext101_32x8d,51.227,48.773,78.240,21.760,88.79,224,0.875,bilinear,-45.973,-21.300,-1 -tf_efficientnet_b4_ns,51.227,48.773,79.187,20.813,19.34,380,0.922,bicubic,-45.723,-20.393,+18 -resnetv2_152x2_bit_teacher_384,51.187,48.813,78.480,21.520,236.34,384,1.000,bicubic,-45.643,-20.970,+25 -beit_base_patch16_224,50.693,49.307,79.693,20.307,86.53,224,0.900,bicubic,-46.397,-19.917,+2 -xcit_small_12_p8_384_dist,50.573,49.427,79.587,20.413,26.21,384,1.000,bicubic,-46.657,-19.893,-8 -volo_d3_224,50.253,49.747,78.173,21.827,86.33,224,0.960,bicubic,-46.837,-21.297,+2 -cait_s24_384,49.733,50.267,78.760,21.240,47.06,384,1.000,bicubic,-47.347,-20.860,+4 -deit_base_distilled_patch16_384,49.333,50.667,79.253,20.747,87.63,384,1.000,bicubic,-47.627,-20.227,+11 -xcit_medium_24_p16_384_dist,49.333,50.667,79.827,20.173,84.40,384,1.000,bicubic,-47.947,-19.633,-15 -tf_efficientnet_b8,48.947,51.053,77.240,22.760,87.41,672,0.954,bicubic,-48.253,-22.330,-11 -dm_nfnet_f2,48.920,51.080,77.147,22.853,193.78,352,0.920,bicubic,-48.110,-22.293,+2 -tf_efficientnetv2_s_in21ft1k,48.507,51.493,77.907,22.093,21.46,384,1.000,bicubic,-48.223,-21.513,+24 -resnest269e,48.200,51.800,74.333,25.667,110.93,416,0.928,bicubic,-48.320,-25.017,+50 -xcit_large_24_p8_224_dist,48.120,51.880,79.107,20.893,188.93,224,1.000,bicubic,-48.950,-20.313,-2 -regnetz_e8,47.827,52.173,76.200,23.800,57.70,320,1.000,bicubic,-49.373,-23.300,-14 -resnetv2_50x3_bitm,47.280,52.720,77.333,22.667,217.32,448,1.000,bilinear,-49.430,-22.137,+22 -xcit_large_24_p8_224,47.160,52.840,74.400,25.600,188.93,224,1.000,bicubic,-49.250,-24.580,+53 -xcit_small_24_p16_384_dist,46.960,53.040,77.173,22.827,47.67,384,1.000,bicubic,-50.160,-22.287,-14 -tf_efficientnet_b8_ap,46.893,53.107,76.507,23.493,87.41,672,0.954,bicubic,-50.217,-23.153,-14 -efficientnetv2_rw_m,46.280,53.720,75.707,24.293,53.24,416,1.000,bicubic,-50.700,-23.823,-2 -swsl_resnext101_32x16d,46.120,53.880,72.253,27.747,194.03,224,0.875,bilinear,-50.480,-27.277,+34 -volo_d2_224,46.080,53.920,75.267,24.733,58.68,224,0.960,bicubic,-50.920,-24.123,-6 -vit_small_patch16_384,45.907,54.093,76.707,23.293,22.20,384,1.000,bicubic,-50.793,-22.773,+20 -ecaresnet269d,45.880,54.120,75.133,24.867,102.09,352,1.000,bicubic,-51.200,-24.337,-14 -vit_small_r26_s32_384,45.747,54.253,76.040,23.960,36.47,384,1.000,bicubic,-50.933,-23.540,+21 -tf_efficientnetv2_m,45.533,54.467,74.547,25.453,54.14,480,1.000,bicubic,-51.607,-24.863,-23 -tf_efficientnet_b7_ap,45.373,54.627,74.200,25.800,66.35,600,0.949,bicubic,-51.827,-25.300,-29 -dm_nfnet_f1,45.307,54.693,74.107,25.893,132.63,320,0.910,bicubic,-51.603,-25.303,-3 -ig_resnext101_32x8d,45.293,54.707,70.853,29.147,88.79,224,0.875,bilinear,-51.017,-28.577,+53 -xcit_medium_24_p8_224_dist,45.213,54.787,76.693,23.307,84.32,224,1.000,bicubic,-51.707,-22.697,-6 -eca_nfnet_l2,44.960,55.040,75.893,24.107,56.72,384,1.000,bicubic,-52.130,-23.617,-24 -crossvit_18_dagger_408,44.280,55.720,73.813,26.187,44.61,408,1.000,bicubic,-52.250,-25.447,+29 -resnest200e,44.147,55.853,73.467,26.533,70.20,320,0.909,bicubic,-52.463,-25.883,+20 -cait_xs24_384,43.947,56.053,75.160,24.840,26.67,384,1.000,bicubic,-52.603,-24.260,+24 -resnetrs200,43.747,56.253,72.813,27.187,93.21,320,1.000,bicubic,-52.953,-26.557,+7 -tresnet_xl_448,43.467,56.533,72.440,27.560,78.44,448,0.875,bilinear,-52.503,-26.750,+75 -xcit_small_12_p16_384_dist,43.280,56.720,73.867,26.133,26.25,384,1.000,bicubic,-53.650,-25.533,-16 -vit_base_patch16_224,43.253,56.747,72.920,27.080,86.57,224,0.900,bicubic,-53.627,-26.610,-12 -resnetrs420,43.147,56.853,70.440,29.560,191.89,416,1.000,bicubic,-53.773,-29.020,-17 -xcit_medium_24_p8_224,43.093,56.907,70.347,29.653,84.32,224,1.000,bicubic,-53.017,-28.543,+61 -tf_efficientnet_b7,42.960,57.040,73.120,26.880,66.35,600,0.949,bicubic,-54.050,-26.400,-26 -xcit_tiny_24_p8_384_dist,42.467,57.533,72.867,27.133,12.11,384,1.000,bicubic,-54.073,-26.493,+17 -crossvit_15_dagger_408,41.907,58.093,72.053,27.947,28.50,408,1.000,bicubic,-54.483,-27.107,+29 -xcit_small_24_p8_224_dist,41.893,58.107,73.693,26.307,47.63,224,1.000,bicubic,-54.977,-25.787,-17 -xcit_small_24_p8_224,41.733,58.267,71.013,28.987,47.63,224,1.000,bicubic,-54.667,-28.137,+26 -vit_large_r50_s32_224,41.627,58.373,70.240,29.760,328.99,224,0.900,bicubic,-55.163,-29.110,-15 -swsl_resnext101_32x4d,41.547,58.453,71.760,28.240,44.18,224,0.875,bilinear,-54.883,-27.710,+21 -convnext_large,41.373,58.627,73.293,26.707,197.77,224,0.875,bicubic,-55.387,-26.007,-14 -tf_efficientnet_b6_ap,40.800,59.200,71.627,28.373,43.04,528,0.942,bicubic,-56.280,-27.803,-40 -resmlp_big_24_224_in22ft1k,40.373,59.627,74.773,25.227,129.14,224,0.875,bicubic,-56.247,-24.737,+1 -tresnet_l_448,40.213,59.787,69.893,30.107,55.99,448,0.875,bilinear,-55.647,-29.317,+69 -deit_base_patch16_384,40.187,59.813,70.760,29.240,86.86,384,1.000,bicubic,-55.963,-28.380,+42 -regnetz_d8_evos,40.093,59.907,72.187,27.813,23.46,320,0.950,bicubic,-56.517,-27.253,-1 -regnetz_040h,39.987,60.013,71.333,28.667,28.94,320,1.000,bicubic,-56.723,-28.167,-15 -resnetrs350,39.947,60.053,68.920,31.080,163.96,384,1.000,bicubic,-56.813,-30.450,-20 -regnetz_d8,39.933,60.067,71.640,28.360,23.37,320,1.000,bicubic,-56.687,-27.810,-6 -swin_s3_base_224,39.800,60.200,70.453,29.547,71.13,224,0.900,bicubic,-56.450,-28.687,+28 -seresnext101_32x8d,39.547,60.453,69.467,30.533,93.57,288,1.000,bicubic,-57.223,-29.883,-25 -volo_d1_224,38.960,61.040,70.267,29.733,26.63,224,0.960,bicubic,-57.370,-29.043,+22 -resnetv2_101x1_bitm,38.947,61.053,71.040,28.960,44.54,448,1.000,bilinear,-57.153,-28.240,+43 -vit_large_patch32_384,38.947,61.053,68.933,31.067,306.63,384,1.000,bicubic,-56.883,-30.217,+62 -regnetz_040,38.747,61.253,70.413,29.587,27.12,320,1.000,bicubic,-57.963,-29.137,-22 -xcit_small_12_p8_224_dist,38.213,61.787,71.293,28.707,26.21,224,1.000,bicubic,-58.487,-28.097,-19 -resnet200d,38.160,61.840,68.627,31.373,64.69,320,1.000,bicubic,-58.560,-30.703,-27 -xcit_large_24_p16_224_dist,37.680,62.320,71.573,28.427,189.10,224,1.000,bicubic,-59.120,-27.777,-35 -seresnet152d,37.640,62.360,69.493,30.507,66.84,320,1.000,bicubic,-59.130,-29.957,-34 -xcit_small_12_p8_224,37.533,62.467,68.187,31.813,26.21,224,1.000,bicubic,-58.577,-30.973,+34 -eca_nfnet_l1,37.533,62.467,70.947,29.053,41.41,320,1.000,bicubic,-59.167,-28.343,-26 -twins_svt_large,37.213,62.787,69.253,30.747,99.27,224,0.900,bicubic,-59.057,-29.917,+15 -regnetz_d32,37.133,62.867,70.480,29.520,27.58,320,0.950,bicubic,-59.467,-28.900,-16 -vit_base_patch32_384,37.107,62.893,69.787,30.213,88.30,384,1.000,bicubic,-59.383,-29.623,-7 -regnety_064,36.973,63.027,68.173,31.827,30.58,288,1.000,bicubic,-59.387,-31.217,+4 +deit3_base_patch16_384,53.427,46.573,80.573,19.427,86.88,384,1.000,bicubic,-43.593,-18.817,+17 +tf_efficientnetv2_l,53.173,46.827,79.147,20.853,118.52,480,1.000,bicubic,-44.107,-20.403,-6 +ig_resnext101_32x16d,53.093,46.907,76.933,23.067,194.03,224,0.875,bilinear,-43.717,-22.667,+36 +volo_d4_224,52.933,47.067,80.440,19.560,192.96,224,0.960,bicubic,-44.367,-19.080,-10 +xcit_large_24_p16_384_dist,52.840,47.160,81.827,18.173,189.10,384,1.000,bicubic,-44.680,-17.653,-26 +swin_base_patch4_window7_224,51.427,48.573,79.973,20.027,87.77,224,0.900,bicubic,-45.823,-19.557,-8 +tf_efficientnet_b4_ns,51.253,48.747,79.173,20.827,19.34,380,0.922,bicubic,-45.697,-20.407,+19 +swsl_resnext101_32x8d,51.227,48.773,78.240,21.760,88.79,224,0.875,bilinear,-45.973,-21.330,-7 +resnetv2_152x2_bit_teacher_384,51.173,48.827,78.480,21.520,236.34,384,1.000,bicubic,-45.657,-20.970,+29 +beit_base_patch16_224,50.707,49.293,79.693,20.307,86.53,224,0.900,bicubic,-46.383,-19.917,0 +xcit_small_12_p8_384_dist,50.587,49.413,79.600,20.400,26.21,384,1.000,bicubic,-46.643,-19.880,-11 +volo_d3_224,50.253,49.747,78.173,21.827,86.33,224,0.960,bicubic,-46.837,-21.297,0 +cait_s24_384,49.733,50.267,78.733,21.267,47.06,384,1.000,bicubic,-47.337,-20.697,+2 +xcit_medium_24_p16_384_dist,49.333,50.667,79.853,20.147,84.40,384,1.000,bicubic,-47.947,-19.607,-17 +deit_base_distilled_patch16_384,49.320,50.680,79.253,20.747,87.63,384,1.000,bicubic,-47.640,-20.227,+10 +tf_efficientnet_b8,48.960,51.040,77.240,22.760,87.41,672,0.954,bicubic,-48.240,-22.260,-12 +dm_nfnet_f2,48.920,51.080,77.147,22.853,193.78,352,0.920,bicubic,-48.100,-22.293,0 +deit3_large_patch16_224,48.627,51.373,78.133,21.867,304.37,224,0.900,bicubic,-48.313,-21.207,+10 +tf_efficientnetv2_s_in21ft1k,48.507,51.493,77.893,22.107,21.46,384,1.000,bicubic,-48.213,-21.527,+28 +resnest269e,48.200,51.800,74.333,25.667,110.93,416,0.928,bicubic,-48.320,-25.017,+57 +xcit_large_24_p8_224_dist,48.120,51.880,79.107,20.893,188.93,224,1.000,bicubic,-48.950,-20.313,-5 +regnetz_e8,47.827,52.173,76.200,23.800,57.70,320,1.000,bicubic,-49.373,-23.300,-19 +resnetv2_50x3_bitm,47.280,52.720,77.333,22.667,217.32,448,1.000,bilinear,-49.430,-22.217,+26 +xcit_large_24_p8_224,47.160,52.840,74.400,25.600,188.93,224,1.000,bicubic,-49.250,-24.580,+62 +xcit_small_24_p16_384_dist,46.947,53.053,77.160,22.840,47.67,384,1.000,bicubic,-50.173,-22.290,-17 +tf_efficientnet_b8_ap,46.893,53.107,76.507,23.493,87.41,672,0.954,bicubic,-50.217,-23.153,-17 +efficientnetv2_rw_m,46.280,53.720,75.680,24.320,53.24,416,1.000,bicubic,-50.700,-23.860,-3 +swinv2_base_window16_256,46.267,53.733,75.187,24.813,87.92,256,0.900,bicubic,-50.493,-24.163,+17 +swsl_resnext101_32x16d,46.133,53.867,72.253,27.747,194.03,224,0.875,bilinear,-50.467,-27.277,+38 +volo_d2_224,46.080,53.920,75.253,24.747,58.68,224,0.960,bicubic,-50.920,-24.137,-9 +vit_small_patch16_384,45.920,54.080,76.707,23.293,22.20,384,1.000,bicubic,-50.780,-22.773,+22 +ecaresnet269d,45.880,54.120,75.133,24.867,102.09,352,1.000,bicubic,-51.200,-24.337,-18 +vit_small_r26_s32_384,45.733,54.267,76.053,23.947,36.47,384,1.000,bicubic,-50.947,-23.527,+25 +tf_efficientnetv2_m,45.533,54.467,74.533,25.467,54.14,480,1.000,bicubic,-51.607,-24.877,-28 +tf_efficientnet_b7_ap,45.373,54.627,74.213,25.787,66.35,600,0.949,bicubic,-51.827,-25.327,-33 +dm_nfnet_f1,45.320,54.680,74.107,25.893,132.63,320,0.910,bicubic,-51.590,-25.303,-3 +ig_resnext101_32x8d,45.293,54.707,70.853,29.147,88.79,224,0.875,bilinear,-51.017,-28.577,+61 +xcit_medium_24_p8_224_dist,45.213,54.787,76.720,23.280,84.32,224,1.000,bicubic,-51.707,-22.670,-8 +eca_nfnet_l2,44.960,55.040,75.893,24.107,56.72,384,1.000,bicubic,-52.130,-23.617,-28 +convnext_tiny_384_in22ft1k,44.840,55.160,76.680,23.320,28.59,384,1.000,bicubic,-52.040,-22.790,-4 +convnext_small_in22ft1k,44.813,55.187,77.373,22.627,50.22,224,0.875,bicubic,-52.177,-22.037,-18 +crossvit_18_dagger_408,44.293,55.707,73.827,26.173,44.61,408,1.000,bicubic,-52.237,-25.433,+34 +resnest200e,44.133,55.867,73.467,26.533,70.20,320,0.909,bicubic,-52.477,-25.883,+23 +cait_xs24_384,43.947,56.053,75.160,24.840,26.67,384,1.000,bicubic,-52.593,-24.260,+28 +seresnextaa101d_32x8d,43.947,56.053,73.400,26.600,93.59,288,1.000,bicubic,-53.003,-25.990,-18 +resnetrs200,43.747,56.253,72.813,27.187,93.21,320,1.000,bicubic,-52.953,-26.557,+8 +tresnet_xl_448,43.467,56.533,72.453,27.547,78.44,448,0.875,bilinear,-52.503,-26.677,+92 +xcit_small_12_p16_384_dist,43.267,56.733,73.880,26.120,26.25,384,1.000,bicubic,-53.663,-25.520,-19 +vit_base_patch16_224,43.253,56.747,72.893,27.107,86.57,224,0.900,bicubic,-53.627,-26.637,-14 +resnetrs420,43.147,56.853,70.467,29.533,191.89,416,1.000,bicubic,-53.763,-28.993,-18 +xcit_medium_24_p8_224,43.093,56.907,70.347,29.653,84.32,224,1.000,bicubic,-53.017,-28.543,+74 +tf_efficientnet_b7,42.960,57.040,73.133,26.867,66.35,600,0.949,bicubic,-54.050,-26.387,-32 +xcit_tiny_24_p8_384_dist,42.467,57.533,72.867,27.133,12.11,384,1.000,bicubic,-54.083,-26.453,+18 +swinv2_small_window16_256,42.293,57.707,72.920,27.080,49.73,256,0.900,bicubic,-54.167,-26.280,+26 +crossvit_15_dagger_408,41.907,58.093,72.067,27.933,28.50,408,1.000,bicubic,-54.483,-27.093,+34 +xcit_small_24_p8_224_dist,41.893,58.107,73.680,26.320,47.63,224,1.000,bicubic,-54.977,-25.800,-19 +xcit_small_24_p8_224,41.773,58.227,71.013,28.987,47.63,224,1.000,bicubic,-54.627,-28.137,+30 +vit_large_r50_s32_224,41.653,58.347,70.253,29.747,328.99,224,0.900,bicubic,-55.137,-29.097,-17 +swsl_resnext101_32x4d,41.560,58.440,71.747,28.253,44.18,224,0.875,bilinear,-54.870,-27.723,+25 +swinv2_base_window8_256,41.507,58.493,72.440,27.560,87.92,256,0.900,bicubic,-55.033,-26.830,+14 +convnext_large,41.373,58.627,73.293,26.707,197.77,224,0.875,bicubic,-55.387,-26.007,-15 +deit3_small_patch16_224_in21ft1k,41.240,58.760,71.933,28.067,22.06,224,1.000,bicubic,-55.420,-27.397,0 +seresnext101d_32x8d,41.133,58.867,70.880,29.120,93.59,288,1.000,bicubic,-55.577,-28.480,-11 +tf_efficientnet_b6_ap,40.813,59.187,71.627,28.373,43.04,528,0.942,bicubic,-56.267,-27.993,-51 +resmlp_big_24_224_in22ft1k,40.373,59.627,74.787,25.213,129.14,224,0.875,bicubic,-56.247,-24.723,-2 +deit3_small_patch16_384,40.307,59.693,70.333,29.667,22.21,384,1.000,bicubic,-55.893,-28.957,+43 +tresnet_l_448,40.213,59.787,69.907,30.093,55.99,448,0.875,bilinear,-55.647,-29.213,+84 +deit_base_patch16_384,40.173,59.827,70.760,29.240,86.86,384,1.000,bicubic,-55.977,-28.380,+51 +regnetz_d8_evos,40.093,59.907,72.187,27.813,23.46,320,0.950,bicubic,-56.517,-27.253,-4 +regnetz_040h,40.000,60.000,71.333,28.667,28.94,320,1.000,bicubic,-56.710,-28.167,-20 +resnetrs350,39.947,60.053,68.933,31.067,163.96,384,1.000,bicubic,-56.813,-30.437,-27 +regnetz_d8,39.933,60.067,71.640,28.360,23.37,320,1.000,bicubic,-56.687,-27.810,-8 +swin_s3_base_224,39.787,60.213,70.493,29.507,71.13,224,0.900,bicubic,-56.463,-28.647,+31 +seresnext101_32x8d,39.547,60.453,69.467,30.533,93.57,288,1.000,bicubic,-57.223,-29.883,-31 +deit3_base_patch16_224,39.200,60.800,71.027,28.973,86.59,224,0.900,bicubic,-57.100,-28.153,+25 +volo_d1_224,38.947,61.053,70.267,29.733,26.63,224,0.960,bicubic,-57.383,-29.043,+21 +resnetv2_101x1_bitm,38.933,61.067,71.040,28.960,44.54,448,1.000,bilinear,-57.167,-28.240,+49 +vit_large_patch32_384,38.933,61.067,68.947,31.053,306.63,384,1.000,bicubic,-56.897,-30.203,+75 +regnetz_040,38.733,61.267,70.413,29.587,27.12,320,1.000,bicubic,-57.977,-29.057,-28 +xcit_small_12_p8_224_dist,38.213,61.787,71.280,28.720,26.21,224,1.000,bicubic,-58.477,-28.110,-24 +resnet200d,38.147,61.853,68.627,31.373,64.69,320,1.000,bicubic,-58.573,-30.703,-33 +swinv2_small_window8_256,37.787,62.213,69.867,30.133,49.73,256,0.900,bicubic,-58.503,-29.343,+19 +xcit_large_24_p16_224_dist,37.680,62.320,71.587,28.413,189.10,224,1.000,bicubic,-59.120,-27.763,-43 +seresnet152d,37.653,62.347,69.480,30.520,66.84,320,1.000,bicubic,-59.117,-29.970,-42 +eca_nfnet_l1,37.533,62.467,70.960,29.040,41.41,320,1.000,bicubic,-59.167,-28.330,-30 +xcit_small_12_p8_224,37.533,62.467,68.213,31.787,26.21,224,1.000,bicubic,-58.577,-30.947,+38 +twins_svt_large,37.213,62.787,69.227,30.773,99.27,224,0.900,bicubic,-59.057,-29.943,+15 +regnetz_d32,37.133,62.867,70.480,29.520,27.58,320,0.950,bicubic,-59.467,-28.900,-20 +vit_base_patch32_384,37.107,62.893,69.787,30.213,88.30,384,1.000,bicubic,-59.383,-29.623,-11 +regnety_064,37.000,63.000,68.187,31.813,30.58,288,1.000,bicubic,-59.360,-31.043,+2 swin_s3_small_224,36.867,63.133,68.213,31.787,49.74,224,0.900,bicubic,-59.363,-30.877,+14 -efficientnetv2_rw_s,36.800,63.200,68.320,31.680,23.94,384,1.000,bicubic,-59.740,-31.000,-14 -regnety_160,36.773,63.227,69.093,30.907,83.59,288,1.000,bicubic,-59.577,-30.237,+2 -convnext_base,36.760,63.240,70.413,29.587,88.59,224,0.875,bicubic,-59.710,-28.817,-11 -resnext101_64x4d,36.733,63.267,66.640,33.360,83.46,288,1.000,bicubic,-59.347,-32.600,+29 -cait_xxs36_384,36.200,63.800,67.787,32.213,17.37,384,1.000,bicubic,-59.640,-31.303,+44 -jx_nest_base,36.067,63.933,66.773,33.227,67.72,224,0.875,bicubic,-60.173,-32.437,+7 -pit_b_distilled_224,35.627,64.373,69.120,30.880,74.79,224,0.900,bicubic,-61.043,-30.250,-31 -regnety_080,35.573,64.427,67.227,32.773,39.18,288,1.000,bicubic,-60.957,-32.093,-19 -tf_efficientnet_b3_ns,35.520,64.480,67.760,32.240,12.23,300,0.904,bicubic,-60.870,-31.590,-9 -tf_efficientnet_b6,35.213,64.787,67.733,32.267,43.04,528,0.942,bicubic,-61.457,-31.617,-36 -resnetrs270,35.013,64.987,65.480,34.520,129.86,352,1.000,bicubic,-61.677,-33.870,-39 -tf_efficientnet_b5_ap,34.800,65.200,67.467,32.533,30.39,456,0.934,bicubic,-61.870,-31.993,-37 -xcit_tiny_12_p8_384_dist,34.627,65.373,66.307,33.693,6.71,384,1.000,bicubic,-61.453,-32.833,+21 -vit_base_patch16_224_miil,34.533,65.467,65.000,35.000,86.54,224,0.875,bilinear,-61.917,-34.300,-20 -xcit_medium_24_p16_224_dist,34.347,65.653,67.893,32.107,84.40,224,1.000,bicubic,-62.243,-31.377,-32 -resnet152d,34.333,65.667,65.907,34.093,60.21,320,1.000,bicubic,-62.027,-33.323,-14 -tresnet_m_448,34.107,65.893,64.507,35.493,31.39,448,0.875,bilinear,-60.883,-34.473,+115 -resmlp_big_24_distilled_224,34.067,65.933,69.587,30.413,129.14,224,0.875,bicubic,-62.383,-29.723,-25 -regnetv_064,33.973,66.027,67.853,32.147,30.58,288,1.000,bicubic,-62.437,-31.507,-23 -xcit_tiny_24_p16_384_dist,33.827,66.173,65.373,34.627,12.12,384,1.000,bicubic,-62.103,-33.847,+21 -twins_pcpvt_large,33.413,66.587,67.947,32.053,60.99,224,0.900,bicubic,-62.737,-31.303,+1 -twins_svt_base,33.173,66.827,65.773,34.227,56.07,224,0.900,bicubic,-62.987,-33.287,-2 -pit_b_224,33.133,66.867,62.320,37.680,73.76,224,0.900,bicubic,-62.507,-36.870,+43 -resnetv2_152x2_bit_teacher,33.053,66.947,64.267,35.733,236.34,224,0.875,bicubic,-63.047,-35.003,+7 -swsl_resnext50_32x4d,33.040,66.960,65.080,34.920,25.03,224,0.875,bilinear,-62.830,-34.170,+21 -xception65,32.773,67.227,62.973,37.027,39.92,299,0.940,bicubic,-63.577,-36.267,-20 -xcit_large_24_p16_224,32.773,67.227,62.107,37.893,189.10,224,1.000,bicubic,-62.647,-36.513,+64 -ssl_resnext101_32x16d,32.653,67.347,64.027,35.973,194.03,224,0.875,bilinear,-63.137,-35.153,+25 -swin_small_patch4_window7_224,32.600,67.400,65.440,34.560,49.61,224,0.900,bicubic,-63.310,-33.580,+13 -jx_nest_small,32.267,67.733,63.760,36.240,38.35,224,0.875,bicubic,-63.703,-35.370,+9 -tf_efficientnet_b5,31.840,68.160,65.293,34.707,30.39,456,0.934,bicubic,-64.510,-34.017,-26 -regnetz_c16_evos,31.493,68.507,66.280,33.720,13.49,320,0.950,bicubic,-64.637,-33.080,-7 -resnest101e,31.400,68.600,64.373,35.627,48.28,256,0.875,bilinear,-64.460,-34.747,+15 -crossvit_base_240,31.347,68.653,61.293,38.707,105.03,240,0.875,bicubic,-64.173,-37.527,+44 -regnetv_040,31.333,68.667,64.667,35.333,20.64,288,1.000,bicubic,-64.857,-34.663,-18 -convnext_small,31.307,68.693,66.027,33.973,50.22,224,0.875,bicubic,-64.863,-33.073,-18 -cait_s24_224,31.200,68.800,64.573,35.427,46.92,224,1.000,bicubic,-65.180,-34.577,-36 -efficientnet_b4,30.840,69.160,64.600,35.400,19.34,384,1.000,bicubic,-65.310,-34.580,-14 -regnety_040,30.600,69.400,63.813,36.187,20.65,288,1.000,bicubic,-65.420,-35.377,-3 -crossvit_18_240,30.573,69.427,61.960,38.040,43.27,240,0.875,bicubic,-64.867,-37.170,+47 -dm_nfnet_f0,30.547,69.453,62.867,37.133,71.49,256,0.900,bicubic,-65.603,-36.323,-18 -crossvit_18_dagger_240,30.520,69.480,61.813,38.187,44.27,240,0.875,bicubic,-65.050,-37.247,+28 -xcit_small_24_p16_224_dist,30.440,69.560,64.693,35.307,47.67,224,1.000,bicubic,-65.780,-34.517,-28 -xcit_medium_24_p16_224,30.200,69.800,59.320,40.680,84.40,224,1.000,bicubic,-65.330,-39.730,+31 -cait_xxs24_384,30.027,69.973,63.933,36.067,12.03,384,1.000,bicubic,-65.243,-35.027,+56 -twins_pcpvt_base,29.960,70.040,64.587,35.413,43.83,224,0.900,bicubic,-65.830,-34.543,+8 -swsl_resnet50,29.853,70.147,63.813,36.187,25.56,224,0.875,bilinear,-65.547,-35.487,+47 -deit_base_distilled_patch16_224,29.600,70.400,64.427,35.573,87.34,224,0.900,bicubic,-66.490,-34.763,-16 -convit_base,29.520,70.480,61.760,38.240,86.54,224,0.875,bicubic,-66.030,-37.110,+22 -ssl_resnext101_32x8d,29.120,70.880,61.013,38.987,88.79,224,0.875,bilinear,-66.370,-38.107,+33 -tf_efficientnetv2_s,29.040,70.960,61.227,38.773,21.46,384,1.000,bicubic,-67.300,-37.973,-44 -resnet101d,29.000,71.000,62.053,37.947,44.57,320,1.000,bicubic,-67.300,-37.177,-42 -xception65p,28.973,71.027,59.920,40.080,39.82,299,0.940,bicubic,-67.227,-39.260,-37 -resnetrs152,28.920,71.080,60.507,39.493,86.62,320,1.000,bicubic,-67.660,-38.733,-70 +efficientnetv2_rw_s,36.813,63.187,68.320,31.680,23.94,384,1.000,bicubic,-59.727,-31.040,-19 +regnety_160,36.787,63.213,69.107,30.893,83.59,288,1.000,bicubic,-59.563,-30.223,0 +convnext_base,36.747,63.253,70.413,29.587,88.59,224,0.875,bicubic,-59.723,-28.817,-15 +resnext101_64x4d,36.720,63.280,66.653,33.347,83.46,288,1.000,bicubic,-59.360,-32.587,+34 +convnext_tiny_in22ft1k,36.267,63.733,69.560,30.440,28.59,224,0.875,bicubic,-59.953,-29.780,+10 +cait_xxs36_384,36.253,63.747,67.800,32.200,17.37,384,1.000,bicubic,-59.587,-31.290,+55 +jx_nest_base,36.067,63.933,66.760,33.240,67.72,224,0.875,bicubic,-60.183,-32.450,+5 +pit_b_distilled_224,35.627,64.373,69.120,30.880,74.79,224,0.900,bicubic,-61.043,-30.230,-38 +sequencer2d_l,35.560,64.440,67.333,32.667,54.30,224,0.875,bicubic,-60.580,-31.827,+20 +regnety_080,35.560,64.440,67.240,32.760,39.18,288,1.000,bicubic,-60.970,-32.080,-26 +tf_efficientnet_b3_ns,35.507,64.493,67.747,32.253,12.23,300,0.904,bicubic,-60.883,-31.603,-14 +cs3se_edgenet_x,35.427,64.573,67.280,32.720,50.72,320,1.000,bicubic,-61.013,-32.120,-20 +tf_efficientnet_b6,35.227,64.773,67.720,32.280,43.04,528,0.942,bicubic,-61.443,-31.650,-44 +resnetrs270,35.000,65.000,65.480,34.520,129.86,352,1.000,bicubic,-61.690,-33.870,-48 +tf_efficientnet_b5_ap,34.800,65.200,67.467,32.533,30.39,456,0.934,bicubic,-61.880,-31.993,-47 +xcit_tiny_12_p8_384_dist,34.653,65.347,66.280,33.720,6.71,384,1.000,bicubic,-61.427,-32.860,+23 +vit_base_patch16_224_miil,34.520,65.480,65.000,35.000,86.54,224,0.875,bilinear,-61.930,-34.300,-26 +xcit_medium_24_p16_224_dist,34.320,65.680,67.893,32.107,84.40,224,1.000,bicubic,-62.270,-31.377,-40 +resnet152d,34.307,65.693,65.907,34.093,60.21,320,1.000,bicubic,-62.053,-33.483,-19 +tresnet_m_448,34.107,65.893,64.507,35.493,31.39,448,0.875,bilinear,-60.883,-34.473,+147 +resmlp_big_24_distilled_224,34.067,65.933,69.600,30.400,129.14,224,0.875,bicubic,-62.383,-29.710,-31 +regnetv_064,33.987,66.013,67.867,32.133,30.58,288,1.000,bicubic,-62.423,-31.493,-28 +xcit_tiny_24_p16_384_dist,33.827,66.173,65.387,34.613,12.12,384,1.000,bicubic,-62.093,-33.833,+29 +twins_pcpvt_large,33.413,66.587,67.933,32.067,60.99,224,0.900,bicubic,-62.737,-31.247,+3 +twins_svt_base,33.173,66.827,65.773,34.227,56.07,224,0.900,bicubic,-62.987,-33.287,-1 +pit_b_224,33.160,66.840,62.347,37.653,73.76,224,0.900,bicubic,-62.480,-36.323,+55 +resnetv2_152x2_bit_teacher,33.053,66.947,64.253,35.747,236.34,224,0.875,bicubic,-63.047,-35.017,+9 +swsl_resnext50_32x4d,33.027,66.973,65.080,34.920,25.03,224,0.875,bilinear,-62.833,-34.170,+29 +mobilevitv2_200_384_in22ft1k,32.960,67.040,65.480,34.520,18.45,384,1.000,bicubic,-63.080,-33.600,+14 +swinv2_cr_small_ns_224,32.933,67.067,65.960,34.040,49.70,224,0.900,bicubic,-63.247,-33.180,-10 +xception65,32.760,67.240,62.973,37.027,39.92,299,0.940,bicubic,-63.590,-36.267,-27 +xcit_large_24_p16_224,32.760,67.240,62.120,37.880,189.10,224,1.000,bicubic,-62.660,-36.500,+81 +ssl_resnext101_32x16d,32.653,67.347,64.040,35.960,194.03,224,0.875,bilinear,-63.137,-35.140,+33 +swin_small_patch4_window7_224,32.587,67.413,65.453,34.547,49.61,224,0.900,bicubic,-63.323,-33.567,+19 +mobilevitv2_175_384_in22ft1k,32.453,67.547,64.720,35.280,14.25,384,1.000,bicubic,-63.727,-34.410,-14 +jx_nest_small,32.280,67.720,63.733,36.267,38.35,224,0.875,bicubic,-63.680,-35.297,+13 +tf_efficientnet_b5,31.853,68.147,65.307,34.693,30.39,456,0.934,bicubic,-64.497,-34.003,-34 +swinv2_tiny_window16_256,31.720,68.280,65.587,34.413,28.35,256,0.900,bicubic,-64.220,-33.553,+13 +swinv2_cr_small_224,31.680,68.320,62.507,37.493,49.70,224,0.900,bicubic,-64.380,-36.363,+1 +regnetz_c16_evos,31.493,68.507,66.280,33.720,13.49,320,0.950,bicubic,-64.637,-33.080,-10 +resnest101e,31.400,68.600,64.347,35.653,48.28,256,0.875,bilinear,-64.460,-34.863,+17 +crossvit_base_240,31.347,68.653,61.293,38.707,105.03,240,0.875,bicubic,-64.173,-37.527,+52 +regnetv_040,31.333,68.667,64.667,35.333,20.64,288,1.000,bicubic,-64.857,-34.663,-24 +convnext_small,31.320,68.680,66.040,33.960,50.22,224,0.875,bicubic,-64.850,-33.060,-22 +cait_s24_224,31.200,68.800,64.560,35.440,46.92,224,1.000,bicubic,-65.180,-34.590,-46 +efficientnet_b4,30.840,69.160,64.600,35.400,19.34,384,1.000,bicubic,-65.310,-34.590,-20 +regnety_040,30.613,69.387,63.827,36.173,20.65,288,1.000,bicubic,-65.397,-35.353,-2 +sequencer2d_m,30.600,69.400,62.933,37.067,38.31,224,0.875,bicubic,-65.210,-36.177,+16 +crossvit_18_240,30.600,69.400,61.947,38.053,43.27,240,0.875,bicubic,-64.840,-36.843,+59 +dm_nfnet_f0,30.547,69.453,62.867,37.133,71.49,256,0.900,bicubic,-65.603,-36.383,-25 +xcit_small_24_p16_224_dist,30.520,69.480,64.760,35.240,47.67,224,1.000,bicubic,-65.690,-34.450,-35 +crossvit_18_dagger_240,30.507,69.493,61.840,38.160,44.27,240,0.875,bicubic,-65.063,-37.220,+33 +xcit_medium_24_p16_224,30.187,69.813,59.333,40.667,84.40,224,1.000,bicubic,-65.343,-39.407,+40 +cait_xxs24_384,30.040,69.960,63.920,36.080,12.03,384,1.000,bicubic,-65.240,-35.040,+72 +twins_pcpvt_base,29.973,70.027,64.600,35.400,43.83,224,0.900,bicubic,-65.817,-34.530,+12 +swsl_resnet50,29.840,70.160,63.827,36.173,25.56,224,0.875,bilinear,-65.570,-35.473,+58 +mobilevitv2_150_384_in22ft1k,29.840,70.160,62.213,37.787,10.59,384,1.000,bicubic,-65.860,-36.927,+18 +vit_relpos_base_patch16_clsgap_224,29.720,70.280,62.867,37.133,86.43,224,0.900,bicubic,-66.040,-36.173,+12 +deit_base_distilled_patch16_224,29.600,70.400,64.440,35.560,87.34,224,0.900,bicubic,-66.490,-34.750,-22 +cs3sedarknet_x,29.573,70.427,61.493,38.507,35.40,288,1.000,bicubic,-66.467,-37.617,-18 +convit_base,29.507,70.493,61.760,38.240,86.54,224,0.875,bicubic,-66.043,-37.110,+27 +vit_relpos_medium_patch16_cls_224,29.320,70.680,60.653,39.347,38.76,224,0.900,bicubic,-66.160,-38.297,+40 +ssl_resnext101_32x8d,29.120,70.880,61.013,38.987,88.79,224,0.875,bilinear,-66.370,-38.107,+38 +tf_efficientnetv2_s,29.053,70.947,61.227,38.773,21.46,384,1.000,bicubic,-67.287,-37.973,-59 +resnet101d,28.987,71.013,62.040,37.960,44.57,320,1.000,bicubic,-67.313,-37.190,-57 +xception65p,28.987,71.013,59.920,40.080,39.82,299,0.940,bicubic,-67.223,-39.260,-49 +resnetrs152,28.920,71.080,60.507,39.493,86.62,320,1.000,bicubic,-67.660,-38.733,-88 regnetz_c16,28.907,71.093,63.347,36.653,13.46,320,0.940,bicubic,-66.893,-35.753,-3 -xcit_tiny_24_p8_224_dist,28.720,71.280,61.400,38.600,12.11,224,1.000,bicubic,-67.090,-37.810,-5 -xcit_tiny_24_p8_224,28.707,71.293,60.453,39.547,12.11,224,1.000,bicubic,-66.963,-38.597,+6 -crossvit_15_dagger_240,28.533,71.467,60.333,39.667,28.21,240,0.875,bicubic,-67.157,-38.497,+3 -xcit_small_24_p16_224,28.333,71.667,58.813,41.187,47.67,224,1.000,bicubic,-67.197,-40.317,+15 -coat_lite_small,27.547,72.453,58.533,41.467,19.84,224,0.900,bicubic,-67.993,-40.327,+13 -deit_base_patch16_224,27.440,72.560,58.893,41.107,86.57,224,0.900,bicubic,-68.000,-40.157,+27 -resnetv2_50x1_bitm,27.307,72.693,62.853,37.147,25.55,448,1.000,bilinear,-67.703,-36.207,+68 -xcit_small_12_p16_224_dist,27.120,72.880,59.813,40.187,26.25,224,1.000,bicubic,-68.910,-39.327,-28 -vit_small_patch16_224,27.013,72.987,59.187,40.813,22.05,224,0.900,bicubic,-68.357,-39.963,+32 -swin_s3_tiny_224,26.493,73.507,60.333,39.667,28.33,224,0.900,bicubic,-68.667,-38.607,+43 -tf_efficientnet_b4,26.293,73.707,60.107,39.893,19.34,380,0.922,bicubic,-69.607,-39.063,-22 -tf_efficientnet_b4_ap,26.253,73.747,60.213,39.787,19.34,380,0.922,bicubic,-69.917,-39.067,-48 -nfnet_l0,26.227,73.773,61.747,38.253,35.07,288,1.000,bicubic,-69.893,-37.493,-42 -regnety_032,26.213,73.787,60.987,39.013,19.44,288,1.000,bicubic,-69.757,-38.043,-32 -ecaresnet50t,26.107,73.893,60.013,39.987,25.57,320,0.950,bicubic,-69.403,-39.107,+11 -fbnetv3_g,26.093,73.907,61.040,38.960,16.62,288,0.950,bilinear,-69.417,-37.950,+11 -ecaresnet101d,26.013,73.987,59.000,41.000,44.57,224,0.875,bicubic,-69.517,-39.760,+5 -visformer_small,25.840,74.160,58.880,41.120,40.22,224,0.900,bicubic,-69.650,-40.020,+11 -halo2botnet50ts_256,25.587,74.413,56.840,43.160,22.64,256,0.950,bicubic,-69.823,-42.170,+19 -coat_mini,25.493,74.507,57.693,42.307,10.34,224,0.900,bicubic,-69.477,-41.087,+58 -crossvit_15_240,25.453,74.547,57.573,42.427,27.53,240,0.875,bicubic,-69.687,-41.277,+37 -xcit_small_12_p16_224,25.107,74.893,56.027,43.973,26.25,224,1.000,bicubic,-70.313,-42.813,+14 -resnetv2_50x1_bit_distilled,25.107,74.893,59.640,40.360,25.55,224,0.875,bicubic,-71.013,-39.640,-50 -convit_small,25.080,74.920,57.267,42.733,27.78,224,0.875,bicubic,-70.120,-41.633,+26 -gc_efficientnetv2_rw_t,25.040,74.960,57.707,42.293,13.68,288,1.000,bicubic,-70.700,-41.313,-23 -eca_nfnet_l0,24.827,75.173,60.093,39.907,24.14,288,1.000,bicubic,-71.123,-39.117,-41 -xception41p,24.800,75.200,55.187,44.813,26.91,299,0.940,bicubic,-70.720,-43.723,-3 -tnt_s_patch16_224,24.747,75.253,58.187,41.813,23.76,224,0.900,bicubic,-70.293,-40.653,+43 -resnetv2_50d_evos,24.493,75.507,56.360,43.640,25.59,288,0.950,bicubic,-71.117,-42.670,-15 -xcit_tiny_12_p16_384_dist,24.467,75.533,57.093,42.907,6.72,384,1.000,bicubic,-70.663,-41.927,+29 -efficientnetv2_rw_t,24.333,75.667,57.400,42.600,13.65,288,1.000,bicubic,-71.277,-41.670,-18 -convnext_tiny,24.253,75.747,59.333,40.667,28.59,224,0.875,bicubic,-71.297,-39.667,-15 -ssl_resnext101_32x4d,24.173,75.827,57.387,42.613,44.18,224,0.875,bilinear,-71.267,-41.403,-3 -twins_svt_small,24.107,75.893,57.160,42.840,24.06,224,0.900,bicubic,-71.093,-41.720,+17 -vit_small_r26_s32_224,24.080,75.920,56.173,43.827,36.43,224,0.900,bicubic,-71.560,-42.767,-25 -poolformer_m48,24.053,75.947,57.280,42.720,73.47,224,0.950,bicubic,-71.587,-41.390,-27 -tf_efficientnet_b2_ns,24.013,75.987,57.293,42.707,9.11,260,0.890,bicubic,-71.757,-41.827,-36 -resnetv2_50d_gn,23.920,76.080,56.307,43.693,25.57,288,0.950,bicubic,-71.510,-42.733,-3 -vit_small_patch32_384,23.800,76.200,57.307,42.693,22.92,384,1.000,bicubic,-71.260,-41.723,+28 -lamhalobotnet50ts_256,23.587,76.413,55.280,44.720,22.57,256,0.950,bicubic,-71.563,-43.600,+16 -resnet152,23.533,76.467,53.667,46.333,60.19,224,0.950,bicubic,-72.367,-45.413,-53 -nasnetalarge,23.480,76.520,55.013,44.987,88.75,331,0.911,bicubic,-72.200,-43.917,-35 -crossvit_small_240,23.440,76.560,56.787,43.213,26.86,240,0.875,bicubic,-71.390,-42.233,+47 -levit_384,23.413,76.587,56.373,43.627,39.13,224,0.900,bicubic,-72.117,-42.367,-23 -pnasnet5large,23.347,76.653,53.640,46.360,86.06,331,0.911,bicubic,-72.363,-45.390,-40 -convnext_tiny_hnf,23.240,76.760,55.187,44.813,28.59,224,0.950,bicubic,-72.270,-43.833,-21 -efficientnet_b3,23.213,76.787,55.960,44.040,12.23,320,1.000,bicubic,-72.497,-43.080,-44 -jx_nest_tiny,23.173,76.827,56.213,43.787,17.06,224,0.875,bicubic,-72.067,-42.837,0 -resnet61q,22.987,77.013,55.760,44.240,36.85,288,1.000,bicubic,-72.793,-43.230,-49 -halonet50ts,22.920,77.080,53.987,46.013,22.73,256,0.940,bicubic,-72.230,-44.783,+5 -resmlp_big_24_224,22.853,77.147,54.307,45.693,129.14,224,0.875,bicubic,-71.817,-44.173,+49 -twins_pcpvt_small,22.707,77.293,56.853,43.147,24.11,224,0.900,bicubic,-72.503,-42.027,-3 -poolformer_m36,22.507,77.493,55.280,44.720,56.17,224,0.950,bicubic,-72.873,-43.570,-13 -vit_base_patch32_224,22.387,77.613,54.000,46.000,88.22,224,0.900,bicubic,-72.613,-45.030,+22 -pit_s_distilled_224,22.373,77.627,57.093,42.907,24.04,224,0.900,bicubic,-72.867,-41.887,-8 -xcit_tiny_12_p8_224_dist,22.067,77.933,54.320,45.680,6.71,224,1.000,bicubic,-73.023,-44.590,+7 -tresnet_m,21.680,78.320,53.840,46.160,31.39,224,0.875,bilinear,-74.030,-45.080,-53 -convmixer_1536_20,21.200,78.800,55.520,44.480,51.63,224,0.960,bicubic,-73.860,-43.530,+10 -swin_tiny_patch4_window7_224,21.160,78.840,55.987,44.013,28.29,224,0.900,bicubic,-73.980,-42.943,-2 -pit_s_224,21.093,78.907,53.560,46.440,23.46,224,0.900,bicubic,-73.497,-45.140,+47 -xcit_tiny_12_p8_224,21.040,78.960,52.440,47.560,6.71,224,1.000,bicubic,-73.650,-46.390,+38 -regnetz_b16,20.960,79.040,53.840,46.160,9.72,288,0.940,bicubic,-74.100,-45.150,+7 -resnet51q,20.960,79.040,55.693,44.307,35.70,288,1.000,bilinear,-74.910,-43.427,-73 -resnetrs101,20.880,79.120,52.813,47.187,63.62,288,0.940,bicubic,-74.550,-46.217,-30 -sebotnet33ts_256,20.747,79.253,48.800,51.200,13.70,256,0.940,bicubic,-73.823,-49.700,+44 -deit_small_distilled_patch16_224,20.693,79.307,55.147,44.853,22.44,224,0.900,bicubic,-74.017,-43.883,+31 -resnest50d_4s2x40d,20.373,79.627,52.827,47.173,30.42,224,0.875,bicubic,-74.587,-46.243,+12 -ssl_resnext50_32x4d,20.027,79.973,53.613,46.387,25.03,224,0.875,bilinear,-74.843,-45.277,+18 -haloregnetz_b,20.000,80.000,50.000,50.000,11.68,224,0.940,bicubic,-74.700,-48.660,+29 -resnetv2_101,19.880,80.120,49.213,50.787,44.54,224,0.950,bicubic,-75.750,-49.777,-58 -xcit_nano_12_p8_384_dist,19.773,80.227,50.587,49.413,3.05,384,1.000,bicubic,-73.727,-48.143,+142 -tresnet_xl,19.640,80.360,53.147,46.853,78.44,224,0.875,bilinear,-75.800,-45.693,-41 -gluon_senet154,19.333,80.667,47.560,52.440,115.09,224,0.875,bicubic,-75.587,-51.200,+8 -resnet101,19.320,80.680,49.600,50.400,44.55,224,0.950,bicubic,-76.040,-49.260,-32 -levit_256,19.200,80.800,50.053,49.947,18.89,224,0.900,bicubic,-75.820,-48.837,-2 -rexnet_200,19.200,80.800,52.720,47.280,16.37,224,0.875,bicubic,-75.750,-46.290,+4 -repvgg_b3,19.133,80.867,50.307,49.693,123.09,224,0.875,bilinear,-75.437,-48.473,+31 -lambda_resnet50ts,19.107,80.893,49.280,50.720,21.54,256,0.950,bicubic,-75.683,-49.180,+13 -legacy_senet154,19.040,80.960,47.960,52.040,115.09,224,0.875,bilinear,-76.030,-50.870,-14 -mixer_b16_224_miil,19.040,80.960,51.240,48.760,59.88,224,0.875,bilinear,-76.270,-47.630,-36 -gluon_seresnext101_64x4d,18.920,81.080,49.173,50.827,88.23,224,0.875,bicubic,-76.000,-49.657,+2 -deit_small_patch16_224,18.907,81.093,51.387,48.613,22.05,224,0.900,bicubic,-75.483,-47.303,+51 -tf_efficientnet_b1_ns,18.693,81.307,51.693,48.307,7.79,240,0.882,bicubic,-76.477,-47.427,-31 -poolformer_s36,18.400,81.600,51.853,48.147,30.86,224,0.900,bicubic,-76.690,-47.057,-22 -seresnext50_32x4d,18.373,81.627,50.973,49.027,27.56,224,0.875,bicubic,-76.657,-47.907,-13 -cait_xxs36_224,18.280,81.720,49.440,50.560,17.30,224,1.000,bicubic,-75.980,-49.280,+58 -ecaresnet50d,18.240,81.760,51.853,48.147,25.58,224,0.875,bicubic,-76.390,-46.907,+17 -sehalonet33ts,18.227,81.773,47.800,52.200,13.69,256,0.940,bicubic,-76.543,-50.770,+5 -tf_efficientnet_lite4,18.147,81.853,50.720,49.280,13.01,380,0.920,bilinear,-76.743,-48.300,-5 -vit_tiny_patch16_384,18.027,81.973,50.333,49.667,5.79,384,1.000,bicubic,-75.633,-48.267,+112 -resnest50d_1s4x24d,17.693,82.307,49.787,50.213,25.68,224,0.875,bicubic,-77.067,-49.193,+3 -gluon_seresnext101_32x4d,17.373,82.627,46.387,53.613,48.96,224,0.875,bicubic,-77.547,-52.423,-10 -resnest50d,17.360,82.640,50.747,49.253,27.48,224,0.875,bilinear,-77.490,-48.133,-5 -efficientnet_el,17.320,82.680,50.027,49.973,10.59,300,0.904,bicubic,-77.800,-48.953,-34 -inception_v4,17.280,82.720,45.933,54.067,42.68,299,0.875,bicubic,-77.100,-52.647,+39 -tf_efficientnet_b3_ap,17.213,82.787,49.680,50.320,12.23,300,0.904,bicubic,-78.107,-49.220,-53 -xcit_tiny_24_p16_224_dist,17.187,82.813,47.493,52.507,12.12,224,1.000,bicubic,-77.353,-51.287,+20 -xception71,17.000,83.000,45.533,54.467,42.34,299,0.903,bicubic,-77.280,-53.107,+45 -tf_efficientnet_b3,16.987,83.013,49.267,50.733,12.23,300,0.904,bicubic,-78.033,-49.643,-25 -gluon_resnext101_64x4d,16.893,83.107,44.147,55.853,83.46,224,0.875,bicubic,-77.767,-54.503,+2 +vit_relpos_medium_patch16_224,28.840,71.160,62.013,37.987,38.75,224,0.900,bicubic,-66.620,-36.947,+35 +xcit_tiny_24_p8_224_dist,28.733,71.267,61.373,38.627,12.11,224,1.000,bicubic,-67.077,-37.837,-7 +xcit_tiny_24_p8_224,28.707,71.293,60.440,39.560,12.11,224,1.000,bicubic,-66.963,-38.610,+7 +crossvit_15_dagger_240,28.533,71.467,60.333,39.667,28.21,240,0.875,bicubic,-67.157,-38.497,+4 +xcit_small_24_p16_224,28.347,71.653,58.707,41.293,47.67,224,1.000,bicubic,-67.183,-40.063,+19 +cs3edgenet_x,28.333,71.667,60.813,39.187,47.82,288,1.000,bicubic,-67.717,-38.327,-33 +coat_lite_small,27.547,72.453,58.560,41.440,19.84,224,0.900,bicubic,-67.993,-40.300,+14 +deit_base_patch16_224,27.440,72.560,58.893,41.107,86.57,224,0.900,bicubic,-68.000,-39.947,+31 +vit_relpos_base_patch16_224,27.347,72.653,61.147,38.853,86.43,224,0.900,bicubic,-68.223,-37.883,+9 +resnetv2_50x1_bitm,27.307,72.693,62.853,37.147,25.55,448,1.000,bilinear,-67.703,-36.207,+84 +xcit_small_12_p16_224_dist,27.120,72.880,59.800,40.200,26.25,224,1.000,bicubic,-68.900,-39.330,-35 +vit_small_patch16_224,27.013,72.987,59.187,40.813,22.05,224,0.900,bicubic,-68.357,-39.963,+38 +sequencer2d_s,26.813,73.187,60.613,39.387,27.65,224,0.875,bicubic,-69.177,-38.437,-35 +mobilevitv2_200_in22ft1k,26.680,73.320,59.373,40.627,18.45,256,0.888,bicubic,-68.480,-39.577,+55 +swin_s3_tiny_224,26.520,73.480,60.320,39.680,28.33,224,0.900,bicubic,-68.640,-38.620,+56 +swinv2_tiny_window8_256,26.413,73.587,60.560,39.440,28.35,256,0.900,bicubic,-69.087,-38.560,+16 +tf_efficientnet_b4,26.320,73.680,60.107,39.893,19.34,380,0.922,bicubic,-69.580,-39.063,-31 +tf_efficientnet_b4_ap,26.240,73.760,60.213,39.787,19.34,380,0.922,bicubic,-69.920,-39.067,-63 +nfnet_l0,26.213,73.787,61.720,38.280,35.07,288,1.000,bicubic,-69.907,-37.520,-55 +deit3_small_patch16_224,26.213,73.787,54.413,45.587,22.06,224,0.900,bicubic,-68.787,-44.047,+78 +regnety_032,26.200,73.800,60.973,39.027,19.44,288,1.000,bicubic,-69.770,-38.217,-42 +fbnetv3_g,26.120,73.880,61.067,38.933,16.62,288,0.950,bilinear,-69.390,-37.923,+8 +ecaresnet50t,26.120,73.880,59.987,40.013,25.57,320,0.950,bicubic,-69.390,-39.133,+4 +ecaresnet101d,26.040,73.960,59.000,41.000,44.57,224,0.875,bicubic,-69.490,-40.130,-2 +mobilevitv2_175_in22ft1k,26.040,73.960,58.453,41.547,14.25,256,0.888,bicubic,-69.190,-40.337,+37 +visformer_small,25.840,74.160,58.907,41.093,40.22,224,0.900,bicubic,-69.630,-39.993,+9 +halo2botnet50ts_256,25.587,74.413,56.853,43.147,22.64,256,0.950,bicubic,-69.833,-42.157,+16 +coat_mini,25.493,74.507,57.707,42.293,10.34,224,0.900,bicubic,-69.477,-41.073,+72 +vit_relpos_medium_patch16_rpn_224,25.453,74.547,58.627,41.373,38.73,224,0.900,bicubic,-70.057,-40.453,-1 +crossvit_15_240,25.453,74.547,57.547,42.453,27.53,240,0.875,bicubic,-69.697,-41.383,+43 +vit_srelpos_medium_patch16_224,25.387,74.613,58.480,41.520,38.74,224,0.900,bicubic,-69.843,-40.510,+30 +xcit_small_12_p16_224,25.173,74.827,56.080,43.920,26.25,224,1.000,bicubic,-70.247,-42.760,+12 +resnetv2_50x1_bit_distilled,25.133,74.867,59.653,40.347,25.55,224,0.875,bicubic,-70.987,-39.627,-70 +convit_small,25.107,74.893,57.280,42.720,27.78,224,0.875,bicubic,-70.093,-41.620,+31 +vit_base_patch16_rpn_224,25.080,74.920,58.653,41.347,86.54,224,0.900,bicubic,-70.300,-40.277,+13 +gc_efficientnetv2_rw_t,25.053,74.947,57.720,42.280,13.68,288,1.000,bicubic,-70.687,-41.300,-33 +eca_nfnet_l0,24.813,75.187,60.093,39.907,24.14,288,1.000,bicubic,-71.137,-39.117,-55 +xception41p,24.800,75.200,55.173,44.827,26.91,299,0.940,bicubic,-70.710,-43.737,-7 +tnt_s_patch16_224,24.720,75.280,58.187,41.813,23.76,224,0.900,bicubic,-70.320,-40.643,+52 +resnetv2_50d_evos,24.467,75.533,56.387,43.613,25.59,288,0.950,bicubic,-71.143,-42.643,-25 +xcit_tiny_12_p16_384_dist,24.440,75.560,57.067,42.933,6.72,384,1.000,bicubic,-70.690,-41.953,+36 +cs3darknet_x,24.360,75.640,57.813,42.187,35.05,288,1.000,bicubic,-71.500,-41.367,-51 +efficientnetv2_rw_t,24.280,75.720,57.360,42.640,13.65,288,1.000,bicubic,-71.320,-41.710,-27 +convnext_tiny,24.267,75.733,59.333,40.667,28.59,224,0.875,bicubic,-71.283,-39.667,-25 +ssl_resnext101_32x4d,24.173,75.827,57.413,42.587,44.18,224,0.875,bilinear,-71.267,-41.717,-8 +swinv2_cr_tiny_ns_224,24.120,75.880,58.227,41.773,28.33,224,0.900,bicubic,-71.250,-40.713,+5 +twins_svt_small,24.107,75.893,57.133,42.867,24.06,224,0.900,bicubic,-71.093,-41.747,+19 +vit_small_r26_s32_224,24.080,75.920,56.173,43.827,36.43,224,0.900,bicubic,-71.560,-43.017,-37 +mobilevitv2_150_in22ft1k,24.053,75.947,55.987,44.013,10.59,256,0.888,bicubic,-71.087,-42.873,+26 +vit_relpos_small_patch16_224,24.027,75.973,58.200,41.800,21.98,224,0.900,bicubic,-71.133,-40.750,+20 +poolformer_m48,24.027,75.973,57.280,42.720,73.47,224,0.950,bicubic,-71.613,-41.660,-39 +tf_efficientnet_b2_ns,24.013,75.987,57.280,42.720,9.11,260,0.890,bicubic,-71.747,-41.840,-51 +cs3sedarknet_l,23.960,76.040,58.707,41.293,21.91,288,0.950,bicubic,-71.350,-40.423,+2 +resnetv2_50d_gn,23.920,76.080,56.307,43.693,25.57,288,0.950,bicubic,-71.510,-42.733,-13 +vit_small_patch32_384,23.760,76.240,57.293,42.707,22.92,384,1.000,bicubic,-71.290,-41.697,+34 +convnext_nano,23.640,76.360,55.800,44.200,15.59,288,1.000,bicubic,-71.720,-43.050,-3 +lamhalobotnet50ts_256,23.573,76.427,55.333,44.667,22.57,256,0.950,bicubic,-71.577,-43.547,+17 +resnet152,23.560,76.440,53.680,46.320,60.19,224,0.950,bicubic,-72.340,-45.400,-71 +nasnetalarge,23.467,76.533,55.013,44.987,88.75,331,0.911,bicubic,-72.213,-43.917,-50 +crossvit_small_240,23.440,76.560,56.813,43.187,26.86,240,0.875,bicubic,-71.390,-42.207,+53 +levit_384,23.427,76.573,56.373,43.627,39.13,224,0.900,bicubic,-72.103,-42.677,-38 +pnasnet5large,23.320,76.680,53.640,46.360,86.06,331,0.911,bicubic,-72.390,-45.280,-56 +convnext_tiny_hnf,23.227,76.773,55.200,44.800,28.59,224,0.950,bicubic,-72.283,-43.820,-34 +efficientnet_b3,23.213,76.787,55.960,44.040,12.23,320,1.000,bicubic,-72.497,-43.080,-60 +jx_nest_tiny,23.173,76.827,56.213,43.787,17.06,224,0.875,bicubic,-72.067,-42.767,-5 +resnet61q,22.987,77.013,55.747,44.253,36.85,288,1.000,bicubic,-72.793,-43.243,-66 +halonet50ts,22.920,77.080,54.000,46.000,22.73,256,0.940,bicubic,-72.220,-44.770,+9 +vit_srelpos_small_patch16_224,22.907,77.093,55.733,44.267,21.97,224,0.900,bicubic,-72.123,-43.227,+24 +resmlp_big_24_224,22.853,77.147,54.293,45.707,129.14,224,0.875,bicubic,-71.807,-44.187,+59 +twins_pcpvt_small,22.707,77.293,56.853,43.147,24.11,224,0.900,bicubic,-72.503,-42.027,-6 +poolformer_m36,22.507,77.493,55.293,44.707,56.17,224,0.950,bicubic,-72.873,-43.557,-22 +vit_base_patch32_224,22.400,77.600,53.987,46.013,88.22,224,0.900,bicubic,-72.600,-45.043,+25 +pit_s_distilled_224,22.360,77.640,57.093,42.907,24.04,224,0.900,bicubic,-72.880,-41.957,-14 +xcit_tiny_12_p8_224_dist,22.067,77.933,54.280,45.720,6.71,224,1.000,bicubic,-73.033,-44.630,+7 +tresnet_m,21.667,78.333,53.840,46.160,31.39,224,0.875,bilinear,-74.043,-45.190,-70 +convmixer_1536_20,21.213,78.787,55.520,44.480,51.63,224,0.960,bicubic,-73.857,-43.510,+10 +swin_tiny_patch4_window7_224,21.147,78.853,55.973,44.027,28.29,224,0.900,bicubic,-73.983,-42.877,+1 +pit_s_224,21.093,78.907,53.587,46.413,23.46,224,0.900,bicubic,-73.497,-45.113,+56 +xcit_tiny_12_p8_224,21.027,78.973,52.467,47.533,6.71,224,1.000,bicubic,-73.663,-46.363,+45 +resnet51q,20.960,79.040,55.693,44.307,35.70,288,1.000,bilinear,-74.910,-43.437,-92 +regnetz_b16,20.933,79.067,53.853,46.147,9.72,288,0.940,bicubic,-74.127,-45.197,+7 +resnetrs101,20.867,79.133,52.813,47.187,63.62,288,0.940,bicubic,-74.563,-46.217,-40 +sebotnet33ts_256,20.733,79.267,48.787,51.213,13.70,256,0.940,bicubic,-73.847,-49.713,+52 +deit_small_distilled_patch16_224,20.707,79.293,55.147,44.853,22.44,224,0.900,bicubic,-74.003,-43.883,+38 +resnest50d_4s2x40d,20.373,79.627,52.827,47.173,30.42,224,0.875,bicubic,-74.587,-46.243,+16 +resnetaa50,20.093,79.907,52.000,48.000,25.56,288,1.000,bicubic,-75.117,-46.930,-23 +ssl_resnext50_32x4d,20.013,79.987,53.627,46.373,25.03,224,0.875,bilinear,-74.857,-45.263,+22 +haloregnetz_b,19.987,80.013,50.013,49.987,11.68,224,0.940,bicubic,-74.713,-48.647,+35 +resnetv2_101,19.960,80.040,49.227,50.773,44.54,224,0.950,bicubic,-75.660,-49.763,-75 +xcit_nano_12_p8_384_dist,19.800,80.200,50.573,49.427,3.05,384,1.000,bicubic,-73.720,-47.967,+151 +tresnet_xl,19.640,80.360,53.133,46.867,78.44,224,0.875,bilinear,-75.800,-45.917,-53 +gluon_senet154,19.333,80.667,47.573,52.427,115.09,224,0.875,bicubic,-75.587,-51.187,+13 +resnet101,19.320,80.680,49.587,50.413,44.55,224,0.950,bicubic,-76.040,-49.273,-41 +rexnet_200,19.227,80.773,52.720,47.280,16.37,224,0.875,bicubic,-75.723,-46.290,+8 +levit_256,19.187,80.813,50.093,49.907,18.89,224,0.900,bicubic,-75.823,-48.797,+1 +repvgg_b3,19.133,80.867,50.280,49.720,123.09,224,0.875,bilinear,-75.437,-48.500,+40 +lambda_resnet50ts,19.133,80.867,49.307,50.693,21.54,256,0.950,bicubic,-75.647,-49.153,+20 +mixer_b16_224_miil,19.040,80.960,51.227,48.773,59.88,224,0.875,bilinear,-76.260,-47.653,-42 +legacy_senet154,19.027,80.973,47.960,52.040,115.09,224,0.875,bilinear,-76.043,-50.870,-12 +gluon_seresnext101_64x4d,18.933,81.067,49.160,50.840,88.23,224,0.875,bicubic,-75.987,-49.670,+3 +deit_small_patch16_224,18.920,81.080,51.400,48.600,22.05,224,0.900,bicubic,-75.470,-47.290,+60 +mobilevitv2_200,18.920,81.080,50.560,49.440,18.45,256,0.888,bicubic,-75.910,-48.150,+13 +edgenext_small,18.667,81.333,53.600,46.400,5.59,320,1.000,bicubic,-76.743,-45.500,-56 +tf_efficientnet_b1_ns,18.667,81.333,51.693,48.307,7.79,240,0.882,bicubic,-76.513,-47.417,-37 +poolformer_s36,18.400,81.600,51.867,48.133,30.86,224,0.900,bicubic,-76.690,-47.043,-23 +seresnext50_32x4d,18.360,81.640,50.960,49.040,27.56,224,0.875,bicubic,-76.670,-47.920,-13 +cs3darknet_l,18.307,81.693,51.867,48.133,21.16,288,0.950,bicubic,-76.813,-47.113,-28 +ecaresnet50d,18.267,81.733,51.840,48.160,25.58,224,0.875,bicubic,-76.353,-47.050,+23 +cait_xxs36_224,18.267,81.733,49.427,50.573,17.30,224,1.000,bicubic,-75.993,-49.293,+63 +sehalonet33ts,18.227,81.773,47.787,52.213,13.69,256,0.940,bicubic,-76.553,-50.783,+6 +tf_efficientnet_lite4,18.133,81.867,50.720,49.280,13.01,380,0.920,bilinear,-76.747,-48.300,-4 +vit_tiny_patch16_384,18.013,81.987,50.333,49.667,5.79,384,1.000,bicubic,-75.637,-48.267,+120 +mobilevitv2_175,17.773,82.227,49.760,50.240,14.25,256,0.888,bicubic,-77.117,-49.100,-7 +resnest50d_1s4x24d,17.693,82.307,49.800,50.200,25.68,224,0.875,bicubic,-77.057,-49.180,+5 +resnest50d,17.360,82.640,50.733,49.267,27.48,224,0.875,bilinear,-77.490,-48.147,-4 +gluon_seresnext101_32x4d,17.360,82.640,46.373,53.627,48.96,224,0.875,bicubic,-77.560,-52.437,-12 +efficientnet_el,17.320,82.680,50.000,50.000,10.59,300,0.904,bicubic,-77.800,-48.980,-37 +inception_v4,17.280,82.720,45.933,54.067,42.68,299,0.875,bicubic,-77.100,-52.647,+44 +tf_efficientnet_b3_ap,17.200,82.800,49.667,50.333,12.23,300,0.904,bicubic,-78.120,-49.233,-65 +xcit_tiny_24_p16_224_dist,17.187,82.813,47.480,52.520,12.12,224,1.000,bicubic,-77.343,-51.300,+25 +tf_efficientnet_b3,17.000,83.000,49.267,50.733,12.23,300,0.904,bicubic,-78.010,-49.643,-26 +xception71,17.000,83.000,45.533,54.467,42.34,299,0.903,bicubic,-77.280,-53.107,+49 +cs3darknet_focus_l,16.973,83.027,50.480,49.520,21.15,288,0.950,bicubic,-78.197,-48.480,-55 resmlp_36_distilled_224,16.880,83.120,51.480,48.520,44.69,224,0.875,bicubic,-78.000,-47.360,-16 -tf_efficientnetv2_b3,16.653,83.347,48.680,51.320,14.36,300,0.904,bicubic,-78.507,-50.140,-48 -tresnet_l,16.587,83.413,49.933,50.067,55.99,224,0.875,bilinear,-78.703,-49.077,-58 -gluon_resnet152_v1s,16.573,83.427,44.520,55.480,60.32,224,0.875,bicubic,-78.467,-54.410,-34 -inception_resnet_v2,16.573,83.427,44.947,55.053,55.84,299,0.897,bicubic,-77.977,-53.803,+9 -gluon_resnet152_v1d,16.560,83.440,44.267,55.733,60.21,224,0.875,bicubic,-78.180,-54.473,-11 -gmlp_s16_224,16.547,83.453,45.107,54.893,19.42,224,0.875,bicubic,-77.603,-53.393,+53 -resmlp_24_distilled_224,16.453,83.547,50.387,49.613,30.02,224,0.875,bicubic,-78.007,-48.383,+19 -gluon_xception65,16.427,83.573,46.053,53.947,39.92,299,0.903,bicubic,-77.833,-52.517,+36 -gcresnet50t,16.360,83.640,48.227,51.773,25.90,256,0.900,bicubic,-78.490,-50.563,-23 -gernet_l,16.307,83.693,47.200,52.800,31.08,256,0.875,bilinear,-78.793,-51.700,-50 -wide_resnet50_2,16.307,83.693,48.413,51.587,68.88,224,0.875,bicubic,-78.763,-50.557,-46 -xcit_tiny_24_p16_224,16.293,83.707,45.973,54.027,12.12,224,1.000,bicubic,-77.777,-52.487,+54 -repvgg_b3g4,16.240,83.760,47.640,52.360,83.83,224,0.875,bilinear,-78.280,-51.330,+3 -ens_adv_inception_resnet_v2,16.240,83.760,43.640,56.360,55.84,299,0.897,bicubic,-77.920,-54.960,+44 -gcresnext50ts,16.227,83.773,46.533,53.467,15.67,256,0.900,bicubic,-78.263,-52.137,+4 -ssl_resnet50,15.920,84.080,49.387,50.613,25.56,224,0.875,bilinear,-78.530,-49.533,+11 -regnety_320,15.627,84.373,44.827,55.173,145.05,224,0.875,bicubic,-78.913,-54.023,-2 -ecaresnet101d_pruned,15.600,84.400,48.013,51.987,24.88,224,0.875,bicubic,-79.480,-50.967,-55 -convmixer_768_32,15.533,84.467,47.960,52.040,21.11,224,0.960,bicubic,-78.967,-50.890,-1 -ecaresnet26t,15.467,84.533,47.933,52.067,16.01,320,0.950,bicubic,-78.843,-50.787,+19 -coat_tiny,15.400,84.600,45.613,54.387,5.50,224,0.900,bicubic,-78.190,-52.807,+85 -skresnext50_32x4d,15.360,84.640,44.507,55.493,27.48,224,0.875,bicubic,-78.900,-53.953,+24 -ecaresnetlight,15.173,84.827,45.827,54.173,30.16,224,0.875,bicubic,-79.597,-52.973,-32 -cait_xxs24_224,15.160,84.840,44.947,55.053,11.96,224,1.000,bicubic,-78.440,-53.503,+80 -levit_192,14.893,85.107,44.973,55.027,10.95,224,0.900,bicubic,-79.277,-53.577,+31 -rexnet_150,14.720,85.280,46.920,53.080,9.73,224,0.875,bicubic,-79.760,-51.870,-4 -resnext50_32x4d,14.533,85.467,44.173,55.827,25.03,224,0.950,bicubic,-80.017,-54.617,-17 -efficientnet_el_pruned,14.507,85.493,46.093,53.907,10.59,300,0.904,bicubic,-79.893,-52.617,+3 -coat_lite_mini,14.493,85.507,44.507,55.493,11.01,224,0.900,bicubic,-79.557,-54.053,+39 -efficientnet_b2,14.440,85.560,46.080,53.920,9.11,288,1.000,bicubic,-80.170,-52.630,-25 -seresnet33ts,14.427,85.573,46.133,53.867,19.78,256,0.900,bicubic,-80.423,-52.657,-43 -poolformer_s24,14.267,85.733,47.240,52.760,21.39,224,0.900,bicubic,-80.283,-51.540,-23 -legacy_seresnext101_32x4d,14.160,85.840,43.000,57.000,48.96,224,0.875,bilinear,-80.200,-55.650,+1 -seresnet50,14.147,85.853,45.507,54.493,28.09,224,0.875,bicubic,-80.403,-53.373,-23 -fbnetv3_d,14.120,85.880,46.453,53.547,10.31,256,0.950,bilinear,-79.810,-52.287,+43 -eca_resnet33ts,14.093,85.907,47.373,52.627,19.68,256,0.900,bicubic,-80.097,-51.397,+17 -gernet_m,14.080,85.920,46.053,53.947,21.14,224,0.875,bilinear,-80.540,-52.807,-33 -gluon_resnext101_32x4d,13.867,86.133,41.667,58.333,44.18,224,0.875,bicubic,-80.673,-56.963,-24 -gcresnet33ts,13.760,86.240,45.040,54.960,19.88,256,0.900,bicubic,-80.710,-53.730,-15 -gluon_seresnext50_32x4d,13.613,86.387,43.720,56.280,27.56,224,0.875,bicubic,-80.717,-54.890,-2 -resmlp_36_224,13.507,86.493,46.693,53.307,44.69,224,0.875,bicubic,-80.693,-51.967,+10 -resnet50_gn,13.453,86.547,42.760,57.240,25.56,224,0.940,bicubic,-80.897,-55.950,-6 -repvgg_b2g4,13.413,86.587,43.827,56.173,61.76,224,0.875,bilinear,-80.427,-54.983,+41 -eca_botnext26ts_256,13.373,86.627,42.160,57.840,10.59,256,0.950,bicubic,-80.407,-56.340,+46 -regnetx_320,13.333,86.667,40.707,59.293,107.81,224,0.875,bicubic,-81.127,-58.033,-20 -ese_vovnet39b,13.320,86.680,43.813,56.187,24.57,224,0.875,bicubic,-80.770,-54.847,+19 -pit_xs_distilled_224,13.253,86.747,44.560,55.440,11.00,224,0.900,bicubic,-80.567,-54.110,+40 -efficientnet_b3_pruned,13.173,86.827,45.227,54.773,9.86,300,0.904,bicubic,-81.457,-53.663,-46 -gluon_resnet101_v1d,13.173,86.827,41.493,58.507,44.57,224,0.875,bicubic,-81.057,-57.237,-1 -mixnet_xl,13.107,86.893,43.253,56.747,11.90,224,0.875,bicubic,-81.083,-55.087,+4 -nf_regnet_b1,12.947,87.053,44.400,55.600,10.22,288,0.900,bicubic,-81.173,-54.220,+12 -eca_halonext26ts,12.933,87.067,42.773,57.227,10.76,256,0.940,bicubic,-81.117,-55.717,+17 -mobilevit_s,12.880,87.120,40.827,59.173,5.58,256,0.900,bicubic,-80.290,-57.613,+87 -pit_xs_224,12.827,87.173,42.827,57.173,10.62,224,0.900,bicubic,-80.283,-55.503,+90 -gluon_inception_v3,12.640,87.360,40.507,59.493,23.83,299,0.875,bicubic,-80.810,-58.063,+63 -crossvit_9_dagger_240,12.560,87.440,41.787,58.213,8.78,240,0.875,bicubic,-80.330,-56.463,+100 -coat_lite_tiny,12.533,87.467,41.120,58.880,5.72,224,0.900,bicubic,-80.697,-57.140,+79 -resmlp_24_224,12.493,87.507,43.427,56.573,30.02,224,0.875,bicubic,-81.527,-54.903,+13 -regnety_120,12.400,87.600,42.200,57.800,51.82,224,0.875,bicubic,-82.080,-56.610,-38 -efficientnet_em,12.360,87.640,43.867,56.133,6.90,240,0.882,bicubic,-81.480,-54.723,+25 -cspdarknet53,12.027,87.973,43.253,56.747,27.64,256,0.887,bilinear,-82.633,-55.547,-61 -hrnet_w64,12.013,87.987,40.800,59.200,128.06,224,0.875,bilinear,-81.997,-57.810,+10 -xcit_tiny_12_p16_224_dist,11.987,88.013,40.093,59.907,6.72,224,1.000,bicubic,-81.413,-58.257,+60 -gluon_resnet101_v1s,11.880,88.120,40.987,59.013,44.67,224,0.875,bicubic,-82.840,-57.833,-69 -gmixer_24_224,11.867,88.133,37.787,62.213,24.72,224,0.875,bicubic,-80.963,-60.393,+95 -nf_resnet50,11.760,88.240,45.947,54.053,25.56,288,0.940,bicubic,-82.790,-52.663,-54 -fbnetv3_b,11.747,88.253,44.387,55.613,8.60,256,0.950,bilinear,-82.223,-54.243,+7 -resnet50d,11.693,88.307,42.453,57.547,25.58,224,0.875,bicubic,-82.567,-56.267,-23 -dpn92,11.613,88.387,40.293,59.707,37.67,224,0.875,bicubic,-82.617,-58.267,-20 -xception41,11.600,88.400,39.147,60.853,26.97,299,0.903,bicubic,-81.830,-59.283,+50 +gluon_resnext101_64x4d,16.880,83.120,44.173,55.827,83.46,224,0.875,bicubic,-77.780,-54.477,+2 +tf_efficientnetv2_b3,16.667,83.333,48.680,51.320,14.36,300,0.904,bicubic,-78.493,-50.140,-54 +gluon_resnet152_v1d,16.600,83.400,44.293,55.707,60.21,224,0.875,bicubic,-78.140,-54.447,-7 +tresnet_l,16.573,83.427,49.947,50.053,55.99,224,0.875,bilinear,-78.717,-49.063,-71 +inception_resnet_v2,16.573,83.427,44.933,55.067,55.84,299,0.897,bicubic,-77.957,-53.847,+15 +gluon_resnet152_v1s,16.560,83.440,44.507,55.493,60.32,224,0.875,bicubic,-78.480,-54.423,-40 +gmlp_s16_224,16.547,83.453,45.120,54.880,19.42,224,0.875,bicubic,-77.613,-53.380,+57 +mobilevitv2_150,16.480,83.520,48.453,51.547,10.59,256,0.888,bicubic,-78.070,-50.257,+8 +resmlp_24_distilled_224,16.440,83.560,50.373,49.627,30.02,224,0.875,bicubic,-78.020,-48.397,+21 +gluon_xception65,16.440,83.560,46.040,53.960,39.92,299,0.903,bicubic,-77.820,-52.530,+40 +gcresnet50t,16.373,83.627,48.227,51.773,25.90,256,0.900,bicubic,-78.477,-50.563,-23 +gernet_l,16.347,83.653,47.213,52.787,31.08,256,0.875,bilinear,-78.743,-51.687,-53 +wide_resnet50_2,16.307,83.693,48.400,51.600,68.88,224,0.875,bicubic,-78.773,-50.570,-52 +xcit_tiny_24_p16_224,16.280,83.720,45.973,54.027,12.12,224,1.000,bicubic,-77.790,-52.557,+57 +gcresnext50ts,16.240,83.760,46.533,53.467,15.67,256,0.900,bicubic,-78.250,-52.137,+9 +repvgg_b3g4,16.227,83.773,47.640,52.360,83.83,224,0.875,bilinear,-78.293,-51.330,+6 +ens_adv_inception_resnet_v2,16.213,83.787,43.613,56.387,55.84,299,0.897,bicubic,-77.947,-54.987,+46 +edgenext_small_rw,15.960,84.040,49.667,50.333,7.83,320,1.000,bicubic,-78.700,-49.123,-16 +ssl_resnet50,15.920,84.080,49.400,50.600,25.56,224,0.875,bilinear,-78.520,-49.520,+13 +regnety_320,15.653,84.347,44.827,55.173,145.05,224,0.875,bicubic,-78.887,-54.033,-3 +ecaresnet101d_pruned,15.600,84.400,48.053,51.947,24.88,224,0.875,bicubic,-79.480,-50.927,-61 +convmixer_768_32,15.533,84.467,47.960,52.040,21.11,224,0.960,bicubic,-78.967,-50.890,+1 +ecaresnet26t,15.467,84.533,47.907,52.093,16.01,320,0.950,bicubic,-78.853,-50.813,+21 +coat_tiny,15.387,84.613,45.640,54.360,5.50,224,0.900,bicubic,-78.203,-52.780,+89 +skresnext50_32x4d,15.347,84.653,44.507,55.493,27.48,224,0.875,bicubic,-78.903,-53.953,+26 +vit_relpos_base_patch32_plus_rpn_256,15.240,84.760,42.613,57.387,119.42,256,0.900,bicubic,-78.490,-55.457,+76 +cait_xxs24_224,15.160,84.840,44.947,55.053,11.96,224,1.000,bicubic,-78.440,-53.493,+85 +ecaresnetlight,15.147,84.853,45.800,54.200,30.16,224,0.875,bicubic,-79.623,-53.000,-34 +levit_192,14.893,85.107,44.920,55.080,10.95,224,0.900,bicubic,-79.287,-53.620,+32 +rexnet_150,14.707,85.293,46.920,53.080,9.73,224,0.875,bicubic,-79.773,-51.870,-3 +darknet53,14.680,85.320,47.120,52.880,41.61,288,1.000,bicubic,-79.950,-51.770,-26 +darknetaa53,14.573,85.427,45.453,54.547,36.02,288,1.000,bilinear,-79.897,-53.307,-3 +resnext50_32x4d,14.533,85.467,44.187,55.813,25.03,224,0.950,bicubic,-80.007,-54.423,-14 +coat_lite_mini,14.493,85.507,44.547,55.453,11.01,224,0.900,bicubic,-79.557,-54.013,+39 +efficientnet_el_pruned,14.480,85.520,46.080,53.920,10.59,300,0.904,bicubic,-79.920,-52.660,0 +efficientnet_b2,14.440,85.560,46.067,53.933,9.11,288,1.000,bicubic,-80.170,-52.643,-27 +seresnet33ts,14.427,85.573,46.133,53.867,19.78,256,0.900,bicubic,-80.433,-52.657,-51 +poolformer_s24,14.267,85.733,47.227,52.773,21.39,224,0.900,bicubic,-80.283,-51.653,-25 +legacy_seresnext101_32x4d,14.160,85.840,43.013,56.987,48.96,224,0.875,bilinear,-80.210,-55.637,0 +seresnet50,14.147,85.853,45.507,54.493,28.09,224,0.875,bicubic,-80.403,-53.243,-25 +fbnetv3_d,14.107,85.893,46.480,53.520,10.31,256,0.950,bilinear,-79.823,-52.260,+43 +eca_resnet33ts,14.080,85.920,47.360,52.640,19.68,256,0.900,bicubic,-80.110,-51.400,+16 +gernet_m,14.053,85.947,46.013,53.987,21.14,224,0.875,bilinear,-80.567,-52.847,-35 +mobilevitv2_125,14.000,86.000,44.987,55.013,7.48,256,0.888,bicubic,-79.970,-53.573,+36 +gluon_resnext101_32x4d,13.867,86.133,41.653,58.347,44.18,224,0.875,bicubic,-80.673,-56.977,-27 +gcresnet33ts,13.760,86.240,45.053,54.947,19.88,256,0.900,bicubic,-80.710,-53.717,-18 +gluon_seresnext50_32x4d,13.613,86.387,43.720,56.280,27.56,224,0.875,bicubic,-80.717,-54.890,-4 +resmlp_36_224,13.520,86.480,46.693,53.307,44.69,224,0.875,bicubic,-80.680,-51.967,+9 +resnet50_gn,13.467,86.533,42.747,57.253,25.56,224,0.940,bicubic,-80.883,-55.963,-8 +repvgg_b2g4,13.427,86.573,43.827,56.173,61.76,224,0.875,bilinear,-80.413,-54.763,+41 +eca_botnext26ts_256,13.373,86.627,42.173,57.827,10.59,256,0.950,bicubic,-80.407,-56.327,+45 +ese_vovnet39b,13.333,86.667,43.813,56.187,24.57,224,0.875,bicubic,-80.757,-54.847,+18 +regnetx_320,13.320,86.680,40.720,59.280,107.81,224,0.875,bicubic,-81.140,-58.020,-22 +pit_xs_distilled_224,13.267,86.733,44.560,55.440,11.00,224,0.900,bicubic,-80.553,-54.110,+39 +efficientnet_b3_pruned,13.173,86.827,45.227,54.773,9.86,300,0.904,bicubic,-81.457,-53.533,-49 +gluon_resnet101_v1d,13.173,86.827,41.480,58.520,44.57,224,0.875,bicubic,-81.057,-57.070,-2 +mixnet_xl,13.120,86.880,43.240,56.760,11.90,224,0.875,bicubic,-81.070,-55.100,+3 +cspresnext50,13.053,86.947,45.000,55.000,20.57,256,0.887,bilinear,-81.777,-53.770,-68 +nf_regnet_b1,12.947,87.053,44.387,55.613,10.22,288,0.900,bicubic,-81.163,-54.243,+10 +eca_halonext26ts,12.933,87.067,42.800,57.200,10.76,256,0.940,bicubic,-81.107,-55.690,+14 +mobilevit_s,12.880,87.120,40.787,59.213,5.58,256,0.900,bicubic,-80.300,-57.653,+86 +pit_xs_224,12.813,87.187,42.827,57.173,10.62,224,0.900,bicubic,-80.307,-55.503,+91 +gluon_inception_v3,12.640,87.360,40.493,59.507,23.83,299,0.875,bicubic,-80.810,-58.077,+62 +crossvit_9_dagger_240,12.573,87.427,41.787,58.213,8.78,240,0.875,bicubic,-80.317,-56.463,+101 +coat_lite_tiny,12.547,87.453,41.133,58.867,5.72,224,0.900,bicubic,-80.683,-57.127,+80 +resmlp_24_224,12.507,87.493,43.427,56.573,30.02,224,0.875,bicubic,-81.513,-54.903,+10 +regnety_120,12.400,87.600,42.213,57.787,51.82,224,0.875,bicubic,-82.080,-56.597,-41 +efficientnet_em,12.360,87.640,43.853,56.147,6.90,240,0.882,bicubic,-81.480,-54.957,+22 +cspdarknet53,12.027,87.973,43.280,56.720,27.64,256,0.887,bilinear,-82.633,-55.520,-68 +hrnet_w64,12.000,88.000,40.813,59.187,128.06,224,0.875,bilinear,-82.020,-57.807,+5 +xcit_tiny_12_p16_224_dist,11.973,88.027,40.107,59.893,6.72,224,1.000,bicubic,-81.427,-58.373,+59 +gluon_resnet101_v1s,11.880,88.120,40.973,59.027,44.67,224,0.875,bicubic,-82.840,-57.847,-75 +gmixer_24_224,11.867,88.133,37.787,62.213,24.72,224,0.875,bicubic,-80.963,-60.093,+97 +nf_resnet50,11.760,88.240,45.933,54.067,25.56,288,0.940,bicubic,-82.790,-52.857,-60 +fbnetv3_b,11.733,88.267,44.387,55.613,8.60,256,0.950,bilinear,-82.237,-54.243,+4 +resnet50d,11.720,88.280,42.467,57.533,25.58,224,0.875,bicubic,-82.540,-56.253,-27 +dpn92,11.613,88.387,40.293,59.707,37.67,224,0.875,bicubic,-82.617,-58.437,-24 +dla102x2,11.600,88.400,41.267,58.733,41.28,224,0.875,bilinear,-82.370,-57.233,+3 +xception41,11.600,88.400,39.147,60.853,26.97,299,0.903,bicubic,-81.830,-59.283,+48 botnet26t_256,11.587,88.413,40.133,59.867,12.49,256,0.950,bicubic,-81.923,-58.167,+39 -dla102x2,11.560,88.440,41.307,58.693,41.28,224,0.875,bilinear,-82.400,-57.183,+3 -vit_small_patch32_224,11.480,88.520,39.533,60.467,22.88,224,0.900,bicubic,-80.560,-58.757,+133 -levit_128,11.440,88.560,40.173,59.827,9.21,224,0.900,bicubic,-81.880,-58.217,+58 -lambda_resnet26t,11.373,88.627,40.187,59.813,10.96,256,0.940,bicubic,-82.457,-58.463,+11 -efficientnet_b2_pruned,11.333,88.667,42.027,57.973,8.31,260,0.890,bicubic,-82.807,-56.503,-16 -tf_efficientnet_el,11.320,88.680,42.040,57.960,10.59,300,0.904,bicubic,-83.080,-56.700,-47 -xcit_nano_12_p16_384_dist,11.253,88.747,39.907,60.093,3.05,384,1.000,bicubic,-80.577,-58.113,+141 -halonet26t,11.107,88.893,38.813,61.187,12.48,256,0.950,bicubic,-82.913,-59.687,-9 -gluon_resnet152_v1c,11.093,88.907,37.133,62.867,60.21,224,0.875,bicubic,-83.067,-61.507,-22 -vit_tiny_r_s16_p8_384,11.093,88.907,40.013,59.987,6.36,384,1.000,bicubic,-80.947,-58.217,+124 -hrnet_w48,11.067,88.933,40.307,59.693,77.47,224,0.875,bilinear,-82.853,-58.303,-3 -dpn107,11.053,88.947,38.640,61.360,86.92,224,0.875,bicubic,-83.247,-59.830,-43 -adv_inception_v3,11.013,88.987,36.733,63.267,23.83,299,0.875,bicubic,-81.877,-61.407,+71 -ecaresnet50d_pruned,11.013,88.987,41.947,58.053,19.94,224,0.875,bicubic,-83.207,-56.783,-35 -tf_efficientnetv2_b2,11.013,88.987,39.760,60.240,10.10,260,0.890,bicubic,-83.407,-58.810,-57 -xcit_tiny_12_p16_224,10.973,89.027,37.013,62.987,6.72,224,1.000,bicubic,-81.527,-61.227,+97 -resnetv2_50,10.960,89.040,39.347,60.653,25.55,224,0.950,bicubic,-83.470,-59.393,-60 -tf_efficientnet_b0_ns,10.947,89.053,40.093,59.907,5.29,224,0.875,bicubic,-82.693,-58.547,+13 -tf_inception_v3,10.827,89.173,36.840,63.160,23.83,299,0.875,bicubic,-82.493,-61.540,+38 -xcit_nano_12_p8_224_dist,10.787,89.213,38.133,61.867,3.05,224,1.000,bicubic,-81.313,-60.027,+112 -dpn131,10.720,89.280,37.173,62.827,79.25,224,0.875,bicubic,-83.270,-61.547,-19 -tf_efficientnet_b2_ap,10.533,89.467,40.107,59.893,9.11,260,0.890,bicubic,-83.957,-58.513,-73 -resnext50d_32x4d,10.400,89.600,39.720,60.280,25.05,224,0.875,bicubic,-83.780,-58.850,-39 -rexnet_130,10.400,89.600,41.547,58.453,7.56,224,0.875,bicubic,-83.500,-56.853,-14 -hrnet_w44,10.320,89.680,39.493,60.507,67.06,224,0.875,bilinear,-83.230,-59.207,+11 -xcit_nano_12_p8_224,10.293,89.707,37.000,63.000,3.05,224,1.000,bicubic,-80.727,-60.790,+143 -lambda_resnet26rpt_256,10.253,89.747,38.107,61.893,10.99,256,0.940,bicubic,-83.457,-60.403,-1 -resnext101_32x8d,10.173,89.827,37.800,62.200,88.79,224,0.875,bilinear,-83.647,-60.780,-11 -cspresnext50,10.133,89.867,40.307,59.693,20.57,224,0.875,bilinear,-84.337,-58.373,-77 -dpn98,10.133,89.867,36.613,63.387,61.57,224,0.875,bicubic,-83.977,-61.967,-37 -regnetx_160,10.133,89.867,38.000,62.000,54.28,224,0.875,bicubic,-83.997,-60.740,-40 -resnet50,10.133,89.867,37.907,62.093,25.56,224,0.950,bicubic,-84.207,-60.533,-66 -legacy_seresnext50_32x4d,10.107,89.893,39.200,60.800,27.56,224,0.875,bilinear,-83.623,-59.380,-9 -resnetrs50,10.080,89.920,37.520,62.480,35.69,224,0.910,bicubic,-84.220,-61.120,-64 -inception_v3,10.027,89.973,35.227,64.773,23.83,299,0.875,bicubic,-82.693,-62.743,+63 -efficientnet_b1,10.000,90.000,37.560,62.440,7.79,256,1.000,bicubic,-83.250,-60.730,+28 -xception,9.960,90.040,38.040,61.960,22.86,299,0.897,bicubic,-83.510,-60.490,+9 -dpn68b,9.787,90.213,38.027,61.973,12.61,224,0.875,bicubic,-83.903,-60.493,-11 -gluon_resnet152_v1b,9.733,90.267,36.067,63.933,60.19,224,0.875,bicubic,-84.337,-62.443,-43 -tf_efficientnet_b2,9.653,90.347,38.880,61.120,9.11,260,0.890,bicubic,-84.707,-59.730,-76 -tf_efficientnet_lite3,9.653,90.347,38.987,61.013,8.20,300,0.904,bilinear,-84.547,-59.653,-60 -tf_efficientnet_cc_b1_8e,9.600,90.400,36.760,63.240,39.72,240,0.882,bicubic,-84.310,-61.500,-33 -res2net101_26w_4s,9.520,90.480,35.027,64.973,45.21,224,0.875,bilinear,-84.230,-63.283,-21 -legacy_seresnet152,9.333,90.667,37.413,62.587,66.82,224,0.875,bilinear,-84.067,-61.067,+9 -cspresnet50,9.267,90.733,39.653,60.347,21.62,256,0.887,bilinear,-84.473,-58.987,-22 -hrnet_w40,9.240,90.760,36.907,63.093,57.56,224,0.875,bilinear,-84.250,-61.673,-3 -resnet33ts,9.227,90.773,38.693,61.307,19.68,256,0.900,bicubic,-84.373,-59.847,-13 -regnetx_120,9.187,90.813,37.187,62.813,46.11,224,0.875,bicubic,-85.053,-61.463,-72 -seresnext26d_32x4d,9.147,90.853,36.840,63.160,16.81,224,0.875,bicubic,-83.553,-61.310,+50 -crossvit_tiny_240,9.080,90.920,34.600,65.400,7.01,240,0.875,bicubic,-81.160,-62.990,+137 -resnest26d,9.080,90.920,37.840,62.160,17.07,224,0.875,bilinear,-84.240,-60.190,+9 -vit_tiny_patch16_224,9.040,90.960,34.640,65.360,5.72,224,0.900,bicubic,-82.730,-63.400,+98 -vit_base_patch16_224_sam,8.987,91.013,36.173,63.827,86.57,224,0.900,bicubic,-85.153,-62.497,-63 -gluon_resnext50_32x4d,8.973,91.027,36.307,63.693,25.03,224,0.875,bicubic,-84.837,-62.103,-36 -rexnet_100,8.907,91.093,36.387,63.613,4.80,224,0.875,bicubic,-84.123,-61.803,+23 -seresnext26t_32x4d,8.893,91.107,36.920,63.080,16.81,224,0.875,bicubic,-83.927,-61.450,+34 -bat_resnext26ts,8.867,91.133,36.413,63.587,10.73,256,0.900,bicubic,-84.463,-61.937,-2 -mobilenetv3_large_100_miil,8.853,91.147,32.987,67.013,5.48,224,0.875,bilinear,-83.417,-64.653,+67 -mixnet_l,8.840,91.160,36.200,63.800,7.33,224,0.875,bicubic,-84.610,-62.020,-11 -convit_tiny,8.813,91.187,34.347,65.653,5.71,224,0.875,bicubic,-81.837,-63.393,+122 -resnet32ts,8.760,91.240,37.227,62.773,17.96,256,0.900,bicubic,-84.710,-61.263,-16 -levit_128s,8.720,91.280,33.120,66.880,7.78,224,0.900,bicubic,-83.230,-64.950,+77 -gcresnext26ts,8.680,91.320,35.707,64.293,10.48,256,0.900,bicubic,-84.090,-62.553,+30 -dla169,8.640,91.360,36.053,63.947,53.39,224,0.875,bilinear,-84.700,-62.537,-10 -mixer_b16_224,8.600,91.400,29.413,70.587,59.88,224,0.875,bicubic,-83.270,-68.507,+80 -hrnet_w30,8.587,91.413,37.040,62.960,37.71,224,0.875,bilinear,-84.603,-61.370,0 -legacy_seresnet101,8.533,91.467,36.013,63.987,49.33,224,0.875,bilinear,-84.767,-62.497,-5 -tf_efficientnet_b1_ap,8.453,91.547,35.253,64.747,7.79,240,0.882,bicubic,-85.237,-63.107,-40 -repvgg_b2,8.427,91.573,36.453,63.547,89.02,224,0.875,bilinear,-85.073,-62.087,-27 -resmlp_12_distilled_224,8.307,91.693,36.853,63.147,15.35,224,0.875,bicubic,-84.523,-61.027,+17 -resnetblur50,8.253,91.747,37.347,62.653,25.56,224,0.875,bicubic,-85.687,-61.233,-67 -crossvit_9_240,8.253,91.747,34.120,65.880,8.55,240,0.875,bicubic,-82.397,-63.620,+110 -dla102x,8.200,91.800,37.013,62.987,26.31,224,0.875,bilinear,-85.310,-61.497,-33 -eca_resnext26ts,8.080,91.920,35.960,64.040,10.30,256,0.900,bicubic,-84.530,-62.300,+33 -hrnet_w32,8.040,91.960,37.493,62.507,41.23,224,0.875,bilinear,-85.490,-60.967,-37 -gluon_resnet101_v1c,7.987,92.013,33.360,66.640,44.57,224,0.875,bicubic,-85.683,-65.060,-47 -gluon_resnet50_v1d,7.933,92.067,34.987,65.013,25.58,224,0.875,bicubic,-85.837,-63.403,-57 -res2net50_26w_8s,7.853,92.147,33.747,66.253,48.40,224,0.875,bilinear,-85.557,-64.533,-28 -dla60_res2next,7.773,92.227,34.973,65.027,17.03,224,0.875,bilinear,-85.407,-63.437,-11 -densenetblur121d,7.733,92.267,34.747,65.253,8.00,224,0.875,bicubic,-84.177,-63.323,+62 -mobilevit_xs,7.733,92.267,32.573,67.427,2.32,256,0.900,bicubic,-83.107,-65.347,+95 -deit_tiny_distilled_patch16_224,7.693,92.307,33.573,66.427,5.91,224,0.900,bicubic,-83.017,-63.997,+96 -tf_efficientnetv2_b1,7.693,92.307,34.627,65.373,8.14,240,0.882,bicubic,-86.247,-63.993,-77 -dla60_res2net,7.560,92.440,34.627,65.373,20.85,224,0.875,bilinear,-85.620,-63.793,-17 -efficientnet_b1_pruned,7.427,92.573,34.493,65.507,6.33,240,0.882,bicubic,-85.343,-63.547,+7 -wide_resnet101_2,7.360,92.640,34.133,65.867,126.89,224,0.875,bilinear,-86.360,-64.407,-61 -regnetx_064,7.347,92.653,34.347,65.653,26.21,224,0.875,bicubic,-86.543,-64.283,-76 -deit_tiny_patch16_224,7.320,92.680,30.680,69.320,5.72,224,0.900,bicubic,-82.360,-66.770,+108 -hardcorenas_e,7.240,92.760,33.293,66.707,8.07,224,0.875,bilinear,-85.340,-64.817,+19 -gluon_resnet101_v1b,7.240,92.760,32.747,67.253,44.55,224,0.875,bicubic,-86.510,-65.633,-68 -efficientnet_b0,7.213,92.787,34.013,65.987,5.29,224,0.875,bicubic,-85.477,-64.057,+9 -gluon_resnet50_v1s,7.213,92.787,33.480,66.520,25.68,224,0.875,bicubic,-86.407,-64.980,-60 -tf_efficientnet_b1,7.147,92.853,33.040,66.960,7.79,240,0.882,bicubic,-86.343,-65.320,-49 -tf_mixnet_l,7.147,92.853,31.600,68.400,7.33,224,0.875,bicubic,-86.173,-66.430,-35 -tf_efficientnet_cc_b0_8e,7.120,92.880,31.787,68.213,24.01,224,0.875,bicubic,-85.710,-66.353,-7 -convmixer_1024_20_ks9_p14,7.080,92.920,33.053,66.947,24.38,224,0.960,bicubic,-85.340,-65.217,+21 -seresnext26ts,7.053,92.947,34.933,65.067,10.39,256,0.900,bicubic,-85.637,-63.357,+4 -resmlp_12_224,7.000,93.000,33.933,66.067,15.35,224,0.875,bicubic,-85.210,-64.227,+30 -hardcorenas_f,6.827,93.173,34.120,65.880,8.20,224,0.875,bilinear,-86.123,-64.040,-17 -ese_vovnet19b_dw,6.733,93.267,33.400,66.600,6.54,224,0.875,bicubic,-85.547,-64.690,+23 -selecsls60b,6.720,93.280,33.293,66.707,32.77,224,0.875,bicubic,-86.570,-64.987,-38 -res2net50_26w_6s,6.707,93.293,31.627,68.373,37.05,224,0.875,bilinear,-86.703,-66.553,-51 -efficientnet_es,6.680,93.320,33.840,66.160,5.44,224,0.875,bicubic,-86.460,-64.580,-33 -legacy_seresnext26_32x4d,6.627,93.373,33.240,66.760,16.79,224,0.875,bicubic,-86.013,-64.890,0 -mixnet_m,6.627,93.373,32.053,67.947,5.01,224,0.875,bicubic,-85.803,-65.817,+11 -pit_ti_distilled_224,6.627,93.373,30.720,69.280,5.10,224,0.900,bicubic,-84.273,-67.000,+68 -tinynet_a,6.627,93.373,32.213,67.787,6.19,192,0.875,bicubic,-85.813,-65.867,+8 -poolformer_s12,6.560,93.440,34.467,65.533,11.92,224,0.900,bicubic,-86.060,-63.733,-3 -skresnet34,6.480,93.520,31.573,68.427,22.28,224,0.875,bicubic,-85.910,-66.577,+11 -repvgg_b1,6.453,93.547,33.787,66.213,57.42,224,0.875,bilinear,-86.877,-64.723,-54 -hardcorenas_d,6.427,93.573,32.213,67.787,7.50,224,0.875,bilinear,-85.973,-65.857,+7 -dla60x,6.413,93.587,34.093,65.907,17.35,224,0.875,bilinear,-86.697,-64.417,-40 -resnet34d,6.400,93.600,31.480,68.520,21.82,224,0.875,bicubic,-86.280,-66.830,-11 -regnetx_080,6.307,93.693,32.307,67.693,39.57,224,0.875,bicubic,-87.563,-66.213,-102 -swsl_resnet18,6.240,93.760,31.600,68.400,11.69,224,0.875,bilinear,-84.450,-66.100,+65 -legacy_seresnet50,6.187,93.813,32.653,67.347,28.09,224,0.875,bilinear,-86.773,-65.527,-35 -resnet26t,6.107,93.893,32.240,67.760,16.01,256,0.940,bicubic,-86.643,-65.990,-23 -pit_ti_224,6.107,93.893,30.213,69.787,4.85,224,0.900,bicubic,-83.843,-67.237,+76 -tv_resnet152,6.027,93.973,32.053,67.947,60.19,224,0.875,bilinear,-87.293,-66.577,-61 -regnetx_040,5.973,94.027,31.573,68.427,22.12,224,0.875,bicubic,-87.577,-66.977,-83 -tf_efficientnet_cc_b0_4e,5.973,94.027,29.600,70.400,13.31,224,0.875,bicubic,-86.627,-68.480,-13 -tf_efficientnetv2_b0,5.907,94.093,30.787,69.213,7.14,224,0.875,bicubic,-87.203,-67.603,-48 -mixer_l16_224,5.880,94.120,18.533,81.467,208.20,224,0.875,bicubic,-81.270,-74.977,+95 -dla102,5.867,94.133,32.747,67.253,33.27,224,0.875,bilinear,-87.193,-65.793,-49 -regnety_016,5.680,94.320,30.440,69.560,11.20,224,0.875,bicubic,-87.350,-67.920,-48 -selecsls60,5.653,94.347,32.493,67.507,30.67,224,0.875,bicubic,-87.367,-65.817,-47 -hardcorenas_c,5.640,94.360,30.400,69.600,5.52,224,0.875,bilinear,-86.380,-67.440,+10 -res2next50,5.640,94.360,30.853,69.147,24.67,224,0.875,bilinear,-87.220,-67.337,-42 -hrnet_w18,5.493,94.507,30.947,69.053,21.30,224,0.875,bilinear,-86.827,-67.303,-7 -resnest14d,5.467,94.533,28.547,71.453,10.61,224,0.875,bilinear,-86.253,-69.323,+22 -tf_efficientnet_lite2,5.360,94.640,30.893,69.107,6.09,260,0.890,bicubic,-87.290,-67.337,-28 -tf_efficientnet_em,5.347,94.653,31.107,68.893,6.90,240,0.882,bicubic,-87.583,-67.093,-49 -gernet_s,5.307,94.693,30.120,69.880,8.17,224,0.875,bilinear,-86.833,-68.070,-2 -tf_efficientnet_b0_ap,5.307,94.693,28.800,71.200,5.29,224,0.875,bicubic,-86.893,-69.220,-5 -densenet121,5.293,94.707,29.880,70.120,7.98,224,0.875,bicubic,-86.287,-68.150,+18 -repvgg_b1g4,5.280,94.720,30.813,69.187,39.97,224,0.875,bilinear,-87.700,-67.617,-56 -xcit_nano_12_p16_224_dist,5.240,94.760,26.560,73.440,3.05,224,1.000,bicubic,-84.440,-70.530,+61 -res2net50_26w_4s,5.160,94.840,29.373,70.627,25.70,224,0.875,bilinear,-87.330,-68.687,-24 -tf_mixnet_m,5.080,94.920,28.133,71.867,5.01,224,0.875,bicubic,-87.250,-69.757,-18 -vit_tiny_r_s16_p8_224,5.080,94.920,27.053,72.947,6.34,224,0.900,bicubic,-84.100,-70.177,+62 -mobilenetv3_large_100,5.067,94.933,28.200,71.800,5.48,224,0.875,bicubic,-86.263,-69.510,+17 -tf_efficientnet_b0,5.067,94.933,28.787,71.213,5.29,224,0.875,bicubic,-87.183,-69.213,-16 -res2net50_14w_8s,5.040,94.960,28.773,71.227,25.06,224,0.875,bilinear,-87.700,-69.407,-46 -hardcorenas_b,4.947,95.053,28.107,71.893,5.18,224,0.875,bilinear,-86.833,-69.673,+5 -mixnet_s,4.907,95.093,28.573,71.427,4.13,224,0.875,bicubic,-86.923,-69.117,+2 -mobilenetv3_rw,4.907,95.093,29.853,70.147,5.48,224,0.875,bicubic,-86.303,-67.807,+15 -gluon_resnet50_v1c,4.893,95.107,28.133,71.867,25.58,224,0.875,bicubic,-88.137,-70.257,-71 -hardcorenas_a,4.880,95.120,28.107,71.893,5.26,224,0.875,bilinear,-86.470,-69.753,+9 -regnetx_032,4.853,95.147,30.280,69.720,15.30,224,0.875,bicubic,-88.267,-68.110,-78 -tv_resnext50_32x4d,4.840,95.160,30.307,69.693,25.03,224,0.875,bilinear,-87.910,-67.963,-54 -xcit_nano_12_p16_224,4.840,95.160,25.453,74.547,3.05,224,1.000,bicubic,-83.770,-71.337,+59 -densenet161,4.720,95.280,29.533,70.467,28.68,224,0.875,bicubic,-87.780,-68.757,-40 -tv_resnet101,4.693,95.307,29.373,70.627,44.55,224,0.875,bilinear,-88.127,-68.877,-63 -resnext26ts,4.693,95.307,29.013,70.987,10.30,256,0.900,bicubic,-87.177,-68.237,-9 -selecsls42b,4.667,95.333,28.587,71.413,32.46,224,0.875,bicubic,-87.613,-69.543,-31 -tf_efficientnet_lite1,4.613,95.387,28.400,71.600,5.42,240,0.882,bicubic,-88.007,-69.680,-50 -mobilenetv2_120d,4.533,95.467,29.280,70.720,5.83,224,0.875,bicubic,-87.867,-68.770,-38 +vit_small_patch32_224,11.480,88.520,39.547,60.453,22.88,224,0.900,bicubic,-80.550,-58.683,+135 +levit_128,11.387,88.613,40.240,59.760,9.21,224,0.900,bicubic,-81.943,-58.140,+53 +tf_efficientnet_el,11.373,88.627,42.040,57.960,10.59,300,0.904,bicubic,-83.027,-56.670,-47 +lambda_resnet26t,11.373,88.627,40.173,59.827,10.96,256,0.940,bicubic,-82.457,-58.477,+8 +efficientnet_b2_pruned,11.347,88.653,42.013,57.987,8.31,260,0.890,bicubic,-82.803,-56.517,-20 +xcit_nano_12_p16_384_dist,11.227,88.773,39.853,60.147,3.05,384,1.000,bicubic,-80.603,-58.167,+141 +halonet26t,11.120,88.880,38.813,61.187,12.48,256,0.950,bicubic,-82.890,-59.687,-10 +hrnet_w48,11.093,88.907,40.293,59.707,77.47,224,0.875,bilinear,-82.827,-58.317,-3 +vit_tiny_r_s16_p8_384,11.093,88.907,39.973,60.027,6.36,384,1.000,bicubic,-80.947,-58.317,+126 +gluon_resnet152_v1c,11.093,88.907,37.120,62.880,60.21,224,0.875,bicubic,-83.067,-61.520,-28 +dpn107,11.053,88.947,38.640,61.360,86.92,224,0.875,bicubic,-83.257,-59.830,-46 +ecaresnet50d_pruned,11.013,88.987,41.960,58.040,19.94,224,0.875,bicubic,-83.207,-56.770,-37 +mobilevitv2_100,11.013,88.987,40.653,59.347,4.90,256,0.888,bicubic,-82.287,-57.627,+48 +tf_efficientnetv2_b2,11.000,89.000,39.760,60.240,10.10,260,0.890,bicubic,-83.420,-58.810,-60 +adv_inception_v3,11.000,89.000,36.720,63.280,23.83,299,0.875,bicubic,-81.880,-61.420,+71 +tf_efficientnet_b0_ns,10.973,89.027,40.067,59.933,5.29,224,0.875,bicubic,-82.657,-58.573,+13 +xcit_tiny_12_p16_224,10.973,89.027,37.027,62.973,6.72,224,1.000,bicubic,-81.527,-61.213,+97 +resnetv2_50,10.960,89.040,39.333,60.667,25.55,224,0.950,bicubic,-83.470,-59.397,-65 +tf_inception_v3,10.813,89.187,36.840,63.160,23.83,299,0.875,bicubic,-82.507,-61.190,+39 +xcit_nano_12_p8_224_dist,10.800,89.200,38.120,61.880,3.05,224,1.000,bicubic,-81.300,-60.030,+113 +dpn131,10.720,89.280,37.187,62.813,79.25,224,0.875,bicubic,-83.270,-61.533,-23 +tf_efficientnet_b2_ap,10.533,89.467,40.107,59.893,9.11,260,0.890,bicubic,-83.957,-58.513,-77 +resnext50d_32x4d,10.413,89.587,39.733,60.267,25.05,224,0.875,bicubic,-83.777,-58.827,-44 +rexnet_130,10.400,89.600,41.547,58.453,7.56,224,0.875,bicubic,-83.500,-56.853,-17 +hrnet_w44,10.307,89.693,39.480,60.520,67.06,224,0.875,bilinear,-83.243,-59.220,+10 +xcit_nano_12_p8_224,10.293,89.707,37.000,63.000,3.05,224,1.000,bicubic,-80.727,-60.790,+146 +lambda_resnet26rpt_256,10.253,89.747,38.107,61.893,10.99,256,0.940,bicubic,-83.467,-60.413,-4 +resnext101_32x8d,10.173,89.827,37.800,62.200,88.79,224,0.875,bilinear,-83.647,-60.780,-14 +regnetx_160,10.147,89.853,38.000,62.000,54.28,224,0.875,bicubic,-83.983,-60.740,-42 +dpn98,10.133,89.867,36.587,63.413,61.57,224,0.875,bicubic,-83.987,-61.993,-42 +resnet50,10.120,89.880,37.907,62.093,25.56,224,0.950,bicubic,-84.220,-60.533,-69 +legacy_seresnext50_32x4d,10.093,89.907,39.200,60.800,27.56,224,0.875,bilinear,-83.637,-59.380,-11 +resnetrs50,10.067,89.933,37.507,62.493,35.69,224,0.910,bicubic,-84.233,-61.133,-67 +inception_v3,10.027,89.973,35.227,64.773,23.83,299,0.875,bicubic,-82.693,-62.743,+65 +xception,9.987,90.013,38.040,61.960,22.86,299,0.897,bicubic,-83.483,-60.490,+8 +efficientnet_b1,9.987,90.013,37.560,62.440,7.79,256,1.000,bicubic,-83.253,-60.740,+28 +dpn68b,9.787,90.213,38.027,61.973,12.61,224,0.875,bicubic,-83.903,-60.493,-12 +gluon_resnet152_v1b,9.747,90.253,36.080,63.920,60.19,224,0.875,bicubic,-84.323,-62.380,-46 +tf_efficientnet_lite3,9.653,90.347,38.987,61.013,8.20,300,0.904,bilinear,-84.557,-59.653,-63 +tf_efficientnet_b2,9.653,90.347,38.893,61.107,9.11,260,0.890,bicubic,-84.707,-59.717,-80 +tf_efficientnet_cc_b1_8e,9.600,90.400,36.787,63.213,39.72,240,0.882,bicubic,-84.310,-61.473,-35 +res2net101_26w_4s,9.520,90.480,35.027,64.973,45.21,224,0.875,bilinear,-84.230,-63.283,-23 +legacy_seresnet152,9.333,90.667,37.427,62.573,66.82,224,0.875,bilinear,-84.057,-60.913,+8 +cspresnet50,9.293,90.707,39.613,60.387,21.62,256,0.887,bilinear,-84.437,-59.027,-24 +resnet33ts,9.240,90.760,38.667,61.333,19.68,256,0.900,bicubic,-84.360,-59.863,-14 +hrnet_w40,9.227,90.773,36.880,63.120,57.56,224,0.875,bilinear,-84.263,-61.700,-4 +regnetx_120,9.187,90.813,37.187,62.813,46.11,224,0.875,bicubic,-85.053,-61.463,-75 +seresnext26d_32x4d,9.147,90.853,36.813,63.187,16.81,224,0.875,bicubic,-83.543,-61.337,+53 +crossvit_tiny_240,9.107,90.893,34.600,65.400,7.01,240,0.875,bicubic,-81.133,-62.990,+141 +resnest26d,9.067,90.933,37.840,62.160,17.07,224,0.875,bilinear,-84.263,-60.790,+4 +vit_tiny_patch16_224,9.053,90.947,34.627,65.373,5.72,224,0.900,bicubic,-82.717,-63.413,+99 +vit_base_patch16_224_sam,8.987,91.013,36.173,63.827,86.57,224,0.900,bicubic,-85.153,-62.497,-66 +gluon_resnext50_32x4d,8.973,91.027,36.307,63.693,25.03,224,0.875,bicubic,-84.837,-62.103,-38 +rexnet_100,8.907,91.093,36.373,63.627,4.80,224,0.875,bicubic,-84.123,-61.817,+24 +seresnext26t_32x4d,8.893,91.107,36.893,63.107,16.81,224,0.875,bicubic,-83.927,-61.477,+36 +bat_resnext26ts,8.867,91.133,36.413,63.587,10.73,256,0.900,bicubic,-84.463,-61.937,0 +mixnet_l,8.853,91.147,36.213,63.787,7.33,224,0.875,bicubic,-84.597,-62.007,-11 +mobilenetv3_large_100_miil,8.853,91.147,33.080,66.920,5.48,224,0.875,bilinear,-83.417,-64.560,+68 +convit_tiny,8.813,91.187,34.360,65.640,5.71,224,0.875,bicubic,-81.827,-63.380,+125 +resnet32ts,8.760,91.240,37.227,62.773,17.96,256,0.900,bicubic,-84.700,-61.263,-16 +gcresnext26ts,8.707,91.293,35.733,64.267,10.48,256,0.900,bicubic,-84.073,-62.527,+32 +levit_128s,8.707,91.293,33.160,66.840,7.78,224,0.900,bicubic,-83.223,-64.910,+79 +dla169,8.653,91.347,35.947,64.053,53.39,224,0.875,bilinear,-84.687,-62.643,-10 +hrnet_w30,8.600,91.400,37.027,62.973,37.71,224,0.875,bilinear,-84.600,-61.383,+2 +mixer_b16_224,8.600,91.400,29.440,70.560,59.88,224,0.875,bicubic,-83.270,-67.810,+81 +legacy_seresnet101,8.533,91.467,36.013,63.987,49.33,224,0.875,bilinear,-84.757,-62.497,-4 +tf_efficientnet_b1_ap,8.453,91.547,35.227,64.773,7.79,240,0.882,bicubic,-85.227,-63.133,-41 +repvgg_b2,8.427,91.573,36.453,63.547,89.02,224,0.875,bilinear,-85.063,-62.277,-27 +resmlp_12_distilled_224,8.307,91.693,36.840,63.160,15.35,224,0.875,bicubic,-84.533,-61.300,+19 +resnetblur50,8.253,91.747,37.373,62.627,25.56,224,0.875,bicubic,-85.687,-61.207,-67 +crossvit_9_240,8.253,91.747,34.107,65.893,8.55,240,0.875,bicubic,-82.377,-63.633,+114 +dla102x,8.213,91.787,37.040,62.960,26.31,224,0.875,bilinear,-85.307,-61.460,-34 +eca_resnext26ts,8.080,91.920,35.960,64.040,10.30,256,0.900,bicubic,-84.530,-62.300,+35 +hrnet_w32,8.027,91.973,37.520,62.480,41.23,224,0.875,bilinear,-85.503,-60.940,-38 +cs3darknet_m,7.987,92.013,36.507,63.493,9.31,288,0.950,bicubic,-85.373,-62.093,-23 +gluon_resnet101_v1c,7.987,92.013,33.360,66.640,44.57,224,0.875,bicubic,-85.683,-65.060,-49 +gluon_resnet50_v1d,7.933,92.067,35.000,65.000,25.58,224,0.875,bicubic,-85.837,-63.390,-60 +dla60_res2next,7.827,92.173,34.987,65.013,17.03,224,0.875,bilinear,-85.343,-63.413,-10 +res2net50_26w_8s,7.827,92.173,33.720,66.280,48.40,224,0.875,bilinear,-85.593,-64.450,-31 +mobilevitv2_075,7.827,92.173,33.693,66.307,2.87,256,0.888,bicubic,-83.933,-64.167,+71 +mobilevit_xs,7.747,92.253,32.533,67.467,2.32,256,0.900,bicubic,-83.073,-65.387,+98 +densenetblur121d,7.733,92.267,34.773,65.227,8.00,224,0.875,bicubic,-84.177,-63.297,+61 +tf_efficientnetv2_b1,7.707,92.293,34.653,65.347,8.14,240,0.882,bicubic,-86.233,-63.967,-81 +deit_tiny_distilled_patch16_224,7.693,92.307,33.547,66.453,5.91,224,0.900,bicubic,-83.017,-64.023,+97 +dla60_res2net,7.600,92.400,34.600,65.400,20.85,224,0.875,bilinear,-85.560,-63.800,-16 +efficientnet_b1_pruned,7.427,92.573,34.507,65.493,6.33,240,0.882,bicubic,-85.343,-63.533,+8 +wide_resnet101_2,7.360,92.640,34.160,65.840,126.89,224,0.875,bilinear,-86.350,-64.380,-63 +regnetx_064,7.347,92.653,34.373,65.627,26.21,224,0.875,bicubic,-86.543,-64.257,-80 +deit_tiny_patch16_224,7.320,92.680,30.707,69.293,5.72,224,0.900,bicubic,-82.340,-66.743,+112 +hardcorenas_e,7.253,92.747,33.293,66.707,8.07,224,0.875,bilinear,-85.317,-64.807,+20 +gluon_resnet101_v1b,7.240,92.760,32.773,67.227,44.55,224,0.875,bicubic,-86.510,-65.607,-73 +efficientnet_b0,7.227,92.773,34.013,65.987,5.29,224,0.875,bicubic,-85.463,-64.057,+10 +gluon_resnet50_v1s,7.213,92.787,33.493,66.507,25.68,224,0.875,bicubic,-86.407,-64.967,-63 +tf_efficientnet_b1,7.147,92.853,33.053,66.947,7.79,240,0.882,bicubic,-86.353,-65.307,-54 +tf_mixnet_l,7.147,92.853,31.627,68.373,7.33,224,0.875,bicubic,-86.173,-66.403,-36 +tf_efficientnet_cc_b0_8e,7.120,92.880,31.827,68.173,24.01,224,0.875,bicubic,-85.710,-66.353,-7 +convmixer_1024_20_ks9_p14,7.080,92.920,33.067,66.933,24.38,224,0.960,bicubic,-85.350,-65.203,+20 +seresnext26ts,7.053,92.947,34.920,65.080,10.39,256,0.900,bicubic,-85.637,-63.370,+2 +resmlp_12_224,7.013,92.987,33.947,66.053,15.35,224,0.875,bicubic,-85.197,-64.213,+29 +cs3darknet_focus_m,6.947,93.053,34.640,65.360,9.30,288,0.950,bicubic,-86.023,-63.750,-19 +hardcorenas_f,6.853,93.147,34.067,65.933,8.20,224,0.875,bilinear,-86.107,-64.093,-18 +selecsls60b,6.733,93.267,33.253,66.747,32.77,224,0.875,bicubic,-86.557,-65.027,-39 +res2net50_26w_6s,6.720,93.280,31.640,68.360,37.05,224,0.875,bilinear,-86.690,-66.640,-54 +ese_vovnet19b_dw,6.707,93.293,33.400,66.600,6.54,224,0.875,bicubic,-85.573,-64.690,+21 +efficientnet_es,6.680,93.320,33.827,66.173,5.44,224,0.875,bicubic,-86.460,-64.593,-35 +tinynet_a,6.640,93.360,32.227,67.773,6.19,192,0.875,bicubic,-85.800,-65.853,+10 +mixnet_m,6.640,93.360,32.053,67.947,5.01,224,0.875,bicubic,-85.790,-65.807,+11 +pit_ti_distilled_224,6.627,93.373,30.747,69.253,5.10,224,0.900,bicubic,-84.273,-66.973,+68 +legacy_seresnext26_32x4d,6.613,93.387,33.280,66.720,16.79,224,0.875,bicubic,-86.027,-64.850,-4 +poolformer_s12,6.560,93.440,34.453,65.547,11.92,224,0.900,bicubic,-86.070,-63.747,-4 +repvgg_b1,6.467,93.533,33.813,66.187,57.42,224,0.875,bilinear,-86.853,-64.697,-54 +skresnet34,6.467,93.533,31.587,68.413,22.28,224,0.875,bicubic,-85.923,-66.563,+8 +dla60x,6.427,93.573,34.120,65.880,17.35,224,0.875,bilinear,-86.693,-64.390,-42 +hardcorenas_d,6.413,93.587,32.200,67.800,7.50,224,0.875,bilinear,-85.977,-65.880,+7 +resnet34d,6.400,93.600,31.507,68.493,21.82,224,0.875,bicubic,-86.280,-66.803,-12 +edgenext_x_small,6.373,93.627,29.720,70.280,2.34,256,0.900,bicubic,-84.717,-67.830,+53 +regnetx_080,6.307,93.693,32.333,67.667,39.57,224,0.875,bicubic,-87.563,-66.187,-108 +swsl_resnet18,6.253,93.747,31.600,68.400,11.69,224,0.875,bilinear,-84.437,-66.100,+65 +legacy_seresnet50,6.187,93.813,32.653,67.347,28.09,224,0.875,bilinear,-86.783,-65.537,-37 +resnet26t,6.133,93.867,32.227,67.773,16.01,256,0.940,bicubic,-86.617,-66.003,-24 +pit_ti_224,6.107,93.893,30.240,69.760,4.85,224,0.900,bicubic,-83.843,-67.200,+75 +tv_resnet152,6.027,93.973,32.067,67.933,60.19,224,0.875,bilinear,-87.283,-66.323,-62 +tf_efficientnet_cc_b0_4e,5.987,94.013,29.587,70.413,13.31,224,0.875,bicubic,-86.603,-68.493,-14 +regnetx_040,5.973,94.027,31.587,68.413,22.12,224,0.875,bicubic,-87.587,-66.963,-90 +tf_efficientnetv2_b0,5.893,94.107,30.773,69.227,7.14,224,0.875,bicubic,-87.217,-67.617,-51 +mixer_l16_224,5.867,94.133,18.533,81.467,208.20,224,0.875,bicubic,-81.273,-74.987,+98 +dla102,5.853,94.147,32.720,67.280,33.27,224,0.875,bilinear,-87.207,-65.830,-52 +selecsls60,5.667,94.333,32.493,67.507,30.67,224,0.875,bicubic,-87.353,-65.807,-49 +regnety_016,5.653,94.347,30.440,69.560,11.20,224,0.875,bicubic,-87.377,-67.910,-52 +res2next50,5.640,94.360,30.867,69.133,24.67,224,0.875,bilinear,-87.220,-67.323,-43 +hardcorenas_c,5.640,94.360,30.453,69.547,5.52,224,0.875,bilinear,-86.390,-67.387,+7 +hrnet_w18,5.493,94.507,30.987,69.013,21.30,224,0.875,bilinear,-86.827,-67.263,-10 +resnest14d,5.467,94.533,28.547,71.453,10.61,224,0.875,bilinear,-86.253,-69.323,+21 +tf_efficientnet_lite2,5.360,94.640,30.920,69.080,6.09,260,0.890,bicubic,-87.290,-67.310,-30 +tf_efficientnet_em,5.347,94.653,31.107,68.893,6.90,240,0.882,bicubic,-87.583,-67.093,-51 +tf_efficientnet_b0_ap,5.307,94.693,28.827,71.173,5.29,224,0.875,bicubic,-86.893,-69.193,-6 +gernet_s,5.293,94.707,30.107,69.893,8.17,224,0.875,bilinear,-86.847,-68.093,-5 +densenet121,5.293,94.707,29.893,70.107,7.98,224,0.875,bicubic,-86.287,-68.137,+17 +repvgg_b1g4,5.280,94.720,30.800,69.200,39.97,224,0.875,bilinear,-87.700,-67.630,-59 +xcit_nano_12_p16_224_dist,5.240,94.760,26.560,73.440,3.05,224,1.000,bicubic,-84.450,-70.540,+59 +res2net50_26w_4s,5.160,94.840,29.373,70.627,25.70,224,0.875,bilinear,-87.330,-68.687,-26 +vit_tiny_r_s16_p8_224,5.080,94.920,27.067,72.933,6.34,224,0.900,bicubic,-84.100,-70.163,+63 +mobilenetv3_large_100,5.067,94.933,28.187,71.813,5.48,224,0.875,bicubic,-86.263,-69.533,+17 +tf_mixnet_m,5.067,94.933,28.147,71.853,5.01,224,0.875,bicubic,-87.253,-69.743,-21 +tf_efficientnet_b0,5.053,94.947,28.720,71.280,5.29,224,0.875,bicubic,-87.197,-69.270,-18 +res2net50_14w_8s,5.040,94.960,28.773,71.227,25.06,224,0.875,bilinear,-87.700,-69.407,-48 +hardcorenas_b,4.947,95.053,28.067,71.933,5.18,224,0.875,bilinear,-86.813,-69.713,+5 +mixnet_s,4.920,95.080,28.547,71.453,4.13,224,0.875,bicubic,-86.900,-69.143,+1 +mobilenetv3_rw,4.907,95.093,29.853,70.147,5.48,224,0.875,bicubic,-86.303,-67.807,+14 +gluon_resnet50_v1c,4.893,95.107,28.147,71.853,25.58,224,0.875,bicubic,-88.137,-70.243,-74 +hardcorenas_a,4.880,95.120,28.093,71.907,5.26,224,0.875,bilinear,-86.470,-69.767,+8 +regnetx_032,4.853,95.147,30.253,69.747,15.30,224,0.875,bicubic,-88.267,-68.137,-80 +xcit_nano_12_p16_224,4.853,95.147,25.453,74.547,3.05,224,1.000,bicubic,-83.757,-71.337,+61 +tv_resnext50_32x4d,4.840,95.160,30.280,69.720,25.03,224,0.875,bilinear,-87.910,-68.000,-59 +densenet161,4.720,95.280,29.560,70.440,28.68,224,0.875,bicubic,-87.780,-68.730,-42 +tv_resnet101,4.720,95.280,29.373,70.627,44.55,224,0.875,bilinear,-88.100,-68.877,-64 +resnext26ts,4.680,95.320,29.013,70.987,10.30,256,0.900,bicubic,-87.190,-68.907,-12 +selecsls42b,4.667,95.333,28.613,71.387,32.46,224,0.875,bicubic,-87.613,-69.527,-34 +tf_efficientnet_lite1,4.613,95.387,28.413,71.587,5.42,240,0.882,bicubic,-88.007,-69.667,-52 +mobilenetv2_120d,4.533,95.467,29.293,70.707,5.83,224,0.875,bicubic,-87.867,-68.757,-41 vit_base_patch32_224_sam,4.333,95.667,24.387,75.613,88.22,224,0.900,bicubic,-85.417,-72.613,+37 -efficientnet_es_pruned,4.213,95.787,26.533,73.467,5.44,224,0.875,bicubic,-86.967,-71.217,+4 -tinynet_b,4.187,95.813,26.707,73.293,3.73,188,0.875,bicubic,-86.743,-70.963,+12 +tinynet_b,4.187,95.813,26.720,73.280,3.73,188,0.875,bicubic,-86.733,-70.950,+13 +efficientnet_es_pruned,4.187,95.813,26.547,73.453,5.44,224,0.875,bicubic,-86.993,-71.203,+2 fbnetc_100,4.133,95.867,25.933,74.067,5.57,224,0.875,bilinear,-86.577,-71.277,+18 -gluon_resnet50_v1b,4.120,95.880,26.920,73.080,25.56,224,0.875,bicubic,-88.420,-71.250,-52 -densenet201,4.120,95.880,27.547,72.453,20.01,224,0.875,bicubic,-88.630,-70.683,-68 -resnet26d,4.027,95.973,28.507,71.493,16.01,224,0.875,bicubic,-88.043,-69.463,-31 -semnasnet_100,3.960,96.040,26.947,73.053,3.89,224,0.875,bicubic,-87.310,-70.613,-6 -repvgg_a2,3.933,96.067,27.267,72.733,28.21,224,0.875,bilinear,-88.007,-70.883,-26 -tf_mixnet_s,3.880,96.120,25.267,74.733,4.13,224,0.875,bicubic,-87.630,-72.353,-13 -dpn68,3.853,96.147,26.053,73.947,12.61,224,0.875,bicubic,-88.177,-71.997,-32 -semnasnet_075,3.853,96.147,27.013,72.987,2.91,224,0.875,bicubic,-86.217,-70.417,+22 -mobilevit_xxs,3.840,96.160,21.760,78.240,1.27,256,0.900,bicubic,-83.350,-74.340,+47 -regnety_008,3.813,96.187,27.133,72.867,6.26,224,0.875,bicubic,-87.907,-71.047,-20 -tf_efficientnet_es,3.813,96.187,26.107,73.893,5.44,224,0.875,bicubic,-88.167,-71.753,-34 -dla60,3.787,96.213,27.947,72.053,22.04,224,0.875,bilinear,-88.443,-70.163,-46 -ssl_resnet18,3.747,96.253,25.440,74.560,11.69,224,0.875,bilinear,-86.473,-72.110,+14 -mobilenetv2_140,3.720,96.280,26.760,73.240,6.11,224,0.875,bicubic,-88.120,-71.090,-29 -densenet169,3.707,96.293,25.613,74.387,14.15,224,0.875,bicubic,-88.223,-72.487,-35 -regnetx_016,3.627,96.373,26.293,73.707,9.19,224,0.875,bicubic,-88.533,-71.917,-47 -res2net50_48w_2s,3.587,96.413,26.600,73.400,25.29,224,0.875,bilinear,-88.963,-71.480,-68 -spnasnet_100,3.547,96.453,24.293,75.707,4.42,224,0.875,bilinear,-86.803,-72.897,+7 -tf_mobilenetv3_large_100,3.547,96.453,25.053,74.947,5.48,224,0.875,bilinear,-87.693,-72.607,-20 -regnety_006,3.467,96.533,24.907,75.093,6.06,224,0.875,bicubic,-87.913,-72.803,-25 -legacy_seresnet34,3.333,96.667,23.813,76.187,21.96,224,0.875,bilinear,-87.567,-73.767,-9 -efficientnet_lite0,3.253,96.747,25.853,74.147,4.65,224,0.875,bicubic,-87.867,-71.767,-18 -dla34,3.240,96.760,23.573,76.427,15.74,224,0.875,bilinear,-87.530,-74.087,-7 -ghostnet_100,3.213,96.787,24.853,75.147,5.18,224,0.875,bilinear,-86.817,-72.517,+7 -regnety_004,3.200,96.800,22.653,77.347,4.34,224,0.875,bicubic,-87.290,-74.887,-2 -mobilenetv2_110d,3.173,96.827,24.587,75.413,4.52,224,0.875,bicubic,-87.787,-72.973,-16 -tinynet_c,3.120,96.880,21.520,78.480,2.46,184,0.875,bicubic,-84.650,-74.850,+25 -mnasnet_100,3.107,96.893,24.227,75.773,4.38,224,0.875,bicubic,-87.403,-73.243,-6 -tf_efficientnet_lite0,3.080,96.920,22.920,77.080,4.65,224,0.875,bicubic,-87.970,-74.670,-22 -skresnet18,3.000,97.000,22.813,77.187,11.96,224,0.875,bicubic,-86.660,-74.417,+8 -vgg19_bn,2.947,97.053,23.480,76.520,143.68,224,0.875,bilinear,-87.133,-74.100,-2 -resnet34,2.920,97.080,23.680,76.320,21.80,224,0.875,bilinear,-88.210,-73.940,-29 -tf_mobilenetv3_large_075,2.867,97.133,21.573,78.427,3.99,224,0.875,bilinear,-86.813,-75.637,+3 -tinynet_d,2.867,97.133,17.800,82.200,2.34,152,0.875,bicubic,-81.883,-77.380,+31 -hrnet_w18_small_v2,2.707,97.293,23.693,76.307,15.60,224,0.875,bilinear,-88.483,-74.207,-34 -gluon_resnet34_v1b,2.667,97.333,21.667,78.333,21.80,224,0.875,bicubic,-88.293,-75.973,-27 -regnetx_008,2.667,97.333,22.467,77.533,7.26,224,0.875,bicubic,-88.383,-75.243,-31 -vgg16_bn,2.653,97.347,23.787,76.213,138.37,224,0.875,bilinear,-87.437,-73.583,-10 -vgg16,2.627,97.373,20.427,79.573,138.36,224,0.875,bilinear,-85.923,-76.363,+10 -lcnet_100,2.627,97.373,20.880,79.120,2.95,224,0.875,bicubic,-86.173,-75.850,+8 -resnet18d,2.600,97.400,21.600,78.400,11.71,224,0.875,bicubic,-86.670,-75.540,-1 -tv_densenet121,2.560,97.440,22.667,77.333,7.98,224,0.875,bicubic,-88.330,-75.043,-28 -repvgg_b0,2.547,97.453,24.000,76.000,15.82,224,0.875,bilinear,-88.883,-73.990,-49 -regnetx_006,2.507,97.493,20.627,79.373,6.20,224,0.875,bicubic,-87.843,-76.813,-20 -legacy_seresnet18,2.493,97.507,20.080,79.920,11.78,224,0.875,bicubic,-86.387,-76.900,+1 -resnet26,2.480,97.520,23.013,76.987,16.00,224,0.875,bicubic,-88.640,-74.737,-41 -lcnet_075,2.320,97.680,17.133,82.867,2.36,224,0.875,bicubic,-83.670,-78.547,+15 -mobilenetv3_small_075,2.307,97.693,15.907,84.093,2.04,224,0.875,bicubic,-80.733,-78.183,+23 +densenet201,4.120,95.880,27.533,72.467,20.01,224,0.875,bicubic,-88.620,-70.697,-68 +gluon_resnet50_v1b,4.120,95.880,26.920,73.080,25.56,224,0.875,bicubic,-88.420,-71.250,-55 +resnet26d,4.040,95.960,28.507,71.493,16.01,224,0.875,bicubic,-88.030,-69.463,-33 +semnasnet_100,3.960,96.040,26.933,73.067,3.89,224,0.875,bicubic,-87.320,-70.627,-7 +repvgg_a2,3.933,96.067,27.280,72.720,28.21,224,0.875,bilinear,-88.007,-70.870,-29 +mobilevitv2_050,3.933,96.067,23.867,76.133,1.37,256,0.888,bicubic,-84.297,-73.123,+48 +tf_mixnet_s,3.893,96.107,25.280,74.720,4.13,224,0.875,bicubic,-87.617,-72.330,-15 +semnasnet_075,3.867,96.133,27.000,73.000,2.91,224,0.875,bicubic,-86.193,-70.430,+22 +dpn68,3.867,96.133,26.067,73.933,12.61,224,0.875,bicubic,-88.163,-71.983,-36 +mobilevit_xxs,3.827,96.173,21.707,78.293,1.27,256,0.900,bicubic,-83.363,-74.393,+49 +regnety_008,3.813,96.187,27.160,72.840,6.26,224,0.875,bicubic,-87.907,-71.020,-22 +tf_efficientnet_es,3.813,96.187,26.120,73.880,5.44,224,0.875,bicubic,-88.167,-71.740,-37 +edgenext_xx_small,3.787,96.213,23.693,76.307,1.33,256,0.900,bicubic,-84.563,-72.827,+40 +dla60,3.773,96.227,27.973,72.027,22.04,224,0.875,bilinear,-88.437,-70.127,-49 +ssl_resnet18,3.747,96.253,25.440,74.560,11.69,224,0.875,bilinear,-86.463,-72.110,+12 +mobilenetv2_140,3.720,96.280,26.747,73.253,6.11,224,0.875,bicubic,-88.110,-71.103,-32 +densenet169,3.693,96.307,25.600,74.400,14.15,224,0.875,bicubic,-88.227,-72.500,-39 +regnetx_016,3.613,96.387,26.253,73.747,9.19,224,0.875,bicubic,-88.547,-71.947,-51 +res2net50_48w_2s,3.587,96.413,26.613,73.387,25.29,224,0.875,bilinear,-88.953,-71.467,-71 +tf_mobilenetv3_large_100,3.560,96.440,25.093,74.907,5.48,224,0.875,bilinear,-87.660,-72.567,-22 +spnasnet_100,3.560,96.440,24.293,75.707,4.42,224,0.875,bilinear,-86.780,-72.897,+4 +regnety_006,3.467,96.533,24.893,75.107,6.06,224,0.875,bicubic,-87.903,-72.817,-28 +legacy_seresnet34,3.333,96.667,23.813,76.187,21.96,224,0.875,bilinear,-87.567,-73.767,-10 +efficientnet_lite0,3.253,96.747,25.880,74.120,4.65,224,0.875,bicubic,-87.857,-71.750,-20 +dla34,3.253,96.747,23.613,76.387,15.74,224,0.875,bilinear,-87.527,-74.047,-9 +ghostnet_100,3.227,96.773,24.867,75.133,5.18,224,0.875,bilinear,-86.803,-72.503,+5 +regnety_004,3.200,96.800,22.667,77.333,4.34,224,0.875,bicubic,-87.310,-74.873,-5 +mobilenetv2_110d,3.187,96.813,24.573,75.427,4.52,224,0.875,bicubic,-87.773,-72.987,-18 +mnasnet_100,3.107,96.893,24.200,75.800,4.38,224,0.875,bicubic,-87.403,-73.270,-6 +tinynet_c,3.107,96.893,21.533,78.467,2.46,184,0.875,bicubic,-84.673,-74.837,+25 +tf_efficientnet_lite0,3.093,96.907,22.920,77.080,4.65,224,0.875,bicubic,-87.947,-74.670,-24 +skresnet18,3.000,97.000,22.773,77.227,11.96,224,0.875,bicubic,-86.660,-74.467,+6 +vgg19_bn,2.947,97.053,23.480,76.520,143.68,224,0.875,bilinear,-87.133,-74.100,-4 +resnet34,2.920,97.080,23.693,76.307,21.80,224,0.875,bilinear,-88.210,-73.927,-32 +tf_mobilenetv3_large_075,2.867,97.133,21.560,78.440,3.99,224,0.875,bilinear,-86.813,-75.650,+1 +tinynet_d,2.867,97.133,17.787,82.213,2.34,152,0.875,bicubic,-81.893,-77.393,+33 +resnet14t,2.760,97.240,19.280,80.720,10.08,224,0.950,bilinear,-86.280,-77.320,+6 +hrnet_w18_small_v2,2.707,97.293,23.707,76.293,15.60,224,0.875,bilinear,-88.483,-74.193,-38 +regnetx_008,2.667,97.333,22.467,77.533,7.26,224,0.875,bicubic,-88.383,-75.243,-33 +gluon_resnet34_v1b,2.667,97.333,21.667,78.333,21.80,224,0.875,bicubic,-88.293,-75.973,-31 +vgg16_bn,2.653,97.347,23.787,76.213,138.37,224,0.875,bilinear,-87.437,-73.583,-13 +vgg16,2.627,97.373,20.427,79.573,138.36,224,0.875,bilinear,-85.923,-76.363,+9 +lcnet_100,2.613,97.387,20.867,79.133,2.95,224,0.875,bicubic,-86.177,-75.863,+5 +resnet18d,2.600,97.400,21.600,78.400,11.71,224,0.875,bicubic,-86.680,-75.540,-4 +tv_densenet121,2.560,97.440,22.667,77.333,7.98,224,0.875,bicubic,-88.330,-75.043,-31 +repvgg_b0,2.547,97.453,24.000,76.000,15.82,224,0.875,bilinear,-88.853,-73.990,-53 +regnetx_006,2.507,97.493,20.627,79.373,6.20,224,0.875,bicubic,-87.853,-76.803,-23 +legacy_seresnet18,2.493,97.507,20.080,79.920,11.78,224,0.875,bicubic,-86.387,-76.900,-1 +resnet26,2.480,97.520,23.053,76.947,16.00,224,0.875,bicubic,-88.640,-74.697,-46 +lcnet_075,2.307,97.693,17.160,82.840,2.36,224,0.875,bicubic,-83.683,-78.530,+16 +mobilenetv3_small_075,2.293,97.707,15.907,84.093,2.04,224,0.875,bicubic,-80.747,-78.193,+24 regnety_002,2.160,97.840,18.893,81.107,3.16,224,0.875,bicubic,-85.220,-77.697,+6 -mobilenetv2_100,2.147,97.853,19.907,80.093,3.50,224,0.875,bicubic,-87.463,-77.243,-11 -vgg19,2.107,97.893,20.747,79.253,143.67,224,0.875,bilinear,-86.933,-76.123,-8 -vgg13_bn,2.093,97.907,20.307,79.693,133.05,224,0.875,bilinear,-86.667,-76.663,-4 -tf_mobilenetv3_small_100,2.013,97.987,15.853,84.147,2.54,224,0.875,bilinear,-83.197,-79.917,+11 -mobilenetv3_small_100,2.000,98.000,17.080,82.920,2.54,224,0.875,bicubic,-83.220,-78.540,+9 -tf_mobilenetv3_small_075,2.000,98.000,14.813,85.187,2.04,224,0.875,bilinear,-81.510,-79.987,+15 -regnetx_004,1.960,98.040,19.160,80.840,5.16,224,0.875,bicubic,-86.940,-77.960,-11 +mobilenetv2_100,2.147,97.853,19.907,80.093,3.50,224,0.875,bicubic,-87.463,-77.243,-14 +vgg19,2.107,97.893,20.747,79.253,143.67,224,0.875,bilinear,-86.933,-76.123,-12 +vgg13_bn,2.093,97.907,20.307,79.693,133.05,224,0.875,bilinear,-86.667,-76.663,-6 +tf_mobilenetv3_small_100,2.013,97.987,15.853,84.147,2.54,224,0.875,bilinear,-83.177,-79.917,+12 +mobilenetv3_small_100,2.000,98.000,17.080,82.920,2.54,224,0.875,bicubic,-83.220,-78.550,+10 +tf_mobilenetv3_small_075,2.000,98.000,14.813,85.187,2.04,224,0.875,bilinear,-81.520,-79.987,+16 +regnetx_004,1.947,98.053,19.160,80.840,5.16,224,0.875,bicubic,-86.953,-77.960,-13 +tv_resnet34,1.867,98.133,20.000,80.000,21.80,224,0.875,bilinear,-88.063,-77.340,-27 vgg13,1.867,98.133,17.960,82.040,133.05,224,0.875,bilinear,-85.183,-78.360,0 -tv_resnet34,1.867,98.133,20.000,80.000,21.80,224,0.875,bilinear,-88.063,-77.340,-24 -tinynet_e,1.853,98.147,14.013,85.987,2.04,106,0.875,bicubic,-77.047,-78.547,+15 -mobilenetv3_small_050,1.840,98.160,12.507,87.493,1.59,224,0.875,bicubic,-75.150,-78.793,+15 -lcnet_050,1.813,98.187,13.880,86.120,1.88,224,0.875,bicubic,-79.967,-79.830,+11 -dla46x_c,1.760,98.240,16.480,83.520,1.07,224,0.875,bilinear,-82.490,-78.790,+5 -mnasnet_small,1.760,98.240,15.093,84.907,2.03,224,0.875,bicubic,-82.680,-80.087,+3 -vgg11_bn,1.720,98.280,18.093,81.907,132.87,224,0.875,bilinear,-85.780,-78.727,-11 -tf_mobilenetv3_large_minimal_100,1.627,98.373,17.120,82.880,3.92,224,0.875,bilinear,-87.333,-79.740,-21 -mobilenetv2_050,1.613,98.387,14.200,85.800,1.97,224,0.875,bicubic,-82.277,-80.510,+1 -dla60x_c,1.613,98.387,18.040,81.960,1.32,224,0.875,bilinear,-84.677,-78.120,-6 -vgg11,1.560,98.440,16.227,83.773,132.86,224,0.875,bilinear,-84.990,-80.053,-9 -gluon_resnet18_v1b,1.547,98.453,16.613,83.387,11.69,224,0.875,bicubic,-86.853,-80.067,-18 -hrnet_w18_small,1.547,98.453,18.133,81.867,13.19,224,0.875,bilinear,-87.503,-78.977,-28 -dla46_c,1.507,98.493,15.267,84.733,1.30,224,0.875,bilinear,-82.143,-79.653,-2 -regnetx_002,1.373,98.627,15.027,84.973,2.68,224,0.875,bicubic,-84.817,-80.953,-11 -resnet18,1.160,98.840,16.227,83.773,11.69,224,0.875,bilinear,-86.230,-80.063,-19 -tf_mobilenetv3_small_minimal_100,1.013,98.987,11.493,88.507,2.04,224,0.875,bilinear,-80.367,-82.177,-1 -tv_resnet50,0.000,100.000,14.453,85.547,25.56,224,0.875,bilinear,-91.890,-83.587,-93 +tinynet_e,1.853,98.147,14.013,85.987,2.04,106,0.875,bicubic,-77.047,-78.547,+16 +mobilenetv3_small_050,1.840,98.160,12.507,87.493,1.59,224,0.875,bicubic,-75.150,-78.793,+16 +lcnet_050,1.813,98.187,13.893,86.107,1.88,224,0.875,bicubic,-79.967,-79.827,+12 +dla46x_c,1.760,98.240,16.493,83.507,1.07,224,0.875,bilinear,-82.490,-78.767,+6 +mnasnet_small,1.760,98.240,15.093,84.907,2.03,224,0.875,bicubic,-82.680,-80.087,+4 +resnet10t,1.733,98.267,15.813,84.187,5.44,224,0.950,bilinear,-84.477,-79.847,-3 +vgg11_bn,1.720,98.280,18.080,81.920,132.87,224,0.875,bilinear,-85.780,-78.740,-12 +dla60x_c,1.627,98.373,18.053,81.947,1.32,224,0.875,bilinear,-84.643,-78.117,-6 +tf_mobilenetv3_large_minimal_100,1.613,98.387,17.120,82.880,3.92,224,0.875,bilinear,-87.357,-79.730,-25 +mobilenetv2_050,1.613,98.387,14.187,85.813,1.97,224,0.875,bicubic,-82.277,-80.533,+1 +vgg11,1.560,98.440,16.227,83.773,132.86,224,0.875,bilinear,-84.990,-80.053,-10 +gluon_resnet18_v1b,1.547,98.453,16.613,83.387,11.69,224,0.875,bicubic,-86.853,-80.067,-21 +hrnet_w18_small,1.533,98.467,18.133,81.867,13.19,224,0.875,bilinear,-87.497,-78.977,-30 +dla46_c,1.520,98.480,15.253,84.747,1.30,224,0.875,bilinear,-82.120,-79.667,-2 +regnetx_002,1.373,98.627,15.027,84.973,2.68,224,0.875,bicubic,-84.827,-80.953,-11 +resnet18,1.160,98.840,16.227,83.773,11.69,224,0.875,bilinear,-86.230,-80.063,-20 +tf_mobilenetv3_small_minimal_100,1.013,98.987,11.453,88.547,2.04,224,0.875,bilinear,-80.387,-82.227,-1 +tv_resnet50,0.000,100.000,14.453,85.547,25.56,224,0.875,bilinear,-91.900,-83.587,-99 diff --git a/results/results-imagenet-r-clean.csv b/results/results-imagenet-r-clean.csv index edcde1c6..0e42fcda 100644 --- a/results/results-imagenet-r-clean.csv +++ b/results/results-imagenet-r-clean.csv @@ -1,60 +1,73 @@ -model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation +model,top1,top1_err,top5,top5_err,param_count,img_size,crop_pct,interpolation beit_large_patch16_384,97.810,2.190,99.790,0.210,305.00,384,1.000,bicubic tf_efficientnet_l2_ns,97.780,2.220,99.890,0.110,480.31,800,0.960,bicubic beit_large_patch16_512,97.780,2.220,99.820,0.180,305.67,512,1.000,bicubic tf_efficientnet_l2_ns_475,97.750,2.250,99.820,0.180,480.31,475,0.936,bicubic +deit3_large_patch16_384_in21ft1k,97.560,2.440,99.710,0.290,304.76,384,1.000,bicubic convnext_xlarge_384_in22ft1k,97.550,2.450,99.800,0.200,350.20,384,1.000,bicubic beit_large_patch16_224,97.480,2.520,99.690,0.310,304.43,224,0.900,bicubic convnext_large_384_in22ft1k,97.440,2.560,99.780,0.220,197.77,384,1.000,bicubic vit_large_patch16_384,97.420,2.580,99.780,0.220,304.72,384,1.000,bicubic beit_base_patch16_384,97.330,2.670,99.720,0.280,86.74,384,1.000,bicubic +deit3_large_patch16_224_in21ft1k,97.310,2.690,99.680,0.320,304.37,224,1.000,bicubic convnext_base_384_in22ft1k,97.290,2.710,99.780,0.220,88.59,384,1.000,bicubic volo_d5_512,97.290,2.710,99.760,0.240,296.09,512,1.150,bicubic +swinv2_large_window12to24_192to384_22kft1k,97.280,2.720,99.780,0.220,196.74,384,1.000,bicubic +swinv2_base_window12to24_192to384_22kft1k,97.260,2.740,99.790,0.210,87.92,384,1.000,bicubic convnext_large_in22ft1k,97.260,2.740,99.650,0.350,197.77,224,0.875,bicubic -convnext_xlarge_in22ft1k,97.240,2.760,99.730,0.270,350.20,224,0.875,bicubic +deit3_huge_patch14_224_in21ft1k,97.250,2.750,99.720,0.280,632.13,224,1.000,bicubic volo_d5_448,97.240,2.760,99.740,0.260,295.91,448,1.150,bicubic -tf_efficientnet_b7_ns,97.200,2.800,99.700,0.300,66.35,600,0.949,bicubic +convnext_xlarge_in22ft1k,97.240,2.760,99.730,0.270,350.20,224,0.875,bicubic +swinv2_large_window12to16_192to256_22kft1k,97.240,2.760,99.710,0.290,196.74,256,0.900,bicubic +deit3_base_patch16_384_in21ft1k,97.240,2.760,99.670,0.330,86.88,384,1.000,bicubic +tf_efficientnet_b7_ns,97.190,2.810,99.700,0.300,66.35,600,0.949,bicubic swin_large_patch4_window12_384,97.180,2.820,99.680,0.320,196.74,384,1.000,bicubic tf_efficientnetv2_xl_in21ft1k,97.150,2.850,99.620,0.380,208.12,512,1.000,bicubic swin_base_patch4_window12_384,97.120,2.880,99.780,0.220,87.90,384,1.000,bicubic tf_efficientnetv2_l_in21ft1k,97.110,2.890,99.710,0.290,118.52,480,1.000,bicubic -vit_base_patch8_224,97.080,2.920,99.610,0.390,86.58,224,0.900,bicubic +convnext_small_384_in22ft1k,97.090,2.910,99.690,0.310,50.22,384,1.000,bicubic +vit_base_patch8_224,97.080,2.920,99.620,0.380,86.58,224,0.900,bicubic volo_d4_448,97.070,2.930,99.750,0.250,193.41,448,1.150,bicubic -volo_d3_448,97.020,2.980,99.680,0.320,86.63,448,1.000,bicubic -vit_base_patch16_384,97.020,2.980,99.710,0.290,86.86,384,1.000,bicubic +swinv2_base_window12to16_192to256_22kft1k,97.060,2.940,99.660,0.340,87.92,256,0.900,bicubic tf_efficientnet_b6_ns,97.020,2.980,99.710,0.290,43.04,528,0.942,bicubic +vit_base_patch16_384,97.020,2.980,99.710,0.290,86.86,384,1.000,bicubic +volo_d3_448,97.020,2.980,99.680,0.320,86.63,448,1.000,bicubic ig_resnext101_32x48d,96.970,3.030,99.670,0.330,828.41,224,0.875,bilinear tf_efficientnetv2_m_in21ft1k,96.970,3.030,99.610,0.390,54.14,480,1.000,bicubic -swin_large_patch4_window7_224,96.950,3.050,99.660,0.340,196.53,224,0.900,bicubic vit_large_r50_s32_384,96.950,3.050,99.710,0.290,329.09,384,1.000,bicubic +swin_large_patch4_window7_224,96.950,3.050,99.660,0.340,196.53,224,0.900,bicubic xcit_large_24_p16_384_dist,96.940,3.060,99.510,0.490,189.10,384,1.000,bicubic dm_nfnet_f6,96.920,3.080,99.720,0.280,438.36,576,0.956,bicubic volo_d5_224,96.880,3.120,99.670,0.330,295.46,224,0.960,bicubic -cait_m48_448,96.880,3.120,99.620,0.380,356.46,448,1.000,bicubic resnetv2_152x4_bitm,96.880,3.120,99.660,0.340,936.53,480,1.000,bilinear +cait_m48_448,96.880,3.120,99.620,0.380,356.46,448,1.000,bicubic tf_efficientnet_b5_ns,96.870,3.130,99.640,0.360,30.39,456,0.934,bicubic +deit3_base_patch16_224_in21ft1k,96.870,3.130,99.620,0.380,86.59,224,1.000,bicubic +deit3_large_patch16_384,96.850,3.150,99.620,0.380,304.76,384,1.000,bicubic convnext_base_in22ft1k,96.840,3.160,99.650,0.350,88.59,224,0.875,bicubic cait_m36_384,96.830,3.170,99.660,0.340,271.22,384,1.000,bicubic -xcit_small_24_p8_384_dist,96.820,3.180,99.630,0.370,47.63,384,1.000,bicubic dm_nfnet_f5,96.810,3.190,99.670,0.330,377.21,544,0.954,bicubic -ig_resnext101_32x32d,96.780,3.220,99.530,0.470,468.53,224,0.875,bilinear -xcit_medium_24_p8_384_dist,96.780,3.220,99.610,0.390,84.32,384,1.000,bicubic +xcit_small_24_p8_384_dist,96.810,3.190,99.630,0.370,47.63,384,1.000,bicubic volo_d4_224,96.780,3.220,99.670,0.330,192.96,224,0.960,bicubic dm_nfnet_f4,96.780,3.220,99.620,0.380,316.07,512,0.951,bicubic +xcit_medium_24_p8_384_dist,96.780,3.220,99.610,0.390,84.32,384,1.000,bicubic +ig_resnext101_32x32d,96.780,3.220,99.530,0.470,468.53,224,0.875,bilinear xcit_large_24_p8_384_dist,96.760,3.240,99.560,0.440,188.93,384,1.000,bicubic dm_nfnet_f3,96.730,3.270,99.630,0.370,254.92,416,0.940,bicubic -tf_efficientnet_b4_ns,96.710,3.290,99.640,0.360,19.34,380,0.922,bicubic vit_large_patch16_224,96.710,3.290,99.650,0.350,304.33,224,0.900,bicubic +tf_efficientnet_b4_ns,96.710,3.290,99.640,0.360,19.34,380,0.922,bicubic volo_d2_384,96.710,3.290,99.600,0.400,58.87,384,1.000,bicubic xcit_medium_24_p16_384_dist,96.700,3.300,99.600,0.400,84.40,384,1.000,bicubic tf_efficientnet_b8,96.700,3.300,99.530,0.470,87.41,672,0.954,bicubic swin_base_patch4_window7_224,96.680,3.320,99.660,0.340,87.77,224,0.900,bicubic +deit3_small_patch16_384_in21ft1k,96.670,3.330,99.640,0.360,22.21,384,1.000,bicubic beit_base_patch16_224,96.660,3.340,99.660,0.340,86.53,224,0.900,bicubic tf_efficientnetv2_l,96.650,3.350,99.560,0.440,118.52,480,1.000,bicubic xcit_large_24_p8_224_dist,96.640,3.360,99.460,0.540,188.93,224,1.000,bicubic cait_s36_384,96.630,3.370,99.600,0.400,68.37,384,1.000,bicubic regnetz_e8,96.600,3.400,99.610,0.390,57.70,320,1.000,bicubic -tf_efficientnet_b7,96.580,3.420,99.510,0.490,66.35,600,0.949,bicubic +deit3_huge_patch14_224,96.580,3.420,99.520,0.480,632.13,224,0.900,bicubic +tf_efficientnet_b7,96.580,3.420,99.520,0.480,66.35,600,0.949,bicubic cait_s24_384,96.570,3.430,99.550,0.450,47.06,384,1.000,bicubic xcit_small_24_p8_224_dist,96.550,3.450,99.570,0.430,47.63,224,1.000,bicubic tf_efficientnet_b8_ap,96.550,3.450,99.540,0.460,87.41,672,0.954,bicubic @@ -67,18 +80,21 @@ tf_efficientnetv2_s_in21ft1k,96.470,3.530,99.570,0.430,21.46,384,1.000,bicubic volo_d1_384,96.470,3.530,99.550,0.450,26.78,384,1.000,bicubic ecaresnet269d,96.460,3.540,99.610,0.390,102.09,352,1.000,bicubic dm_nfnet_f2,96.460,3.540,99.540,0.460,193.78,352,0.920,bicubic -eca_nfnet_l2,96.450,3.550,99.630,0.370,56.72,384,1.000,bicubic +convnext_small_in22ft1k,96.460,3.540,99.470,0.530,50.22,224,0.875,bicubic vit_base_r50_s16_384,96.450,3.550,99.660,0.340,98.95,384,1.000,bicubic -ig_resnext101_32x16d,96.440,3.560,99.540,0.460,194.03,224,0.875,bilinear +eca_nfnet_l2,96.450,3.550,99.620,0.380,56.72,384,1.000,bicubic volo_d3_224,96.440,3.560,99.620,0.380,86.33,224,0.960,bicubic +ig_resnext101_32x16d,96.440,3.560,99.540,0.460,194.03,224,0.875,bilinear +seresnextaa101d_32x8d,96.420,3.580,99.520,0.480,93.59,288,1.000,bicubic volo_d2_224,96.420,3.580,99.500,0.500,58.68,224,0.960,bicubic -resnetrs420,96.400,3.600,99.540,0.460,191.89,416,1.000,bicubic +resnetrs420,96.410,3.590,99.540,0.460,191.89,416,1.000,bicubic dm_nfnet_f1,96.380,3.620,99.470,0.530,132.63,320,0.910,bicubic tf_efficientnet_b6_ap,96.370,3.630,99.550,0.450,43.04,528,0.942,bicubic +seresnext101d_32x8d,96.360,3.640,99.470,0.530,93.59,288,1.000,bicubic tf_efficientnet_b7_ap,96.350,3.650,99.590,0.410,66.35,600,0.949,bicubic resmlp_big_24_224_in22ft1k,96.350,3.650,99.520,0.480,129.14,224,0.875,bicubic -resnetrs200,96.340,3.660,99.550,0.450,93.21,320,1.000,bicubic xcit_small_24_p16_384_dist,96.340,3.660,99.580,0.420,47.67,384,1.000,bicubic +resnetrs200,96.340,3.660,99.550,0.450,93.21,320,1.000,bicubic regnetz_040h,96.330,3.670,99.520,0.480,28.94,320,1.000,bicubic xcit_small_12_p16_384_dist,96.330,3.670,99.490,0.510,26.25,384,1.000,bicubic xcit_large_24_p16_224_dist,96.320,3.680,99.500,0.500,189.10,224,1.000,bicubic @@ -86,506 +102,568 @@ seresnet152d,96.310,3.690,99.510,0.490,66.84,320,1.000,bicubic vit_base_patch16_224,96.300,3.700,99.560,0.440,86.57,224,0.900,bicubic tf_efficientnet_b6,96.290,3.710,99.520,0.480,43.04,528,0.942,bicubic swsl_resnext101_32x16d,96.280,3.720,99.500,0.500,194.03,224,0.875,bilinear -efficientnetv2_rw_m,96.270,3.730,99.560,0.440,53.24,416,1.000,bicubic resnetv2_50x3_bitm,96.270,3.730,99.630,0.370,217.32,448,1.000,bilinear +efficientnetv2_rw_m,96.270,3.730,99.560,0.440,53.24,416,1.000,bicubic xcit_medium_24_p16_224_dist,96.260,3.740,99.410,0.590,84.40,224,1.000,bicubic -resnetv2_101x3_bitm,96.250,3.750,99.580,0.420,387.93,448,1.000,bilinear -resnetrs350,96.240,3.760,99.470,0.530,163.96,384,1.000,bicubic +resnetv2_101x3_bitm,96.250,3.750,99.590,0.410,387.93,448,1.000,bilinear swsl_resnext101_32x8d,96.240,3.760,99.590,0.410,88.79,224,0.875,bilinear -xcit_tiny_24_p8_384_dist,96.230,3.770,99.440,0.560,12.11,384,1.000,bicubic +resnetrs350,96.240,3.760,99.470,0.530,163.96,384,1.000,bicubic +xcit_tiny_24_p8_384_dist,96.240,3.760,99.440,0.560,12.11,384,1.000,bicubic +deit3_base_patch16_384,96.230,3.770,99.400,0.600,86.88,384,1.000,bicubic regnetz_d8_evos,96.220,3.780,99.490,0.510,23.46,320,0.950,bicubic resnetv2_152x2_bit_teacher_384,96.190,3.810,99.500,0.500,236.34,384,1.000,bicubic +deit3_large_patch16_224,96.190,3.810,99.300,0.700,304.37,224,0.900,bicubic +vit_large_r50_s32_224,96.180,3.820,99.540,0.460,328.99,224,0.900,bicubic regnetz_040,96.180,3.820,99.510,0.490,27.12,320,1.000,bicubic -vit_large_r50_s32_224,96.180,3.820,99.530,0.470,328.99,224,0.900,bicubic -crossvit_18_dagger_408,96.140,3.860,99.470,0.530,44.61,408,1.000,bicubic +convnext_tiny_384_in22ft1k,96.170,3.830,99.480,0.520,28.59,384,1.000,bicubic +swinv2_base_window16_256,96.170,3.830,99.400,0.600,87.92,256,0.900,bicubic +crossvit_18_dagger_408,96.130,3.870,99.470,0.530,44.61,408,1.000,bicubic seresnext101_32x8d,96.130,3.870,99.360,0.640,93.57,288,1.000,bicubic resnest269e,96.120,3.880,99.520,0.480,110.93,416,0.928,bicubic resnet200d,96.110,3.890,99.460,0.540,64.69,320,1.000,bicubic tf_efficientnet_b3_ns,96.100,3.900,99.480,0.520,12.23,300,0.904,bicubic -xcit_large_24_p8_224,96.080,3.920,99.150,0.850,188.93,224,1.000,bicubic tf_efficientnet_b5_ap,96.080,3.920,99.540,0.460,30.39,456,0.934,bicubic -pit_b_distilled_224,96.070,3.930,99.380,0.620,74.79,224,0.900,bicubic +xcit_large_24_p8_224,96.080,3.920,99.150,0.850,188.93,224,1.000,bicubic resnest200e,96.070,3.930,99.480,0.520,70.20,320,0.909,bicubic -resnetrs270,96.060,3.940,99.480,0.520,129.86,352,1.000,bicubic +swinv2_base_window8_256,96.070,3.930,99.420,0.580,87.92,256,0.900,bicubic +pit_b_distilled_224,96.070,3.930,99.380,0.620,74.79,224,0.900,bicubic +swinv2_small_window16_256,96.070,3.930,99.340,0.660,49.73,256,0.900,bicubic vit_small_r26_s32_384,96.060,3.940,99.550,0.450,36.47,384,1.000,bicubic -swsl_resnext101_32x4d,96.050,3.950,99.530,0.470,44.18,224,0.875,bilinear +resnetrs270,96.060,3.940,99.480,0.520,129.86,352,1.000,bicubic +swsl_resnext101_32x4d,96.040,3.960,99.530,0.470,44.18,224,0.875,bilinear swin_s3_base_224,96.040,3.960,99.350,0.650,71.13,224,0.900,bicubic -vit_base_patch16_224_miil,96.030,3.970,99.350,0.650,86.54,224,0.875,bilinear volo_d1_224,96.030,3.970,99.390,0.610,26.63,224,0.960,bicubic +vit_base_patch16_224_miil,96.030,3.970,99.350,0.650,86.54,224,0.875,bilinear convnext_large,96.020,3.980,99.470,0.530,197.77,224,0.875,bicubic -cait_xs24_384,96.010,3.990,99.430,0.570,26.67,384,1.000,bicubic regnetz_d8,96.010,3.990,99.520,0.480,23.37,320,1.000,bicubic -tf_efficientnet_b5,95.980,4.020,99.450,0.550,30.39,456,0.934,bicubic +cs3se_edgenet_x,96.010,3.990,99.440,0.560,50.72,320,1.000,bicubic +cait_xs24_384,96.010,3.990,99.430,0.570,26.67,384,1.000,bicubic vit_small_patch16_384,95.980,4.020,99.590,0.410,22.20,384,1.000,bicubic -resnetrs152,95.960,4.040,99.380,0.620,86.62,320,1.000,bicubic +tf_efficientnet_b5,95.980,4.020,99.450,0.550,30.39,456,0.934,bicubic xcit_small_12_p8_224_dist,95.960,4.040,99.420,0.580,26.21,224,1.000,bicubic +resnetrs152,95.960,4.040,99.380,0.620,86.62,320,1.000,bicubic +eca_nfnet_l1,95.940,4.060,99.490,0.510,41.41,320,1.000,bicubic convnext_base,95.940,4.060,99.380,0.620,88.59,224,0.875,bicubic ig_resnext101_32x8d,95.940,4.060,99.380,0.620,88.79,224,0.875,bilinear -eca_nfnet_l1,95.930,4.070,99.490,0.510,41.41,320,1.000,bicubic xcit_small_24_p8_224,95.910,4.090,99.180,0.820,47.63,224,1.000,bicubic vit_base_patch32_384,95.900,4.100,99.440,0.560,88.30,384,1.000,bicubic regnety_160,95.880,4.120,99.560,0.440,83.59,288,1.000,bicubic +sequencer2d_l,95.870,4.130,99.470,0.530,54.30,224,0.875,bicubic resmlp_big_24_distilled_224,95.870,4.130,99.440,0.560,129.14,224,0.875,bicubic +regnetz_d32,95.870,4.130,99.430,0.570,27.58,320,0.950,bicubic resnet152d,95.870,4.130,99.430,0.570,60.21,320,1.000,bicubic xcit_medium_24_p8_224,95.870,4.130,99.080,0.920,84.32,224,1.000,bicubic -regnetz_d32,95.860,4.140,99.430,0.570,27.58,320,0.950,bicubic regnety_080,95.850,4.150,99.440,0.560,39.18,288,1.000,bicubic -swin_s3_small_224,95.830,4.170,99.200,0.800,49.74,224,0.900,bicubic +swin_s3_small_224,95.840,4.160,99.200,0.800,49.74,224,0.900,bicubic +deit3_small_patch16_224_in21ft1k,95.820,4.180,99.400,0.600,22.06,224,1.000,bicubic crossvit_15_dagger_408,95.820,4.180,99.310,0.690,28.50,408,1.000,bicubic -xcit_small_24_p16_224_dist,95.800,4.200,99.340,0.660,47.67,224,1.000,bicubic +xcit_small_24_p16_224_dist,95.790,4.210,99.350,0.650,47.67,224,1.000,bicubic regnety_064,95.790,4.210,99.290,0.710,30.58,288,1.000,bicubic +deit3_base_patch16_224,95.780,4.220,99.270,0.730,86.59,224,0.900,bicubic regnetv_064,95.770,4.230,99.420,0.580,30.58,288,1.000,bicubic -deit_base_distilled_patch16_224,95.750,4.250,99.280,0.720,87.34,224,0.900,bicubic resnet101d,95.750,4.250,99.440,0.560,44.57,320,1.000,bicubic resnetv2_152x2_bit_teacher,95.750,4.250,99.430,0.570,236.34,224,0.875,bicubic -xcit_small_12_p16_224_dist,95.740,4.260,99.300,0.700,26.25,224,1.000,bicubic +deit_base_distilled_patch16_224,95.750,4.250,99.280,0.720,87.34,224,0.900,bicubic regnetv_040,95.730,4.270,99.380,0.620,20.64,288,1.000,bicubic -swin_small_patch4_window7_224,95.720,4.280,99.290,0.710,49.61,224,0.900,bicubic +convnext_tiny_in22ft1k,95.730,4.270,99.360,0.640,28.59,224,0.875,bicubic +swinv2_small_window8_256,95.730,4.270,99.360,0.640,49.73,256,0.900,bicubic +xcit_small_12_p16_224_dist,95.730,4.270,99.300,0.700,26.25,224,1.000,bicubic twins_pcpvt_large,95.720,4.280,99.490,0.510,60.99,224,0.900,bicubic twins_svt_large,95.720,4.280,99.370,0.630,99.27,224,0.900,bicubic +swin_small_patch4_window7_224,95.720,4.280,99.290,0.710,49.61,224,0.900,bicubic tf_efficientnetv2_s,95.710,4.290,99.400,0.600,21.46,384,1.000,bicubic efficientnetv2_rw_s,95.700,4.300,99.380,0.620,23.94,384,1.000,bicubic dm_nfnet_f0,95.690,4.310,99.330,0.670,71.49,256,0.900,bicubic +swinv2_cr_small_ns_224,95.690,4.310,99.310,0.690,49.70,224,0.900,bicubic xception65,95.690,4.310,99.310,0.690,39.92,299,0.940,bicubic -xception65p,95.650,4.350,99.270,0.730,39.82,299,0.940,bicubic +xception65p,95.660,4.340,99.270,0.730,39.82,299,0.940,bicubic deit_base_patch16_384,95.650,4.350,99.240,0.760,86.86,384,1.000,bicubic -cait_s24_224,95.650,4.350,99.390,0.610,46.92,224,1.000,bicubic +cait_s24_224,95.640,4.360,99.390,0.610,46.92,224,1.000,bicubic regnetz_c16_evos,95.630,4.370,99.420,0.580,13.49,320,0.950,bicubic +swsl_resnext50_32x4d,95.610,4.390,99.440,0.560,25.03,224,0.875,bilinear +deit3_small_patch16_384,95.610,4.390,99.390,0.610,22.21,384,1.000,bicubic convnext_small,95.610,4.390,99.260,0.740,50.22,224,0.875,bicubic -swsl_resnext50_32x4d,95.600,4.400,99.440,0.560,25.03,224,0.875,bilinear +sequencer2d_m,95.600,4.400,99.270,0.730,38.31,224,0.875,bicubic tf_efficientnet_b4,95.590,4.410,99.330,0.670,19.34,380,0.922,bicubic -resnet152,95.570,4.430,99.270,0.730,60.19,224,0.950,bicubic twins_svt_base,95.570,4.430,99.230,0.770,56.07,224,0.900,bicubic resnest101e,95.560,4.440,99.270,0.730,48.28,256,0.875,bilinear +resnet152,95.550,4.450,99.260,0.740,60.19,224,0.950,bicubic jx_nest_base,95.540,4.460,99.300,0.700,67.72,224,0.875,bicubic resnext101_64x4d,95.540,4.460,99.290,0.710,83.46,288,1.000,bicubic efficientnet_b4,95.530,4.470,99.400,0.600,19.34,384,1.000,bicubic -jx_nest_small,95.530,4.470,99.210,0.790,38.35,224,0.875,bicubic +jx_nest_small,95.530,4.470,99.220,0.780,38.35,224,0.875,bicubic tf_efficientnet_b2_ns,95.520,4.480,99.340,0.660,9.11,260,0.890,bicubic tresnet_xl_448,95.510,4.490,99.340,0.660,78.44,448,0.875,bilinear tf_efficientnet_b4_ap,95.490,4.510,99.390,0.610,19.34,380,0.922,bicubic +xcit_tiny_24_p16_384_dist,95.490,4.510,99.360,0.640,12.12,384,1.000,bicubic regnety_032,95.480,4.520,99.320,0.680,19.44,288,1.000,bicubic -regnety_040,95.480,4.520,99.420,0.580,20.65,288,1.000,bicubic -xcit_tiny_24_p16_384_dist,95.480,4.520,99.360,0.640,12.12,384,1.000,bicubic -xcit_tiny_24_p8_224_dist,95.460,4.540,99.360,0.640,12.11,224,1.000,bicubic +regnety_040,95.470,4.530,99.420,0.580,20.65,288,1.000,bicubic +cs3edgenet_x,95.470,4.530,99.280,0.720,47.82,288,1.000,bicubic +sequencer2d_s,95.470,4.530,99.270,0.730,27.65,224,0.875,bicubic twins_pcpvt_base,95.460,4.540,99.390,0.610,43.83,224,0.900,bicubic +xcit_tiny_24_p8_224_dist,95.460,4.540,99.360,0.640,12.11,224,1.000,bicubic eca_nfnet_l0,95.450,4.550,99.390,0.610,24.14,288,1.000,bicubic +cs3sedarknet_x,95.420,4.580,99.320,0.680,35.40,288,1.000,bicubic xcit_small_12_p8_224,95.420,4.580,99.200,0.800,26.21,224,1.000,bicubic ssl_resnext101_32x16d,95.410,4.590,99.410,0.590,194.03,224,0.875,bilinear -regnetz_c16,95.400,4.600,99.310,0.690,13.46,320,0.940,bicubic +resnetv2_50x1_bit_distilled,95.400,4.600,99.430,0.570,25.55,224,0.875,bicubic tresnet_l_448,95.400,4.600,99.300,0.700,55.99,448,0.875,bilinear +swinv2_cr_small_224,95.400,4.600,99.050,0.950,49.70,224,0.900,bicubic nfnet_l0,95.390,4.610,99.420,0.580,35.07,288,1.000,bicubic -resnetv2_50x1_bit_distilled,95.390,4.610,99.430,0.570,25.55,224,0.875,bicubic +regnetz_c16,95.390,4.610,99.310,0.690,13.46,320,0.940,bicubic +mobilevitv2_200_384_in22ft1k,95.390,4.610,99.280,0.720,18.45,384,1.000,bicubic tresnet_m,95.380,4.620,99.150,0.850,31.39,224,0.875,bilinear +swinv2_tiny_window16_256,95.360,4.640,99.300,0.700,28.35,256,0.900,bicubic pnasnet5large,95.360,4.640,99.130,0.870,86.06,331,0.911,bicubic xcit_tiny_12_p8_384_dist,95.340,4.660,99.340,0.660,6.71,384,1.000,bicubic +mobilevitv2_150_384_in22ft1k,95.340,4.660,99.130,0.870,10.59,384,1.000,bicubic ssl_resnext101_32x8d,95.330,4.670,99.310,0.690,88.79,224,0.875,bilinear resnetv2_101x1_bitm,95.320,4.680,99.370,0.630,44.54,448,1.000,bilinear -gc_efficientnetv2_rw_t,95.280,4.720,99.220,0.780,13.68,288,1.000,bicubic +vit_relpos_medium_patch16_cls_224,95.300,4.700,99.090,0.910,38.76,224,0.900,bicubic +gc_efficientnetv2_rw_t,95.290,4.710,99.220,0.780,13.68,288,1.000,bicubic +cs3darknet_x,95.270,4.730,99.280,0.720,35.05,288,1.000,bicubic resnetrs101,95.250,4.750,99.210,0.790,63.62,288,0.940,bicubic +vit_relpos_base_patch16_clsgap_224,95.250,4.750,99.200,0.800,86.43,224,0.900,bicubic +mobilevitv2_175_384_in22ft1k,95.240,4.760,99.380,0.620,14.25,384,1.000,bicubic vit_large_patch32_384,95.240,4.760,99.320,0.680,306.63,384,1.000,bicubic -cait_xxs36_384,95.230,4.770,99.330,0.670,17.37,384,1.000,bicubic +cait_xxs36_384,95.220,4.780,99.320,0.680,17.37,384,1.000,bicubic levit_384,95.210,4.790,99.160,0.840,39.13,224,0.900,bicubic swsl_resnet50,95.200,4.800,99.390,0.610,25.56,224,0.875,bilinear resnet51q,95.200,4.800,99.280,0.720,35.70,288,1.000,bilinear -crossvit_18_dagger_240,95.190,4.810,99.120,0.880,44.27,240,0.875,bicubic +vit_relpos_medium_patch16_224,95.200,4.800,99.220,0.780,38.75,224,0.900,bicubic +crossvit_18_dagger_240,95.180,4.820,99.120,0.880,44.27,240,0.875,bicubic ecaresnet101d,95.160,4.840,99.230,0.770,44.57,224,0.875,bicubic -ssl_resnext101_32x4d,95.160,4.840,99.310,0.690,44.18,224,0.875,bilinear +ssl_resnext101_32x4d,95.150,4.850,99.300,0.700,44.18,224,0.875,bilinear nasnetalarge,95.150,4.850,99.130,0.870,88.75,331,0.911,bicubic efficientnet_b3,95.140,4.860,99.210,0.790,12.23,320,1.000,bicubic -vit_small_r26_s32_224,95.130,4.870,99.220,0.780,36.43,224,0.900,bicubic -xcit_medium_24_p16_224,95.130,4.870,98.920,1.080,84.40,224,1.000,bicubic -poolformer_m48,95.130,4.870,99.120,0.880,73.47,224,0.950,bicubic +vit_relpos_base_patch16_224,95.130,4.870,99.300,0.700,86.43,224,0.900,bicubic fbnetv3_g,95.130,4.870,99.200,0.800,16.62,288,0.950,bilinear -tf_efficientnetv2_b3,95.120,4.880,99.200,0.800,14.36,300,0.904,bicubic +poolformer_m48,95.130,4.870,99.120,0.880,73.47,224,0.950,bicubic +xcit_medium_24_p16_224,95.130,4.870,98.930,1.070,84.40,224,1.000,bicubic resnetv2_50d_evos,95.120,4.880,99.230,0.770,25.59,288,0.950,bicubic -resnet61q,95.110,4.890,99.080,0.920,36.85,288,1.000,bicubic +vit_small_r26_s32_224,95.120,4.880,99.220,0.780,36.43,224,0.900,bicubic +cs3sedarknet_l,95.120,4.880,99.210,0.790,21.91,288,0.950,bicubic +tf_efficientnetv2_b3,95.120,4.880,99.200,0.800,14.36,300,0.904,bicubic +resnet61q,95.120,4.880,99.080,0.920,36.85,288,1.000,bicubic convit_base,95.100,4.900,99.140,0.860,86.54,224,0.875,bicubic resnetv2_50d_gn,95.100,4.900,99.060,0.940,25.57,288,0.950,bicubic +xcit_small_24_p16_224,95.080,4.920,99.070,0.930,47.67,224,1.000,bicubic coat_lite_small,95.080,4.920,99.030,0.970,19.84,224,0.900,bicubic -xcit_small_24_p16_224,95.080,4.920,99.060,0.940,47.67,224,1.000,bicubic ecaresnet50t,95.070,4.930,99.290,0.710,25.57,320,0.950,bicubic efficientnetv2_rw_t,95.070,4.930,99.220,0.780,13.65,288,1.000,bicubic -crossvit_base_240,95.070,4.930,98.980,1.020,105.03,240,0.875,bicubic +vit_relpos_medium_patch16_rpn_224,95.070,4.930,99.190,0.810,38.73,224,0.900,bicubic crossvit_18_240,95.070,4.930,99.120,0.880,43.27,240,0.875,bicubic +crossvit_base_240,95.070,4.930,98.980,1.020,105.03,240,0.875,bicubic tresnet_xl,95.060,4.940,99.260,0.740,78.44,224,0.875,bilinear xception41p,95.060,4.940,99.150,0.850,26.91,299,0.940,bicubic -deit_base_patch16_224,95.010,4.990,98.980,1.020,86.57,224,0.900,bicubic -halo2botnet50ts_256,95.010,4.990,99.040,0.960,22.64,256,0.950,bicubic +mobilevitv2_200_in22ft1k,95.050,4.950,99.080,0.920,18.45,256,0.888,bicubic +swinv2_tiny_window8_256,95.030,4.970,99.170,0.830,28.35,256,0.900,bicubic poolformer_m36,95.010,4.990,99.100,0.900,56.17,224,0.950,bicubic +halo2botnet50ts_256,95.010,4.990,99.040,0.960,22.64,256,0.950,bicubic +deit_base_patch16_224,95.010,4.990,98.980,1.020,86.57,224,0.900,bicubic crossvit_15_dagger_240,94.980,5.020,99.160,0.840,28.21,240,0.875,bicubic +resnet101,94.980,5.020,99.080,0.920,44.55,224,0.950,bicubic +visformer_small,94.970,5.030,99.210,0.790,40.22,224,0.900,bicubic convmixer_1536_20,94.970,5.030,99.170,0.830,51.63,224,0.960,bicubic tf_efficientnet_b3_ap,94.970,5.030,99.110,0.890,12.23,300,0.904,bicubic convnext_tiny,94.960,5.040,99.200,0.800,28.59,224,0.875,bicubic -resnet101,94.960,5.040,99.080,0.920,44.55,224,0.950,bicubic -visformer_small,94.960,5.040,99.210,0.790,40.22,224,0.900,bicubic jx_nest_tiny,94.950,5.050,99.100,0.900,17.06,224,0.875,bicubic xcit_large_24_p16_224,94.950,5.050,98.830,1.170,189.10,224,1.000,bicubic -cait_xxs24_384,94.940,5.060,99.130,0.870,12.03,384,1.000,bicubic -resnetv2_101,94.930,5.070,99.130,0.870,44.54,224,0.950,bicubic gernet_l,94.930,5.070,99.200,0.800,31.08,256,0.875,bilinear -convit_small,94.920,5.080,99.100,0.900,27.78,224,0.875,bicubic +cait_xxs24_384,94.930,5.070,99.140,0.860,12.03,384,1.000,bicubic +resnetv2_101,94.930,5.070,99.120,0.880,44.54,224,0.950,bicubic +convit_small,94.920,5.080,99.110,0.890,27.78,224,0.875,bicubic tf_efficientnet_b3,94.910,5.090,99.110,0.890,12.23,300,0.904,bicubic -swin_s3_tiny_224,94.910,5.090,99.160,0.840,28.33,224,0.900,bicubic +vit_srelpos_medium_patch16_224,94.900,5.100,99.200,0.800,38.74,224,0.900,bicubic +swin_s3_tiny_224,94.900,5.100,99.160,0.840,28.33,224,0.900,bicubic tresnet_l,94.900,5.100,99.030,0.970,55.99,224,0.875,bilinear xcit_tiny_24_p8_224,94.890,5.110,99.190,0.810,12.11,224,1.000,bicubic -mixer_b16_224_miil,94.880,5.120,99.080,0.920,59.88,224,0.875,bilinear +mixer_b16_224_miil,94.890,5.110,99.080,0.920,59.88,224,0.875,bilinear vit_small_patch16_224,94.880,5.120,99.270,0.730,22.05,224,0.900,bicubic +resnetaa50,94.880,5.120,99.130,0.870,25.56,288,1.000,bicubic tf_efficientnet_lite4,94.870,5.130,99.090,0.910,13.01,380,0.920,bilinear tf_efficientnet_b1_ns,94.860,5.140,99.250,0.750,7.79,240,0.882,bicubic +convnext_nano,94.860,5.140,99.150,0.850,15.59,288,1.000,bicubic +edgenext_small,94.830,5.170,99.410,0.590,5.59,320,1.000,bicubic +vit_base_patch16_rpn_224,94.820,5.180,99.090,0.910,86.54,224,0.900,bicubic xcit_small_12_p16_224,94.820,5.180,99.060,0.940,26.25,224,1.000,bicubic -seresnext50_32x4d,94.800,5.200,99.130,0.870,27.56,224,0.875,bicubic +seresnext50_32x4d,94.810,5.190,99.130,0.870,27.56,224,0.875,bicubic +cs3darknet_focus_l,94.790,5.210,99.150,0.850,21.15,288,0.950,bicubic pit_b_224,94.790,5.210,98.820,1.180,73.76,224,0.900,bicubic -lamhalobotnet50ts_256,94.780,5.220,98.980,1.020,22.57,256,0.950,bicubic -coat_mini,94.770,5.230,98.950,1.050,10.34,224,0.900,bicubic +mobilevitv2_175_in22ft1k,94.780,5.220,99.100,0.900,14.25,256,0.888,bicubic convnext_tiny_hnf,94.770,5.230,99.160,0.840,28.59,224,0.950,bicubic twins_svt_small,94.770,5.230,99.080,0.920,24.06,224,0.900,bicubic +lamhalobotnet50ts_256,94.770,5.230,98.980,1.020,22.57,256,0.950,bicubic +coat_mini,94.770,5.230,98.950,1.050,10.34,224,0.900,bicubic +swinv2_cr_tiny_ns_224,94.760,5.240,99.110,0.890,28.33,224,0.900,bicubic resnetv2_50x1_bitm,94.750,5.250,99.180,0.820,25.55,448,1.000,bilinear pit_s_distilled_224,94.740,5.260,99.180,0.820,24.04,224,0.900,bicubic -xcit_tiny_12_p8_224_dist,94.730,5.270,99.180,0.820,6.71,224,1.000,bicubic legacy_senet154,94.730,5.270,99.100,0.900,115.09,224,0.875,bilinear +xcit_tiny_12_p8_224_dist,94.720,5.280,99.180,0.820,6.71,224,1.000,bicubic +crossvit_15_240,94.720,5.280,99.080,0.920,27.53,240,0.875,bicubic gluon_resnet152_v1s,94.720,5.280,99.060,0.940,60.32,224,0.875,bicubic -crossvit_15_240,94.710,5.290,99.070,0.930,27.53,240,0.875,bicubic -gluon_senet154,94.710,5.290,98.970,1.030,115.09,224,0.875,bicubic -halonet50ts,94.710,5.290,98.820,1.180,22.73,256,0.940,bicubic resnest50d_4s2x40d,94.710,5.290,99.140,0.860,30.42,224,0.875,bicubic +gluon_senet154,94.710,5.290,98.970,1.030,115.09,224,0.875,bicubic +halonet50ts,94.710,5.290,98.830,1.170,22.73,256,0.940,bicubic ssl_resnext50_32x4d,94.700,5.300,99.240,0.760,25.03,224,0.875,bilinear +vit_relpos_small_patch16_224,94.690,5.310,99.100,0.900,21.98,224,0.900,bicubic +mobilevitv2_150_in22ft1k,94.690,5.310,98.920,1.080,10.59,256,0.888,bicubic +deit3_small_patch16_224,94.690,5.310,98.750,1.250,22.06,224,0.900,bicubic +cs3darknet_l,94.680,5.320,99.220,0.780,21.16,288,0.950,bicubic regnetz_b16,94.680,5.320,99.160,0.840,9.72,288,0.940,bicubic efficientnet_el,94.670,5.330,99.130,0.870,10.59,300,0.904,bicubic -gluon_seresnext101_64x4d,94.660,5.340,98.980,1.020,88.23,224,0.875,bicubic +tresnet_m_448,94.660,5.340,99.150,0.850,31.39,448,0.875,bilinear rexnet_200,94.660,5.340,99.090,0.910,16.37,224,0.875,bicubic wide_resnet50_2,94.660,5.340,99.050,0.950,68.88,224,0.875,bicubic -tresnet_m_448,94.650,5.350,99.150,0.850,31.39,448,0.875,bilinear -resnest50d,94.620,5.380,99.030,0.970,27.48,224,0.875,bilinear +gluon_seresnext101_64x4d,94.660,5.340,98.980,1.020,88.23,224,0.875,bicubic swin_tiny_patch4_window7_224,94.620,5.380,99.120,0.880,28.29,224,0.900,bicubic poolformer_s36,94.620,5.380,99.050,0.950,30.86,224,0.900,bicubic +resnest50d,94.620,5.380,99.030,0.970,27.48,224,0.875,bilinear gcresnet50t,94.620,5.380,98.980,1.020,25.90,256,0.900,bicubic -deit_small_distilled_patch16_224,94.600,5.400,99.100,0.900,22.44,224,0.900,bicubic twins_pcpvt_small,94.600,5.400,99.150,0.850,24.11,224,0.900,bicubic vit_small_patch32_384,94.600,5.400,99.140,0.860,22.92,384,1.000,bicubic -pit_s_224,94.590,5.410,98.920,1.080,23.46,224,0.900,bicubic +deit_small_distilled_patch16_224,94.600,5.400,99.100,0.900,22.44,224,0.900,bicubic crossvit_small_240,94.580,5.420,99.120,0.880,26.86,240,0.875,bicubic efficientnet_b3_pruned,94.580,5.420,99.070,0.930,9.86,300,0.904,bicubic -tnt_s_patch16_224,94.580,5.420,99.180,0.820,23.76,224,0.900,bicubic -resnext50_32x4d,94.570,5.430,98.800,1.200,25.03,224,0.950,bicubic +pit_s_224,94.580,5.420,98.930,1.070,23.46,224,0.900,bicubic +resnext50_32x4d,94.580,5.420,98.800,1.200,25.03,224,0.950,bicubic +tnt_s_patch16_224,94.570,5.430,99.180,0.820,23.76,224,0.900,bicubic lambda_resnet50ts,94.570,5.430,98.650,1.350,21.54,256,0.950,bicubic repvgg_b3,94.560,5.440,98.910,1.090,123.09,224,0.875,bilinear -gernet_m,94.550,5.450,98.930,1.070,21.14,224,0.875,bilinear resmlp_36_distilled_224,94.550,5.450,99.160,0.840,44.69,224,0.875,bicubic +vit_srelpos_small_patch16_224,94.550,5.450,99.140,0.860,21.97,224,0.900,bicubic +gernet_m,94.550,5.450,98.930,1.070,21.14,224,0.875,bilinear +sehalonet33ts,94.540,5.460,98.760,1.240,13.69,256,0.940,bicubic xcit_tiny_12_p16_384_dist,94.530,5.470,99.170,0.830,6.72,384,1.000,bicubic -haloregnetz_b,94.520,5.480,98.970,1.030,11.68,224,0.940,bicubic regnety_320,94.520,5.480,99.170,0.830,145.05,224,0.875,bicubic -sehalonet33ts,94.520,5.480,98.750,1.250,13.69,256,0.940,bicubic +haloregnetz_b,94.520,5.480,98.960,1.040,11.68,224,0.940,bicubic +mobilevitv2_200,94.510,5.490,98.970,1.030,18.45,256,0.888,bicubic repvgg_b3g4,94.500,5.500,99.020,0.980,83.83,224,0.875,bilinear -ecaresnet101d_pruned,94.450,5.550,99.100,0.900,24.88,224,0.875,bicubic +ecaresnet101d_pruned,94.460,5.540,99.090,0.910,24.88,224,0.875,bicubic gluon_seresnext101_32x4d,94.450,5.550,99.090,0.910,48.96,224,0.875,bicubic gluon_resnet152_v1d,94.440,5.560,99.010,0.990,60.21,224,0.875,bicubic convmixer_768_32,94.430,5.570,99.110,0.890,21.11,224,0.960,bicubic +levit_256,94.410,5.590,99.060,0.940,18.89,224,0.900,bicubic gcresnext50ts,94.410,5.590,98.990,1.010,15.67,256,0.900,bicubic -levit_256,94.400,5.600,99.060,0.940,18.89,224,0.900,bicubic nf_resnet50,94.390,5.610,99.070,0.930,25.56,288,0.940,bicubic +resnest50d_1s4x24d,94.390,5.610,99.070,0.930,25.68,224,0.875,bicubic vit_base_patch32_224,94.390,5.610,99.060,0.940,88.22,224,0.900,bicubic -resnest50d_1s4x24d,94.380,5.620,99.070,0.930,25.68,224,0.875,bicubic inception_v4,94.380,5.620,98.820,1.180,42.68,299,0.875,bicubic efficientnet_b2,94.370,5.630,99.050,0.950,9.11,288,1.000,bicubic tf_efficientnet_el,94.360,5.640,99.100,0.900,10.59,300,0.904,bicubic xcit_tiny_12_p8_224,94.360,5.640,99.070,0.930,6.71,224,1.000,bicubic +darknet53,94.360,5.640,99.050,0.950,41.61,288,1.000,bicubic +edgenext_small_rw,94.360,5.640,99.040,0.960,7.83,320,1.000,bicubic gluon_resnext101_64x4d,94.350,5.650,98.880,1.120,83.46,224,0.875,bicubic -inception_resnet_v2,94.340,5.660,98.800,1.200,55.84,299,0.897,bicubic resmlp_24_distilled_224,94.340,5.660,99.090,0.910,30.02,224,0.875,bicubic poolformer_s24,94.330,5.670,99.060,0.940,21.39,224,0.900,bicubic -ssl_resnet50,94.310,5.690,99.150,0.850,25.56,224,0.875,bilinear -sebotnet33ts_256,94.310,5.690,98.590,1.410,13.70,256,0.940,bicubic -resmlp_big_24_224,94.270,5.730,98.820,1.180,129.14,224,0.875,bicubic +inception_resnet_v2,94.330,5.670,98.800,1.200,55.84,299,0.897,bicubic +ssl_resnet50,94.320,5.680,99.150,0.850,25.56,224,0.875,bilinear +sebotnet33ts_256,94.310,5.690,98.600,1.400,13.70,256,0.940,bicubic +rexnet_150,94.280,5.720,99.080,0.920,9.73,224,0.875,bicubic tf_efficientnet_b2_ap,94.270,5.730,98.950,1.050,9.11,260,0.890,bicubic resnetv2_50,94.270,5.730,98.930,1.070,25.55,224,0.950,bicubic seresnet33ts,94.270,5.730,98.780,1.220,19.78,256,0.900,bicubic regnetx_120,94.260,5.740,99.190,0.810,46.11,224,0.875,bicubic -rexnet_150,94.260,5.740,99.080,0.920,9.73,224,0.875,bicubic +resmlp_big_24_224,94.260,5.740,98.820,1.180,129.14,224,0.875,bicubic +cspresnext50,94.240,5.760,99.050,0.950,20.57,256,0.887,bilinear +mobilevitv2_175,94.230,5.770,98.930,1.070,14.25,256,0.888,bicubic mixnet_xl,94.230,5.770,98.820,1.180,11.90,224,0.875,bicubic regnetx_320,94.220,5.780,99.050,0.950,107.81,224,0.875,bicubic xcit_tiny_24_p16_224_dist,94.220,5.780,98.960,1.040,12.12,224,1.000,bicubic -tf_efficientnet_b2,94.210,5.790,99.030,0.970,9.11,260,0.890,bicubic +tf_efficientnet_b2,94.210,5.790,99.040,0.960,9.11,260,0.890,bicubic +darknetaa53,94.210,5.790,98.950,1.050,36.02,288,1.000,bilinear ecaresnet50d,94.200,5.800,99.020,0.980,25.58,224,0.875,bicubic +gluon_resnet101_v1d,94.180,5.820,98.940,1.060,44.57,224,0.875,bicubic dpn92,94.180,5.820,98.930,1.070,37.67,224,0.875,bicubic resnet50_gn,94.180,5.820,98.920,1.080,25.56,224,0.940,bicubic -gluon_resnet101_v1d,94.170,5.830,98.940,1.060,44.57,224,0.875,bicubic gluon_resnet101_v1s,94.170,5.830,99.010,0.990,44.67,224,0.875,bicubic gluon_seresnext50_32x4d,94.170,5.830,98.910,1.090,27.56,224,0.875,bicubic ecaresnetlight,94.140,5.860,98.950,1.050,30.16,224,0.875,bicubic -ens_adv_inception_resnet_v2,94.130,5.870,98.790,1.210,55.84,299,0.897,bicubic -tf_efficientnet_lite3,94.120,5.880,98.960,1.040,8.20,300,0.904,bilinear -gluon_resnext101_32x4d,94.120,5.880,98.940,1.060,44.18,224,0.875,bicubic legacy_seresnext101_32x4d,94.120,5.880,98.970,1.030,48.96,224,0.875,bilinear +gluon_resnext101_32x4d,94.120,5.880,98.930,1.070,44.18,224,0.875,bicubic +ens_adv_inception_resnet_v2,94.120,5.880,98.790,1.210,55.84,299,0.897,bicubic +tf_efficientnet_lite3,94.110,5.890,98.960,1.040,8.20,300,0.904,bilinear +efficientnet_el_pruned,94.090,5.910,99.010,0.990,10.59,300,0.904,bicubic cspdarknet53,94.090,5.910,98.980,1.020,27.64,256,0.887,bilinear -efficientnet_el_pruned,94.090,5.910,99.020,0.980,10.59,300,0.904,bicubic seresnet50,94.080,5.920,98.950,1.050,28.09,224,0.875,bicubic resnet50d,94.070,5.930,98.920,1.080,25.58,224,0.875,bicubic -tf_efficientnetv2_b2,94.070,5.930,98.930,1.070,10.10,260,0.890,bicubic +mobilevitv2_150,94.070,5.930,98.900,1.100,10.59,256,0.888,bicubic +tf_efficientnetv2_b2,94.060,5.940,98.930,1.070,10.10,260,0.890,bicubic +hrnet_w48,94.030,5.970,99.030,0.970,77.47,224,0.875,bilinear gluon_resnet152_v1b,94.030,5.970,98.750,1.250,60.19,224,0.875,bicubic -hrnet_w48,94.030,5.970,99.040,0.960,77.47,224,0.875,bilinear resnetrs50,94.020,5.980,98.850,1.150,35.69,224,0.910,bicubic +regnety_120,94.010,5.990,99.030,0.970,51.82,224,0.875,bicubic gluon_xception65,94.010,5.990,99.020,0.980,39.92,299,0.903,bicubic -regnety_120,94.010,5.990,99.040,0.960,51.82,224,0.875,bicubic dla102x2,94.000,6.000,99.030,0.970,41.28,224,0.875,bilinear -deit_small_patch16_224,93.980,6.020,98.960,1.040,22.05,224,0.900,bicubic +deit_small_patch16_224,93.990,6.010,98.960,1.040,22.05,224,0.900,bicubic +ecaresnet26t,93.960,6.040,98.920,1.080,16.01,320,0.950,bicubic dpn107,93.960,6.040,98.830,1.170,86.92,224,0.875,bicubic -ecaresnet26t,93.950,6.050,98.920,1.080,16.01,320,0.950,bicubic skresnext50_32x4d,93.950,6.050,98.830,1.170,27.48,224,0.875,bicubic -cait_xxs36_224,93.930,6.070,98.880,1.120,17.30,224,1.000,bicubic -dpn98,93.920,6.080,98.920,1.080,61.57,224,0.875,bicubic -resnet50,93.920,6.080,98.470,1.530,25.56,224,0.950,bicubic -gluon_resnet152_v1c,93.890,6.110,98.800,1.200,60.21,224,0.875,bicubic +dpn98,93.930,6.070,98.920,1.080,61.57,224,0.875,bicubic +cait_xxs36_224,93.930,6.070,98.890,1.110,17.30,224,1.000,bicubic +resnet50,93.930,6.070,98.470,1.530,25.56,224,0.950,bicubic regnetx_160,93.890,6.110,99.090,0.910,54.28,224,0.875,bicubic vit_base_patch16_224_sam,93.890,6.110,98.890,1.110,86.57,224,0.900,bicubic -xception71,93.890,6.110,98.950,1.050,42.34,299,0.903,bicubic -nf_regnet_b1,93.880,6.120,98.740,1.260,10.22,288,0.900,bicubic -cspresnet50,93.860,6.140,98.860,1.140,21.62,256,0.887,bilinear +gluon_resnet152_v1c,93.890,6.110,98.800,1.200,60.21,224,0.875,bicubic +xception71,93.880,6.120,98.950,1.050,42.34,299,0.903,bicubic +nf_regnet_b1,93.880,6.120,98.750,1.250,10.22,288,0.900,bicubic eca_resnet33ts,93.860,6.140,98.890,1.110,19.68,256,0.900,bicubic +cspresnet50,93.860,6.140,98.860,1.140,21.62,256,0.887,bilinear +fbnetv3_d,93.850,6.150,98.910,1.090,10.31,256,0.950,bilinear ese_vovnet39b,93.850,6.150,98.900,1.100,24.57,224,0.875,bicubic -fbnetv3_d,93.840,6.160,98.910,1.090,10.31,256,0.950,bilinear -hrnet_w64,93.840,6.160,98.930,1.070,128.06,224,0.875,bilinear xcit_tiny_24_p16_224,93.840,6.160,98.760,1.240,12.12,224,1.000,bicubic +hrnet_w64,93.830,6.170,98.920,1.080,128.06,224,0.875,bilinear +gcresnet33ts,93.830,6.170,98.910,1.090,19.88,256,0.900,bicubic ecaresnet50d_pruned,93.820,6.180,99.000,1.000,19.94,224,0.875,bicubic -gcresnet33ts,93.820,6.180,98.910,1.090,19.88,256,0.900,bicubic -repvgg_b2g4,93.810,6.190,98.930,1.070,61.76,224,0.875,bilinear -resnext50d_32x4d,93.810,6.190,98.740,1.260,25.05,224,0.875,bicubic +repvgg_b2g4,93.820,6.180,98.930,1.070,61.76,224,0.875,bilinear +resnext50d_32x4d,93.820,6.180,98.740,1.260,25.05,224,0.875,bicubic efficientnet_b2_pruned,93.800,6.200,98.910,1.090,8.31,260,0.890,bicubic -dla169,93.800,6.200,98.830,1.170,53.39,224,0.875,bilinear regnetx_080,93.790,6.210,98.900,1.100,39.57,224,0.875,bicubic -cspresnext50,93.780,6.220,98.840,1.160,20.57,224,0.875,bilinear +dla169,93.790,6.210,98.830,1.170,53.39,224,0.875,bilinear resnext101_32x8d,93.770,6.230,98.950,1.050,88.79,224,0.875,bilinear gluon_resnet101_v1b,93.760,6.240,98.700,1.300,44.55,224,0.875,bicubic +tf_efficientnet_b0_ns,93.750,6.250,98.970,1.030,5.29,224,0.875,bicubic dpn131,93.750,6.250,98.830,1.170,79.25,224,0.875,bicubic efficientnet_em,93.740,6.260,98.930,1.070,6.90,240,0.882,bicubic -tf_efficientnet_b0_ns,93.740,6.260,98.980,1.020,5.29,224,0.875,bicubic -wide_resnet101_2,93.730,6.270,98.810,1.190,126.89,224,0.875,bilinear -hrnet_w40,93.710,6.290,98.800,1.200,57.56,224,0.875,bilinear -levit_192,93.710,6.290,98.800,1.200,10.95,224,0.900,bicubic +wide_resnet101_2,93.720,6.280,98.810,1.190,126.89,224,0.875,bilinear +levit_192,93.720,6.280,98.790,1.210,10.95,224,0.900,bicubic +tf_efficientnetv2_b1,93.710,6.290,98.820,1.180,8.14,240,0.882,bicubic resnetblur50,93.710,6.290,98.810,1.190,25.56,224,0.875,bicubic +hrnet_w40,93.710,6.290,98.800,1.200,57.56,224,0.875,bilinear tf_efficientnet_b1,93.710,6.290,98.800,1.200,7.79,240,0.882,bicubic -tf_efficientnetv2_b1,93.710,6.290,98.820,1.180,8.14,240,0.882,bicubic -gluon_resnet101_v1c,93.690,6.310,98.760,1.240,44.57,224,0.875,bicubic -rexnet_130,93.680,6.320,98.710,1.290,7.56,224,0.875,bicubic +gluon_resnet101_v1c,93.680,6.320,98.760,1.240,44.57,224,0.875,bicubic regnetx_040,93.670,6.330,98.940,1.060,22.12,224,0.875,bicubic +rexnet_130,93.670,6.330,98.700,1.300,7.56,224,0.875,bicubic resmlp_36_224,93.650,6.350,98.950,1.050,44.69,224,0.875,bicubic gluon_resnext50_32x4d,93.650,6.350,98.690,1.310,25.03,224,0.875,bicubic xception,93.640,6.360,98.760,1.240,22.86,299,0.897,bicubic -fbnetv3_b,93.640,6.360,98.910,1.090,8.60,256,0.950,bilinear -resnet33ts,93.630,6.370,98.760,1.240,19.68,256,0.900,bicubic +fbnetv3_b,93.630,6.370,98.910,1.090,8.60,256,0.950,bilinear tf_efficientnet_b1_ap,93.630,6.370,98.800,1.200,7.79,240,0.882,bicubic -dpn68b,93.620,6.380,98.700,1.300,12.61,224,0.875,bicubic +resnet33ts,93.630,6.370,98.760,1.240,19.68,256,0.900,bicubic regnetx_064,93.620,6.380,99.050,0.950,26.21,224,0.875,bicubic +dpn68b,93.620,6.380,98.700,1.300,12.61,224,0.875,bicubic hrnet_w44,93.610,6.390,98.960,1.040,67.06,224,0.875,bilinear -halonet26t,93.600,6.400,98.640,1.360,12.48,256,0.950,bicubic +halonet26t,93.610,6.390,98.640,1.360,12.48,256,0.950,bicubic res2net50_26w_6s,93.600,6.400,98.750,1.250,37.05,224,0.875,bilinear -gluon_resnet50_v1s,93.590,6.410,98.840,1.160,25.68,224,0.875,bicubic repvgg_b2,93.590,6.410,99.070,0.930,89.02,224,0.875,bilinear -dla60_res2next,93.570,6.430,98.790,1.210,17.03,224,0.875,bilinear -resnet32ts,93.570,6.430,98.750,1.250,17.96,256,0.900,bicubic +gluon_resnet50_v1s,93.590,6.410,98.840,1.160,25.68,224,0.875,bicubic tf_efficientnet_cc_b1_8e,93.570,6.430,98.690,1.310,39.72,240,0.882,bicubic +resnet32ts,93.560,6.440,98.750,1.250,17.96,256,0.900,bicubic eca_halonext26ts,93.560,6.440,98.680,1.320,10.76,256,0.940,bicubic +dla60_res2next,93.550,6.450,98.780,1.220,17.03,224,0.875,bilinear gluon_inception_v3,93.540,6.460,98.830,1.170,23.83,299,0.875,bicubic +dla102x,93.530,6.470,98.850,1.150,26.31,224,0.875,bilinear gluon_resnet50_v1d,93.530,6.470,98.710,1.290,25.58,224,0.875,bicubic -res2net101_26w_4s,93.520,6.480,98.600,1.400,45.21,224,0.875,bilinear -coat_tiny,93.520,6.480,98.690,1.310,5.50,224,0.900,bicubic -dla102x,93.520,6.480,98.850,1.150,26.31,224,0.875,bilinear +res2net101_26w_4s,93.530,6.470,98.600,1.400,45.21,224,0.875,bilinear gmlp_s16_224,93.510,6.490,98.780,1.220,19.42,224,0.875,bicubic +coat_tiny,93.510,6.490,98.690,1.310,5.50,224,0.900,bicubic selecsls60b,93.500,6.500,98.840,1.160,32.77,224,0.875,bicubic -cait_xxs24_224,93.490,6.510,98.780,1.220,11.96,224,1.000,bicubic +cait_xxs24_224,93.490,6.510,98.770,1.230,11.96,224,1.000,bicubic xception41,93.480,6.520,98.750,1.250,26.97,299,0.903,bicubic +mobilevitv2_125,93.460,6.540,98.860,1.140,7.48,256,0.888,bicubic coat_lite_mini,93.460,6.540,98.780,1.220,11.01,224,0.900,bicubic -vit_tiny_patch16_384,93.450,6.550,98.830,1.170,5.79,384,1.000,bicubic -legacy_seresnet152,93.440,6.560,98.850,1.150,66.82,224,0.875,bilinear +vit_tiny_patch16_384,93.440,6.560,98.830,1.170,5.79,384,1.000,bicubic resmlp_24_224,93.440,6.560,98.810,1.190,30.02,224,0.875,bicubic -botnet26t_256,93.430,6.570,98.660,1.340,12.49,256,0.950,bicubic +res2net50_26w_8s,93.440,6.560,98.690,1.310,48.40,224,0.875,bilinear lambda_resnet26rpt_256,93.430,6.570,98.880,1.120,10.99,256,0.940,bicubic -legacy_seresnext50_32x4d,93.430,6.570,98.800,1.200,27.56,224,0.875,bilinear -res2net50_26w_8s,93.420,6.580,98.690,1.310,48.40,224,0.875,bilinear +legacy_seresnet152,93.430,6.570,98.850,1.150,66.82,224,0.875,bilinear +botnet26t_256,93.430,6.570,98.650,1.350,12.49,256,0.950,bicubic +legacy_seresnext50_32x4d,93.420,6.580,98.800,1.200,27.56,224,0.875,bilinear repvgg_b1,93.410,6.590,98.790,1.210,57.42,224,0.875,bilinear lambda_resnet26t,93.400,6.600,98.730,1.270,10.96,256,0.940,bicubic -hrnet_w30,93.390,6.610,98.830,1.170,37.71,224,0.875,bilinear -dla60_res2net,93.380,6.620,98.860,1.140,20.85,224,0.875,bilinear +hrnet_w30,93.380,6.620,98.830,1.170,37.71,224,0.875,bilinear +dla60_res2net,93.370,6.630,98.840,1.160,20.85,224,0.875,bilinear eca_botnext26ts_256,93.370,6.630,98.700,1.300,10.59,256,0.950,bicubic xcit_tiny_12_p16_224_dist,93.350,6.650,98.740,1.260,6.72,224,1.000,bicubic +xcit_nano_12_p8_384_dist,93.270,6.730,98.850,1.150,3.05,384,1.000,bicubic legacy_seresnet101,93.270,6.730,98.740,1.260,49.33,224,0.875,bilinear mixnet_l,93.270,6.730,98.700,1.300,7.33,224,0.875,bicubic dla102,93.260,6.740,98.770,1.230,33.27,224,0.875,bilinear -xcit_nano_12_p8_384_dist,93.260,6.740,98.850,1.150,3.05,384,1.000,bicubic +cs3darknet_m,93.260,6.740,98.720,1.280,9.31,288,0.950,bicubic +tv_resnet152,93.250,6.750,98.750,1.250,60.19,224,0.875,bilinear regnetx_032,93.250,6.750,98.730,1.270,15.30,224,0.875,bicubic resnest26d,93.240,6.760,98.850,1.150,17.07,224,0.875,bilinear -tv_resnet152,93.240,6.760,98.750,1.250,60.19,224,0.875,bilinear -pit_xs_distilled_224,93.240,6.760,98.820,1.180,11.00,224,0.900,bicubic +pit_xs_distilled_224,93.240,6.760,98.830,1.170,11.00,224,0.900,bicubic tf_inception_v3,93.200,6.800,98.480,1.520,23.83,299,0.875,bicubic dla60x,93.190,6.810,98.710,1.290,17.35,224,0.875,bilinear res2net50_26w_4s,93.180,6.820,98.670,1.330,25.70,224,0.875,bilinear tf_efficientnet_em,93.170,6.830,98.670,1.330,6.90,240,0.882,bicubic -mobilevit_s,93.160,6.840,98.780,1.220,5.58,256,0.900,bicubic -res2next50,93.140,6.860,98.650,1.350,24.67,224,0.875,bilinear -bat_resnext26ts,93.110,6.890,98.730,1.270,10.73,256,0.900,bicubic -tf_efficientnetv2_b0,93.060,6.940,98.700,1.300,7.14,224,0.875,bicubic +mobilevit_s,93.160,6.840,98.770,1.230,5.58,256,0.900,bicubic +res2next50,93.160,6.840,98.650,1.350,24.67,224,0.875,bilinear +vit_relpos_base_patch32_plus_rpn_256,93.160,6.840,98.320,1.680,119.42,256,0.900,bicubic +mobilevitv2_100,93.130,6.870,98.760,1.240,4.90,256,0.888,bicubic +cs3darknet_focus_m,93.110,6.890,98.740,1.260,9.30,288,0.950,bicubic +bat_resnext26ts,93.100,6.900,98.730,1.270,10.73,256,0.900,bicubic +tf_efficientnetv2_b0,93.060,6.940,98.690,1.310,7.14,224,0.875,bicubic +levit_128,93.050,6.950,98.700,1.300,9.21,224,0.900,bicubic +res2net50_14w_8s,93.040,6.960,98.700,1.300,25.06,224,0.875,bilinear tf_mixnet_l,93.040,6.960,98.540,1.460,7.33,224,0.875,bicubic -levit_128,93.040,6.960,98.680,1.320,9.21,224,0.900,bicubic -efficientnet_b1,93.030,6.970,98.710,1.290,7.79,256,1.000,bicubic repvgg_b1g4,93.030,6.970,98.820,1.180,39.97,224,0.875,bilinear -res2net50_14w_8s,93.030,6.970,98.700,1.300,25.06,224,0.875,bilinear +efficientnet_b1,93.020,6.980,98.710,1.290,7.79,256,1.000,bicubic +selecsls60,93.010,6.990,98.830,1.170,30.67,224,0.875,bicubic adv_inception_v3,93.010,6.990,98.490,1.510,23.83,299,0.875,bicubic regnety_016,93.000,7.000,98.680,1.320,11.20,224,0.875,bicubic -selecsls60,93.000,7.000,98.830,1.170,30.67,224,0.875,bicubic hardcorenas_f,92.980,7.020,98.620,1.380,8.20,224,0.875,bilinear efficientnet_b1_pruned,92.970,7.030,98.520,1.480,6.33,240,0.882,bicubic hrnet_w32,92.950,7.050,98.840,1.160,41.23,224,0.875,bilinear -hardcorenas_e,92.940,7.060,98.570,1.430,8.07,224,0.875,bilinear +hardcorenas_e,92.940,7.060,98.580,1.420,8.07,224,0.875,bilinear efficientnet_es,92.920,7.080,98.690,1.310,5.44,224,0.875,bicubic -gluon_resnet50_v1c,92.920,7.080,98.700,1.300,25.58,224,0.875,bicubic pit_xs_224,92.910,7.090,98.780,1.220,10.62,224,0.900,bicubic tv_resnext50_32x4d,92.910,7.090,98.720,1.280,25.03,224,0.875,bilinear +gluon_resnet50_v1c,92.910,7.090,98.700,1.300,25.58,224,0.875,bicubic +densenet161,92.900,7.100,98.810,1.190,28.68,224,0.875,bicubic inception_v3,92.900,7.100,98.330,1.670,23.83,299,0.875,bicubic -densenet161,92.890,7.110,98.810,1.190,28.68,224,0.875,bicubic tv_resnet101,92.880,7.120,98.660,1.340,44.55,224,0.875,bilinear resmlp_12_distilled_224,92.870,7.130,98.620,1.380,15.35,224,0.875,bicubic -tf_efficientnet_cc_b0_8e,92.870,7.130,98.460,1.540,24.01,224,0.875,bicubic +tf_efficientnet_cc_b0_8e,92.870,7.130,98.450,1.550,24.01,224,0.875,bicubic coat_lite_tiny,92.860,7.140,98.640,1.360,5.72,224,0.900,bicubic -rexnet_100,92.840,7.160,98.620,1.380,4.80,224,0.875,bicubic -tf_efficientnet_cc_b0_4e,92.840,7.160,98.440,1.560,13.31,224,0.875,bicubic +rexnet_100,92.850,7.150,98.620,1.380,4.80,224,0.875,bicubic +tf_efficientnet_cc_b0_4e,92.830,7.170,98.440,1.560,13.31,224,0.875,bicubic seresnext26ts,92.820,7.180,98.600,1.400,10.39,256,0.900,bicubic -seresnext26t_32x4d,92.810,7.190,98.560,1.440,16.81,224,0.875,bicubic -tinynet_a,92.790,7.210,98.560,1.440,6.19,192,0.875,bicubic +seresnext26t_32x4d,92.820,7.180,98.560,1.440,16.81,224,0.875,bicubic +tinynet_a,92.810,7.190,98.560,1.440,6.19,192,0.875,bicubic res2net50_48w_2s,92.790,7.210,98.480,1.520,25.29,224,0.875,bilinear +hrnet_w18,92.760,7.240,98.660,1.340,21.30,224,0.875,bilinear crossvit_9_dagger_240,92.760,7.240,98.510,1.490,8.78,240,0.875,bicubic -hrnet_w18,92.750,7.250,98.660,1.340,21.30,224,0.875,bilinear -densenet201,92.690,7.310,98.650,1.350,20.01,224,0.875,bicubic -gmixer_24_224,92.680,7.320,98.280,1.720,24.72,224,0.875,bicubic +densenet201,92.700,7.300,98.650,1.350,20.01,224,0.875,bicubic repvgg_a2,92.680,7.320,98.520,1.480,28.21,224,0.875,bilinear -dla60,92.670,7.330,98.630,1.370,22.04,224,0.875,bilinear +gmixer_24_224,92.680,7.320,98.280,1.720,24.72,224,0.875,bicubic legacy_seresnet50,92.670,7.330,98.650,1.350,28.09,224,0.875,bilinear resnet26t,92.670,7.330,98.580,1.420,16.01,256,0.940,bicubic -resnet34d,92.640,7.360,98.420,1.580,21.82,224,0.875,bicubic +dla60,92.660,7.340,98.630,1.370,22.04,224,0.875,bilinear +resnet34d,92.650,7.350,98.420,1.580,21.82,224,0.875,bicubic +tf_efficientnet_b0_ap,92.620,7.380,98.370,1.630,5.29,224,0.875,bicubic mobilenetv2_120d,92.610,7.390,98.500,1.500,5.83,224,0.875,bicubic -tf_efficientnet_b0_ap,92.610,7.390,98.370,1.630,5.29,224,0.875,bicubic +tf_efficientnet_lite2,92.600,7.400,98.550,1.450,6.09,260,0.890,bicubic hardcorenas_d,92.600,7.400,98.430,1.570,7.50,224,0.875,bilinear -legacy_seresnext26_32x4d,92.580,7.420,98.410,1.590,16.79,224,0.875,bicubic -tf_efficientnet_lite2,92.580,7.420,98.550,1.450,6.09,260,0.890,bicubic +legacy_seresnext26_32x4d,92.590,7.410,98.410,1.590,16.79,224,0.875,bicubic skresnet34,92.570,7.430,98.520,1.480,22.28,224,0.875,bicubic gluon_resnet50_v1b,92.560,7.440,98.550,1.450,25.56,224,0.875,bicubic -regnetx_016,92.540,7.460,98.550,1.450,9.19,224,0.875,bicubic -selecsls42b,92.480,7.520,98.440,1.560,32.46,224,0.875,bicubic +regnetx_016,92.530,7.470,98.550,1.450,9.19,224,0.875,bicubic efficientnet_b0,92.480,7.520,98.680,1.320,5.29,224,0.875,bicubic -gcresnext26ts,92.470,7.530,98.490,1.510,10.48,256,0.900,bicubic +selecsls42b,92.480,7.520,98.440,1.560,32.46,224,0.875,bicubic poolformer_s12,92.470,7.530,98.350,1.650,11.92,224,0.900,bicubic xcit_tiny_12_p16_224,92.460,7.540,98.630,1.370,6.72,224,1.000,bicubic +gcresnext26ts,92.460,7.540,98.490,1.510,10.48,256,0.900,bicubic gernet_s,92.440,7.560,98.500,1.500,8.17,224,0.875,bilinear seresnext26d_32x4d,92.430,7.570,98.540,1.460,16.81,224,0.875,bicubic -xcit_nano_12_p8_224_dist,92.430,7.570,98.520,1.480,3.05,224,1.000,bicubic +xcit_nano_12_p8_224_dist,92.420,7.580,98.520,1.480,3.05,224,1.000,bicubic eca_resnext26ts,92.410,7.590,98.620,1.380,10.30,256,0.900,bicubic +densenetblur121d,92.410,7.590,98.420,1.580,8.00,224,0.875,bicubic tf_efficientnet_b0,92.400,7.600,98.470,1.530,5.29,224,0.875,bicubic -densenetblur121d,92.400,7.600,98.410,1.590,8.00,224,0.875,bicubic +hardcorenas_c,92.360,7.640,98.350,1.650,5.52,224,0.875,bilinear convmixer_1024_20_ks9_p14,92.350,7.650,98.420,1.580,24.38,224,0.960,bicubic -hardcorenas_c,92.330,7.670,98.340,1.660,5.52,224,0.875,bilinear tf_efficientnet_lite1,92.310,7.690,98.490,1.510,5.42,240,0.882,bicubic -densenet169,92.280,7.720,98.590,1.410,14.15,224,0.875,bicubic +densenet169,92.290,7.710,98.590,1.410,14.15,224,0.875,bicubic mixnet_m,92.270,7.730,98.350,1.650,5.01,224,0.875,bicubic -dpn68,92.260,7.740,98.610,1.390,12.61,224,0.875,bicubic -mobilenetv3_large_100_miil,92.250,7.750,98.250,1.750,5.48,224,0.875,bilinear -resnet26d,92.250,7.750,98.450,1.550,16.01,224,0.875,bicubic +mobilenetv3_large_100_miil,92.270,7.730,98.240,1.760,5.48,224,0.875,bilinear +resnet26d,92.260,7.740,98.450,1.550,16.01,224,0.875,bicubic +dpn68,92.250,7.750,98.610,1.390,12.61,224,0.875,bicubic resnext26ts,92.220,7.780,98.250,1.750,10.30,256,0.900,bicubic -tf_mixnet_m,92.200,7.800,98.420,1.580,5.01,224,0.875,bicubic -vit_small_patch32_224,92.150,7.850,98.510,1.490,22.88,224,0.900,bicubic -tv_resnet50,92.140,7.860,98.420,1.580,25.56,224,0.875,bilinear +tf_mixnet_m,92.210,7.790,98.420,1.580,5.01,224,0.875,bicubic +vit_small_patch32_224,92.160,7.840,98.510,1.490,22.88,224,0.900,bicubic +xcit_nano_12_p16_384_dist,92.130,7.870,98.520,1.480,3.05,384,1.000,bicubic +tv_resnet50,92.130,7.870,98.420,1.580,25.56,224,0.875,bilinear resmlp_12_224,92.120,7.880,98.570,1.430,15.35,224,0.875,bicubic -tf_efficientnet_es,92.110,7.890,98.430,1.570,5.44,224,0.875,bicubic -xcit_nano_12_p16_384_dist,92.110,7.890,98.520,1.480,3.05,384,1.000,bicubic +tf_efficientnet_es,92.120,7.880,98.430,1.570,5.44,224,0.875,bicubic mobilenetv2_140,92.040,7.960,98.250,1.750,6.11,224,0.875,bicubic -ese_vovnet19b_dw,92.010,7.990,98.510,1.490,6.54,224,0.875,bicubic -hardcorenas_b,91.940,8.060,98.400,1.600,5.18,224,0.875,bilinear +ese_vovnet19b_dw,92.000,8.000,98.510,1.490,6.54,224,0.875,bicubic +mobilevitv2_075,91.970,8.030,98.300,1.700,2.87,256,0.888,bicubic densenet121,91.940,8.060,98.280,1.720,7.98,224,0.875,bicubic -regnety_008,91.910,8.090,98.420,1.580,6.26,224,0.875,bicubic +hardcorenas_b,91.930,8.070,98.400,1.600,5.18,224,0.875,bilinear vit_tiny_patch16_224,91.910,8.090,98.340,1.660,5.72,224,0.900,bicubic -mixnet_s,91.780,8.220,98.300,1.700,4.13,224,0.875,bicubic +regnety_008,91.900,8.100,98.420,1.580,6.26,224,0.875,bicubic +mixnet_s,91.770,8.230,98.300,1.700,4.13,224,0.875,bicubic vit_tiny_r_s16_p8_384,91.730,8.270,98.430,1.570,6.36,384,1.000,bicubic -efficientnet_es_pruned,91.700,8.300,98.410,1.590,5.44,224,0.875,bicubic +efficientnet_es_pruned,91.710,8.290,98.410,1.590,5.44,224,0.875,bicubic +tf_mixnet_s,91.690,8.310,98.240,1.760,4.13,224,0.875,bicubic repvgg_b0,91.680,8.320,98.450,1.550,15.82,224,0.875,bilinear -tf_mixnet_s,91.680,8.320,98.240,1.760,4.13,224,0.875,bicubic semnasnet_100,91.660,8.340,98.270,1.730,3.89,224,0.875,bicubic hardcorenas_a,91.620,8.380,98.170,1.830,5.26,224,0.875,bilinear -regnety_006,91.560,8.440,98.430,1.570,6.06,224,0.875,bicubic -mobilenetv3_rw,91.540,8.460,98.270,1.730,5.48,224,0.875,bicubic +regnety_006,91.550,8.450,98.430,1.570,6.06,224,0.875,bicubic +mobilenetv3_rw,91.550,8.450,98.280,1.720,5.48,224,0.875,bicubic levit_128s,91.500,8.500,98.400,1.600,7.78,224,0.900,bicubic -legacy_seresnet34,91.480,8.520,98.200,1.800,21.96,224,0.875,bilinear +legacy_seresnet34,91.490,8.510,98.200,1.800,21.96,224,0.875,bilinear mobilenetv3_large_100,91.480,8.520,98.320,1.680,5.48,224,0.875,bicubic resnet26,91.440,8.560,98.260,1.740,16.00,224,0.875,bicubic tf_mobilenetv3_large_100,91.420,8.580,98.260,1.740,5.48,224,0.875,bilinear -tv_densenet121,91.410,8.590,98.250,1.750,7.98,224,0.875,bicubic -mobilenetv2_110d,91.340,8.660,98.180,1.820,4.52,224,0.875,bicubic +tv_densenet121,91.400,8.600,98.250,1.750,7.98,224,0.875,bicubic +edgenext_x_small,91.400,8.600,98.160,1.840,2.34,256,0.900,bicubic +mobilenetv2_110d,91.330,8.670,98.190,1.810,4.52,224,0.875,bicubic tf_efficientnet_lite0,91.300,8.700,98.090,1.910,4.65,224,0.875,bicubic -fbnetc_100,91.260,8.740,97.830,2.170,5.57,224,0.875,bilinear efficientnet_lite0,91.260,8.740,98.250,1.750,4.65,224,0.875,bicubic -dla34,91.230,8.770,98.180,1.820,15.74,224,0.875,bilinear -mnasnet_100,91.200,8.800,98.050,1.950,4.38,224,0.875,bicubic +fbnetc_100,91.250,8.750,97.850,2.150,5.57,224,0.875,bilinear +dla34,91.230,8.770,98.170,1.830,15.74,224,0.875,bilinear +mnasnet_100,91.210,8.790,98.050,1.950,4.38,224,0.875,bicubic resnet34,91.200,8.800,98.240,1.760,21.80,224,0.875,bilinear -mobilevit_xs,91.180,8.820,98.220,1.780,2.32,256,0.900,bicubic -hrnet_w18_small_v2,91.170,8.830,98.340,1.660,15.60,224,0.875,bilinear +mobilevit_xs,91.200,8.800,98.220,1.780,2.32,256,0.900,bicubic +hrnet_w18_small_v2,91.170,8.830,98.330,1.670,15.60,224,0.875,bilinear regnetx_008,91.160,8.840,98.380,1.620,7.26,224,0.875,bicubic -xcit_nano_12_p8_224,91.140,8.860,98.230,1.770,3.05,224,1.000,bicubic -mixer_b16_224,91.140,8.860,97.400,2.600,59.88,224,0.875,bicubic +mixer_b16_224,91.150,8.850,97.400,2.600,59.88,224,0.875,bicubic +tinynet_b,91.140,8.860,98.060,1.940,3.73,188,0.875,bicubic resnest14d,91.130,8.870,98.330,1.670,10.61,224,0.875,bilinear -tinynet_b,91.130,8.870,98.070,1.930,3.73,188,0.875,bicubic -deit_tiny_distilled_patch16_224,91.110,8.890,98.270,1.730,5.91,224,0.900,bicubic +xcit_nano_12_p8_224,91.130,8.870,98.230,1.770,3.05,224,1.000,bicubic gluon_resnet34_v1b,91.100,8.900,98.180,1.820,21.80,224,0.875,bicubic -swsl_resnet18,91.080,8.920,98.210,1.790,11.69,224,0.875,bilinear +deit_tiny_distilled_patch16_224,91.080,8.920,98.270,1.730,5.91,224,0.900,bicubic +swsl_resnet18,91.070,8.930,98.210,1.790,11.69,224,0.875,bilinear crossvit_9_240,91.050,8.950,98.310,1.690,8.55,240,0.875,bicubic vgg19_bn,90.990,9.010,98.110,1.890,143.68,224,0.875,bilinear pit_ti_distilled_224,90.900,9.100,98.220,1.780,5.10,224,0.900,bicubic regnetx_006,90.770,9.230,98.100,1.900,6.20,224,0.875,bicubic regnety_004,90.770,9.230,98.080,1.920,4.34,224,0.875,bicubic ssl_resnet18,90.700,9.300,98.030,1.970,11.69,224,0.875,bilinear -spnasnet_100,90.610,9.390,97.950,2.050,4.42,224,0.875,bilinear -convit_tiny,90.550,9.450,98.210,1.790,5.71,224,0.875,bicubic -crossvit_tiny_240,90.540,9.460,97.940,2.060,7.01,240,0.875,bicubic +spnasnet_100,90.600,9.400,97.960,2.040,4.42,224,0.875,bilinear +convit_tiny,90.550,9.450,98.220,1.780,5.71,224,0.875,bicubic vgg16_bn,90.540,9.460,97.990,2.010,138.37,224,0.875,bilinear +crossvit_tiny_240,90.540,9.460,97.940,2.060,7.01,240,0.875,bicubic +pit_ti_224,90.440,9.560,98.010,1.990,4.85,224,0.900,bicubic ghostnet_100,90.440,9.560,97.830,2.170,5.18,224,0.875,bilinear -pit_ti_224,90.430,9.570,98.000,2.000,4.85,224,0.900,bicubic -tf_mobilenetv3_large_075,90.320,9.680,97.870,2.130,3.99,224,0.875,bilinear +tf_mobilenetv3_large_075,90.330,9.670,97.880,2.120,3.99,224,0.875,bilinear tv_resnet34,90.290,9.710,97.980,2.020,21.80,224,0.875,bilinear semnasnet_075,90.210,9.790,97.970,2.030,2.91,224,0.875,bicubic skresnet18,90.170,9.830,97.780,2.220,11.96,224,0.875,bicubic -xcit_nano_12_p16_224_dist,90.160,9.840,97.760,2.240,3.05,224,1.000,bicubic -resnet18d,89.990,10.010,97.830,2.170,11.71,224,0.875,bicubic -hrnet_w18_small,89.880,10.120,97.890,2.110,13.19,224,0.875,bilinear +xcit_nano_12_p16_224_dist,90.170,9.830,97.750,2.250,3.05,224,1.000,bicubic +resnet18d,89.980,10.020,97.830,2.170,11.71,224,0.875,bicubic +hrnet_w18_small,89.870,10.130,97.890,2.110,13.19,224,0.875,bilinear vit_base_patch32_224_sam,89.860,10.140,97.600,2.400,88.22,224,0.900,bicubic -mobilenetv2_100,89.830,10.170,97.830,2.170,3.50,224,0.875,bicubic +mobilenetv2_100,89.820,10.180,97.830,2.170,3.50,224,0.875,bicubic vgg19,89.680,10.320,97.550,2.450,143.67,224,0.875,bilinear deit_tiny_patch16_224,89.620,10.380,97.960,2.040,5.72,224,0.900,bicubic regnetx_004,89.470,10.530,97.770,2.230,5.16,224,0.875,bicubic vgg16,89.360,10.640,97.520,2.480,138.36,224,0.875,bilinear -vit_tiny_r_s16_p8_224,89.340,10.660,97.700,2.300,6.34,224,0.900,bicubic -legacy_seresnet18,89.260,10.740,97.680,2.320,11.78,224,0.875,bicubic -vgg13_bn,89.200,10.800,97.520,2.480,133.05,224,0.875,bilinear -tf_mobilenetv3_large_minimal_100,89.170,10.830,97.320,2.680,3.92,224,0.875,bilinear -lcnet_100,88.960,11.040,97.380,2.620,2.95,224,0.875,bicubic -xcit_nano_12_p16_224,88.950,11.050,97.390,2.610,3.05,224,1.000,bicubic +vit_tiny_r_s16_p8_224,89.350,10.650,97.700,2.300,6.34,224,0.900,bicubic +legacy_seresnet18,89.260,10.740,97.690,2.310,11.78,224,0.875,bicubic +edgenext_xx_small,89.230,10.770,97.260,2.740,1.33,256,0.900,bicubic +vgg13_bn,89.210,10.790,97.520,2.480,133.05,224,0.875,bilinear +tf_mobilenetv3_large_minimal_100,89.180,10.820,97.320,2.680,3.92,224,0.875,bilinear +resnet14t,89.110,10.890,97.370,2.630,10.08,224,0.950,bilinear +mobilevitv2_050,89.050,10.950,97.590,2.410,1.37,256,0.888,bicubic +lcnet_100,88.970,11.030,97.380,2.620,2.95,224,0.875,bicubic +xcit_nano_12_p16_224,88.960,11.040,97.400,2.600,3.05,224,1.000,bicubic gluon_resnet18_v1b,88.660,11.340,97.100,2.900,11.69,224,0.875,bicubic -tinynet_c,88.420,11.580,97.260,2.740,2.46,184,0.875,bicubic +tinynet_c,88.420,11.580,97.270,2.730,2.46,184,0.875,bicubic vgg11_bn,88.390,11.610,97.270,2.730,132.87,224,0.875,bilinear -regnety_002,88.190,11.810,97.420,2.580,3.16,224,0.875,bicubic +regnety_002,88.190,11.810,97.440,2.560,3.16,224,0.875,bicubic resnet18,88.150,11.850,97.120,2.880,11.69,224,0.875,bilinear mobilevit_xxs,87.950,12.050,97.180,2.820,1.27,256,0.900,bicubic vgg13,87.570,12.430,97.120,2.880,133.05,224,0.875,bilinear regnetx_002,87.380,12.620,96.990,3.010,2.68,224,0.875,bicubic vgg11,87.340,12.660,97.110,2.890,132.86,224,0.875,bilinear -dla60x_c,87.110,12.890,97.140,2.860,1.32,224,0.875,bilinear -mixer_l16_224,86.970,13.030,94.040,5.960,208.20,224,0.875,bicubic +dla60x_c,87.130,12.870,97.140,2.860,1.32,224,0.875,bilinear +mixer_l16_224,86.970,13.030,94.050,5.950,208.20,224,0.875,bicubic lcnet_075,86.940,13.060,96.530,3.470,2.36,224,0.875,bicubic -mobilenetv3_small_100,86.170,13.830,96.460,3.540,2.54,224,0.875,bicubic -tf_mobilenetv3_small_100,85.970,14.030,96.410,3.590,2.54,224,0.875,bilinear +resnet10t,86.730,13.270,96.670,3.330,5.44,224,0.950,bilinear +mobilenetv3_small_100,86.180,13.820,96.460,3.540,2.54,224,0.875,bicubic +tf_mobilenetv3_small_100,85.970,14.030,96.400,3.600,2.54,224,0.875,bilinear mnasnet_small,85.510,14.490,95.980,4.020,2.03,224,0.875,bicubic -dla46x_c,85.480,14.520,96.440,3.560,1.07,224,0.875,bilinear -tinynet_d,85.430,14.570,96.020,3.980,2.34,152,0.875,bicubic -mobilenetv2_050,84.990,15.010,95.620,4.380,1.97,224,0.875,bicubic -dla46_c,84.670,15.330,96.200,3.800,1.30,224,0.875,bilinear -tf_mobilenetv3_small_075,84.530,15.470,95.890,4.110,2.04,224,0.875,bilinear +dla46x_c,85.460,14.540,96.450,3.550,1.07,224,0.875,bilinear +tinynet_d,85.420,14.580,96.020,3.980,2.34,152,0.875,bicubic +mobilenetv2_050,85.010,14.990,95.620,4.380,1.97,224,0.875,bicubic +dla46_c,84.660,15.340,96.210,3.790,1.30,224,0.875,bilinear +tf_mobilenetv3_small_075,84.520,15.480,95.890,4.110,2.04,224,0.875,bilinear mobilenetv3_small_075,84.120,15.880,95.500,4.500,2.04,224,0.875,bicubic -lcnet_050,83.000,17.000,95.020,4.980,1.88,224,0.875,bicubic -tf_mobilenetv3_small_minimal_100,82.680,17.320,95.010,4.990,2.04,224,0.875,bilinear +lcnet_050,83.010,16.990,95.010,4.990,1.88,224,0.875,bicubic +tf_mobilenetv3_small_minimal_100,82.690,17.310,95.000,5.000,2.04,224,0.875,bilinear tinynet_e,79.800,20.200,93.980,6.020,2.04,106,0.875,bicubic mobilenetv3_small_050,78.100,21.900,93.010,6.990,1.59,224,0.875,bicubic diff --git a/results/results-imagenet-r.csv b/results/results-imagenet-r.csv index 41c51649..507e75d3 100644 --- a/results/results-imagenet-r.csv +++ b/results/results-imagenet-r.csv @@ -1,591 +1,669 @@ -model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation,top1_diff,top5_diff,rank_diff -ig_resnext101_32x48d,79.640,20.360,89.390,10.610,828.41,224,0.875,bilinear,-17.330,-10.280,+24 -ig_resnext101_32x32d,79.467,20.533,89.190,10.810,468.53,224,0.875,bilinear,-17.313,-10.430,+37 -ig_resnext101_32x16d,78.817,21.183,88.470,11.530,194.03,224,0.875,bilinear,-17.623,-11.070,+68 +model,top1,top1_err,top5,top5_err,param_count,img_size,crop_pct,interpolation,top1_diff,top5_diff,rank_diff +ig_resnext101_32x48d,79.650,20.350,89.393,10.607,828.41,224,0.875,bilinear,-17.320,-10.277,+33 +ig_resnext101_32x32d,79.467,20.533,89.180,10.820,468.53,224,0.875,bilinear,-17.313,-10.350,+51 +ig_resnext101_32x16d,78.817,21.183,88.477,11.523,194.03,224,0.875,bilinear,-17.623,-11.063,+83 tf_efficientnet_l2_ns_475,76.470,23.530,88.653,11.347,480.31,475,0.936,bicubic,-21.280,-11.167,0 -swsl_resnext101_32x16d,76.307,23.693,87.743,12.257,194.03,224,0.875,bilinear,-19.973,-11.757,+82 -ig_resnext101_32x8d,75.800,24.200,86.213,13.787,88.79,224,0.875,bilinear,-20.140,-13.167,+116 -swsl_resnext101_32x8d,75.587,24.413,86.940,13.060,88.79,224,0.875,bilinear,-20.653,-12.650,+86 -tf_efficientnet_l2_ns,74.660,25.340,87.543,12.457,480.31,800,0.960,bicubic,-23.120,-12.277,-6 +swsl_resnext101_32x16d,76.307,23.693,87.740,12.260,194.03,224,0.875,bilinear,-19.973,-11.760,+98 +ig_resnext101_32x8d,75.800,24.200,86.213,13.787,88.79,224,0.875,bilinear,-20.140,-13.167,+140 +swsl_resnext101_32x8d,75.583,24.417,86.940,13.060,88.79,224,0.875,bilinear,-20.657,-12.650,+101 +tf_efficientnet_l2_ns,74.657,25.343,87.547,12.453,480.31,800,0.960,bicubic,-23.123,-12.343,-6 beit_large_patch16_384,73.280,26.720,85.023,14.977,305.00,384,1.000,bicubic,-24.530,-14.767,-8 -beit_large_patch16_512,73.157,26.843,85.077,14.923,305.67,512,1.000,bicubic,-24.623,-14.813,-7 -swsl_resnext101_32x4d,72.663,27.337,85.160,14.840,44.18,224,0.875,bilinear,-23.387,-14.370,+99 -beit_large_patch16_224,71.043,28.957,83.417,16.583,304.43,224,0.900,bicubic,-26.437,-16.273,-6 -swsl_resnext50_32x4d,68.970,31.030,82.803,17.197,25.03,224,0.875,bilinear,-26.630,-16.637,+141 -swsl_resnet50,68.283,31.717,83.307,16.693,25.56,224,0.875,bilinear,-26.917,-15.973,+174 -tf_efficientnet_b7_ns,67.510,32.490,81.383,18.617,66.35,600,0.949,bicubic,-29.690,-18.317,0 -vit_large_patch16_384,67.060,32.940,78.710,21.290,304.72,384,1.000,bicubic,-30.360,-21.070,-8 -convnext_xlarge_384_in22ft1k,66.967,33.033,79.703,20.297,350.20,384,1.000,bicubic,-30.583,-20.097,-12 -swin_large_patch4_window12_384,66.290,33.710,79.787,20.213,196.74,384,1.000,bicubic,-30.890,-19.893,-2 -convnext_large_384_in22ft1k,65.977,34.023,79.203,20.797,197.77,384,1.000,bicubic,-31.463,-20.577,-12 -tf_efficientnet_b6_ns,65.590,34.410,79.563,20.437,43.04,528,0.942,bicubic,-31.430,-20.117,+4 +beit_large_patch16_512,73.157,26.843,85.080,14.920,305.67,512,1.000,bicubic,-24.623,-14.740,-7 +swsl_resnext101_32x4d,72.657,27.343,85.157,14.843,44.18,224,0.875,bilinear,-23.383,-14.373,+121 +beit_large_patch16_224,71.043,28.957,83.420,16.580,304.43,224,0.900,bicubic,-26.437,-16.270,-5 +deit3_huge_patch14_224_in21ft1k,70.813,29.187,82.193,17.807,632.13,224,1.000,bicubic,-26.437,-17.527,+4 +deit3_large_patch16_384_in21ft1k,70.563,29.437,82.437,17.563,304.76,384,1.000,bicubic,-26.997,-17.273,-9 +deit3_large_patch16_224_in21ft1k,69.720,30.280,81.197,18.803,304.37,224,1.000,bicubic,-27.590,-18.483,-4 +swsl_resnext50_32x4d,68.970,31.030,82.807,17.193,25.03,224,0.875,bilinear,-26.640,-16.633,+166 +swsl_resnet50,68.293,31.707,83.300,16.700,25.56,224,0.875,bilinear,-26.907,-16.090,+213 +swinv2_large_window12to24_192to384_22kft1k,67.673,32.327,80.097,19.903,196.74,384,1.000,bicubic,-29.607,-19.683,-4 +tf_efficientnet_b7_ns,67.537,32.463,81.380,18.620,66.35,600,0.949,bicubic,-29.653,-18.320,+3 +vit_large_patch16_384,67.060,32.940,78.703,21.297,304.72,384,1.000,bicubic,-30.360,-21.077,-11 +convnext_xlarge_384_in22ft1k,66.967,33.033,79.703,20.297,350.20,384,1.000,bicubic,-30.583,-20.097,-15 +swin_large_patch4_window12_384,66.290,33.710,79.783,20.217,196.74,384,1.000,bicubic,-30.890,-19.897,+1 +convnext_large_384_in22ft1k,65.980,34.020,79.203,20.797,197.77,384,1.000,bicubic,-31.460,-20.577,-15 +swinv2_base_window12to24_192to384_22kft1k,65.740,34.260,79.310,20.690,87.92,384,1.000,bicubic,-31.520,-20.480,-9 +swinv2_large_window12to16_192to256_22kft1k,65.633,34.367,78.460,21.540,196.74,256,0.900,bicubic,-31.607,-21.250,-5 +tf_efficientnet_b6_ns,65.590,34.410,79.560,20.440,43.04,528,0.942,bicubic,-31.430,-20.150,+5 convnext_xlarge_in22ft1k,65.423,34.577,78.243,21.757,350.20,224,0.875,bicubic,-31.817,-21.487,-8 -vit_large_patch16_224,64.343,35.657,76.187,23.813,304.33,224,0.900,bicubic,-32.367,-23.463,+24 -convnext_large_in22ft1k,64.177,35.823,77.580,22.420,197.77,224,0.875,bicubic,-33.083,-22.070,-11 -vit_large_r50_s32_384,64.107,35.893,75.847,24.153,329.09,384,1.000,bicubic,-32.843,-23.863,+4 -convnext_base_384_in22ft1k,64.093,35.907,77.737,22.263,88.59,384,1.000,bicubic,-33.197,-22.043,-15 -swin_large_patch4_window7_224,63.867,36.133,78.177,21.823,196.53,224,0.900,bicubic,-33.083,-21.483,+1 -beit_base_patch16_384,63.613,36.387,78.120,21.880,86.74,384,1.000,bicubic,-33.717,-21.600,-18 -swin_base_patch4_window12_384,63.473,36.527,78.067,21.933,87.90,384,1.000,bicubic,-33.647,-21.713,-10 -tf_efficientnet_b5_ns,63.047,36.953,77.787,22.213,30.39,456,0.934,bicubic,-33.823,-21.853,+5 -vit_base_patch8_224,62.197,37.803,75.613,24.387,86.58,224,0.900,bicubic,-34.883,-23.997,-10 -convnext_base_in22ft1k,62.017,37.983,76.037,23.963,88.59,224,0.875,bicubic,-34.823,-23.613,+4 -tf_efficientnet_b4_ns,61.230,38.770,76.170,23.830,19.34,380,0.922,bicubic,-35.480,-23.470,+13 -tf_efficientnetv2_l_in21ft1k,60.953,39.047,75.843,24.157,118.52,480,1.000,bicubic,-36.157,-23.867,-14 -tf_efficientnetv2_xl_in21ft1k,60.680,39.320,74.397,25.603,208.12,512,1.000,bicubic,-36.470,-25.223,-17 -beit_base_patch16_224,60.320,39.680,75.597,24.403,86.53,224,0.900,bicubic,-36.340,-24.063,+16 -vit_base_patch16_384,60.193,39.807,73.840,26.160,86.86,384,1.000,bicubic,-36.827,-25.870,-13 -swin_base_patch4_window7_224,59.543,40.457,74.220,25.780,87.77,224,0.900,bicubic,-37.137,-25.440,+13 -volo_d5_512,58.917,41.083,73.200,26.800,296.09,512,1.150,bicubic,-38.373,-26.560,-27 -volo_d5_448,58.790,41.210,73.053,26.947,295.91,448,1.150,bicubic,-38.450,-26.687,-25 -tf_efficientnetv2_m_in21ft1k,58.640,41.360,73.983,26.017,54.14,480,1.000,bicubic,-38.330,-25.627,-14 -vit_large_r50_s32_224,58.633,41.367,71.720,28.280,328.99,224,0.900,bicubic,-37.547,-27.810,+57 -tf_efficientnet_b8_ap,57.830,42.170,72.957,27.043,87.41,672,0.954,bicubic,-38.720,-26.613,+17 -cait_m48_448,57.477,42.523,71.870,28.130,356.46,448,1.000,bicubic,-39.403,-27.790,-11 -cait_m36_384,57.467,42.533,72.317,27.683,271.22,384,1.000,bicubic,-39.363,-27.343,-8 -tf_efficientnet_b3_ns,57.417,42.583,72.380,27.620,12.23,300,0.904,bicubic,-38.683,-27.100,+58 -volo_d4_448,57.290,42.710,71.533,28.467,193.41,448,1.150,bicubic,-39.780,-28.217,-25 -vit_base_patch16_224,56.833,43.167,70.643,29.357,86.57,224,0.900,bicubic,-39.467,-28.917,+38 -volo_d5_224,56.490,43.510,70.647,29.353,295.46,224,0.960,bicubic,-40.390,-28.973,-17 -xcit_large_24_p8_384_dist,56.350,43.650,71.320,28.680,188.93,384,1.000,bicubic,-40.410,-28.240,-6 -xcit_large_24_p8_224_dist,56.030,43.970,70.663,29.337,188.93,224,1.000,bicubic,-40.610,-28.797,+3 -xcit_large_24_p16_384_dist,54.910,45.090,69.853,30.147,189.10,384,1.000,bicubic,-42.030,-29.657,-22 -volo_d4_224,54.750,45.250,68.863,31.137,192.96,224,0.960,bicubic,-42.030,-30.807,-11 -vit_base_r50_s16_384,54.400,45.600,69.557,30.443,98.95,384,1.000,bicubic,-42.050,-30.103,+17 -resnetv2_152x4_bitm,54.320,45.680,70.170,29.830,936.53,480,1.000,bilinear,-42.560,-29.500,-21 -xcit_large_24_p16_224_dist,54.260,45.740,68.977,31.023,189.10,224,1.000,bicubic,-42.060,-30.523,+28 -vit_small_r26_s32_384,54.203,45.797,68.753,31.247,36.47,384,1.000,bicubic,-41.857,-30.797,+53 -volo_d3_448,53.990,46.010,68.020,31.980,86.63,448,1.000,bicubic,-43.030,-31.690,-35 -tf_efficientnet_b5_ap,53.867,46.133,69.160,30.840,30.39,456,0.934,bicubic,-42.213,-29.990,+47 -xcit_medium_24_p8_224_dist,53.663,46.337,68.403,31.597,84.32,224,1.000,bicubic,-42.857,-31.107,+3 -tf_efficientnet_b2_ns,53.600,46.400,70.270,29.730,9.11,260,0.890,bicubic,-41.920,-29.070,+103 -tf_efficientnet_b6_ap,53.557,46.443,68.550,31.450,43.04,528,0.942,bicubic,-42.813,-31.000,+15 -cait_s36_384,53.547,46.453,68.003,31.997,68.37,384,1.000,bicubic,-43.083,-31.597,-8 -convnext_large,53.530,46.470,68.180,31.820,197.77,224,0.875,bicubic,-42.490,-31.290,+51 -tf_efficientnet_b8,53.413,46.587,69.090,30.910,87.41,672,0.954,bicubic,-43.287,-30.510,-15 -xcit_medium_24_p8_384_dist,53.407,46.593,68.137,31.863,84.32,384,1.000,bicubic,-43.373,-31.393,-25 -vit_base_patch32_384,53.297,46.703,68.047,31.953,88.30,384,1.000,bicubic,-42.603,-31.393,+59 -tf_efficientnet_b7_ap,53.263,46.737,68.877,31.123,66.35,600,0.949,bicubic,-43.087,-30.643,+10 -xcit_medium_24_p16_384_dist,53.220,46.780,68.057,31.943,84.40,384,1.000,bicubic,-43.480,-31.473,-20 -tf_efficientnetv2_s_in21ft1k,53.140,46.860,69.003,30.997,21.46,384,1.000,bicubic,-43.330,-30.567,-4 -tf_efficientnet_b4_ap,53.090,46.910,68.213,31.787,19.34,380,0.922,bicubic,-42.400,-31.177,+95 -regnetz_e8,53.017,46.983,67.137,32.863,57.70,320,1.000,bicubic,-43.583,-32.473,-16 -dm_nfnet_f5,52.870,47.130,67.427,32.573,377.21,544,0.954,bicubic,-43.940,-32.243,-34 -volo_d3_224,52.707,47.293,66.317,33.683,86.33,224,0.960,bicubic,-43.733,-33.303,-1 -dm_nfnet_f6,52.447,47.553,67.117,32.883,438.36,576,0.956,bicubic,-44.473,-32.603,-44 -tf_efficientnet_b7,52.390,47.610,68.233,31.767,66.35,600,0.949,bicubic,-44.190,-31.277,-19 -tf_efficientnetv2_l,52.390,47.610,67.243,32.757,118.52,480,1.000,bicubic,-44.260,-32.317,-24 -xcit_small_24_p8_384_dist,52.360,47.640,66.840,33.160,47.63,384,1.000,bicubic,-44.460,-32.790,-40 -swsl_resnet18,52.333,47.667,70.477,29.523,11.69,224,0.875,bilinear,-38.747,-27.733,+456 -efficientnetv2_rw_m,52.327,47.673,67.210,32.790,53.24,416,1.000,bicubic,-43.943,-32.350,+9 -deit_base_distilled_patch16_384,52.253,47.747,67.737,32.263,87.63,384,1.000,bicubic,-44.257,-31.853,-17 -xcit_medium_24_p16_224_dist,52.200,47.800,66.890,33.110,84.40,224,1.000,bicubic,-44.060,-32.520,+9 -xcit_small_24_p8_224_dist,52.200,47.800,66.763,33.237,47.63,224,1.000,bicubic,-44.350,-32.777,-24 -dm_nfnet_f3,52.130,47.870,66.747,33.253,254.92,416,0.940,bicubic,-44.600,-32.883,-39 -resnetv2_152x2_bit_teacher_384,51.933,48.067,68.663,31.337,236.34,384,1.000,bicubic,-44.257,-30.837,+12 -resmlp_big_24_224_in22ft1k,51.893,48.107,68.470,31.530,129.14,224,0.875,bicubic,-44.457,-31.120,-7 -xcit_small_24_p16_384_dist,51.887,48.113,66.360,33.640,47.67,384,1.000,bicubic,-44.453,-33.220,-6 -cait_s24_384,51.773,48.227,66.313,33.687,47.06,384,1.000,bicubic,-44.797,-33.237,-30 -resnetv2_152x2_bitm,51.753,48.247,69.253,30.747,236.34,448,1.000,bilinear,-44.767,-30.337,-27 -ecaresnet269d,51.663,48.337,66.047,33.953,102.09,352,1.000,bicubic,-44.797,-33.493,-22 -vit_base_patch16_224_miil,51.550,48.450,65.207,34.793,86.54,224,0.875,bilinear,-44.480,-34.143,+22 -convnext_base,51.250,48.750,66.193,33.807,88.59,224,0.875,bicubic,-44.690,-33.187,+30 -pit_b_distilled_224,51.153,48.847,66.773,33.227,74.79,224,0.900,bicubic,-44.917,-32.607,+14 -xcit_small_12_p8_384_dist,51.090,48.910,65.843,34.157,26.21,384,1.000,bicubic,-45.390,-33.647,-29 -dm_nfnet_f4,50.903,49.097,65.557,34.443,316.07,512,0.951,bicubic,-45.877,-34.053,-52 -tf_efficientnet_b1_ns,50.880,49.120,67.923,32.077,7.79,240,0.882,bicubic,-43.980,-31.327,+139 -volo_d2_384,50.880,49.120,65.633,34.367,58.87,384,1.000,bicubic,-45.830,-33.967,-49 -xcit_small_24_p16_224_dist,50.737,49.263,65.010,34.990,47.67,224,1.000,bicubic,-45.063,-34.330,+37 -tf_efficientnetv2_m,50.553,49.447,66.007,33.993,54.14,480,1.000,bicubic,-45.987,-33.563,-38 -xcit_small_12_p16_384_dist,50.527,49.473,65.303,34.697,26.25,384,1.000,bicubic,-45.803,-34.187,-17 -efficientnet_b4,50.503,49.497,65.717,34.283,19.34,384,1.000,bicubic,-45.027,-33.683,+61 -volo_d1_384,50.473,49.527,64.920,35.080,26.78,384,1.000,bicubic,-45.997,-34.630,-35 -xcit_small_12_p8_224_dist,50.443,49.557,65.430,34.570,26.21,224,1.000,bicubic,-45.517,-33.990,+18 -resnetv2_101x3_bitm,50.400,49.600,67.790,32.210,387.93,448,1.000,bilinear,-45.850,-31.790,-12 -regnetz_040h,50.333,49.667,65.623,34.377,28.94,320,1.000,bicubic,-45.997,-33.897,-23 -ssl_resnext101_32x16d,50.250,49.750,66.017,33.983,194.03,224,0.875,bilinear,-45.160,-33.393,+68 -cait_s24_224,50.247,49.753,65.013,34.987,46.92,224,1.000,bicubic,-45.403,-34.257,+45 -eca_nfnet_l2,50.233,49.767,65.453,34.547,56.72,384,1.000,bicubic,-46.217,-34.177,-38 -vit_small_patch16_384,50.163,49.837,65.800,34.200,22.20,384,1.000,bicubic,-45.817,-33.790,+10 -resnest269e,50.153,49.847,64.670,35.330,110.93,416,0.928,bicubic,-45.967,-34.850,-8 -deit_base_distilled_patch16_224,50.060,49.940,66.227,33.773,87.34,224,0.900,bicubic,-45.690,-33.053,+27 -tf_efficientnet_b3_ap,50.057,49.943,65.207,34.793,12.23,300,0.904,bicubic,-44.913,-33.903,+106 -resnest200e,49.870,50.130,64.743,35.257,70.20,320,0.909,bicubic,-46.200,-34.737,-5 -volo_d2_224,49.813,50.187,64.590,35.410,58.68,224,0.960,bicubic,-46.607,-34.910,-40 -xception65,49.760,50.240,63.527,36.473,39.92,299,0.940,bicubic,-45.930,-35.783,+34 -convnext_small,49.570,50.430,64.833,35.167,50.22,224,0.875,bicubic,-46.040,-34.427,+38 -cait_xs24_384,49.527,50.473,64.903,35.097,26.67,384,1.000,bicubic,-46.483,-34.527,-1 -tf_efficientnet_b5,49.520,50.480,65.650,34.350,30.39,456,0.934,bicubic,-46.460,-33.800,0 -resnetv2_152x2_bit_teacher,49.480,50.520,65.613,34.387,236.34,224,0.875,bicubic,-46.270,-33.817,+21 -resnet200d,49.477,50.523,64.327,35.673,64.69,320,1.000,bicubic,-46.633,-35.133,-17 -xcit_small_12_p16_224_dist,49.420,50.580,63.850,36.150,26.25,224,1.000,bicubic,-46.320,-35.450,+20 -resnest101e,49.367,50.633,65.593,34.407,48.28,256,0.875,bilinear,-46.193,-33.677,+37 -regnetz_040,49.283,50.717,64.063,35.937,27.12,320,1.000,bicubic,-46.897,-35.447,-25 -seresnet152d,49.250,50.750,64.173,35.827,66.84,320,1.000,bicubic,-47.060,-35.337,-39 -resnet152d,49.247,50.753,64.410,35.590,60.21,320,1.000,bicubic,-46.623,-35.020,+4 -vit_base_patch32_224,49.247,50.753,64.340,35.660,88.22,224,0.900,bicubic,-45.143,-34.720,+161 -xcit_large_24_p8_224,49.243,50.757,62.843,37.157,188.93,224,1.000,bicubic,-46.837,-36.697,-22 -ssl_resnext101_32x8d,49.097,50.903,65.483,34.517,88.79,224,0.875,bilinear,-46.233,-33.827,+54 -resmlp_big_24_distilled_224,49.093,50.907,65.470,34.530,129.14,224,0.875,bicubic,-46.777,-33.970,-1 -volo_d1_224,48.970,51.030,63.183,36.817,26.63,224,0.960,bicubic,-47.060,-36.207,-16 -repvgg_b3,48.927,51.073,64.880,35.120,123.09,224,0.875,bilinear,-45.633,-34.030,+141 -resnetrs420,48.860,51.140,63.420,36.580,191.89,416,1.000,bicubic,-47.540,-36.120,-57 -efficientnetv2_rw_s,48.597,51.403,63.840,36.160,23.94,384,1.000,bicubic,-47.103,-35.540,+14 -regnetz_d32,48.593,51.407,65.193,34.807,27.58,320,0.950,bicubic,-47.267,-34.237,-3 -efficientnet_b3,48.563,51.437,64.250,35.750,12.23,320,1.000,bicubic,-46.577,-34.960,+60 -ecaresnet101d,48.543,51.457,64.103,35.897,44.57,224,0.875,bicubic,-46.617,-35.127,+56 -dm_nfnet_f2,48.377,51.623,63.237,36.763,193.78,352,0.920,bicubic,-48.083,-36.373,-68 -vit_small_r26_s32_224,48.367,51.633,63.803,36.197,36.43,224,0.900,bicubic,-46.763,-35.397,+58 -repvgg_b3g4,48.313,51.687,64.793,35.207,83.83,224,0.875,bilinear,-46.187,-34.227,+140 -vit_large_patch32_384,48.250,51.750,61.823,38.177,306.63,384,1.000,bicubic,-46.990,-37.497,+46 -convit_base,48.227,51.773,63.000,37.000,86.54,224,0.875,bicubic,-46.873,-36.140,+62 -swin_s3_base_224,48.140,51.860,62.270,37.730,71.13,224,0.900,bicubic,-47.900,-37.080,-30 -resnetrs350,48.060,51.940,62.650,37.350,163.96,384,1.000,bicubic,-48.180,-36.820,-50 -regnetz_d8,48.013,51.987,64.420,35.580,23.37,320,1.000,bicubic,-47.997,-35.100,-27 -twins_svt_large,47.947,52.053,62.903,37.097,99.27,224,0.900,bicubic,-47.773,-36.467,0 -repvgg_b2g4,47.797,52.203,64.380,35.620,61.76,224,0.875,bilinear,-46.013,-34.550,+205 -mixer_b16_224_miil,47.790,52.210,63.400,36.600,59.88,224,0.875,bilinear,-47.090,-35.680,+85 -seresnext101_32x8d,47.657,52.343,61.443,38.557,93.57,288,1.000,bicubic,-48.473,-37.917,-47 -eca_nfnet_l1,47.647,52.353,62.763,37.237,41.41,320,1.000,bicubic,-48.283,-36.727,-25 -resnetv2_50x3_bitm,47.593,52.407,65.603,34.397,217.32,448,1.000,bilinear,-48.677,-34.027,-60 -pit_s_distilled_224,47.550,52.450,63.497,36.503,24.04,224,0.900,bicubic,-47.190,-35.683,+93 -resnest50d_4s2x40d,47.483,52.517,63.810,36.190,30.42,224,0.875,bicubic,-47.227,-35.330,+99 -efficientnet_b3_pruned,47.450,52.550,62.800,37.200,9.86,300,0.904,bicubic,-47.130,-36.270,+115 -crossvit_18_dagger_408,47.383,52.617,60.940,39.060,44.61,408,1.000,bicubic,-48.757,-38.530,-54 -xcit_small_24_p8_224,47.293,52.707,60.980,39.020,47.63,224,1.000,bicubic,-48.617,-38.200,-30 -tresnet_m,47.223,52.777,62.000,38.000,31.39,224,0.875,bilinear,-48.157,-37.150,+23 -tf_efficientnet_b6,47.210,52.790,63.117,36.883,43.04,528,0.942,bicubic,-49.080,-36.403,-70 -convnext_tiny,47.180,52.820,63.217,36.783,28.59,224,0.875,bicubic,-47.780,-35.983,+61 -ssl_resnext101_32x4d,47.167,52.833,63.380,36.620,44.18,224,0.875,bilinear,-47.993,-35.930,+34 -resnetrs270,47.107,52.893,62.007,37.993,129.86,352,1.000,bicubic,-48.953,-37.473,-51 -regnetz_d8_evos,47.080,52.920,63.390,36.610,23.46,320,0.950,bicubic,-49.140,-36.100,-65 -tf_efficientnet_b4,47.077,52.923,62.867,37.133,19.34,380,0.922,bicubic,-48.513,-36.463,-6 -xcit_small_12_p8_224,46.983,53.017,60.527,39.473,26.21,224,1.000,bicubic,-48.437,-38.673,+10 -xcit_large_24_p16_224,46.957,53.043,60.667,39.333,189.10,224,1.000,bicubic,-47.993,-38.163,+59 -convnext_tiny_hnf,46.940,53.060,61.203,38.797,28.59,224,0.950,bicubic,-47.830,-37.957,+76 -xception65p,46.930,53.070,61.083,38.917,39.82,299,0.940,bicubic,-48.720,-38.307,-16 -resnet101d,46.897,53.103,62.323,37.677,44.57,320,1.000,bicubic,-48.853,-37.117,-28 -resnet152,46.793,53.207,60.420,39.580,60.19,224,0.950,bicubic,-48.777,-38.850,-11 -gluon_seresnext101_64x4d,46.670,53.330,61.297,38.703,88.23,224,0.875,bicubic,-47.990,-37.683,+86 -twins_pcpvt_large,46.630,53.370,62.243,37.757,60.99,224,0.900,bicubic,-49.090,-37.247,-26 -dm_nfnet_f1,46.547,53.453,61.403,38.597,132.63,320,0.910,bicubic,-49.833,-38.067,-95 -regnetv_064,46.483,53.517,62.253,37.747,30.58,288,1.000,bicubic,-49.287,-37.167,-35 -xcit_medium_24_p8_224,46.473,53.527,59.647,40.353,84.32,224,1.000,bicubic,-49.397,-39.433,-43 -crossvit_15_dagger_408,46.457,53.543,60.473,39.527,28.50,408,1.000,bicubic,-49.363,-38.837,-40 -resnetrs200,46.430,53.570,61.067,38.933,93.21,320,1.000,bicubic,-49.910,-38.483,-95 -swin_s3_small_224,46.390,53.610,60.893,39.107,49.74,224,0.900,bicubic,-49.440,-38.307,-43 -fbnetv3_g,46.333,53.667,62.407,37.593,16.62,288,0.950,bilinear,-48.797,-36.513,+22 -tresnet_xl,46.277,53.723,61.947,38.053,78.44,224,0.875,bilinear,-48.783,-37.313,+33 -xcit_tiny_24_p8_384_dist,46.257,53.743,60.710,39.290,12.11,384,1.000,bicubic,-49.973,-38.730,-84 -xcit_tiny_24_p8_224_dist,46.250,53.750,60.597,39.403,12.11,224,1.000,bicubic,-49.210,-38.793,-10 -gernet_m,46.177,53.823,62.690,37.310,21.14,224,0.875,bilinear,-48.373,-36.240,+92 -deit_small_distilled_patch16_224,46.170,53.830,62.407,37.593,22.44,224,0.900,bicubic,-48.430,-36.693,+81 -regnety_160,46.163,53.837,61.843,38.157,83.59,288,1.000,bicubic,-49.717,-37.717,-56 -crossvit_base_240,46.133,53.867,60.227,39.773,105.03,240,0.875,bicubic,-48.937,-39.063,+25 -resnest50d_1s4x24d,46.080,53.920,62.370,37.630,25.68,224,0.875,bicubic,-48.300,-36.450,+103 -tf_efficientnet_b0_ns,46.053,53.947,63.243,36.757,5.29,224,0.875,bicubic,-47.687,-35.737,+175 -jx_nest_base,46.043,53.957,60.103,39.897,67.72,224,0.875,bicubic,-49.497,-39.197,-27 -resnet51q,46.030,53.970,60.907,39.093,35.70,288,1.000,bilinear,-49.170,-38.483,+2 -vit_small_patch16_224,46.003,53.997,61.823,38.177,22.05,224,0.900,bicubic,-48.877,-37.447,+44 -regnety_080,45.953,54.047,60.867,39.133,39.18,288,1.000,bicubic,-49.897,-38.573,-58 -resnest50d,45.940,54.060,62.637,37.363,27.48,224,0.875,bilinear,-48.680,-36.343,+68 -crossvit_18_240,45.897,54.103,60.373,39.627,43.27,240,0.875,bicubic,-49.173,-38.847,+18 -regnety_032,45.893,54.107,61.540,38.460,19.44,288,1.000,bicubic,-49.587,-37.780,-26 -twins_pcpvt_base,45.890,54.110,61.343,38.657,43.83,224,0.900,bicubic,-49.570,-38.017,-23 -twins_svt_base,45.873,54.127,60.967,39.033,56.07,224,0.900,bicubic,-49.697,-38.263,-37 -levit_384,45.870,54.130,61.700,38.300,39.13,224,0.900,bicubic,-49.340,-37.460,-8 -crossvit_18_dagger_240,45.857,54.143,59.923,40.077,44.27,240,0.875,bicubic,-49.333,-39.197,-6 -crossvit_15_dagger_240,45.693,54.307,60.087,39.913,28.21,240,0.875,bicubic,-49.287,-39.073,+18 -regnetz_c16,45.690,54.310,62.517,37.483,13.46,320,0.940,bicubic,-49.710,-36.793,-24 -convmixer_1536_20,45.660,54.340,61.767,38.233,51.63,224,0.960,bicubic,-49.310,-37.403,+17 -gc_efficientnetv2_rw_t,45.650,54.350,60.197,39.803,13.68,288,1.000,bicubic,-49.630,-39.023,-17 -efficientnetv2_rw_t,45.603,54.397,60.183,39.817,13.65,288,1.000,bicubic,-49.467,-38.797,+6 -gluon_seresnext101_32x4d,45.597,54.403,61.150,38.850,48.96,224,0.875,bicubic,-48.853,-37.940,+78 -xcit_tiny_24_p16_384_dist,45.577,54.423,60.510,39.490,12.12,384,1.000,bicubic,-49.903,-38.850,-35 -xcit_small_24_p16_224,45.540,54.460,58.910,41.090,47.67,224,1.000,bicubic,-49.540,-40.150,+1 -xcit_medium_24_p16_224,45.530,54.470,59.000,41.000,84.40,224,1.000,bicubic,-49.600,-40.120,-9 -dm_nfnet_f0,45.470,54.530,60.987,39.013,71.49,256,0.900,bicubic,-50.220,-38.343,-59 -resnext101_64x4d,45.457,54.543,59.043,40.957,83.46,288,1.000,bicubic,-50.083,-40.247,-47 -gluon_resnet152_v1d,45.437,54.563,60.073,39.927,60.21,224,0.875,bicubic,-49.003,-38.937,+73 -nfnet_l0,45.417,54.583,62.080,37.920,35.07,288,1.000,bicubic,-49.973,-37.340,-33 -ssl_resnext50_32x4d,45.407,54.593,62.030,37.970,25.03,224,0.875,bilinear,-49.293,-37.210,+41 -resnetv2_50x1_bit_distilled,45.397,54.603,62.297,37.703,25.55,224,0.875,bicubic,-49.993,-37.133,-34 -xcit_small_12_p16_224,45.387,54.613,59.423,40.577,26.25,224,1.000,bicubic,-49.433,-39.637,+23 -jx_nest_small,45.357,54.643,59.010,40.990,38.35,224,0.875,bicubic,-50.173,-40.200,-51 -resnet61q,45.287,54.713,59.407,40.593,36.85,288,1.000,bicubic,-49.823,-39.673,-13 -tresnet_xl_448,45.230,54.770,61.440,38.560,78.44,448,0.875,bilinear,-50.280,-37.900,-51 -nasnetalarge,45.210,54.790,57.880,42.120,88.75,331,0.911,bicubic,-49.940,-41.250,-23 -convit_small,45.203,54.797,60.493,39.507,27.78,224,0.875,bicubic,-49.717,-38.607,+9 -swin_small_patch4_window7_224,45.163,54.837,60.323,39.677,49.61,224,0.900,bicubic,-50.557,-38.967,-76 -tf_efficientnet_b3,45.110,54.890,60.643,39.357,12.23,300,0.904,bicubic,-49.800,-38.517,+8 -resnet101,45.080,54.920,59.590,40.410,44.55,224,0.950,bicubic,-49.880,-39.490,-1 -rexnet_200,45.050,54.950,62.303,37.697,16.37,224,0.875,bicubic,-49.610,-36.787,+34 -resnetrs152,44.950,55.050,59.713,40.287,86.62,320,1.000,bicubic,-51.010,-39.667,-103 -resnetv2_101,44.933,55.067,58.847,41.153,44.54,224,0.950,bicubic,-49.997,-40.353,+1 -ecaresnetlight,44.890,55.110,60.783,39.217,30.16,224,0.875,bicubic,-49.250,-38.167,+90 -deit_base_patch16_224,44.873,55.127,59.187,40.813,86.57,224,0.900,bicubic,-50.137,-39.793,-13 -cait_xxs36_384,44.767,55.233,59.377,40.623,17.37,384,1.000,bicubic,-50.463,-39.953,-40 -deit_base_patch16_384,44.767,55.233,59.623,40.377,86.86,384,1.000,bicubic,-50.883,-39.617,-77 -resmlp_36_distilled_224,44.760,55.240,61.067,38.933,44.69,224,0.875,bicubic,-49.790,-38.093,+45 -gernet_l,44.740,55.260,58.950,41.050,31.08,256,0.875,bilinear,-50.190,-40.180,-4 -xcit_tiny_24_p16_224_dist,44.720,55.280,59.403,40.597,12.12,224,1.000,bicubic,-49.500,-39.557,+76 -resmlp_24_distilled_224,44.707,55.293,61.457,38.543,30.02,224,0.875,bicubic,-49.633,-37.633,+63 -tf_efficientnet_b2_ap,44.703,55.297,60.680,39.320,9.11,260,0.890,bicubic,-49.567,-38.250,+67 -gmlp_s16_224,44.477,55.523,58.630,41.370,19.42,224,0.875,bicubic,-49.033,-40.150,+159 -ens_adv_inception_resnet_v2,44.393,55.607,58.123,41.877,55.84,299,0.897,bicubic,-49.737,-40.667,+81 -tresnet_l,44.363,55.637,59.943,40.057,55.99,224,0.875,bilinear,-50.537,-39.087,-6 -gluon_resnext101_32x4d,44.297,55.703,59.087,40.913,44.18,224,0.875,bicubic,-49.823,-39.883,+81 -poolformer_m48,44.267,55.733,59.300,40.700,73.47,224,0.950,bicubic,-50.863,-39.920,-40 -wide_resnet50_2,44.177,55.823,59.697,40.303,68.88,224,0.875,bicubic,-50.483,-39.353,+18 -regnetz_c16_evos,44.153,55.847,61.057,38.943,13.49,320,0.950,bicubic,-51.477,-38.363,-87 -cspresnext50,44.147,55.853,60.537,39.463,20.57,224,0.875,bilinear,-49.633,-38.303,+115 -resnetv2_101x1_bitm,44.117,55.883,61.977,38.023,44.54,448,1.000,bilinear,-51.203,-37.393,-60 -crossvit_15_240,44.117,55.883,59.137,40.863,27.53,240,0.875,bicubic,-50.593,-39.933,+6 -seresnext50_32x4d,44.107,55.893,59.483,40.517,27.56,224,0.875,bicubic,-50.693,-39.647,-7 -gluon_resnet152_v1s,44.070,55.930,58.707,41.293,60.32,224,0.875,bicubic,-50.650,-40.353,+2 -pit_b_224,44.067,55.933,58.030,41.970,73.76,224,0.900,bicubic,-50.723,-40.790,-8 -poolformer_m36,44.030,55.970,59.067,40.933,56.17,224,0.950,bicubic,-50.980,-40.033,-32 -ssl_resnet50,44.023,55.977,61.907,38.093,25.56,224,0.875,bilinear,-50.287,-36.683,+49 -inception_resnet_v2,44.003,55.997,57.913,42.087,55.84,299,0.897,bicubic,-50.337,-40.887,+45 -pnasnet5large,43.953,56.047,56.723,43.277,86.06,331,0.911,bicubic,-51.407,-42.407,-70 -pit_s_224,43.897,56.103,58.633,41.367,23.46,224,0.900,bicubic,-50.693,-40.287,+15 -gluon_resnext101_64x4d,43.887,56.113,58.700,41.300,83.46,224,0.875,bicubic,-50.463,-40.180,+41 -coat_lite_small,43.820,56.180,57.137,42.863,19.84,224,0.900,bicubic,-51.260,-41.893,-48 -regnetv_040,43.787,56.213,58.467,41.533,20.64,288,1.000,bicubic,-51.943,-40.913,-112 -tnt_s_patch16_224,43.777,56.223,59.207,40.793,23.76,224,0.900,bicubic,-50.803,-39.973,+14 -cait_xxs36_224,43.767,56.233,58.733,41.267,17.30,224,1.000,bicubic,-50.163,-40.147,+79 -ecaresnet50d,43.750,56.250,60.377,39.623,25.58,224,0.875,bicubic,-50.450,-38.643,+52 -ecaresnet101d_pruned,43.733,56.267,59.603,40.397,24.88,224,0.875,bicubic,-50.717,-39.497,+22 -swin_s3_tiny_224,43.710,56.290,59.500,40.500,28.33,224,0.900,bicubic,-51.200,-39.610,-30 -tf_efficientnetv2_s,43.703,56.297,58.597,41.403,21.46,384,1.000,bicubic,-52.007,-40.803,-114 -rexnet_150,43.693,56.307,60.890,39.110,9.73,224,0.875,bicubic,-50.567,-38.190,+43 -pit_xs_distilled_224,43.660,56.340,60.710,39.290,11.00,224,0.900,bicubic,-49.580,-38.040,+156 -xcit_tiny_12_p8_224_dist,43.640,56.360,58.467,41.533,6.71,224,1.000,bicubic,-51.090,-40.633,-18 -crossvit_small_240,43.467,56.533,58.947,41.053,26.86,240,0.875,bicubic,-51.113,-40.173,+3 -gluon_resnet101_v1d,43.433,56.567,58.617,41.383,44.57,224,0.875,bicubic,-50.737,-40.323,+47 -ecaresnet50t,43.413,56.587,59.300,40.700,25.57,320,0.950,bicubic,-51.657,-39.820,-59 -gluon_resnet101_v1s,43.363,56.637,58.513,41.487,44.67,224,0.875,bicubic,-50.807,-40.497,+46 -cspdarknet53,43.360,56.640,59.433,40.567,27.64,256,0.887,bilinear,-50.730,-39.547,+52 -xcit_tiny_24_p8_224,43.307,56.693,57.277,42.723,12.11,224,1.000,bicubic,-51.583,-41.913,-38 -xcit_tiny_12_p8_384_dist,43.303,56.697,58.180,41.820,6.71,384,1.000,bicubic,-52.037,-41.160,-89 -dpn68b,43.277,56.723,58.673,41.327,12.61,224,0.875,bicubic,-50.343,-40.027,+106 -convmixer_768_32,43.267,56.733,59.367,40.633,21.11,224,0.960,bicubic,-51.163,-39.743,+11 -visformer_small,43.260,56.740,57.977,42.023,40.22,224,0.900,bicubic,-51.700,-41.233,-52 -eca_nfnet_l0,43.237,56.763,59.910,40.090,24.14,288,1.000,bicubic,-52.213,-39.480,-102 -regnety_064,43.223,56.777,57.227,42.773,30.58,288,1.000,bicubic,-52.567,-42.063,-139 -resnest26d,43.143,56.857,60.633,39.367,17.07,224,0.875,bilinear,-50.097,-38.187,+140 -vit_small_patch32_384,43.140,56.860,59.303,40.697,22.92,384,1.000,bicubic,-51.460,-39.837,-12 -twins_pcpvt_small,43.087,56.913,58.877,41.123,24.11,224,0.900,bicubic,-51.513,-40.273,-14 -resmlp_36_224,43.047,56.953,59.313,40.687,44.69,224,0.875,bicubic,-50.603,-39.377,+92 -cspresnet50,43.040,56.960,59.147,40.853,21.62,256,0.887,bilinear,-50.820,-39.713,+63 -dpn131,43.037,56.963,57.430,42.570,79.25,224,0.875,bicubic,-50.713,-41.400,+78 -tf_efficientnet_lite4,42.970,57.030,57.643,42.357,13.01,380,0.920,bilinear,-51.900,-41.447,-48 -twins_svt_small,42.927,57.073,58.467,41.533,24.06,224,0.900,bicubic,-51.843,-40.613,-41 -gluon_resnet152_v1b,42.897,57.103,57.733,42.267,60.19,224,0.875,bicubic,-51.133,-41.017,+41 -fbnetv3_d,42.883,57.117,59.693,40.307,10.31,256,0.950,bilinear,-50.957,-39.217,+61 -dpn107,42.863,57.137,57.373,42.627,86.92,224,0.875,bicubic,-51.097,-41.457,+46 -levit_256,42.820,57.180,57.907,42.093,18.89,224,0.900,bicubic,-51.580,-41.153,-2 -gluon_resnet152_v1c,42.810,57.190,57.733,42.267,60.21,224,0.875,bicubic,-51.080,-41.067,+50 -tf_efficientnet_b1_ap,42.807,57.193,58.813,41.187,7.79,240,0.882,bicubic,-50.823,-39.987,+87 -gcresnet50t,42.790,57.210,59.180,40.820,25.90,256,0.900,bicubic,-51.830,-39.940,-28 -gluon_xception65,42.787,57.213,58.817,41.183,39.92,299,0.903,bicubic,-51.223,-40.203,+37 -tresnet_l_448,42.743,57.257,58.947,41.053,55.99,448,0.875,bilinear,-52.657,-40.353,-116 -resnet50d,42.713,57.287,58.683,41.317,25.58,224,0.875,bicubic,-51.357,-40.237,+30 -gluon_seresnext50_32x4d,42.683,57.317,58.687,41.313,27.56,224,0.875,bicubic,-51.487,-40.223,+20 -xcit_tiny_12_p16_384_dist,42.587,57.413,58.080,41.920,6.72,384,1.000,bicubic,-51.943,-41.090,-20 -regnety_040,42.580,57.420,57.027,42.973,20.65,288,1.000,bicubic,-52.900,-42.393,-128 -resnext101_32x8d,42.570,57.430,58.293,41.707,88.79,224,0.875,bilinear,-51.200,-40.657,+60 -seresnet50,42.513,57.487,58.680,41.320,28.09,224,0.875,bicubic,-51.567,-40.270,+24 -nf_resnet50,42.507,57.493,59.530,40.470,25.56,288,0.940,bicubic,-51.883,-39.540,-13 -resnetrs101,42.443,57.557,57.287,42.713,63.62,288,0.940,bicubic,-52.807,-41.923,-115 -jx_nest_tiny,42.320,57.680,57.047,42.953,17.06,224,0.875,bicubic,-52.630,-42.053,-79 -poolformer_s36,42.320,57.680,58.750,41.250,30.86,224,0.900,bicubic,-52.300,-40.280,-41 -tf_efficientnetv2_b3,42.320,57.680,57.937,42.063,14.36,300,0.904,bicubic,-52.800,-41.293,-103 -convmixer_1024_20_ks9_p14,42.277,57.723,59.713,40.287,24.38,224,0.960,bicubic,-50.073,-38.707,+179 -xcit_tiny_24_p16_224,42.277,57.723,56.827,43.173,12.12,224,1.000,bicubic,-51.563,-41.933,+43 -deit_small_patch16_224,42.273,57.727,58.010,41.990,22.05,224,0.900,bicubic,-51.707,-40.950,+25 -dpn98,42.273,57.727,56.877,43.123,61.57,224,0.875,bicubic,-51.647,-42.043,+29 -tf_efficientnet_cc_b1_8e,42.233,57.767,58.427,41.573,39.72,240,0.882,bicubic,-51.337,-40.263,+78 -legacy_senet154,42.203,57.797,56.590,43.410,115.09,224,0.875,bilinear,-52.527,-42.590,-63 -cait_xxs24_384,42.187,57.813,57.463,42.537,12.03,384,1.000,bicubic,-52.753,-41.667,-86 -xception41p,42.160,57.840,56.900,43.100,26.91,299,0.940,bicubic,-52.900,-42.250,-99 -tf_efficientnet_b2,42.117,57.883,58.193,41.807,9.11,260,0.890,bicubic,-52.093,-40.837,-4 -gluon_resnext50_32x4d,42.040,57.960,57.670,42.330,25.03,224,0.875,bicubic,-51.610,-41.280,+59 -resnext50_32x4d,41.970,58.030,56.747,43.253,25.03,224,0.950,bicubic,-52.600,-41.903,-44 -ecaresnet50d_pruned,41.950,58.050,58.210,41.790,19.94,224,0.875,bicubic,-51.870,-40.790,+34 -efficientnet_b2,41.930,58.070,58.297,41.703,9.11,288,1.000,bicubic,-52.440,-40.753,-26 -xcit_tiny_12_p16_224_dist,41.927,58.073,57.233,42.767,6.72,224,1.000,bicubic,-51.423,-41.507,+93 -hrnet_w64,41.640,58.360,57.123,42.877,128.06,224,0.875,bilinear,-52.200,-41.807,+29 -dla102x2,41.637,58.363,57.970,42.030,41.28,224,0.875,bilinear,-52.363,-41.060,+11 -gluon_senet154,41.623,58.377,56.377,43.623,115.09,224,0.875,bicubic,-53.087,-42.593,-71 -poolformer_s24,41.610,58.390,58.447,41.553,21.39,224,0.900,bicubic,-52.720,-40.613,-25 -inception_v4,41.580,58.420,55.380,44.620,42.68,299,0.875,bicubic,-52.800,-43.690,-33 -haloregnetz_b,41.540,58.460,57.087,42.913,11.68,224,0.940,bicubic,-52.980,-41.883,-47 -efficientnet_em,41.497,58.503,58.870,41.130,6.90,240,0.882,bicubic,-52.243,-40.060,+36 -tf_efficientnet_cc_b0_8e,41.487,58.513,57.377,42.623,24.01,224,0.875,bicubic,-51.383,-41.083,+121 -efficientnet_el,41.487,58.513,58.310,41.690,10.59,300,0.904,bicubic,-53.183,-40.820,-71 -halo2botnet50ts_256,41.467,58.533,56.200,43.800,22.64,256,0.950,bicubic,-53.543,-42.840,-113 -swin_tiny_patch4_window7_224,41.460,58.540,57.303,42.697,28.29,224,0.900,bicubic,-53.160,-41.747,-68 -resnetv2_50,41.390,58.610,56.750,43.250,25.55,224,0.950,bicubic,-52.880,-42.030,-28 -cait_xxs24_224,41.380,58.620,57.523,42.477,11.96,224,1.000,bicubic,-52.110,-41.257,+65 -tv_resnet152,41.337,58.663,57.527,42.473,60.19,224,0.875,bilinear,-51.903,-41.323,+86 -xception71,41.277,58.723,55.880,44.120,42.34,299,0.903,bicubic,-52.613,-43.070,+9 -dpn92,41.270,58.730,56.337,43.663,37.67,224,0.875,bicubic,-52.910,-42.593,-23 -gcresnext50ts,41.267,58.733,57.137,42.863,15.67,256,0.900,bicubic,-53.143,-41.853,-51 -adv_inception_v3,41.267,58.733,56.317,43.683,23.83,299,0.875,bicubic,-51.743,-42.173,+98 -gernet_s,41.257,58.743,58.833,41.167,8.17,224,0.875,bilinear,-51.183,-39.667,+141 -resnetv2_50d_evos,41.133,58.867,56.047,43.953,25.59,288,0.950,bicubic,-53.987,-43.153,-136 -resnetblur50,41.073,58.927,57.080,42.920,25.56,224,0.875,bicubic,-52.637,-41.730,+27 -nf_regnet_b1,41.007,58.993,58.117,41.883,10.22,288,0.900,bicubic,-52.873,-40.623,+3 -gluon_resnet50_v1d,40.967,59.033,57.147,42.853,25.58,224,0.875,bicubic,-52.563,-41.563,+49 -fbnetv3_b,40.940,59.060,58.660,41.340,8.60,256,0.950,bilinear,-52.700,-40.100,+33 -gluon_inception_v3,40.907,59.093,55.617,44.383,23.83,299,0.875,bicubic,-52.633,-43.213,+46 -ese_vovnet39b,40.870,59.130,56.943,43.057,24.57,224,0.875,bicubic,-52.980,-41.957,+2 -levit_192,40.840,59.160,56.693,43.307,10.95,224,0.900,bicubic,-52.870,-42.107,+20 -resnet34d,40.810,59.190,56.533,43.467,21.82,224,0.875,bicubic,-51.830,-41.887,+118 -regnety_320,40.803,59.197,56.110,43.890,145.05,224,0.875,bicubic,-53.717,-43.060,-69 -resnetv2_50d_gn,40.783,59.217,56.207,43.793,25.57,288,0.950,bicubic,-54.317,-42.853,-143 -xception,40.770,59.230,56.383,43.617,22.86,299,0.897,bicubic,-52.870,-42.527,+25 -lamhalobotnet50ts_256,40.747,59.253,56.097,43.903,22.57,256,0.950,bicubic,-54.033,-42.883,-110 -resnet50_gn,40.737,59.263,55.743,44.257,25.56,224,0.940,bicubic,-53.443,-43.177,-39 -skresnext50_32x4d,40.690,59.310,56.023,43.977,27.48,224,0.875,bicubic,-53.260,-42.807,-17 -hrnet_w40,40.680,59.320,56.757,43.243,57.56,224,0.875,bilinear,-53.030,-42.043,+10 -gluon_resnet101_v1b,40.680,59.320,56.127,43.873,44.55,224,0.875,bicubic,-53.080,-42.573,+6 -resmlp_24_224,40.643,59.357,56.570,43.430,30.02,224,0.875,bicubic,-52.797,-42.240,+46 -repvgg_b1,40.590,59.410,57.830,42.170,57.42,224,0.875,bilinear,-52.820,-40.960,+50 -halonet50ts,40.573,59.427,55.203,44.797,22.73,256,0.940,bicubic,-54.137,-43.617,-106 -tf_efficientnet_lite3,40.567,59.433,56.477,43.523,8.20,300,0.904,bilinear,-53.553,-42.463,-40 -xcit_tiny_12_p8_224,40.530,59.470,55.620,44.380,6.71,224,1.000,bicubic,-53.830,-43.450,-66 -tresnet_m_448,40.527,59.473,56.703,43.297,31.39,448,0.875,bilinear,-54.123,-42.447,-101 -dla169,40.497,59.503,57.267,42.733,53.39,224,0.875,bilinear,-53.303,-41.643,-6 -pit_xs_224,40.483,59.517,56.533,43.467,10.62,224,0.900,bicubic,-52.427,-42.247,+80 -repvgg_b2,40.467,59.533,57.773,42.227,89.02,224,0.875,bilinear,-53.123,-41.297,+21 -regnetx_320,40.450,59.550,55.663,44.337,107.81,224,0.875,bicubic,-53.770,-43.387,-57 -coat_mini,40.420,59.580,55.160,44.840,10.34,224,0.900,bicubic,-54.350,-43.790,-124 -skresnet34,40.397,59.603,56.737,43.263,22.28,224,0.875,bicubic,-52.173,-41.783,+104 -efficientnet_el_pruned,40.390,59.610,56.913,43.087,10.59,300,0.904,bicubic,-53.700,-42.107,-45 -efficientnet_b2_pruned,40.380,59.620,56.537,43.463,8.31,260,0.890,bicubic,-53.420,-42.293,-14 -resnet50,40.363,59.637,54.660,45.340,25.56,224,0.950,bicubic,-53.557,-43.810,-31 -wide_resnet101_2,40.363,59.637,55.783,44.217,126.89,224,0.875,bilinear,-53.367,-43.027,-7 -coat_lite_mini,40.357,59.643,55.713,44.287,11.01,224,0.900,bicubic,-53.103,-43.067,+27 -legacy_seresnext101_32x4d,40.350,59.650,54.823,45.177,48.96,224,0.875,bilinear,-53.770,-44.137,-52 -sebotnet33ts_256,40.340,59.660,53.207,46.793,13.70,256,0.940,bicubic,-53.970,-45.943,-74 -tf_efficientnet_b0_ap,40.337,59.663,56.790,43.210,5.29,224,0.875,bicubic,-52.273,-41.580,+92 -densenet201,40.270,59.730,56.710,43.290,20.01,224,0.875,bicubic,-52.420,-41.940,+83 -regnetx_160,40.270,59.730,56.057,43.943,54.28,224,0.875,bicubic,-53.620,-43.033,-36 -resnext50d_32x4d,40.163,59.837,55.487,44.513,25.05,224,0.875,bicubic,-53.647,-43.253,-24 -eca_resnet33ts,40.133,59.867,57.000,43.000,19.68,256,0.900,bicubic,-53.727,-41.890,-33 -hrnet_w48,40.097,59.903,56.633,43.367,77.47,224,0.875,bilinear,-53.933,-42.407,-52 -vit_base_patch16_224_sam,40.097,59.903,55.433,44.567,86.57,224,0.900,bicubic,-53.793,-43.457,-39 -legacy_seresnet152,40.050,59.950,55.817,44.183,66.82,224,0.875,bilinear,-53.390,-43.033,+19 -hrnet_w30,40.030,59.970,57.113,42.887,37.71,224,0.875,bilinear,-53.360,-41.717,+26 -regnetz_b16,40.000,60.000,55.630,44.370,9.72,288,0.940,bicubic,-54.680,-43.530,-129 -regnetx_080,39.993,60.007,55.967,44.033,39.57,224,0.875,bicubic,-53.797,-42.933,-28 -tf_efficientnet_b1,39.980,60.020,56.130,43.870,7.79,240,0.882,bicubic,-53.730,-42.670,-18 -gluon_resnet101_v1c,39.953,60.047,55.317,44.683,44.57,224,0.875,bicubic,-53.737,-43.443,-17 -resmlp_12_distilled_224,39.850,60.150,57.447,42.553,15.35,224,0.875,bicubic,-53.020,-41.173,+60 -seresnet33ts,39.830,60.170,56.517,43.483,19.78,256,0.900,bicubic,-54.440,-42.433,-85 -tf_efficientnetv2_b0,39.780,60.220,56.290,43.710,7.14,224,0.875,bicubic,-53.280,-42.410,+38 -res2net50_26w_8s,39.760,60.240,54.907,45.093,48.40,224,0.875,bilinear,-53.660,-43.783,+15 -lambda_resnet50ts,39.733,60.267,54.350,45.650,21.54,256,0.950,bicubic,-54.837,-44.450,-119 -res2net101_26w_4s,39.710,60.290,54.553,45.447,45.21,224,0.875,bilinear,-53.810,-44.137,-1 -regnetx_120,39.690,60.310,55.650,44.350,46.11,224,0.875,bicubic,-54.570,-43.540,-89 -hrnet_w44,39.673,60.327,55.327,44.673,67.06,224,0.875,bilinear,-53.937,-43.633,-14 -vit_small_patch32_224,39.670,60.330,55.263,44.737,22.88,224,0.900,bicubic,-52.480,-43.247,+99 -densenet161,39.623,60.377,56.133,43.867,28.68,224,0.875,bicubic,-53.267,-42.677,+49 -resmlp_big_24_224,39.623,60.377,54.827,45.173,129.14,224,0.875,bicubic,-54.647,-43.993,-97 -mixnet_xl,39.610,60.390,55.883,44.117,11.90,224,0.875,bicubic,-54.620,-42.937,-92 -xception41,39.603,60.397,55.033,44.967,26.97,299,0.903,bicubic,-53.877,-43.717,-2 -tf_efficientnetv2_b1,39.570,60.430,55.347,44.653,8.14,240,0.882,bicubic,-54.140,-43.473,-32 -dla102x,39.560,60.440,56.310,43.690,26.31,224,0.875,bilinear,-53.960,-42.290,-8 -gcresnet33ts,39.550,60.450,55.820,44.180,19.88,256,0.900,bicubic,-54.270,-43.090,-51 -xcit_tiny_12_p16_224,39.543,60.457,55.023,44.977,6.72,224,1.000,bicubic,-52.917,-43.607,+74 -sehalonet33ts,39.533,60.467,54.003,45.997,13.69,256,0.940,bicubic,-54.987,-44.747,-125 -rexnet_130,39.490,60.510,56.633,43.367,7.56,224,0.875,bicubic,-54.190,-42.077,-35 -hrnet_w32,39.463,60.537,56.133,43.867,41.23,224,0.875,bilinear,-53.487,-42.707,+32 -levit_128,39.433,60.567,55.343,44.657,9.21,224,0.900,bicubic,-53.607,-43.197,+22 -resnetv2_50x1_bitm,39.430,60.570,57.853,42.147,25.55,448,1.000,bilinear,-55.320,-41.327,-164 -densenetblur121d,39.387,60.613,56.640,43.360,8.00,224,0.875,bicubic,-53.013,-41.830,+74 -regnety_120,39.357,60.643,55.273,44.727,51.82,224,0.875,bicubic,-54.653,-43.767,-80 -tf_efficientnet_el,39.307,60.693,55.377,44.623,10.59,300,0.904,bicubic,-55.053,-43.723,-119 -tv_resnet101,39.287,60.713,55.790,44.210,44.55,224,0.875,bilinear,-53.593,-42.870,+34 -tf_inception_v3,39.240,60.760,54.307,45.693,23.83,299,0.875,bicubic,-53.960,-44.173,+7 +vit_large_patch16_224,64.353,35.647,76.187,23.813,304.33,224,0.900,bicubic,-32.357,-23.463,+28 +convnext_large_in22ft1k,64.177,35.823,77.580,22.420,197.77,224,0.875,bicubic,-33.083,-22.070,-13 +vit_large_r50_s32_384,64.103,35.897,75.850,24.150,329.09,384,1.000,bicubic,-32.847,-23.860,+6 +convnext_base_384_in22ft1k,64.093,35.907,77.733,22.267,88.59,384,1.000,bicubic,-33.197,-22.047,-19 +swin_large_patch4_window7_224,63.867,36.133,78.177,21.823,196.53,224,0.900,bicubic,-33.083,-21.483,+5 +beit_base_patch16_384,63.617,36.383,78.113,21.887,86.74,384,1.000,bicubic,-33.713,-21.607,-23 +swin_base_patch4_window12_384,63.470,36.530,78.080,21.920,87.90,384,1.000,bicubic,-33.650,-21.700,-9 +swinv2_base_window12to16_192to256_22kft1k,63.200,36.800,77.120,22.880,87.92,256,0.900,bicubic,-33.860,-22.540,-5 +tf_efficientnet_b5_ns,63.043,36.957,77.773,22.227,30.39,456,0.934,bicubic,-33.827,-21.867,+7 +deit3_base_patch16_384_in21ft1k,62.637,37.363,75.550,24.450,86.88,384,1.000,bicubic,-34.603,-24.120,-16 +vit_base_patch8_224,62.197,37.803,75.617,24.383,86.58,224,0.900,bicubic,-34.883,-24.003,-10 +convnext_base_in22ft1k,62.010,37.990,76.037,23.963,88.59,224,0.875,bicubic,-34.830,-23.613,+7 +deit3_base_patch16_224_in21ft1k,61.787,38.213,74.723,25.277,86.59,224,1.000,bicubic,-35.083,-24.897,+4 +tf_efficientnet_b4_ns,61.233,38.767,76.160,23.840,19.34,380,0.922,bicubic,-35.477,-23.480,+16 +tf_efficientnetv2_l_in21ft1k,60.953,39.047,75.843,24.157,118.52,480,1.000,bicubic,-36.157,-23.867,-16 +tf_efficientnetv2_xl_in21ft1k,60.680,39.320,74.397,25.603,208.12,512,1.000,bicubic,-36.470,-25.223,-19 +beit_base_patch16_224,60.317,39.683,75.597,24.403,86.53,224,0.900,bicubic,-36.343,-24.063,+19 +vit_base_patch16_384,60.187,39.813,73.837,26.163,86.86,384,1.000,bicubic,-36.833,-25.873,-13 +swin_base_patch4_window7_224,59.537,40.463,74.240,25.760,87.77,224,0.900,bicubic,-37.143,-25.420,+15 +convnext_small_384_in22ft1k,59.110,40.890,73.903,26.097,50.22,384,1.000,bicubic,-37.980,-25.787,-20 +volo_d5_512,58.920,41.080,73.200,26.800,296.09,512,1.150,bicubic,-38.370,-26.560,-35 +volo_d5_448,58.793,41.207,73.057,26.943,295.91,448,1.150,bicubic,-38.447,-26.683,-31 +tf_efficientnetv2_m_in21ft1k,58.643,41.357,73.980,26.020,54.14,480,1.000,bicubic,-38.327,-25.630,-15 +vit_large_r50_s32_224,58.633,41.367,71.720,28.280,328.99,224,0.900,bicubic,-37.547,-27.820,+64 +deit3_large_patch16_384,58.357,41.643,72.970,27.030,304.76,384,1.000,bicubic,-38.493,-26.650,-7 +deit3_huge_patch14_224,58.110,41.890,72.130,27.870,632.13,224,0.900,bicubic,-38.470,-27.390,+15 +tf_efficientnet_b8_ap,57.830,42.170,72.953,27.047,87.41,672,0.954,bicubic,-38.720,-26.587,+18 +convnext_small_in22ft1k,57.533,42.467,72.677,27.323,50.22,224,0.875,bicubic,-38.927,-26.793,+27 +cait_m48_448,57.477,42.523,71.867,28.133,356.46,448,1.000,bicubic,-39.403,-27.753,-14 +cait_m36_384,57.467,42.533,72.320,27.680,271.22,384,1.000,bicubic,-39.363,-27.340,-10 +tf_efficientnet_b3_ns,57.413,42.587,72.387,27.613,12.23,300,0.904,bicubic,-38.687,-27.093,+65 +volo_d4_448,57.293,42.707,71.533,28.467,193.41,448,1.150,bicubic,-39.777,-28.217,-30 +vit_base_patch16_224,56.840,43.160,70.637,29.363,86.57,224,0.900,bicubic,-39.460,-28.923,+41 +volo_d5_224,56.490,43.510,70.647,29.353,295.46,224,0.960,bicubic,-40.390,-29.023,-21 +deit3_large_patch16_224,56.463,43.537,70.463,29.537,304.37,224,0.900,bicubic,-39.727,-28.837,+52 +xcit_large_24_p8_384_dist,56.350,43.650,71.320,28.680,188.93,384,1.000,bicubic,-40.410,-28.240,-9 +xcit_large_24_p8_224_dist,56.027,43.973,70.663,29.337,188.93,224,1.000,bicubic,-40.613,-28.797,+1 +xcit_large_24_p16_384_dist,54.910,45.090,69.863,30.137,189.10,384,1.000,bicubic,-42.030,-29.647,-27 +volo_d4_224,54.743,45.257,68.860,31.140,192.96,224,0.960,bicubic,-42.037,-30.810,-16 +deit3_small_patch16_384_in21ft1k,54.467,45.533,68.310,31.690,22.21,384,1.000,bicubic,-42.203,-31.330,-5 +vit_base_r50_s16_384,54.400,45.600,69.563,30.437,98.95,384,1.000,bicubic,-42.050,-30.097,+15 +resnetv2_152x4_bitm,54.323,45.677,70.173,29.827,936.53,480,1.000,bilinear,-42.557,-29.487,-28 +xcit_large_24_p16_224_dist,54.260,45.740,68.980,31.020,189.10,224,1.000,bicubic,-42.060,-30.520,+29 +vit_small_r26_s32_384,54.203,45.797,68.747,31.253,36.47,384,1.000,bicubic,-41.857,-30.803,+59 +volo_d3_448,53.993,46.007,68.023,31.977,86.63,448,1.000,bicubic,-43.027,-31.657,-39 +tf_efficientnet_b5_ap,53.867,46.133,69.163,30.837,30.39,456,0.934,bicubic,-42.213,-30.377,+51 +xcit_medium_24_p8_224_dist,53.663,46.337,68.407,31.593,84.32,224,1.000,bicubic,-42.857,-31.103,+1 +tf_efficientnet_b2_ns,53.597,46.403,70.277,29.723,9.11,260,0.890,bicubic,-41.923,-29.063,+119 +tf_efficientnet_b6_ap,53.567,46.433,68.550,31.450,43.04,528,0.942,bicubic,-42.803,-31.000,+15 +cait_s36_384,53.550,46.450,68.020,31.980,68.37,384,1.000,bicubic,-43.080,-31.580,-11 +convnext_large,53.533,46.467,68.183,31.817,197.77,224,0.875,bicubic,-42.487,-31.287,+58 +deit3_base_patch16_384,53.510,46.490,67.630,32.370,86.88,384,1.000,bicubic,-42.720,-31.770,+32 +deit3_base_patch16_224,53.457,46.543,67.593,32.407,86.59,224,0.900,bicubic,-42.323,-31.677,+81 +tf_efficientnet_b8,53.410,46.590,69.090,30.910,87.41,672,0.954,bicubic,-43.290,-30.440,-21 +xcit_medium_24_p8_384_dist,53.407,46.593,68.137,31.863,84.32,384,1.000,bicubic,-43.373,-31.473,-30 +vit_base_patch32_384,53.300,46.700,68.043,31.957,88.30,384,1.000,bicubic,-42.600,-31.397,+65 +tf_efficientnet_b7_ap,53.260,46.740,68.867,31.133,66.35,600,0.949,bicubic,-43.090,-30.723,+9 +xcit_medium_24_p16_384_dist,53.213,46.787,68.057,31.943,84.40,384,1.000,bicubic,-43.487,-31.543,-26 +tf_efficientnetv2_s_in21ft1k,53.143,46.857,69.007,30.993,21.46,384,1.000,bicubic,-43.327,-30.563,-8 +tf_efficientnet_b4_ap,53.093,46.907,68.213,31.787,19.34,380,0.922,bicubic,-42.397,-31.177,+109 +regnetz_e8,53.017,46.983,67.140,32.860,57.70,320,1.000,bicubic,-43.583,-32.470,-21 +dm_nfnet_f5,52.870,47.130,67.427,32.573,377.21,544,0.954,bicubic,-43.940,-32.243,-41 +volo_d3_224,52.703,47.297,66.320,33.680,86.33,224,0.960,bicubic,-43.737,-33.300,-5 +deit3_small_patch16_224_in21ft1k,52.690,47.310,66.877,33.123,22.06,224,1.000,bicubic,-43.130,-32.523,+66 +dm_nfnet_f6,52.447,47.553,67.113,32.887,438.36,576,0.956,bicubic,-44.473,-32.607,-53 +tf_efficientnet_b7,52.393,47.607,68.230,31.770,66.35,600,0.949,bicubic,-44.187,-31.290,-24 +tf_efficientnetv2_l,52.387,47.613,67.240,32.760,118.52,480,1.000,bicubic,-44.263,-32.320,-30 +xcit_small_24_p8_384_dist,52.360,47.640,66.833,33.167,47.63,384,1.000,bicubic,-44.450,-32.797,-46 +swsl_resnet18,52.337,47.663,70.477,29.523,11.69,224,0.875,bilinear,-38.733,-27.733,+512 +efficientnetv2_rw_m,52.323,47.677,67.210,32.790,53.24,416,1.000,bicubic,-43.947,-32.350,+8 +deit_base_distilled_patch16_384,52.253,47.747,67.737,32.263,87.63,384,1.000,bicubic,-44.257,-31.853,-22 +xcit_medium_24_p16_224_dist,52.197,47.803,66.893,33.107,84.40,224,1.000,bicubic,-44.063,-32.517,+7 +xcit_small_24_p8_224_dist,52.197,47.803,66.767,33.233,47.63,224,1.000,bicubic,-44.353,-32.803,-29 +dm_nfnet_f3,52.130,47.870,66.740,33.260,254.92,416,0.940,bicubic,-44.600,-32.890,-46 +resnetv2_152x2_bit_teacher_384,51.943,48.057,68.663,31.337,236.34,384,1.000,bicubic,-44.247,-30.837,+11 +resmlp_big_24_224_in22ft1k,51.893,48.107,68.470,31.530,129.14,224,0.875,bicubic,-44.457,-31.050,-9 +xcit_small_24_p16_384_dist,51.883,48.117,66.367,33.633,47.67,384,1.000,bicubic,-44.457,-33.213,-9 +cait_s24_384,51.783,48.217,66.320,33.680,47.06,384,1.000,bicubic,-44.787,-33.230,-35 +resnetv2_152x2_bitm,51.757,48.243,69.247,30.753,236.34,448,1.000,bilinear,-44.763,-30.343,-32 +ecaresnet269d,51.663,48.337,66.043,33.957,102.09,352,1.000,bicubic,-44.797,-33.567,-27 +vit_base_patch16_224_miil,51.550,48.450,65.207,34.793,86.54,224,0.875,bilinear,-44.480,-34.143,+27 +convnext_tiny_384_in22ft1k,51.453,48.547,66.427,33.573,28.59,384,1.000,bicubic,-44.717,-33.053,+8 +convnext_base,51.247,48.753,66.190,33.810,88.59,224,0.875,bicubic,-44.693,-33.190,+35 +pit_b_distilled_224,51.157,48.843,66.773,33.227,74.79,224,0.900,bicubic,-44.913,-32.607,+17 +xcit_small_12_p8_384_dist,51.093,48.907,65.833,34.167,26.21,384,1.000,bicubic,-45.387,-33.657,-35 +convnext_tiny_in22ft1k,51.083,48.917,66.620,33.380,28.59,224,0.875,bicubic,-44.647,-32.740,+54 +dm_nfnet_f4,50.907,49.093,65.563,34.437,316.07,512,0.951,bicubic,-45.873,-34.057,-63 +tf_efficientnet_b1_ns,50.900,49.100,67.927,32.073,7.79,240,0.882,bicubic,-43.960,-31.323,+169 +volo_d2_384,50.883,49.117,65.637,34.363,58.87,384,1.000,bicubic,-45.827,-33.963,-58 +xcit_small_24_p16_224_dist,50.730,49.270,65.033,34.967,47.67,224,1.000,bicubic,-45.060,-34.317,+42 +tf_efficientnetv2_m,50.560,49.440,66.000,34.000,54.14,480,1.000,bicubic,-45.980,-33.570,-45 +xcit_small_12_p16_384_dist,50.527,49.473,65.297,34.703,26.25,384,1.000,bicubic,-45.803,-34.193,-21 +efficientnet_b4,50.503,49.497,65.707,34.293,19.34,384,1.000,bicubic,-45.027,-33.693,+72 +volo_d1_384,50.473,49.527,64.927,35.073,26.78,384,1.000,bicubic,-45.997,-34.623,-42 +xcit_small_12_p8_224_dist,50.440,49.560,65.433,34.567,26.21,224,1.000,bicubic,-45.520,-33.987,+20 +resnetv2_101x3_bitm,50.403,49.597,67.787,32.213,387.93,448,1.000,bilinear,-45.847,-31.803,-16 +regnetz_040h,50.330,49.670,65.630,34.370,28.94,320,1.000,bicubic,-46.000,-33.890,-27 +ssl_resnext101_32x16d,50.250,49.750,66.017,33.983,194.03,224,0.875,bilinear,-45.160,-33.393,+82 +cait_s24_224,50.240,49.760,65.023,34.977,46.92,224,1.000,bicubic,-45.400,-34.367,+54 +eca_nfnet_l2,50.233,49.767,65.453,34.547,56.72,384,1.000,bicubic,-46.217,-34.167,-43 +vit_small_patch16_384,50.167,49.833,65.807,34.193,22.20,384,1.000,bicubic,-45.813,-33.783,+12 +resnest269e,50.153,49.847,64.663,35.337,110.93,416,0.928,bicubic,-45.967,-34.857,-8 +deit_base_distilled_patch16_224,50.060,49.940,66.223,33.777,87.34,224,0.900,bicubic,-45.690,-33.057,+35 +tf_efficientnet_b3_ap,50.043,49.957,65.213,34.787,12.23,300,0.904,bicubic,-44.927,-33.897,+136 +resnest200e,49.877,50.123,64.740,35.260,70.20,320,0.909,bicubic,-46.193,-34.740,-6 +volo_d2_224,49.813,50.187,64.587,35.413,58.68,224,0.960,bicubic,-46.607,-34.913,-45 +seresnextaa101d_32x8d,49.767,50.233,64.420,35.580,93.59,288,1.000,bicubic,-46.653,-35.100,-47 +xception65,49.757,50.243,63.523,36.477,39.92,299,0.940,bicubic,-45.933,-35.787,+42 +swinv2_base_window16_256,49.667,50.333,63.810,36.190,87.92,256,0.900,bicubic,-46.503,-35.590,-18 +convnext_small,49.573,50.427,64.830,35.170,50.22,224,0.875,bicubic,-46.037,-34.430,+47 +cait_xs24_384,49.537,50.463,64.900,35.100,26.67,384,1.000,bicubic,-46.473,-34.530,+1 +tf_efficientnet_b5,49.510,50.490,65.650,34.350,30.39,456,0.934,bicubic,-46.470,-33.800,+2 +resnetv2_152x2_bit_teacher,49.487,50.513,65.620,34.380,236.34,224,0.875,bicubic,-46.263,-33.810,+24 +resnet200d,49.473,50.527,64.327,35.673,64.69,320,1.000,bicubic,-46.637,-35.133,-19 +xcit_small_12_p16_224_dist,49.420,50.580,63.840,36.160,26.25,224,1.000,bicubic,-46.310,-35.460,+27 +resnest101e,49.363,50.637,65.597,34.403,48.28,256,0.875,bilinear,-46.197,-33.673,+45 +regnetz_040,49.283,50.717,64.063,35.937,27.12,320,1.000,bicubic,-46.897,-35.447,-28 +resnet152d,49.250,50.750,64.417,35.583,60.21,320,1.000,bicubic,-46.620,-35.013,+8 +vit_base_patch32_224,49.250,50.750,64.343,35.657,88.22,224,0.900,bicubic,-45.140,-34.717,+203 +seresnet152d,49.250,50.750,64.177,35.823,66.84,320,1.000,bicubic,-47.060,-35.333,-47 +xcit_large_24_p8_224,49.237,50.763,62.840,37.160,188.93,224,1.000,bicubic,-46.843,-36.310,-23 +ssl_resnext101_32x8d,49.097,50.903,65.483,34.517,88.79,224,0.875,bilinear,-46.233,-33.827,+70 +resmlp_big_24_distilled_224,49.097,50.903,65.477,34.523,129.14,224,0.875,bicubic,-46.773,-33.963,+1 +volo_d1_224,48.970,51.030,63.190,36.810,26.63,224,0.960,bicubic,-47.060,-36.200,-17 +repvgg_b3,48.920,51.080,64.880,35.120,123.09,224,0.875,bilinear,-45.640,-34.030,+179 +resnetrs420,48.857,51.143,63.427,36.573,191.89,416,1.000,bicubic,-47.553,-36.113,-64 +deit3_small_patch16_384,48.670,51.330,62.823,37.177,22.21,384,1.000,bicubic,-46.940,-36.567,+29 +seresnext101d_32x8d,48.597,51.403,62.960,37.040,93.59,288,1.000,bicubic,-47.763,-36.510,-63 +efficientnetv2_rw_s,48.593,51.407,63.837,36.163,23.94,384,1.000,bicubic,-47.107,-35.543,+18 +regnetz_d32,48.590,51.410,65.190,34.810,27.58,320,0.950,bicubic,-47.280,-34.240,-5 +swinv2_small_window16_256,48.577,51.423,62.763,37.237,49.73,256,0.900,bicubic,-47.493,-36.577,-29 +efficientnet_b3,48.567,51.433,64.250,35.750,12.23,320,1.000,bicubic,-46.573,-34.960,+78 +ecaresnet101d,48.537,51.463,64.097,35.903,44.57,224,0.875,bicubic,-46.623,-35.133,+74 +vit_small_r26_s32_224,48.367,51.633,63.800,36.200,36.43,224,0.900,bicubic,-46.753,-35.420,+82 +dm_nfnet_f2,48.367,51.633,63.230,36.770,193.78,352,0.920,bicubic,-48.093,-36.310,-81 +swinv2_base_window8_256,48.340,51.660,63.597,36.403,87.92,256,0.900,bicubic,-47.730,-35.823,-36 +repvgg_b3g4,48.303,51.697,64.793,35.207,83.83,224,0.875,bilinear,-46.197,-34.227,+176 +vit_large_patch32_384,48.247,51.753,61.823,38.177,306.63,384,1.000,bicubic,-46.993,-37.497,+62 +convit_base,48.220,51.780,63.007,36.993,86.54,224,0.875,bicubic,-46.880,-36.133,+81 +swin_s3_base_224,48.140,51.860,62.263,37.737,71.13,224,0.900,bicubic,-47.900,-37.087,-34 +sequencer2d_l,48.107,51.893,62.343,37.657,54.30,224,0.875,bicubic,-47.763,-37.127,-18 +resnetrs350,48.057,51.943,62.650,37.350,163.96,384,1.000,bicubic,-48.183,-36.820,-60 +regnetz_d8,48.013,51.987,64.410,35.590,23.37,320,1.000,bicubic,-47.997,-35.110,-33 +twins_svt_large,47.947,52.053,62.910,37.090,99.27,224,0.900,bicubic,-47.773,-36.460,0 +vit_relpos_base_patch16_224,47.937,52.063,62.847,37.153,86.43,224,0.900,bicubic,-47.193,-36.453,+66 +mixer_b16_224_miil,47.800,52.200,63.397,36.603,59.88,224,0.875,bilinear,-47.090,-35.683,+107 +repvgg_b2g4,47.793,52.207,64.377,35.623,61.76,224,0.875,bilinear,-46.027,-34.553,+244 +vit_relpos_base_patch16_clsgap_224,47.763,52.237,62.410,37.590,86.43,224,0.900,bicubic,-47.487,-36.790,+50 +vit_relpos_medium_patch16_cls_224,47.660,52.340,61.803,38.197,38.76,224,0.900,bicubic,-47.640,-37.287,+45 +seresnext101_32x8d,47.653,52.347,61.447,38.553,93.57,288,1.000,bicubic,-48.477,-37.913,-57 +eca_nfnet_l1,47.643,52.357,62.763,37.237,41.41,320,1.000,bicubic,-48.297,-36.727,-34 +resnetv2_50x3_bitm,47.593,52.407,65.603,34.397,217.32,448,1.000,bilinear,-48.677,-34.027,-75 +pit_s_distilled_224,47.547,52.453,63.497,36.503,24.04,224,0.900,bicubic,-47.193,-35.683,+119 +resnest50d_4s2x40d,47.490,52.510,63.817,36.183,30.42,224,0.875,bicubic,-47.220,-35.323,+123 +efficientnet_b3_pruned,47.443,52.557,62.787,37.213,9.86,300,0.904,bicubic,-47.137,-36.283,+144 +crossvit_18_dagger_408,47.380,52.620,60.943,39.057,44.61,408,1.000,bicubic,-48.750,-38.527,-64 +xcit_small_24_p8_224,47.297,52.703,60.983,39.017,47.63,224,1.000,bicubic,-48.613,-38.197,-37 +tresnet_m,47.217,52.783,62.000,38.000,31.39,224,0.875,bilinear,-48.163,-37.150,+29 +tf_efficientnet_b6,47.207,52.793,63.110,36.890,43.04,528,0.942,bicubic,-49.083,-36.410,-84 +convnext_tiny,47.180,52.820,63.217,36.783,28.59,224,0.875,bicubic,-47.780,-35.983,+81 +ssl_resnext101_32x4d,47.167,52.833,63.367,36.633,44.18,224,0.875,bilinear,-47.983,-35.933,+47 +resnetrs270,47.107,52.893,62.013,37.987,129.86,352,1.000,bicubic,-48.953,-37.467,-58 +regnetz_d8_evos,47.080,52.920,63.390,36.610,23.46,320,0.950,bicubic,-49.140,-36.100,-78 +tf_efficientnet_b4,47.080,52.920,62.857,37.143,19.34,380,0.922,bicubic,-48.510,-36.473,-5 +vit_base_patch16_rpn_224,47.063,52.937,62.403,37.597,86.54,224,0.900,bicubic,-47.757,-36.687,+95 +swinv2_small_window8_256,47.030,52.970,62.297,37.703,49.73,256,0.900,bicubic,-48.700,-37.063,-25 +xcit_small_12_p8_224,46.983,53.017,60.537,39.463,26.21,224,1.000,bicubic,-48.437,-38.663,+12 +xcit_large_24_p16_224,46.960,53.040,60.670,39.330,189.10,224,1.000,bicubic,-47.990,-38.160,+75 +convnext_tiny_hnf,46.937,53.063,61.200,38.800,28.59,224,0.950,bicubic,-47.833,-37.960,+97 +xception65p,46.933,53.067,61.083,38.917,39.82,299,0.940,bicubic,-48.727,-38.187,-19 +resnet101d,46.893,53.107,62.323,37.677,44.57,320,1.000,bicubic,-48.857,-37.117,-35 +resnet152,46.800,53.200,60.410,39.590,60.19,224,0.950,bicubic,-48.750,-38.850,-10 +gluon_seresnext101_64x4d,46.677,53.323,61.297,38.703,88.23,224,0.875,bicubic,-47.983,-37.683,+117 +twins_pcpvt_large,46.627,53.373,62.233,37.767,60.99,224,0.900,bicubic,-49.093,-37.257,-31 +dm_nfnet_f1,46.547,53.453,61.403,38.597,132.63,320,0.910,bicubic,-49.833,-38.067,-112 +regnetv_064,46.480,53.520,62.253,37.747,30.58,288,1.000,bicubic,-49.290,-37.167,-41 +xcit_medium_24_p8_224,46.473,53.527,59.647,40.353,84.32,224,1.000,bicubic,-49.397,-39.433,-50 +crossvit_15_dagger_408,46.457,53.543,60.487,39.513,28.50,408,1.000,bicubic,-49.363,-38.823,-47 +resnetrs200,46.430,53.570,61.060,38.940,93.21,320,1.000,bicubic,-49.910,-38.490,-110 +swin_s3_small_224,46.393,53.607,60.897,39.103,49.74,224,0.900,bicubic,-49.447,-38.303,-51 +fbnetv3_g,46.347,53.653,62.403,37.597,16.62,288,0.950,bilinear,-48.783,-36.797,+31 +sequencer2d_m,46.297,53.703,60.903,39.097,38.31,224,0.875,bicubic,-49.303,-38.367,-24 +tresnet_xl,46.280,53.720,61.950,38.050,78.44,224,0.875,bilinear,-48.780,-37.310,+46 +xcit_tiny_24_p8_384_dist,46.263,53.737,60.713,39.287,12.11,384,1.000,bicubic,-49.977,-38.727,-101 +xcit_tiny_24_p8_224_dist,46.257,53.743,60.607,39.393,12.11,224,1.000,bicubic,-49.203,-38.753,-9 +gernet_m,46.170,53.830,62.700,37.300,21.14,224,0.875,bilinear,-48.380,-36.230,+121 +deit_small_distilled_patch16_224,46.163,53.837,62.403,37.597,22.44,224,0.900,bicubic,-48.437,-36.697,+110 +regnety_160,46.163,53.837,61.843,38.157,83.59,288,1.000,bicubic,-49.717,-37.717,-66 +crossvit_base_240,46.133,53.867,60.223,39.777,105.03,240,0.875,bicubic,-48.937,-38.757,+39 +swinv2_cr_small_ns_224,46.123,53.877,60.787,39.213,49.70,224,0.900,bicubic,-49.567,-38.523,-41 +resnest50d_1s4x24d,46.093,53.907,62.377,37.623,25.68,224,0.875,bicubic,-48.297,-36.693,+130 +tf_efficientnet_b0_ns,46.053,53.947,63.270,36.730,5.29,224,0.875,bicubic,-47.697,-35.700,+206 +jx_nest_base,46.040,53.960,60.093,39.907,67.72,224,0.875,bicubic,-49.500,-39.207,-30 +resnet51q,46.027,53.973,60.903,39.097,35.70,288,1.000,bilinear,-49.173,-38.377,+10 +vit_small_patch16_224,46.000,54.000,61.820,38.180,22.05,224,0.900,bicubic,-48.880,-37.450,+59 +vit_relpos_medium_patch16_224,45.960,54.040,61.030,38.970,38.75,224,0.900,bicubic,-49.240,-38.190,+9 +regnety_080,45.953,54.047,60.880,39.120,39.18,288,1.000,bicubic,-49.897,-38.560,-69 +resnest50d,45.943,54.057,62.630,37.370,27.48,224,0.875,bilinear,-48.677,-36.400,+95 +deit3_small_patch16_224,45.923,54.077,58.893,41.107,22.06,224,0.900,bicubic,-48.767,-39.857,+84 +crossvit_18_240,45.903,54.097,60.383,39.617,43.27,240,0.875,bicubic,-49.167,-38.737,+27 +twins_pcpvt_base,45.893,54.107,61.343,38.657,43.83,224,0.900,bicubic,-49.567,-38.047,-26 +regnety_032,45.883,54.117,61.533,38.467,19.44,288,1.000,bicubic,-49.597,-37.787,-31 +levit_384,45.873,54.127,61.690,38.310,39.13,224,0.900,bicubic,-49.337,-37.470,-1 +twins_svt_base,45.873,54.127,60.967,39.033,56.07,224,0.900,bicubic,-49.697,-38.263,-44 +crossvit_18_dagger_240,45.850,54.150,59.923,40.077,44.27,240,0.875,bicubic,-49.330,-39.197,+1 +vit_relpos_medium_patch16_rpn_224,45.753,54.247,60.957,39.043,38.73,224,0.900,bicubic,-49.317,-38.233,+20 +vit_srelpos_medium_patch16_224,45.730,54.270,61.070,38.930,38.74,224,0.900,bicubic,-49.170,-38.130,+42 +crossvit_15_dagger_240,45.697,54.303,60.090,39.910,28.21,240,0.875,bicubic,-49.283,-39.070,+28 +regnetz_c16,45.690,54.310,62.517,37.483,13.46,320,0.940,bicubic,-49.700,-36.793,-24 +convmixer_1536_20,45.660,54.340,61.770,38.230,51.63,224,0.960,bicubic,-49.310,-37.400,+29 +gc_efficientnetv2_rw_t,45.657,54.343,60.200,39.800,13.68,288,1.000,bicubic,-49.633,-39.020,-16 +efficientnetv2_rw_t,45.607,54.393,60.187,39.813,13.65,288,1.000,bicubic,-49.463,-39.033,+13 +gluon_seresnext101_32x4d,45.597,54.403,61.140,38.860,48.96,224,0.875,bicubic,-48.853,-37.950,+102 +xcit_tiny_24_p16_384_dist,45.587,54.413,60.510,39.490,12.12,384,1.000,bicubic,-49.903,-38.850,-44 +xcit_medium_24_p16_224,45.527,54.473,59.000,41.000,84.40,224,1.000,bicubic,-49.603,-39.930,-1 +xcit_small_24_p16_224,45.517,54.483,58.887,41.113,47.67,224,1.000,bicubic,-49.563,-40.183,+6 +dm_nfnet_f0,45.480,54.520,60.990,39.010,71.49,256,0.900,bicubic,-50.210,-38.340,-69 +resnext101_64x4d,45.453,54.547,59.040,40.960,83.46,288,1.000,bicubic,-50.087,-40.250,-54 +gluon_resnet152_v1d,45.437,54.563,60.083,39.917,60.21,224,0.875,bicubic,-49.003,-38.927,+97 +nfnet_l0,45.423,54.577,62.073,37.927,35.07,288,1.000,bicubic,-49.967,-37.347,-36 +ssl_resnext50_32x4d,45.403,54.597,62.033,37.967,25.03,224,0.875,bilinear,-49.297,-37.207,+59 +resnetv2_50x1_bit_distilled,45.397,54.603,62.310,37.690,25.55,224,0.875,bicubic,-50.003,-37.120,-41 +xcit_small_12_p16_224,45.397,54.603,59.417,40.583,26.25,224,1.000,bicubic,-49.423,-39.643,+38 +jx_nest_small,45.353,54.647,59.010,40.990,38.35,224,0.875,bicubic,-50.177,-40.210,-58 +cs3se_edgenet_x,45.327,54.673,60.383,39.617,50.72,320,1.000,bicubic,-50.683,-39.057,-114 +resnet61q,45.283,54.717,59.400,40.600,36.85,288,1.000,bicubic,-49.837,-39.680,-7 +cs3edgenet_x,45.280,54.720,60.287,39.713,47.82,288,1.000,bicubic,-50.190,-38.993,-54 +tresnet_xl_448,45.223,54.777,61.440,38.560,78.44,448,0.875,bilinear,-50.287,-37.900,-60 +nasnetalarge,45.207,54.793,57.880,42.120,88.75,331,0.911,bicubic,-49.943,-41.250,-20 +convit_small,45.197,54.803,60.497,39.503,27.78,224,0.875,bicubic,-49.723,-38.613,+17 +swin_small_patch4_window7_224,45.157,54.843,60.333,39.667,49.61,224,0.900,bicubic,-50.563,-38.957,-86 +tf_efficientnet_b3,45.100,54.900,60.643,39.357,12.23,300,0.904,bicubic,-49.810,-38.467,+16 +resnet101,45.087,54.913,59.577,40.423,44.55,224,0.950,bicubic,-49.893,-39.503,+4 +sequencer2d_s,45.083,54.917,60.067,39.933,27.65,224,0.875,bicubic,-50.387,-39.203,-60 +rexnet_200,45.057,54.943,62.313,37.687,16.37,224,0.875,bicubic,-49.603,-36.777,+53 +resnetrs152,44.957,55.043,59.707,40.293,86.62,320,1.000,bicubic,-51.003,-39.673,-120 +resnetv2_101,44.933,55.067,58.837,41.163,44.54,224,0.950,bicubic,-49.997,-40.283,+9 +ecaresnetlight,44.893,55.107,60.777,39.223,30.16,224,0.875,bicubic,-49.247,-38.173,+116 +deit_base_patch16_224,44.873,55.127,59.190,40.810,86.57,224,0.900,bicubic,-50.137,-39.790,-4 +cait_xxs36_384,44.777,55.223,59.367,40.633,17.37,384,1.000,bicubic,-50.443,-39.953,-39 +deit_base_patch16_384,44.770,55.230,59.627,40.373,86.86,384,1.000,bicubic,-50.880,-39.613,-89 +resmlp_36_distilled_224,44.757,55.243,61.073,38.927,44.69,224,0.875,bicubic,-49.793,-38.087,+63 +gernet_l,44.730,55.270,58.947,41.053,31.08,256,0.875,bilinear,-50.200,-40.253,+1 +xcit_tiny_24_p16_224_dist,44.720,55.280,59.420,40.580,12.12,224,1.000,bicubic,-49.500,-39.540,+101 +resmlp_24_distilled_224,44.710,55.290,61.463,38.537,30.02,224,0.875,bicubic,-49.630,-37.627,+85 +tf_efficientnet_b2_ap,44.707,55.293,60.680,39.320,9.11,260,0.890,bicubic,-49.563,-38.270,+90 +swinv2_tiny_window16_256,44.573,55.427,59.577,40.423,28.35,256,0.900,bicubic,-50.787,-39.723,-59 +vit_relpos_small_patch16_224,44.550,55.450,60.203,39.797,21.98,224,0.900,bicubic,-50.140,-38.897,+33 +gmlp_s16_224,44.483,55.517,58.627,41.373,19.42,224,0.875,bicubic,-49.027,-40.153,+182 +ens_adv_inception_resnet_v2,44.390,55.610,58.110,41.890,55.84,299,0.897,bicubic,-49.730,-40.680,+107 +tresnet_l,44.360,55.640,59.947,40.053,55.99,224,0.875,bilinear,-50.540,-39.083,0 +gluon_resnext101_32x4d,44.287,55.713,59.090,40.910,44.18,224,0.875,bicubic,-49.833,-39.840,+104 +poolformer_m48,44.270,55.730,59.300,40.700,73.47,224,0.950,bicubic,-50.860,-39.820,-40 +wide_resnet50_2,44.180,55.820,59.697,40.303,68.88,224,0.875,bicubic,-50.480,-39.353,+35 +regnetz_c16_evos,44.160,55.840,61.057,38.943,13.49,320,0.950,bicubic,-51.470,-38.363,-101 +vit_srelpos_small_patch16_224,44.137,55.863,59.710,40.290,21.97,224,0.900,bicubic,-50.413,-39.430,+50 +crossvit_15_240,44.123,55.877,59.130,40.870,27.53,240,0.875,bicubic,-50.597,-39.950,+18 +seresnext50_32x4d,44.120,55.880,59.480,40.520,27.56,224,0.875,bicubic,-50.690,-39.650,+4 +resnetv2_101x1_bitm,44.113,55.887,61.980,38.020,44.54,448,1.000,bilinear,-51.207,-37.390,-66 +gluon_resnet152_v1s,44.070,55.930,58.700,41.300,60.32,224,0.875,bicubic,-50.650,-40.360,+16 +pit_b_224,44.067,55.933,58.017,41.983,73.76,224,0.900,bicubic,-50.723,-40.803,+3 +ssl_resnet50,44.020,55.980,61.910,38.090,25.56,224,0.875,bilinear,-50.300,-37.240,+71 +poolformer_m36,44.020,55.980,59.067,40.933,56.17,224,0.950,bicubic,-50.990,-40.033,-30 +inception_resnet_v2,44.007,55.993,57.907,42.093,55.84,299,0.897,bicubic,-50.323,-40.893,+68 +pnasnet5large,43.953,56.047,56.723,43.277,86.06,331,0.911,bicubic,-51.407,-42.407,-76 +pit_s_224,43.893,56.107,58.637,41.363,23.46,224,0.900,bicubic,-50.687,-40.293,+34 +gluon_resnext101_64x4d,43.880,56.120,58.703,41.297,83.46,224,0.875,bicubic,-50.470,-40.177,+62 +coat_lite_small,43.813,56.187,57.143,42.857,19.84,224,0.900,bicubic,-51.267,-41.887,-45 +regnetv_040,43.793,56.207,58.460,41.540,20.64,288,1.000,bicubic,-51.937,-40.920,-130 +tnt_s_patch16_224,43.777,56.223,59.197,40.803,23.76,224,0.900,bicubic,-50.793,-39.983,+32 +mobilevitv2_200_in22ft1k,43.770,56.230,59.500,40.500,18.45,256,0.888,bicubic,-51.280,-39.580,-40 +swinv2_cr_small_224,43.770,56.230,57.690,42.310,49.70,224,0.900,bicubic,-51.630,-41.360,-89 +cspresnext50,43.763,56.237,60.143,39.857,20.57,256,0.887,bilinear,-50.477,-38.907,+68 +cait_xxs36_224,43.760,56.240,58.730,41.270,17.30,224,1.000,bicubic,-50.170,-40.160,+102 +ecaresnet50d,43.743,56.257,60.373,39.627,25.58,224,0.875,bicubic,-50.457,-38.647,+73 +ecaresnet101d_pruned,43.740,56.260,59.607,40.393,24.88,224,0.875,bicubic,-50.720,-39.483,+38 +swin_s3_tiny_224,43.717,56.283,59.510,40.490,28.33,224,0.900,bicubic,-51.183,-39.650,-27 +tf_efficientnetv2_s,43.707,56.293,58.597,41.403,21.46,384,1.000,bicubic,-52.003,-40.803,-132 +rexnet_150,43.687,56.313,60.890,39.110,9.73,224,0.875,bicubic,-50.593,-38.190,+56 +pit_xs_distilled_224,43.660,56.340,60.707,39.293,11.00,224,0.900,bicubic,-49.580,-38.123,+179 +xcit_tiny_12_p8_224_dist,43.640,56.360,58.457,41.543,6.71,224,1.000,bicubic,-51.080,-40.723,-7 +edgenext_small,43.617,56.383,59.883,40.117,5.59,320,1.000,bicubic,-51.213,-39.527,-23 +crossvit_small_240,43.473,56.527,58.940,41.060,26.86,240,0.875,bicubic,-51.107,-40.180,+15 +cs3sedarknet_x,43.460,56.540,58.843,41.157,35.40,288,1.000,bicubic,-51.960,-40.477,-106 +gluon_resnet101_v1d,43.430,56.570,58.610,41.390,44.57,224,0.875,bicubic,-50.750,-40.330,+64 +ecaresnet50t,43.413,56.587,59.300,40.700,25.57,320,0.950,bicubic,-51.657,-39.990,-62 +gluon_resnet101_v1s,43.363,56.637,58.510,41.490,44.67,224,0.875,bicubic,-50.807,-40.500,+65 +cspdarknet53,43.353,56.647,59.430,40.570,27.64,256,0.887,bilinear,-50.737,-39.550,+72 +xcit_tiny_24_p8_224,43.303,56.697,57.273,42.727,12.11,224,1.000,bicubic,-51.587,-41.917,-37 +xcit_tiny_12_p8_384_dist,43.300,56.700,58.177,41.823,6.71,384,1.000,bicubic,-52.040,-41.163,-100 +dpn68b,43.277,56.723,58.673,41.327,12.61,224,0.875,bicubic,-50.343,-40.027,+126 +convmixer_768_32,43.267,56.733,59.367,40.633,21.11,224,0.960,bicubic,-51.163,-39.743,+25 +visformer_small,43.257,56.743,57.980,42.020,40.22,224,0.900,bicubic,-51.713,-41.230,-55 +eca_nfnet_l0,43.233,56.767,59.907,40.093,24.14,288,1.000,bicubic,-52.217,-39.483,-117 +regnety_064,43.223,56.777,57.230,42.770,30.58,288,1.000,bicubic,-52.567,-42.060,-162 +vit_relpos_base_patch32_plus_rpn_256,43.167,56.833,58.430,41.570,119.42,256,0.900,bicubic,-49.993,-39.890,+170 +vit_small_patch32_384,43.143,56.857,59.293,40.707,22.92,384,1.000,bicubic,-51.457,-39.847,-1 +resnest26d,43.140,56.860,60.637,39.363,17.07,224,0.875,bilinear,-50.100,-38.213,+160 +twins_pcpvt_small,43.087,56.913,58.877,41.123,24.11,224,0.900,bicubic,-51.513,-40.273,-4 +resmlp_36_224,43.050,56.950,59.313,40.687,44.69,224,0.875,bicubic,-50.600,-39.637,+110 +cspresnet50,43.047,56.953,59.167,40.833,21.62,256,0.887,bilinear,-50.813,-39.693,+83 +dpn131,43.040,56.960,57.420,42.580,79.25,224,0.875,bicubic,-50.710,-41.410,+97 +tf_efficientnet_lite4,42.980,57.020,57.640,42.360,13.01,380,0.920,bilinear,-51.890,-41.450,-47 +twins_svt_small,42.930,57.070,58.467,41.533,24.06,224,0.900,bicubic,-51.840,-40.613,-37 +mobilevitv2_200_384_in22ft1k,42.917,57.083,58.987,41.013,18.45,384,1.000,bicubic,-52.473,-40.293,-119 +gluon_resnet152_v1b,42.893,57.107,57.740,42.260,60.19,224,0.875,bicubic,-51.137,-41.010,+60 +fbnetv3_d,42.890,57.110,59.690,40.310,10.31,256,0.950,bilinear,-50.960,-39.220,+78 +dpn107,42.860,57.140,57.363,42.637,86.92,224,0.875,bicubic,-51.100,-41.467,+65 +levit_256,42.813,57.187,57.903,42.097,18.89,224,0.900,bicubic,-51.597,-41.157,+9 +gluon_resnet152_v1c,42.810,57.190,57.737,42.263,60.21,224,0.875,bicubic,-51.080,-41.063,+70 +tf_efficientnet_b1_ap,42.800,57.200,58.817,41.183,7.79,240,0.882,bicubic,-50.830,-39.983,+103 +gcresnet50t,42.790,57.210,59.190,40.810,25.90,256,0.900,bicubic,-51.830,-39.790,-18 +gluon_xception65,42.790,57.210,58.820,41.180,39.92,299,0.903,bicubic,-51.220,-40.200,+56 +tresnet_l_448,42.750,57.250,58.943,41.057,55.99,448,0.875,bilinear,-52.650,-40.357,-132 +cs3darknet_x,42.717,57.283,58.197,41.803,35.05,288,1.000,bicubic,-52.553,-41.083,-119 +resnet50d,42.697,57.303,58.687,41.313,25.58,224,0.875,bicubic,-51.373,-40.233,+46 +gluon_seresnext50_32x4d,42.683,57.317,58.700,41.300,27.56,224,0.875,bicubic,-51.487,-40.210,+36 +convnext_nano,42.590,57.410,57.497,42.503,15.59,288,1.000,bicubic,-52.270,-41.653,-60 +xcit_tiny_12_p16_384_dist,42.587,57.413,58.087,41.913,6.72,384,1.000,bicubic,-51.943,-41.083,-10 +resnext101_32x8d,42.570,57.430,58.293,41.707,88.79,224,0.875,bilinear,-51.200,-40.657,+76 +regnety_040,42.567,57.433,57.037,42.963,20.65,288,1.000,bicubic,-52.903,-42.383,-149 +seresnet50,42.513,57.487,58.677,41.323,28.09,224,0.875,bicubic,-51.567,-40.273,+39 +nf_resnet50,42.507,57.493,59.520,40.480,25.56,288,0.940,bicubic,-51.883,-39.550,-3 +mobilevitv2_175_in22ft1k,42.500,57.500,58.133,41.867,14.25,256,0.888,bicubic,-52.280,-40.967,-59 +resnetrs101,42.443,57.557,57.290,42.710,63.62,288,0.940,bicubic,-52.807,-41.920,-128 +poolformer_s36,42.333,57.667,58.737,41.263,30.86,224,0.900,bicubic,-52.287,-40.313,-34 +jx_nest_tiny,42.330,57.670,57.043,42.957,17.06,224,0.875,bicubic,-52.620,-42.057,-85 +tf_efficientnetv2_b3,42.310,57.690,57.943,42.057,14.36,300,0.904,bicubic,-52.810,-41.257,-110 +convmixer_1024_20_ks9_p14,42.277,57.723,59.713,40.287,24.38,224,0.960,bicubic,-50.073,-38.707,+199 +dpn98,42.273,57.727,56.883,43.117,61.57,224,0.875,bicubic,-51.657,-42.037,+45 +xcit_tiny_24_p16_224,42.273,57.727,56.830,43.170,12.12,224,1.000,bicubic,-51.567,-41.930,+56 +deit_small_patch16_224,42.267,57.733,58.013,41.987,22.05,224,0.900,bicubic,-51.723,-40.947,+39 +tf_efficientnet_cc_b1_8e,42.220,57.780,58.430,41.570,39.72,240,0.882,bicubic,-51.350,-40.260,+90 +legacy_senet154,42.213,57.787,56.593,43.407,115.09,224,0.875,bilinear,-52.517,-42.507,-61 +cait_xxs24_384,42.183,57.817,57.460,42.540,12.03,384,1.000,bicubic,-52.747,-41.680,-90 +xception41p,42.163,57.837,56.890,43.110,26.91,299,0.940,bicubic,-52.897,-42.260,-106 +tf_efficientnet_b2,42.117,57.883,58.197,41.803,9.11,260,0.890,bicubic,-52.093,-40.843,+9 +gluon_resnext50_32x4d,42.043,57.957,57.670,42.330,25.03,224,0.875,bicubic,-51.607,-41.020,+73 +resnext50_32x4d,41.963,58.037,56.757,43.243,25.03,224,0.950,bicubic,-52.617,-42.043,-38 +ecaresnet50d_pruned,41.950,58.050,58.217,41.783,19.94,224,0.875,bicubic,-51.870,-40.783,+50 +efficientnet_b2,41.933,58.067,58.287,41.713,9.11,288,1.000,bicubic,-52.437,-40.763,-17 +mobilevitv2_150_in22ft1k,41.920,58.080,57.923,42.077,10.59,256,0.888,bicubic,-52.770,-40.997,-60 +xcit_tiny_12_p16_224_dist,41.920,58.080,57.227,42.773,6.72,224,1.000,bicubic,-51.430,-41.513,+107 +mobilevitv2_150_384_in22ft1k,41.777,58.223,57.820,42.180,10.59,384,1.000,bicubic,-53.563,-41.310,-153 +mobilevitv2_175_384_in22ft1k,41.670,58.330,58.010,41.990,14.25,384,1.000,bicubic,-53.570,-41.370,-146 +edgenext_small_rw,41.663,58.337,58.520,41.480,7.83,320,1.000,bicubic,-52.697,-40.520,-18 +dla102x2,41.643,58.357,57.940,42.060,41.28,224,0.875,bilinear,-52.357,-41.090,+23 +hrnet_w64,41.640,58.360,57.123,42.877,128.06,224,0.875,bilinear,-52.190,-41.797,+40 +gluon_senet154,41.617,58.383,56.377,43.623,115.09,224,0.875,bicubic,-53.093,-42.593,-71 +poolformer_s24,41.607,58.393,58.440,41.560,21.39,224,0.900,bicubic,-52.723,-40.620,-19 +inception_v4,41.580,58.420,55.390,44.610,42.68,299,0.875,bicubic,-52.800,-43.430,-28 +swinv2_cr_tiny_ns_224,41.543,58.457,57.190,42.810,28.33,224,0.900,bicubic,-53.217,-41.920,-82 +haloregnetz_b,41.540,58.460,57.080,42.920,11.68,224,0.940,bicubic,-52.980,-41.880,-42 +cs3sedarknet_l,41.533,58.467,57.347,42.653,21.91,288,0.950,bicubic,-53.587,-41.863,-137 +efficientnet_em,41.490,58.510,58.880,41.120,6.90,240,0.882,bicubic,-52.250,-40.050,+45 +tf_efficientnet_cc_b0_8e,41.490,58.510,57.380,42.620,24.01,224,0.875,bicubic,-51.380,-41.070,+135 +efficientnet_el,41.483,58.517,58.313,41.687,10.59,300,0.904,bicubic,-53.187,-40.817,-71 +halo2botnet50ts_256,41.467,58.533,56.207,43.793,22.64,256,0.950,bicubic,-53.543,-42.833,-124 +swin_tiny_patch4_window7_224,41.460,58.540,57.307,42.693,28.29,224,0.900,bicubic,-53.160,-41.813,-68 +resnetv2_50,41.387,58.613,56.747,43.253,25.55,224,0.950,bicubic,-52.883,-42.183,-23 +swinv2_tiny_window8_256,41.383,58.617,57.117,42.883,28.35,256,0.900,bicubic,-53.647,-42.053,-129 +cait_xxs24_224,41.380,58.620,57.523,42.477,11.96,224,1.000,bicubic,-52.110,-41.247,+72 +tv_resnet152,41.333,58.667,57.523,42.477,60.19,224,0.875,bilinear,-51.917,-41.227,+93 +gcresnext50ts,41.283,58.717,57.147,42.853,15.67,256,0.900,bicubic,-53.127,-41.843,-45 +cs3darknet_l,41.280,58.720,57.347,42.653,21.16,288,0.950,bicubic,-53.400,-41.873,-81 +dpn92,41.277,58.723,56.340,43.660,37.67,224,0.875,bicubic,-52.903,-42.590,-16 +xception71,41.273,58.727,55.877,44.123,42.34,299,0.903,bicubic,-52.607,-43.073,+14 +adv_inception_v3,41.260,58.740,56.317,43.683,23.83,299,0.875,bicubic,-51.750,-42.173,+109 +gernet_s,41.250,58.750,58.827,41.173,8.17,224,0.875,bilinear,-51.190,-39.673,+152 +resnetv2_50d_evos,41.133,58.867,56.050,43.950,25.59,288,0.950,bicubic,-53.987,-43.180,-155 +resnetblur50,41.077,58.923,57.080,42.920,25.56,224,0.875,bicubic,-52.633,-41.730,+33 +nf_regnet_b1,41.027,58.973,58.113,41.887,10.22,288,0.900,bicubic,-52.853,-40.637,+10 +gluon_resnet50_v1d,40.970,59.030,57.137,42.863,25.58,224,0.875,bicubic,-52.560,-41.573,+56 +fbnetv3_b,40.953,59.047,58.653,41.347,8.60,256,0.950,bilinear,-52.677,-40.257,+39 +gluon_inception_v3,40.907,59.093,55.620,44.380,23.83,299,0.875,bicubic,-52.633,-43.210,+52 +cs3darknet_focus_l,40.893,59.107,56.630,43.370,21.15,288,0.950,bicubic,-53.897,-42.520,-113 +ese_vovnet39b,40.867,59.133,56.950,43.050,24.57,224,0.875,bicubic,-52.983,-41.950,+9 +levit_192,40.837,59.163,56.690,43.310,10.95,224,0.900,bicubic,-52.883,-42.100,+24 +regnety_320,40.803,59.197,56.113,43.887,145.05,224,0.875,bicubic,-53.717,-43.057,-69 +resnet34d,40.800,59.200,56.523,43.477,21.82,224,0.875,bicubic,-51.850,-41.897,+127 +resnetv2_50d_gn,40.783,59.217,56.207,43.793,25.57,288,0.950,bicubic,-54.317,-42.853,-160 +xception,40.773,59.227,56.383,43.617,22.86,299,0.897,bicubic,-52.867,-42.377,+30 +lamhalobotnet50ts_256,40.747,59.253,56.093,43.907,22.57,256,0.950,bicubic,-54.023,-42.887,-115 +resnet50_gn,40.737,59.263,55.750,44.250,25.56,224,0.940,bicubic,-53.443,-43.170,-33 +skresnext50_32x4d,40.700,59.300,56.030,43.970,27.48,224,0.875,bicubic,-53.250,-42.800,-11 +gluon_resnet101_v1b,40.683,59.317,56.123,43.877,44.55,224,0.875,bicubic,-53.077,-42.577,+11 +hrnet_w40,40.663,59.337,56.757,43.243,57.56,224,0.875,bilinear,-53.047,-42.043,+18 +resmlp_24_224,40.643,59.357,56.570,43.430,30.02,224,0.875,bicubic,-52.797,-42.240,+51 +repvgg_b1,40.593,59.407,57.830,42.170,57.42,224,0.875,bilinear,-52.817,-40.960,+56 +halonet50ts,40.577,59.423,55.193,44.807,22.73,256,0.940,bicubic,-54.133,-43.637,-111 +tf_efficientnet_lite3,40.563,59.437,56.473,43.527,8.20,300,0.904,bilinear,-53.547,-42.487,-33 +xcit_tiny_12_p8_224,40.533,59.467,55.623,44.377,6.71,224,1.000,bicubic,-53.827,-43.447,-66 +mobilevitv2_175,40.530,59.470,56.277,43.723,14.25,256,0.888,bicubic,-53.700,-42.653,-51 +tresnet_m_448,40.527,59.473,56.703,43.297,31.39,448,0.875,bilinear,-54.133,-42.447,-107 +dla169,40.523,59.477,57.257,42.743,53.39,224,0.875,bilinear,-53.267,-41.573,0 +pit_xs_224,40.487,59.513,56.533,43.467,10.62,224,0.900,bicubic,-52.423,-42.247,+88 +resnetaa50,40.473,59.527,56.027,43.973,25.56,288,1.000,bicubic,-54.407,-43.103,-142 +repvgg_b2,40.463,59.537,57.773,42.227,89.02,224,0.875,bilinear,-53.127,-41.297,+23 +regnetx_320,40.447,59.553,55.667,44.333,107.81,224,0.875,bicubic,-53.773,-43.383,-55 +coat_mini,40.420,59.580,55.157,44.843,10.34,224,0.900,bicubic,-54.350,-43.793,-131 +skresnet34,40.393,59.607,56.740,43.260,22.28,224,0.875,bicubic,-52.177,-41.780,+112 +efficientnet_el_pruned,40.390,59.610,56.887,43.113,10.59,300,0.904,bicubic,-53.700,-42.123,-43 +resnet50,40.383,59.617,54.663,45.337,25.56,224,0.950,bicubic,-53.547,-43.807,-26 +efficientnet_b2_pruned,40.380,59.620,56.533,43.467,8.31,260,0.890,bicubic,-53.420,-42.377,-11 +wide_resnet101_2,40.360,59.640,55.787,44.213,126.89,224,0.875,bilinear,-53.360,-43.023,-4 +coat_lite_mini,40.353,59.647,55.723,44.277,11.01,224,0.900,bicubic,-53.107,-43.057,+31 +legacy_seresnext101_32x4d,40.353,59.647,54.823,45.177,48.96,224,0.875,bilinear,-53.767,-44.147,-52 +sebotnet33ts_256,40.340,59.660,53.217,46.783,13.70,256,0.940,bicubic,-53.970,-45.383,-74 +tf_efficientnet_b0_ap,40.333,59.667,56.793,43.207,5.29,224,0.875,bicubic,-52.287,-41.577,+99 +regnetx_160,40.273,59.727,56.060,43.940,54.28,224,0.875,bicubic,-53.617,-43.030,-32 +densenet201,40.270,59.730,56.713,43.287,20.01,224,0.875,bicubic,-52.430,-41.937,+90 +resnext50d_32x4d,40.157,59.843,55.490,44.510,25.05,224,0.875,bicubic,-53.663,-43.250,-20 +eca_resnet33ts,40.137,59.863,57.003,42.997,19.68,256,0.900,bicubic,-53.723,-41.887,-30 +mobilevitv2_200,40.133,59.867,55.510,44.490,18.45,256,0.888,bicubic,-54.377,-43.460,-102 +darknetaa53,40.120,59.880,55.787,44.213,36.02,288,1.000,bilinear,-54.090,-43.163,-68 +hrnet_w48,40.097,59.903,56.647,43.353,77.47,224,0.875,bilinear,-53.933,-42.383,-51 +vit_base_patch16_224_sam,40.093,59.907,55.433,44.567,86.57,224,0.900,bicubic,-53.797,-43.457,-38 +legacy_seresnet152,40.037,59.963,55.820,44.180,66.82,224,0.875,bilinear,-53.393,-43.030,+24 +hrnet_w30,40.030,59.970,57.100,42.900,37.71,224,0.875,bilinear,-53.350,-41.730,+28 +regnetz_b16,40.000,60.000,55.623,44.377,9.72,288,0.940,bicubic,-54.680,-43.537,-135 +regnetx_080,39.997,60.003,55.963,44.037,39.57,224,0.875,bicubic,-53.793,-42.937,-27 +tf_efficientnet_b1,39.980,60.020,56.133,43.867,7.79,240,0.882,bicubic,-53.730,-42.667,-16 +gluon_resnet101_v1c,39.950,60.050,55.310,44.690,44.57,224,0.875,bicubic,-53.730,-43.450,-16 +resmlp_12_distilled_224,39.833,60.167,57.440,42.560,15.35,224,0.875,bicubic,-53.037,-41.180,+66 +seresnet33ts,39.823,60.177,56.523,43.477,19.78,256,0.900,bicubic,-54.447,-42.257,-87 +res2net50_26w_8s,39.807,60.193,54.910,45.090,48.40,224,0.875,bilinear,-53.633,-43.780,+14 +tf_efficientnetv2_b0,39.787,60.213,56.290,43.710,7.14,224,0.875,bicubic,-53.273,-42.400,+43 +darknet53,39.733,60.267,55.283,44.717,41.61,288,1.000,bicubic,-54.627,-43.767,-101 +lambda_resnet50ts,39.733,60.267,54.340,45.660,21.54,256,0.950,bicubic,-54.837,-44.310,-126 +res2net101_26w_4s,39.713,60.287,54.550,45.450,45.21,224,0.875,bilinear,-53.817,-44.050,0 +regnetx_120,39.690,60.310,55.650,44.350,46.11,224,0.875,bicubic,-54.570,-43.540,-92 +vit_small_patch32_224,39.687,60.313,55.260,44.740,22.88,224,0.900,bicubic,-52.473,-43.250,+105 +hrnet_w44,39.680,60.320,55.333,44.667,67.06,224,0.875,bilinear,-53.930,-43.627,-15 +densenet161,39.623,60.377,56.130,43.870,28.68,224,0.875,bicubic,-53.277,-42.680,+53 +resmlp_big_24_224,39.623,60.377,54.820,45.180,129.14,224,0.875,bicubic,-54.637,-44.000,-95 +mixnet_xl,39.613,60.387,55.883,44.117,11.90,224,0.875,bicubic,-54.617,-42.937,-93 +xception41,39.607,60.393,55.047,44.953,26.97,299,0.903,bicubic,-53.873,-43.703,-2 +tf_efficientnetv2_b1,39.573,60.427,55.353,44.647,8.14,240,0.882,bicubic,-54.137,-43.467,-35 +gcresnet33ts,39.557,60.443,55.823,44.177,19.88,256,0.900,bicubic,-54.273,-43.087,-50 +dla102x,39.543,60.457,56.310,43.690,26.31,224,0.875,bilinear,-53.987,-42.540,-12 +xcit_tiny_12_p16_224,39.543,60.457,55.023,44.977,6.72,224,1.000,bicubic,-52.917,-43.607,+78 +sehalonet33ts,39.533,60.467,54.013,45.987,13.69,256,0.940,bicubic,-55.007,-44.747,-134 +rexnet_130,39.490,60.510,56.643,43.357,7.56,224,0.875,bicubic,-54.180,-42.057,-34 +hrnet_w32,39.463,60.537,56.137,43.863,41.23,224,0.875,bilinear,-53.487,-42.703,+37 +resnetv2_50x1_bitm,39.433,60.567,57.857,42.143,25.55,448,1.000,bilinear,-55.317,-41.323,-174 +levit_128,39.423,60.577,55.350,44.650,9.21,224,0.900,bicubic,-53.627,-43.350,+25 +densenetblur121d,39.380,60.620,56.630,43.370,8.00,224,0.875,bicubic,-53.030,-41.790,+78 +regnety_120,39.353,60.647,55.277,44.723,51.82,224,0.875,bicubic,-54.657,-43.753,-80 +mobilevitv2_150,39.340,60.660,55.203,44.797,10.59,256,0.888,bicubic,-54.730,-43.697,-86 +tf_efficientnet_el,39.307,60.693,55.380,44.620,10.59,300,0.904,bicubic,-55.053,-43.720,-125 +tv_resnet101,39.293,60.707,55.793,44.207,44.55,224,0.875,bilinear,-53.587,-42.867,+38 +tf_inception_v3,39.250,60.750,54.303,45.697,23.83,299,0.875,bicubic,-53.950,-44.177,+8 gluon_resnet50_v1s,39.237,60.763,55.010,44.990,25.68,224,0.875,bicubic,-54.353,-43.830,-31 -tf_efficientnetv2_b2,39.173,60.827,54.567,45.433,10.10,260,0.890,bicubic,-54.897,-44.363,-90 -densenet169,39.167,60.833,55.840,44.160,14.15,224,0.875,bicubic,-53.113,-42.750,+71 -legacy_seresnet101,39.027,60.973,55.000,45.000,49.33,224,0.875,bilinear,-54.243,-43.740,-5 -efficientnet_b1_pruned,39.010,60.990,55.633,44.367,6.33,240,0.882,bicubic,-53.960,-42.887,+19 -repvgg_b1g4,38.997,61.003,56.353,43.647,39.97,224,0.875,bilinear,-54.033,-42.467,+12 -crossvit_9_dagger_240,38.973,61.027,54.863,45.137,8.78,240,0.875,bicubic,-53.787,-43.647,+36 -inception_v3,38.963,61.037,53.847,46.153,23.83,299,0.875,bicubic,-53.937,-44.483,+23 -dpn68,38.937,61.063,54.947,45.053,12.61,224,0.875,bicubic,-53.323,-43.663,+67 -resnet33ts,38.927,61.073,55.583,44.417,19.68,256,0.900,bicubic,-54.703,-43.177,-47 -legacy_seresnext50_32x4d,38.883,61.117,54.597,45.403,27.56,224,0.875,bilinear,-54.547,-44.203,-20 -dla102,38.843,61.157,55.323,44.677,33.27,224,0.875,bilinear,-54.417,-43.447,-11 -densenet121,38.780,61.220,56.280,43.720,7.98,224,0.875,bicubic,-53.160,-42.120,+76 -resnet32ts,38.770,61.230,55.807,44.193,17.96,256,0.900,bicubic,-54.800,-42.943,-41 -regnetx_040,38.707,61.293,55.350,44.650,22.12,224,0.875,bicubic,-54.963,-43.590,-57 -res2net50_14w_8s,38.693,61.307,54.073,45.927,25.06,224,0.875,bilinear,-54.337,-44.627,+3 -regnetx_032,38.690,61.310,55.163,44.837,15.30,224,0.875,bicubic,-54.560,-43.567,-14 -res2net50_26w_6s,38.690,61.310,53.760,46.240,37.05,224,0.875,bilinear,-54.910,-44.990,-49 +densenet169,39.173,60.827,55.847,44.153,14.15,224,0.875,bicubic,-53.117,-42.743,+76 +tf_efficientnetv2_b2,39.173,60.827,54.567,45.433,10.10,260,0.890,bicubic,-54.887,-44.363,-91 +legacy_seresnet101,39.033,60.967,55.007,44.993,49.33,224,0.875,bilinear,-54.237,-43.733,-4 +efficientnet_b1_pruned,39.003,60.997,55.633,44.367,6.33,240,0.882,bicubic,-53.967,-42.887,+23 +repvgg_b1g4,38.987,61.013,56.347,43.653,39.97,224,0.875,bilinear,-54.043,-42.473,+16 +crossvit_9_dagger_240,38.973,61.027,54.860,45.140,8.78,240,0.875,bicubic,-53.787,-43.650,+41 +inception_v3,38.957,61.043,53.840,46.160,23.83,299,0.875,bicubic,-53.943,-44.490,+28 +resnet33ts,38.930,61.070,55.580,44.420,19.68,256,0.900,bicubic,-54.700,-43.180,-46 +dpn68,38.917,61.083,54.930,45.070,12.61,224,0.875,bicubic,-53.333,-43.680,+72 +legacy_seresnext50_32x4d,38.883,61.117,54.597,45.403,27.56,224,0.875,bilinear,-54.537,-44.203,-19 +dla102,38.833,61.167,55.330,44.670,33.27,224,0.875,bilinear,-54.427,-43.440,-10 +densenet121,38.787,61.213,56.273,43.727,7.98,224,0.875,bicubic,-53.153,-42.007,+80 +resnet32ts,38.773,61.227,55.813,44.187,17.96,256,0.900,bicubic,-54.787,-42.937,-42 +regnetx_040,38.707,61.293,55.343,44.657,22.12,224,0.875,bicubic,-54.963,-43.597,-59 +res2net50_14w_8s,38.697,61.303,54.073,45.927,25.06,224,0.875,bilinear,-54.343,-44.627,+4 +regnetx_032,38.683,61.317,55.160,44.840,15.30,224,0.875,bicubic,-54.567,-43.570,-12 +res2net50_26w_6s,38.683,61.317,53.757,46.243,37.05,224,0.875,bilinear,-54.917,-44.993,-50 +selecsls60,38.617,61.383,55.633,44.367,30.67,224,0.875,bicubic,-54.393,-43.197,+5 dla60x,38.617,61.383,55.387,44.613,17.35,224,0.875,bilinear,-54.573,-43.323,-11 -selecsls60,38.613,61.387,55.633,44.367,30.67,224,0.875,bicubic,-54.387,-43.197,+2 -tf_efficientnet_b0,38.607,61.393,55.953,44.047,5.29,224,0.875,bicubic,-53.793,-42.457,+48 -dla60_res2net,38.593,61.407,54.550,45.450,20.85,224,0.875,bilinear,-54.787,-44.310,-26 -selecsls60b,38.563,61.437,55.303,44.697,32.77,224,0.875,bicubic,-54.937,-43.537,-41 -repvgg_a2,38.560,61.440,55.763,44.237,28.21,224,0.875,bilinear,-54.120,-42.757,+23 -hardcorenas_f,38.503,61.497,55.667,44.333,8.20,224,0.875,bilinear,-54.477,-42.953,-2 -dla60_res2next,38.453,61.547,54.957,45.043,17.03,224,0.875,bilinear,-55.117,-43.833,-54 -resmlp_12_224,38.443,61.557,56.323,43.677,15.35,224,0.875,bicubic,-53.677,-42.247,+56 -regnetx_064,38.430,61.570,54.987,45.013,26.21,224,0.875,bicubic,-55.190,-44.063,-62 -gluon_resnet50_v1b,38.410,61.590,54.813,45.187,25.56,224,0.875,bicubic,-54.150,-43.737,+29 -tf_efficientnet_cc_b0_4e,38.410,61.590,55.150,44.850,13.31,224,0.875,bicubic,-54.430,-43.290,+8 -hrnet_w18,38.263,61.737,55.643,44.357,21.30,224,0.875,bilinear,-54.487,-43.017,+13 -tinynet_a,38.223,61.777,55.177,44.823,6.19,192,0.875,bicubic,-54.567,-43.303,+9 -poolformer_s12,38.167,61.833,56.183,43.817,11.92,224,0.900,bicubic,-54.303,-42.167,+30 -mixnet_l,38.153,61.847,54.750,45.250,7.33,224,0.875,bicubic,-55.117,-43.950,-34 -hardcorenas_e,38.133,61.867,55.163,44.837,8.07,224,0.875,bilinear,-54.807,-43.407,-9 -efficientnet_b1,38.087,61.913,54.010,45.990,7.79,256,1.000,bicubic,-54.943,-44.700,-19 -coat_lite_tiny,38.063,61.937,53.460,46.540,5.72,224,0.900,bicubic,-54.797,-45.180,-1 -gmixer_24_224,38.063,61.937,52.077,47.923,24.72,224,0.875,bicubic,-54.617,-46.203,+8 -resnetrs50,37.960,62.040,53.317,46.683,35.69,224,0.910,bicubic,-56.060,-45.533,-124 -hardcorenas_c,37.887,62.113,55.727,44.273,5.52,224,0.875,bilinear,-54.443,-42.613,+32 -gluon_resnet50_v1c,37.853,62.147,54.113,45.887,25.58,224,0.875,bicubic,-55.067,-44.587,-13 -res2net50_26w_4s,37.817,62.183,53.083,46.917,25.70,224,0.875,bilinear,-55.363,-45.587,-33 -efficientnet_es,37.777,62.223,54.977,45.023,5.44,224,0.875,bicubic,-55.143,-43.713,-16 -resnest14d,37.770,62.230,56.463,43.537,10.61,224,0.875,bilinear,-53.360,-41.867,+75 -tv_resnext50_32x4d,37.743,62.257,54.107,45.893,25.03,224,0.875,bilinear,-55.167,-44.613,-15 -resnet26t,37.687,62.313,55.260,44.740,16.01,256,0.940,bicubic,-54.983,-43.320,+4 -ecaresnet26t,37.643,62.357,54.350,45.650,16.01,320,0.950,bicubic,-56.307,-44.570,-126 -hardcorenas_d,37.550,62.450,54.723,45.277,7.50,224,0.875,bilinear,-55.050,-43.707,+6 -res2next50,37.487,62.513,52.860,47.140,24.67,224,0.875,bilinear,-55.653,-45.790,-37 -resnet34,37.450,62.550,54.303,45.697,21.80,224,0.875,bilinear,-53.750,-43.937,+63 -pit_ti_distilled_224,37.333,62.667,55.137,44.863,5.10,224,0.900,bicubic,-53.567,-43.083,+75 -lambda_resnet26t,37.297,62.703,53.577,46.423,10.96,256,0.940,bicubic,-56.103,-45.153,-58 -hardcorenas_b,37.243,62.757,55.073,44.927,5.18,224,0.875,bilinear,-54.697,-43.207,+35 -mobilenetv3_large_100_miil,37.213,62.787,53.513,46.487,5.48,224,0.875,bilinear,-55.037,-44.737,+23 -eca_halonext26ts,37.177,62.823,53.113,46.887,10.76,256,0.940,bicubic,-56.383,-45.567,-80 -res2net50_48w_2s,37.127,62.873,53.340,46.660,25.29,224,0.875,bilinear,-55.663,-45.220,-14 -dla60,37.073,62.927,54.200,45.800,22.04,224,0.875,bilinear,-55.597,-44.430,-9 -lambda_resnet26rpt_256,37.073,62.927,53.830,46.170,10.99,256,0.940,bicubic,-56.357,-45.050,-68 -bat_resnext26ts,37.063,62.937,53.747,46.253,10.73,256,0.900,bicubic,-56.047,-44.983,-46 -rexnet_100,37.060,62.940,54.033,45.967,4.80,224,0.875,bicubic,-55.780,-44.587,-23 -regnety_016,37.013,62.987,54.083,45.917,11.20,224,0.875,bicubic,-55.987,-44.597,-40 -tf_mixnet_l,36.977,63.023,52.577,47.423,7.33,224,0.875,bicubic,-56.063,-46.103,-47 -botnet26t_256,36.960,63.040,53.073,46.927,12.49,256,0.950,bicubic,-56.470,-45.587,-74 -legacy_seresnet50,36.870,63.130,53.473,46.527,28.09,224,0.875,bilinear,-55.800,-45.177,-15 -halonet26t,36.857,63.143,52.277,47.723,12.48,256,0.950,bicubic,-56.743,-46.363,-97 -tv_densenet121,36.807,63.193,54.033,45.967,7.98,224,0.875,bicubic,-54.603,-44.217,+40 -tf_efficientnet_lite2,36.803,63.197,53.323,46.677,6.09,260,0.890,bicubic,-55.777,-45.227,-11 -mobilenetv2_120d,36.773,63.227,54.043,45.957,5.83,224,0.875,bicubic,-55.837,-44.457,-16 -tf_efficientnet_lite1,36.740,63.260,53.587,46.413,5.42,240,0.882,bicubic,-55.570,-44.903,+4 -regnetx_016,36.680,63.320,53.307,46.693,9.19,224,0.875,bicubic,-55.860,-45.243,-11 -eca_botnext26ts_256,36.677,63.323,52.470,47.530,10.59,256,0.950,bicubic,-56.693,-46.230,-74 -hardcorenas_a,36.643,63.357,54.907,45.093,5.26,224,0.875,bilinear,-54.977,-43.263,+26 -levit_128s,36.613,63.387,53.127,46.873,7.78,224,0.900,bicubic,-54.887,-45.273,+28 -efficientnet_b0,36.603,63.397,53.487,46.513,5.29,224,0.875,bicubic,-55.877,-44.953,-13 -vit_base_patch32_224_sam,36.547,63.453,53.043,46.957,88.22,224,0.900,bicubic,-53.313,-44.557,+68 -xcit_nano_12_p8_224_dist,36.537,63.463,52.877,47.123,3.05,224,1.000,bicubic,-55.893,-45.643,-9 -tf_efficientnet_em,36.383,63.617,52.837,47.163,6.90,240,0.882,bicubic,-56.787,-45.833,-67 -skresnet18,36.320,63.680,54.193,45.807,11.96,224,0.875,bicubic,-53.850,-43.587,+61 -repvgg_b0,36.280,63.720,54.050,45.950,15.82,224,0.875,bilinear,-55.400,-44.400,+16 -tv_resnet50,36.180,63.820,52.800,47.200,25.56,224,0.875,bilinear,-55.960,-45.620,+2 -xcit_nano_12_p16_384_dist,36.150,63.850,53.253,46.747,3.05,384,1.000,bicubic,-55.960,-45.267,+4 -legacy_seresnet34,36.140,63.860,52.553,47.447,21.96,224,0.875,bilinear,-55.340,-45.647,+20 -coat_tiny,36.120,63.880,51.060,48.940,5.50,224,0.900,bicubic,-57.400,-47.790,-104 -tv_resnet34,36.083,63.917,53.533,46.467,21.80,224,0.875,bilinear,-54.207,-44.447,+53 -deit_tiny_distilled_patch16_224,36.030,63.970,54.237,45.763,5.91,224,0.900,bicubic,-55.080,-44.033,+36 -mobilenetv2_140,36.013,63.987,53.950,46.050,6.11,224,0.875,bicubic,-56.027,-44.300,0 -tf_efficientnet_lite0,35.927,64.073,53.470,46.530,4.65,224,0.875,bicubic,-55.373,-44.620,+21 -seresnext26ts,35.823,64.177,53.930,46.070,10.39,256,0.900,bicubic,-56.997,-44.670,-49 -selecsls42b,35.813,64.187,52.490,47.510,32.46,224,0.875,bicubic,-56.667,-46.190,-29 -xcit_nano_12_p8_384_dist,35.773,64.227,52.293,47.707,3.05,384,1.000,bicubic,-57.487,-46.557,-88 -gluon_resnet34_v1b,35.767,64.233,52.183,47.817,21.80,224,0.875,bicubic,-55.333,-45.997,+31 -dla34,35.640,64.360,52.783,47.217,15.74,224,0.875,bilinear,-55.590,-45.397,+19 -mixnet_m,35.637,64.363,52.433,47.567,5.01,224,0.875,bicubic,-56.633,-45.917,-18 -efficientnet_lite0,35.633,64.367,53.653,46.347,4.65,224,0.875,bicubic,-55.627,-44.177,+16 -ssl_resnet18,35.590,64.410,53.737,46.263,11.69,224,0.875,bilinear,-55.110,-44.293,+34 -mobilenetv3_rw,35.547,64.453,53.713,46.287,5.48,224,0.875,bicubic,-55.993,-44.557,+4 -efficientnet_es_pruned,35.380,64.620,52.840,47.160,5.44,224,0.875,bicubic,-56.320,-45.570,-3 -mobilenetv2_110d,35.290,64.710,52.837,47.163,4.52,224,0.875,bicubic,-56.050,-45.343,+9 -tf_mixnet_m,35.187,64.813,50.983,49.017,5.01,224,0.875,bicubic,-57.013,-47.437,-19 -hrnet_w18_small_v2,35.173,64.827,52.430,47.570,15.60,224,0.875,bilinear,-55.997,-45.910,+15 -resnet18d,35.127,64.873,52.890,47.110,11.71,224,0.875,bicubic,-54.863,-44.940,+40 -xcit_nano_12_p16_224_dist,35.123,64.877,52.553,47.447,3.05,224,1.000,bicubic,-55.037,-45.207,+38 -eca_resnext26ts,35.047,64.953,52.307,47.693,10.30,256,0.900,bicubic,-57.363,-46.313,-35 -resnext26ts,35.047,64.953,53.417,46.583,10.30,256,0.900,bicubic,-57.173,-44.833,-25 -convit_tiny,35.043,64.957,51.763,48.237,5.71,224,0.875,bicubic,-55.507,-46.447,+26 -gcresnext26ts,34.933,65.067,51.670,48.330,10.48,256,0.900,bicubic,-57.537,-46.820,-44 -tinynet_b,34.873,65.127,52.017,47.983,3.73,188,0.875,bicubic,-56.257,-46.053,+13 -ese_vovnet19b_dw,34.823,65.177,52.047,47.953,6.54,224,0.875,bicubic,-57.187,-46.463,-21 -regnety_008,34.810,65.190,51.750,48.250,6.26,224,0.875,bicubic,-57.100,-46.670,-19 -pit_ti_224,34.680,65.320,52.160,47.840,4.85,224,0.900,bicubic,-55.750,-45.840,+25 -crossvit_9_240,34.607,65.393,51.757,48.243,8.55,240,0.875,bicubic,-56.443,-46.553,+13 -mobilenetv3_large_100,34.603,65.397,52.863,47.137,5.48,224,0.875,bicubic,-56.877,-45.457,-9 -seresnext26d_32x4d,34.540,65.460,51.550,48.450,16.81,224,0.875,bicubic,-57.890,-46.990,-47 -seresnext26t_32x4d,34.533,65.467,51.377,48.623,16.81,224,0.875,bicubic,-58.277,-47.183,-74 -mixer_b16_224,34.430,65.570,48.077,51.923,59.88,224,0.875,bicubic,-56.710,-50.153,+3 -resnet26d,34.273,65.727,51.693,48.307,16.01,224,0.875,bicubic,-57.977,-46.757,-38 -tf_efficientnet_es,34.263,65.737,51.350,48.650,5.44,224,0.875,bicubic,-57.847,-47.080,-33 -fbnetc_100,34.253,65.747,51.180,48.820,5.57,224,0.875,bilinear,-57.007,-47.070,-9 -regnety_006,34.150,65.850,51.273,48.727,6.06,224,0.875,bicubic,-57.410,-47.157,-20 -tf_mobilenetv3_large_100,33.940,66.060,51.487,48.513,5.48,224,0.875,bilinear,-57.480,-46.773,-15 -semnasnet_075,33.783,66.217,52.423,47.577,2.91,224,0.875,bicubic,-56.427,-45.547,+17 -regnetx_008,33.773,66.227,50.540,49.460,7.26,224,0.875,bicubic,-57.387,-47.840,-6 -mnasnet_100,33.763,66.237,51.177,48.823,4.38,224,0.875,bicubic,-57.437,-46.873,-11 -lcnet_100,33.747,66.253,52.100,47.900,2.95,224,0.875,bicubic,-55.213,-45.280,+29 -vit_tiny_r_s16_p8_384,33.657,66.343,50.687,49.313,6.36,384,1.000,bicubic,-58.073,-47.743,-32 -mobilevit_s,33.643,66.357,49.273,50.727,5.58,256,0.900,bicubic,-59.517,-49.507,-115 -xcit_nano_12_p8_224,33.573,66.427,50.210,49.790,3.05,224,1.000,bicubic,-57.567,-47.190,-10 -vit_tiny_patch16_384,33.543,66.457,51.077,48.923,5.79,384,1.000,bicubic,-59.907,-47.753,-142 -semnasnet_100,33.520,66.480,50.777,49.223,3.89,224,0.875,bicubic,-58.140,-47.493,-32 -resnet26,33.507,66.493,50.920,49.080,16.00,224,0.875,bicubic,-57.933,-47.340,-26 -mixnet_s,33.487,66.513,50.993,49.007,4.13,224,0.875,bicubic,-58.293,-47.307,-39 -spnasnet_100,33.483,66.517,51.267,48.733,4.42,224,0.875,bilinear,-57.127,-46.683,-2 -crossvit_tiny_240,33.363,66.637,49.893,50.107,7.01,240,0.875,bicubic,-57.177,-48.047,-1 -vgg19_bn,33.230,66.770,50.803,49.197,143.68,224,0.875,bilinear,-57.760,-47.307,-9 -ghostnet_100,33.203,66.797,51.157,48.843,5.18,224,0.875,bilinear,-57.237,-46.673,-1 -regnetx_006,33.147,66.853,50.253,49.747,6.20,224,0.875,bicubic,-57.623,-47.847,-9 -resnet18,33.070,66.930,51.180,48.820,11.69,224,0.875,bilinear,-55.080,-45.940,+22 -xcit_nano_12_p16_224,32.967,67.033,49.993,50.007,3.05,224,1.000,bicubic,-55.983,-47.397,+16 -legacy_seresnext26_32x4d,32.757,67.243,49.260,50.740,16.79,224,0.875,bicubic,-59.823,-49.150,-84 -hrnet_w18_small,32.670,67.330,50.597,49.403,13.19,224,0.875,bilinear,-57.210,-47.293,+2 -deit_tiny_patch16_224,32.657,67.343,50.277,49.723,5.72,224,0.900,bicubic,-56.963,-47.683,+5 -legacy_seresnet18,32.593,67.407,50.323,49.677,11.78,224,0.875,bicubic,-56.667,-47.357,+8 -regnetx_004,32.520,67.480,49.330,50.670,5.16,224,0.875,bicubic,-56.950,-48.440,+4 -mobilenetv2_100,32.517,67.483,50.793,49.207,3.50,224,0.875,bicubic,-57.313,-47.037,0 -gluon_resnet18_v1b,32.407,67.593,49.727,50.273,11.69,224,0.875,bicubic,-56.253,-47.373,+10 -regnety_004,32.323,67.677,49.447,50.553,4.34,224,0.875,bicubic,-58.447,-48.633,-18 -tf_mixnet_s,32.183,67.817,48.493,51.507,4.13,224,0.875,bicubic,-59.497,-49.747,-51 -vit_tiny_patch16_224,32.020,67.980,49.013,50.987,5.72,224,0.900,bicubic,-59.890,-49.327,-57 -tf_mobilenetv3_large_075,31.863,68.137,49.110,50.890,3.99,224,0.875,bilinear,-58.457,-48.760,-13 -tf_mobilenetv3_large_minimal_100,31.597,68.403,49.340,50.660,3.92,224,0.875,bilinear,-57.573,-47.980,+2 -vit_tiny_r_s16_p8_224,30.807,69.193,47.650,52.350,6.34,224,0.900,bicubic,-58.533,-50.050,-2 -tinynet_c,30.510,69.490,48.483,51.517,2.46,184,0.875,bicubic,-57.910,-48.777,+4 -lcnet_075,30.370,69.630,48.763,51.237,2.36,224,0.875,bicubic,-56.570,-47.767,+13 -vgg16_bn,30.357,69.643,47.257,52.743,138.37,224,0.875,bilinear,-60.183,-50.733,-21 -regnety_002,29.683,70.317,46.800,53.200,3.16,224,0.875,bicubic,-58.507,-50.620,+3 -mobilevit_xs,29.587,70.413,46.000,54.000,2.32,256,0.900,bicubic,-61.593,-52.220,-42 -mobilenetv3_small_100,29.047,70.953,47.183,52.817,2.54,224,0.875,bicubic,-57.123,-49.277,+10 -mnasnet_small,28.950,71.050,47.267,52.733,2.03,224,0.875,bicubic,-56.560,-48.713,+11 -vgg13_bn,28.893,71.107,46.737,53.263,133.05,224,0.875,bilinear,-60.307,-50.783,-8 -regnetx_002,28.863,71.137,45.420,54.580,2.68,224,0.875,bicubic,-58.517,-51.570,+2 -mobilenetv2_050,28.680,71.320,46.597,53.403,1.97,224,0.875,bicubic,-56.310,-49.023,+11 -vgg19,28.577,71.423,45.167,54.833,143.67,224,0.875,bilinear,-61.103,-52.383,-17 -dla60x_c,28.447,71.553,46.193,53.807,1.32,224,0.875,bilinear,-58.663,-50.947,+1 -vgg11_bn,28.423,71.577,46.443,53.557,132.87,224,0.875,bilinear,-59.967,-50.827,-7 -tinynet_d,27.967,72.033,45.853,54.147,2.34,152,0.875,bicubic,-57.463,-50.167,+6 -vgg16,27.877,72.123,44.673,55.327,138.36,224,0.875,bilinear,-61.483,-52.847,-18 -tf_mobilenetv3_small_100,27.297,72.703,44.420,55.580,2.54,224,0.875,bilinear,-58.673,-51.990,+1 -mixer_l16_224,26.847,73.153,37.927,62.073,208.20,224,0.875,bicubic,-60.123,-56.113,-3 -vgg11,26.533,73.467,43.460,56.540,132.86,224,0.875,bilinear,-60.807,-53.650,-6 -mobilenetv3_small_075,26.530,73.470,43.887,56.113,2.04,224,0.875,bicubic,-57.590,-51.613,+5 -mobilevit_xxs,26.347,73.653,43.030,56.970,1.27,256,0.900,bicubic,-61.603,-54.150,-11 -vgg13,26.270,73.730,43.373,56.627,133.05,224,0.875,bilinear,-61.300,-53.747,-11 -lcnet_050,26.220,73.780,44.573,55.427,1.88,224,0.875,bicubic,-56.780,-50.447,+3 -dla46x_c,26.217,73.783,43.780,56.220,1.07,224,0.875,bilinear,-59.263,-52.660,-4 -tf_mobilenetv3_small_075,26.203,73.797,43.640,56.360,2.04,224,0.875,bilinear,-58.327,-52.250,-1 -dla46_c,25.500,74.500,43.800,56.200,1.30,224,0.875,bilinear,-59.170,-52.400,-3 -tf_mobilenetv3_small_minimal_100,25.090,74.910,42.930,57.070,2.04,224,0.875,bilinear,-57.590,-52.080,0 -tinynet_e,23.363,76.637,41.090,58.910,2.04,106,0.875,bicubic,-56.437,-52.890,0 +dla60_res2net,38.607,61.393,54.547,45.453,20.85,224,0.875,bilinear,-54.763,-44.293,-25 +tf_efficientnet_b0,38.577,61.423,55.963,44.037,5.29,224,0.875,bicubic,-53.823,-42.507,+52 +selecsls60b,38.563,61.437,55.287,44.713,32.77,224,0.875,bicubic,-54.937,-43.553,-42 +repvgg_a2,38.557,61.443,55.760,44.240,28.21,224,0.875,bilinear,-54.123,-42.760,+26 +hardcorenas_f,38.503,61.497,55.650,44.350,8.20,224,0.875,bilinear,-54.477,-42.970,+2 +resmlp_12_224,38.443,61.557,56.320,43.680,15.35,224,0.875,bicubic,-53.677,-42.250,+62 +dla60_res2next,38.433,61.567,54.947,45.053,17.03,224,0.875,bilinear,-55.117,-43.833,-53 +regnetx_064,38.420,61.580,54.990,45.010,26.21,224,0.875,bicubic,-55.200,-44.060,-64 +gluon_resnet50_v1b,38.413,61.587,54.817,45.183,25.56,224,0.875,bicubic,-54.147,-43.733,+33 +tf_efficientnet_cc_b0_4e,38.400,61.600,55.157,44.843,13.31,224,0.875,bicubic,-54.430,-43.283,+12 +hrnet_w18,38.273,61.727,55.653,44.347,21.30,224,0.875,bilinear,-54.487,-43.007,+16 +tinynet_a,38.223,61.777,55.177,44.823,6.19,192,0.875,bicubic,-54.587,-43.383,+13 +poolformer_s12,38.163,61.837,56.190,43.810,11.92,224,0.900,bicubic,-54.307,-42.160,+33 +mixnet_l,38.160,61.840,54.753,45.247,7.33,224,0.875,bicubic,-55.110,-43.947,-33 +hardcorenas_e,38.150,61.850,55.167,44.833,8.07,224,0.875,bilinear,-54.790,-43.413,-5 +efficientnet_b1,38.090,61.910,54.020,45.980,7.79,256,1.000,bicubic,-54.930,-44.690,-13 +coat_lite_tiny,38.070,61.930,53.460,46.540,5.72,224,0.900,bicubic,-54.790,-45.180,+3 +gmixer_24_224,38.063,61.937,52.077,47.923,24.72,224,0.875,bicubic,-54.617,-46.203,+13 +resnetrs50,37.970,62.030,53.313,46.687,35.69,224,0.910,bicubic,-56.050,-45.537,-124 +mobilevitv2_125,37.883,62.117,54.060,45.940,7.48,256,0.888,bicubic,-55.577,-44.800,-56 +hardcorenas_c,37.873,62.127,55.713,44.287,5.52,224,0.875,bilinear,-54.487,-42.637,+34 +gluon_resnet50_v1c,37.850,62.150,54.117,45.883,25.58,224,0.875,bicubic,-55.060,-44.583,-8 +res2net50_26w_4s,37.830,62.170,53.070,46.930,25.70,224,0.875,bilinear,-55.350,-45.600,-33 +efficientnet_es,37.787,62.213,54.980,45.020,5.44,224,0.875,bicubic,-55.133,-43.710,-13 +resnest14d,37.773,62.227,56.450,43.550,10.61,224,0.875,bilinear,-53.357,-41.880,+80 +tv_resnext50_32x4d,37.740,62.260,54.120,45.880,25.03,224,0.875,bilinear,-55.170,-44.600,-13 +resnet26t,37.690,62.310,55.260,44.740,16.01,256,0.940,bicubic,-54.980,-43.320,+6 +ecaresnet26t,37.647,62.353,54.347,45.653,16.01,320,0.950,bicubic,-56.313,-44.573,-128 +hardcorenas_d,37.533,62.467,54.713,45.287,7.50,224,0.875,bilinear,-55.067,-43.717,+10 +res2next50,37.483,62.517,52.863,47.137,24.67,224,0.875,bilinear,-55.677,-45.787,-37 +resnet34,37.453,62.547,54.303,45.697,21.80,224,0.875,bilinear,-53.747,-43.937,+68 +pit_ti_distilled_224,37.323,62.677,55.133,44.867,5.10,224,0.900,bicubic,-53.577,-43.087,+80 +lambda_resnet26t,37.297,62.703,53.580,46.420,10.96,256,0.940,bicubic,-56.103,-45.150,-59 +hardcorenas_b,37.240,62.760,55.050,44.950,5.18,224,0.875,bilinear,-54.690,-43.350,+40 +mobilenetv3_large_100_miil,37.220,62.780,53.547,46.453,5.48,224,0.875,bilinear,-55.050,-44.693,+25 +eca_halonext26ts,37.183,62.817,53.120,46.880,10.76,256,0.940,bicubic,-56.377,-45.560,-83 +cs3darknet_focus_m,37.140,62.860,53.917,46.083,9.30,288,0.950,bicubic,-55.970,-44.823,-41 +res2net50_48w_2s,37.127,62.873,53.347,46.653,25.29,224,0.875,bilinear,-55.663,-45.133,-12 +lambda_resnet26rpt_256,37.077,62.923,53.840,46.160,10.99,256,0.940,bicubic,-56.353,-45.040,-70 +dla60,37.073,62.927,54.193,45.807,22.04,224,0.875,bilinear,-55.587,-44.437,-6 +rexnet_100,37.063,62.937,54.037,45.963,4.80,224,0.875,bicubic,-55.787,-44.583,-20 +bat_resnext26ts,37.063,62.937,53.753,46.247,10.73,256,0.900,bicubic,-56.037,-44.977,-45 +regnety_016,37.010,62.990,54.080,45.920,11.20,224,0.875,bicubic,-55.990,-44.600,-37 +tf_mixnet_l,36.973,63.027,52.587,47.413,7.33,224,0.875,bicubic,-56.067,-45.953,-43 +botnet26t_256,36.957,63.043,53.083,46.917,12.49,256,0.950,bicubic,-56.473,-45.567,-74 +legacy_seresnet50,36.867,63.133,53.473,46.527,28.09,224,0.875,bilinear,-55.803,-45.177,-14 +halonet26t,36.850,63.150,52.277,47.723,12.48,256,0.950,bicubic,-56.760,-46.363,-100 +tv_densenet121,36.813,63.187,54.030,45.970,7.98,224,0.875,bicubic,-54.587,-44.220,+43 +tf_efficientnet_lite2,36.803,63.197,53.320,46.680,6.09,260,0.890,bicubic,-55.797,-45.230,-11 +mobilenetv2_120d,36.793,63.207,54.050,45.950,5.83,224,0.875,bicubic,-55.817,-44.450,-13 +tf_efficientnet_lite1,36.727,63.273,53.580,46.420,5.42,240,0.882,bicubic,-55.583,-44.910,+6 +eca_botnext26ts_256,36.687,63.313,52.483,47.517,10.59,256,0.950,bicubic,-56.683,-46.217,-75 +regnetx_016,36.677,63.323,53.293,46.707,9.19,224,0.875,bicubic,-55.853,-45.257,-10 +hardcorenas_a,36.673,63.327,54.917,45.083,5.26,224,0.875,bilinear,-54.947,-43.253,+29 +levit_128s,36.633,63.367,53.123,46.877,7.78,224,0.900,bicubic,-54.867,-45.277,+31 +efficientnet_b0,36.597,63.403,53.487,46.513,5.29,224,0.875,bicubic,-55.883,-45.193,-12 +vit_base_patch32_224_sam,36.550,63.450,53.043,46.957,88.22,224,0.900,bicubic,-53.310,-44.557,+72 +xcit_nano_12_p8_224_dist,36.533,63.467,52.883,47.117,3.05,224,1.000,bicubic,-55.887,-45.637,-7 +cs3darknet_m,36.457,63.543,53.230,46.770,9.31,288,0.950,bicubic,-56.803,-45.490,-76 +mobilevitv2_100,36.393,63.607,53.067,46.933,4.90,256,0.888,bicubic,-56.737,-45.693,-65 +tf_efficientnet_em,36.387,63.613,52.833,47.167,6.90,240,0.882,bicubic,-56.783,-45.837,-70 +skresnet18,36.323,63.677,54.187,45.813,11.96,224,0.875,bicubic,-53.847,-43.593,+63 +repvgg_b0,36.283,63.717,54.067,45.933,15.82,224,0.875,bilinear,-55.397,-44.383,+18 +tv_resnet50,36.167,63.833,52.807,47.193,25.56,224,0.875,bilinear,-55.963,-45.613,+3 +xcit_nano_12_p16_384_dist,36.160,63.840,53.247,46.753,3.05,384,1.000,bicubic,-55.970,-45.273,+1 +legacy_seresnet34,36.140,63.860,52.550,47.450,21.96,224,0.875,bilinear,-55.350,-45.650,+21 +coat_tiny,36.120,63.880,51.060,48.940,5.50,224,0.900,bicubic,-57.390,-47.630,-107 +tv_resnet34,36.077,63.923,53.533,46.467,21.80,224,0.875,bilinear,-54.213,-44.447,+55 +deit_tiny_distilled_patch16_224,36.023,63.977,54.237,45.763,5.91,224,0.900,bicubic,-55.057,-44.033,+39 +mobilenetv2_140,36.010,63.990,53.957,46.043,6.11,224,0.875,bicubic,-56.030,-44.293,0 +tf_efficientnet_lite0,35.917,64.083,53.473,46.527,4.65,224,0.875,bicubic,-55.383,-44.617,+23 +seresnext26ts,35.830,64.170,53.933,46.067,10.39,256,0.900,bicubic,-56.990,-44.667,-49 +selecsls42b,35.807,64.193,52.493,47.507,32.46,224,0.875,bicubic,-56.673,-45.947,-28 +xcit_nano_12_p8_384_dist,35.770,64.230,52.297,47.703,3.05,384,1.000,bicubic,-57.500,-46.553,-95 +gluon_resnet34_v1b,35.760,64.240,52.183,47.817,21.80,224,0.875,bicubic,-55.340,-45.997,+32 +dla34,35.640,64.360,52.787,47.213,15.74,224,0.875,bilinear,-55.590,-45.383,+21 +efficientnet_lite0,35.637,64.363,53.637,46.363,4.65,224,0.875,bicubic,-55.623,-44.613,+18 +mixnet_m,35.637,64.363,52.423,47.577,5.01,224,0.875,bicubic,-56.633,-45.927,-19 +ssl_resnet18,35.593,64.407,53.740,46.260,11.69,224,0.875,bilinear,-55.107,-44.290,+36 +mobilenetv3_rw,35.537,64.463,53.707,46.293,5.48,224,0.875,bicubic,-56.013,-44.573,+5 +efficientnet_es_pruned,35.390,64.610,52.847,47.153,5.44,224,0.875,bicubic,-56.320,-45.563,-2 +mobilenetv2_110d,35.307,64.693,52.847,47.153,4.52,224,0.875,bicubic,-56.023,-45.343,+11 +tf_mixnet_m,35.180,64.820,50.983,49.017,5.01,224,0.875,bicubic,-57.030,-47.437,-19 +hrnet_w18_small_v2,35.170,64.830,52.430,47.570,15.60,224,0.875,bilinear,-56.000,-45.900,+17 +resnet18d,35.133,64.867,52.890,47.110,11.71,224,0.875,bicubic,-54.847,-44.940,+42 +xcit_nano_12_p16_224_dist,35.120,64.880,52.543,47.457,3.05,224,1.000,bicubic,-55.050,-45.207,+40 +eca_resnext26ts,35.050,64.950,52.310,47.690,10.30,256,0.900,bicubic,-57.360,-46.310,-35 +convit_tiny,35.047,64.953,51.770,48.230,5.71,224,0.875,bicubic,-55.503,-46.450,+29 +resnext26ts,35.043,64.957,53.420,46.580,10.30,256,0.900,bicubic,-57.177,-44.830,-26 +gcresnext26ts,34.930,65.070,51.673,48.327,10.48,256,0.900,bicubic,-57.530,-46.817,-42 +tinynet_b,34.863,65.137,52.010,47.990,3.73,188,0.875,bicubic,-56.277,-46.050,+13 +ese_vovnet19b_dw,34.833,65.167,52.033,47.967,6.54,224,0.875,bicubic,-57.167,-46.477,-21 +regnety_008,34.810,65.190,51.750,48.250,6.26,224,0.875,bicubic,-57.090,-46.670,-17 +pit_ti_224,34.677,65.323,52.160,47.840,4.85,224,0.900,bicubic,-55.763,-45.850,+26 +mobilenetv3_large_100,34.600,65.400,52.863,47.137,5.48,224,0.875,bicubic,-56.880,-45.457,-7 +crossvit_9_240,34.597,65.403,51.763,48.237,8.55,240,0.875,bicubic,-56.453,-46.547,+14 +seresnext26t_32x4d,34.543,65.457,51.380,48.620,16.81,224,0.875,bicubic,-58.277,-47.180,-73 +seresnext26d_32x4d,34.533,65.467,51.553,48.447,16.81,224,0.875,bicubic,-57.897,-46.987,-48 +mixer_b16_224,34.423,65.577,48.080,51.920,59.88,224,0.875,bicubic,-56.727,-49.320,+4 +resnet26d,34.283,65.717,51.687,48.313,16.01,224,0.875,bicubic,-57.977,-46.763,-39 +tf_efficientnet_es,34.263,65.737,51.347,48.653,5.44,224,0.875,bicubic,-57.857,-47.083,-32 +fbnetc_100,34.253,65.747,51.187,48.813,5.57,224,0.875,bilinear,-56.997,-46.663,-6 +regnety_006,34.147,65.853,51.270,48.730,6.06,224,0.875,bicubic,-57.403,-47.160,-19 +tf_mobilenetv3_large_100,33.940,66.060,51.483,48.517,5.48,224,0.875,bilinear,-57.480,-46.777,-14 +semnasnet_075,33.780,66.220,52.427,47.573,2.91,224,0.875,bicubic,-56.430,-45.543,+19 +mnasnet_100,33.780,66.220,51.177,48.823,4.38,224,0.875,bicubic,-57.430,-46.873,-8 +regnetx_008,33.773,66.227,50.540,49.460,7.26,224,0.875,bicubic,-57.387,-47.840,-5 +lcnet_100,33.750,66.250,52.090,47.910,2.95,224,0.875,bicubic,-55.220,-45.290,+34 +vit_tiny_r_s16_p8_384,33.647,66.353,50.683,49.317,6.36,384,1.000,bicubic,-58.083,-47.747,-31 +mobilevit_s,33.637,66.363,49.280,50.720,5.58,256,0.900,bicubic,-59.523,-49.490,-118 +xcit_nano_12_p8_224,33.580,66.420,50.213,49.787,3.05,224,1.000,bicubic,-57.550,-48.017,-5 +vit_tiny_patch16_384,33.543,66.457,51.077,48.923,5.79,384,1.000,bicubic,-59.897,-47.753,-146 +semnasnet_100,33.523,66.477,50.787,49.213,3.89,224,0.875,bicubic,-58.137,-47.483,-31 +resnet26,33.493,66.507,50.930,49.070,16.00,224,0.875,bicubic,-57.947,-47.330,-25 +spnasnet_100,33.477,66.523,51.270,48.730,4.42,224,0.875,bilinear,-57.123,-46.690,+1 +mixnet_s,33.477,66.523,51.010,48.990,4.13,224,0.875,bicubic,-58.293,-47.290,-39 +crossvit_tiny_240,33.353,66.647,49.893,50.107,7.01,240,0.875,bicubic,-57.187,-48.047,+2 +mobilevitv2_075,33.350,66.650,50.077,49.923,2.87,256,0.888,bicubic,-58.620,-48.223,-46 +vgg19_bn,33.230,66.770,50.803,49.197,143.68,224,0.875,bilinear,-57.760,-47.307,-8 +ghostnet_100,33.207,66.793,51.160,48.840,5.18,224,0.875,bilinear,-57.233,-46.670,+1 +regnetx_006,33.147,66.853,50.253,49.747,6.20,224,0.875,bicubic,-57.623,-47.847,-8 +resnet18,33.070,66.930,51.180,48.820,11.69,224,0.875,bilinear,-55.080,-45.940,+26 +xcit_nano_12_p16_224,32.953,67.047,49.993,50.007,3.05,224,1.000,bicubic,-56.007,-47.407,+20 +legacy_seresnext26_32x4d,32.763,67.237,49.250,50.750,16.79,224,0.875,bicubic,-59.827,-49.160,-84 +edgenext_x_small,32.720,67.280,48.640,51.360,2.34,256,0.900,bicubic,-58.680,-49.520,-33 +hrnet_w18_small,32.667,67.333,50.597,49.403,13.19,224,0.875,bilinear,-57.203,-47.293,+2 +deit_tiny_patch16_224,32.663,67.337,50.270,49.730,5.72,224,0.900,bicubic,-56.957,-47.690,+5 +legacy_seresnet18,32.593,67.407,50.323,49.677,11.78,224,0.875,bicubic,-56.667,-47.367,+8 +mobilenetv2_100,32.523,67.477,50.820,49.180,3.50,224,0.875,bicubic,-57.297,-47.010,+1 +regnetx_004,32.510,67.490,49.337,50.663,5.16,224,0.875,bicubic,-56.960,-48.433,+3 +gluon_resnet18_v1b,32.407,67.593,49.727,50.273,11.69,224,0.875,bicubic,-56.253,-47.373,+13 +regnety_004,32.340,67.660,49.450,50.550,4.34,224,0.875,bicubic,-58.430,-48.630,-18 +tf_mixnet_s,32.190,67.810,48.503,51.497,4.13,224,0.875,bicubic,-59.500,-49.737,-53 +vit_tiny_patch16_224,32.020,67.980,49.023,50.977,5.72,224,0.900,bicubic,-59.890,-49.317,-59 +tf_mobilenetv3_large_075,31.857,68.143,49.113,50.887,3.99,224,0.875,bilinear,-58.473,-48.767,-13 +tf_mobilenetv3_large_minimal_100,31.593,68.407,49.340,50.660,3.92,224,0.875,bilinear,-57.587,-47.980,+3 +vit_tiny_r_s16_p8_224,30.797,69.203,47.643,52.357,6.34,224,0.900,bicubic,-58.553,-50.057,-2 +tinynet_c,30.510,69.490,48.490,51.510,2.46,184,0.875,bicubic,-57.910,-48.780,+7 +lcnet_075,30.383,69.617,48.753,51.247,2.36,224,0.875,bicubic,-56.557,-47.777,+16 +vgg16_bn,30.360,69.640,47.263,52.737,138.37,224,0.875,bilinear,-60.180,-50.727,-22 +regnety_002,29.687,70.313,46.800,53.200,3.16,224,0.875,bicubic,-58.503,-50.640,+6 +resnet10t,29.610,70.390,47.837,52.163,5.44,224,0.950,bilinear,-57.120,-48.833,+14 +mobilevit_xs,29.597,70.403,46.040,53.960,2.32,256,0.900,bicubic,-61.603,-52.180,-43 +edgenext_xx_small,29.420,70.580,46.500,53.500,1.33,256,0.900,bicubic,-59.810,-50.760,-7 +mobilenetv3_small_100,29.050,70.950,47.190,52.810,2.54,224,0.875,bicubic,-57.130,-49.270,+12 +mnasnet_small,28.950,71.050,47.267,52.733,2.03,224,0.875,bicubic,-56.560,-48.713,+13 +vgg13_bn,28.893,71.107,46.737,53.263,133.05,224,0.875,bilinear,-60.317,-50.783,-9 +regnetx_002,28.847,71.153,45.420,54.580,2.68,224,0.875,bicubic,-58.533,-51.570,+3 +mobilenetv2_050,28.663,71.337,46.593,53.407,1.97,224,0.875,bicubic,-56.347,-49.027,+13 +vgg19,28.580,71.420,45.170,54.830,143.67,224,0.875,bilinear,-61.100,-52.380,-19 +mobilevitv2_050,28.560,71.440,45.193,54.807,1.37,256,0.888,bicubic,-60.490,-52.397,-10 +dla60x_c,28.437,71.563,46.213,53.787,1.32,224,0.875,bilinear,-58.693,-50.927,+1 +vgg11_bn,28.423,71.577,46.447,53.553,132.87,224,0.875,bilinear,-59.967,-50.823,-7 +resnet14t,28.097,71.903,45.297,54.703,10.08,224,0.950,bilinear,-61.013,-52.073,-14 +tinynet_d,27.963,72.037,45.863,54.137,2.34,152,0.875,bicubic,-57.457,-50.157,+6 +vgg16,27.877,72.123,44.673,55.327,138.36,224,0.875,bilinear,-61.483,-52.847,-22 +tf_mobilenetv3_small_100,27.287,72.713,44.420,55.580,2.54,224,0.875,bilinear,-58.683,-51.980,+1 +mixer_l16_224,26.857,73.143,37.923,62.077,208.20,224,0.875,bicubic,-60.113,-56.127,-4 +mobilenetv3_small_075,26.533,73.467,43.887,56.113,2.04,224,0.875,bicubic,-57.587,-51.613,+6 +vgg11,26.533,73.467,43.460,56.540,132.86,224,0.875,bilinear,-60.807,-53.650,-8 +mobilevit_xxs,26.347,73.653,43.030,56.970,1.27,256,0.900,bicubic,-61.603,-54.150,-12 +vgg13,26.270,73.730,43.373,56.627,133.05,224,0.875,bilinear,-61.300,-53.747,-12 +lcnet_050,26.220,73.780,44.607,55.393,1.88,224,0.875,bicubic,-56.790,-50.403,+3 +dla46x_c,26.220,73.780,43.770,56.230,1.07,224,0.875,bilinear,-59.240,-52.680,-4 +tf_mobilenetv3_small_075,26.197,73.803,43.640,56.360,2.04,224,0.875,bilinear,-58.323,-52.250,-1 +dla46_c,25.497,74.503,43.790,56.210,1.30,224,0.875,bilinear,-59.163,-52.420,-3 +tf_mobilenetv3_small_minimal_100,25.097,74.903,42.923,57.077,2.04,224,0.875,bilinear,-57.593,-52.077,0 +tinynet_e,23.363,76.637,41.083,58.917,2.04,106,0.875,bicubic,-56.437,-52.897,0 mobilenetv3_small_050,21.743,78.257,38.757,61.243,1.59,224,0.875,bicubic,-56.357,-54.253,0 diff --git a/results/results-imagenet-real.csv b/results/results-imagenet-real.csv index 4c273da0..c0bc6be6 100644 --- a/results/results-imagenet-real.csv +++ b/results/results-imagenet-real.csv @@ -1,591 +1,669 @@ -model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation,top1_diff,top5_diff,rank_diff -beit_large_patch16_512,90.689,9.311,98.751,1.249,305.67,512,1.000,bicubic,+2.089,+0.095,0 -beit_large_patch16_384,90.610,9.390,98.766,1.234,305.00,384,1.000,bicubic,+2.206,+0.158,0 -volo_d5_512,90.608,9.392,98.698,1.302,296.09,512,1.150,bicubic,+3.566,+0.730,+7 -volo_d5_448,90.582,9.418,98.685,1.315,295.91,448,1.150,bicubic,+3.630,+0.745,+8 -tf_efficientnet_l2_ns,90.563,9.437,98.779,1.221,480.31,800,0.960,bicubic,+2.215,+0.131,-2 +model,top1,top1_err,top5,top5_err,param_count,img_size,crop_pct,interpolation,top1_diff,top5_diff,rank_diff +beit_large_patch16_512,90.691,9.309,98.751,1.249,305.67,512,1.000,bicubic,+2.089,+0.095,0 +beit_large_patch16_384,90.610,9.390,98.764,1.236,305.00,384,1.000,bicubic,+2.204,+0.158,0 +volo_d5_512,90.610,9.390,98.698,1.302,296.09,512,1.150,bicubic,+3.570,+0.730,+11 +volo_d5_448,90.584,9.416,98.685,1.315,295.91,448,1.150,bicubic,+3.630,+0.745,+13 +tf_efficientnet_l2_ns,90.563,9.437,98.779,1.221,480.31,800,0.960,bicubic,+2.213,+0.129,-2 tf_efficientnet_l2_ns_475,90.540,9.460,98.710,1.290,480.31,475,0.936,bicubic,+2.308,+0.164,-2 -volo_d4_448,90.507,9.492,98.591,1.409,193.41,448,1.150,bicubic,+3.717,+0.709,+8 -convnext_xlarge_384_in22ft1k,90.452,9.548,98.672,1.328,350.20,384,1.000,bicubic,+2.906,+0.186,-3 -beit_base_patch16_384,90.373,9.627,98.725,1.275,86.74,384,1.000,bicubic,+3.575,+0.589,+5 -convnext_large_384_in22ft1k,90.258,9.742,98.663,1.337,197.77,384,1.000,bicubic,+2.862,+0.295,-3 -vit_large_patch16_384,90.200,9.800,98.661,1.339,304.72,384,1.000,bicubic,+3.120,+0.361,-2 -cait_m48_448,90.192,9.809,98.484,1.516,356.46,448,1.000,bicubic,+3.706,+0.732,+7 -volo_d3_448,90.168,9.832,98.550,1.450,86.63,448,1.000,bicubic,+3.672,+0.840,+5 -beit_large_patch16_224,90.151,9.849,98.723,1.277,304.43,224,0.900,bicubic,+2.677,+0.419,-8 -convnext_base_384_in22ft1k,90.151,9.849,98.728,1.272,88.59,384,1.000,bicubic,+3.607,+0.538,+2 -tf_efficientnet_b7_ns,90.100,9.900,98.614,1.386,66.35,600,0.949,bicubic,+3.262,+0.518,-3 -cait_m36_384,90.046,9.954,98.493,1.507,271.22,384,1.000,bicubic,+3.994,+0.763,+12 -dm_nfnet_f6,90.044,9.956,98.546,1.454,438.36,576,0.956,bicubic,+3.902,+0.816,+8 -swin_large_patch4_window12_384,90.027,9.973,98.663,1.337,196.74,384,1.000,bicubic,+2.877,+0.423,-11 -tf_efficientnetv2_l_in21ft1k,90.008,9.992,98.619,1.381,118.52,480,1.000,bicubic,+3.704,+0.641,+4 -swin_base_patch4_window12_384,89.995,10.005,98.695,1.304,87.90,384,1.000,bicubic,+3.563,+0.639,0 -vit_base_patch16_384,89.984,10.016,98.680,1.319,86.86,384,1.000,bicubic,+3.974,+0.678,+9 -convnext_xlarge_in22ft1k,89.933,10.067,98.570,1.431,350.20,224,0.875,bicubic,+2.931,+0.358,-12 -xcit_large_24_p8_384_dist,89.886,10.114,98.384,1.616,188.93,384,1.000,bicubic,+3.888,+0.700,+8 -volo_d5_224,89.882,10.118,98.493,1.507,295.46,224,0.960,bicubic,+3.810,+0.915,+3 -cait_s36_384,89.846,10.154,98.427,1.573,68.37,384,1.000,bicubic,+4.384,+0.947,+19 -xcit_medium_24_p8_384_dist,89.814,10.186,98.362,1.638,84.32,384,1.000,bicubic,+4.000,+0.770,+10 -volo_d4_224,89.811,10.188,98.424,1.576,192.96,224,0.960,bicubic,+3.938,+0.956,+4 -convnext_large_in22ft1k,89.811,10.188,98.495,1.505,197.77,224,0.875,bicubic,+3.175,+0.467,-12 -vit_large_r50_s32_384,89.796,10.204,98.516,1.484,329.09,384,1.000,bicubic,+3.614,+0.596,-5 -swin_large_patch4_window7_224,89.792,10.208,98.640,1.360,196.53,224,0.900,bicubic,+3.478,+0.748,-8 -volo_d2_384,89.788,10.212,98.403,1.597,58.87,384,1.000,bicubic,+3.748,+0.831,-2 -tf_efficientnetv2_m_in21ft1k,89.779,10.221,98.501,1.499,54.14,480,1.000,bicubic,+4.189,+0.757,+8 -tf_efficientnet_b6_ns,89.777,10.223,98.512,1.488,43.04,528,0.942,bicubic,+3.323,+0.630,-14 -xcit_small_24_p8_384_dist,89.739,10.261,98.422,1.578,47.63,384,1.000,bicubic,+4.183,+0.850,+7 -volo_d1_384,89.694,10.306,98.294,1.706,26.78,384,1.000,bicubic,+4.446,+1.080,+18 -xcit_large_24_p16_384_dist,89.662,10.338,98.401,1.599,189.10,384,1.000,bicubic,+3.908,+0.863,+2 -tf_efficientnet_b5_ns,89.653,10.347,98.480,1.520,30.39,456,0.934,bicubic,+3.563,+0.730,-11 -convnext_base_in22ft1k,89.628,10.372,98.537,1.462,88.59,224,0.875,bicubic,+3.804,+0.671,-4 -tf_efficientnetv2_xl_in21ft1k,89.587,10.413,98.174,1.825,208.12,512,1.000,bicubic,+3.169,+0.308,-18 -tf_efficientnet_b8_ap,89.581,10.419,98.303,1.697,87.41,672,0.954,bicubic,+4.209,+1.011,+10 -dm_nfnet_f4,89.557,10.443,98.303,1.697,316.07,512,0.951,bicubic,+3.843,+0.781,-2 -volo_d3_224,89.557,10.443,98.375,1.625,86.33,224,0.960,bicubic,+4.145,+1.095,+6 -xcit_large_24_p8_224_dist,89.517,10.483,98.224,1.776,188.93,224,1.000,bicubic,+4.119,+0.814,+6 -xcit_small_12_p8_384_dist,89.515,10.485,98.303,1.697,26.21,384,1.000,bicubic,+4.435,+1.023,+16 -cait_s24_384,89.502,10.498,98.360,1.640,47.06,384,1.000,bicubic,+4.456,+1.014,+18 -dm_nfnet_f3,89.485,10.515,98.399,1.601,254.92,416,0.940,bicubic,+3.963,+0.937,-4 -xcit_medium_24_p16_384_dist,89.474,10.526,98.296,1.704,84.40,384,1.000,bicubic,+4.052,+0.964,-1 -dm_nfnet_f5,89.463,10.537,98.324,1.676,377.21,544,0.954,bicubic,+3.647,+0.838,-13 -deit_base_distilled_patch16_384,89.429,10.571,98.441,1.559,87.63,384,1.000,bicubic,+4.007,+1.035,-2 -tf_efficientnet_b7_ap,89.429,10.571,98.345,1.655,66.35,600,0.949,bicubic,+4.309,+1.093,+7 -vit_base_patch8_224,89.427,10.573,98.486,1.514,86.58,224,0.900,bicubic,+3.633,+0.692,-14 -beit_base_patch16_224,89.410,10.590,98.525,1.475,86.53,224,0.900,bicubic,+4.182,+0.867,+2 -regnetz_e8,89.380,10.620,98.459,1.542,57.70,320,1.000,bicubic,+4.350,+1.195,+12 -tf_efficientnetv2_l,89.367,10.633,98.273,1.727,118.52,480,1.000,bicubic,+3.877,+0.901,-11 -tf_efficientnet_b8,89.355,10.645,98.303,1.697,87.41,672,0.954,bicubic,+3.987,+0.913,-4 -tf_efficientnet_b6_ap,89.342,10.658,98.281,1.719,43.04,528,0.942,bicubic,+4.556,+1.143,+18 -volo_d2_224,89.327,10.673,98.207,1.794,58.68,224,0.960,bicubic,+4.133,+1.019,-2 -vit_large_patch16_224,89.312,10.688,98.394,1.606,304.33,224,0.900,bicubic,+3.474,+0.574,-25 -tf_efficientnet_b4_ns,89.303,10.697,98.347,1.653,19.34,380,0.922,bicubic,+4.141,+0.877,-3 -xcit_small_24_p16_384_dist,89.299,10.701,98.330,1.670,47.67,384,1.000,bicubic,+4.205,+1.020,-1 -xcit_medium_24_p8_224_dist,89.293,10.707,98.192,1.808,84.32,224,1.000,bicubic,+4.221,+0.912,0 -tf_efficientnetv2_m,89.284,10.716,98.236,1.764,54.14,480,1.000,bicubic,+4.246,+0.958,+2 -xcit_small_24_p8_224_dist,89.203,10.797,98.245,1.755,47.63,224,1.000,bicubic,+4.327,+1.057,+9 -xcit_small_12_p16_384_dist,89.199,10.801,98.219,1.781,26.25,384,1.000,bicubic,+4.489,+1.101,+12 -swin_base_patch4_window7_224,89.145,10.855,98.424,1.576,87.77,224,0.900,bicubic,+3.897,+0.862,-13 -cait_xs24_384,89.141,10.859,98.292,1.708,26.67,384,1.000,bicubic,+5.079,+1.402,+38 -eca_nfnet_l2,89.141,10.859,98.315,1.685,56.72,384,1.000,bicubic,+4.445,+1.051,+10 -ig_resnext101_32x48d,89.118,10.882,98.132,1.868,828.41,224,0.875,bilinear,+3.682,+0.556,-23 -ig_resnext101_32x32d,89.109,10.891,98.185,1.815,468.53,224,0.875,bilinear,+4.009,+0.751,-11 -tf_efficientnet_b7,89.083,10.917,98.185,1.815,66.35,600,0.949,bicubic,+4.147,+0.981,-1 -ecaresnet269d,89.066,10.934,98.232,1.768,102.09,352,1.000,bicubic,+4.090,+1.006,-4 -xcit_large_24_p16_224_dist,89.041,10.959,98.064,1.937,189.10,224,1.000,bicubic,+4.119,+0.931,-2 -resmlp_big_24_224_in22ft1k,89.011,10.989,98.215,1.785,129.14,224,0.875,bicubic,+4.617,+1.095,+14 -dm_nfnet_f2,89.007,10.993,98.189,1.810,193.78,352,0.920,bicubic,+3.945,+0.950,-12 -xcit_small_12_p8_224_dist,89.002,10.998,98.078,1.922,26.21,224,1.000,bicubic,+4.766,+1.204,+21 +volo_d4_448,90.507,9.492,98.591,1.409,193.41,448,1.150,bicubic,+3.715,+0.709,+14 +convnext_xlarge_384_in22ft1k,90.450,9.550,98.672,1.328,350.20,384,1.000,bicubic,+2.906,+0.186,-2 +swinv2_base_window12to24_192to384_22kft1k,90.401,9.599,98.740,1.260,87.92,384,1.000,bicubic,+3.293,+0.504,+3 +beit_base_patch16_384,90.371,9.629,98.725,1.275,86.74,384,1.000,bicubic,+3.573,+0.589,+10 +convnext_large_384_in22ft1k,90.258,9.742,98.663,1.337,197.77,384,1.000,bicubic,+2.862,+0.297,-2 +deit3_large_patch16_384_in21ft1k,90.249,9.751,98.625,1.375,304.76,384,1.000,bicubic,+2.533,+0.113,-7 +deit3_huge_patch14_224_in21ft1k,90.213,9.787,98.638,1.362,632.13,224,1.000,bicubic,+3.033,+0.378,-3 +vit_large_patch16_384,90.198,9.802,98.661,1.339,304.72,384,1.000,bicubic,+3.118,+0.361,-1 +cait_m48_448,90.189,9.811,98.484,1.516,356.46,448,1.000,bicubic,+3.701,+0.734,+11 +volo_d3_448,90.168,9.832,98.550,1.450,86.63,448,1.000,bicubic,+3.672,+0.840,+9 +swinv2_large_window12to24_192to384_22kft1k,90.157,9.843,98.604,1.396,196.74,384,1.000,bicubic,+2.701,+0.352,-9 +convnext_base_384_in22ft1k,90.151,9.849,98.728,1.272,88.59,384,1.000,bicubic,+3.609,+0.538,+6 +beit_large_patch16_224,90.151,9.849,98.723,1.277,304.43,224,0.900,bicubic,+2.675,+0.419,-12 +tf_efficientnet_b7_ns,90.093,9.907,98.614,1.386,66.35,600,0.949,bicubic,+3.261,+0.518,-1 +cait_m36_384,90.049,9.951,98.493,1.507,271.22,384,1.000,bicubic,+3.995,+0.763,+16 +dm_nfnet_f6,90.044,9.956,98.546,1.454,438.36,576,0.956,bicubic,+3.902,+0.816,+12 +swin_large_patch4_window12_384,90.027,9.973,98.663,1.337,196.74,384,1.000,bicubic,+2.875,+0.423,-12 +deit3_large_patch16_224_in21ft1k,90.006,9.994,98.661,1.339,304.37,224,1.000,bicubic,+3.024,+0.423,-8 +tf_efficientnetv2_l_in21ft1k,90.004,9.996,98.623,1.377,118.52,480,1.000,bicubic,+3.700,+0.643,+6 +swin_base_patch4_window12_384,89.995,10.005,98.695,1.304,87.90,384,1.000,bicubic,+3.563,+0.639,+2 +vit_base_patch16_384,89.987,10.014,98.680,1.319,86.86,384,1.000,bicubic,+3.981,+0.676,+12 +convnext_xlarge_in22ft1k,89.933,10.067,98.570,1.431,350.20,224,0.875,bicubic,+2.931,+0.358,-13 +swinv2_large_window12to16_192to256_22kft1k,89.922,10.078,98.510,1.490,196.74,256,0.900,bicubic,+2.976,+0.400,-11 +xcit_large_24_p8_384_dist,89.886,10.114,98.384,1.616,188.93,384,1.000,bicubic,+3.888,+0.700,+10 +deit3_base_patch16_384_in21ft1k,89.884,10.116,98.602,1.399,86.88,384,1.000,bicubic,+3.142,+0.490,-9 +volo_d5_224,89.882,10.118,98.493,1.507,295.46,224,0.960,bicubic,+3.812,+0.915,+4 +swinv2_base_window12to16_192to256_22kft1k,89.873,10.127,98.657,1.343,87.92,256,0.900,bicubic,+3.603,+0.761,-1g +cait_s36_384,89.844,10.156,98.424,1.576,68.37,384,1.000,bicubic,+4.384,+0.946,+22 +volo_d4_224,89.814,10.186,98.424,1.576,192.96,224,0.960,bicubic,+3.938,+0.956,+6 +convnext_large_in22ft1k,89.811,10.188,98.493,1.507,197.77,224,0.875,bicubic,+3.175,+0.465,-13 +xcit_medium_24_p8_384_dist,89.811,10.188,98.362,1.638,84.32,384,1.000,bicubic,+3.995,+0.770,+7 +convnext_small_384_in22ft1k,89.803,10.197,98.655,1.345,50.22,384,1.000,bicubic,+4.079,+0.791,+11 +swin_large_patch4_window7_224,89.794,10.206,98.642,1.358,196.53,224,0.900,bicubic,+3.474,+0.750,-9 +vit_large_r50_s32_384,89.792,10.208,98.516,1.484,329.09,384,1.000,bicubic,+3.612,+0.596,-7 +tf_efficientnet_b6_ns,89.784,10.216,98.512,1.488,43.04,528,0.942,bicubic,+3.334,+0.626,-14 +volo_d2_384,89.784,10.216,98.401,1.599,58.87,384,1.000,bicubic,+3.748,+0.827,-4 +tf_efficientnetv2_m_in21ft1k,89.779,10.221,98.501,1.499,54.14,480,1.000,bicubic,+4.193,+0.755,+9 +xcit_small_24_p8_384_dist,89.739,10.261,98.422,1.578,47.63,384,1.000,bicubic,+4.185,+0.850,+9 +volo_d1_384,89.698,10.302,98.294,1.706,26.78,384,1.000,bicubic,+4.448,+1.080,+20 +deit3_large_patch16_384,89.681,10.319,98.392,1.608,304.76,384,1.000,bicubic,+3.875,+0.796,0 +xcit_large_24_p16_384_dist,89.662,10.338,98.401,1.599,189.10,384,1.000,bicubic,+3.910,+0.863,+1 +tf_efficientnet_b5_ns,89.649,10.351,98.482,1.518,30.39,456,0.934,bicubic,+3.561,+0.730,-13 +convnext_base_in22ft1k,89.628,10.372,98.537,1.462,88.59,224,0.875,bicubic,+3.804,+0.671,-6 +tf_efficientnetv2_xl_in21ft1k,89.589,10.411,98.174,1.825,208.12,512,1.000,bicubic,+3.169,+0.306,-21 +tf_efficientnet_b8_ap,89.581,10.419,98.303,1.697,87.41,672,0.954,bicubic,+4.209,+1.009,+11 +volo_d3_224,89.557,10.443,98.375,1.625,86.33,224,0.960,bicubic,+4.145,+1.095,+8 +dm_nfnet_f4,89.557,10.443,98.303,1.697,316.07,512,0.951,bicubic,+3.843,+0.783,-2 +xcit_large_24_p8_224_dist,89.517,10.483,98.224,1.776,188.93,224,1.000,bicubic,+4.119,+0.814,+7 +xcit_small_12_p8_384_dist,89.515,10.485,98.303,1.697,26.21,384,1.000,bicubic,+4.435,+1.023,+18 +cait_s24_384,89.506,10.494,98.367,1.633,47.06,384,1.000,bicubic,+4.456,+1.019,+21 +dm_nfnet_f3,89.485,10.515,98.399,1.601,254.92,416,0.940,bicubic,+3.963,+0.937,-3 +xcit_medium_24_p16_384_dist,89.474,10.526,98.296,1.704,84.40,384,1.000,bicubic,+4.052,+0.890,0 +dm_nfnet_f5,89.463,10.537,98.324,1.676,377.21,544,0.954,bicubic,+3.647,+0.838,-14 +deit3_base_patch16_224_in21ft1k,89.451,10.549,98.557,1.443,86.59,224,1.000,bicubic,+3.735,+0.813,-10 +deit_base_distilled_patch16_384,89.429,10.571,98.439,1.561,87.63,384,1.000,bicubic,+4.007,+1.107,-2 +tf_efficientnet_b7_ap,89.429,10.571,98.345,1.655,66.35,600,0.949,bicubic,+4.309,+1.093,+8 +vit_base_patch8_224,89.427,10.573,98.486,1.514,86.58,224,0.900,bicubic,+3.637,+0.694,-16 +beit_base_patch16_224,89.410,10.590,98.525,1.475,86.53,224,0.900,bicubic,+4.182,+0.869,+2 +regnetz_e8,89.380,10.620,98.459,1.542,57.70,320,1.000,bicubic,+4.350,+1.195,+14 +tf_efficientnetv2_l,89.374,10.626,98.271,1.729,118.52,480,1.000,bicubic,+3.886,+0.899,-11 +deit3_small_patch16_384_in21ft1k,89.367,10.633,98.382,1.618,22.21,384,1.000,bicubic,+4.543,+0.898,+20 +tf_efficientnet_b8,89.352,10.648,98.303,1.697,87.41,672,0.954,bicubic,+3.984,+0.911,-5 +tf_efficientnet_b6_ap,89.344,10.656,98.281,1.719,43.04,528,0.942,bicubic,+4.558,+1.143,+20 +volo_d2_224,89.327,10.673,98.209,1.791,58.68,224,0.960,bicubic,+4.133,+1.021,-2 +vit_large_patch16_224,89.314,10.686,98.394,1.606,304.33,224,0.900,bicubic,+3.470,+0.572,-29 +tf_efficientnet_b4_ns,89.303,10.697,98.347,1.653,19.34,380,0.922,bicubic,+4.143,+0.877,-3 +xcit_small_24_p16_384_dist,89.295,10.705,98.328,1.672,47.67,384,1.000,bicubic,+4.207,+1.020,-1 +xcit_medium_24_p8_224_dist,89.290,10.710,98.192,1.808,84.32,224,1.000,bicubic,+4.220,+0.912,+1 +tf_efficientnetv2_m,89.286,10.714,98.236,1.764,54.14,480,1.000,bicubic,+4.250,+0.958,+3 +deit3_huge_patch14_224,89.212,10.789,98.166,1.834,632.13,224,0.900,bicubic,+4.006,+0.808,-9 +xcit_small_24_p8_224_dist,89.201,10.799,98.245,1.755,47.63,224,1.000,bicubic,+4.325,+1.057,+9 +xcit_small_12_p16_384_dist,89.194,10.806,98.219,1.781,26.25,384,1.000,bicubic,+4.486,+1.103,+14 +swin_base_patch4_window7_224,89.147,10.852,98.424,1.576,87.77,224,0.900,bicubic,+3.897,+0.862,-15 +eca_nfnet_l2,89.141,10.859,98.315,1.685,56.72,384,1.000,bicubic,+4.445,+1.051,+13 +cait_xs24_384,89.139,10.861,98.290,1.710,26.67,384,1.000,bicubic,+5.075,+1.400,+46 +convnext_small_in22ft1k,89.122,10.878,98.322,1.678,50.22,224,0.875,bicubic,+4.554,+0.926,+15 +ig_resnext101_32x48d,89.115,10.885,98.132,1.868,828.41,224,0.875,bilinear,+3.679,+0.556,-26 +ig_resnext101_32x32d,89.109,10.891,98.183,1.817,468.53,224,0.875,bilinear,+4.009,+0.749,-13 +tf_efficientnet_b7,89.083,10.917,98.185,1.815,66.35,600,0.949,bicubic,+4.149,+0.979,-2 +ecaresnet269d,89.069,10.931,98.232,1.768,102.09,352,1.000,bicubic,+4.095,+1.006,-4 +xcit_large_24_p16_224_dist,89.041,10.959,98.061,1.939,189.10,224,1.000,bicubic,+4.121,+0.929,-3 +resmlp_big_24_224_in22ft1k,89.011,10.989,98.215,1.785,129.14,224,0.875,bicubic,+4.613,+1.097,+18 +dm_nfnet_f2,89.011,10.989,98.189,1.810,193.78,352,0.920,bicubic,+3.945,+0.947,-13 +xcit_small_12_p8_224_dist,89.002,10.998,98.078,1.922,26.21,224,1.000,bicubic,+4.772,+1.204,+28 efficientnetv2_rw_m,88.990,11.011,98.213,1.787,53.24,416,1.000,bicubic,+4.178,+1.067,-3 -regnetz_040h,88.953,11.047,98.202,1.798,28.94,320,1.000,bicubic,+4.457,+1.196,+5 -tf_efficientnet_b5_ap,88.942,11.057,98.164,1.836,30.39,456,0.934,bicubic,+4.686,+1.188,+17 -dm_nfnet_f1,88.925,11.075,98.115,1.885,132.63,320,0.910,bicubic,+4.301,+1.015,-1 -volo_d1_224,88.908,11.092,98.034,1.966,26.63,224,0.960,bicubic,+4.746,+1.258,+21 -tf_efficientnetv2_s_in21ft1k,88.902,11.098,98.279,1.721,21.46,384,1.000,bicubic,+4.604,+1.025,+9 -vit_base_patch16_224,88.864,11.136,98.230,1.770,86.57,224,0.900,bicubic,+4.335,+0.936,-3 -regnetz_d8,88.857,11.143,98.189,1.810,23.37,320,1.000,bicubic,+4.805,+1.195,+23 -resnetrs420,88.842,11.158,98.034,1.966,191.89,416,1.000,bicubic,+3.832,+0.910,-18 -regnetz_d8_evos,88.840,11.160,98.132,1.868,23.46,320,0.950,bicubic,+4.786,+1.136,+20 -resnetrs270,88.834,11.166,98.136,1.864,129.86,352,1.000,bicubic,+4.398,+1.166,-1 -ig_resnext101_32x16d,88.825,11.175,98.049,1.951,194.03,224,0.875,bilinear,+4.655,+0.851,+13 -vit_small_r26_s32_384,88.819,11.181,98.339,1.661,36.47,384,1.000,bicubic,+4.777,+1.011,+20 -vit_base_r50_s16_384,88.806,11.194,98.232,1.768,98.95,384,1.000,bicubic,+3.836,+0.942,-21 -xcit_medium_24_p16_224_dist,88.799,11.200,98.038,1.962,84.40,224,1.000,bicubic,+4.525,+1.098,+3 -seresnet152d,88.793,11.207,98.172,1.828,66.84,320,1.000,bicubic,+4.433,+1.132,-2 -swsl_resnext101_32x8d,88.778,11.222,98.149,1.851,88.79,224,0.875,bilinear,+4.488,+0.969,0 -xcit_tiny_24_p8_384_dist,88.776,11.224,98.162,1.838,12.11,384,1.000,bicubic,+5.034,+1.452,+33 -resnetrs200,88.763,11.237,98.113,1.887,93.21,320,1.000,bicubic,+4.325,+1.033,-10 -tf_efficientnet_b6,88.761,11.239,98.064,1.937,43.04,528,0.942,bicubic,+4.651,+1.175,+8 -resnetrs350,88.757,11.243,98.031,1.968,163.96,384,1.000,bicubic,+4.039,+1.043,-21 -vit_base_patch16_224_miil,88.742,11.258,98.029,1.971,86.54,224,0.875,bilinear,+4.470,+1.227,-3 -regnetz_040,88.731,11.269,98.091,1.909,27.12,320,1.000,bicubic,+4.497,+1.159,-1 -resnetv2_152x2_bitm,88.729,11.271,98.309,1.691,236.34,448,1.000,bilinear,+4.223,+0.875,-18 -regnety_160,88.699,11.301,98.068,1.932,83.59,288,1.000,bicubic,+5.009,+1.292,+31 -pit_b_distilled_224,88.674,11.326,98.089,1.911,74.79,224,0.900,bicubic,+4.534,+1.233,+1 -vit_small_patch16_384,88.656,11.344,98.232,1.768,22.20,384,1.000,bicubic,+4.852,+1.130,+22 -regnetz_d32,88.652,11.348,98.083,1.917,27.58,320,0.950,bicubic,+4.630,+1.217,+6 -regnety_080,88.635,11.365,97.970,2.030,39.18,288,1.000,bicubic,+4.709,+1.082,+10 -eca_nfnet_l1,88.624,11.376,98.132,1.868,41.41,320,1.000,bicubic,+4.612,+1.104,+6 -convnext_large,88.573,11.427,97.854,2.146,197.77,224,0.875,bicubic,+4.281,+0.960,-15 -resnetv2_152x4_bitm,88.554,11.446,98.194,1.806,936.53,480,1.000,bilinear,+3.638,+0.752,-36 -resnet200d,88.543,11.457,97.959,2.041,64.69,320,1.000,bicubic,+4.579,+1.135,+4 -xcit_small_24_p16_224_dist,88.541,11.459,97.999,2.001,47.67,224,1.000,bicubic,+4.673,+1.275,+7 -resnest269e,88.522,11.478,98.027,1.973,110.93,416,0.928,bicubic,+4.002,+1.041,-30 -seresnext101_32x8d,88.505,11.495,97.888,2.112,93.57,288,1.000,bicubic,+4.301,+1.012,-13 -efficientnetv2_rw_s,88.473,11.527,97.972,2.028,23.94,384,1.000,bicubic,+4.663,+1.250,+11 -crossvit_18_dagger_408,88.471,11.529,97.893,2.107,44.61,408,1.000,bicubic,+4.277,+1.075,-14 -resnetv2_101x3_bitm,88.464,11.536,98.157,1.843,387.93,448,1.000,bilinear,+4.022,+0.775,-31 -cait_s24_224,88.451,11.549,97.957,2.043,46.92,224,1.000,bicubic,+4.993,+1.393,+21 -resnetv2_50x3_bitm,88.447,11.553,98.198,1.802,217.32,448,1.000,bilinear,+4.433,+1.074,-6 -resmlp_big_24_distilled_224,88.443,11.557,97.940,2.060,129.14,224,0.875,bicubic,+4.855,+1.292,+17 -regnetv_064,88.434,11.566,98.066,1.934,30.58,288,1.000,bicubic,+4.720,+1.452,+12 -resnest200e,88.432,11.568,98.042,1.958,70.20,320,0.909,bicubic,+4.604,+1.150,+2 -tf_efficientnet_b3_ns,88.426,11.574,98.029,1.971,12.23,300,0.904,bicubic,+4.378,+1.121,-13 -vit_large_r50_s32_224,88.417,11.583,98.087,1.913,328.99,224,0.900,bicubic,+3.993,+0.921,-35 -tf_efficientnetv2_s,88.396,11.604,97.927,2.073,21.46,384,1.000,bicubic,+4.510,+1.231,-7 -regnetz_c16_evos,88.379,11.621,98.042,1.958,13.49,320,0.950,bicubic,+5.747,+1.566,+49 -efficientnet_b4,88.368,11.632,97.959,2.041,19.34,384,1.000,bicubic,+4.944,+1.363,+13 -resnet152d,88.355,11.645,97.938,2.062,60.21,320,1.000,bicubic,+4.677,+1.200,+8 -tf_efficientnet_b4_ap,88.349,11.651,97.891,2.109,19.34,380,0.922,bicubic,+5.097,+1.497,+18 -convnext_base,88.345,11.655,97.784,2.216,88.59,224,0.875,bicubic,+4.507,+1.034,-9 -tf_efficientnet_b5,88.321,11.679,97.914,2.086,30.39,456,0.934,bicubic,+4.509,+1.166,-6 -regnety_064,88.319,11.681,97.865,2.135,30.58,288,1.000,bicubic,+4.599,+1.143,-1 -crossvit_15_dagger_408,88.311,11.690,97.874,2.127,28.50,408,1.000,bicubic,+4.475,+1.090,-10 -resnetrs152,88.253,11.747,97.735,2.265,86.62,320,1.000,bicubic,+4.539,+0.989,-2 -xcit_small_12_p16_224_dist,88.251,11.749,97.848,2.152,26.25,224,1.000,bicubic,+4.901,+1.434,+9 -regnetv_040,88.219,11.781,97.974,2.026,20.64,288,1.000,bicubic,+5.019,+1.312,+14 -deit_base_distilled_patch16_224,88.214,11.786,97.918,2.082,87.34,224,0.900,bicubic,+4.822,+1.432,+4 -xception65p,88.185,11.815,97.790,2.210,39.82,299,0.940,bicubic,+5.059,+1.312,+18 -xcit_large_24_p8_224,88.159,11.841,97.387,2.613,188.93,224,1.000,bicubic,+3.765,+0.731,-48 -xcit_tiny_24_p16_384_dist,88.159,11.841,97.946,2.054,12.12,384,1.000,bicubic,+5.587,+1.658,+40 -resnetv2_152x2_bit_teacher_384,88.155,11.845,98.051,1.949,236.34,384,1.000,bicubic,+4.311,+0.933,-22 -ig_resnext101_32x8d,88.155,11.845,97.856,2.144,88.79,224,0.875,bilinear,+5.455,+1.226,+32 -cait_xxs36_384,88.142,11.858,97.906,2.095,17.37,384,1.000,bicubic,+5.948,+1.761,+61 -dm_nfnet_f0,88.125,11.875,97.854,2.146,71.49,256,0.900,bicubic,+4.739,+1.280,-2 -xcit_tiny_12_p8_384_dist,88.106,11.894,97.920,2.080,6.71,384,1.000,bicubic,+5.712,+1.700,+44 -swsl_resnext101_32x4d,88.095,11.905,97.972,2.028,44.18,224,0.875,bilinear,+4.859,+1.208,+2 -xception65,88.073,11.927,97.752,2.248,39.92,299,0.940,bicubic,+4.893,+1.160,+4 -convnext_small,88.052,11.948,97.788,2.212,50.22,224,0.875,bicubic,+4.902,+1.356,+4 -swin_s3_base_224,88.050,11.950,97.656,2.344,71.13,224,0.900,bicubic,+4.118,+0.996,-33 -xcit_tiny_24_p8_224_dist,88.044,11.956,97.812,2.188,12.11,224,1.000,bicubic,+5.480,+1.642,+31 -eca_nfnet_l0,87.975,12.025,97.874,2.127,24.14,288,1.000,bicubic,+5.399,+1.384,+28 -nfnet_l0,87.971,12.029,97.867,2.133,35.07,288,1.000,bicubic,+5.219,+1.349,+18 -xcit_small_24_p8_224,87.967,12.033,97.581,2.419,47.63,224,1.000,bicubic,+4.129,+0.945,-31 -tf_efficientnet_b4,87.965,12.035,97.739,2.261,19.34,380,0.922,bicubic,+4.941,+1.439,+8 -resnet101d,87.937,12.063,97.908,2.092,44.57,320,1.000,bicubic,+4.915,+1.460,+8 -regnety_032,87.933,12.067,97.891,2.109,19.44,288,1.000,bicubic,+5.207,+1.467,+15 -regnety_040,87.915,12.085,97.884,2.116,20.65,288,1.000,bicubic,+4.879,+1.378,+4 -vit_base_patch32_384,87.909,12.091,98.010,1.990,88.30,384,1.000,bicubic,+4.561,+1.176,-13 -twins_svt_large,87.901,12.099,97.581,2.419,99.27,224,0.900,bicubic,+4.221,+0.987,-24 -twins_pcpvt_large,87.877,12.123,97.859,2.142,60.99,224,0.900,bicubic,+4.743,+1.255,-5 -regnetz_c16,87.858,12.142,97.818,2.182,13.46,320,0.940,bicubic,+5.342,+1.458,+23 -swin_s3_small_224,87.856,12.144,97.434,2.566,49.74,224,0.900,bicubic,+4.088,+0.982,-34 -deit_base_patch16_384,87.841,12.159,97.508,2.492,86.86,384,1.000,bicubic,+4.735,+1.140,-5 -xcit_small_12_p8_224,87.826,12.174,97.566,2.434,26.21,224,1.000,bicubic,+4.482,+1.086,-18 -tresnet_xl_448,87.796,12.204,97.457,2.543,78.44,448,0.875,bilinear,+4.742,+1.285,-5 -resnetv2_50x1_bit_distilled,87.792,12.208,97.903,2.097,25.55,224,0.875,bicubic,+4.970,+1.375,+1 -tresnet_m,87.738,12.262,97.521,2.479,31.39,224,0.875,bilinear,+4.668,+1.401,-8 -twins_pcpvt_base,87.734,12.266,97.730,2.270,43.83,224,0.900,bicubic,+5.026,+1.380,+4 -gc_efficientnetv2_rw_t,87.717,12.283,97.807,2.193,13.68,288,1.000,bicubic,+5.251,+1.511,+16 -resnetv2_101x1_bitm,87.683,12.317,97.938,2.062,44.54,448,1.000,bilinear,+5.347,+1.421,+24 -swin_small_patch4_window7_224,87.668,12.332,97.566,2.434,49.61,224,0.900,bicubic,+4.452,+1.242,-22 -efficientnetv2_rw_t,87.644,12.356,97.688,2.312,13.65,288,1.000,bicubic,+5.300,+1.492,+21 -twins_svt_base,87.642,12.358,97.523,2.477,56.07,224,0.900,bicubic,+4.504,+1.103,-19 -pnasnet5large,87.640,12.360,97.487,2.513,86.06,331,0.911,bicubic,+4.850,+1.447,-5 -jx_nest_base,87.608,12.392,97.515,2.485,67.72,224,0.875,bicubic,+4.052,+1.153,-37 -swsl_resnext101_32x16d,87.608,12.392,97.816,2.184,194.03,224,0.875,bilinear,+4.258,+0.972,-33 -xcit_medium_24_p8_224,87.604,12.396,97.201,2.799,84.32,224,1.000,bicubic,+3.868,+0.807,-47 -swsl_resnext50_32x4d,87.595,12.405,97.654,2.346,25.03,224,0.875,bilinear,+5.419,+1.422,+27 -levit_384,87.557,12.443,97.549,2.451,39.13,224,0.900,bicubic,+4.969,+1.527,-2 -tf_efficientnet_b2_ns,87.555,12.445,97.628,2.372,9.11,260,0.890,bicubic,+5.175,+1.380,+10 -ecaresnet50t,87.542,12.458,97.645,2.355,25.57,320,0.950,bicubic,+5.194,+1.507,+11 -jx_nest_small,87.493,12.507,97.519,2.481,38.35,224,0.875,bicubic,+4.375,+1.189,-25 -resnetv2_152x2_bit_teacher,87.493,12.507,97.814,2.186,236.34,224,0.875,bicubic,+4.621,+1.244,-17 -resnet152,87.454,12.546,97.402,2.598,60.19,224,0.950,bicubic,+4.634,+1.272,-16 -fbnetv3_g,87.452,12.548,97.549,2.451,16.62,288,0.950,bilinear,+5.406,+1.485,+28 -resnext101_64x4d,87.439,12.561,97.442,2.558,83.46,288,1.000,bicubic,+4.299,+1.072,-34 -resnet61q,87.439,12.561,97.600,2.400,36.85,288,1.000,bicubic,+4.913,+1.466,-4 -efficientnet_b3,87.433,12.567,97.681,2.319,12.23,320,1.000,bicubic,+5.193,+1.567,+13 -cait_xxs24_384,87.414,12.586,97.617,2.383,12.03,384,1.000,bicubic,+6.448,+1.971,+81 -resnet51q,87.401,12.599,97.585,2.415,35.70,288,1.000,bilinear,+5.039,+1.405,+1 -coat_lite_small,87.380,12.620,97.370,2.630,19.84,224,0.900,bicubic,+5.076,+1.522,+6 -xcit_tiny_24_p8_224,87.377,12.623,97.626,2.374,12.11,224,1.000,bicubic,+5.486,+1.650,+30 -tresnet_l_448,87.375,12.625,97.487,2.513,55.99,448,0.875,bilinear,+5.107,+1.505,+7 -nasnetalarge,87.350,12.650,97.417,2.583,88.75,331,0.911,bicubic,+4.724,+1.371,-18 -crossvit_18_dagger_240,87.346,12.655,97.455,2.545,44.27,240,0.875,bicubic,+4.826,+1.385,-12 -resnetv2_101,87.318,12.682,97.325,2.675,44.54,224,0.950,bicubic,+5.276,+1.461,+18 -crossvit_18_240,87.313,12.687,97.485,2.515,43.27,240,0.875,bicubic,+4.915,+1.427,-10 -convnext_tiny,87.313,12.687,97.447,2.554,28.59,224,0.875,bicubic,+5.249,+1.594,+13 -ecaresnet101d,87.290,12.710,97.555,2.445,44.57,224,0.875,bicubic,+5.118,+1.509,+7 -resnest101e,87.286,12.714,97.560,2.440,48.28,256,0.875,bilinear,+4.396,+1.242,-35 -pit_s_distilled_224,87.273,12.727,97.500,2.500,24.04,224,0.900,bicubic,+5.279,+1.702,+15 -resnetv2_50d_gn,87.262,12.738,97.513,2.487,25.57,288,0.950,bicubic,+5.444,+1.591,+24 -resnetrs101,87.249,12.751,97.455,2.545,63.62,288,0.940,bicubic,+4.961,+1.445,-5 -poolformer_m48,87.239,12.761,97.308,2.692,73.47,224,0.950,bicubic,+4.777,+1.350,-18 -tresnet_xl,87.228,12.772,97.400,2.600,78.44,224,0.875,bilinear,+5.170,+1.463,+6 -mixer_b16_224_miil,87.228,12.772,97.410,2.590,59.88,224,0.875,bilinear,+4.920,+1.692,-9 -xcit_tiny_12_p8_224_dist,87.222,12.778,97.447,2.554,6.71,224,1.000,bicubic,+6.014,+1.847,+48 -xcit_tiny_12_p16_384_dist,87.205,12.795,97.466,2.534,6.72,384,1.000,bicubic,+6.261,+2.054,+64 -convit_base,87.200,12.800,97.288,2.712,86.54,224,0.875,bicubic,+4.914,+1.350,-10 -resnetv2_50d_evos,87.196,12.804,97.359,2.641,25.59,288,0.950,bicubic,+5.216,+1.449,+7 -tf_efficientnet_b3_ap,87.192,12.808,97.380,2.620,12.23,300,0.904,bicubic,+5.366,+1.758,+14 -visformer_small,87.185,12.815,97.320,2.679,40.22,224,0.900,bicubic,+5.079,+1.447,-3 -crossvit_15_dagger_240,87.172,12.828,97.438,2.562,28.21,240,0.875,bicubic,+4.843,+1.480,-18 -xcit_small_24_p16_224,87.132,12.868,97.261,2.739,47.67,224,1.000,bicubic,+4.552,+1.255,-37 -swin_s3_tiny_224,87.132,12.868,97.303,2.697,28.33,224,0.900,bicubic,+5.006,+1.353,-7 -resnet101,87.083,12.917,97.265,2.735,44.55,224,0.950,bicubic,+5.151,+1.495,+5 -crossvit_15_240,87.053,12.947,97.425,2.575,27.53,240,0.875,bicubic,+5.511,+1.735,+17 -xception41p,87.051,12.949,97.203,2.797,26.91,299,0.940,bicubic,+5.091,+1.409,+2 -convit_small,87.049,12.951,97.346,2.654,27.78,224,0.875,bicubic,+5.629,+1.606,+22 -tf_efficientnetv2_b3,87.027,12.973,97.303,2.697,14.36,300,0.904,bicubic,+5.061,+1.523,-1 -regnetz_b16,87.014,12.986,97.427,2.573,9.72,288,0.940,bicubic,+6.300,+1.949,+62 -xcit_small_12_p16_224,87.012,12.988,97.248,2.752,26.25,224,1.000,bicubic,+5.036,+1.430,-4 -jx_nest_tiny,87.008,12.992,97.378,2.622,17.06,224,0.875,bicubic,+5.588,+1.760,+19 -deit_small_distilled_patch16_224,87.002,12.998,97.314,2.686,22.44,224,0.900,bicubic,+5.794,+1.940,+30 -resmlp_36_distilled_224,86.989,13.011,97.276,2.724,44.69,224,0.875,bicubic,+5.835,+1.788,+33 -xcit_large_24_p16_224,86.957,13.043,96.919,3.081,189.10,224,1.000,bicubic,+4.063,+1.037,-62 -poolformer_m36,86.948,13.052,97.148,2.852,56.17,224,0.950,bicubic,+4.836,+1.458,-19 -xcit_medium_24_p16_224,86.938,13.062,97.098,2.902,84.40,224,1.000,bicubic,+4.300,+1.124,-54 -convnext_tiny_hnf,86.921,13.079,97.280,2.720,28.59,224,0.950,bicubic,+4.699,+1.414,-27 -tnt_s_patch16_224,86.906,13.094,97.365,2.635,23.76,224,0.900,bicubic,+5.386,+1.621,+6 -ssl_resnext101_32x16d,86.867,13.133,97.519,2.481,194.03,224,0.875,bilinear,+5.013,+1.423,-7 -vit_small_patch16_224,86.865,13.135,97.609,2.391,22.05,224,0.900,bicubic,+5.469,+1.477,+12 -vit_small_r26_s32_224,86.854,13.146,97.530,2.470,36.43,224,0.900,bicubic,+4.998,+1.510,-10 -convmixer_1536_20,86.850,13.150,97.348,2.652,51.63,224,0.960,bicubic,+5.484,+1.734,+13 -rexnet_200,86.844,13.156,97.276,2.724,16.37,224,0.875,bicubic,+5.214,+1.608,-4 -tf_efficientnet_b3,86.835,13.165,97.297,2.703,12.23,300,0.904,bicubic,+5.199,+1.579,-6 -deit_base_patch16_224,86.829,13.171,97.049,2.951,86.57,224,0.900,bicubic,+4.833,+1.317,-22 -swsl_resnet50,86.825,13.175,97.496,2.504,25.56,224,0.875,bilinear,+5.650,+1.518,+18 -tresnet_m_448,86.814,13.186,97.218,2.782,31.39,448,0.875,bilinear,+5.110,+1.646,-12 -tf_efficientnet_lite4,86.803,13.197,97.265,2.735,13.01,380,0.920,bilinear,+5.267,+1.597,-5 -ssl_resnext101_32x8d,86.801,13.199,97.472,2.528,88.79,224,0.875,bilinear,+5.193,+1.430,-9 -coat_mini,86.790,13.210,97.160,2.840,10.34,224,0.900,bicubic,+5.524,+1.766,+9 -tresnet_l,86.765,13.235,97.269,2.731,55.99,224,0.875,bilinear,+5.273,+1.645,-4 -twins_svt_small,86.758,13.242,97.177,2.823,24.06,224,0.900,bicubic,+5.078,+1.507,-16 -crossvit_base_240,86.735,13.265,97.122,2.878,105.03,240,0.875,bicubic,+4.519,+1.288,-42 -levit_256,86.728,13.272,97.256,2.744,18.89,224,0.900,bicubic,+5.222,+1.764,-9 -seresnext50_32x4d,86.696,13.304,97.218,2.782,27.56,224,0.875,bicubic,+5.438,+1.588,+5 -crossvit_small_240,86.692,13.308,97.273,2.727,26.86,240,0.875,bicubic,+5.674,+1.817,+18 -halo2botnet50ts_256,86.688,13.312,97.096,2.904,22.64,256,0.950,bicubic,+4.628,+1.454,-38 -pit_b_224,86.688,13.312,96.898,3.102,73.76,224,0.900,bicubic,+4.242,+1.188,-63 -tf_efficientnet_b1_ns,86.666,13.334,97.378,2.622,7.79,240,0.882,bicubic,+5.278,+1.642,-6 -swin_tiny_patch4_window7_224,86.662,13.338,97.199,2.801,28.29,224,0.900,bicubic,+5.288,+1.655,-6 -wide_resnet50_2,86.645,13.355,97.207,2.793,68.88,224,0.875,bicubic,+5.193,+1.677,-13 -gernet_l,86.641,13.359,97.190,2.810,31.08,256,0.875,bilinear,+5.297,+1.658,-6 -poolformer_s36,86.639,13.361,97.160,2.840,30.86,224,0.900,bicubic,+5.221,+1.710,-12 -efficientnet_el,86.632,13.368,97.180,2.820,10.59,300,0.904,bicubic,+5.322,+1.650,-7 -twins_pcpvt_small,86.624,13.376,97.340,2.660,24.11,224,0.900,bicubic,+5.534,+1.700,+6 -resmlp_24_distilled_224,86.620,13.380,97.141,2.859,30.02,224,0.875,bicubic,+5.856,+1.917,+22 -nf_resnet50,86.605,13.395,97.291,2.709,25.56,288,0.940,bicubic,+5.951,+1.957,+25 -resnest50d_4s2x40d,86.588,13.412,97.269,2.731,30.42,224,0.875,bicubic,+5.478,+1.705,0 -efficientnet_b3_pruned,86.581,13.419,97.190,2.810,9.86,300,0.904,bicubic,+5.723,+1.946,+16 -sebotnet33ts_256,86.566,13.434,96.791,3.209,13.70,256,0.940,bicubic,+5.410,+1.621,-5 -sehalonet33ts,86.564,13.436,97.007,2.993,13.69,256,0.940,bicubic,+5.600,+1.735,+8 -repvgg_b3,86.562,13.438,97.141,2.859,123.09,224,0.875,bilinear,+6.066,+1.877,+26 -xcit_tiny_24_p16_224_dist,86.534,13.466,97.220,2.780,12.12,224,1.000,bicubic,+6.088,+2.004,+31 -halonet50ts,86.500,13.500,97.152,2.848,22.73,256,0.940,bicubic,+4.840,+1.540,-37 -ssl_resnext101_32x4d,86.479,13.521,97.468,2.532,44.18,224,0.875,bilinear,+5.555,+1.742,+7 -gcresnet50t,86.472,13.528,97.141,2.859,25.90,256,0.900,bicubic,+5.530,+1.687,+5 -ecaresnet50d,86.470,13.530,97.186,2.814,25.58,224,0.875,bicubic,+5.870,+1.866,+18 -gluon_resnet152_v1s,86.470,13.530,97.109,2.891,60.32,224,0.875,bicubic,+5.454,+1.697,-3 -haloregnetz_b,86.464,13.536,96.943,3.057,11.68,224,0.940,bicubic,+5.414,+1.747,-7 -resnest50d_1s4x24d,86.445,13.556,97.150,2.850,25.68,224,0.875,bicubic,+5.455,+1.826,-4 -resnetv2_50x1_bitm,86.442,13.558,97.600,2.400,25.55,448,1.000,bilinear,+6.100,+1.920,+30 -repvgg_b3g4,86.361,13.639,97.054,2.946,83.83,224,0.875,bilinear,+6.149,+1.948,+41 -lamhalobotnet50ts_256,86.355,13.645,97.058,2.942,22.57,256,0.950,bicubic,+4.809,+1.556,-42 -legacy_senet154,86.340,13.660,96.923,3.077,115.09,224,0.875,bilinear,+5.030,+1.427,-26 -cait_xxs36_224,86.338,13.662,97.111,2.889,17.30,224,1.000,bicubic,+6.590,+2.245,+64 -resnext50_32x4d,86.334,13.666,96.966,3.034,25.03,224,0.950,bicubic,+5.225,+1.640,-17 -gernet_m,86.331,13.669,97.096,2.904,21.14,224,0.875,bilinear,+5.587,+1.912,+2 -pit_s_224,86.325,13.675,97.047,2.953,23.46,224,0.900,bicubic,+5.225,+1.717,-18 -efficientnet_b2,86.308,13.692,96.990,3.010,9.11,288,1.000,bicubic,+5.694,+1.674,+4 -vit_small_patch32_384,86.308,13.692,97.419,2.581,22.92,384,1.000,bicubic,+5.824,+1.819,+9 -gluon_senet154,86.272,13.729,96.947,3.053,115.09,224,0.875,bicubic,+5.040,+1.599,-30 -resnest50d,86.240,13.761,97.066,2.934,27.48,224,0.875,bilinear,+5.258,+1.686,-15 -convmixer_768_32,86.225,13.775,97.034,2.966,21.11,224,0.960,bicubic,+6.061,+1.962,+33 -ecaresnet101d_pruned,86.210,13.790,97.333,2.667,24.88,224,0.875,bicubic,+5.396,+1.703,-8 -efficientnet_el_pruned,86.192,13.807,97.024,2.976,10.59,300,0.904,bicubic,+5.890,+1.996,+21 -cspdarknet53,86.186,13.814,97.013,2.987,27.64,256,0.887,bilinear,+6.124,+1.929,+36 -inception_v4,86.171,13.829,96.921,3.079,42.68,299,0.875,bicubic,+6.009,+1.955,+30 -rexnet_150,86.156,13.844,97.062,2.938,9.73,224,0.875,bicubic,+5.846,+1.896,+16 -inception_resnet_v2,86.135,13.865,97.043,2.957,55.84,299,0.897,bicubic,+5.675,+1.735,+3 -xcit_tiny_12_p8_224,86.105,13.895,97.081,2.919,6.71,224,1.000,bicubic,+6.415,+2.027,+52 -ssl_resnext50_32x4d,86.088,13.912,97.212,2.788,25.03,224,0.875,bilinear,+5.772,+1.802,+11 -tf_efficientnet_el,86.082,13.918,96.960,3.040,10.59,300,0.904,bicubic,+5.832,+1.838,+17 -gluon_resnet101_v1s,86.056,13.944,97.028,2.972,44.67,224,0.875,bicubic,+5.758,+1.864,+14 -ecaresnetlight,86.047,13.953,97.064,2.936,30.16,224,0.875,bicubic,+5.595,+1.814,-1 -lambda_resnet50ts,86.039,13.961,96.744,3.256,21.54,256,0.950,bicubic,+4.893,+1.642,-38 -poolformer_s24,86.034,13.966,97.030,2.970,21.39,224,0.900,bicubic,+5.721,+1.984,+7 -gluon_seresnext101_32x4d,86.032,13.968,96.977,3.023,48.96,224,0.875,bicubic,+5.126,+1.683,-24 -resnetv2_50,86.022,13.978,96.900,3.100,25.55,224,0.950,bicubic,+5.602,+1.884,-3 -gcresnext50ts,86.009,13.991,96.966,3.034,15.67,256,0.900,bicubic,+5.431,+1.796,-13 -seresnet33ts,86.007,13.993,97.011,2.989,19.78,256,0.900,bicubic,+5.657,+1.905,-1 -resnet50d,85.998,14.002,96.987,3.013,25.58,224,0.875,bicubic,+5.476,+1.825,-14 -ecaresnet26t,85.979,14.021,97.039,2.961,16.01,320,0.950,bicubic,+6.131,+1.953,+32 -tf_efficientnet_b2_ap,85.975,14.025,96.810,3.190,9.11,260,0.890,bicubic,+5.673,+1.594,+2 -gluon_seresnext101_64x4d,85.958,14.042,96.979,3.021,88.23,224,0.875,bicubic,+5.080,+1.681,-30 -vit_base_patch32_224,85.958,14.042,97.126,2.874,88.22,224,0.900,bicubic,+5.236,+1.560,-25 -fbnetv3_d,85.926,14.074,97.026,2.974,10.31,256,0.950,bilinear,+6.244,+2.078,+37 -gluon_resnet152_v1d,85.913,14.087,96.808,3.192,60.21,224,0.875,bicubic,+5.437,+1.604,-17 -vit_large_patch32_384,85.911,14.089,97.370,2.630,306.63,384,1.000,bicubic,+4.405,+1.276,-72 -tf_efficientnetv2_b2,85.900,14.100,96.889,3.111,10.10,260,0.890,bicubic,+5.694,+1.847,+5 -tf_efficientnet_b2,85.898,14.102,96.862,3.139,9.11,260,0.890,bicubic,+5.818,+1.954,+11 -resnet50_gn,85.885,14.115,96.849,3.151,25.56,224,0.940,bicubic,+5.831,+1.901,+12 -vit_base_patch16_224_sam,85.877,14.123,96.695,3.305,86.57,224,0.900,bicubic,+5.635,+1.941,-2 -seresnet50,85.853,14.147,97.007,2.993,28.09,224,0.875,bicubic,+5.589,+1.935,-5 -gluon_resnet101_v1d,85.849,14.151,96.663,3.337,44.57,224,0.875,bicubic,+5.429,+1.589,-18 -repvgg_b2g4,85.847,14.153,96.812,3.188,61.76,224,0.875,bilinear,+6.477,+2.124,+43 -gcresnet33ts,85.806,14.194,96.902,3.098,19.88,256,0.900,bicubic,+5.726,+1.902,+4 -mixnet_xl,85.795,14.205,96.712,3.288,11.90,224,0.875,bicubic,+5.321,+1.778,-26 -ens_adv_inception_resnet_v2,85.778,14.222,96.759,3.241,55.84,299,0.897,bicubic,+5.800,+1.821,+8 -tf_efficientnet_lite3,85.753,14.247,96.889,3.111,8.20,300,0.904,bilinear,+5.933,+1.977,+18 -cspresnext50,85.748,14.252,96.840,3.160,20.57,224,0.875,bilinear,+5.698,+1.894,+4 -ese_vovnet39b,85.744,14.256,96.894,3.107,24.57,224,0.875,bicubic,+6.432,+2.180,+40 -gluon_resnext101_32x4d,85.744,14.256,96.635,3.365,44.18,224,0.875,bicubic,+5.400,+1.709,-22 -legacy_seresnext101_32x4d,85.744,14.256,96.757,3.243,48.96,224,0.875,bilinear,+5.520,+1.747,-11 -eca_resnet33ts,85.738,14.262,96.900,3.100,19.68,256,0.900,bicubic,+5.658,+1.930,-5 -xcit_tiny_24_p16_224,85.736,14.264,96.938,3.062,12.12,224,1.000,bicubic,+6.292,+2.054,+31 -regnety_320,85.723,14.277,96.725,3.275,145.05,224,0.875,bicubic,+4.913,+1.481,-49 -cspresnet50,85.721,14.279,96.799,3.200,21.62,256,0.887,bilinear,+6.139,+2.096,+22 -resnet50,85.719,14.281,96.492,3.508,25.56,224,0.950,bicubic,+5.343,+1.366,-31 -resmlp_big_24_224,85.697,14.303,96.424,3.576,129.14,224,0.875,bicubic,+4.665,+1.404,-66 -xception71,85.695,14.305,96.776,3.224,42.34,299,0.903,bicubic,+5.819,+1.854,+1 -gluon_resnext101_64x4d,85.693,14.307,96.644,3.356,83.46,224,0.875,bicubic,+5.089,+1.652,-47 -efficientnet_em,85.680,14.320,96.938,3.062,6.90,240,0.882,bicubic,+6.430,+2.144,+39 -deit_small_patch16_224,85.678,14.322,96.904,3.096,22.05,224,0.900,bicubic,+5.818,+1.858,-1 -pit_xs_distilled_224,85.652,14.348,96.665,3.335,11.00,224,0.900,bicubic,+6.346,+2.301,+28 -dpn107,85.650,14.350,96.723,3.277,86.92,224,0.875,bicubic,+5.478,+1.817,-20 -efficientnet_b2_pruned,85.642,14.358,96.746,3.254,8.31,260,0.890,bicubic,+5.726,+1.892,-9 -resmlp_36_224,85.618,14.382,96.795,3.205,44.69,224,0.875,bicubic,+5.850,+1.909,+1 -ecaresnet50d_pruned,85.580,14.420,96.936,3.064,19.94,224,0.875,bicubic,+5.872,+2.056,+3 -gluon_resnet152_v1c,85.576,14.425,96.648,3.352,60.21,224,0.875,bicubic,+5.668,+1.800,-10 -levit_192,85.569,14.431,96.742,3.258,10.95,224,0.900,bicubic,+5.737,+1.956,-5 -resnext50d_32x4d,85.561,14.439,96.748,3.252,25.05,224,0.875,bicubic,+5.891,+1.884,+4 -tf_efficientnetv2_b1,85.561,14.439,96.729,3.271,8.14,240,0.882,bicubic,+6.097,+2.005,+12 -regnety_120,85.546,14.454,96.782,3.217,51.82,224,0.875,bicubic,+5.170,+2.166,-45 -fbnetv3_b,85.522,14.478,96.862,3.139,8.60,256,0.950,bilinear,+6.374,+2.116,+33 -regnetx_320,85.516,14.484,96.669,3.331,107.81,224,0.875,bicubic,+5.276,+1.647,-34 -dpn92,85.503,14.497,96.629,3.371,37.67,224,0.875,bicubic,+5.487,+1.805,-21 -nf_regnet_b1,85.503,14.497,96.789,3.211,10.22,288,0.900,bicubic,+6.215,+2.041,+20 -rexnet_130,85.473,14.527,96.684,3.316,7.56,224,0.875,bicubic,+5.973,+2.000,+3 -gluon_resnet152_v1b,85.467,14.533,96.556,3.444,60.19,224,0.875,bicubic,+5.787,+1.818,-5 -resnetrs50,85.460,14.540,96.733,3.267,35.69,224,0.910,bicubic,+5.574,+1.767,-20 -dpn131,85.394,14.606,96.637,3.363,79.25,224,0.875,bicubic,+5.570,+1.929,-15 -regnetx_160,85.388,14.612,96.637,3.363,54.28,224,0.875,bicubic,+5.538,+1.807,-19 -dla102x2,85.375,14.625,96.624,3.376,41.28,224,0.875,bilinear,+5.929,+1.992,+2 -gmlp_s16_224,85.349,14.651,96.646,3.354,19.42,224,0.875,bicubic,+5.709,+2.022,-7 -botnet26t_256,85.336,14.664,96.629,3.371,12.49,256,0.950,bicubic,+6.084,+2.101,+15 -gluon_seresnext50_32x4d,85.336,14.664,96.674,3.326,27.56,224,0.875,bicubic,+5.422,+1.842,-28 -skresnext50_32x4d,85.317,14.683,96.394,3.606,27.48,224,0.875,bicubic,+5.165,+1.750,-39 -dpn98,85.309,14.691,96.471,3.529,61.57,224,0.875,bicubic,+5.663,+1.875,-12 -gluon_resnet101_v1c,85.302,14.698,96.407,3.593,44.57,224,0.875,bicubic,+5.768,+1.827,-9 -lambda_resnet26t,85.300,14.700,96.727,3.273,10.96,256,0.940,bicubic,+6.202,+2.139,+19 -dpn68b,85.291,14.709,96.464,3.536,12.61,224,0.875,bicubic,+6.072,+2.046,+12 -resnetblur50,85.289,14.711,96.520,3.480,25.56,224,0.875,bicubic,+5.985,+1.886,+2 -resmlp_24_224,85.268,14.732,96.494,3.506,30.02,224,0.875,bicubic,+5.886,+1.948,-6 -coat_lite_mini,85.253,14.747,96.678,3.322,11.01,224,0.900,bicubic,+6.157,+2.074,+16 -cait_xxs24_224,85.228,14.773,96.716,3.284,11.96,224,1.000,bicubic,+6.844,+2.406,+50 -resnet33ts,85.225,14.775,96.629,3.371,19.68,256,0.900,bicubic,+6.015,+2.057,+8 -xcit_tiny_12_p16_224_dist,85.206,14.794,96.597,3.403,6.72,224,1.000,bicubic,+6.630,+2.401,+34 -halonet26t,85.204,14.796,96.462,3.538,12.48,256,0.950,bicubic,+6.088,+2.152,+10 -resnext101_32x8d,85.195,14.805,96.451,3.549,88.79,224,0.875,bilinear,+5.879,+1.933,-9 -gluon_inception_v3,85.183,14.817,96.526,3.474,23.83,299,0.875,bicubic,+6.379,+2.156,+23 -resnet32ts,85.163,14.837,96.624,3.376,17.96,256,0.900,bicubic,+6.151,+2.266,+14 -hrnet_w48,85.153,14.847,96.492,3.508,77.47,224,0.875,bilinear,+5.851,+1.980,-6 -gluon_xception65,85.151,14.849,96.597,3.403,39.92,299,0.903,bicubic,+5.435,+1.737,-33 -gluon_resnet101_v1b,85.144,14.856,96.368,3.632,44.55,224,0.875,bicubic,+5.842,+1.848,-9 -tf_efficientnet_b1_ap,85.131,14.869,96.402,3.598,7.79,240,0.882,bicubic,+5.851,+2.098,-7 -eca_halonext26ts,85.129,14.871,96.584,3.416,10.76,256,0.940,bicubic,+5.639,+1.986,-24 -regnetx_120,85.127,14.873,96.473,3.527,46.11,224,0.875,bicubic,+5.535,+1.739,-29 -eca_botnext26ts_256,85.123,14.877,96.511,3.489,10.59,256,0.950,bicubic,+5.849,+1.895,-9 -xception,85.117,14.883,96.471,3.529,22.86,299,0.897,bicubic,+6.067,+2.079,+5 -hrnet_w64,85.112,14.888,96.744,3.256,128.06,224,0.875,bilinear,+5.640,+2.092,-27 -ssl_resnet50,85.102,14.899,96.864,3.136,25.56,224,0.875,bilinear,+5.876,+2.028,-9 -lambda_resnet26rpt_256,85.097,14.903,96.562,3.438,10.99,256,0.940,bicubic,+6.129,+2.135,+6 -res2net101_26w_4s,85.093,14.907,96.383,3.617,45.21,224,0.875,bilinear,+5.897,+1.947,-7 -tf_efficientnet_cc_b1_8e,85.065,14.935,96.422,3.578,39.72,240,0.882,bicubic,+5.759,+2.050,-21 -xcit_nano_12_p8_384_dist,85.020,14.980,96.631,3.369,3.05,384,1.000,bicubic,+7.202,+2.587,+61 -gluon_resnext50_32x4d,85.010,14.990,96.428,3.572,25.03,224,0.875,bicubic,+5.646,+2.002,-27 -resnest26d,85.010,14.990,96.639,3.361,17.07,224,0.875,bilinear,+6.534,+2.347,+20 -tf_efficientnet_b0_ns,84.986,15.014,96.503,3.497,5.29,224,0.875,bicubic,+6.328,+2.125,+11 -coat_tiny,84.978,15.022,96.411,3.589,5.50,224,0.900,bicubic,+6.548,+2.371,+23 -dla169,84.920,15.080,96.533,3.467,53.39,224,0.875,bilinear,+6.228,+2.193,+8 -tf_efficientnet_b1,84.914,15.086,96.364,3.636,7.79,240,0.882,bicubic,+6.086,+2.166,+1 -legacy_seresnext50_32x4d,84.897,15.103,96.430,3.570,27.56,224,0.875,bilinear,+5.829,+1.996,-10 -hrnet_w44,84.884,15.116,96.437,3.563,67.06,224,0.875,bilinear,+5.984,+2.063,-3 -regnetx_080,84.867,15.133,96.432,3.568,39.57,224,0.875,bicubic,+5.665,+1.878,-19 -gluon_resnet50_v1s,84.856,15.144,96.445,3.555,25.68,224,0.875,bicubic,+6.144,+2.205,+2 -res2net50_26w_8s,84.850,15.150,96.345,3.655,48.40,224,0.875,bilinear,+5.870,+2.051,-10 -levit_128,84.843,15.157,96.351,3.649,9.21,224,0.900,bicubic,+6.351,+2.345,+8 -vit_tiny_patch16_384,84.835,15.165,96.712,3.288,5.79,384,1.000,bicubic,+6.401,+2.170,+13 -gluon_resnet50_v1d,84.830,15.170,96.400,3.600,25.58,224,0.875,bicubic,+5.754,+1.928,-19 -dla60_res2next,84.830,15.170,96.413,3.587,17.03,224,0.875,bilinear,+6.390,+2.263,+11 -mixnet_l,84.822,15.178,96.326,3.674,7.33,224,0.875,bicubic,+5.846,+2.148,-14 -tv_resnet152,84.818,15.182,96.215,3.785,60.19,224,0.875,bilinear,+6.502,+2.180,+16 -dla102x,84.813,15.187,96.548,3.452,26.31,224,0.875,bilinear,+6.297,+2.322,0 -dla60_res2net,84.809,15.191,96.484,3.517,20.85,224,0.875,bilinear,+6.347,+2.278,+4 -pit_xs_224,84.790,15.210,96.494,3.506,10.62,224,0.900,bicubic,+6.604,+2.330,+20 -xception41,84.788,15.212,96.415,3.585,26.97,299,0.903,bicubic,+6.278,+2.137,-2 -regnetx_064,84.781,15.219,96.492,3.508,26.21,224,0.875,bicubic,+5.715,+2.034,-24 -hrnet_w40,84.736,15.264,96.552,3.448,57.56,224,0.875,bilinear,+5.820,+2.078,-19 -res2net50_26w_6s,84.732,15.268,96.283,3.717,37.05,224,0.875,bilinear,+6.166,+2.149,-7 -repvgg_b2,84.722,15.278,96.469,3.531,89.02,224,0.875,bilinear,+5.930,+2.051,-15 -resmlp_12_distilled_224,84.713,15.287,96.223,3.777,15.35,224,0.875,bicubic,+6.771,+2.665,+26 -legacy_seresnet152,84.698,15.302,96.415,3.585,66.82,224,0.875,bilinear,+6.046,+2.045,-12 -selecsls60b,84.655,15.345,96.300,3.700,32.77,224,0.875,bicubic,+6.243,+2.126,0 -hrnet_w32,84.649,15.351,96.409,3.591,41.23,224,0.875,bilinear,+6.201,+2.215,-5 -bat_resnext26ts,84.638,15.362,96.274,3.726,10.73,256,0.900,bicubic,+6.388,+2.176,+6 -tf_efficientnetv2_b0,84.630,15.370,96.276,3.724,7.14,224,0.875,bicubic,+6.270,+2.256,+1 -efficientnet_b1,84.611,15.389,96.332,3.668,7.79,256,1.000,bicubic,+5.814,+1.990,-23 -regnetx_040,84.600,15.400,96.383,3.617,22.12,224,0.875,bicubic,+6.118,+2.139,-12 -efficientnet_es,84.581,15.419,96.313,3.687,5.44,224,0.875,bicubic,+6.525,+2.377,+11 -hrnet_w30,84.574,15.426,96.381,3.619,37.71,224,0.875,bilinear,+6.376,+2.157,+4 -tf_mixnet_l,84.564,15.437,96.244,3.756,7.33,224,0.875,bicubic,+5.790,+2.248,-25 -wide_resnet101_2,84.551,15.449,96.353,3.647,126.89,224,0.875,bilinear,+5.697,+2.063,-31 -dla60x,84.523,15.477,96.287,3.713,17.35,224,0.875,bilinear,+6.279,+2.269,-1 -legacy_seresnet101,84.502,15.498,96.328,3.672,49.33,224,0.875,bilinear,+6.114,+2.064,-10 -resnet26t,84.465,15.535,96.215,3.785,16.01,256,0.940,bicubic,+6.603,+2.371,+15 -coat_lite_tiny,84.461,15.539,96.373,3.627,5.72,224,0.900,bicubic,+6.947,+2.457,+31 -tf_efficientnet_em,84.450,15.550,96.178,3.822,6.90,240,0.882,bicubic,+6.318,+2.134,+1 -repvgg_b1,84.414,15.586,96.215,3.785,57.42,224,0.875,bilinear,+6.046,+2.118,-12 -efficientnet_b1_pruned,84.393,15.607,96.140,3.860,6.33,240,0.882,bicubic,+6.153,+2.306,-6 -res2net50_26w_4s,84.363,15.637,96.080,3.920,25.70,224,0.875,bilinear,+6.403,+2.228,+6 -hardcorenas_f,84.322,15.678,96.022,3.978,8.20,224,0.875,bilinear,+6.224,+2.220,-2 -res2net50_14w_8s,84.305,15.695,96.072,3.929,25.06,224,0.875,bilinear,+6.161,+2.224,-5 -selecsls60,84.284,15.716,96.099,3.901,30.67,224,0.875,bicubic,+6.308,+2.353,+2 -mobilevit_s,84.271,15.729,96.264,3.736,5.58,256,0.900,bicubic,+5.959,+2.112,-15 -regnetx_032,84.239,15.761,96.249,3.751,15.30,224,0.875,bicubic,+6.067,+2.161,-9 -res2next50,84.237,15.763,96.001,3.999,24.67,224,0.875,bilinear,+5.985,+2.115,-16 -gluon_resnet50_v1c,84.211,15.789,96.159,3.841,25.58,224,0.875,bicubic,+6.199,+2.169,-4 -dla102,84.192,15.808,96.210,3.790,33.27,224,0.875,bilinear,+6.162,+2.262,-6 -gcresnext26ts,84.177,15.823,96.084,3.916,10.48,256,0.900,bicubic,+6.357,+2.254,+6 -rexnet_100,84.164,15.836,96.255,3.745,4.80,224,0.875,bicubic,+6.306,+2.385,+2 -seresnext26ts,84.147,15.853,96.072,3.929,10.39,256,0.900,bicubic,+6.295,+2.281,+3 -tf_inception_v3,84.139,15.861,95.918,4.082,23.83,299,0.875,bicubic,+6.283,+2.278,+1 -res2net50_48w_2s,84.126,15.874,95.967,4.033,25.29,224,0.875,bilinear,+6.606,+2.415,+13 -xcit_tiny_12_p16_224,84.094,15.906,96.238,3.762,6.72,224,1.000,bicubic,+6.968,+2.522,+24 -resnet34d,84.094,15.906,95.975,4.025,21.82,224,0.875,bicubic,+6.980,+2.595,+27 -tf_efficientnet_lite2,84.094,15.906,96.069,3.931,6.09,260,0.890,bicubic,+6.626,+2.313,+13 -poolformer_s12,84.034,15.966,96.163,3.837,11.92,224,0.900,bicubic,+6.798,+2.659,+21 -efficientnet_b0,84.025,15.975,95.952,4.048,5.29,224,0.875,bicubic,+6.335,+2.422,0 -crossvit_9_dagger_240,84.019,15.981,96.082,3.918,8.78,240,0.875,bicubic,+7.037,+2.472,+27 -hardcorenas_e,83.968,16.032,95.901,4.099,8.07,224,0.875,bilinear,+6.174,+2.205,-3 -gmixer_24_224,83.966,16.034,95.854,4.146,24.72,224,0.875,bicubic,+5.930,+2.184,-20 -tf_efficientnet_cc_b0_8e,83.963,16.037,96.069,3.931,24.01,224,0.875,bicubic,+6.057,+2.413,-13 -regnety_016,83.957,16.043,96.005,3.995,11.20,224,0.875,bicubic,+6.097,+2.283,-12 -tv_resnext50_32x4d,83.957,16.043,95.963,4.037,25.03,224,0.875,bilinear,+6.341,+2.263,-3 -gluon_resnet50_v1b,83.942,16.058,96.016,3.984,25.56,224,0.875,bicubic,+6.362,+2.294,0 -densenet161,83.908,16.092,96.012,3.988,28.68,224,0.875,bicubic,+6.554,+2.376,+7 -adv_inception_v3,83.900,16.101,95.933,4.067,23.83,299,0.875,bicubic,+6.318,+2.197,-3 -mobilenetv2_120d,83.891,16.109,95.905,4.095,5.83,224,0.875,bicubic,+6.597,+2.409,+7 -seresnext26t_32x4d,83.874,16.126,95.931,4.069,16.81,224,0.875,bicubic,+5.898,+2.101,-25 -tv_resnet101,83.850,16.150,95.890,4.110,44.55,224,0.875,bilinear,+6.472,+2.348,+2 -tinynet_a,83.827,16.173,95.820,4.181,6.19,192,0.875,bicubic,+6.177,+2.284,-12 -hardcorenas_d,83.759,16.241,95.734,4.266,7.50,224,0.875,bilinear,+6.329,+2.252,-1 -inception_v3,83.759,16.241,95.882,4.119,23.83,299,0.875,bicubic,+6.321,+2.407,-3 -seresnext26d_32x4d,83.754,16.246,95.852,4.148,16.81,224,0.875,bicubic,+6.150,+2.244,-12 -dla60,83.731,16.269,95.935,4.065,22.04,224,0.875,bilinear,+6.701,+2.615,+10 -xcit_nano_12_p8_224_dist,83.729,16.271,95.952,4.048,3.05,224,1.000,bicubic,+7.409,+2.864,+30 -eca_resnext26ts,83.699,16.301,95.943,4.057,10.30,256,0.900,bicubic,+6.245,+2.377,-8 -repvgg_b1g4,83.695,16.305,96.025,3.975,39.97,224,0.875,bilinear,+6.109,+2.195,-15 -convmixer_1024_20_ks9_p14,83.682,16.318,95.890,4.110,24.38,224,0.960,bicubic,+6.740,+2.534,+9 -legacy_seresnet50,83.662,16.337,95.978,4.022,28.09,224,0.875,bilinear,+6.032,+2.228,-20 -tf_efficientnet_b0_ap,83.652,16.348,95.781,4.219,5.29,224,0.875,bicubic,+6.558,+2.525,+2 -tf_efficientnet_cc_b0_4e,83.635,16.365,95.740,4.260,13.31,224,0.875,bicubic,+6.333,+2.406,-9 -skresnet34,83.635,16.365,95.928,4.072,22.28,224,0.875,bicubic,+6.731,+2.608,+9 -resmlp_12_224,83.569,16.431,95.762,4.238,15.35,224,0.875,bicubic,+6.912,+2.582,+13 -mobilenetv3_large_100_miil,83.556,16.444,95.450,4.550,5.48,224,0.875,bilinear,+5.640,+2.544,-37 -densenet201,83.554,16.446,95.811,4.189,20.01,224,0.875,bicubic,+6.264,+2.333,-10 -gernet_s,83.519,16.481,95.794,4.206,8.17,224,0.875,bilinear,+6.611,+2.662,+3 -legacy_seresnext26_32x4d,83.519,16.481,95.717,4.283,16.79,224,0.875,bicubic,+6.413,+2.399,-6 -mixnet_m,83.519,16.481,95.689,4.311,5.01,224,0.875,bicubic,+6.255,+2.265,-12 -tf_efficientnet_b0,83.515,16.485,95.719,4.281,5.29,224,0.875,bicubic,+6.671,+2.491,+2 -hrnet_w18,83.498,16.502,95.911,4.089,21.30,224,0.875,bilinear,+6.744,+2.471,+4 -resnext26ts,83.470,16.530,95.726,4.274,10.30,256,0.900,bicubic,+6.690,+2.598,+2 -densenetblur121d,83.466,16.534,95.822,4.178,8.00,224,0.875,bicubic,+6.882,+2.630,+8 -selecsls42b,83.455,16.545,95.749,4.251,32.46,224,0.875,bicubic,+6.281,+2.357,-15 -hardcorenas_c,83.340,16.660,95.706,4.294,5.52,224,0.875,bilinear,+6.290,+2.548,-11 -tf_efficientnet_lite1,83.340,16.660,95.640,4.360,5.42,240,0.882,bicubic,+6.700,+2.420,+2 -regnetx_016,83.197,16.803,95.740,4.260,9.19,224,0.875,bicubic,+6.247,+2.319,-10 -dpn68,83.180,16.820,95.597,4.402,12.61,224,0.875,bicubic,+6.874,+2.623,+10 -mobilenetv2_140,83.180,16.820,95.687,4.313,6.11,224,0.875,bicubic,+6.658,+2.691,+4 -tf_efficientnet_es,83.178,16.822,95.587,4.413,5.44,224,0.875,bicubic,+6.582,+2.383,0 -tf_mixnet_m,83.176,16.824,95.461,4.539,5.01,224,0.875,bicubic,+6.234,+2.307,-12 -xcit_nano_12_p16_384_dist,83.171,16.829,95.751,4.249,3.05,384,1.000,bicubic,+7.715,+3.061,+21 -ese_vovnet19b_dw,83.114,16.886,95.779,4.221,6.54,224,0.875,bicubic,+6.312,+2.507,-10 -levit_128s,83.062,16.938,95.529,4.471,7.78,224,0.900,bicubic,+6.543,+2.657,0 -resnet26d,83.062,16.938,95.610,4.390,16.01,224,0.875,bicubic,+6.359,+2.460,-9 -repvgg_a2,83.001,16.999,95.591,4.409,28.21,224,0.875,bilinear,+6.543,+2.581,-1 -tv_resnet50,82.954,17.046,95.472,4.529,25.56,224,0.875,bilinear,+6.820,+2.604,+2 -hardcorenas_b,82.868,17.132,95.390,4.610,5.18,224,0.875,bilinear,+6.332,+2.636,-6 -densenet121,82.821,17.179,95.583,4.417,7.98,224,0.875,bicubic,+7.237,+2.931,+9 -vit_tiny_r_s16_p8_384,82.691,17.309,95.845,4.155,6.36,384,1.000,bicubic,+6.737,+2.581,+2 -densenet169,82.678,17.322,95.600,4.400,14.15,224,0.875,bicubic,+6.780,+2.570,+3 -mixnet_s,82.522,17.478,95.356,4.644,4.13,224,0.875,bicubic,+6.530,+2.558,-2 -vit_small_patch32_224,82.507,17.493,95.668,4.332,22.88,224,0.900,bicubic,+6.521,+2.398,-2 -regnety_008,82.488,17.512,95.491,4.509,6.26,224,0.875,bicubic,+6.178,+2.421,-7 -efficientnet_lite0,82.386,17.614,95.281,4.718,4.65,224,0.875,bicubic,+6.910,+2.769,+6 -resnest14d,82.349,17.651,95.341,4.659,10.61,224,0.875,bilinear,+6.845,+2.821,+4 -hardcorenas_a,82.311,17.689,95.296,4.704,5.26,224,0.875,bilinear,+6.391,+2.776,-4 -efficientnet_es_pruned,82.287,17.712,95.301,4.699,5.44,224,0.875,bicubic,+7.291,+2.861,+15 -mobilenetv3_rw,82.273,17.727,95.234,4.766,5.48,224,0.875,bicubic,+6.641,+2.526,-2 -semnasnet_100,82.251,17.749,95.230,4.770,3.89,224,0.875,bicubic,+6.801,+2.630,+4 -mobilenetv3_large_100,82.179,17.821,95.198,4.802,5.48,224,0.875,bicubic,+6.413,+2.654,-6 -resnet34,82.144,17.855,95.128,4.872,21.80,224,0.875,bilinear,+7.030,+2.844,+8 -vit_tiny_patch16_224,82.076,17.924,95.482,4.518,5.72,224,0.900,bicubic,+6.614,+2.638,-1 -mobilenetv2_110d,82.074,17.926,95.076,4.923,4.52,224,0.875,bicubic,+7.036,+2.892,+7 -tf_mixnet_s,82.038,17.962,95.124,4.877,4.13,224,0.875,bicubic,+6.388,+2.496,-9 -repvgg_b0,82.006,17.994,95.098,4.902,15.82,224,0.875,bilinear,+6.846,+2.680,+1 -deit_tiny_distilled_patch16_224,81.997,18.003,95.134,4.866,5.91,224,0.900,bicubic,+7.485,+3.248,+16 -mixer_b16_224,81.987,18.014,94.453,5.547,59.88,224,0.875,bicubic,+5.375,+2.225,-29 -pit_ti_distilled_224,81.972,18.029,95.145,4.855,5.10,224,0.900,bicubic,+7.440,+3.049,+13 -hrnet_w18_small_v2,81.963,18.037,95.164,4.836,15.60,224,0.875,bilinear,+6.845,+2.748,-1 -resnet26,81.954,18.046,95.247,4.753,16.00,224,0.875,bicubic,+6.654,+2.669,-6 -tf_efficientnet_lite0,81.952,18.048,95.162,4.838,4.65,224,0.875,bicubic,+7.120,+2.988,+3 -tinynet_b,81.873,18.127,94.880,5.120,3.73,188,0.875,bicubic,+6.897,+2.696,+1 -tf_mobilenetv3_large_100,81.848,18.152,95.070,4.930,5.48,224,0.875,bilinear,+6.330,+2.466,-15 -tv_densenet121,81.724,18.276,95.036,4.964,7.98,224,0.875,bicubic,+6.980,+2.884,+2 -regnety_006,81.698,18.302,95.121,4.879,6.06,224,0.875,bicubic,+6.448,+2.587,-10 -dla34,81.645,18.355,94.882,5.118,15.74,224,0.875,bilinear,+7.025,+2.810,+3 -xcit_nano_12_p8_224,81.638,18.362,95.271,4.729,3.05,224,1.000,bicubic,+7.728,+3.103,+11 -crossvit_9_240,81.615,18.385,94.981,5.019,8.55,240,0.875,bicubic,+7.655,+3.013,+9 -mobilevit_xs,81.570,18.430,95.036,4.964,2.32,256,0.900,bicubic,+6.926,+2.680,-1 -fbnetc_100,81.559,18.441,94.966,5.035,5.57,224,0.875,bilinear,+6.430,+2.580,-13 -legacy_seresnet34,81.536,18.464,94.897,5.103,21.96,224,0.875,bilinear,+6.728,+2.771,-6 -gluon_resnet34_v1b,81.498,18.503,94.805,5.195,21.80,224,0.875,bicubic,+6.910,+2.817,-2 -regnetx_008,81.481,18.520,95.064,4.936,7.26,224,0.875,bicubic,+6.447,+2.724,-12 -mnasnet_100,81.453,18.547,94.901,5.098,4.38,224,0.875,bicubic,+6.795,+2.790,-7 -vgg19_bn,81.446,18.554,94.765,5.235,143.68,224,0.875,bilinear,+7.232,+2.917,-2 -convit_tiny,81.132,18.868,95.040,4.960,5.71,224,0.875,bicubic,+8.018,+3.326,+10 -crossvit_tiny_240,81.090,18.910,94.985,5.015,7.01,240,0.875,bicubic,+7.758,+3.071,+6 -spnasnet_100,80.872,19.128,94.526,5.474,4.42,224,0.875,bilinear,+6.788,+2.706,-4 -ghostnet_100,80.701,19.299,94.291,5.709,5.18,224,0.875,bilinear,+6.727,+2.831,-3 -regnety_004,80.650,19.350,94.684,5.316,4.34,224,0.875,bicubic,+6.626,+2.930,-5 -skresnet18,80.641,19.359,94.376,5.624,11.96,224,0.875,bicubic,+7.605,+3.208,+6 -regnetx_006,80.635,19.365,94.526,5.474,6.20,224,0.875,bicubic,+6.775,+2.854,-3 -pit_ti_224,80.614,19.386,94.615,5.385,4.85,224,0.900,bicubic,+7.702,+3.209,+7 -swsl_resnet18,80.573,19.427,94.746,5.254,11.69,224,0.875,bilinear,+7.297,+3.010,+1 +regnetz_040h,88.953,11.047,98.202,1.798,28.94,320,1.000,bicubic,+4.457,+1.196,+9 +tf_efficientnet_b5_ap,88.942,11.057,98.164,1.836,30.39,456,0.934,bicubic,+4.688,+1.186,+23 +deit3_base_patch16_384,88.928,11.072,98.046,1.954,86.88,384,1.000,bicubic,+3.852,+0.792,-20 +dm_nfnet_f1,88.925,11.075,98.115,1.885,132.63,320,0.910,bicubic,+4.301,+1.017,-1 +volo_d1_224,88.906,11.094,98.031,1.968,26.63,224,0.960,bicubic,+4.742,+1.257,+27 +tf_efficientnetv2_s_in21ft1k,88.904,11.096,98.279,1.721,21.46,384,1.000,bicubic,+4.608,+1.025,+13 +vit_base_patch16_224,88.864,11.136,98.230,1.770,86.57,224,0.900,bicubic,+4.334,+0.934,0 +regnetz_d8,88.855,11.145,98.189,1.810,23.37,320,1.000,bicubic,+4.803,+1.193,+29 +resnetrs420,88.842,11.158,98.034,1.966,191.89,416,1.000,bicubic,+3.834,+0.910,-20 +regnetz_d8_evos,88.838,11.162,98.132,1.868,23.46,320,0.950,bicubic,+4.788,+1.136,+28 +resnetrs270,88.834,11.166,98.136,1.864,129.86,352,1.000,bicubic,+4.398,+1.162,+2 +ig_resnext101_32x16d,88.825,11.175,98.049,1.951,194.03,224,0.875,bilinear,+4.655,+0.851,+19 +vit_small_r26_s32_384,88.812,11.188,98.343,1.657,36.47,384,1.000,bicubic,+4.764,+1.015,+26 +vit_base_r50_s16_384,88.804,11.196,98.232,1.768,98.95,384,1.000,bicubic,+3.828,+0.942,-24 +xcit_medium_24_p16_224_dist,88.804,11.196,98.038,1.962,84.40,224,1.000,bicubic,+4.526,+1.098,+7 +seresnet152d,88.797,11.203,98.174,1.825,66.84,320,1.000,bicubic,+4.433,+1.130,+1 +xcit_tiny_24_p8_384_dist,88.778,11.222,98.164,1.836,12.11,384,1.000,bicubic,+5.032,+1.452,+43 +swsl_resnext101_32x8d,88.778,11.222,98.149,1.851,88.79,224,0.875,bilinear,+4.488,+0.967,+3 +convnext_tiny_384_in22ft1k,88.772,11.228,98.298,1.702,28.59,384,1.000,bicubic,+4.696,+1.140,+16 +resnetrs200,88.759,11.241,98.113,1.887,93.21,320,1.000,bicubic,+4.319,+1.033,-8 +tf_efficientnet_b6,88.759,11.241,98.068,1.932,43.04,528,0.942,bicubic,+4.651,+1.180,+13 +deit3_large_patch16_224,88.759,11.241,97.912,2.088,304.37,224,0.900,bicubic,+3.997,+0.874,-23 +resnetrs350,88.755,11.245,98.031,1.968,163.96,384,1.000,bicubic,+4.043,+1.041,-23 +vit_base_patch16_224_miil,88.742,11.258,98.027,1.973,86.54,224,0.875,bilinear,+4.470,+1.225,-1 +regnetz_040,88.727,11.273,98.091,1.909,27.12,320,1.000,bicubic,+4.491,+1.159,+1 +resnetv2_152x2_bitm,88.725,11.275,98.307,1.693,236.34,448,1.000,bilinear,+4.215,+0.873,-17 +regnety_160,88.699,11.301,98.068,1.932,83.59,288,1.000,bicubic,+5.007,+1.292,+38 +pit_b_distilled_224,88.674,11.326,98.091,1.909,74.79,224,0.900,bicubic,+4.532,+1.235,+5 +regnetz_d32,88.652,11.348,98.081,1.919,27.58,320,0.950,bicubic,+4.628,+1.213,+12 +vit_small_patch16_384,88.648,11.352,98.230,1.770,22.20,384,1.000,bicubic,+4.848,+1.130,+27 +regnety_080,88.635,11.365,97.972,2.028,39.18,288,1.000,bicubic,+4.707,+1.084,+15 +eca_nfnet_l1,88.624,11.376,98.134,1.866,41.41,320,1.000,bicubic,+4.612,+1.102,+11 +swinv2_base_window16_256,88.584,11.416,97.895,2.105,87.92,256,0.900,bicubic,+3.992,+0.821,-29 +convnext_large,88.577,11.423,97.854,2.146,197.77,224,0.875,bicubic,+4.281,+0.960,-14 +resnetv2_152x4_bitm,88.552,11.448,98.189,1.810,936.53,480,1.000,bilinear,+3.634,+0.747,-41 +resnet200d,88.545,11.455,97.959,2.041,64.69,320,1.000,bicubic,+4.585,+1.135,+8 +seresnextaa101d_32x8d,88.543,11.457,98.002,1.998,93.59,288,1.000,bicubic,+3.971,+0.932,-32 +xcit_small_24_p16_224_dist,88.535,11.465,98.002,1.998,47.67,224,1.000,bicubic,+4.665,+1.270,+10 +resnest269e,88.522,11.478,98.027,1.973,110.93,416,0.928,bicubic,+4.004,+1.041,-31 +swinv2_base_window8_256,88.518,11.482,97.893,2.107,87.92,256,0.900,bicubic,+4.256,+0.971,-16 +seresnext101_32x8d,88.505,11.495,97.888,2.112,93.57,288,1.000,bicubic,+4.301,+1.014,-12 +efficientnetv2_rw_s,88.475,11.525,97.972,2.028,23.94,384,1.000,bicubic,+4.665,+1.248,+14 +crossvit_18_dagger_408,88.475,11.525,97.893,2.107,44.61,408,1.000,bicubic,+4.281,+1.075,-13 +resnetv2_101x3_bitm,88.469,11.531,98.157,1.843,387.93,448,1.000,bilinear,+4.025,+0.775,-33 +cait_s24_224,88.451,11.549,97.957,2.043,46.92,224,1.000,bicubic,+4.993,+1.395,+27 +resnetv2_50x3_bitm,88.445,11.555,98.198,1.802,217.32,448,1.000,bilinear,+4.433,+1.072,-4 +resmlp_big_24_distilled_224,88.441,11.559,97.940,2.060,129.14,224,0.875,bicubic,+4.853,+1.292,+21 +regnetv_064,88.432,11.568,98.064,1.937,30.58,288,1.000,bicubic,+4.720,+1.318,+16 +resnest200e,88.430,11.570,98.044,1.956,70.20,320,0.909,bicubic,+4.602,+1.152,+5 +tf_efficientnet_b3_ns,88.428,11.572,98.027,1.973,12.23,300,0.904,bicubic,+4.380,+1.115,-10 +vit_large_r50_s32_224,88.424,11.576,98.085,1.915,328.99,224,0.900,bicubic,+3.994,+0.919,-37 +seresnext101d_32x8d,88.424,11.576,97.955,2.045,93.59,288,1.000,bicubic,+4.062,+1.037,-34 +tf_efficientnetv2_s,88.396,11.604,97.927,2.073,21.46,384,1.000,bicubic,+4.512,+1.229,-6 +regnetz_c16_evos,88.379,11.621,98.042,1.958,13.49,320,0.950,bicubic,+5.747,+1.566,+66 +efficientnet_b4,88.368,11.632,97.961,2.039,19.34,384,1.000,bicubic,+4.944,+1.363,+19 +swinv2_small_window16_256,88.364,11.636,97.852,2.148,49.73,256,0.900,bicubic,+4.154,+0.982,-28 +resnet152d,88.353,11.647,97.938,2.062,60.21,320,1.000,bicubic,+4.675,+1.198,+10 +tf_efficientnet_b4_ap,88.351,11.649,97.893,2.107,19.34,380,0.922,bicubic,+5.103,+1.501,+25 +convnext_base,88.347,11.653,97.784,2.216,88.59,224,0.875,bicubic,+4.507,+1.034,-8 +deit3_small_patch16_224_in21ft1k,88.334,11.666,98.127,1.873,22.06,224,1.000,bicubic,+5.258,+1.351,+36 +tf_efficientnet_b5,88.323,11.677,97.912,2.088,30.39,456,0.934,bicubic,+4.509,+1.164,-6 +regnety_064,88.319,11.681,97.861,2.139,30.58,288,1.000,bicubic,+4.599,+1.135,0 +crossvit_15_dagger_408,88.308,11.692,97.869,2.131,28.50,408,1.000,bicubic,+4.470,+1.089,-10 +deit3_small_patch16_384,88.298,11.702,97.888,2.112,22.21,384,1.000,bicubic,+4.870,+1.212,+9 +cs3se_edgenet_x,88.291,11.709,97.931,2.069,50.72,320,1.000,bicubic,+4.743,+1.265,+5 +resnetrs152,88.255,11.745,97.737,2.263,86.62,320,1.000,bicubic,+4.541,+1.123,-3 +deit3_base_patch16_224,88.251,11.749,97.807,2.193,86.59,224,0.900,bicubic,+4.459,+1.223,-9 +xcit_small_12_p16_224_dist,88.246,11.754,97.846,2.154,26.25,224,1.000,bicubic,+4.900,+1.428,+13 +regnetv_040,88.219,11.781,97.972,2.028,20.64,288,1.000,bicubic,+5.021,+1.308,+17 +deit_base_distilled_patch16_224,88.214,11.786,97.920,2.080,87.34,224,0.900,bicubic,+4.826,+1.432,+7 +xception65p,88.185,11.815,97.790,2.210,39.82,299,0.940,bicubic,+5.055,+1.310,+22 +swinv2_small_window8_256,88.185,11.815,97.775,2.225,49.73,256,0.900,bicubic,+4.331,+1.133,-23 +xcit_tiny_24_p16_384_dist,88.161,11.839,97.946,2.054,12.12,384,1.000,bicubic,+5.589,+1.658,+53 +xcit_large_24_p8_224,88.157,11.843,97.389,2.611,188.93,224,1.000,bicubic,+3.765,+0.731,-58 +ig_resnext101_32x8d,88.155,11.845,97.856,2.144,88.79,224,0.875,bilinear,+5.457,+1.224,+42 +resnetv2_152x2_bit_teacher_384,88.150,11.850,98.053,1.947,236.34,384,1.000,bicubic,+4.306,+0.937,-26 +cait_xxs36_384,88.138,11.862,97.908,2.092,17.37,384,1.000,bicubic,+5.946,+1.764,+82 +dm_nfnet_f0,88.125,11.875,97.854,2.146,71.49,256,0.900,bicubic,+4.741,+1.280,0 +xcit_tiny_12_p8_384_dist,88.101,11.899,97.923,2.077,6.71,384,1.000,bicubic,+5.715,+1.701,+59 +swsl_resnext101_32x4d,88.099,11.901,97.970,2.030,44.18,224,0.875,bilinear,+4.859,+1.210,+4 +xception65,88.071,11.929,97.750,2.250,39.92,299,0.940,bicubic,+4.897,+1.158,+6 +convnext_small,88.050,11.950,97.788,2.212,50.22,224,0.875,bicubic,+4.900,+1.358,+6 +swin_s3_base_224,88.050,11.950,97.660,2.340,71.13,224,0.900,bicubic,+4.118,+1.000,-38 +xcit_tiny_24_p8_224_dist,88.035,11.965,97.812,2.188,12.11,224,1.000,bicubic,+5.475,+1.644,+44 +convnext_tiny_in22ft1k,87.997,12.003,97.920,2.080,28.59,224,0.875,bicubic,+5.085,+1.296,+18 +cs3sedarknet_x,87.995,12.005,97.790,2.210,35.40,288,1.000,bicubic,+5.341,+1.444,+32 +eca_nfnet_l0,87.978,12.023,97.871,2.129,24.14,288,1.000,bicubic,+5.400,+1.381,+38 +nfnet_l0,87.971,12.029,97.867,2.133,35.07,288,1.000,bicubic,+5.219,+1.349,+25 +xcit_small_24_p8_224,87.969,12.031,97.581,2.419,47.63,224,1.000,bicubic,+4.129,+0.945,-37 +tf_efficientnet_b4,87.967,12.033,97.739,2.261,19.34,380,0.922,bicubic,+4.943,+1.439,+10 +regnety_032,87.941,12.059,97.888,2.112,19.44,288,1.000,bicubic,+5.217,+1.466,+23 +resnet101d,87.937,12.063,97.908,2.092,44.57,320,1.000,bicubic,+4.915,+1.462,+9 +mobilevitv2_200_384_in22ft1k,87.935,12.065,97.822,2.178,18.45,384,1.000,bicubic,+4.535,+1.240,-17 +swinv2_cr_small_ns_224,87.922,12.078,97.666,2.334,49.70,224,0.900,bicubic,+4.436,+1.182,-23 +sequencer2d_l,87.915,12.085,97.698,2.302,54.30,224,0.875,bicubic,+4.509,+1.198,-20 +regnety_040,87.913,12.087,97.884,2.116,20.65,288,1.000,bicubic,+4.877,+1.374,+3 +vit_base_patch32_384,87.911,12.089,98.012,1.988,88.30,384,1.000,bicubic,+4.559,+1.176,-18 +twins_svt_large,87.901,12.099,97.581,2.419,99.27,224,0.900,bicubic,+4.221,+0.987,-32 +twins_pcpvt_large,87.877,12.123,97.859,2.142,60.99,224,0.900,bicubic,+4.741,+1.255,-7 +swin_s3_small_224,87.860,12.140,97.434,2.566,49.74,224,0.900,bicubic,+4.086,+0.982,-41 +regnetz_c16,87.858,12.142,97.818,2.182,13.46,320,0.940,bicubic,+5.338,+1.458,+28 +deit_base_patch16_384,87.841,12.159,97.510,2.490,86.86,384,1.000,bicubic,+4.735,+1.140,-7 +mobilevitv2_175_384_in22ft1k,87.837,12.164,97.726,2.274,14.25,384,1.000,bicubic,+4.903,+1.296,-1 +xcit_small_12_p8_224,87.828,12.172,97.566,2.434,26.21,224,1.000,bicubic,+4.488,+1.086,-22 +tresnet_xl_448,87.796,12.204,97.459,2.541,78.44,448,0.875,bilinear,+4.748,+1.289,-7 +resnetv2_50x1_bit_distilled,87.792,12.208,97.899,2.101,25.55,224,0.875,bicubic,+4.970,+1.377,+1 +tresnet_m,87.740,12.259,97.523,2.477,31.39,224,0.875,bilinear,+4.666,+1.403,-10 +twins_pcpvt_base,87.732,12.268,97.728,2.272,43.83,224,0.900,bicubic,+5.024,+1.378,+8 +gc_efficientnetv2_rw_t,87.717,12.283,97.807,2.193,13.68,288,1.000,bicubic,+5.251,+1.509,+24 +resnetv2_101x1_bitm,87.683,12.317,97.938,2.062,44.54,448,1.000,bilinear,+5.351,+1.422,+35 +swin_small_patch4_window7_224,87.670,12.330,97.568,2.432,49.61,224,0.900,bicubic,+4.452,+1.242,-26 +mobilevitv2_150_384_in22ft1k,87.653,12.347,97.649,2.351,10.59,384,1.000,bicubic,+5.063,+1.333,+10 +twins_svt_base,87.644,12.356,97.525,2.474,56.07,224,0.900,bicubic,+4.506,+1.105,-23 +efficientnetv2_rw_t,87.642,12.358,97.688,2.312,13.65,288,1.000,bicubic,+5.298,+1.492,+28 +pnasnet5large,87.640,12.360,97.485,2.515,86.06,331,0.911,bicubic,+4.858,+1.443,-4 +cs3edgenet_x,87.632,12.368,97.662,2.338,47.82,288,1.000,bicubic,+4.910,+1.286,-1 +swinv2_tiny_window16_256,87.617,12.383,97.562,2.438,28.35,256,0.900,bicubic,+4.807,+1.332,-8 +swsl_resnext101_32x16d,87.608,12.392,97.820,2.180,194.03,224,0.875,bilinear,+4.258,+0.976,-38 +jx_nest_base,87.608,12.392,97.515,2.485,67.72,224,0.875,bicubic,+4.054,+1.151,-50 +xcit_medium_24_p8_224,87.606,12.394,97.197,2.803,84.32,224,1.000,bicubic,+3.868,+0.803,-59 +swsl_resnext50_32x4d,87.602,12.398,97.654,2.346,25.03,224,0.875,bilinear,+5.426,+1.422,+39 +sequencer2d_m,87.565,12.435,97.581,2.419,38.31,224,0.875,bicubic,+4.757,+1.313,-12 +tf_efficientnet_b2_ns,87.559,12.441,97.628,2.372,9.11,260,0.890,bicubic,+5.175,+1.382,+16 +levit_384,87.555,12.445,97.545,2.455,39.13,224,0.900,bicubic,+4.967,+1.527,-1 +ecaresnet50t,87.542,12.458,97.645,2.355,25.57,320,0.950,bicubic,+5.194,+1.507,+16 +vit_base_patch16_rpn_224,87.506,12.494,97.489,2.511,86.54,224,0.900,bicubic,+5.306,+1.493,+32 +edgenext_small,87.504,12.496,97.587,2.413,5.59,320,1.000,bicubic,+5.930,+1.873,+66 +resnetv2_152x2_bit_teacher,87.493,12.507,97.812,2.188,236.34,224,0.875,bicubic,+4.625,+1.244,-22 +jx_nest_small,87.491,12.509,97.521,2.479,38.35,224,0.875,bicubic,+4.371,+1.191,-35 +vit_relpos_base_patch16_clsgap_224,87.469,12.531,97.525,2.474,86.43,224,0.900,bicubic,+4.709,+1.351,-18 +vit_relpos_base_patch16_224,87.463,12.537,97.560,2.440,86.43,224,0.900,bicubic,+4.977,+1.418,+1 +resnet152,87.454,12.546,97.400,2.600,60.19,224,0.950,bicubic,+4.636,+1.268,-24 +fbnetv3_g,87.446,12.554,97.545,2.455,16.62,288,0.950,bilinear,+5.412,+1.479,+36 +resnext101_64x4d,87.444,12.556,97.442,2.558,83.46,288,1.000,bicubic,+4.300,+1.068,-45 +efficientnet_b3,87.435,12.565,97.679,2.321,12.23,320,1.000,bicubic,+5.195,+1.561,+18 +resnet61q,87.431,12.569,97.598,2.402,36.85,288,1.000,bicubic,+4.913,+1.468,-5 +cait_xxs24_384,87.414,12.586,97.619,2.381,12.03,384,1.000,bicubic,+6.452,+1.975,+101 +cs3sedarknet_l,87.407,12.593,97.572,2.428,21.91,288,0.950,bicubic,+5.631,+1.602,+47 +cs3darknet_x,87.399,12.601,97.607,2.393,35.05,288,1.000,bicubic,+5.175,+1.377,+16 +resnet51q,87.392,12.608,97.581,2.419,35.70,288,1.000,bilinear,+5.034,+1.403,0 +xcit_tiny_24_p8_224,87.380,12.620,97.626,2.374,12.11,224,1.000,bicubic,+5.484,+1.652,+37 +tresnet_l_448,87.380,12.620,97.487,2.513,55.99,448,0.875,bilinear,+5.110,+1.507,+10 +coat_lite_small,87.377,12.623,97.372,2.628,19.84,224,0.900,bicubic,+5.073,+1.522,+4 +sequencer2d_s,87.375,12.625,97.391,2.609,27.65,224,0.875,bicubic,+5.031,+1.357,-1 +swinv2_cr_small_224,87.371,12.629,97.344,2.656,49.70,224,0.900,bicubic,+4.233,+1.246,-54 +vit_relpos_medium_patch16_cls_224,87.369,12.631,97.453,2.547,38.76,224,0.900,bicubic,+4.807,+1.387,-19 +nasnetalarge,87.348,12.652,97.417,2.583,88.75,331,0.911,bicubic,+4.730,+1.373,-26 +crossvit_18_dagger_240,87.346,12.655,97.455,2.545,44.27,240,0.875,bicubic,+4.826,+1.387,-18 +resnetv2_101,87.322,12.678,97.325,2.675,44.54,224,0.950,bicubic,+5.276,+1.463,+19 +crossvit_18_240,87.316,12.684,97.487,2.513,43.27,240,0.875,bicubic,+4.918,+1.433,-13 +convnext_tiny,87.313,12.687,97.449,2.551,28.59,224,0.875,bicubic,+5.251,+1.595,+16 +resnest101e,87.286,12.714,97.560,2.440,48.28,256,0.875,bilinear,+4.398,+1.240,-47 +ecaresnet101d,87.284,12.716,97.562,2.438,44.57,224,0.875,bicubic,+5.114,+1.514,+8 +pit_s_distilled_224,87.275,12.725,97.500,2.500,24.04,224,0.900,bicubic,+5.281,+1.704,+16 +resnetv2_50d_gn,87.269,12.731,97.513,2.487,25.57,288,0.950,bicubic,+5.445,+1.589,+26 +vit_relpos_medium_patch16_rpn_224,87.256,12.744,97.442,2.558,38.73,224,0.900,bicubic,+4.962,+1.470,-7 +resnetrs101,87.243,12.757,97.457,2.543,63.62,288,0.940,bicubic,+4.959,+1.449,-6 +poolformer_m48,87.239,12.761,97.308,2.692,73.47,224,0.950,bicubic,+4.779,+1.350,-23 +mixer_b16_224_miil,87.230,12.770,97.410,2.590,59.88,224,0.875,bilinear,+4.926,+1.690,-11 +tresnet_xl,87.226,12.774,97.400,2.600,78.44,224,0.875,bilinear,+5.164,+1.464,+6 +xcit_tiny_12_p8_224_dist,87.219,12.780,97.449,2.551,6.71,224,1.000,bicubic,+6.011,+1.843,+58 +convit_base,87.207,12.793,97.286,2.714,86.54,224,0.875,bicubic,+4.915,+1.348,-12 +xcit_tiny_12_p16_384_dist,87.202,12.798,97.468,2.532,6.72,384,1.000,bicubic,+6.260,+2.060,+76 +resnetv2_50d_evos,87.194,12.806,97.359,2.641,25.59,288,0.950,bicubic,+5.216,+1.447,+8 +tf_efficientnet_b3_ap,87.188,12.812,97.380,2.620,12.23,300,0.904,bicubic,+5.364,+1.756,+17 +visformer_small,87.185,12.815,97.325,2.675,40.22,224,0.900,bicubic,+5.077,+1.449,-3 +crossvit_15_dagger_240,87.170,12.830,97.438,2.562,28.21,240,0.875,bicubic,+4.844,+1.482,-21 +vit_srelpos_medium_patch16_224,87.168,12.832,97.312,2.688,38.74,224,0.900,bicubic,+4.932,+1.378,-14 +vit_relpos_medium_patch16_224,87.138,12.862,97.506,2.494,38.75,224,0.900,bicubic,+4.676,+1.420,-35 +xcit_small_24_p16_224,87.134,12.866,97.263,2.737,47.67,224,1.000,bicubic,+4.550,+1.263,-46 +swin_s3_tiny_224,87.130,12.870,97.303,2.697,28.33,224,0.900,bicubic,+5.006,+1.353,-9 +resnet101,87.081,12.919,97.265,2.735,44.55,224,0.950,bicubic,+5.151,+1.499,+5 +swinv2_tiny_window8_256,87.079,12.921,97.517,2.483,28.35,256,0.900,bicubic,+5.269,+1.523,+10 +mobilevitv2_200_in22ft1k,87.059,12.941,97.425,2.575,18.45,256,0.888,bicubic,+4.725,+1.487,-30 +xception41p,87.057,12.943,97.201,2.799,26.91,299,0.940,bicubic,+5.089,+1.407,-1 +crossvit_15_240,87.055,12.945,97.423,2.577,27.53,240,0.875,bicubic,+5.511,+1.733,+19 +convit_small,87.051,12.949,97.350,2.650,27.78,224,0.875,bicubic,+5.623,+1.608,+28 +tf_efficientnetv2_b3,87.029,12.970,97.303,2.697,14.36,300,0.904,bicubic,+5.063,+1.521,-3 +xcit_small_12_p16_224,87.017,12.983,97.242,2.759,26.25,224,1.000,bicubic,+5.045,+1.430,-6 +regnetz_b16,87.012,12.988,97.425,2.575,9.72,288,0.940,bicubic,+6.300,+1.951,+73 +jx_nest_tiny,87.008,12.992,97.378,2.622,17.06,224,0.875,bicubic,+5.590,+1.760,+25 +deit3_small_patch16_224,87.004,12.996,97.167,2.833,22.06,224,0.900,bicubic,+5.622,+1.717,+28 +deit_small_distilled_patch16_224,87.002,12.998,97.316,2.684,22.44,224,0.900,bicubic,+5.794,+1.942,+37 +swinv2_cr_tiny_ns_224,86.998,13.002,97.282,2.718,28.33,224,0.900,bicubic,+5.212,+1.460,0 +resmlp_36_distilled_224,86.989,13.011,97.276,2.724,44.69,224,0.875,bicubic,+5.833,+1.790,+37 +xcit_large_24_p16_224,86.955,13.045,96.919,3.081,189.10,224,1.000,bicubic,+4.063,+1.041,-82 +mobilevitv2_175_in22ft1k,86.953,13.047,97.333,2.667,14.25,256,0.888,bicubic,+5.013,+1.543,-11 +poolformer_m36,86.946,13.054,97.148,2.852,56.17,224,0.950,bicubic,+4.838,+1.458,-24 +xcit_medium_24_p16_224,86.938,13.062,97.098,2.902,84.40,224,1.000,bicubic,+4.300,+1.120,-70 +convnext_tiny_hnf,86.918,13.082,97.280,2.720,28.59,224,0.950,bicubic,+4.698,+1.414,-34 +tnt_s_patch16_224,86.906,13.094,97.365,2.635,23.76,224,0.900,bicubic,+5.388,+1.619,+6 +vit_relpos_small_patch16_224,86.891,13.109,97.491,2.509,21.98,224,0.900,bicubic,+5.437,+1.663,+12 +vit_small_patch16_224,86.865,13.135,97.613,2.387,22.05,224,0.900,bicubic,+5.469,+1.475,+15 +ssl_resnext101_32x16d,86.865,13.135,97.519,2.481,194.03,224,0.875,bilinear,+5.009,+1.423,-14 +vit_small_r26_s32_224,86.856,13.143,97.528,2.472,36.43,224,0.900,bicubic,+4.994,+1.506,-16 +convmixer_1536_20,86.854,13.146,97.346,2.654,51.63,224,0.960,bicubic,+5.484,+1.734,+16 +rexnet_200,86.842,13.158,97.276,2.724,16.37,224,0.875,bicubic,+5.214,+1.608,-7 +tf_efficientnet_b3,86.837,13.163,97.297,2.703,12.23,300,0.904,bicubic,+5.199,+1.579,-9 +swsl_resnet50,86.835,13.165,97.493,2.507,25.56,224,0.875,bilinear,+5.655,+1.513,+22 +deit_base_patch16_224,86.827,13.173,97.052,2.949,86.57,224,0.900,bicubic,+4.833,+1.320,-29 +tresnet_m_448,86.814,13.186,97.216,2.784,31.39,448,0.875,bilinear,+5.108,+1.644,-15 +ssl_resnext101_32x8d,86.801,13.199,97.472,2.528,88.79,224,0.875,bilinear,+5.193,+1.430,-10 +tf_efficientnet_lite4,86.801,13.199,97.263,2.737,13.01,380,0.920,bilinear,+5.267,+1.597,-7 +coat_mini,86.790,13.210,97.158,2.842,10.34,224,0.900,bicubic,+5.524,+1.766,+12 +resnetaa50,86.771,13.229,97.389,2.611,25.56,288,1.000,bicubic,+5.153,+1.579,-14 +tresnet_l,86.763,13.237,97.271,2.729,55.99,224,0.875,bilinear,+5.273,+1.645,-6 +twins_svt_small,86.756,13.244,97.177,2.823,24.06,224,0.900,bicubic,+5.074,+1.511,-20 +cs3darknet_l,86.748,13.252,97.463,2.537,21.16,288,0.950,bicubic,+5.862,+1.795,+35 +mobilevitv2_150_in22ft1k,86.743,13.257,97.218,2.782,10.59,256,0.888,bicubic,+5.273,+1.550,-7 +levit_256,86.739,13.261,97.259,2.741,18.89,224,0.900,bicubic,+5.223,+1.769,-12 +cs3darknet_focus_l,86.735,13.265,97.380,2.620,21.15,288,0.950,bicubic,+5.861,+1.688,+34 +crossvit_base_240,86.735,13.265,97.122,2.878,105.03,240,0.875,bicubic,+4.519,+1.290,-55 +vit_srelpos_small_patch16_224,86.703,13.297,97.250,2.750,21.97,224,0.900,bicubic,+5.605,+1.678,+14 +halo2botnet50ts_256,86.692,13.308,97.096,2.904,22.64,256,0.950,bicubic,+4.624,+1.454,-49 +seresnext50_32x4d,86.690,13.310,97.222,2.778,27.56,224,0.875,bicubic,+5.428,+1.594,+2 +crossvit_small_240,86.688,13.312,97.273,2.727,26.86,240,0.875,bicubic,+5.672,+1.817,+17 +pit_b_224,86.688,13.312,96.898,3.102,73.76,224,0.900,bicubic,+4.244,+1.186,-81 +tf_efficientnet_b1_ns,86.666,13.334,97.378,2.622,7.79,240,0.882,bicubic,+5.280,+1.642,-9 +swin_tiny_patch4_window7_224,86.658,13.342,97.197,2.803,28.29,224,0.900,bicubic,+5.282,+1.655,-8 +wide_resnet50_2,86.641,13.359,97.212,2.788,68.88,224,0.875,bicubic,+5.185,+1.682,-17 +gernet_l,86.641,13.359,97.190,2.810,31.08,256,0.875,bilinear,+5.291,+1.654,-8 +poolformer_s36,86.639,13.361,97.158,2.842,30.86,224,0.900,bicubic,+5.221,+1.710,-15 +efficientnet_el,86.635,13.366,97.180,2.820,10.59,300,0.904,bicubic,+5.329,+1.646,-8 +twins_pcpvt_small,86.626,13.374,97.340,2.660,24.11,224,0.900,bicubic,+5.536,+1.698,+6 +resmlp_24_distilled_224,86.620,13.380,97.139,2.861,30.02,224,0.875,bicubic,+5.856,+1.917,+25 +nf_resnet50,86.605,13.395,97.293,2.707,25.56,288,0.940,bicubic,+5.951,+1.959,+28 +resnest50d_4s2x40d,86.583,13.417,97.269,2.731,30.42,224,0.875,bicubic,+5.475,+1.707,-1 +efficientnet_b3_pruned,86.579,13.421,97.188,2.812,9.86,300,0.904,bicubic,+5.721,+1.944,+19 +sebotnet33ts_256,86.573,13.427,96.791,3.209,13.70,256,0.940,bicubic,+5.419,+1.625,-6 +sehalonet33ts,86.570,13.430,97.009,2.991,13.69,256,0.940,bicubic,+5.598,+1.737,+7 +repvgg_b3,86.564,13.436,97.141,2.859,123.09,224,0.875,bilinear,+6.068,+1.877,+32 +xcit_tiny_24_p16_224_dist,86.534,13.466,97.216,2.784,12.12,224,1.000,bicubic,+6.086,+2.004,+38 +convnext_nano,86.532,13.468,97.182,2.818,15.59,288,1.000,bicubic,+5.056,+1.522,-32 +halonet50ts,86.500,13.500,97.152,2.848,22.73,256,0.940,bicubic,+4.848,+1.540,-46 +ssl_resnext101_32x4d,86.477,13.524,97.470,2.530,44.18,224,0.875,bilinear,+5.553,+1.744,+6 +gcresnet50t,86.474,13.526,97.141,2.859,25.90,256,0.900,bicubic,+5.540,+1.687,+4 +ecaresnet50d,86.472,13.528,97.184,2.816,25.58,224,0.875,bicubic,+5.874,+1.866,+20 +gluon_resnet152_v1s,86.462,13.538,97.109,2.891,60.32,224,0.875,bicubic,+5.448,+1.695,-4 +haloregnetz_b,86.462,13.538,96.943,3.057,11.68,224,0.940,bicubic,+5.418,+1.745,-8 +mobilevitv2_200,86.455,13.545,96.970,3.030,18.45,256,0.888,bicubic,+5.315,+1.602,-15 +resnetv2_50x1_bitm,86.442,13.558,97.600,2.400,25.55,448,1.000,bilinear,+6.100,+1.914,+36 +resnest50d_1s4x24d,86.440,13.560,97.152,2.848,25.68,224,0.875,bicubic,+5.456,+1.828,-7 +repvgg_b3g4,86.368,13.632,97.054,2.946,83.83,224,0.875,bilinear,+6.152,+1.946,+47 +darknetaa53,86.361,13.639,97.165,2.835,36.02,288,1.000,bilinear,+5.839,+1.839,+18 +darknet53,86.359,13.641,97.113,2.887,41.61,288,1.000,bicubic,+5.821,+1.693,+15 +lamhalobotnet50ts_256,86.357,13.643,97.062,2.938,22.57,256,0.950,bicubic,+4.805,+1.558,-52 +legacy_senet154,86.340,13.660,96.925,3.075,115.09,224,0.875,bilinear,+5.032,+1.429,-33 +cait_xxs36_224,86.338,13.662,97.111,2.889,17.30,224,1.000,bicubic,+6.590,+2.243,+67 +resnext50_32x4d,86.329,13.671,96.964,3.036,25.03,224,0.950,bicubic,+5.233,+1.638,-20 +pit_s_224,86.325,13.675,97.049,2.951,23.46,224,0.900,bicubic,+5.227,+1.717,-22 +vit_small_patch32_384,86.316,13.684,97.419,2.581,22.92,384,1.000,bicubic,+5.826,+1.819,+13 +gernet_m,86.316,13.684,97.098,2.902,21.14,224,0.875,bilinear,+5.586,+1.912,-1 +mobilevitv2_175,86.316,13.684,96.990,3.010,14.25,256,0.888,bicubic,+5.454,+1.728,-7 +efficientnet_b2,86.310,13.690,96.987,3.013,9.11,288,1.000,bicubic,+5.694,+1.671,+1 +gluon_senet154,86.278,13.722,96.945,3.055,115.09,224,0.875,bicubic,+5.048,+1.599,-37 +resnest50d,86.240,13.761,97.071,2.929,27.48,224,0.875,bilinear,+5.266,+1.691,-20 +convmixer_768_32,86.225,13.775,97.034,2.966,21.11,224,0.960,bicubic,+6.061,+1.962,+37 +ecaresnet101d_pruned,86.210,13.790,97.338,2.662,24.88,224,0.875,bicubic,+5.400,+1.710,-10 +efficientnet_el_pruned,86.195,13.805,97.022,2.978,10.59,300,0.904,bicubic,+5.897,+1.808,+24 +cspdarknet53,86.184,13.816,97.013,2.987,27.64,256,0.887,bilinear,+6.128,+1.927,+40 +inception_v4,86.167,13.833,96.915,3.085,42.68,299,0.875,bicubic,+5.999,+1.951,+31 +rexnet_150,86.156,13.844,97.060,2.940,9.73,224,0.875,bicubic,+5.842,+1.894,+19 +inception_resnet_v2,86.137,13.863,97.043,2.957,55.84,299,0.897,bicubic,+5.677,+1.737,+4 +xcit_tiny_12_p8_224,86.114,13.886,97.086,2.914,6.71,224,1.000,bicubic,+6.420,+2.038,+54 +tf_efficientnet_el,86.086,13.914,96.964,3.036,10.59,300,0.904,bicubic,+5.832,+1.836,+21 +ssl_resnext50_32x4d,86.084,13.916,97.212,2.788,25.03,224,0.875,bilinear,+5.758,+1.800,+13 +cspresnext50,86.073,13.927,97.103,2.897,20.57,256,0.887,bilinear,+5.529,+1.779,-8 +mobilevitv2_150,86.073,13.927,96.853,3.147,10.59,256,0.888,bicubic,+5.705,+1.789,+7 +ecaresnetlight,86.054,13.946,97.071,2.929,30.16,224,0.875,bicubic,+5.598,+1.825,-1 +gluon_resnet101_v1s,86.054,13.946,97.024,2.976,44.67,224,0.875,bicubic,+5.756,+1.862,+14 +edgenext_small_rw,86.049,13.950,96.925,3.075,7.83,320,1.000,bicubic,+5.597,+1.735,-2 +lambda_resnet50ts,86.039,13.961,96.746,3.254,21.54,256,0.950,bicubic,+4.887,+1.644,-48 +poolformer_s24,86.037,13.963,97.030,2.970,21.39,224,0.900,bicubic,+5.721,+1.988,+7 +gluon_seresnext101_32x4d,86.032,13.968,96.977,3.023,48.96,224,0.875,bicubic,+5.126,+1.681,-32 +resnetv2_50,86.015,13.985,96.902,3.098,25.55,224,0.950,bicubic,+5.603,+1.830,-3 +seresnet33ts,86.009,13.991,97.011,2.989,19.78,256,0.900,bicubic,+5.655,+1.905,0 +gcresnext50ts,86.009,13.991,96.966,3.034,15.67,256,0.900,bicubic,+5.431,+1.796,-19 +resnet50d,86.002,13.998,96.987,3.013,25.58,224,0.875,bicubic,+5.474,+1.819,-17 +ecaresnet26t,85.985,14.015,97.037,2.963,16.01,320,0.950,bicubic,+6.133,+1.953,+31 +tf_efficientnet_b2_ap,85.973,14.027,96.808,3.192,9.11,260,0.890,bicubic,+5.671,+1.780,+2 +vit_base_patch32_224,85.958,14.042,97.130,2.869,88.22,224,0.900,bicubic,+5.234,+1.564,-29 +gluon_seresnext101_64x4d,85.958,14.042,96.981,3.019,88.23,224,0.875,bicubic,+5.078,+1.685,-38 +fbnetv3_d,85.924,14.076,97.028,2.972,10.31,256,0.950,bilinear,+6.244,+2.088,+38 +vit_large_patch32_384,85.911,14.089,97.368,2.632,306.63,384,1.000,bicubic,+4.403,+1.278,-85 +tf_efficientnet_b2,85.909,14.091,96.862,3.139,9.11,260,0.890,bicubic,+5.821,+1.954,+11 +gluon_resnet152_v1d,85.906,14.094,96.806,3.194,60.21,224,0.875,bicubic,+5.430,+1.606,-20 +tf_efficientnetv2_b2,85.902,14.098,96.885,3.115,10.10,260,0.890,bicubic,+5.694,+1.841,+4 +resnet50_gn,85.881,14.119,96.849,3.151,25.56,224,0.940,bicubic,+5.821,+1.901,+11 +vit_base_patch16_224_sam,85.879,14.121,96.695,3.305,86.57,224,0.900,bicubic,+5.635,+1.941,-1 +seresnet50,85.853,14.147,97.007,2.993,28.09,224,0.875,bicubic,+5.587,+1.937,-5 +gluon_resnet101_v1d,85.851,14.149,96.663,3.337,44.57,224,0.875,bicubic,+5.433,+1.649,-20 +repvgg_b2g4,85.847,14.153,96.812,3.188,61.76,224,0.875,bilinear,+6.481,+2.124,+44 +gcresnet33ts,85.804,14.196,96.902,3.098,19.88,256,0.900,bicubic,+5.728,+1.908,+5 +mixnet_xl,85.798,14.202,96.710,3.290,11.90,224,0.875,bicubic,+5.320,+1.776,-29 +ens_adv_inception_resnet_v2,85.768,14.232,96.761,3.239,55.84,299,0.897,bicubic,+5.794,+1.819,+7 +tf_efficientnet_lite3,85.761,14.239,96.889,3.111,8.20,300,0.904,bilinear,+5.943,+1.975,+17 +legacy_seresnext101_32x4d,85.744,14.256,96.755,3.245,48.96,224,0.875,bilinear,+5.522,+1.741,-8 +ese_vovnet39b,85.742,14.258,96.894,3.107,24.57,224,0.875,bicubic,+6.430,+2.180,+42 +gluon_resnext101_32x4d,85.742,14.258,96.635,3.365,44.18,224,0.875,bicubic,+5.402,+1.709,-21 +eca_resnet33ts,85.740,14.260,96.902,3.098,19.68,256,0.900,bicubic,+5.660,+1.930,-3 +xcit_tiny_24_p16_224,85.736,14.264,96.938,3.062,12.12,224,1.000,bicubic,+6.292,+2.050,+32 +cspresnet50,85.727,14.273,96.799,3.200,21.62,256,0.887,bilinear,+6.145,+2.091,+24 +regnety_320,85.719,14.281,96.723,3.277,145.05,224,0.875,bicubic,+4.915,+1.479,-54 +resnet50,85.719,14.281,96.492,3.508,25.56,224,0.950,bicubic,+5.345,+1.878,-30 +gluon_resnext101_64x4d,85.693,14.307,96.644,3.356,83.46,224,0.875,bicubic,+5.089,+1.652,-49 +resmlp_big_24_224,85.693,14.307,96.424,3.576,129.14,224,0.875,bicubic,+4.663,+1.404,-74 +xception71,85.691,14.309,96.774,3.226,42.34,299,0.903,bicubic,+5.821,+1.850,0 +efficientnet_em,85.686,14.313,96.936,3.064,6.90,240,0.882,bicubic,+6.434,+2.144,+41 +deit_small_patch16_224,85.678,14.322,96.904,3.096,22.05,224,0.900,bicubic,+5.814,+1.856,-1 +pit_xs_distilled_224,85.659,14.341,96.665,3.335,11.00,224,0.900,bicubic,+6.351,+2.299,+31 +dpn107,85.650,14.350,96.725,3.275,86.92,224,0.875,bicubic,+5.482,+1.819,-18 +efficientnet_b2_pruned,85.640,14.360,96.746,3.254,8.31,260,0.890,bicubic,+5.722,+1.896,-9 +resmlp_36_224,85.625,14.375,96.795,3.205,44.69,224,0.875,bicubic,+5.855,+1.909,+1 +mobilevitv2_125,85.584,14.416,96.665,3.335,7.48,256,0.888,bicubic,+5.902,+1.817,+5 +gluon_resnet152_v1c,85.582,14.418,96.646,3.354,60.21,224,0.875,bicubic,+5.670,+1.804,-11 +levit_192,85.578,14.422,96.744,3.256,10.95,224,0.900,bicubic,+5.742,+1.954,-5 +ecaresnet50d_pruned,85.576,14.425,96.932,3.068,19.94,224,0.875,bicubic,+5.858,+2.056,0 +resnext50d_32x4d,85.571,14.429,96.748,3.252,25.05,224,0.875,bicubic,+5.895,+1.882,+4 +tf_efficientnetv2_b1,85.561,14.439,96.727,3.273,8.14,240,0.882,bicubic,+6.095,+2.005,+13 +regnety_120,85.543,14.457,96.785,3.215,51.82,224,0.875,bicubic,+5.167,+1.663,-47 +regnetx_320,85.522,14.478,96.669,3.331,107.81,224,0.875,bicubic,+5.278,+1.649,-34 +fbnetv3_b,85.514,14.486,96.862,3.139,8.60,256,0.950,bilinear,+6.372,+2.112,+33 +nf_regnet_b1,85.514,14.486,96.795,3.205,10.22,288,0.900,bicubic,+6.214,+2.041,+20 +dpn92,85.501,14.499,96.631,3.369,37.67,224,0.875,bicubic,+5.481,+1.801,-23 +rexnet_130,85.475,14.525,96.686,3.314,7.56,224,0.875,bicubic,+5.973,+2.004,+3 +gluon_resnet152_v1b,85.465,14.536,96.556,3.444,60.19,224,0.875,bicubic,+5.783,+1.820,-6 +resnetrs50,85.462,14.538,96.738,3.262,35.69,224,0.910,bicubic,+5.576,+1.768,-21 +dpn131,85.400,14.600,96.631,3.369,79.25,224,0.875,bicubic,+5.574,+1.923,-16 +regnetx_160,85.390,14.610,96.637,3.363,54.28,224,0.875,bicubic,+5.536,+1.807,-20 +dla102x2,85.377,14.623,96.629,3.371,41.28,224,0.875,bilinear,+5.935,+1.983,+4 +gmlp_s16_224,85.351,14.649,96.646,3.354,19.42,224,0.875,bicubic,+5.711,+2.022,-7 +gluon_seresnext50_32x4d,85.334,14.666,96.671,3.329,27.56,224,0.875,bicubic,+5.422,+1.839,-27 +botnet26t_256,85.332,14.668,96.631,3.369,12.49,256,0.950,bicubic,+6.074,+2.103,+15 +skresnext50_32x4d,85.317,14.683,96.394,3.606,27.48,224,0.875,bicubic,+5.163,+1.748,-39 +gluon_resnet101_v1c,85.311,14.689,96.407,3.593,44.57,224,0.875,bicubic,+5.775,+1.829,-8 +dpn98,85.304,14.696,96.466,3.534,61.57,224,0.875,bicubic,+5.660,+1.866,-13 +lambda_resnet26t,85.302,14.698,96.727,3.273,10.96,256,0.940,bicubic,+6.204,+2.137,+20 +resnetblur50,85.291,14.709,96.520,3.480,25.56,224,0.875,bicubic,+5.997,+1.886,+7 +dpn68b,85.291,14.709,96.464,3.536,12.61,224,0.875,bicubic,+6.075,+2.050,+12 +resmlp_24_224,85.264,14.736,96.496,3.504,30.02,224,0.875,bicubic,+5.886,+1.950,-5 +coat_lite_mini,85.255,14.745,96.680,3.320,11.01,224,0.900,bicubic,+6.167,+2.072,+17 +cait_xxs24_224,85.225,14.775,96.716,3.284,11.96,224,1.000,bicubic,+6.839,+2.408,+50 +resnet33ts,85.225,14.775,96.627,3.373,19.68,256,0.900,bicubic,+6.017,+2.053,+9 +xcit_tiny_12_p16_224_dist,85.215,14.785,96.599,3.401,6.72,224,1.000,bicubic,+6.637,+2.401,+35 +halonet26t,85.202,14.798,96.464,3.536,12.48,256,0.950,bicubic,+6.090,+2.150,+11 +resnext101_32x8d,85.195,14.805,96.451,3.549,88.79,224,0.875,bilinear,+5.879,+1.933,-8 +gluon_inception_v3,85.180,14.819,96.526,3.474,23.83,299,0.875,bicubic,+6.374,+2.156,+24 +resnet32ts,85.168,14.832,96.622,3.378,17.96,256,0.900,bicubic,+6.154,+2.266,+15 +gluon_xception65,85.155,14.845,96.597,3.403,39.92,299,0.903,bicubic,+5.433,+1.737,-33 +hrnet_w48,85.148,14.851,96.492,3.508,77.47,224,0.875,bilinear,+5.848,+1.978,-6 +gluon_resnet101_v1b,85.142,14.858,96.368,3.632,44.55,224,0.875,bicubic,+5.838,+1.848,-9 +eca_halonext26ts,85.127,14.873,96.586,3.414,10.76,256,0.940,bicubic,+5.639,+1.982,-23 +regnetx_120,85.127,14.873,96.473,3.527,46.11,224,0.875,bicubic,+5.535,+1.739,-28 +eca_botnext26ts_256,85.125,14.875,96.507,3.493,10.59,256,0.950,bicubic,+5.849,+1.891,-8 +tf_efficientnet_b1_ap,85.125,14.875,96.407,3.593,7.79,240,0.882,bicubic,+5.851,+2.099,-8 +xception,85.123,14.877,96.471,3.529,22.86,299,0.897,bicubic,+6.079,+2.077,+6 +hrnet_w64,85.114,14.886,96.746,3.254,128.06,224,0.875,bilinear,+5.644,+2.092,-26 +lambda_resnet26rpt_256,85.095,14.905,96.560,3.440,10.99,256,0.940,bicubic,+6.131,+2.134,+7 +res2net101_26w_4s,85.095,14.905,96.383,3.617,45.21,224,0.875,bilinear,+5.899,+1.947,-5 +ssl_resnet50,85.091,14.909,96.862,3.139,25.56,224,0.875,bilinear,+5.867,+2.032,-10 +tf_efficientnet_cc_b1_8e,85.065,14.935,96.422,3.578,39.72,240,0.882,bicubic,+5.751,+2.052,-22 +xcit_nano_12_p8_384_dist,85.025,14.975,96.631,3.369,3.05,384,1.000,bicubic,+7.209,+2.585,+62 +resnest26d,85.010,14.990,96.637,3.363,17.07,224,0.875,bilinear,+6.526,+2.343,+21 +gluon_resnext50_32x4d,85.008,14.992,96.428,3.572,25.03,224,0.875,bicubic,+5.648,+2.002,-27 +tf_efficientnet_b0_ns,84.997,15.003,96.505,3.495,5.29,224,0.875,bicubic,+6.333,+2.129,+12 +coat_tiny,84.980,15.020,96.409,3.591,5.50,224,0.900,bicubic,+6.544,+2.371,+23 +dla169,84.922,15.078,96.535,3.465,53.39,224,0.875,bilinear,+6.240,+2.199,+9 +tf_efficientnet_b1,84.914,15.086,96.362,3.638,7.79,240,0.882,bicubic,+6.086,+2.164,+2 +mobilevitv2_100,84.905,15.095,96.390,3.610,4.90,256,0.888,bicubic,+6.819,+2.230,+39 +legacy_seresnext50_32x4d,84.899,15.101,96.428,3.572,27.56,224,0.875,bilinear,+5.823,+1.994,-11 +hrnet_w44,84.886,15.114,96.437,3.563,67.06,224,0.875,bilinear,+5.990,+2.067,-3 +regnetx_080,84.867,15.133,96.428,3.572,39.57,224,0.875,bicubic,+5.665,+1.876,-19 +gluon_resnet50_v1s,84.858,15.142,96.441,3.559,25.68,224,0.875,bicubic,+6.152,+2.203,+2 +res2net50_26w_8s,84.847,15.153,96.355,3.645,48.40,224,0.875,bilinear,+5.895,+2.049,-8 +levit_128,84.839,15.161,96.353,3.647,9.21,224,0.900,bicubic,+6.357,+2.341,+10 +vit_tiny_patch16_384,84.832,15.168,96.712,3.288,5.79,384,1.000,bicubic,+6.402,+2.168,+14 +gluon_resnet50_v1d,84.830,15.170,96.398,3.602,25.58,224,0.875,bicubic,+5.760,+1.932,-16 +dla60_res2next,84.826,15.174,96.411,3.589,17.03,224,0.875,bilinear,+6.370,+2.265,+9 +mixnet_l,84.824,15.176,96.328,3.672,7.33,224,0.875,bicubic,+5.848,+2.150,-15 +tv_resnet152,84.818,15.182,96.221,3.779,60.19,224,0.875,bilinear,+6.498,+2.187,+16 +dla102x,84.807,15.193,96.548,3.452,26.31,224,0.875,bilinear,+6.295,+2.320,+1 +dla60_res2net,84.803,15.197,96.479,3.521,20.85,224,0.875,bilinear,+6.345,+2.283,+4 +pit_xs_224,84.794,15.206,96.494,3.506,10.62,224,0.900,bicubic,+6.604,+2.328,+20 +xception41,84.792,15.208,96.417,3.583,26.97,299,0.903,bicubic,+6.276,+2.137,-3 +regnetx_064,84.779,15.221,96.492,3.508,26.21,224,0.875,bicubic,+5.705,+2.032,-25 +hrnet_w40,84.741,15.259,96.554,3.446,57.56,224,0.875,bilinear,+5.819,+2.084,-19 +res2net50_26w_6s,84.726,15.274,96.281,3.719,37.05,224,0.875,bilinear,+6.156,+2.157,-7 +repvgg_b2,84.722,15.278,96.469,3.531,89.02,224,0.875,bilinear,+5.928,+2.051,-16 +resmlp_12_distilled_224,84.715,15.285,96.221,3.779,15.35,224,0.875,bicubic,+6.769,+2.661,+27 +legacy_seresnet152,84.702,15.298,96.415,3.585,66.82,224,0.875,bilinear,+6.050,+2.045,-12 +cs3darknet_m,84.692,15.308,96.492,3.508,9.31,288,0.950,bicubic,+7.066,+2.478,+39 +hrnet_w32,84.655,15.345,96.411,3.589,41.23,224,0.875,bilinear,+6.203,+2.223,-4 +selecsls60b,84.651,15.349,96.304,3.696,32.77,224,0.875,bicubic,+6.247,+2.132,-2 +bat_resnext26ts,84.636,15.364,96.268,3.732,10.73,256,0.900,bicubic,+6.388,+2.172,+5 +tf_efficientnetv2_b0,84.617,15.383,96.274,3.726,7.14,224,0.875,bicubic,+6.265,+2.248,0 +regnetx_040,84.604,15.396,96.379,3.621,22.12,224,0.875,bicubic,+6.116,+2.141,-13 +efficientnet_b1,84.604,15.396,96.336,3.664,7.79,256,1.000,bicubic,+5.816,+1.990,-24 +vit_relpos_base_patch32_plus_rpn_256,84.593,15.407,96.010,3.990,119.42,256,0.900,bicubic,+5.107,+1.870,-68 +efficientnet_es,84.581,15.419,96.317,3.683,5.44,224,0.875,bicubic,+6.523,+2.373,+10 +hrnet_w30,84.576,15.424,96.383,3.617,37.71,224,0.875,bilinear,+6.378,+2.159,+2 +tf_mixnet_l,84.564,15.437,96.242,3.758,7.33,224,0.875,bicubic,+5.786,+2.244,-27 +wide_resnet101_2,84.549,15.451,96.353,3.647,126.89,224,0.875,bilinear,+5.697,+2.065,-33 +dla60x,84.521,15.479,96.289,3.711,17.35,224,0.875,bilinear,+6.293,+2.265,-2 +legacy_seresnet101,84.506,15.494,96.330,3.670,49.33,224,0.875,bilinear,+6.126,+2.068,-11 +cs3darknet_focus_m,84.482,15.518,96.422,3.578,9.30,288,0.950,bicubic,+7.200,+2.450,+42 +resnet26t,84.467,15.533,96.217,3.783,16.01,256,0.940,bicubic,+6.603,+2.375,+13 +coat_lite_tiny,84.459,15.541,96.370,3.630,5.72,224,0.900,bicubic,+6.943,+2.456,+30 +tf_efficientnet_em,84.448,15.552,96.183,3.817,6.90,240,0.882,bicubic,+6.322,+2.137,-2 +repvgg_b1,84.416,15.584,96.215,3.785,57.42,224,0.875,bilinear,+6.048,+2.121,-15 +efficientnet_b1_pruned,84.397,15.603,96.140,3.860,6.33,240,0.882,bicubic,+6.153,+2.306,-10 +res2net50_26w_4s,84.363,15.637,96.080,3.920,25.70,224,0.875,bilinear,+6.401,+2.228,+4 +hardcorenas_f,84.329,15.671,96.025,3.975,8.20,224,0.875,bilinear,+6.227,+2.223,-5 +res2net50_14w_8s,84.305,15.695,96.072,3.929,25.06,224,0.875,bilinear,+6.161,+2.220,-8 +selecsls60,84.297,15.703,96.101,3.899,30.67,224,0.875,bicubic,+6.313,+2.269,-1 +mobilevit_s,84.269,15.731,96.266,3.734,5.58,256,0.900,bicubic,+5.959,+2.114,-18 +regnetx_032,84.243,15.757,96.251,3.749,15.30,224,0.875,bicubic,+6.059,+2.163,-12 +res2next50,84.237,15.763,95.999,4.001,24.67,224,0.875,bilinear,+5.979,+2.111,-19 +gluon_resnet50_v1c,84.211,15.789,96.163,3.837,25.58,224,0.875,bicubic,+6.203,+2.173,-6 +dla102,84.190,15.810,96.208,3.792,33.27,224,0.875,bilinear,+6.162,+2.258,-8 +gcresnext26ts,84.171,15.829,96.084,3.916,10.48,256,0.900,bicubic,+6.357,+2.248,+5 +rexnet_100,84.168,15.832,96.255,3.745,4.80,224,0.875,bicubic,+6.308,+2.381,-1 +seresnext26ts,84.147,15.853,96.069,3.931,10.39,256,0.900,bicubic,+6.289,+2.279,-1 +tf_inception_v3,84.139,15.861,95.918,4.082,23.83,299,0.875,bicubic,+6.287,+2.278,0 +res2net50_48w_2s,84.128,15.872,95.965,4.035,25.29,224,0.875,bilinear,+6.604,+2.415,+12 +resnet34d,84.096,15.904,95.978,4.022,21.82,224,0.875,bicubic,+6.980,+2.596,+27 +xcit_tiny_12_p16_224,84.094,15.906,96.234,3.766,6.72,224,1.000,bicubic,+6.970,+2.522,+25 +tf_efficientnet_lite2,84.085,15.915,96.076,3.924,6.09,260,0.890,bicubic,+6.619,+2.318,+11 +poolformer_s12,84.036,15.964,96.163,3.837,11.92,224,0.900,bicubic,+6.798,+2.657,+21 +efficientnet_b0,84.032,15.968,95.958,4.042,5.29,224,0.875,bicubic,+6.332,+2.426,-2 +crossvit_9_dagger_240,84.015,15.985,96.084,3.916,8.78,240,0.875,bicubic,+7.037,+2.470,+27 +tf_efficientnet_cc_b0_8e,83.970,16.030,96.074,3.926,24.01,224,0.875,bicubic,+6.070,+2.416,-13 +hardcorenas_e,83.966,16.034,95.903,4.097,8.07,224,0.875,bilinear,+6.180,+2.199,-6 +gmixer_24_224,83.966,16.034,95.854,4.146,24.72,224,0.875,bicubic,+5.930,+2.184,-23 +regnety_016,83.957,16.043,96.005,3.995,11.20,224,0.875,bicubic,+6.101,+2.285,-12 +tv_resnext50_32x4d,83.957,16.043,95.967,4.033,25.03,224,0.875,bilinear,+6.339,+2.267,-4 +gluon_resnet50_v1b,83.936,16.064,96.014,3.986,25.56,224,0.875,bicubic,+6.352,+2.294,-2 +densenet161,83.906,16.094,96.014,3.986,28.68,224,0.875,bicubic,+6.552,+2.378,+6 +adv_inception_v3,83.897,16.103,95.933,4.067,23.83,299,0.875,bicubic,+6.319,+2.195,-3 +mobilenetv2_120d,83.889,16.111,95.909,4.091,5.83,224,0.875,bicubic,+6.599,+2.409,+6 +seresnext26t_32x4d,83.874,16.126,95.935,4.065,16.81,224,0.875,bicubic,+5.906,+2.187,-26 +tv_resnet101,83.853,16.148,95.892,4.108,44.55,224,0.875,bilinear,+6.473,+2.348,+1 +tinynet_a,83.833,16.167,95.817,4.183,6.19,192,0.875,bicubic,+6.185,+2.281,-14 +inception_v3,83.763,16.237,95.877,4.123,23.83,299,0.875,bicubic,+6.325,+2.401,-3 +hardcorenas_d,83.759,16.241,95.736,4.264,7.50,224,0.875,bilinear,+6.329,+2.252,-3 +seresnext26d_32x4d,83.750,16.250,95.852,4.148,16.81,224,0.875,bicubic,+6.144,+2.246,-13 +xcit_nano_12_p8_224_dist,83.731,16.269,95.958,4.042,3.05,224,1.000,bicubic,+7.403,+2.864,+31 +dla60,83.720,16.280,95.926,4.074,22.04,224,0.875,bilinear,+6.698,+2.606,+9 +eca_resnext26ts,83.705,16.295,95.948,4.052,10.30,256,0.900,bicubic,+6.247,+2.380,-9 +repvgg_b1g4,83.697,16.303,96.025,3.975,39.97,224,0.875,bilinear,+6.109,+2.195,-16 +convmixer_1024_20_ks9_p14,83.686,16.314,95.894,4.106,24.38,224,0.960,bicubic,+6.744,+2.536,+10 +legacy_seresnet50,83.665,16.335,95.978,4.022,28.09,224,0.875,bilinear,+6.033,+2.228,-22 +tf_efficientnet_b0_ap,83.652,16.348,95.781,4.219,5.29,224,0.875,bicubic,+6.564,+2.523,+2 +tf_efficientnet_cc_b0_4e,83.639,16.361,95.743,4.257,13.31,224,0.875,bicubic,+6.329,+2.403,-9 +skresnet34,83.635,16.365,95.928,4.072,22.28,224,0.875,bicubic,+6.731,+2.608,+8 +resmlp_12_224,83.573,16.427,95.762,4.238,15.35,224,0.875,bicubic,+6.917,+2.582,+13 +mobilenetv3_large_100_miil,83.558,16.442,95.452,4.548,5.48,224,0.875,bilinear,+5.636,+2.532,-39 +densenet201,83.554,16.446,95.811,4.189,20.01,224,0.875,bicubic,+6.266,+2.331,-11 +mixnet_m,83.526,16.474,95.685,4.315,5.01,224,0.875,bicubic,+6.264,+2.263,-10 +legacy_seresnext26_32x4d,83.522,16.478,95.717,4.283,16.79,224,0.875,bicubic,+6.418,+2.401,-6 +gernet_s,83.517,16.483,95.796,4.204,8.17,224,0.875,bilinear,+6.601,+2.662,+1 +tf_efficientnet_b0,83.511,16.489,95.704,4.296,5.29,224,0.875,bicubic,+6.671,+2.486,+2 +hrnet_w18,83.502,16.498,95.909,4.091,21.30,224,0.875,bilinear,+6.742,+2.465,+4 +densenetblur121d,83.470,16.530,95.817,4.183,8.00,224,0.875,bicubic,+6.890,+2.629,+9 +resnext26ts,83.464,16.536,95.726,4.274,10.30,256,0.900,bicubic,+6.684,+2.594,+1 +selecsls42b,83.460,16.540,95.743,4.257,32.46,224,0.875,bicubic,+6.282,+2.351,-15 +hardcorenas_c,83.336,16.664,95.713,4.287,5.52,224,0.875,bilinear,+6.284,+2.553,-11 +tf_efficientnet_lite1,83.332,16.668,95.640,4.360,5.42,240,0.882,bicubic,+6.694,+2.416,+2 +regnetx_016,83.193,16.807,95.743,4.257,9.19,224,0.875,bicubic,+6.251,+2.319,-9 +dpn68,83.184,16.816,95.600,4.400,12.61,224,0.875,bicubic,+6.874,+2.622,+10 +mobilenetv2_140,83.180,16.820,95.687,4.313,6.11,224,0.875,bicubic,+6.668,+2.689,+5 +tf_efficientnet_es,83.176,16.824,95.585,4.415,5.44,224,0.875,bicubic,+6.578,+2.381,0 +tf_mixnet_m,83.176,16.824,95.459,4.541,5.01,224,0.875,bicubic,+6.230,+2.307,-14 +xcit_nano_12_p16_384_dist,83.174,16.826,95.751,4.249,3.05,384,1.000,bicubic,+7.718,+3.061,+22 +ese_vovnet19b_dw,83.109,16.890,95.775,4.225,6.54,224,0.875,bicubic,+6.315,+2.509,-10 +levit_128s,83.058,16.942,95.531,4.469,7.78,224,0.900,bicubic,+6.544,+2.661,-1 +resnet26d,83.056,16.944,95.610,4.390,16.01,224,0.875,bicubic,+6.354,+2.458,-9 +repvgg_a2,83.001,16.999,95.593,4.407,28.21,224,0.875,bilinear,+6.541,+2.583,-1 +tv_resnet50,82.956,17.044,95.474,4.526,25.56,224,0.875,bilinear,+6.822,+2.606,+2 +hardcorenas_b,82.866,17.134,95.390,4.610,5.18,224,0.875,bilinear,+6.330,+2.636,-6 +densenet121,82.826,17.174,95.580,4.420,7.98,224,0.875,bicubic,+7.246,+2.932,+10 +mobilevitv2_075,82.806,17.194,95.572,4.428,2.87,256,0.888,bicubic,+7.198,+2.814,+8 +vit_tiny_r_s16_p8_384,82.687,17.313,95.849,4.151,6.36,384,1.000,bicubic,+6.735,+2.587,+1 +densenet169,82.683,17.317,95.597,4.402,14.15,224,0.875,bicubic,+6.779,+2.573,+2 +mixnet_s,82.527,17.473,95.356,4.644,4.13,224,0.875,bicubic,+6.531,+2.556,-3 +vit_small_patch32_224,82.514,17.486,95.664,4.336,22.88,224,0.900,bicubic,+6.524,+2.396,-3 +regnety_008,82.493,17.508,95.491,4.509,6.26,224,0.875,bicubic,+6.179,+2.421,-8 +efficientnet_lite0,82.371,17.629,95.284,4.716,4.65,224,0.875,bicubic,+6.903,+2.768,+6 +resnest14d,82.354,17.646,95.346,4.654,10.61,224,0.875,bilinear,+6.846,+2.822,+4 +hardcorenas_a,82.324,17.676,95.290,4.710,5.26,224,0.875,bilinear,+6.394,+2.780,-5 +efficientnet_es_pruned,82.292,17.708,95.303,4.697,5.44,224,0.875,bicubic,+7.292,+2.861,+15 +mobilenetv3_rw,82.266,17.734,95.234,4.766,5.48,224,0.875,bicubic,+6.632,+2.526,-3 +semnasnet_100,82.251,17.749,95.226,4.774,3.89,224,0.875,bicubic,+6.801,+2.626,+4 +mobilenetv3_large_100,82.170,17.830,95.196,4.804,5.48,224,0.875,bicubic,+6.394,+2.656,-7 +resnet34,82.144,17.855,95.128,4.872,21.80,224,0.875,bilinear,+7.032,+2.844,+7 +vit_tiny_patch16_224,82.076,17.924,95.482,4.518,5.72,224,0.900,bicubic,+6.612,+2.638,-1 +mobilenetv2_110d,82.070,17.930,95.079,4.921,4.52,224,0.875,bicubic,+7.034,+2.887,+7 +tf_mixnet_s,82.040,17.960,95.121,4.879,4.13,224,0.875,bicubic,+6.388,+2.495,-10 +repvgg_b0,82.006,17.994,95.098,4.902,15.82,224,0.875,bilinear,+6.852,+2.682,+1 +deit_tiny_distilled_patch16_224,81.993,18.007,95.138,4.862,5.91,224,0.900,bicubic,+7.481,+3.248,+17 +mixer_b16_224,81.987,18.014,94.449,5.551,59.88,224,0.875,bicubic,+5.377,+2.219,-30 +pit_ti_distilled_224,81.969,18.031,95.147,4.853,5.10,224,0.900,bicubic,+7.435,+3.051,+14 +hrnet_w18_small_v2,81.961,18.039,95.164,4.836,15.60,224,0.875,bilinear,+6.851,+2.748,0 +tf_efficientnet_lite0,81.959,18.041,95.162,4.838,4.65,224,0.875,bicubic,+7.127,+2.988,+5 +resnet26,81.957,18.043,95.252,4.748,16.00,224,0.875,bicubic,+6.657,+2.672,-7 +edgenext_x_small,81.897,18.103,95.032,4.968,2.34,256,0.900,bicubic,+7.033,+2.732,+2 +tinynet_b,81.871,18.129,94.878,5.122,3.73,188,0.875,bicubic,+6.897,+2.696,0 +tf_mobilenetv3_large_100,81.848,18.152,95.066,4.934,5.48,224,0.875,bilinear,+6.336,+2.460,-16 +tv_densenet121,81.722,18.278,95.034,4.966,7.98,224,0.875,bicubic,+6.982,+2.886,+2 +regnety_006,81.703,18.297,95.121,4.879,6.06,224,0.875,bicubic,+6.451,+2.589,-11 +dla34,81.660,18.340,94.876,5.124,15.74,224,0.875,bilinear,+7.036,+2.804,+3 +xcit_nano_12_p8_224,81.645,18.355,95.267,4.733,3.05,224,1.000,bicubic,+7.729,+3.099,+11 +crossvit_9_240,81.613,18.387,94.974,5.026,8.55,240,0.875,bicubic,+7.653,+3.010,+9 +mobilevit_xs,81.574,18.426,95.030,4.970,2.32,256,0.900,bicubic,+6.940,+2.684,-1 +fbnetc_100,81.559,18.441,94.959,5.041,5.57,224,0.875,bilinear,+6.443,+2.573,-14 +legacy_seresnet34,81.538,18.462,94.897,5.103,21.96,224,0.875,bilinear,+6.728,+2.771,-6 +gluon_resnet34_v1b,81.498,18.503,94.808,5.192,21.80,224,0.875,bicubic,+6.906,+2.820,-2 +regnetx_008,81.481,18.520,95.064,4.936,7.26,224,0.875,bicubic,+6.447,+2.724,-13 +mnasnet_100,81.451,18.549,94.904,5.096,4.38,224,0.875,bicubic,+6.801,+2.790,-7 +vgg19_bn,81.442,18.558,94.767,5.233,143.68,224,0.875,bilinear,+7.228,+2.923,-2 +convit_tiny,81.126,18.874,95.047,4.953,5.71,224,0.875,bicubic,+8.012,+3.327,+10 +crossvit_tiny_240,81.096,18.904,94.985,5.015,7.01,240,0.875,bicubic,+7.758,+3.071,+6 +spnasnet_100,80.880,19.119,94.530,5.470,4.42,224,0.875,bilinear,+6.790,+2.714,-4 +ghostnet_100,80.703,19.297,94.291,5.709,5.18,224,0.875,bilinear,+6.723,+2.833,-3 +regnety_004,80.650,19.350,94.688,5.312,4.34,224,0.875,bicubic,+6.626,+2.932,-5 +skresnet18,80.639,19.361,94.376,5.624,11.96,224,0.875,bicubic,+7.605,+3.210,+6 +regnetx_006,80.633,19.367,94.526,5.474,6.20,224,0.875,bicubic,+6.777,+2.854,-3 +pit_ti_224,80.614,19.386,94.620,5.380,4.85,224,0.900,bicubic,+7.702,+3.214,+7 +swsl_resnet18,80.573,19.427,94.743,5.256,11.69,224,0.875,bilinear,+7.299,+3.007,+1 vgg16_bn,80.556,19.444,94.592,5.408,138.37,224,0.875,bilinear,+7.206,+3.088,-3 -semnasnet_075,80.473,19.527,94.323,5.677,2.91,224,0.875,bicubic,+7.501,+3.187,+2 -tv_resnet34,80.389,19.611,94.438,5.562,21.80,224,0.875,bilinear,+7.083,+3.014,-3 -resnet18d,80.385,19.615,94.246,5.754,11.71,224,0.875,bicubic,+8.135,+3.558,+8 -mobilenetv2_100,80.255,19.745,94.197,5.803,3.50,224,0.875,bicubic,+7.285,+3.177,0 -xcit_nano_12_p16_224_dist,80.216,19.784,94.359,5.641,3.05,224,1.000,bicubic,+7.914,+3.501,+5 -vit_base_patch32_224_sam,80.210,19.790,93.823,6.177,88.22,224,0.900,bicubic,+6.516,+2.813,-11 -ssl_resnet18,80.097,19.903,94.590,5.410,11.69,224,0.875,bilinear,+7.489,+3.166,-1 -tf_mobilenetv3_large_075,80.091,19.910,94.184,5.816,3.99,224,0.875,bilinear,+6.654,+2.840,-12 -deit_tiny_patch16_224,80.016,19.984,94.449,5.551,5.72,224,0.900,bicubic,+7.844,+3.335,+4 -hrnet_w18_small,79.565,20.435,93.896,6.104,13.19,224,0.875,bilinear,+7.227,+3.216,-1 -vgg19,79.478,20.522,93.868,6.132,143.67,224,0.875,bilinear,+7.112,+2.998,-3 -regnetx_004,79.422,20.578,93.851,6.149,5.16,224,0.875,bicubic,+7.030,+3.019,-5 -tf_mobilenetv3_large_minimal_100,79.224,20.776,93.702,6.298,3.92,224,0.875,bilinear,+6.974,+3.072,-1 -legacy_seresnet18,79.157,20.843,93.781,6.219,11.78,224,0.875,bicubic,+7.415,+3.449,+3 +semnasnet_075,80.475,19.525,94.319,5.681,2.91,224,0.875,bicubic,+7.501,+3.185,+2 +resnet18d,80.392,19.608,94.246,5.754,11.71,224,0.875,bicubic,+8.134,+3.558,+10 +tv_resnet34,80.389,19.611,94.436,5.564,21.80,224,0.875,bilinear,+7.081,+3.012,-4 +mobilenetv2_100,80.236,19.764,94.193,5.807,3.50,224,0.875,bicubic,+7.280,+3.183,0 +xcit_nano_12_p16_224_dist,80.214,19.786,94.355,5.645,3.05,224,1.000,bicubic,+7.912,+3.493,+6 +vit_base_patch32_224_sam,80.208,19.792,93.821,6.179,88.22,224,0.900,bicubic,+6.516,+2.809,-11 +ssl_resnet18,80.099,19.901,94.590,5.410,11.69,224,0.875,bilinear,+7.495,+3.166,-1 +tf_mobilenetv3_large_075,80.093,19.907,94.184,5.816,3.99,224,0.875,bilinear,+6.653,+2.836,-12 +deit_tiny_patch16_224,80.018,19.982,94.447,5.553,5.72,224,0.900,bicubic,+7.844,+3.333,+5 +hrnet_w18_small,79.557,20.443,93.902,6.098,13.19,224,0.875,bilinear,+7.221,+3.222,0 +vgg19,79.476,20.524,93.870,6.130,143.67,224,0.875,bilinear,+7.110,+2.998,-3 +regnetx_004,79.429,20.571,93.853,6.147,5.16,224,0.875,bicubic,+7.033,+3.015,-5 +resnet14t,79.243,20.757,93.603,6.397,10.08,224,0.950,bilinear,+6.887,+3.263,-4 +tf_mobilenetv3_large_minimal_100,79.228,20.772,93.693,6.307,3.92,224,0.875,bilinear,+6.978,+3.073,-1 +legacy_seresnet18,79.155,20.845,93.781,6.219,11.78,224,0.875,bicubic,+7.415,+3.451,+3 vgg16,79.034,20.966,93.646,6.354,138.36,224,0.875,bilinear,+7.444,+3.264,+4 -vgg13_bn,79.008,20.992,93.657,6.343,133.05,224,0.875,bilinear,+7.414,+3.281,+2 -vit_tiny_r_s16_p8_224,78.991,21.009,93.900,6.100,6.34,224,0.900,bicubic,+7.199,+3.078,-1 -lcnet_100,78.895,21.105,93.558,6.441,2.95,224,0.875,bicubic,+6.791,+3.182,-4 -tinynet_c,78.432,21.568,93.140,6.860,2.46,184,0.875,bicubic,+7.204,+3.390,+1 -gluon_resnet18_v1b,78.374,21.626,93.136,6.864,11.69,224,0.875,bicubic,+7.540,+3.374,+1 -vgg11_bn,77.926,22.074,93.230,6.770,132.87,224,0.875,bilinear,+7.566,+3.428,+1 -xcit_nano_12_p16_224,77.891,22.109,93.433,6.567,3.05,224,1.000,bicubic,+7.937,+3.678,+2 -regnety_002,77.411,22.589,92.907,7.093,3.16,224,0.875,bicubic,+7.157,+3.375,0 -mixer_l16_224,77.283,22.717,90.578,9.422,208.20,224,0.875,bicubic,+5.229,+2.916,-9 -resnet18,77.274,22.726,92.760,7.240,11.69,224,0.875,bilinear,+7.530,+3.678,+1 -vgg13,77.227,22.773,92.687,7.313,133.05,224,0.875,bilinear,+7.301,+3.441,-1 -mobilevit_xxs,76.602,23.398,92.692,7.308,1.27,256,0.900,bicubic,+7.682,+3.748,+1 -vgg11,76.393,23.607,92.154,7.846,132.86,224,0.875,bilinear,+7.365,+3.528,-1 -regnetx_002,76.117,23.883,92.209,7.791,2.68,224,0.875,bicubic,+7.361,+3.653,+1 -lcnet_075,76.057,23.943,92.064,7.936,2.36,224,0.875,bicubic,+7.241,+3.694,-1 -dla60x_c,75.637,24.363,92.177,7.823,1.32,224,0.875,bilinear,+7.745,+3.751,+1 -mobilenetv3_small_100,74.913,25.087,91.494,8.506,2.54,224,0.875,bicubic,+7.257,+3.860,+1 -tf_mobilenetv3_small_100,74.719,25.281,91.257,8.743,2.54,224,0.875,bilinear,+6.795,+3.593,-2 -tinynet_d,74.281,25.719,90.922,9.078,2.34,152,0.875,bicubic,+7.323,+3.858,0 -mnasnet_small,73.816,26.184,90.730,9.270,2.03,224,0.875,bicubic,+7.610,+4.222,0 -dla46x_c,73.647,26.353,91.095,8.905,1.07,224,0.875,bilinear,+7.677,+4.115,0 -mobilenetv2_050,73.463,26.537,90.317,9.682,1.97,224,0.875,bicubic,+7.521,+4.236,0 -tf_mobilenetv3_small_075,72.806,27.194,90.038,9.962,2.04,224,0.875,bilinear,+7.092,+3.904,0 -dla46_c,72.607,27.393,90.499,9.501,1.30,224,0.875,bilinear,+7.741,+4.205,+1 -mobilenetv3_small_075,72.325,27.675,89.671,10.329,2.04,224,0.875,bicubic,+7.083,+4.233,-1 -lcnet_050,70.393,29.607,88.825,11.175,1.88,224,0.875,bicubic,+7.293,+4.443,0 -tf_mobilenetv3_small_minimal_100,70.111,29.889,88.507,11.493,2.04,224,0.875,bilinear,+7.203,+4.273,0 -tinynet_e,66.813,33.187,86.274,13.726,2.04,106,0.875,bicubic,+6.957,+4.510,0 +vgg13_bn,79.006,20.994,93.661,6.339,133.05,224,0.875,bilinear,+7.408,+3.285,+2 +vit_tiny_r_s16_p8_224,78.993,21.007,93.898,6.102,6.34,224,0.900,bicubic,+7.199,+3.080,-1 +lcnet_100,78.912,21.088,93.561,6.439,2.95,224,0.875,bicubic,+6.802,+3.183,-4 +edgenext_xx_small,78.698,21.302,93.503,6.497,1.33,256,0.900,bicubic,+7.592,+3.471,+2 +tinynet_c,78.436,21.564,93.140,6.860,2.46,184,0.875,bicubic,+7.208,+3.392,0 +gluon_resnet18_v1b,78.376,21.624,93.136,6.864,11.69,224,0.875,bicubic,+7.538,+3.374,+1 +mobilevitv2_050,78.124,21.876,93.573,6.426,1.37,256,0.888,bicubic,+7.984,+3.643,+3 +vgg11_bn,77.926,22.074,93.230,6.770,132.87,224,0.875,bilinear,+7.566,+3.428,0 +xcit_nano_12_p16_224,77.900,22.100,93.430,6.570,3.05,224,1.000,bicubic,+7.946,+3.674,+2 +regnety_002,77.411,22.589,92.912,7.088,3.16,224,0.875,bicubic,+7.155,+3.378,-1 +mixer_l16_224,77.287,22.713,90.574,9.426,208.20,224,0.875,bicubic,+5.221,+2.908,-11 +resnet18,77.279,22.721,92.760,7.240,11.69,224,0.875,bilinear,+7.531,+3.676,+1 +vgg13,77.227,22.773,92.689,7.311,133.05,224,0.875,bilinear,+7.301,+3.443,-1 +mobilevit_xxs,76.602,23.398,92.694,7.306,1.27,256,0.900,bicubic,+7.682,+3.748,+1 +vgg11,76.393,23.607,92.154,7.846,132.86,224,0.875,bilinear,+7.365,+3.526,-1 +resnet10t,76.222,23.778,92.224,7.776,5.44,224,0.950,bilinear,+7.914,+4.144,+2 +regnetx_002,76.119,23.881,92.211,7.789,2.68,224,0.875,bicubic,+7.365,+3.655,0 +lcnet_075,76.051,23.949,92.068,7.932,2.36,224,0.875,bicubic,+7.237,+3.704,-2 +dla60x_c,75.618,24.382,92.179,7.821,1.32,224,0.875,bilinear,+7.738,+3.745,+1 +mobilenetv3_small_100,74.911,25.089,91.496,8.504,2.54,224,0.875,bicubic,+7.253,+3.862,+1 +tf_mobilenetv3_small_100,74.717,25.283,91.257,8.743,2.54,224,0.875,bilinear,+6.791,+3.589,-2 +tinynet_d,74.283,25.717,90.926,9.074,2.34,152,0.875,bicubic,+7.321,+3.862,0 +mnasnet_small,73.816,26.184,90.727,9.273,2.03,224,0.875,bicubic,+7.610,+4.221,0 +dla46x_c,73.632,26.368,91.110,8.890,1.07,224,0.875,bilinear,+7.680,+4.124,0 +mobilenetv2_050,73.468,26.532,90.317,9.682,1.97,224,0.875,bicubic,+7.524,+4.237,0 +tf_mobilenetv3_small_075,72.812,27.188,90.038,9.962,2.04,224,0.875,bilinear,+7.100,+3.908,0 +dla46_c,72.611,27.389,90.503,9.497,1.30,224,0.875,bilinear,+7.739,+4.201,+1 +mobilenetv3_small_075,72.323,27.677,89.671,10.329,2.04,224,0.875,bicubic,+7.085,+4.231,-1 +lcnet_050,70.385,29.616,88.821,11.179,1.88,224,0.875,bicubic,+7.291,+4.439,0 +tf_mobilenetv3_small_minimal_100,70.113,29.887,88.505,11.495,2.04,224,0.875,bilinear,+7.213,+4.271,0 +tinynet_e,66.813,33.187,86.276,13.724,2.04,106,0.875,bicubic,+6.957,+4.510,0 mobilenetv3_small_050,64.671,35.329,84.867,15.133,1.59,224,0.875,bicubic,+6.781,+4.673,0 diff --git a/results/results-imagenet.csv b/results/results-imagenet.csv index 78a58276..d475f4da 100644 --- a/results/results-imagenet.csv +++ b/results/results-imagenet.csv @@ -1,591 +1,669 @@ -model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation -beit_large_patch16_512,88.600,11.400,98.656,1.344,305.67,512,1.000,bicubic -beit_large_patch16_384,88.404,11.596,98.608,1.392,305.00,384,1.000,bicubic -tf_efficientnet_l2_ns,88.348,11.652,98.648,1.352,480.31,800,0.960,bicubic +model,top1,top1_err,top5,top5_err,param_count,img_size,crop_pct,interpolation +beit_large_patch16_512,88.602,11.398,98.656,1.344,305.67,512,1.000,bicubic +beit_large_patch16_384,88.406,11.594,98.606,1.394,305.00,384,1.000,bicubic +tf_efficientnet_l2_ns,88.350,11.650,98.650,1.350,480.31,800,0.960,bicubic tf_efficientnet_l2_ns_475,88.232,11.768,98.546,1.454,480.31,475,0.936,bicubic -convnext_xlarge_384_in22ft1k,87.546,12.454,98.486,1.514,350.20,384,1.000,bicubic -beit_large_patch16_224,87.474,12.526,98.304,1.696,304.43,224,0.900,bicubic -convnext_large_384_in22ft1k,87.396,12.604,98.368,1.632,197.77,384,1.000,bicubic -swin_large_patch4_window12_384,87.150,12.850,98.240,1.760,196.74,384,1.000,bicubic +deit3_large_patch16_384_in21ft1k,87.716,12.284,98.512,1.488,304.76,384,1.000,bicubic +convnext_xlarge_384_in22ft1k,87.544,12.456,98.486,1.514,350.20,384,1.000,bicubic +beit_large_patch16_224,87.476,12.524,98.304,1.696,304.43,224,0.900,bicubic +swinv2_large_window12to24_192to384_22kft1k,87.456,12.544,98.252,1.748,196.74,384,1.000,bicubic +convnext_large_384_in22ft1k,87.396,12.604,98.366,1.634,197.77,384,1.000,bicubic +deit3_huge_patch14_224_in21ft1k,87.180,12.820,98.260,1.740,632.13,224,1.000,bicubic +swin_large_patch4_window12_384,87.152,12.848,98.240,1.760,196.74,384,1.000,bicubic +swinv2_base_window12to24_192to384_22kft1k,87.108,12.892,98.236,1.764,87.92,384,1.000,bicubic vit_large_patch16_384,87.080,12.920,98.300,1.700,304.72,384,1.000,bicubic -volo_d5_512,87.042,12.958,97.968,2.032,296.09,512,1.150,bicubic +volo_d5_512,87.040,12.960,97.968,2.032,296.09,512,1.150,bicubic convnext_xlarge_in22ft1k,87.002,12.998,98.212,1.788,350.20,224,0.875,bicubic -volo_d5_448,86.952,13.048,97.940,2.060,295.91,448,1.150,bicubic -tf_efficientnet_b7_ns,86.838,13.162,98.096,1.904,66.35,600,0.949,bicubic +deit3_large_patch16_224_in21ft1k,86.982,13.018,98.238,1.762,304.37,224,1.000,bicubic +volo_d5_448,86.954,13.046,97.940,2.060,295.91,448,1.150,bicubic +swinv2_large_window12to16_192to256_22kft1k,86.946,13.054,98.110,1.890,196.74,256,0.900,bicubic +tf_efficientnet_b7_ns,86.832,13.168,98.096,1.904,66.35,600,0.949,bicubic beit_base_patch16_384,86.798,13.202,98.136,1.864,86.74,384,1.000,bicubic -volo_d4_448,86.790,13.210,97.882,2.118,193.41,448,1.150,bicubic +volo_d4_448,86.792,13.208,97.882,2.118,193.41,448,1.150,bicubic +deit3_base_patch16_384_in21ft1k,86.742,13.258,98.112,1.888,86.88,384,1.000,bicubic convnext_large_in22ft1k,86.636,13.364,98.028,1.972,197.77,224,0.875,bicubic -convnext_base_384_in22ft1k,86.544,13.456,98.190,1.810,88.59,384,1.000,bicubic +convnext_base_384_in22ft1k,86.542,13.458,98.190,1.810,88.59,384,1.000,bicubic volo_d3_448,86.496,13.504,97.710,2.290,86.63,448,1.000,bicubic -cait_m48_448,86.486,13.514,97.752,2.248,356.46,448,1.000,bicubic -tf_efficientnet_b6_ns,86.454,13.546,97.882,2.118,43.04,528,0.942,bicubic +cait_m48_448,86.488,13.512,97.750,2.250,356.46,448,1.000,bicubic +tf_efficientnet_b6_ns,86.450,13.550,97.886,2.114,43.04,528,0.942,bicubic swin_base_patch4_window12_384,86.432,13.568,98.056,1.944,87.90,384,1.000,bicubic -tf_efficientnetv2_xl_in21ft1k,86.418,13.582,97.866,2.134,208.12,512,1.000,bicubic -swin_large_patch4_window7_224,86.314,13.686,97.892,2.108,196.53,224,0.900,bicubic -tf_efficientnetv2_l_in21ft1k,86.304,13.696,97.978,2.022,118.52,480,1.000,bicubic -vit_large_r50_s32_384,86.182,13.818,97.920,2.080,329.09,384,1.000,bicubic +tf_efficientnetv2_xl_in21ft1k,86.420,13.580,97.868,2.132,208.12,512,1.000,bicubic +swin_large_patch4_window7_224,86.320,13.680,97.892,2.108,196.53,224,0.900,bicubic +tf_efficientnetv2_l_in21ft1k,86.304,13.696,97.980,2.020,118.52,480,1.000,bicubic +swinv2_base_window12to16_192to256_22kft1k,86.270,13.730,97.896,2.104,87.92,256,0.900,bicubic +vit_large_r50_s32_384,86.180,13.820,97.920,2.080,329.09,384,1.000,bicubic dm_nfnet_f6,86.142,13.858,97.730,2.270,438.36,576,0.956,bicubic -tf_efficientnet_b5_ns,86.090,13.910,97.750,2.250,30.39,456,0.934,bicubic -volo_d5_224,86.072,13.928,97.578,2.422,295.46,224,0.960,bicubic -cait_m36_384,86.052,13.948,97.730,2.270,271.22,384,1.000,bicubic -volo_d2_384,86.040,13.960,97.572,2.428,58.87,384,1.000,bicubic -vit_base_patch16_384,86.010,13.990,98.002,1.998,86.86,384,1.000,bicubic +tf_efficientnet_b5_ns,86.088,13.912,97.752,2.248,30.39,456,0.934,bicubic +volo_d5_224,86.070,13.930,97.578,2.422,295.46,224,0.960,bicubic +cait_m36_384,86.054,13.946,97.730,2.270,271.22,384,1.000,bicubic +volo_d2_384,86.036,13.964,97.574,2.426,58.87,384,1.000,bicubic +vit_base_patch16_384,86.006,13.994,98.004,1.996,86.86,384,1.000,bicubic xcit_large_24_p8_384_dist,85.998,14.002,97.684,2.316,188.93,384,1.000,bicubic -volo_d4_224,85.874,14.126,97.468,2.532,192.96,224,0.960,bicubic -vit_large_patch16_224,85.838,14.162,97.820,2.180,304.33,224,0.900,bicubic +volo_d4_224,85.876,14.124,97.468,2.532,192.96,224,0.960,bicubic +vit_large_patch16_224,85.844,14.156,97.822,2.178,304.33,224,0.900,bicubic convnext_base_in22ft1k,85.824,14.176,97.866,2.134,88.59,224,0.875,bicubic +xcit_medium_24_p8_384_dist,85.816,14.184,97.592,2.408,84.32,384,1.000,bicubic dm_nfnet_f5,85.816,14.184,97.486,2.514,377.21,544,0.954,bicubic -xcit_medium_24_p8_384_dist,85.814,14.186,97.592,2.408,84.32,384,1.000,bicubic -vit_base_patch8_224,85.794,14.206,97.794,2.206,86.58,224,0.900,bicubic -xcit_large_24_p16_384_dist,85.754,14.246,97.538,2.462,189.10,384,1.000,bicubic -dm_nfnet_f4,85.714,14.286,97.522,2.478,316.07,512,0.951,bicubic -tf_efficientnetv2_m_in21ft1k,85.590,14.410,97.744,2.256,54.14,480,1.000,bicubic -xcit_small_24_p8_384_dist,85.556,14.444,97.572,2.428,47.63,384,1.000,bicubic +deit3_large_patch16_384,85.806,14.194,97.596,2.404,304.76,384,1.000,bicubic +vit_base_patch8_224,85.790,14.210,97.792,2.208,86.58,224,0.900,bicubic +xcit_large_24_p16_384_dist,85.752,14.248,97.538,2.462,189.10,384,1.000,bicubic +convnext_small_384_in22ft1k,85.724,14.276,97.864,2.136,50.22,384,1.000,bicubic +deit3_base_patch16_224_in21ft1k,85.716,14.284,97.744,2.256,86.59,224,1.000,bicubic +dm_nfnet_f4,85.714,14.286,97.520,2.480,316.07,512,0.951,bicubic +tf_efficientnetv2_m_in21ft1k,85.586,14.414,97.746,2.254,54.14,480,1.000,bicubic +xcit_small_24_p8_384_dist,85.554,14.446,97.572,2.428,47.63,384,1.000,bicubic dm_nfnet_f3,85.522,14.478,97.462,2.538,254.92,416,0.940,bicubic -tf_efficientnetv2_l,85.490,14.510,97.372,2.628,118.52,480,1.000,bicubic -cait_s36_384,85.462,14.538,97.480,2.520,68.37,384,1.000,bicubic +tf_efficientnetv2_l,85.488,14.512,97.372,2.628,118.52,480,1.000,bicubic +cait_s36_384,85.460,14.540,97.478,2.522,68.37,384,1.000,bicubic ig_resnext101_32x48d,85.436,14.564,97.576,2.424,828.41,224,0.875,bilinear xcit_medium_24_p16_384_dist,85.422,14.578,97.406,2.594,84.40,384,1.000,bicubic deit_base_distilled_patch16_384,85.422,14.578,97.332,2.668,87.63,384,1.000,bicubic volo_d3_224,85.412,14.588,97.280,2.720,86.33,224,0.960,bicubic xcit_large_24_p8_224_dist,85.398,14.602,97.410,2.590,188.93,224,1.000,bicubic -tf_efficientnet_b8_ap,85.372,14.628,97.292,2.708,87.41,672,0.954,bicubic -tf_efficientnet_b8,85.368,14.632,97.390,2.610,87.41,672,0.954,bicubic -swin_base_patch4_window7_224,85.248,14.752,97.562,2.438,87.77,224,0.900,bicubic -volo_d1_384,85.248,14.752,97.214,2.786,26.78,384,1.000,bicubic -beit_base_patch16_224,85.228,14.772,97.658,2.342,86.53,224,0.900,bicubic +tf_efficientnet_b8_ap,85.372,14.628,97.294,2.706,87.41,672,0.954,bicubic +tf_efficientnet_b8,85.368,14.632,97.392,2.608,87.41,672,0.954,bicubic +swin_base_patch4_window7_224,85.250,14.750,97.562,2.438,87.77,224,0.900,bicubic +volo_d1_384,85.250,14.750,97.214,2.786,26.78,384,1.000,bicubic +beit_base_patch16_224,85.228,14.772,97.656,2.344,86.53,224,0.900,bicubic +deit3_huge_patch14_224,85.206,14.794,97.358,2.642,632.13,224,0.900,bicubic volo_d2_224,85.194,14.806,97.188,2.812,58.68,224,0.960,bicubic -tf_efficientnet_b4_ns,85.162,14.838,97.470,2.530,19.34,380,0.922,bicubic +tf_efficientnet_b4_ns,85.160,14.840,97.470,2.530,19.34,380,0.922,bicubic tf_efficientnet_b7_ap,85.120,14.880,97.252,2.748,66.35,600,0.949,bicubic ig_resnext101_32x32d,85.100,14.900,97.434,2.566,468.53,224,0.875,bilinear -xcit_small_24_p16_384_dist,85.094,14.906,97.310,2.690,47.67,384,1.000,bicubic +xcit_small_24_p16_384_dist,85.088,14.912,97.308,2.692,47.67,384,1.000,bicubic xcit_small_12_p8_384_dist,85.080,14.920,97.280,2.720,26.21,384,1.000,bicubic -xcit_medium_24_p8_224_dist,85.072,14.928,97.280,2.720,84.32,224,1.000,bicubic -dm_nfnet_f2,85.062,14.938,97.240,2.760,193.78,352,0.920,bicubic -cait_s24_384,85.046,14.954,97.346,2.654,47.06,384,1.000,bicubic -tf_efficientnetv2_m,85.038,14.962,97.278,2.722,54.14,480,1.000,bicubic +deit3_base_patch16_384,85.076,14.924,97.254,2.746,86.88,384,1.000,bicubic +xcit_medium_24_p8_224_dist,85.070,14.930,97.280,2.720,84.32,224,1.000,bicubic +dm_nfnet_f2,85.066,14.934,97.242,2.758,193.78,352,0.920,bicubic +cait_s24_384,85.050,14.950,97.348,2.652,47.06,384,1.000,bicubic +tf_efficientnetv2_m,85.036,14.964,97.278,2.722,54.14,480,1.000,bicubic regnetz_e8,85.030,14.970,97.264,2.736,57.70,320,1.000,bicubic -resnetrs420,85.010,14.990,97.124,2.876,191.89,416,1.000,bicubic -ecaresnet269d,84.976,15.024,97.226,2.774,102.09,352,1.000,bicubic -vit_base_r50_s16_384,84.970,15.030,97.290,2.710,98.95,384,1.000,bicubic -tf_efficientnet_b7,84.936,15.064,97.204,2.796,66.35,600,0.949,bicubic -xcit_large_24_p16_224_dist,84.922,15.078,97.132,2.868,189.10,224,1.000,bicubic -resnetv2_152x4_bitm,84.916,15.084,97.442,2.558,936.53,480,1.000,bilinear +resnetrs420,85.008,14.992,97.124,2.876,191.89,416,1.000,bicubic +vit_base_r50_s16_384,84.976,15.024,97.290,2.710,98.95,384,1.000,bicubic +ecaresnet269d,84.974,15.026,97.226,2.774,102.09,352,1.000,bicubic +tf_efficientnet_b7,84.934,15.066,97.206,2.794,66.35,600,0.949,bicubic +xcit_large_24_p16_224_dist,84.920,15.080,97.132,2.868,189.10,224,1.000,bicubic +resnetv2_152x4_bitm,84.918,15.082,97.442,2.558,936.53,480,1.000,bilinear xcit_small_24_p8_224_dist,84.876,15.124,97.188,2.812,47.63,224,1.000,bicubic +deit3_small_patch16_384_in21ft1k,84.824,15.176,97.484,2.516,22.21,384,1.000,bicubic efficientnetv2_rw_m,84.812,15.188,97.146,2.854,53.24,416,1.000,bicubic tf_efficientnet_b6_ap,84.786,15.214,97.138,2.862,43.04,528,0.942,bicubic -resnetrs350,84.718,15.282,96.988,3.012,163.96,384,1.000,bicubic -xcit_small_12_p16_384_dist,84.710,15.290,97.118,2.882,26.25,384,1.000,bicubic +deit3_large_patch16_224,84.762,15.238,97.038,2.962,304.37,224,0.900,bicubic +resnetrs350,84.712,15.288,96.990,3.010,163.96,384,1.000,bicubic +xcit_small_12_p16_384_dist,84.708,15.292,97.116,2.884,26.25,384,1.000,bicubic eca_nfnet_l2,84.696,15.304,97.264,2.736,56.72,384,1.000,bicubic -dm_nfnet_f1,84.624,15.376,97.100,2.900,132.63,320,0.910,bicubic -vit_base_patch16_224,84.528,15.472,97.294,2.706,86.57,224,0.900,bicubic -resnest269e,84.520,15.480,96.986,3.014,110.93,416,0.928,bicubic -resnetv2_152x2_bitm,84.506,15.494,97.434,2.566,236.34,448,1.000,bilinear +dm_nfnet_f1,84.624,15.376,97.098,2.902,132.63,320,0.910,bicubic +swinv2_base_window16_256,84.592,15.408,97.074,2.926,87.92,256,0.900,bicubic +seresnextaa101d_32x8d,84.572,15.428,97.070,2.930,93.59,288,1.000,bicubic +convnext_small_in22ft1k,84.568,15.432,97.396,2.604,50.22,224,0.875,bicubic +vit_base_patch16_224,84.530,15.470,97.296,2.704,86.57,224,0.900,bicubic +resnest269e,84.518,15.482,96.986,3.014,110.93,416,0.928,bicubic +resnetv2_152x2_bitm,84.510,15.490,97.434,2.566,236.34,448,1.000,bilinear regnetz_040h,84.496,15.504,97.006,2.994,28.94,320,1.000,bicubic -resnetv2_101x3_bitm,84.442,15.558,97.382,2.618,387.93,448,1.000,bilinear -resnetrs200,84.438,15.562,97.080,2.920,93.21,320,1.000,bicubic -resnetrs270,84.436,15.564,96.970,3.030,129.86,352,1.000,bicubic -vit_large_r50_s32_224,84.424,15.576,97.166,2.834,328.99,224,0.900,bicubic -resmlp_big_24_224_in22ft1k,84.394,15.606,97.120,2.880,129.14,224,0.875,bicubic -xcit_large_24_p8_224,84.394,15.606,96.656,3.344,188.93,224,1.000,bicubic -seresnet152d,84.360,15.640,97.040,2.960,66.84,320,1.000,bicubic -tf_efficientnetv2_s_in21ft1k,84.298,15.702,97.254,2.746,21.46,384,1.000,bicubic -convnext_large,84.292,15.708,96.894,3.106,197.77,224,0.875,bicubic -swsl_resnext101_32x8d,84.290,15.710,97.180,2.820,88.79,224,0.875,bilinear -xcit_medium_24_p16_224_dist,84.274,15.726,96.940,3.060,84.40,224,1.000,bicubic +resnetv2_101x3_bitm,84.444,15.556,97.382,2.618,387.93,448,1.000,bilinear +resnetrs200,84.440,15.560,97.080,2.920,93.21,320,1.000,bicubic +resnetrs270,84.436,15.564,96.974,3.026,129.86,352,1.000,bicubic +vit_large_r50_s32_224,84.430,15.570,97.166,2.834,328.99,224,0.900,bicubic +resmlp_big_24_224_in22ft1k,84.398,15.602,97.118,2.882,129.14,224,0.875,bicubic +xcit_large_24_p8_224,84.392,15.608,96.658,3.342,188.93,224,1.000,bicubic +seresnet152d,84.364,15.636,97.044,2.956,66.84,320,1.000,bicubic +seresnext101d_32x8d,84.362,15.638,96.918,3.082,93.59,288,1.000,bicubic +tf_efficientnetv2_s_in21ft1k,84.296,15.704,97.254,2.746,21.46,384,1.000,bicubic +convnext_large,84.296,15.704,96.894,3.106,197.77,224,0.875,bicubic +swsl_resnext101_32x8d,84.290,15.710,97.182,2.818,88.79,224,0.875,bilinear +xcit_medium_24_p16_224_dist,84.278,15.722,96.940,3.060,84.40,224,1.000,bicubic vit_base_patch16_224_miil,84.272,15.728,96.802,3.198,86.54,224,0.875,bilinear -tf_efficientnet_b5_ap,84.256,15.744,96.976,3.024,30.39,456,0.934,bicubic -xcit_small_12_p8_224_dist,84.236,15.764,96.874,3.126,26.21,224,1.000,bicubic -regnetz_040,84.234,15.766,96.932,3.068,27.12,320,1.000,bicubic -seresnext101_32x8d,84.204,15.796,96.876,3.124,93.57,288,1.000,bicubic +swinv2_base_window8_256,84.262,15.738,96.922,3.078,87.92,256,0.900,bicubic +tf_efficientnet_b5_ap,84.254,15.746,96.978,3.022,30.39,456,0.934,bicubic +regnetz_040,84.236,15.764,96.932,3.068,27.12,320,1.000,bicubic +xcit_small_12_p8_224_dist,84.230,15.770,96.874,3.126,26.21,224,1.000,bicubic +swinv2_small_window16_256,84.210,15.790,96.870,3.130,49.73,256,0.900,bicubic +seresnext101_32x8d,84.204,15.796,96.874,3.126,93.57,288,1.000,bicubic crossvit_18_dagger_408,84.194,15.806,96.818,3.182,44.61,408,1.000,bicubic ig_resnext101_32x16d,84.170,15.830,97.198,2.802,194.03,224,0.875,bilinear -volo_d1_224,84.162,15.838,96.776,3.224,26.63,224,0.960,bicubic -pit_b_distilled_224,84.140,15.860,96.856,3.144,74.79,224,0.900,bicubic -tf_efficientnet_b6,84.110,15.890,96.888,3.112,43.04,528,0.942,bicubic -cait_xs24_384,84.062,15.938,96.890,3.110,26.67,384,1.000,bicubic -regnetz_d8_evos,84.054,15.946,96.996,3.004,23.46,320,0.950,bicubic -regnetz_d8,84.052,15.948,96.994,3.006,23.37,320,1.000,bicubic -tf_efficientnet_b3_ns,84.048,15.952,96.908,3.092,12.23,300,0.904,bicubic -vit_small_r26_s32_384,84.042,15.958,97.328,2.672,36.47,384,1.000,bicubic -regnetz_d32,84.022,15.978,96.866,3.134,27.58,320,0.950,bicubic -resnetv2_50x3_bitm,84.014,15.986,97.124,2.876,217.32,448,1.000,bilinear -eca_nfnet_l1,84.012,15.988,97.028,2.972,41.41,320,1.000,bicubic -resnet200d,83.964,16.036,96.824,3.176,64.69,320,1.000,bicubic +volo_d1_224,84.164,15.836,96.774,3.226,26.63,224,0.960,bicubic +pit_b_distilled_224,84.142,15.858,96.856,3.144,74.79,224,0.900,bicubic +tf_efficientnet_b6,84.108,15.892,96.888,3.112,43.04,528,0.942,bicubic +convnext_tiny_384_in22ft1k,84.076,15.924,97.158,2.842,28.59,384,1.000,bicubic +cait_xs24_384,84.064,15.936,96.890,3.110,26.67,384,1.000,bicubic +regnetz_d8,84.052,15.948,96.996,3.004,23.37,320,1.000,bicubic +regnetz_d8_evos,84.050,15.950,96.996,3.004,23.46,320,0.950,bicubic +vit_small_r26_s32_384,84.048,15.952,97.328,2.672,36.47,384,1.000,bicubic +tf_efficientnet_b3_ns,84.048,15.952,96.912,3.088,12.23,300,0.904,bicubic +regnetz_d32,84.024,15.976,96.868,3.132,27.58,320,0.950,bicubic +resnetv2_50x3_bitm,84.012,15.988,97.126,2.874,217.32,448,1.000,bilinear +eca_nfnet_l1,84.012,15.988,97.032,2.968,41.41,320,1.000,bicubic +resnet200d,83.960,16.040,96.824,3.176,64.69,320,1.000,bicubic swin_s3_base_224,83.932,16.068,96.660,3.340,71.13,224,0.900,bicubic -regnety_080,83.926,16.074,96.888,3.112,39.18,288,1.000,bicubic -tf_efficientnetv2_s,83.886,16.114,96.696,3.304,21.46,384,1.000,bicubic -xcit_small_24_p16_224_dist,83.868,16.132,96.724,3.276,47.67,224,1.000,bicubic -resnetv2_152x2_bit_teacher_384,83.844,16.156,97.118,2.882,236.34,384,1.000,bicubic -convnext_base,83.838,16.162,96.750,3.250,88.59,224,0.875,bicubic -xcit_small_24_p8_224,83.838,16.162,96.636,3.364,47.63,224,1.000,bicubic -crossvit_15_dagger_408,83.836,16.164,96.784,3.216,28.50,408,1.000,bicubic +regnety_080,83.928,16.072,96.888,3.112,39.18,288,1.000,bicubic +tf_efficientnetv2_s,83.884,16.116,96.698,3.302,21.46,384,1.000,bicubic +xcit_small_24_p16_224_dist,83.870,16.130,96.732,3.268,47.67,224,1.000,bicubic +swinv2_small_window8_256,83.854,16.146,96.642,3.358,49.73,256,0.900,bicubic +resnetv2_152x2_bit_teacher_384,83.844,16.156,97.116,2.884,236.34,384,1.000,bicubic +convnext_base,83.840,16.160,96.750,3.250,88.59,224,0.875,bicubic +xcit_small_24_p8_224,83.840,16.160,96.636,3.364,47.63,224,1.000,bicubic +crossvit_15_dagger_408,83.838,16.162,96.780,3.220,28.50,408,1.000,bicubic resnest200e,83.828,16.172,96.892,3.108,70.20,320,0.909,bicubic -tf_efficientnet_b5,83.812,16.188,96.748,3.252,30.39,456,0.934,bicubic -efficientnetv2_rw_s,83.810,16.190,96.722,3.278,23.94,384,1.000,bicubic -vit_small_patch16_384,83.804,16.196,97.102,2.898,22.20,384,1.000,bicubic -swin_s3_small_224,83.768,16.232,96.452,3.548,49.74,224,0.900,bicubic -xcit_tiny_24_p8_384_dist,83.742,16.258,96.710,3.290,12.11,384,1.000,bicubic -xcit_medium_24_p8_224,83.736,16.264,96.394,3.606,84.32,224,1.000,bicubic -regnety_064,83.720,16.280,96.722,3.278,30.58,288,1.000,bicubic +tf_efficientnet_b5,83.814,16.186,96.748,3.252,30.39,456,0.934,bicubic +efficientnetv2_rw_s,83.810,16.190,96.724,3.276,23.94,384,1.000,bicubic +vit_small_patch16_384,83.800,16.200,97.100,2.900,22.20,384,1.000,bicubic +deit3_base_patch16_224,83.792,16.208,96.584,3.416,86.59,224,0.900,bicubic +swin_s3_small_224,83.774,16.226,96.452,3.548,49.74,224,0.900,bicubic +xcit_tiny_24_p8_384_dist,83.746,16.254,96.712,3.288,12.11,384,1.000,bicubic +xcit_medium_24_p8_224,83.738,16.262,96.394,3.606,84.32,224,1.000,bicubic +regnety_064,83.720,16.280,96.726,3.274,30.58,288,1.000,bicubic resnetrs152,83.714,16.286,96.614,3.386,86.62,320,1.000,bicubic -regnetv_064,83.714,16.286,96.746,3.254,30.58,288,1.000,bicubic -regnety_160,83.690,16.310,96.776,3.224,83.59,288,1.000,bicubic +regnetv_064,83.712,16.288,96.746,3.254,30.58,288,1.000,bicubic +regnety_160,83.692,16.308,96.776,3.224,83.59,288,1.000,bicubic twins_svt_large,83.680,16.320,96.594,3.406,99.27,224,0.900,bicubic -resnet152d,83.678,16.322,96.738,3.262,60.21,320,1.000,bicubic +resnet152d,83.678,16.322,96.740,3.260,60.21,320,1.000,bicubic resmlp_big_24_distilled_224,83.588,16.412,96.648,3.352,129.14,224,0.875,bicubic -jx_nest_base,83.556,16.444,96.362,3.638,67.72,224,0.875,bicubic -cait_s24_224,83.458,16.542,96.564,3.436,46.92,224,1.000,bicubic -efficientnet_b4,83.424,16.576,96.596,3.404,19.34,384,1.000,bicubic -deit_base_distilled_patch16_224,83.392,16.608,96.486,3.514,87.34,224,0.900,bicubic -dm_nfnet_f0,83.386,16.614,96.574,3.426,71.49,256,0.900,bicubic +jx_nest_base,83.554,16.446,96.364,3.636,67.72,224,0.875,bicubic +cs3se_edgenet_x,83.548,16.452,96.666,3.334,50.72,320,1.000,bicubic +swinv2_cr_small_ns_224,83.486,16.514,96.484,3.516,49.70,224,0.900,bicubic +cait_s24_224,83.458,16.542,96.562,3.438,46.92,224,1.000,bicubic +deit3_small_patch16_384,83.428,16.572,96.676,3.324,22.21,384,1.000,bicubic +efficientnet_b4,83.424,16.576,96.598,3.402,19.34,384,1.000,bicubic +sequencer2d_l,83.406,16.594,96.500,3.500,54.30,224,0.875,bicubic +mobilevitv2_200_384_in22ft1k,83.400,16.600,96.582,3.418,18.45,384,1.000,bicubic +deit_base_distilled_patch16_224,83.388,16.612,96.488,3.512,87.34,224,0.900,bicubic +dm_nfnet_f0,83.384,16.616,96.574,3.426,71.49,256,0.900,bicubic +vit_base_patch32_384,83.352,16.648,96.836,3.164,88.30,384,1.000,bicubic swsl_resnext101_32x16d,83.350,16.650,96.844,3.156,194.03,224,0.875,bilinear -xcit_small_12_p16_224_dist,83.350,16.650,96.414,3.586,26.25,224,1.000,bicubic -vit_base_patch32_384,83.348,16.652,96.834,3.166,88.30,384,1.000,bicubic -xcit_small_12_p8_224,83.344,16.656,96.480,3.520,26.21,224,1.000,bicubic -tf_efficientnet_b4_ap,83.252,16.748,96.394,3.606,19.34,380,0.922,bicubic -swsl_resnext101_32x4d,83.236,16.764,96.764,3.236,44.18,224,0.875,bilinear -swin_small_patch4_window7_224,83.216,16.784,96.324,3.676,49.61,224,0.900,bicubic -regnetv_040,83.200,16.800,96.662,3.338,20.64,288,1.000,bicubic -xception65,83.180,16.820,96.592,3.408,39.92,299,0.940,bicubic -convnext_small,83.150,16.850,96.432,3.568,50.22,224,0.875,bicubic -resnext101_64x4d,83.140,16.860,96.370,3.630,83.46,288,1.000,bicubic +xcit_small_12_p16_224_dist,83.346,16.654,96.418,3.582,26.25,224,1.000,bicubic +xcit_small_12_p8_224,83.340,16.660,96.480,3.520,26.21,224,1.000,bicubic +tf_efficientnet_b4_ap,83.248,16.752,96.392,3.608,19.34,380,0.922,bicubic +swsl_resnext101_32x4d,83.240,16.760,96.760,3.240,44.18,224,0.875,bilinear +swin_small_patch4_window7_224,83.218,16.782,96.326,3.674,49.61,224,0.900,bicubic +regnetv_040,83.198,16.802,96.664,3.336,20.64,288,1.000,bicubic +xception65,83.174,16.826,96.592,3.408,39.92,299,0.940,bicubic +convnext_small,83.150,16.850,96.430,3.570,50.22,224,0.875,bicubic +resnext101_64x4d,83.144,16.856,96.374,3.626,83.46,288,1.000,bicubic twins_svt_base,83.138,16.862,96.420,3.580,56.07,224,0.900,bicubic -twins_pcpvt_large,83.134,16.866,96.604,3.396,60.99,224,0.900,bicubic -xception65p,83.126,16.874,96.478,3.522,39.82,299,0.940,bicubic -jx_nest_small,83.118,16.882,96.330,3.670,38.35,224,0.875,bicubic -deit_base_patch16_384,83.106,16.894,96.368,3.632,86.86,384,1.000,bicubic -tresnet_m,83.070,16.930,96.120,3.880,31.39,224,0.875,bilinear -tresnet_xl_448,83.054,16.946,96.172,3.828,78.44,448,0.875,bilinear -regnety_040,83.036,16.964,96.506,3.494,20.65,288,1.000,bicubic +swinv2_cr_small_224,83.138,16.862,96.098,3.902,49.70,224,0.900,bicubic +twins_pcpvt_large,83.136,16.864,96.604,3.396,60.99,224,0.900,bicubic +xception65p,83.130,16.870,96.480,3.520,39.82,299,0.940,bicubic +jx_nest_small,83.120,16.880,96.330,3.670,38.35,224,0.875,bicubic +deit_base_patch16_384,83.106,16.894,96.370,3.630,86.86,384,1.000,bicubic +deit3_small_patch16_224_in21ft1k,83.076,16.924,96.776,3.224,22.06,224,1.000,bicubic +tresnet_m,83.074,16.926,96.120,3.880,31.39,224,0.875,bilinear +tresnet_xl_448,83.048,16.952,96.170,3.830,78.44,448,0.875,bilinear +regnety_040,83.036,16.964,96.510,3.490,20.65,288,1.000,bicubic tf_efficientnet_b4,83.024,16.976,96.300,3.700,19.34,380,0.922,bicubic -resnet101d,83.022,16.978,96.448,3.552,44.57,320,1.000,bicubic -xcit_large_24_p16_224,82.894,17.106,95.882,4.118,189.10,224,1.000,bicubic -resnest101e,82.890,17.110,96.318,3.682,48.28,256,0.875,bilinear -resnetv2_152x2_bit_teacher,82.872,17.128,96.570,3.430,236.34,224,0.875,bicubic -resnetv2_50x1_bit_distilled,82.822,17.178,96.528,3.472,25.55,224,0.875,bicubic -resnet152,82.820,17.180,96.130,3.870,60.19,224,0.950,bicubic -pnasnet5large,82.790,17.210,96.040,3.960,86.06,331,0.911,bicubic +resnet101d,83.022,16.978,96.446,3.554,44.57,320,1.000,bicubic +mobilevitv2_175_384_in22ft1k,82.934,17.066,96.430,3.570,14.25,384,1.000,bicubic +convnext_tiny_in22ft1k,82.912,17.088,96.624,3.376,28.59,224,0.875,bicubic +xcit_large_24_p16_224,82.892,17.108,95.878,4.122,189.10,224,1.000,bicubic +resnest101e,82.888,17.112,96.320,3.680,48.28,256,0.875,bilinear +resnetv2_152x2_bit_teacher,82.868,17.132,96.568,3.432,236.34,224,0.875,bicubic +resnetv2_50x1_bit_distilled,82.822,17.178,96.522,3.478,25.55,224,0.875,bicubic +resnet152,82.818,17.182,96.132,3.868,60.19,224,0.950,bicubic +swinv2_tiny_window16_256,82.810,17.190,96.230,3.770,28.35,256,0.900,bicubic +sequencer2d_m,82.808,17.192,96.268,3.732,38.31,224,0.875,bicubic +pnasnet5large,82.782,17.218,96.042,3.958,86.06,331,0.911,bicubic +vit_relpos_base_patch16_clsgap_224,82.760,17.240,96.174,3.826,86.43,224,0.900,bicubic nfnet_l0,82.752,17.248,96.518,3.482,35.07,288,1.000,bicubic -regnety_032,82.726,17.274,96.424,3.576,19.44,288,1.000,bicubic +regnety_032,82.724,17.276,96.422,3.578,19.44,288,1.000,bicubic +cs3edgenet_x,82.722,17.278,96.376,3.624,47.82,288,1.000,bicubic twins_pcpvt_base,82.708,17.292,96.350,3.650,43.83,224,0.900,bicubic -ig_resnext101_32x8d,82.700,17.300,96.630,3.370,88.79,224,0.875,bilinear -xcit_medium_24_p16_224,82.638,17.362,95.974,4.026,84.40,224,1.000,bicubic +ig_resnext101_32x8d,82.698,17.302,96.632,3.368,88.79,224,0.875,bilinear +cs3sedarknet_x,82.654,17.346,96.346,3.654,35.40,288,1.000,bicubic +xcit_medium_24_p16_224,82.638,17.362,95.978,4.022,84.40,224,1.000,bicubic regnetz_c16_evos,82.632,17.368,96.476,3.524,13.49,320,0.950,bicubic -nasnetalarge,82.626,17.374,96.046,3.954,88.75,331,0.911,bicubic -levit_384,82.588,17.412,96.022,3.978,39.13,224,0.900,bicubic -xcit_small_24_p16_224,82.580,17.420,96.006,3.994,47.67,224,1.000,bicubic -eca_nfnet_l0,82.576,17.424,96.490,3.510,24.14,288,1.000,bicubic +nasnetalarge,82.618,17.382,96.044,3.956,88.75,331,0.911,bicubic +mobilevitv2_150_384_in22ft1k,82.590,17.410,96.316,3.684,10.59,384,1.000,bicubic +levit_384,82.588,17.412,96.018,3.982,39.13,224,0.900,bicubic +xcit_small_24_p16_224,82.584,17.416,96.000,4.000,47.67,224,1.000,bicubic +eca_nfnet_l0,82.578,17.422,96.490,3.510,24.14,288,1.000,bicubic xcit_tiny_24_p16_384_dist,82.572,17.428,96.288,3.712,12.12,384,1.000,bicubic -xcit_tiny_24_p8_224_dist,82.564,17.436,96.170,3.830,12.11,224,1.000,bicubic -resnet61q,82.526,17.474,96.134,3.866,36.85,288,1.000,bicubic -crossvit_18_dagger_240,82.520,17.480,96.070,3.930,44.27,240,0.875,bicubic -regnetz_c16,82.516,17.484,96.360,3.640,13.46,320,0.940,bicubic -gc_efficientnetv2_rw_t,82.466,17.534,96.296,3.704,13.68,288,1.000,bicubic -poolformer_m48,82.462,17.538,95.958,4.042,73.47,224,0.950,bicubic -pit_b_224,82.446,17.554,95.710,4.290,73.76,224,0.900,bicubic -crossvit_18_240,82.398,17.602,96.058,3.942,43.27,240,0.875,bicubic -xcit_tiny_12_p8_384_dist,82.394,17.606,96.220,3.780,6.71,384,1.000,bicubic -tf_efficientnet_b2_ns,82.380,17.620,96.248,3.752,9.11,260,0.890,bicubic -resnet51q,82.362,17.638,96.180,3.820,35.70,288,1.000,bilinear +vit_relpos_medium_patch16_cls_224,82.562,17.438,96.066,3.934,38.76,224,0.900,bicubic +xcit_tiny_24_p8_224_dist,82.560,17.440,96.168,3.832,12.11,224,1.000,bicubic +regnetz_c16,82.520,17.480,96.360,3.640,13.46,320,0.940,bicubic +crossvit_18_dagger_240,82.520,17.480,96.068,3.932,44.27,240,0.875,bicubic +resnet61q,82.518,17.482,96.130,3.870,36.85,288,1.000,bicubic +vit_relpos_base_patch16_224,82.486,17.514,96.142,3.858,86.43,224,0.900,bicubic +gc_efficientnetv2_rw_t,82.466,17.534,96.298,3.702,13.68,288,1.000,bicubic +vit_relpos_medium_patch16_224,82.462,17.538,96.086,3.914,38.75,224,0.900,bicubic +poolformer_m48,82.460,17.540,95.958,4.042,73.47,224,0.950,bicubic +pit_b_224,82.444,17.556,95.712,4.288,73.76,224,0.900,bicubic +crossvit_18_240,82.398,17.602,96.054,3.946,43.27,240,0.875,bicubic +xcit_tiny_12_p8_384_dist,82.386,17.614,96.222,3.778,6.71,384,1.000,bicubic +tf_efficientnet_b2_ns,82.384,17.616,96.246,3.754,9.11,260,0.890,bicubic +resnet51q,82.358,17.642,96.178,3.822,35.70,288,1.000,bilinear ecaresnet50t,82.348,17.652,96.138,3.862,25.57,320,0.950,bicubic efficientnetv2_rw_t,82.344,17.656,96.196,3.804,13.65,288,1.000,bicubic -resnetv2_101x1_bitm,82.336,17.664,96.516,3.484,44.54,448,1.000,bilinear -crossvit_15_dagger_240,82.330,17.670,95.958,4.042,28.21,240,0.875,bicubic -mixer_b16_224_miil,82.308,17.692,95.718,4.282,59.88,224,0.875,bilinear -coat_lite_small,82.304,17.696,95.848,4.152,19.84,224,0.900,bicubic -resnetrs101,82.288,17.712,96.010,3.990,63.62,288,0.940,bicubic -convit_base,82.286,17.714,95.938,4.062,86.54,224,0.875,bicubic -tresnet_l_448,82.268,17.732,95.982,4.018,55.99,448,0.875,bilinear -efficientnet_b3,82.240,17.760,96.114,3.886,12.23,320,1.000,bicubic -convnext_tiny_hnf,82.222,17.778,95.866,4.134,28.59,224,0.950,bicubic -crossvit_base_240,82.216,17.784,95.834,4.166,105.03,240,0.875,bicubic -cait_xxs36_384,82.194,17.806,96.144,3.856,17.37,384,1.000,bicubic +sequencer2d_s,82.344,17.656,96.034,3.966,27.65,224,0.875,bicubic +mobilevitv2_200_in22ft1k,82.334,17.666,95.938,4.062,18.45,256,0.888,bicubic +resnetv2_101x1_bitm,82.332,17.668,96.516,3.484,44.54,448,1.000,bilinear +crossvit_15_dagger_240,82.326,17.674,95.956,4.044,28.21,240,0.875,bicubic +coat_lite_small,82.304,17.696,95.850,4.150,19.84,224,0.900,bicubic +mixer_b16_224_miil,82.304,17.696,95.720,4.280,59.88,224,0.875,bilinear +vit_relpos_medium_patch16_rpn_224,82.294,17.706,95.972,4.028,38.73,224,0.900,bicubic +convit_base,82.292,17.708,95.938,4.062,86.54,224,0.875,bicubic +resnetrs101,82.284,17.716,96.008,3.992,63.62,288,0.940,bicubic +tresnet_l_448,82.270,17.730,95.980,4.020,55.99,448,0.875,bilinear +efficientnet_b3,82.240,17.760,96.118,3.882,12.23,320,1.000,bicubic +vit_srelpos_medium_patch16_224,82.236,17.764,95.934,4.066,38.74,224,0.900,bicubic +cs3darknet_x,82.224,17.776,96.230,3.770,35.05,288,1.000,bicubic +convnext_tiny_hnf,82.220,17.780,95.866,4.134,28.59,224,0.950,bicubic +crossvit_base_240,82.216,17.784,95.832,4.168,105.03,240,0.875,bicubic +vit_base_patch16_rpn_224,82.200,17.800,95.996,4.004,86.54,224,0.900,bicubic +cait_xxs36_384,82.192,17.808,96.144,3.856,17.37,384,1.000,bicubic swsl_resnext50_32x4d,82.176,17.824,96.232,3.768,25.03,224,0.875,bilinear -ecaresnet101d,82.172,17.828,96.046,3.954,44.57,224,0.875,bicubic -swin_s3_tiny_224,82.126,17.874,95.950,4.050,28.33,224,0.900,bicubic -poolformer_m36,82.112,17.888,95.690,4.310,56.17,224,0.950,bicubic -visformer_small,82.106,17.894,95.874,4.126,40.22,224,0.900,bicubic -convnext_tiny,82.064,17.936,95.852,4.148,28.59,224,0.875,bicubic -halo2botnet50ts_256,82.060,17.940,95.642,4.358,22.64,256,0.950,bicubic -tresnet_xl,82.058,17.942,95.936,4.064,78.44,224,0.875,bilinear -fbnetv3_g,82.046,17.954,96.064,3.936,16.62,288,0.950,bilinear -resnetv2_101,82.042,17.958,95.864,4.136,44.54,224,0.950,bicubic -deit_base_patch16_224,81.996,18.004,95.732,4.268,86.57,224,0.900,bicubic -pit_s_distilled_224,81.994,18.006,95.798,4.202,24.04,224,0.900,bicubic -resnetv2_50d_evos,81.980,18.020,95.910,4.090,25.59,288,0.950,bicubic -xcit_small_12_p16_224,81.976,18.024,95.818,4.182,26.25,224,1.000,bicubic -tf_efficientnetv2_b3,81.966,18.034,95.780,4.220,14.36,300,0.904,bicubic -xception41p,81.960,18.040,95.794,4.206,26.91,299,0.940,bicubic -resnet101,81.932,18.068,95.770,4.230,44.55,224,0.950,bicubic -xcit_tiny_24_p8_224,81.892,18.108,95.976,4.024,12.11,224,1.000,bicubic -vit_small_r26_s32_224,81.856,18.144,96.020,3.980,36.43,224,0.900,bicubic -ssl_resnext101_32x16d,81.854,18.146,96.096,3.904,194.03,224,0.875,bilinear -tf_efficientnet_b3_ap,81.826,18.174,95.622,4.378,12.23,300,0.904,bicubic -resnetv2_50d_gn,81.818,18.182,95.922,4.078,25.57,288,0.950,bicubic -tresnet_m_448,81.704,18.296,95.572,4.428,31.39,448,0.875,bilinear -twins_svt_small,81.680,18.320,95.670,4.330,24.06,224,0.900,bicubic -halonet50ts,81.660,18.340,95.612,4.388,22.73,256,0.940,bicubic -tf_efficientnet_b3,81.636,18.364,95.718,4.282,12.23,300,0.904,bicubic -rexnet_200,81.630,18.370,95.668,4.332,16.37,224,0.875,bicubic +ecaresnet101d,82.170,17.830,96.048,3.952,44.57,224,0.875,bicubic +swin_s3_tiny_224,82.124,17.876,95.950,4.050,28.33,224,0.900,bicubic +visformer_small,82.108,17.892,95.876,4.124,40.22,224,0.900,bicubic +poolformer_m36,82.108,17.892,95.690,4.310,56.17,224,0.950,bicubic +halo2botnet50ts_256,82.068,17.932,95.642,4.358,22.64,256,0.950,bicubic +tresnet_xl,82.062,17.938,95.936,4.064,78.44,224,0.875,bilinear +convnext_tiny,82.062,17.938,95.854,4.146,28.59,224,0.875,bicubic +resnetv2_101,82.046,17.954,95.862,4.138,44.54,224,0.950,bicubic +fbnetv3_g,82.034,17.966,96.066,3.934,16.62,288,0.950,bilinear +pit_s_distilled_224,81.994,18.006,95.796,4.204,24.04,224,0.900,bicubic +deit_base_patch16_224,81.994,18.006,95.732,4.268,86.57,224,0.900,bicubic +resnetv2_50d_evos,81.978,18.022,95.912,4.088,25.59,288,0.950,bicubic +xcit_small_12_p16_224,81.972,18.028,95.812,4.188,26.25,224,1.000,bicubic +xception41p,81.968,18.032,95.794,4.206,26.91,299,0.940,bicubic +tf_efficientnetv2_b3,81.966,18.034,95.782,4.218,14.36,300,0.904,bicubic +mobilevitv2_175_in22ft1k,81.940,18.060,95.790,4.210,14.25,256,0.888,bicubic +resnet101,81.930,18.070,95.766,4.234,44.55,224,0.950,bicubic +xcit_tiny_24_p8_224,81.896,18.104,95.974,4.026,12.11,224,1.000,bicubic +vit_small_r26_s32_224,81.862,18.138,96.022,3.978,36.43,224,0.900,bicubic +ssl_resnext101_32x16d,81.856,18.144,96.096,3.904,194.03,224,0.875,bilinear +resnetv2_50d_gn,81.824,18.176,95.924,4.076,25.57,288,0.950,bicubic +tf_efficientnet_b3_ap,81.824,18.176,95.624,4.376,12.23,300,0.904,bicubic +swinv2_tiny_window8_256,81.810,18.190,95.994,4.006,28.35,256,0.900,bicubic +swinv2_cr_tiny_ns_224,81.786,18.214,95.822,4.178,28.33,224,0.900,bicubic +cs3sedarknet_l,81.776,18.224,95.970,4.030,21.91,288,0.950,bicubic +tresnet_m_448,81.706,18.294,95.572,4.428,31.39,448,0.875,bilinear +twins_svt_small,81.682,18.318,95.666,4.334,24.06,224,0.900,bicubic +halonet50ts,81.652,18.348,95.612,4.388,22.73,256,0.940,bicubic +tf_efficientnet_b3,81.638,18.362,95.718,4.282,12.23,300,0.904,bicubic +rexnet_200,81.628,18.372,95.668,4.332,16.37,224,0.875,bicubic +resnetaa50,81.618,18.382,95.810,4.190,25.56,288,1.000,bicubic ssl_resnext101_32x8d,81.608,18.392,96.042,3.958,88.79,224,0.875,bilinear -lamhalobotnet50ts_256,81.546,18.454,95.502,4.498,22.57,256,0.950,bicubic -crossvit_15_240,81.542,18.458,95.690,4.310,27.53,240,0.875,bicubic -tf_efficientnet_lite4,81.536,18.464,95.668,4.332,13.01,380,0.920,bilinear -tnt_s_patch16_224,81.520,18.480,95.744,4.256,23.76,224,0.900,bicubic -levit_256,81.506,18.494,95.492,4.508,18.89,224,0.900,bicubic -vit_large_patch32_384,81.506,18.494,96.094,3.906,306.63,384,1.000,bicubic -tresnet_l,81.492,18.508,95.624,4.376,55.99,224,0.875,bilinear -wide_resnet50_2,81.452,18.548,95.530,4.470,68.88,224,0.875,bicubic -convit_small,81.420,18.580,95.740,4.260,27.78,224,0.875,bicubic -jx_nest_tiny,81.420,18.580,95.618,4.382,17.06,224,0.875,bicubic -poolformer_s36,81.418,18.582,95.450,4.550,30.86,224,0.900,bicubic -vit_small_patch16_224,81.396,18.604,96.132,3.868,22.05,224,0.900,bicubic -tf_efficientnet_b1_ns,81.388,18.612,95.736,4.264,7.79,240,0.882,bicubic -swin_tiny_patch4_window7_224,81.374,18.626,95.544,4.456,28.29,224,0.900,bicubic -convmixer_1536_20,81.366,18.634,95.614,4.386,51.63,224,0.960,bicubic -gernet_l,81.344,18.656,95.532,4.468,31.08,256,0.875,bilinear -efficientnet_el,81.310,18.690,95.530,4.470,10.59,300,0.904,bicubic -legacy_senet154,81.310,18.690,95.496,4.504,115.09,224,0.875,bilinear -coat_mini,81.266,18.734,95.394,4.606,10.34,224,0.900,bicubic -seresnext50_32x4d,81.258,18.742,95.630,4.370,27.56,224,0.875,bicubic -gluon_senet154,81.232,18.768,95.348,4.652,115.09,224,0.875,bicubic +edgenext_small,81.574,18.426,95.714,4.286,5.59,320,1.000,bicubic +lamhalobotnet50ts_256,81.552,18.448,95.504,4.496,22.57,256,0.950,bicubic +crossvit_15_240,81.544,18.456,95.690,4.310,27.53,240,0.875,bicubic +tf_efficientnet_lite4,81.534,18.466,95.666,4.334,13.01,380,0.920,bilinear +tnt_s_patch16_224,81.518,18.482,95.746,4.254,23.76,224,0.900,bicubic +levit_256,81.516,18.484,95.490,4.510,18.89,224,0.900,bicubic +vit_large_patch32_384,81.508,18.492,96.090,3.910,306.63,384,1.000,bicubic +tresnet_l,81.490,18.510,95.626,4.374,55.99,224,0.875,bilinear +convnext_nano,81.476,18.524,95.660,4.340,15.59,288,1.000,bicubic +mobilevitv2_150_in22ft1k,81.470,18.530,95.668,4.332,10.59,256,0.888,bicubic +wide_resnet50_2,81.456,18.544,95.530,4.470,68.88,224,0.875,bicubic +vit_relpos_small_patch16_224,81.454,18.546,95.828,4.172,21.98,224,0.900,bicubic +convit_small,81.428,18.572,95.742,4.258,27.78,224,0.875,bicubic +jx_nest_tiny,81.418,18.582,95.618,4.382,17.06,224,0.875,bicubic +poolformer_s36,81.418,18.582,95.448,4.552,30.86,224,0.900,bicubic +vit_small_patch16_224,81.396,18.604,96.138,3.862,22.05,224,0.900,bicubic +tf_efficientnet_b1_ns,81.386,18.614,95.736,4.264,7.79,240,0.882,bicubic +deit3_small_patch16_224,81.382,18.618,95.450,4.550,22.06,224,0.900,bicubic +swin_tiny_patch4_window7_224,81.376,18.624,95.542,4.458,28.29,224,0.900,bicubic +convmixer_1536_20,81.370,18.630,95.612,4.388,51.63,224,0.960,bicubic +gernet_l,81.350,18.650,95.536,4.464,31.08,256,0.875,bilinear +legacy_senet154,81.308,18.692,95.496,4.504,115.09,224,0.875,bilinear +efficientnet_el,81.306,18.694,95.534,4.466,10.59,300,0.904,bicubic +coat_mini,81.266,18.734,95.392,4.608,10.34,224,0.900,bicubic +seresnext50_32x4d,81.262,18.738,95.628,4.372,27.56,224,0.875,bicubic +gluon_senet154,81.230,18.770,95.346,4.654,115.09,224,0.875,bicubic +xcit_tiny_12_p8_224_dist,81.208,18.792,95.606,4.394,6.71,224,1.000,bicubic deit_small_distilled_patch16_224,81.208,18.792,95.374,4.626,22.44,224,0.900,bicubic -xcit_tiny_12_p8_224_dist,81.208,18.792,95.600,4.400,6.71,224,1.000,bicubic -swsl_resnet50,81.174,18.826,95.978,4.022,25.56,224,0.875,bilinear -sebotnet33ts_256,81.156,18.844,95.170,4.830,13.70,256,0.940,bicubic -resmlp_36_distilled_224,81.154,18.846,95.488,4.512,44.69,224,0.875,bicubic -lambda_resnet50ts,81.146,18.854,95.102,4.898,21.54,256,0.950,bicubic -resnest50d_4s2x40d,81.110,18.890,95.564,4.436,30.42,224,0.875,bicubic -resnext50_32x4d,81.108,18.892,95.326,4.674,25.03,224,0.950,bicubic -pit_s_224,81.100,18.900,95.330,4.670,23.46,224,0.900,bicubic -twins_pcpvt_small,81.090,18.910,95.640,4.360,24.11,224,0.900,bicubic -haloregnetz_b,81.050,18.950,95.196,4.804,11.68,224,0.940,bicubic -resmlp_big_24_224,81.032,18.968,95.020,4.980,129.14,224,0.875,bicubic -crossvit_small_240,81.018,18.982,95.456,4.544,26.86,240,0.875,bicubic -gluon_resnet152_v1s,81.016,18.984,95.412,4.588,60.32,224,0.875,bicubic -resnest50d_1s4x24d,80.990,19.010,95.324,4.676,25.68,224,0.875,bicubic -resnest50d,80.982,19.018,95.380,4.620,27.48,224,0.875,bilinear -cait_xxs24_384,80.966,19.034,95.646,4.354,12.03,384,1.000,bicubic -sehalonet33ts,80.964,19.036,95.272,4.728,13.69,256,0.940,bicubic -xcit_tiny_12_p16_384_dist,80.944,19.056,95.412,4.588,6.72,384,1.000,bicubic -gcresnet50t,80.942,19.058,95.454,4.546,25.90,256,0.900,bicubic +swsl_resnet50,81.180,18.820,95.980,4.020,25.56,224,0.875,bilinear +resmlp_36_distilled_224,81.156,18.844,95.486,4.514,44.69,224,0.875,bicubic +sebotnet33ts_256,81.154,18.846,95.166,4.834,13.70,256,0.940,bicubic +lambda_resnet50ts,81.152,18.848,95.102,4.898,21.54,256,0.950,bicubic +mobilevitv2_200,81.140,18.860,95.368,4.632,18.45,256,0.888,bicubic +resnest50d_4s2x40d,81.108,18.892,95.562,4.438,30.42,224,0.875,bicubic +vit_srelpos_small_patch16_224,81.098,18.902,95.572,4.428,21.97,224,0.900,bicubic +pit_s_224,81.098,18.902,95.332,4.668,23.46,224,0.900,bicubic +resnext50_32x4d,81.096,18.904,95.326,4.674,25.03,224,0.950,bicubic +twins_pcpvt_small,81.090,18.910,95.642,4.358,24.11,224,0.900,bicubic +haloregnetz_b,81.044,18.956,95.198,4.802,11.68,224,0.940,bicubic +resmlp_big_24_224,81.030,18.970,95.020,4.980,129.14,224,0.875,bicubic +crossvit_small_240,81.016,18.984,95.456,4.544,26.86,240,0.875,bicubic +gluon_resnet152_v1s,81.014,18.986,95.414,4.586,60.32,224,0.875,bicubic +resnest50d_1s4x24d,80.984,19.016,95.324,4.676,25.68,224,0.875,bicubic +resnest50d,80.974,19.026,95.380,4.620,27.48,224,0.875,bilinear +sehalonet33ts,80.972,19.028,95.272,4.728,13.69,256,0.940,bicubic +cait_xxs24_384,80.962,19.038,95.644,4.356,12.03,384,1.000,bicubic +xcit_tiny_12_p16_384_dist,80.942,19.058,95.408,4.592,6.72,384,1.000,bicubic +gcresnet50t,80.934,19.066,95.454,4.546,25.90,256,0.900,bicubic ssl_resnext101_32x4d,80.924,19.076,95.726,4.274,44.18,224,0.875,bilinear -gluon_seresnext101_32x4d,80.906,19.094,95.294,4.706,48.96,224,0.875,bicubic -gluon_seresnext101_64x4d,80.878,19.122,95.298,4.702,88.23,224,0.875,bicubic +gluon_seresnext101_32x4d,80.906,19.094,95.296,4.704,48.96,224,0.875,bicubic +cs3darknet_l,80.886,19.114,95.668,4.332,21.16,288,0.950,bicubic +gluon_seresnext101_64x4d,80.880,19.120,95.296,4.704,88.23,224,0.875,bicubic +cs3darknet_focus_l,80.874,19.126,95.692,4.308,21.15,288,0.950,bicubic +mobilevitv2_175,80.862,19.138,95.262,4.738,14.25,256,0.888,bicubic efficientnet_b3_pruned,80.858,19.142,95.244,4.756,9.86,300,0.904,bicubic -ecaresnet101d_pruned,80.814,19.186,95.630,4.370,24.88,224,0.875,bicubic -regnety_320,80.810,19.190,95.244,4.756,145.05,224,0.875,bicubic -resmlp_24_distilled_224,80.764,19.236,95.224,4.776,30.02,224,0.875,bicubic -gernet_m,80.744,19.256,95.184,4.816,21.14,224,0.875,bilinear -vit_base_patch32_224,80.722,19.278,95.566,4.434,88.22,224,0.900,bicubic -regnetz_b16,80.714,19.286,95.478,4.522,9.72,288,0.940,bicubic +ecaresnet101d_pruned,80.810,19.190,95.628,4.372,24.88,224,0.875,bicubic +regnety_320,80.804,19.196,95.244,4.756,145.05,224,0.875,bicubic +resmlp_24_distilled_224,80.764,19.236,95.222,4.778,30.02,224,0.875,bicubic +gernet_m,80.730,19.270,95.186,4.814,21.14,224,0.875,bilinear +vit_base_patch32_224,80.724,19.276,95.566,4.434,88.22,224,0.900,bicubic +regnetz_b16,80.712,19.288,95.474,4.526,9.72,288,0.940,bicubic nf_resnet50,80.654,19.346,95.334,4.666,25.56,288,0.940,bicubic -efficientnet_b2,80.614,19.386,95.316,4.684,9.11,288,1.000,bicubic +efficientnet_b2,80.616,19.384,95.316,4.684,9.11,288,1.000,bicubic gluon_resnext101_64x4d,80.604,19.396,94.992,5.008,83.46,224,0.875,bicubic -ecaresnet50d,80.600,19.400,95.320,4.680,25.58,224,0.875,bicubic +ecaresnet50d,80.598,19.402,95.318,4.682,25.58,224,0.875,bicubic gcresnext50ts,80.578,19.422,95.170,4.830,15.67,256,0.900,bicubic -resnet50d,80.522,19.478,95.162,4.838,25.58,224,0.875,bicubic +cspresnext50,80.544,19.456,95.324,4.676,20.57,256,0.887,bilinear +darknet53,80.538,19.462,95.420,4.580,41.61,288,1.000,bicubic +resnet50d,80.528,19.472,95.168,4.832,25.58,224,0.875,bicubic +darknetaa53,80.522,19.478,95.326,4.674,36.02,288,1.000,bilinear repvgg_b3,80.496,19.504,95.264,4.736,123.09,224,0.875,bilinear -vit_small_patch32_384,80.484,19.516,95.600,4.400,22.92,384,1.000,bicubic -gluon_resnet152_v1d,80.476,19.524,95.204,4.796,60.21,224,0.875,bicubic -mixnet_xl,80.474,19.526,94.934,5.066,11.90,224,0.875,bicubic -inception_resnet_v2,80.460,19.540,95.308,4.692,55.84,299,0.897,bicubic -ecaresnetlight,80.452,19.548,95.250,4.750,30.16,224,0.875,bicubic -xcit_tiny_24_p16_224_dist,80.446,19.554,95.216,4.784,12.12,224,1.000,bicubic -resnetv2_50,80.420,19.580,95.074,4.926,25.55,224,0.950,bicubic -gluon_resnet101_v1d,80.420,19.580,95.016,4.984,44.57,224,0.875,bicubic -resnet50,80.376,19.624,94.616,5.384,25.56,224,0.950,bicubic -regnety_120,80.376,19.624,95.126,4.874,51.82,224,0.875,bicubic -seresnet33ts,80.350,19.650,95.106,4.894,19.78,256,0.900,bicubic -gluon_resnext101_32x4d,80.344,19.656,94.926,5.074,44.18,224,0.875,bicubic -resnetv2_50x1_bitm,80.342,19.658,95.680,4.320,25.55,448,1.000,bilinear -ssl_resnext50_32x4d,80.316,19.684,95.410,4.590,25.03,224,0.875,bilinear -poolformer_s24,80.314,19.686,95.046,4.954,21.39,224,0.900,bicubic -rexnet_150,80.310,19.690,95.166,4.834,9.73,224,0.875,bicubic +vit_small_patch32_384,80.490,19.510,95.600,4.400,22.92,384,1.000,bicubic +mixnet_xl,80.478,19.522,94.934,5.066,11.90,224,0.875,bicubic +gluon_resnet152_v1d,80.476,19.524,95.200,4.800,60.21,224,0.875,bicubic +inception_resnet_v2,80.460,19.540,95.306,4.694,55.84,299,0.897,bicubic +ecaresnetlight,80.456,19.544,95.246,4.754,30.16,224,0.875,bicubic +edgenext_small_rw,80.452,19.548,95.190,4.810,7.83,320,1.000,bicubic +xcit_tiny_24_p16_224_dist,80.448,19.552,95.212,4.788,12.12,224,1.000,bicubic +gluon_resnet101_v1d,80.418,19.582,95.014,4.986,44.57,224,0.875,bicubic +resnetv2_50,80.412,19.588,95.072,4.928,25.55,224,0.950,bicubic +regnety_120,80.376,19.624,95.122,4.878,51.82,224,0.875,bicubic +resnet50,80.374,19.626,94.614,5.386,25.56,224,0.950,bicubic +mobilevitv2_150,80.368,19.632,95.064,4.936,10.59,256,0.888,bicubic +seresnet33ts,80.354,19.646,95.106,4.894,19.78,256,0.900,bicubic +resnetv2_50x1_bitm,80.342,19.658,95.686,4.314,25.55,448,1.000,bilinear +gluon_resnext101_32x4d,80.340,19.660,94.926,5.074,44.18,224,0.875,bicubic +ssl_resnext50_32x4d,80.326,19.674,95.412,4.588,25.03,224,0.875,bilinear +poolformer_s24,80.316,19.684,95.042,4.958,21.39,224,0.900,bicubic +rexnet_150,80.314,19.686,95.166,4.834,9.73,224,0.875,bicubic tf_efficientnet_b2_ap,80.302,19.698,95.028,4.972,9.11,260,0.890,bicubic -efficientnet_el_pruned,80.302,19.698,95.216,4.784,10.59,300,0.904,bicubic -gluon_resnet101_v1s,80.298,19.702,95.164,4.836,44.67,224,0.875,bicubic -seresnet50,80.264,19.736,95.072,4.928,28.09,224,0.875,bicubic -tf_efficientnet_el,80.250,19.750,95.122,4.878,10.59,300,0.904,bicubic -vit_base_patch16_224_sam,80.242,19.758,94.754,5.246,86.57,224,0.900,bicubic -regnetx_320,80.240,19.760,95.022,4.978,107.81,224,0.875,bicubic -legacy_seresnext101_32x4d,80.224,19.776,95.010,4.990,48.96,224,0.875,bilinear -repvgg_b3g4,80.212,19.788,95.106,4.894,83.83,224,0.875,bilinear -tf_efficientnetv2_b2,80.206,19.794,95.042,4.958,10.10,260,0.890,bicubic -dpn107,80.172,19.828,94.906,5.094,86.92,224,0.875,bicubic +efficientnet_el_pruned,80.298,19.702,95.214,4.786,10.59,300,0.904,bicubic +gluon_resnet101_v1s,80.298,19.702,95.162,4.838,44.67,224,0.875,bicubic +seresnet50,80.266,19.734,95.070,4.930,28.09,224,0.875,bicubic +tf_efficientnet_el,80.254,19.746,95.128,4.872,10.59,300,0.904,bicubic +regnetx_320,80.244,19.756,95.020,4.980,107.81,224,0.875,bicubic +vit_base_patch16_224_sam,80.244,19.756,94.754,5.246,86.57,224,0.900,bicubic +legacy_seresnext101_32x4d,80.222,19.778,95.014,4.986,48.96,224,0.875,bilinear +repvgg_b3g4,80.216,19.784,95.108,4.892,83.83,224,0.875,bilinear +tf_efficientnetv2_b2,80.208,19.792,95.044,4.956,10.10,260,0.890,bicubic +inception_v4,80.168,19.832,94.964,5.036,42.68,299,0.875,bicubic +dpn107,80.168,19.832,94.906,5.094,86.92,224,0.875,bicubic convmixer_768_32,80.164,19.836,95.072,4.928,21.11,224,0.960,bicubic -inception_v4,80.162,19.838,94.966,5.034,42.68,299,0.875,bicubic -skresnext50_32x4d,80.152,19.848,94.644,5.356,27.48,224,0.875,bicubic -eca_resnet33ts,80.080,19.920,94.970,5.030,19.68,256,0.900,bicubic -gcresnet33ts,80.080,19.920,95.000,5.000,19.88,256,0.900,bicubic -tf_efficientnet_b2,80.080,19.920,94.908,5.092,9.11,260,0.890,bicubic -cspdarknet53,80.062,19.938,95.084,4.916,27.64,256,0.887,bilinear -resnet50_gn,80.054,19.946,94.948,5.052,25.56,224,0.940,bicubic -cspresnext50,80.050,19.950,94.946,5.054,20.57,224,0.875,bilinear -dpn92,80.016,19.984,94.824,5.176,37.67,224,0.875,bicubic -ens_adv_inception_resnet_v2,79.978,20.022,94.938,5.062,55.84,299,0.897,bicubic -efficientnet_b2_pruned,79.916,20.084,94.854,5.146,8.31,260,0.890,bicubic -gluon_seresnext50_32x4d,79.914,20.086,94.832,5.168,27.56,224,0.875,bicubic -gluon_resnet152_v1c,79.908,20.092,94.848,5.152,60.21,224,0.875,bicubic -resnetrs50,79.886,20.114,94.966,5.034,35.69,224,0.910,bicubic -xception71,79.876,20.124,94.922,5.078,42.34,299,0.903,bicubic -deit_small_patch16_224,79.860,20.140,95.046,4.954,22.05,224,0.900,bicubic -regnetx_160,79.850,20.150,94.830,5.170,54.28,224,0.875,bicubic -ecaresnet26t,79.848,20.152,95.086,4.914,16.01,320,0.950,bicubic -levit_192,79.832,20.168,94.786,5.214,10.95,224,0.900,bicubic -dpn131,79.824,20.176,94.708,5.292,79.25,224,0.875,bicubic -tf_efficientnet_lite3,79.820,20.180,94.912,5.088,8.20,300,0.904,bilinear -resmlp_36_224,79.768,20.232,94.886,5.114,44.69,224,0.875,bicubic -cait_xxs36_224,79.748,20.252,94.866,5.134,17.30,224,1.000,bicubic -gluon_xception65,79.716,20.284,94.860,5.140,39.92,299,0.903,bicubic -ecaresnet50d_pruned,79.708,20.292,94.880,5.120,19.94,224,0.875,bicubic -xcit_tiny_12_p8_224,79.690,20.310,95.054,4.946,6.71,224,1.000,bicubic -fbnetv3_d,79.682,20.318,94.948,5.052,10.31,256,0.950,bilinear -gluon_resnet152_v1b,79.680,20.320,94.738,5.262,60.19,224,0.875,bicubic -resnext50d_32x4d,79.670,20.330,94.864,5.136,25.05,224,0.875,bicubic -dpn98,79.646,20.354,94.596,5.404,61.57,224,0.875,bicubic +skresnext50_32x4d,80.154,19.846,94.646,5.354,27.48,224,0.875,bicubic +tf_efficientnet_b2,80.088,19.912,94.908,5.092,9.11,260,0.890,bicubic +eca_resnet33ts,80.080,19.920,94.972,5.028,19.68,256,0.900,bicubic +gcresnet33ts,80.076,19.924,94.994,5.006,19.88,256,0.900,bicubic +resnet50_gn,80.060,19.940,94.948,5.052,25.56,224,0.940,bicubic +cspdarknet53,80.056,19.944,95.086,4.914,27.64,256,0.887,bilinear +dpn92,80.020,19.980,94.830,5.170,37.67,224,0.875,bicubic +ens_adv_inception_resnet_v2,79.974,20.026,94.942,5.058,55.84,299,0.897,bicubic +efficientnet_b2_pruned,79.918,20.082,94.850,5.150,8.31,260,0.890,bicubic +gluon_resnet152_v1c,79.912,20.088,94.842,5.158,60.21,224,0.875,bicubic +gluon_seresnext50_32x4d,79.912,20.088,94.832,5.168,27.56,224,0.875,bicubic +resnetrs50,79.886,20.114,94.970,5.030,35.69,224,0.910,bicubic +xception71,79.870,20.130,94.924,5.076,42.34,299,0.903,bicubic +deit_small_patch16_224,79.864,20.136,95.048,4.952,22.05,224,0.900,bicubic +regnetx_160,79.854,20.146,94.830,5.170,54.28,224,0.875,bicubic +ecaresnet26t,79.852,20.148,95.084,4.916,16.01,320,0.950,bicubic +levit_192,79.836,20.164,94.790,5.210,10.95,224,0.900,bicubic +dpn131,79.826,20.174,94.708,5.292,79.25,224,0.875,bicubic +tf_efficientnet_lite3,79.818,20.182,94.914,5.086,8.20,300,0.904,bilinear +resmlp_36_224,79.770,20.230,94.886,5.114,44.69,224,0.875,bicubic +cait_xxs36_224,79.748,20.252,94.868,5.132,17.30,224,1.000,bicubic +gluon_xception65,79.722,20.278,94.860,5.140,39.92,299,0.903,bicubic +ecaresnet50d_pruned,79.718,20.282,94.876,5.124,19.94,224,0.875,bicubic +xcit_tiny_12_p8_224,79.694,20.306,95.048,4.952,6.71,224,1.000,bicubic +mobilevitv2_125,79.682,20.318,94.848,5.152,7.48,256,0.888,bicubic +gluon_resnet152_v1b,79.682,20.318,94.736,5.264,60.19,224,0.875,bicubic +fbnetv3_d,79.680,20.320,94.940,5.060,10.31,256,0.950,bilinear +resnext50d_32x4d,79.676,20.324,94.866,5.134,25.05,224,0.875,bicubic +dpn98,79.644,20.356,94.600,5.400,61.57,224,0.875,bicubic gmlp_s16_224,79.640,20.360,94.624,5.376,19.42,224,0.875,bicubic regnetx_120,79.592,20.408,94.734,5.266,46.11,224,0.875,bicubic -cspresnet50,79.582,20.418,94.704,5.296,21.62,256,0.887,bilinear -gluon_resnet101_v1c,79.534,20.466,94.580,5.420,44.57,224,0.875,bicubic -rexnet_130,79.500,20.500,94.684,5.316,7.56,224,0.875,bicubic -eca_halonext26ts,79.490,20.510,94.598,5.402,10.76,256,0.940,bicubic -hrnet_w64,79.472,20.528,94.652,5.348,128.06,224,0.875,bilinear -tf_efficientnetv2_b1,79.464,20.536,94.724,5.276,8.14,240,0.882,bicubic -dla102x2,79.446,20.554,94.632,5.368,41.28,224,0.875,bilinear -xcit_tiny_24_p16_224,79.444,20.556,94.884,5.116,12.12,224,1.000,bicubic -resmlp_24_224,79.382,20.618,94.546,5.454,30.02,224,0.875,bicubic -repvgg_b2g4,79.370,20.630,94.688,5.312,61.76,224,0.875,bilinear -gluon_resnext50_32x4d,79.364,20.636,94.426,5.574,25.03,224,0.875,bicubic +cspresnet50,79.582,20.418,94.708,5.292,21.62,256,0.887,bilinear +gluon_resnet101_v1c,79.536,20.464,94.578,5.422,44.57,224,0.875,bicubic +rexnet_130,79.502,20.498,94.682,5.318,7.56,224,0.875,bicubic +eca_halonext26ts,79.488,20.512,94.604,5.396,10.76,256,0.940,bicubic +vit_relpos_base_patch32_plus_rpn_256,79.486,20.514,94.140,5.860,119.42,256,0.900,bicubic +hrnet_w64,79.470,20.530,94.654,5.346,128.06,224,0.875,bilinear +tf_efficientnetv2_b1,79.466,20.534,94.722,5.278,8.14,240,0.882,bicubic +xcit_tiny_24_p16_224,79.444,20.556,94.888,5.112,12.12,224,1.000,bicubic +dla102x2,79.442,20.558,94.646,5.354,41.28,224,0.875,bilinear +resmlp_24_224,79.378,20.622,94.546,5.454,30.02,224,0.875,bicubic +repvgg_b2g4,79.366,20.634,94.688,5.312,61.76,224,0.875,bilinear +gluon_resnext50_32x4d,79.360,20.640,94.426,5.574,25.03,224,0.875,bicubic resnext101_32x8d,79.316,20.684,94.518,5.482,88.79,224,0.875,bilinear +tf_efficientnet_cc_b1_8e,79.314,20.686,94.370,5.630,39.72,240,0.882,bicubic ese_vovnet39b,79.312,20.688,94.714,5.286,24.57,224,0.875,bicubic -pit_xs_distilled_224,79.306,20.694,94.364,5.636,11.00,224,0.900,bicubic -tf_efficientnet_cc_b1_8e,79.306,20.694,94.372,5.628,39.72,240,0.882,bicubic -resnetblur50,79.304,20.696,94.634,5.366,25.56,224,0.875,bicubic -gluon_resnet101_v1b,79.302,20.698,94.520,5.480,44.55,224,0.875,bicubic -hrnet_w48,79.302,20.698,94.512,5.488,77.47,224,0.875,bilinear -nf_regnet_b1,79.288,20.712,94.748,5.252,10.22,288,0.900,bicubic -tf_efficientnet_b1_ap,79.280,20.720,94.304,5.696,7.79,240,0.882,bicubic -eca_botnext26ts_256,79.274,20.726,94.616,5.384,10.59,256,0.950,bicubic -botnet26t_256,79.252,20.748,94.528,5.472,12.49,256,0.950,bicubic -efficientnet_em,79.250,20.750,94.794,5.206,6.90,240,0.882,bicubic -ssl_resnet50,79.226,20.774,94.836,5.164,25.56,224,0.875,bilinear -dpn68b,79.220,20.780,94.418,5.582,12.61,224,0.875,bicubic -resnet33ts,79.210,20.790,94.572,5.428,19.68,256,0.900,bicubic -regnetx_080,79.202,20.798,94.554,5.446,39.57,224,0.875,bicubic +pit_xs_distilled_224,79.308,20.692,94.366,5.634,11.00,224,0.900,bicubic +gluon_resnet101_v1b,79.304,20.696,94.520,5.480,44.55,224,0.875,bicubic +nf_regnet_b1,79.300,20.700,94.754,5.246,10.22,288,0.900,bicubic +hrnet_w48,79.300,20.700,94.514,5.486,77.47,224,0.875,bilinear +resnetblur50,79.294,20.706,94.634,5.366,25.56,224,0.875,bicubic +eca_botnext26ts_256,79.276,20.724,94.616,5.384,10.59,256,0.950,bicubic +tf_efficientnet_b1_ap,79.274,20.726,94.308,5.692,7.79,240,0.882,bicubic +botnet26t_256,79.258,20.742,94.528,5.472,12.49,256,0.950,bicubic +efficientnet_em,79.252,20.748,94.792,5.208,6.90,240,0.882,bicubic +ssl_resnet50,79.224,20.776,94.830,5.170,25.56,224,0.875,bilinear +dpn68b,79.216,20.784,94.414,5.586,12.61,224,0.875,bicubic +resnet33ts,79.208,20.792,94.574,5.426,19.68,256,0.900,bicubic +regnetx_080,79.202,20.798,94.552,5.448,39.57,224,0.875,bicubic res2net101_26w_4s,79.196,20.804,94.436,5.564,45.21,224,0.875,bilinear -fbnetv3_b,79.148,20.852,94.746,5.254,8.60,256,0.950,bilinear -halonet26t,79.116,20.884,94.310,5.690,12.48,256,0.950,bicubic -lambda_resnet26t,79.098,20.902,94.588,5.412,10.96,256,0.940,bicubic -coat_lite_mini,79.096,20.904,94.604,5.396,11.01,224,0.900,bicubic -gluon_resnet50_v1d,79.076,20.924,94.472,5.528,25.58,224,0.875,bicubic -legacy_seresnext50_32x4d,79.068,20.932,94.434,5.566,27.56,224,0.875,bilinear -regnetx_064,79.066,20.934,94.458,5.542,26.21,224,0.875,bicubic -xception,79.050,20.950,94.392,5.608,22.86,299,0.897,bicubic -resnet32ts,79.012,20.988,94.358,5.642,17.96,256,0.900,bicubic -res2net50_26w_8s,78.980,21.020,94.294,5.706,48.40,224,0.875,bilinear +fbnetv3_b,79.142,20.858,94.750,5.250,8.60,256,0.950,bilinear +halonet26t,79.112,20.888,94.314,5.686,12.48,256,0.950,bicubic +lambda_resnet26t,79.098,20.902,94.590,5.410,10.96,256,0.940,bicubic +coat_lite_mini,79.088,20.912,94.608,5.392,11.01,224,0.900,bicubic +legacy_seresnext50_32x4d,79.076,20.924,94.434,5.566,27.56,224,0.875,bilinear +regnetx_064,79.074,20.926,94.460,5.540,26.21,224,0.875,bicubic +gluon_resnet50_v1d,79.070,20.930,94.466,5.534,25.58,224,0.875,bicubic +xception,79.044,20.956,94.394,5.606,22.86,299,0.897,bicubic +resnet32ts,79.014,20.986,94.356,5.644,17.96,256,0.900,bicubic mixnet_l,78.976,21.024,94.178,5.822,7.33,224,0.875,bicubic -lambda_resnet26rpt_256,78.968,21.032,94.428,5.572,10.99,256,0.940,bicubic -hrnet_w40,78.916,21.084,94.474,5.526,57.56,224,0.875,bilinear -hrnet_w44,78.900,21.100,94.374,5.626,67.06,224,0.875,bilinear -wide_resnet101_2,78.854,21.146,94.290,5.710,126.89,224,0.875,bilinear +lambda_resnet26rpt_256,78.964,21.036,94.426,5.574,10.99,256,0.940,bicubic +res2net50_26w_8s,78.952,21.048,94.306,5.694,48.40,224,0.875,bilinear +hrnet_w40,78.922,21.078,94.470,5.530,57.56,224,0.875,bilinear +hrnet_w44,78.896,21.104,94.370,5.630,67.06,224,0.875,bilinear +wide_resnet101_2,78.852,21.148,94.288,5.712,126.89,224,0.875,bilinear tf_efficientnet_b1,78.828,21.172,94.198,5.802,7.79,240,0.882,bicubic -gluon_inception_v3,78.804,21.196,94.370,5.630,23.83,299,0.875,bicubic -efficientnet_b1,78.796,21.204,94.342,5.658,7.79,256,1.000,bicubic -repvgg_b2,78.792,21.208,94.418,5.582,89.02,224,0.875,bilinear -tf_mixnet_l,78.774,21.226,93.996,6.004,7.33,224,0.875,bicubic -gluon_resnet50_v1s,78.712,21.288,94.240,5.760,25.68,224,0.875,bicubic -dla169,78.692,21.308,94.340,5.660,53.39,224,0.875,bilinear -tf_efficientnet_b0_ns,78.658,21.342,94.378,5.622,5.29,224,0.875,bicubic +gluon_inception_v3,78.806,21.194,94.370,5.630,23.83,299,0.875,bicubic +repvgg_b2,78.794,21.206,94.418,5.582,89.02,224,0.875,bilinear +efficientnet_b1,78.788,21.212,94.346,5.654,7.79,256,1.000,bicubic +tf_mixnet_l,78.778,21.222,93.998,6.002,7.33,224,0.875,bicubic +gluon_resnet50_v1s,78.706,21.294,94.238,5.762,25.68,224,0.875,bicubic +dla169,78.682,21.318,94.336,5.664,53.39,224,0.875,bilinear +tf_efficientnet_b0_ns,78.664,21.336,94.376,5.624,5.29,224,0.875,bicubic legacy_seresnet152,78.652,21.348,94.370,5.630,66.82,224,0.875,bilinear -xcit_tiny_12_p16_224_dist,78.576,21.424,94.196,5.804,6.72,224,1.000,bicubic -res2net50_26w_6s,78.566,21.434,94.134,5.866,37.05,224,0.875,bilinear -dla102x,78.516,21.484,94.226,5.774,26.31,224,0.875,bilinear -xception41,78.510,21.490,94.278,5.722,26.97,299,0.903,bicubic -levit_128,78.492,21.508,94.006,5.994,9.21,224,0.900,bicubic -regnetx_040,78.482,21.518,94.244,5.756,22.12,224,0.875,bicubic -resnest26d,78.476,21.524,94.292,5.708,17.07,224,0.875,bilinear -dla60_res2net,78.462,21.538,94.206,5.794,20.85,224,0.875,bilinear -hrnet_w32,78.448,21.552,94.194,5.806,41.23,224,0.875,bilinear -dla60_res2next,78.440,21.560,94.150,5.850,17.03,224,0.875,bilinear -vit_tiny_patch16_384,78.434,21.566,94.542,5.458,5.79,384,1.000,bicubic -coat_tiny,78.430,21.570,94.040,5.960,5.50,224,0.900,bicubic -selecsls60b,78.412,21.588,94.174,5.826,32.77,224,0.875,bicubic -legacy_seresnet101,78.388,21.612,94.264,5.736,49.33,224,0.875,bilinear -cait_xxs24_224,78.384,21.616,94.310,5.690,11.96,224,1.000,bicubic -repvgg_b1,78.368,21.632,94.096,5.904,57.42,224,0.875,bilinear -tf_efficientnetv2_b0,78.360,21.640,94.020,5.980,7.14,224,0.875,bicubic -tv_resnet152,78.316,21.684,94.034,5.966,60.19,224,0.875,bilinear -mobilevit_s,78.312,21.688,94.152,5.848,5.58,256,0.900,bicubic -res2next50,78.252,21.748,93.886,6.114,24.67,224,0.875,bilinear -bat_resnext26ts,78.250,21.750,94.098,5.902,10.73,256,0.900,bicubic -dla60x,78.244,21.756,94.018,5.982,17.35,224,0.875,bilinear -efficientnet_b1_pruned,78.240,21.760,93.834,6.166,6.33,240,0.882,bicubic +xcit_tiny_12_p16_224_dist,78.578,21.422,94.198,5.802,6.72,224,1.000,bicubic +res2net50_26w_6s,78.570,21.430,94.124,5.876,37.05,224,0.875,bilinear +xception41,78.516,21.484,94.280,5.720,26.97,299,0.903,bicubic +dla102x,78.512,21.488,94.228,5.772,26.31,224,0.875,bilinear +regnetx_040,78.488,21.512,94.238,5.762,22.12,224,0.875,bicubic +resnest26d,78.484,21.516,94.294,5.706,17.07,224,0.875,bilinear +levit_128,78.482,21.518,94.012,5.988,9.21,224,0.900,bicubic +dla60_res2net,78.458,21.542,94.196,5.804,20.85,224,0.875,bilinear +dla60_res2next,78.456,21.544,94.146,5.854,17.03,224,0.875,bilinear +hrnet_w32,78.452,21.548,94.188,5.812,41.23,224,0.875,bilinear +coat_tiny,78.436,21.564,94.038,5.962,5.50,224,0.900,bicubic +vit_tiny_patch16_384,78.430,21.570,94.544,5.456,5.79,384,1.000,bicubic +selecsls60b,78.404,21.596,94.172,5.828,32.77,224,0.875,bicubic +cait_xxs24_224,78.386,21.614,94.308,5.692,11.96,224,1.000,bicubic +legacy_seresnet101,78.380,21.620,94.262,5.738,49.33,224,0.875,bilinear +repvgg_b1,78.368,21.632,94.094,5.906,57.42,224,0.875,bilinear +tf_efficientnetv2_b0,78.352,21.648,94.026,5.974,7.14,224,0.875,bicubic +tv_resnet152,78.320,21.680,94.034,5.966,60.19,224,0.875,bilinear +mobilevit_s,78.310,21.690,94.152,5.848,5.58,256,0.900,bicubic +res2next50,78.258,21.742,93.888,6.112,24.67,224,0.875,bilinear +bat_resnext26ts,78.248,21.752,94.096,5.904,10.73,256,0.900,bicubic +efficientnet_b1_pruned,78.244,21.756,93.834,6.166,6.33,240,0.882,bicubic +dla60x,78.228,21.772,94.024,5.976,17.35,224,0.875,bilinear hrnet_w30,78.198,21.802,94.224,5.776,37.71,224,0.875,bilinear -pit_xs_224,78.186,21.814,94.164,5.836,10.62,224,0.900,bicubic -regnetx_032,78.172,21.828,94.088,5.912,15.30,224,0.875,bicubic -res2net50_14w_8s,78.144,21.856,93.848,6.152,25.06,224,0.875,bilinear -tf_efficientnet_em,78.132,21.868,94.044,5.956,6.90,240,0.882,bicubic -hardcorenas_f,78.098,21.902,93.802,6.198,8.20,224,0.875,bilinear -efficientnet_es,78.056,21.944,93.936,6.064,5.44,224,0.875,bicubic +pit_xs_224,78.190,21.810,94.166,5.834,10.62,224,0.900,bicubic +regnetx_032,78.184,21.816,94.088,5.912,15.30,224,0.875,bicubic +res2net50_14w_8s,78.144,21.856,93.852,6.148,25.06,224,0.875,bilinear +tf_efficientnet_em,78.126,21.874,94.046,5.954,6.90,240,0.882,bicubic +hardcorenas_f,78.102,21.898,93.802,6.198,8.20,224,0.875,bilinear +mobilevitv2_100,78.086,21.914,94.160,5.840,4.90,256,0.888,bicubic +efficientnet_es,78.058,21.942,93.944,6.056,5.44,224,0.875,bicubic gmixer_24_224,78.036,21.964,93.670,6.330,24.72,224,0.875,bicubic -dla102,78.030,21.970,93.948,6.052,33.27,224,0.875,bilinear -gluon_resnet50_v1c,78.012,21.988,93.990,6.010,25.58,224,0.875,bicubic -seresnext26t_32x4d,77.976,22.024,93.746,6.254,16.81,224,0.875,bicubic -selecsls60,77.976,22.024,93.830,6.170,30.67,224,0.875,bicubic -res2net50_26w_4s,77.960,22.040,93.852,6.148,25.70,224,0.875,bilinear -resmlp_12_distilled_224,77.942,22.058,93.558,6.442,15.35,224,0.875,bicubic -mobilenetv3_large_100_miil,77.916,22.084,92.906,7.094,5.48,224,0.875,bilinear -tf_efficientnet_cc_b0_8e,77.906,22.094,93.656,6.344,24.01,224,0.875,bicubic -resnet26t,77.862,22.138,93.844,6.156,16.01,256,0.940,bicubic -regnety_016,77.860,22.140,93.722,6.278,11.20,224,0.875,bicubic -rexnet_100,77.858,22.142,93.870,6.130,4.80,224,0.875,bicubic -tf_inception_v3,77.856,22.144,93.640,6.360,23.83,299,0.875,bicubic -seresnext26ts,77.852,22.148,93.790,6.210,10.39,256,0.900,bicubic -gcresnext26ts,77.820,22.180,93.830,6.170,10.48,256,0.900,bicubic -xcit_nano_12_p8_384_dist,77.818,22.182,94.044,5.956,3.05,384,1.000,bicubic -hardcorenas_e,77.794,22.206,93.696,6.304,8.07,224,0.875,bilinear -efficientnet_b0,77.690,22.310,93.530,6.470,5.29,224,0.875,bicubic -tinynet_a,77.650,22.350,93.536,6.464,6.19,192,0.875,bicubic -legacy_seresnet50,77.630,22.370,93.750,6.250,28.09,224,0.875,bilinear -tv_resnext50_32x4d,77.616,22.384,93.700,6.300,25.03,224,0.875,bilinear -seresnext26d_32x4d,77.604,22.396,93.608,6.392,16.81,224,0.875,bicubic -repvgg_b1g4,77.586,22.414,93.830,6.170,39.97,224,0.875,bilinear -adv_inception_v3,77.582,22.418,93.736,6.264,23.83,299,0.875,bicubic -gluon_resnet50_v1b,77.580,22.420,93.722,6.278,25.56,224,0.875,bicubic -res2net50_48w_2s,77.520,22.480,93.552,6.448,25.29,224,0.875,bilinear -coat_lite_tiny,77.514,22.486,93.916,6.084,5.72,224,0.900,bicubic -tf_efficientnet_lite2,77.468,22.532,93.756,6.244,6.09,260,0.890,bicubic -eca_resnext26ts,77.454,22.546,93.566,6.434,10.30,256,0.900,bicubic -inception_v3,77.438,22.562,93.474,6.526,23.83,299,0.875,bicubic -hardcorenas_d,77.430,22.570,93.482,6.518,7.50,224,0.875,bilinear -tv_resnet101,77.378,22.622,93.542,6.458,44.55,224,0.875,bilinear +dla102,78.028,21.972,93.950,6.050,33.27,224,0.875,bilinear +gluon_resnet50_v1c,78.008,21.992,93.990,6.010,25.58,224,0.875,bicubic +selecsls60,77.984,22.016,93.832,6.168,30.67,224,0.875,bicubic +seresnext26t_32x4d,77.968,22.032,93.748,6.252,16.81,224,0.875,bicubic +res2net50_26w_4s,77.962,22.038,93.852,6.148,25.70,224,0.875,bilinear +resmlp_12_distilled_224,77.946,22.054,93.560,6.440,15.35,224,0.875,bicubic +mobilenetv3_large_100_miil,77.922,22.078,92.920,7.080,5.48,224,0.875,bilinear +tf_efficientnet_cc_b0_8e,77.900,22.100,93.658,6.342,24.01,224,0.875,bicubic +resnet26t,77.864,22.136,93.842,6.158,16.01,256,0.940,bicubic +rexnet_100,77.860,22.140,93.874,6.126,4.80,224,0.875,bicubic +seresnext26ts,77.858,22.142,93.790,6.210,10.39,256,0.900,bicubic +regnety_016,77.856,22.144,93.720,6.280,11.20,224,0.875,bicubic +tf_inception_v3,77.852,22.148,93.640,6.360,23.83,299,0.875,bicubic +xcit_nano_12_p8_384_dist,77.816,22.184,94.046,5.954,3.05,384,1.000,bicubic +gcresnext26ts,77.814,22.186,93.836,6.164,10.48,256,0.900,bicubic +hardcorenas_e,77.786,22.214,93.704,6.296,8.07,224,0.875,bilinear +efficientnet_b0,77.700,22.300,93.532,6.468,5.29,224,0.875,bicubic +tinynet_a,77.648,22.352,93.536,6.464,6.19,192,0.875,bicubic +legacy_seresnet50,77.632,22.368,93.750,6.250,28.09,224,0.875,bilinear +cs3darknet_m,77.626,22.374,94.014,5.986,9.31,288,0.950,bicubic +tv_resnext50_32x4d,77.618,22.382,93.700,6.300,25.03,224,0.875,bilinear +seresnext26d_32x4d,77.606,22.394,93.606,6.394,16.81,224,0.875,bicubic +repvgg_b1g4,77.588,22.412,93.830,6.170,39.97,224,0.875,bilinear +gluon_resnet50_v1b,77.584,22.416,93.720,6.280,25.56,224,0.875,bicubic +adv_inception_v3,77.578,22.422,93.738,6.262,23.83,299,0.875,bicubic +res2net50_48w_2s,77.524,22.476,93.550,6.450,25.29,224,0.875,bilinear +coat_lite_tiny,77.516,22.484,93.914,6.086,5.72,224,0.900,bicubic +tf_efficientnet_lite2,77.466,22.534,93.758,6.242,6.09,260,0.890,bicubic +eca_resnext26ts,77.458,22.542,93.568,6.432,10.30,256,0.900,bicubic +inception_v3,77.438,22.562,93.476,6.524,23.83,299,0.875,bicubic +hardcorenas_d,77.430,22.570,93.484,6.516,7.50,224,0.875,bilinear +tv_resnet101,77.380,22.620,93.544,6.456,44.55,224,0.875,bilinear densenet161,77.354,22.646,93.636,6.364,28.68,224,0.875,bicubic -tf_efficientnet_cc_b0_4e,77.302,22.698,93.334,6.666,13.31,224,0.875,bicubic -mobilenetv2_120d,77.294,22.706,93.496,6.504,5.83,224,0.875,bicubic -densenet201,77.290,22.710,93.478,6.522,20.01,224,0.875,bicubic -mixnet_m,77.264,22.736,93.424,6.576,5.01,224,0.875,bicubic -poolformer_s12,77.236,22.764,93.504,6.496,11.92,224,0.900,bicubic -selecsls42b,77.174,22.826,93.392,6.608,32.46,224,0.875,bicubic -xcit_tiny_12_p16_224,77.126,22.874,93.716,6.284,6.72,224,1.000,bicubic -resnet34d,77.114,22.886,93.380,6.620,21.82,224,0.875,bicubic -legacy_seresnext26_32x4d,77.106,22.894,93.318,6.682,16.79,224,0.875,bicubic -tf_efficientnet_b0_ap,77.094,22.906,93.256,6.744,5.29,224,0.875,bicubic -hardcorenas_c,77.050,22.950,93.158,6.842,5.52,224,0.875,bilinear -dla60,77.030,22.970,93.320,6.680,22.04,224,0.875,bilinear -crossvit_9_dagger_240,76.982,23.018,93.610,6.390,8.78,240,0.875,bicubic -regnetx_016,76.950,23.050,93.422,6.578,9.19,224,0.875,bicubic -convmixer_1024_20_ks9_p14,76.942,23.058,93.356,6.644,24.38,224,0.960,bicubic -tf_mixnet_m,76.942,23.058,93.154,6.846,5.01,224,0.875,bicubic -gernet_s,76.908,23.092,93.132,6.868,8.17,224,0.875,bilinear +tf_efficientnet_cc_b0_4e,77.310,22.690,93.340,6.660,13.31,224,0.875,bicubic +mobilenetv2_120d,77.290,22.710,93.500,6.500,5.83,224,0.875,bicubic +densenet201,77.288,22.712,93.480,6.520,20.01,224,0.875,bicubic +cs3darknet_focus_m,77.282,22.718,93.972,6.028,9.30,288,0.950,bicubic +mixnet_m,77.262,22.738,93.422,6.578,5.01,224,0.875,bicubic +poolformer_s12,77.238,22.762,93.506,6.494,11.92,224,0.900,bicubic +selecsls42b,77.178,22.822,93.392,6.608,32.46,224,0.875,bicubic +xcit_tiny_12_p16_224,77.124,22.876,93.712,6.288,6.72,224,1.000,bicubic +resnet34d,77.116,22.884,93.382,6.618,21.82,224,0.875,bicubic +legacy_seresnext26_32x4d,77.104,22.896,93.316,6.684,16.79,224,0.875,bicubic +tf_efficientnet_b0_ap,77.088,22.912,93.258,6.742,5.29,224,0.875,bicubic +hardcorenas_c,77.052,22.948,93.160,6.840,5.52,224,0.875,bilinear +dla60,77.022,22.978,93.320,6.680,22.04,224,0.875,bilinear +crossvit_9_dagger_240,76.978,23.022,93.614,6.386,8.78,240,0.875,bicubic +tf_mixnet_m,76.946,23.054,93.152,6.848,5.01,224,0.875,bicubic +regnetx_016,76.942,23.058,93.424,6.576,9.19,224,0.875,bicubic +convmixer_1024_20_ks9_p14,76.942,23.058,93.358,6.642,24.38,224,0.960,bicubic +gernet_s,76.916,23.084,93.134,6.866,8.17,224,0.875,bilinear skresnet34,76.904,23.096,93.320,6.680,22.28,224,0.875,bicubic -tf_efficientnet_b0,76.844,23.156,93.228,6.772,5.29,224,0.875,bicubic -ese_vovnet19b_dw,76.802,23.198,93.272,6.728,6.54,224,0.875,bicubic -resnext26ts,76.780,23.220,93.128,6.872,10.30,256,0.900,bicubic -hrnet_w18,76.754,23.246,93.440,6.560,21.30,224,0.875,bilinear -resnet26d,76.704,23.296,93.150,6.850,16.01,224,0.875,bicubic +tf_efficientnet_b0,76.840,23.160,93.218,6.782,5.29,224,0.875,bicubic +ese_vovnet19b_dw,76.794,23.206,93.266,6.734,6.54,224,0.875,bicubic +resnext26ts,76.780,23.220,93.132,6.868,10.30,256,0.900,bicubic +hrnet_w18,76.760,23.240,93.444,6.556,21.30,224,0.875,bilinear +resnet26d,76.702,23.298,93.152,6.848,16.01,224,0.875,bicubic resmlp_12_224,76.656,23.344,93.180,6.820,15.35,224,0.875,bicubic -tf_efficientnet_lite1,76.640,23.360,93.220,6.780,5.42,240,0.882,bicubic -mixer_b16_224,76.612,23.388,92.228,7.772,59.88,224,0.875,bicubic -tf_efficientnet_es,76.596,23.404,93.204,6.796,5.44,224,0.875,bicubic -densenetblur121d,76.584,23.416,93.192,6.808,8.00,224,0.875,bicubic +tf_efficientnet_lite1,76.638,23.362,93.224,6.776,5.42,240,0.882,bicubic +mixer_b16_224,76.610,23.390,92.230,7.770,59.88,224,0.875,bicubic +tf_efficientnet_es,76.598,23.402,93.204,6.796,5.44,224,0.875,bicubic +densenetblur121d,76.580,23.420,93.188,6.812,8.00,224,0.875,bicubic hardcorenas_b,76.536,23.464,92.754,7.246,5.18,224,0.875,bilinear -mobilenetv2_140,76.522,23.478,92.996,7.004,6.11,224,0.875,bicubic -levit_128s,76.520,23.480,92.872,7.128,7.78,224,0.900,bicubic -repvgg_a2,76.458,23.542,93.010,6.990,28.21,224,0.875,bilinear -xcit_nano_12_p8_224_dist,76.320,23.680,93.088,6.912,3.05,224,1.000,bicubic -regnety_008,76.310,23.690,93.070,6.930,6.26,224,0.875,bicubic -dpn68,76.306,23.694,92.974,7.026,12.61,224,0.875,bicubic +levit_128s,76.514,23.486,92.870,7.130,7.78,224,0.900,bicubic +mobilenetv2_140,76.512,23.488,92.998,7.002,6.11,224,0.875,bicubic +repvgg_a2,76.460,23.540,93.010,6.990,28.21,224,0.875,bilinear +xcit_nano_12_p8_224_dist,76.328,23.672,93.094,6.906,3.05,224,1.000,bicubic +regnety_008,76.314,23.686,93.070,6.930,6.26,224,0.875,bicubic +dpn68,76.310,23.690,92.978,7.022,12.61,224,0.875,bicubic tv_resnet50,76.134,23.866,92.868,7.132,25.56,224,0.875,bilinear -mixnet_s,75.992,24.008,92.798,7.202,4.13,224,0.875,bicubic -vit_small_patch32_224,75.986,24.014,93.270,6.730,22.88,224,0.900,bicubic -vit_tiny_r_s16_p8_384,75.954,24.046,93.264,6.736,6.36,384,1.000,bicubic -hardcorenas_a,75.920,24.080,92.520,7.480,5.26,224,0.875,bilinear -densenet169,75.898,24.102,93.030,6.970,14.15,224,0.875,bicubic -mobilenetv3_large_100,75.766,24.234,92.544,7.456,5.48,224,0.875,bicubic -tf_mixnet_s,75.650,24.350,92.628,7.372,4.13,224,0.875,bicubic -mobilenetv3_rw,75.632,24.368,92.708,7.292,5.48,224,0.875,bicubic -densenet121,75.584,24.416,92.652,7.348,7.98,224,0.875,bicubic -tf_mobilenetv3_large_100,75.518,24.482,92.604,7.396,5.48,224,0.875,bilinear -resnest14d,75.504,24.496,92.520,7.480,10.61,224,0.875,bilinear -efficientnet_lite0,75.476,24.524,92.512,7.488,4.65,224,0.875,bicubic -vit_tiny_patch16_224,75.462,24.538,92.844,7.156,5.72,224,0.900,bicubic +mixnet_s,75.996,24.004,92.800,7.200,4.13,224,0.875,bicubic +vit_small_patch32_224,75.990,24.010,93.268,6.732,22.88,224,0.900,bicubic +vit_tiny_r_s16_p8_384,75.952,24.048,93.262,6.738,6.36,384,1.000,bicubic +hardcorenas_a,75.930,24.070,92.510,7.490,5.26,224,0.875,bilinear +densenet169,75.904,24.096,93.024,6.976,14.15,224,0.875,bicubic +mobilenetv3_large_100,75.776,24.224,92.540,7.460,5.48,224,0.875,bicubic +tf_mixnet_s,75.652,24.348,92.626,7.374,4.13,224,0.875,bicubic +mobilenetv3_rw,75.634,24.366,92.708,7.292,5.48,224,0.875,bicubic +mobilevitv2_075,75.608,24.392,92.758,7.242,2.87,256,0.888,bicubic +densenet121,75.580,24.420,92.648,7.352,7.98,224,0.875,bicubic +tf_mobilenetv3_large_100,75.512,24.488,92.606,7.394,5.48,224,0.875,bilinear +resnest14d,75.508,24.492,92.524,7.476,10.61,224,0.875,bilinear +efficientnet_lite0,75.468,24.532,92.516,7.484,4.65,224,0.875,bicubic +vit_tiny_patch16_224,75.464,24.536,92.844,7.156,5.72,224,0.900,bicubic xcit_nano_12_p16_384_dist,75.456,24.544,92.690,7.310,3.05,384,1.000,bicubic semnasnet_100,75.450,24.550,92.600,7.400,3.89,224,0.875,bicubic -resnet26,75.300,24.700,92.578,7.422,16.00,224,0.875,bicubic -regnety_006,75.250,24.750,92.534,7.466,6.06,224,0.875,bicubic -repvgg_b0,75.160,24.840,92.418,7.582,15.82,224,0.875,bilinear -fbnetc_100,75.130,24.870,92.386,7.614,5.57,224,0.875,bilinear -hrnet_w18_small_v2,75.118,24.882,92.416,7.584,15.60,224,0.875,bilinear -resnet34,75.114,24.886,92.284,7.716,21.80,224,0.875,bilinear -mobilenetv2_110d,75.038,24.962,92.184,7.816,4.52,224,0.875,bicubic +resnet26,75.300,24.700,92.580,7.420,16.00,224,0.875,bicubic +regnety_006,75.252,24.748,92.532,7.468,6.06,224,0.875,bicubic +repvgg_b0,75.154,24.846,92.416,7.584,15.82,224,0.875,bilinear +fbnetc_100,75.116,24.884,92.386,7.614,5.57,224,0.875,bilinear +resnet34,75.112,24.888,92.284,7.716,21.80,224,0.875,bilinear +hrnet_w18_small_v2,75.110,24.890,92.416,7.584,15.60,224,0.875,bilinear +mobilenetv2_110d,75.036,24.964,92.192,7.808,4.52,224,0.875,bicubic regnetx_008,75.034,24.966,92.340,7.660,7.26,224,0.875,bicubic -efficientnet_es_pruned,74.996,25.004,92.440,7.560,5.44,224,0.875,bicubic -tinynet_b,74.976,25.024,92.184,7.816,3.73,188,0.875,bicubic +efficientnet_es_pruned,75.000,25.000,92.442,7.558,5.44,224,0.875,bicubic +tinynet_b,74.974,25.026,92.182,7.818,3.73,188,0.875,bicubic +edgenext_x_small,74.864,25.136,92.300,7.700,2.34,256,0.900,bicubic tf_efficientnet_lite0,74.832,25.168,92.174,7.826,4.65,224,0.875,bicubic -legacy_seresnet34,74.808,25.192,92.126,7.874,21.96,224,0.875,bilinear -tv_densenet121,74.744,25.256,92.152,7.848,7.98,224,0.875,bicubic -mnasnet_100,74.658,25.342,92.112,7.888,4.38,224,0.875,bicubic -mobilevit_xs,74.644,25.356,92.356,7.644,2.32,256,0.900,bicubic -dla34,74.620,25.380,92.072,7.928,15.74,224,0.875,bilinear -gluon_resnet34_v1b,74.588,25.412,91.988,8.012,21.80,224,0.875,bicubic -pit_ti_distilled_224,74.532,25.468,92.096,7.904,5.10,224,0.900,bicubic -deit_tiny_distilled_patch16_224,74.512,25.488,91.886,8.114,5.91,224,0.900,bicubic -vgg19_bn,74.214,25.786,91.848,8.152,143.68,224,0.875,bilinear -spnasnet_100,74.084,25.916,91.820,8.180,4.42,224,0.875,bilinear -regnety_004,74.024,25.976,91.754,8.246,4.34,224,0.875,bicubic -ghostnet_100,73.974,26.026,91.460,8.540,5.18,224,0.875,bilinear -crossvit_9_240,73.960,26.040,91.968,8.032,8.55,240,0.875,bicubic -xcit_nano_12_p8_224,73.910,26.090,92.168,7.832,3.05,224,1.000,bicubic -regnetx_006,73.860,26.140,91.672,8.328,6.20,224,0.875,bicubic -vit_base_patch32_224_sam,73.694,26.306,91.010,8.990,88.22,224,0.900,bicubic -tf_mobilenetv3_large_075,73.436,26.564,91.344,8.656,3.99,224,0.875,bilinear +legacy_seresnet34,74.810,25.190,92.126,7.874,21.96,224,0.875,bilinear +tv_densenet121,74.740,25.260,92.148,7.852,7.98,224,0.875,bicubic +mnasnet_100,74.650,25.350,92.114,7.886,4.38,224,0.875,bicubic +mobilevit_xs,74.634,25.366,92.346,7.654,2.32,256,0.900,bicubic +dla34,74.624,25.376,92.072,7.928,15.74,224,0.875,bilinear +gluon_resnet34_v1b,74.592,25.408,91.988,8.012,21.80,224,0.875,bicubic +pit_ti_distilled_224,74.534,25.466,92.096,7.904,5.10,224,0.900,bicubic +deit_tiny_distilled_patch16_224,74.512,25.488,91.890,8.110,5.91,224,0.900,bicubic +vgg19_bn,74.214,25.786,91.844,8.156,143.68,224,0.875,bilinear +spnasnet_100,74.090,25.910,91.816,8.184,4.42,224,0.875,bilinear +regnety_004,74.024,25.976,91.756,8.244,4.34,224,0.875,bicubic +ghostnet_100,73.980,26.020,91.458,8.542,5.18,224,0.875,bilinear +crossvit_9_240,73.960,26.040,91.964,8.036,8.55,240,0.875,bicubic +xcit_nano_12_p8_224,73.916,26.084,92.168,7.832,3.05,224,1.000,bicubic +regnetx_006,73.856,26.144,91.672,8.328,6.20,224,0.875,bicubic +vit_base_patch32_224_sam,73.692,26.308,91.012,8.988,88.22,224,0.900,bicubic +tf_mobilenetv3_large_075,73.440,26.560,91.348,8.652,3.99,224,0.875,bilinear vgg16_bn,73.350,26.650,91.504,8.496,138.37,224,0.875,bilinear -crossvit_tiny_240,73.332,26.668,91.914,8.086,7.01,240,0.875,bicubic -tv_resnet34,73.306,26.694,91.424,8.576,21.80,224,0.875,bilinear -swsl_resnet18,73.276,26.724,91.736,8.264,11.69,224,0.875,bilinear -convit_tiny,73.114,26.886,91.714,8.286,5.71,224,0.875,bicubic -skresnet18,73.036,26.964,91.168,8.832,11.96,224,0.875,bicubic -semnasnet_075,72.972,27.028,91.136,8.864,2.91,224,0.875,bicubic -mobilenetv2_100,72.970,27.030,91.020,8.980,3.50,224,0.875,bicubic +crossvit_tiny_240,73.338,26.662,91.914,8.086,7.01,240,0.875,bicubic +tv_resnet34,73.308,26.692,91.424,8.576,21.80,224,0.875,bilinear +swsl_resnet18,73.274,26.726,91.736,8.264,11.69,224,0.875,bilinear +convit_tiny,73.114,26.886,91.720,8.280,5.71,224,0.875,bicubic +skresnet18,73.034,26.966,91.166,8.834,11.96,224,0.875,bicubic +semnasnet_075,72.974,27.026,91.134,8.866,2.91,224,0.875,bicubic +mobilenetv2_100,72.956,27.044,91.010,8.990,3.50,224,0.875,bicubic pit_ti_224,72.912,27.088,91.406,8.594,4.85,224,0.900,bicubic -ssl_resnet18,72.608,27.392,91.424,8.576,11.69,224,0.875,bilinear -regnetx_004,72.392,27.608,90.832,9.168,5.16,224,0.875,bicubic -vgg19,72.366,27.634,90.870,9.130,143.67,224,0.875,bilinear -hrnet_w18_small,72.338,27.662,90.680,9.320,13.19,224,0.875,bilinear -xcit_nano_12_p16_224_dist,72.302,27.698,90.858,9.142,3.05,224,1.000,bicubic -resnet18d,72.250,27.750,90.688,9.312,11.71,224,0.875,bicubic -tf_mobilenetv3_large_minimal_100,72.250,27.750,90.630,9.370,3.92,224,0.875,bilinear -deit_tiny_patch16_224,72.172,27.828,91.114,8.886,5.72,224,0.900,bicubic -lcnet_100,72.104,27.896,90.376,9.624,2.95,224,0.875,bicubic -mixer_l16_224,72.054,27.946,87.662,12.338,208.20,224,0.875,bicubic -vit_tiny_r_s16_p8_224,71.792,28.208,90.822,9.178,6.34,224,0.900,bicubic -legacy_seresnet18,71.742,28.258,90.332,9.668,11.78,224,0.875,bicubic -vgg13_bn,71.594,28.406,90.376,9.624,133.05,224,0.875,bilinear +ssl_resnet18,72.604,27.396,91.424,8.576,11.69,224,0.875,bilinear +regnetx_004,72.396,27.604,90.838,9.162,5.16,224,0.875,bicubic +vgg19,72.366,27.634,90.872,9.128,143.67,224,0.875,bilinear +resnet14t,72.356,27.644,90.340,9.660,10.08,224,0.950,bilinear +hrnet_w18_small,72.336,27.664,90.680,9.320,13.19,224,0.875,bilinear +xcit_nano_12_p16_224_dist,72.302,27.698,90.862,9.138,3.05,224,1.000,bicubic +resnet18d,72.258,27.742,90.688,9.312,11.71,224,0.875,bicubic +tf_mobilenetv3_large_minimal_100,72.250,27.750,90.620,9.380,3.92,224,0.875,bilinear +deit_tiny_patch16_224,72.174,27.826,91.114,8.886,5.72,224,0.900,bicubic +lcnet_100,72.110,27.890,90.378,9.622,2.95,224,0.875,bicubic +mixer_l16_224,72.066,27.934,87.666,12.334,208.20,224,0.875,bicubic +vit_tiny_r_s16_p8_224,71.794,28.206,90.818,9.182,6.34,224,0.900,bicubic +legacy_seresnet18,71.740,28.260,90.330,9.670,11.78,224,0.875,bicubic +vgg13_bn,71.598,28.402,90.376,9.624,133.05,224,0.875,bilinear vgg16,71.590,28.410,90.382,9.618,138.36,224,0.875,bilinear -tinynet_c,71.228,28.772,89.750,10.250,2.46,184,0.875,bicubic -gluon_resnet18_v1b,70.834,29.166,89.762,10.238,11.69,224,0.875,bicubic +tinynet_c,71.228,28.772,89.748,10.252,2.46,184,0.875,bicubic +edgenext_xx_small,71.106,28.894,90.032,9.968,1.33,256,0.900,bicubic +gluon_resnet18_v1b,70.838,29.162,89.762,10.238,11.69,224,0.875,bicubic vgg11_bn,70.360,29.640,89.802,10.198,132.87,224,0.875,bilinear -regnety_002,70.254,29.746,89.532,10.468,3.16,224,0.875,bicubic -xcit_nano_12_p16_224,69.954,30.046,89.754,10.246,3.05,224,1.000,bicubic +regnety_002,70.256,29.744,89.534,10.466,3.16,224,0.875,bicubic +mobilevitv2_050,70.140,29.860,89.930,10.070,1.37,256,0.888,bicubic +xcit_nano_12_p16_224,69.954,30.046,89.756,10.244,3.05,224,1.000,bicubic vgg13,69.926,30.074,89.246,10.754,133.05,224,0.875,bilinear -resnet18,69.744,30.256,89.082,10.918,11.69,224,0.875,bilinear -vgg11,69.028,30.972,88.626,11.374,132.86,224,0.875,bilinear -mobilevit_xxs,68.920,31.080,88.944,11.056,1.27,256,0.900,bicubic -lcnet_075,68.816,31.184,88.370,11.630,2.36,224,0.875,bicubic -regnetx_002,68.756,31.244,88.556,11.444,2.68,224,0.875,bicubic -tf_mobilenetv3_small_100,67.924,32.076,87.664,12.336,2.54,224,0.875,bilinear -dla60x_c,67.892,32.108,88.426,11.574,1.32,224,0.875,bilinear -mobilenetv3_small_100,67.656,32.344,87.634,12.366,2.54,224,0.875,bicubic -tinynet_d,66.958,33.042,87.064,12.936,2.34,152,0.875,bicubic -mnasnet_small,66.206,33.794,86.508,13.492,2.03,224,0.875,bicubic -dla46x_c,65.970,34.030,86.980,13.020,1.07,224,0.875,bilinear -mobilenetv2_050,65.942,34.058,86.082,13.918,1.97,224,0.875,bicubic -tf_mobilenetv3_small_075,65.714,34.286,86.134,13.866,2.04,224,0.875,bilinear -mobilenetv3_small_075,65.242,34.758,85.438,14.562,2.04,224,0.875,bicubic -dla46_c,64.866,35.134,86.294,13.706,1.30,224,0.875,bilinear -lcnet_050,63.100,36.900,84.382,15.618,1.88,224,0.875,bicubic -tf_mobilenetv3_small_minimal_100,62.908,37.092,84.234,15.766,2.04,224,0.875,bilinear -tinynet_e,59.856,40.144,81.764,18.236,2.04,106,0.875,bicubic +resnet18,69.748,30.252,89.084,10.916,11.69,224,0.875,bilinear +vgg11,69.028,30.972,88.628,11.372,132.86,224,0.875,bilinear +mobilevit_xxs,68.920,31.080,88.946,11.054,1.27,256,0.900,bicubic +lcnet_075,68.814,31.186,88.364,11.636,2.36,224,0.875,bicubic +regnetx_002,68.754,31.246,88.556,11.444,2.68,224,0.875,bicubic +resnet10t,68.308,31.692,88.080,11.920,5.44,224,0.950,bilinear +tf_mobilenetv3_small_100,67.926,32.074,87.668,12.332,2.54,224,0.875,bilinear +dla60x_c,67.880,32.120,88.434,11.566,1.32,224,0.875,bilinear +mobilenetv3_small_100,67.658,32.342,87.634,12.366,2.54,224,0.875,bicubic +tinynet_d,66.962,33.038,87.064,12.936,2.34,152,0.875,bicubic +mnasnet_small,66.206,33.794,86.506,13.494,2.03,224,0.875,bicubic +dla46x_c,65.952,34.048,86.986,13.014,1.07,224,0.875,bilinear +mobilenetv2_050,65.944,34.056,86.080,13.920,1.97,224,0.875,bicubic +tf_mobilenetv3_small_075,65.712,34.288,86.130,13.870,2.04,224,0.875,bilinear +mobilenetv3_small_075,65.238,34.762,85.440,14.560,2.04,224,0.875,bicubic +dla46_c,64.872,35.128,86.302,13.698,1.30,224,0.875,bilinear +lcnet_050,63.094,36.906,84.382,15.618,1.88,224,0.875,bicubic +tf_mobilenetv3_small_minimal_100,62.900,37.100,84.234,15.766,2.04,224,0.875,bilinear +tinynet_e,59.856,40.144,81.766,18.234,2.04,106,0.875,bicubic mobilenetv3_small_050,57.890,42.110,80.194,19.806,1.59,224,0.875,bicubic diff --git a/results/results-imagenetv2-matched-frequency.csv b/results/results-imagenetv2-matched-frequency.csv index f6b5b99c..131dd32e 100644 --- a/results/results-imagenetv2-matched-frequency.csv +++ b/results/results-imagenetv2-matched-frequency.csv @@ -1,591 +1,669 @@ -model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation,top1_diff,top5_diff,rank_diff +model,top1,top1_err,top5,top5_err,param_count,img_size,crop_pct,interpolation,top1_diff,top5_diff,rank_diff tf_efficientnet_l2_ns_475,80.460,19.540,95.730,4.270,480.31,475,0.936,bicubic,-7.772,-2.816,+3 -tf_efficientnet_l2_ns,80.250,19.750,95.840,4.160,480.31,800,0.960,bicubic,-8.098,-2.808,+1 -beit_large_patch16_512,79.940,20.060,95.350,4.650,305.67,512,1.000,bicubic,-8.660,-3.306,-2 -beit_large_patch16_384,79.500,20.500,95.170,4.830,305.00,384,1.000,bicubic,-8.904,-3.438,-2 -beit_large_patch16_224,78.810,21.190,94.600,5.400,304.43,224,0.900,bicubic,-8.664,-3.704,+1 -tf_efficientnet_b7_ns,78.510,21.490,94.380,5.620,66.35,600,0.949,bicubic,-8.328,-3.716,+7 -volo_d5_512,77.970,22.030,94.170,5.830,296.09,512,1.150,bicubic,-9.072,-3.798,+3 -vit_large_patch16_384,77.940,22.060,94.440,5.560,304.72,384,1.000,bicubic,-9.140,-3.860,+1 -volo_d5_448,77.770,22.230,94.060,5.940,295.91,448,1.150,bicubic,-9.182,-3.880,+3 -volo_d4_448,77.750,22.250,93.930,6.070,193.41,448,1.150,bicubic,-9.040,-3.952,+5 -convnext_large_384_in22ft1k,77.730,22.270,94.080,5.920,197.77,384,1.000,bicubic,-9.666,-4.288,-4 -convnext_xlarge_384_in22ft1k,77.710,22.290,94.200,5.800,350.20,384,1.000,bicubic,-9.836,-4.286,-7 -tf_efficientnet_b6_ns,77.280,22.720,93.900,6.100,43.04,528,0.942,bicubic,-9.174,-3.982,+7 -volo_d3_448,77.080,22.920,94.110,5.890,86.63,448,1.000,bicubic,-9.416,-3.600,+4 -vit_large_r50_s32_384,77.060,22.940,93.720,6.280,329.09,384,1.000,bicubic,-9.122,-4.200,+10 -swin_large_patch4_window12_384,77.040,22.960,93.750,6.250,196.74,384,1.000,bicubic,-10.110,-4.490,-8 -tf_efficientnetv2_xl_in21ft1k,77.040,22.960,93.270,6.730,208.12,512,1.000,bicubic,-9.378,-4.596,+5 -tf_efficientnetv2_l_in21ft1k,76.940,23.060,93.960,6.040,118.52,480,1.000,bicubic,-9.364,-4.018,+6 -beit_base_patch16_384,76.890,23.110,93.910,6.090,86.74,384,1.000,bicubic,-9.908,-4.226,-5 -ig_resnext101_32x48d,76.880,23.120,93.310,6.690,828.41,224,0.875,bilinear,-8.556,-4.266,+26 -cait_m48_448,76.860,23.140,93.370,6.630,356.46,448,1.000,bicubic,-9.626,-4.382,-2 -ig_resnext101_32x32d,76.820,23.180,93.210,6.790,468.53,224,0.875,bilinear,-8.280,-4.224,+37 -tf_efficientnet_b5_ns,76.810,23.190,93.580,6.420,30.39,456,0.934,bicubic,-9.280,-4.170,+4 -convnext_xlarge_in22ft1k,76.770,23.230,93.550,6.450,350.20,224,0.875,bicubic,-10.232,-4.662,-13 +tf_efficientnet_l2_ns,80.250,19.750,95.840,4.160,480.31,800,0.960,bicubic,-8.100,-2.810,+1 +beit_large_patch16_512,79.940,20.060,95.350,4.650,305.67,512,1.000,bicubic,-8.662,-3.306,-2 +beit_large_patch16_384,79.500,20.500,95.170,4.830,305.00,384,1.000,bicubic,-8.906,-3.436,-2 +deit3_huge_patch14_224_in21ft1k,79.160,20.840,94.860,5.140,632.13,224,1.000,bicubic,-8.020,-3.400,+5 +deit3_large_patch16_384_in21ft1k,79.100,20.900,94.880,5.120,304.76,384,1.000,bicubic,-8.616,-3.632,-1 +beit_large_patch16_224,78.820,21.180,94.610,5.390,304.43,224,0.900,bicubic,-8.656,-3.694,0 +deit3_large_patch16_224_in21ft1k,78.630,21.370,94.720,5.280,304.37,224,1.000,bicubic,-8.352,-3.518,+8 +tf_efficientnet_b7_ns,78.520,21.480,94.390,5.610,66.35,600,0.949,bicubic,-8.312,-3.706,+10 +volo_d5_512,77.970,22.030,94.160,5.840,296.09,512,1.150,bicubic,-9.070,-3.808,+4 +vit_large_patch16_384,77.940,22.060,94.440,5.560,304.72,384,1.000,bicubic,-9.140,-3.860,+2 +deit3_base_patch16_384_in21ft1k,77.880,22.120,94.030,5.970,86.88,384,1.000,bicubic,-8.862,-4.082,+10 +volo_d5_448,77.770,22.230,94.050,5.950,295.91,448,1.150,bicubic,-9.184,-3.890,+4 +volo_d4_448,77.750,22.250,93.930,6.070,193.41,448,1.150,bicubic,-9.042,-3.952,+7 +convnext_large_384_in22ft1k,77.730,22.270,94.080,5.920,197.77,384,1.000,bicubic,-9.666,-4.286,-6 +convnext_xlarge_384_in22ft1k,77.710,22.290,94.200,5.800,350.20,384,1.000,bicubic,-9.834,-4.286,-10 +swinv2_large_window12to24_192to384_22kft1k,77.310,22.690,93.930,6.070,196.74,384,1.000,bicubic,-10.146,-4.322,-9 +tf_efficientnet_b6_ns,77.280,22.720,93.890,6.110,43.04,528,0.942,bicubic,-9.170,-3.996,+9 +swinv2_base_window12to24_192to384_22kft1k,77.170,22.830,94.260,5.740,87.92,384,1.000,bicubic,-9.938,-3.976,-7 +volo_d3_448,77.070,22.930,94.110,5.890,86.63,448,1.000,bicubic,-9.426,-3.600,+5 +vit_large_r50_s32_384,77.070,22.930,93.720,6.280,329.09,384,1.000,bicubic,-9.110,-4.200,+12 +tf_efficientnetv2_xl_in21ft1k,77.040,22.960,93.270,6.730,208.12,512,1.000,bicubic,-9.380,-4.598,+7 +swin_large_patch4_window12_384,77.030,22.970,93.750,6.250,196.74,384,1.000,bicubic,-10.122,-4.490,-12 +tf_efficientnetv2_l_in21ft1k,76.940,23.060,93.960,6.040,118.52,480,1.000,bicubic,-9.364,-4.020,+7 +swinv2_large_window12to16_192to256_22kft1k,76.930,23.070,93.540,6.460,196.74,256,0.900,bicubic,-10.016,-4.570,-7 +beit_base_patch16_384,76.900,23.100,93.910,6.090,86.74,384,1.000,bicubic,-9.898,-4.226,-6 +ig_resnext101_32x48d,76.880,23.120,93.310,6.690,828.41,224,0.875,bilinear,-8.556,-4.266,+30 +cait_m48_448,76.870,23.130,93.370,6.630,356.46,448,1.000,bicubic,-9.618,-4.380,-2 +ig_resnext101_32x32d,76.820,23.180,93.200,6.800,468.53,224,0.875,bilinear,-8.280,-4.234,+42 +tf_efficientnet_b5_ns,76.810,23.190,93.580,6.420,30.39,456,0.934,bicubic,-9.278,-4.172,+5 +convnext_xlarge_in22ft1k,76.770,23.230,93.550,6.450,350.20,224,0.875,bicubic,-10.232,-4.662,-16 +deit3_large_patch16_384,76.690,23.310,93.350,6.650,304.76,384,1.000,bicubic,-9.116,-4.246,+14 xcit_large_24_p8_384_dist,76.620,23.380,93.090,6.910,188.93,384,1.000,bicubic,-9.378,-4.594,+7 -convnext_base_384_in22ft1k,76.570,23.430,93.720,6.280,88.59,384,1.000,bicubic,-9.974,-4.470,-9 -volo_d5_224,76.570,23.430,93.300,6.700,295.46,224,0.960,bicubic,-9.502,-4.278,+1 -vit_base_patch16_384,76.490,23.510,93.770,6.230,86.86,384,1.000,bicubic,-9.520,-4.232,+3 -convnext_large_in22ft1k,76.440,23.560,93.470,6.530,197.77,224,0.875,bicubic,-10.196,-4.558,-13 -cait_m36_384,76.320,23.680,93.060,6.940,271.22,384,1.000,bicubic,-9.732,-4.670,-1 -vit_large_patch16_224,76.300,23.700,93.600,6.400,304.33,224,0.900,bicubic,-9.538,-4.220,+3 -swin_large_patch4_window7_224,76.290,23.710,93.400,6.600,196.53,224,0.900,bicubic,-10.024,-4.492,-9 -swin_base_patch4_window12_384,76.280,23.720,93.310,6.690,87.90,384,1.000,bicubic,-10.152,-4.746,-12 -tf_efficientnetv2_l,76.280,23.720,92.970,7.030,118.52,480,1.000,bicubic,-9.210,-4.402,+10 -cait_s36_384,76.220,23.780,92.970,7.030,68.37,384,1.000,bicubic,-9.242,-4.510,+10 -xcit_medium_24_p8_384_dist,76.140,23.860,92.970,7.030,84.32,384,1.000,bicubic,-9.674,-4.622,+1 -dm_nfnet_f6,76.130,23.870,93.110,6.890,438.36,576,0.956,bicubic,-10.012,-4.620,-11 -tf_efficientnet_b7_ap,76.090,23.910,92.970,7.030,66.35,600,0.949,bicubic,-9.030,-4.282,+20 -tf_efficientnet_b8_ap,76.090,23.910,92.730,7.270,87.41,672,0.954,bicubic,-9.282,-4.562,+12 -volo_d2_384,76.090,23.910,93.130,6.870,58.87,384,1.000,bicubic,-9.950,-4.442,-10 -vit_base_patch8_224,76.010,23.990,93.380,6.620,86.58,224,0.900,bicubic,-9.784,-4.414,-3 -volo_d4_224,76.000,24.000,93.010,6.990,192.96,224,0.960,bicubic,-9.874,-4.458,-9 -xcit_large_24_p8_224_dist,75.990,24.010,92.730,7.270,188.93,224,1.000,bicubic,-9.408,-4.680,+7 -tf_efficientnetv2_m_in21ft1k,75.910,24.090,93.290,6.710,54.14,480,1.000,bicubic,-9.680,-4.454,-3 -dm_nfnet_f4,75.850,24.150,92.970,7.030,316.07,512,0.951,bicubic,-9.864,-4.552,-5 -xcit_large_24_p16_384_dist,75.820,24.180,92.750,7.250,189.10,384,1.000,bicubic,-9.934,-4.788,-7 -xcit_small_24_p8_384_dist,75.770,24.230,92.970,7.030,47.63,384,1.000,bicubic,-9.786,-4.602,-5 -ig_resnext101_32x16d,75.750,24.250,92.880,7.120,194.03,224,0.875,bilinear,-8.420,-4.318,+53 -tf_efficientnet_b4_ns,75.680,24.320,93.050,6.950,19.34,380,0.922,bicubic,-9.482,-4.420,+8 -volo_d1_384,75.620,24.380,93.070,6.930,26.78,384,1.000,bicubic,-9.628,-4.144,+4 +convnext_base_384_in22ft1k,76.580,23.420,93.720,6.280,88.59,384,1.000,bicubic,-9.962,-4.470,-10 +volo_d5_224,76.580,23.420,93.300,6.700,295.46,224,0.960,bicubic,-9.490,-4.278,+1 +deit3_base_patch16_224_in21ft1k,76.540,23.460,93.560,6.440,86.59,224,1.000,bicubic,-9.176,-4.184,+14 +vit_base_patch16_384,76.480,23.520,93.770,6.230,86.86,384,1.000,bicubic,-9.526,-4.234,+2 +swinv2_base_window12to16_192to256_22kft1k,76.430,23.570,93.690,6.310,87.92,256,0.900,bicubic,-9.840,-4.206,-6 +convnext_large_in22ft1k,76.430,23.570,93.470,6.530,197.77,224,0.875,bicubic,-10.206,-4.558,-16 +cait_m36_384,76.330,23.670,93.050,6.950,271.22,384,1.000,bicubic,-9.724,-4.680,-3 +vit_large_patch16_224,76.300,23.700,93.600,6.400,304.33,224,0.900,bicubic,-9.544,-4.222,+1 +swin_base_patch4_window12_384,76.290,23.710,93.320,6.680,87.90,384,1.000,bicubic,-10.142,-4.736,-14 +tf_efficientnetv2_l,76.280,23.720,92.970,7.030,118.52,480,1.000,bicubic,-9.208,-4.402,+12 +swin_large_patch4_window7_224,76.270,23.730,93.410,6.590,196.53,224,0.900,bicubic,-10.050,-4.482,-14 +cait_s36_384,76.210,23.790,92.970,7.030,68.37,384,1.000,bicubic,-9.250,-4.508,+11 +xcit_medium_24_p8_384_dist,76.140,23.860,92.980,7.020,84.32,384,1.000,bicubic,-9.676,-4.612,-2 +dm_nfnet_f6,76.130,23.870,93.110,6.890,438.36,576,0.956,bicubic,-10.012,-4.620,-13 +tf_efficientnet_b7_ap,76.100,23.900,92.970,7.030,66.35,600,0.949,bicubic,-9.020,-4.282,+22 +volo_d2_384,76.090,23.910,93.130,6.870,58.87,384,1.000,bicubic,-9.946,-4.444,-11 +tf_efficientnet_b8_ap,76.080,23.920,92.730,7.270,87.41,672,0.954,bicubic,-9.292,-4.564,+12 +vit_base_patch8_224,76.010,23.990,93.370,6.630,86.58,224,0.900,bicubic,-9.780,-4.422,-4 +volo_d4_224,76.010,23.990,93.010,6.990,192.96,224,0.960,bicubic,-9.866,-4.458,-11 +xcit_large_24_p8_224_dist,75.990,24.010,92.730,7.270,188.93,224,1.000,bicubic,-9.408,-4.680,+8 +tf_efficientnetv2_m_in21ft1k,75.920,24.080,93.280,6.720,54.14,480,1.000,bicubic,-9.666,-4.466,-2 +dm_nfnet_f4,75.850,24.150,92.970,7.030,316.07,512,0.951,bicubic,-9.864,-4.550,-4 +xcit_large_24_p16_384_dist,75.820,24.180,92.750,7.250,189.10,384,1.000,bicubic,-9.932,-4.788,-8 +deit3_huge_patch14_224,75.790,24.210,92.760,7.240,632.13,224,0.900,bicubic,-9.416,-4.598,+10 +xcit_small_24_p8_384_dist,75.770,24.230,92.970,7.030,47.63,384,1.000,bicubic,-9.784,-4.602,-5 +ig_resnext101_32x16d,75.750,24.250,92.880,7.120,194.03,224,0.875,bilinear,-8.420,-4.318,+63 +tf_efficientnet_b4_ns,75.670,24.330,93.050,6.950,19.34,380,0.922,bicubic,-9.490,-4.420,+9 +volo_d1_384,75.620,24.380,93.060,6.940,26.78,384,1.000,bicubic,-9.630,-4.154,+4 volo_d3_224,75.610,24.390,93.000,7.000,86.33,224,0.960,bicubic,-9.802,-4.280,-2 -vit_base_r50_s16_384,75.590,24.410,92.790,7.210,98.95,384,1.000,bicubic,-9.380,-4.500,+17 -convnext_base_in22ft1k,75.570,24.430,93.130,6.870,88.59,224,0.875,bicubic,-10.254,-4.736,-18 -deit_base_distilled_patch16_384,75.540,24.460,92.500,7.500,87.63,384,1.000,bicubic,-9.882,-4.906,-6 -tf_efficientnetv2_m,75.520,24.480,92.620,7.380,54.14,480,1.000,bicubic,-9.518,-4.658,+10 -regnetz_e8,75.490,24.510,92.690,7.310,57.70,320,1.000,bicubic,-9.540,-4.574,+10 -cait_s24_384,75.480,24.520,92.590,7.410,47.06,384,1.000,bicubic,-9.566,-4.756,+7 -xcit_medium_24_p8_224_dist,75.470,24.530,92.900,7.100,84.32,224,1.000,bicubic,-9.602,-4.380,+4 -swsl_resnext101_32x8d,75.420,24.580,92.750,7.250,88.79,224,0.875,bilinear,-8.870,-4.430,+34 -tf_efficientnet_b6_ap,75.380,24.620,92.440,7.560,43.04,528,0.942,bicubic,-9.406,-4.698,+15 -beit_base_patch16_224,75.370,24.630,93.040,6.960,86.53,224,0.900,bicubic,-9.858,-4.618,-6 -volo_d2_224,75.310,24.690,92.510,7.490,58.68,224,0.960,bicubic,-9.884,-4.678,-6 -dm_nfnet_f3,75.210,24.790,92.940,7.060,254.92,416,0.940,bicubic,-10.312,-4.522,-20 -efficientnetv2_rw_m,75.160,24.840,92.570,7.430,53.24,416,1.000,bicubic,-9.652,-4.576,+10 -ecaresnet269d,75.120,24.880,92.840,7.160,102.09,352,1.000,bicubic,-9.856,-4.386,+3 -xcit_medium_24_p16_384_dist,75.100,24.900,92.450,7.550,84.40,384,1.000,bicubic,-10.322,-4.882,-19 -dm_nfnet_f5,75.000,25.000,92.600,7.400,377.21,544,0.954,bicubic,-10.816,-4.886,-31 -xcit_small_24_p8_224_dist,74.970,25.030,92.300,7.700,47.63,224,1.000,bicubic,-9.906,-4.888,+5 -tf_efficientnet_b8,74.920,25.080,92.330,7.670,87.41,672,0.954,bicubic,-10.448,-5.060,-17 -xcit_small_12_p8_384_dist,74.860,25.140,92.460,7.540,26.21,384,1.000,bicubic,-10.220,-4.820,-9 -eca_nfnet_l2,74.830,25.170,92.650,7.350,56.72,384,1.000,bicubic,-9.866,-4.614,+7 -tf_efficientnet_b7,74.720,25.280,92.220,7.780,66.35,600,0.949,bicubic,-10.216,-4.984,-2 -xcit_large_24_p16_224_dist,74.670,25.330,91.860,8.140,189.10,224,1.000,bicubic,-10.252,-5.272,-2 -dm_nfnet_f2,74.620,25.380,92.260,7.740,193.78,352,0.920,bicubic,-10.442,-4.980,-11 -xcit_small_24_p16_384_dist,74.600,25.400,92.450,7.550,47.67,384,1.000,bicubic,-10.494,-4.860,-15 -tf_efficientnet_b5_ap,74.590,25.410,91.990,8.010,30.39,456,0.934,bicubic,-9.666,-4.986,+20 -dm_nfnet_f1,74.570,25.430,92.260,7.740,132.63,320,0.910,bicubic,-10.054,-4.840,+2 -swin_base_patch4_window7_224,74.550,25.450,92.560,7.440,87.77,224,0.900,bicubic,-10.698,-5.002,-25 -seresnet152d,74.520,25.480,92.080,7.920,66.84,320,1.000,bicubic,-9.840,-4.960,+11 -regnetz_040,74.460,25.540,91.890,8.110,27.12,320,1.000,bicubic,-9.774,-5.042,+18 -resnest200e,74.460,25.540,91.860,8.140,70.20,320,0.909,bicubic,-9.368,-5.032,+41 -tf_efficientnetv2_s_in21ft1k,74.460,25.540,92.500,7.500,21.46,384,1.000,bicubic,-9.838,-4.754,+9 -regnetz_040h,74.440,25.560,92.240,7.760,28.94,320,1.000,bicubic,-10.056,-4.766,0 -resnetrs200,74.380,25.620,91.940,8.060,93.21,320,1.000,bicubic,-10.058,-5.140,+1 -efficientnetv2_rw_s,74.180,25.820,91.710,8.290,23.94,384,1.000,bicubic,-9.630,-5.012,+39 -cait_xs24_384,74.170,25.830,91.910,8.090,26.67,384,1.000,bicubic,-9.892,-4.980,+19 -resnest269e,74.170,25.830,91.930,8.070,110.93,416,0.928,bicubic,-10.350,-5.056,-6 -pit_b_distilled_224,74.160,25.840,91.670,8.330,74.79,224,0.900,bicubic,-9.980,-5.186,+15 -swsl_resnext101_32x4d,74.140,25.860,92.000,8.000,44.18,224,0.875,bilinear,-9.096,-4.764,+57 -eca_nfnet_l1,74.120,25.880,92.070,7.930,41.41,320,1.000,bicubic,-9.892,-4.958,+22 -volo_d1_224,74.120,25.880,92.030,7.970,26.63,224,0.960,bicubic,-10.042,-4.746,+11 -xcit_small_12_p16_384_dist,74.120,25.880,92.080,7.920,26.25,384,1.000,bicubic,-10.590,-5.038,-15 -vit_large_r50_s32_224,74.110,25.890,92.380,7.620,328.99,224,0.900,bicubic,-10.314,-4.786,-6 -convnext_large,74.070,25.930,91.560,8.440,197.77,224,0.875,bicubic,-10.222,-5.334,-2 -xcit_large_24_p8_224,74.070,25.930,90.890,9.110,188.93,224,1.000,bicubic,-10.324,-5.766,-6 -vit_base_patch16_224_miil,74.040,25.960,91.700,8.300,86.54,224,0.875,bilinear,-10.232,-5.102,-1 -resnetv2_152x4_bitm,74.010,25.990,92.330,7.670,936.53,480,1.000,bilinear,-10.906,-5.112,-25 -tf_efficientnetv2_s,74.000,26.000,91.530,8.470,21.46,384,1.000,bicubic,-9.886,-5.166,+18 -vit_base_patch16_224,74.000,26.000,92.470,7.530,86.57,224,0.900,bicubic,-10.528,-4.824,-19 -swsl_resnext101_32x16d,73.980,26.020,92.170,7.830,194.03,224,0.875,bilinear,-9.370,-4.674,+41 -regnetz_d32,73.970,26.030,91.950,8.050,27.58,320,0.950,bicubic,-10.052,-4.916,+9 -crossvit_18_dagger_408,73.960,26.040,91.410,8.590,44.61,408,1.000,bicubic,-10.234,-5.408,-2 -seresnext101_32x8d,73.940,26.060,91.450,8.550,93.57,288,1.000,bicubic,-10.264,-5.426,-4 -resnetrs420,73.920,26.080,91.760,8.240,191.89,416,1.000,bicubic,-11.090,-5.364,-37 -resnetv2_152x2_bitm,73.920,26.080,92.670,7.330,236.34,448,1.000,bilinear,-10.586,-4.764,-23 -xcit_small_12_p8_224_dist,73.920,26.080,91.720,8.280,26.21,224,1.000,bicubic,-10.316,-5.154,-9 -resmlp_big_24_224_in22ft1k,73.900,26.100,91.750,8.250,129.14,224,0.875,bicubic,-10.494,-5.370,-19 -tf_efficientnet_b6,73.900,26.100,91.750,8.250,43.04,528,0.942,bicubic,-10.210,-5.138,-4 -tf_efficientnet_b3_ns,73.890,26.110,91.870,8.130,12.23,300,0.904,bicubic,-10.158,-5.038,-1 -convnext_base,73.870,26.130,91.320,8.680,88.59,224,0.875,bicubic,-9.968,-5.430,+9 -vit_small_r26_s32_384,73.800,26.200,92.300,7.700,36.47,384,1.000,bicubic,-10.242,-5.028,-2 -regnetz_d8,73.760,26.240,92.020,7.980,23.37,320,1.000,bicubic,-10.292,-4.974,-5 -regnety_080,73.740,26.260,91.810,8.190,39.18,288,1.000,bicubic,-10.186,-5.078,+2 -resnetrs270,73.690,26.310,91.570,8.430,129.86,352,1.000,bicubic,-10.746,-5.400,-28 -resnetv2_101x3_bitm,73.690,26.310,92.470,7.530,387.93,448,1.000,bilinear,-10.752,-4.912,-31 -resnet200d,73.680,26.320,91.570,8.430,64.69,320,1.000,bicubic,-10.284,-5.254,-3 -ig_resnext101_32x8d,73.660,26.340,92.160,7.840,88.79,224,0.875,bilinear,-9.040,-4.470,+54 -xcit_medium_24_p16_224_dist,73.660,26.340,91.580,8.420,84.40,224,1.000,bicubic,-10.614,-5.360,-24 -regnety_064,73.570,26.430,91.350,8.650,30.58,288,1.000,bicubic,-10.150,-5.372,+10 -tf_efficientnet_b5,73.560,26.440,91.460,8.540,30.39,456,0.934,bicubic,-10.252,-5.288,+3 -resnet152d,73.520,26.480,91.230,8.770,60.21,320,1.000,bicubic,-10.158,-5.508,+13 -regnetv_064,73.480,26.520,91.600,8.400,30.58,288,1.000,bicubic,-10.234,-5.014,+9 -xcit_tiny_24_p8_384_dist,73.420,26.580,91.560,8.440,12.11,384,1.000,bicubic,-10.322,-5.150,+4 -resnetrs350,73.400,26.600,91.310,8.690,163.96,384,1.000,bicubic,-11.318,-5.678,-48 -twins_svt_large,73.390,26.610,90.910,9.090,99.27,224,0.900,bicubic,-10.290,-5.684,+8 -regnetz_d8_evos,73.380,26.620,91.640,8.360,23.46,320,0.950,bicubic,-10.674,-5.356,-20 -regnety_160,73.370,26.630,91.700,8.300,83.59,288,1.000,bicubic,-10.320,-5.076,+5 -efficientnet_b4,73.310,26.690,91.280,8.720,19.34,384,1.000,bicubic,-10.114,-5.316,+10 -swin_s3_base_224,73.310,26.690,91.190,8.810,71.13,224,0.900,bicubic,-10.622,-5.470,-15 -xcit_small_24_p16_224_dist,73.290,26.710,91.440,8.560,47.67,224,1.000,bicubic,-10.578,-5.284,-14 -resmlp_big_24_distilled_224,73.290,26.710,91.170,8.830,129.14,224,0.875,bicubic,-10.298,-5.478,+5 -vit_small_patch16_384,73.280,26.720,92.000,8.000,22.20,384,1.000,bicubic,-10.524,-5.102,-7 -deit_base_distilled_patch16_224,73.240,26.760,91.000,9.000,87.34,224,0.900,bicubic,-10.152,-5.486,+6 -resnetrs152,73.200,26.800,91.270,8.730,86.62,320,1.000,bicubic,-10.514,-5.476,-4 -xcit_medium_24_p8_224,73.150,26.850,90.280,9.720,84.32,224,1.000,bicubic,-10.586,-6.114,-7 -vit_base_patch32_384,73.130,26.870,91.250,8.750,88.30,384,1.000,bicubic,-10.218,-5.584,+7 -jx_nest_base,73.120,26.880,91.060,8.940,67.72,224,0.875,bicubic,-10.436,-5.302,-1 -xcit_small_24_p8_224,73.080,26.920,91.150,8.850,47.63,224,1.000,bicubic,-10.758,-5.486,-18 -cait_s24_224,73.070,26.930,91.120,8.880,46.92,224,1.000,bicubic,-10.388,-5.444,-2 -crossvit_15_dagger_408,72.960,27.040,91.090,8.910,28.50,408,1.000,bicubic,-10.876,-5.694,-19 -resnetv2_152x2_bit_teacher_384,72.900,27.100,91.550,8.450,236.34,384,1.000,bicubic,-10.944,-5.568,-23 -dm_nfnet_f0,72.880,27.120,91.080,8.920,71.49,256,0.900,bicubic,-10.506,-5.494,-2 -regnetv_040,72.880,27.120,91.100,8.900,20.64,288,1.000,bicubic,-10.320,-5.562,+5 -tf_efficientnet_b4_ap,72.880,27.120,90.980,9.020,19.34,380,0.922,bicubic,-10.372,-5.414,+1 -xception65p,72.790,27.210,90.910,9.090,39.82,299,0.940,bicubic,-10.336,-5.568,+9 -regnety_032,72.770,27.230,90.950,9.050,19.44,288,1.000,bicubic,-9.956,-5.474,+23 -regnety_040,72.720,27.280,90.720,9.280,20.65,288,1.000,bicubic,-10.316,-5.786,+12 -swin_s3_small_224,72.690,27.310,90.550,9.450,49.74,224,0.900,bicubic,-11.078,-5.902,-22 -resnext101_64x4d,72.620,27.380,90.840,9.160,83.46,288,1.000,bicubic,-10.520,-5.530,+2 -xcit_small_12_p8_224,72.610,27.390,90.670,9.330,26.21,224,1.000,bicubic,-10.734,-5.810,-8 -nfnet_l0,72.610,27.390,91.000,9.000,35.07,288,1.000,bicubic,-10.142,-5.518,+18 -pnasnet5large,72.610,27.390,90.500,9.500,86.06,331,0.911,bicubic,-10.180,-5.540,+16 -xception65,72.600,27.400,90.820,9.180,39.92,299,0.940,bicubic,-10.580,-5.772,-4 -resnest101e,72.580,27.420,90.820,9.180,48.28,256,0.875,bilinear,-10.310,-5.498,+9 -twins_pcpvt_large,72.580,27.420,90.700,9.300,60.99,224,0.900,bicubic,-10.554,-5.904,-2 -swsl_resnext50_32x4d,72.560,27.440,90.850,9.150,25.03,224,0.875,bilinear,-9.616,-5.382,+47 -twins_svt_base,72.560,27.440,90.460,9.540,56.07,224,0.900,bicubic,-10.578,-5.960,-5 -tresnet_xl_448,72.550,27.450,90.310,9.690,78.44,448,0.875,bilinear,-10.504,-5.862,0 -deit_base_patch16_384,72.540,27.460,90.270,9.730,86.86,384,1.000,bicubic,-10.566,-6.098,-3 -gc_efficientnetv2_rw_t,72.530,27.470,90.820,9.180,13.68,288,1.000,bicubic,-9.936,-5.476,+23 -resnetv2_50x3_bitm,72.510,27.490,91.760,8.240,217.32,448,1.000,bilinear,-11.504,-5.364,-50 -xcit_small_12_p16_224_dist,72.500,27.500,91.120,8.880,26.25,224,1.000,bicubic,-10.850,-5.294,-20 -xcit_tiny_24_p8_224_dist,72.450,27.550,90.920,9.080,12.11,224,1.000,bicubic,-10.114,-5.250,+16 -resnet101d,72.410,27.590,90.660,9.340,44.57,320,1.000,bicubic,-10.612,-5.788,-3 -jx_nest_small,72.370,27.630,90.700,9.300,38.35,224,0.875,bicubic,-10.748,-5.630,-10 -convnext_small,72.320,27.680,90.850,9.150,50.22,224,0.875,bicubic,-10.830,-5.582,-16 -regnetz_c16,72.300,27.700,90.820,9.180,13.46,320,0.940,bicubic,-10.216,-5.540,+15 +convnext_base_in22ft1k,75.580,24.420,93.130,6.870,88.59,224,0.875,bicubic,-10.244,-4.736,-20 +vit_base_r50_s16_384,75.580,24.420,92.790,7.210,98.95,384,1.000,bicubic,-9.396,-4.500,+17 +deit_base_distilled_patch16_384,75.550,24.450,92.500,7.500,87.63,384,1.000,bicubic,-9.872,-4.832,-6 +tf_efficientnetv2_m,75.520,24.480,92.620,7.380,54.14,480,1.000,bicubic,-9.516,-4.658,+12 +regnetz_e8,75.490,24.510,92.710,7.290,57.70,320,1.000,bicubic,-9.540,-4.554,+12 +cait_s24_384,75.480,24.520,92.600,7.400,47.06,384,1.000,bicubic,-9.570,-4.748,+9 +xcit_medium_24_p8_224_dist,75.470,24.530,92.900,7.100,84.32,224,1.000,bicubic,-9.600,-4.380,+6 +swsl_resnext101_32x8d,75.420,24.580,92.750,7.250,88.79,224,0.875,bilinear,-8.870,-4.432,+42 +tf_efficientnet_b6_ap,75.380,24.620,92.440,7.560,43.04,528,0.942,bicubic,-9.406,-4.698,+18 +beit_base_patch16_224,75.370,24.630,93.040,6.960,86.53,224,0.900,bicubic,-9.858,-4.616,-6 +volo_d2_224,75.300,24.700,92.510,7.490,58.68,224,0.960,bicubic,-9.894,-4.678,-5 +dm_nfnet_f3,75.200,24.800,92.940,7.060,254.92,416,0.940,bicubic,-10.322,-4.522,-20 +efficientnetv2_rw_m,75.160,24.840,92.570,7.430,53.24,416,1.000,bicubic,-9.652,-4.576,+13 +deit3_large_patch16_224,75.140,24.860,92.280,7.720,304.37,224,0.900,bicubic,-9.622,-4.758,+14 +ecaresnet269d,75.120,24.880,92.840,7.160,102.09,352,1.000,bicubic,-9.854,-4.386,+5 +xcit_medium_24_p16_384_dist,75.110,24.890,92.440,7.560,84.40,384,1.000,bicubic,-10.312,-4.966,-20 +deit3_small_patch16_384_in21ft1k,75.090,24.910,92.800,7.200,22.21,384,1.000,bicubic,-9.734,-4.684,+8 +convnext_small_384_in22ft1k,75.050,24.950,93.010,6.990,50.22,384,1.000,bicubic,-10.674,-4.854,-31 +dm_nfnet_f5,75.010,24.990,92.600,7.400,377.21,544,0.954,bicubic,-10.806,-4.886,-36 +xcit_small_24_p8_224_dist,74.980,25.020,92.300,7.700,47.63,224,1.000,bicubic,-9.896,-4.888,+4 +tf_efficientnet_b8,74.930,25.070,92.320,7.680,87.41,672,0.954,bicubic,-10.438,-5.072,-20 +xcit_small_12_p8_384_dist,74.860,25.140,92.460,7.540,26.21,384,1.000,bicubic,-10.220,-4.820,-11 +eca_nfnet_l2,74.830,25.170,92.650,7.350,56.72,384,1.000,bicubic,-9.866,-4.614,+8 +deit3_base_patch16_384,74.790,25.210,92.240,7.760,86.88,384,1.000,bicubic,-10.286,-5.014,-12 +tf_efficientnet_b7,74.720,25.280,92.220,7.780,66.35,600,0.949,bicubic,-10.214,-4.986,-4 +xcit_large_24_p16_224_dist,74.670,25.330,91.860,8.140,189.10,224,1.000,bicubic,-10.250,-5.272,-4 +dm_nfnet_f2,74.620,25.380,92.250,7.750,193.78,352,0.920,bicubic,-10.446,-4.992,-13 +tf_efficientnet_b5_ap,74.590,25.410,91.990,8.010,30.39,456,0.934,bicubic,-9.664,-4.988,+26 +xcit_small_24_p16_384_dist,74.580,25.420,92.450,7.550,47.67,384,1.000,bicubic,-10.508,-4.858,-19 +dm_nfnet_f1,74.570,25.430,92.260,7.740,132.63,320,0.910,bicubic,-10.054,-4.838,+2 +swin_base_patch4_window7_224,74.540,25.460,92.560,7.440,87.77,224,0.900,bicubic,-10.710,-5.002,-29 +seresnet152d,74.520,25.480,92.080,7.920,66.84,320,1.000,bicubic,-9.844,-4.964,+14 +regnetz_040,74.460,25.540,91.900,8.100,27.12,320,1.000,bicubic,-9.776,-5.032,+22 +resnest200e,74.460,25.540,91.860,8.140,70.20,320,0.909,bicubic,-9.368,-5.032,+49 +tf_efficientnetv2_s_in21ft1k,74.450,25.550,92.500,7.500,21.46,384,1.000,bicubic,-9.846,-4.754,+13 +regnetz_040h,74.440,25.560,92.240,7.760,28.94,320,1.000,bicubic,-10.056,-4.766,+3 +resnetrs200,74.360,25.640,91.940,8.060,93.21,320,1.000,bicubic,-10.080,-5.140,+4 +seresnextaa101d_32x8d,74.320,25.680,91.720,8.280,93.59,288,1.000,bicubic,-10.252,-5.350,-4 +convnext_small_in22ft1k,74.210,25.790,92.550,7.450,50.22,224,0.875,bicubic,-10.358,-4.846,-4 +seresnext101d_32x8d,74.210,25.790,91.860,8.140,93.59,288,1.000,bicubic,-10.152,-5.058,+7 +efficientnetv2_rw_s,74.180,25.820,91.710,8.290,23.94,384,1.000,bicubic,-9.630,-5.014,+44 +resnest269e,74.170,25.830,91.930,8.070,110.93,416,0.928,bicubic,-10.348,-5.056,-5 +cait_xs24_384,74.170,25.830,91.910,8.090,26.67,384,1.000,bicubic,-9.894,-4.980,+22 +pit_b_distilled_224,74.160,25.840,91.660,8.340,74.79,224,0.900,bicubic,-9.982,-5.196,+18 +swsl_resnext101_32x4d,74.140,25.860,91.990,8.010,44.18,224,0.875,bilinear,-9.100,-4.770,+68 +vit_large_r50_s32_224,74.120,25.880,92.380,7.620,328.99,224,0.900,bicubic,-10.310,-4.786,-3 +eca_nfnet_l1,74.120,25.880,92.070,7.930,41.41,320,1.000,bicubic,-9.892,-4.962,+25 +xcit_small_12_p16_384_dist,74.120,25.880,92.070,7.930,26.25,384,1.000,bicubic,-10.588,-5.046,-18 +volo_d1_224,74.120,25.880,92.030,7.970,26.63,224,0.960,bicubic,-10.044,-4.744,+12 +convnext_large,74.070,25.930,91.550,8.450,197.77,224,0.875,bicubic,-10.226,-5.344,-1 +xcit_large_24_p8_224,74.070,25.930,90.890,9.110,188.93,224,1.000,bicubic,-10.322,-5.768,-6 +vit_base_patch16_224_miil,74.040,25.960,91.700,8.300,86.54,224,0.875,bilinear,-10.232,-5.102,0 +resnetv2_152x4_bitm,74.010,25.990,92.340,7.660,936.53,480,1.000,bilinear,-10.908,-5.102,-30 +swinv2_base_window16_256,74.010,25.990,91.750,8.250,87.92,256,0.900,bicubic,-10.582,-5.324,-21 +vit_base_patch16_224,74.000,26.000,92.470,7.530,86.57,224,0.900,bicubic,-10.530,-4.826,-19 +tf_efficientnetv2_s,74.000,26.000,91.530,8.470,21.46,384,1.000,bicubic,-9.884,-5.168,+20 +swsl_resnext101_32x16d,73.990,26.010,92.180,7.820,194.03,224,0.875,bilinear,-9.360,-4.664,+52 +regnetz_d32,73.970,26.030,91.950,8.050,27.58,320,0.950,bicubic,-10.054,-4.918,+12 +crossvit_18_dagger_408,73.970,26.030,91.410,8.590,44.61,408,1.000,bicubic,-10.224,-5.408,0 +seresnext101_32x8d,73.940,26.060,91.450,8.550,93.57,288,1.000,bicubic,-10.264,-5.424,-2 +resnetv2_152x2_bitm,73.920,26.080,92.670,7.330,236.34,448,1.000,bilinear,-10.590,-4.764,-23 +resnetrs420,73.920,26.080,91.760,8.240,191.89,416,1.000,bicubic,-11.088,-5.364,-44 +xcit_small_12_p8_224_dist,73.920,26.080,91.720,8.280,26.21,224,1.000,bicubic,-10.310,-5.154,-7 +resmlp_big_24_224_in22ft1k,73.900,26.100,91.750,8.250,129.14,224,0.875,bicubic,-10.498,-5.368,-20 +tf_efficientnet_b6,73.890,26.110,91.750,8.250,43.04,528,0.942,bicubic,-10.218,-5.138,-2 +tf_efficientnet_b3_ns,73.880,26.120,91.870,8.130,12.23,300,0.904,bicubic,-10.168,-5.042,+3 +convnext_base,73.870,26.130,91.320,8.680,88.59,224,0.875,bicubic,-9.970,-5.430,+13 +deit3_small_patch16_224_in21ft1k,73.840,26.160,91.960,8.040,22.06,224,1.000,bicubic,-9.236,-4.816,+57 +vit_small_r26_s32_384,73.800,26.200,92.290,7.710,36.47,384,1.000,bicubic,-10.248,-5.038,-1 +regnetz_d8,73.760,26.240,92.020,7.980,23.37,320,1.000,bicubic,-10.292,-4.976,-4 +regnety_080,73.730,26.270,91.790,8.210,39.18,288,1.000,bicubic,-10.198,-5.098,+4 +resnetrs270,73.690,26.310,91.570,8.430,129.86,352,1.000,bicubic,-10.746,-5.404,-30 +resnetv2_101x3_bitm,73.680,26.320,92.470,7.530,387.93,448,1.000,bilinear,-10.764,-4.912,-33 +resnet200d,73.680,26.320,91.570,8.430,64.69,320,1.000,bicubic,-10.280,-5.254,-1 +ig_resnext101_32x8d,73.660,26.340,92.160,7.840,88.79,224,0.875,bilinear,-9.038,-4.472,+71 +xcit_medium_24_p16_224_dist,73.650,26.350,91.580,8.420,84.40,224,1.000,bicubic,-10.628,-5.360,-25 +regnety_064,73.590,26.410,91.350,8.650,30.58,288,1.000,bicubic,-10.130,-5.376,+14 +tf_efficientnet_b5,73.560,26.440,91.460,8.540,30.39,456,0.934,bicubic,-10.254,-5.288,+6 +swinv2_base_window8_256,73.540,26.460,91.520,8.480,87.92,256,0.900,bicubic,-10.722,-5.402,-26 +resnet152d,73.530,26.470,91.230,8.770,60.21,320,1.000,bicubic,-10.148,-5.510,+16 +regnetv_064,73.490,26.510,91.590,8.410,30.58,288,1.000,bicubic,-10.222,-5.156,+12 +deit3_base_patch16_224,73.480,26.520,91.290,8.710,86.59,224,0.900,bicubic,-10.312,-5.294,+5 +sequencer2d_l,73.480,26.520,91.100,8.900,54.30,224,0.875,bicubic,-9.926,-5.400,+21 +xcit_tiny_24_p8_384_dist,73.420,26.580,91.560,8.440,12.11,384,1.000,bicubic,-10.326,-5.152,+5 +resnetrs350,73.400,26.600,91.310,8.690,163.96,384,1.000,bicubic,-11.312,-5.680,-56 +twins_svt_large,73.390,26.610,90.910,9.090,99.27,224,0.900,bicubic,-10.290,-5.684,+9 +regnetz_d8_evos,73.370,26.630,91.640,8.360,23.46,320,0.950,bicubic,-10.680,-5.356,-20 +regnety_160,73.360,26.640,91.700,8.300,83.59,288,1.000,bicubic,-10.332,-5.076,+6 +swin_s3_base_224,73.320,26.680,91.190,8.810,71.13,224,0.900,bicubic,-10.612,-5.470,-15 +efficientnet_b4,73.310,26.690,91.280,8.720,19.34,384,1.000,bicubic,-10.114,-5.318,+13 +vit_small_patch16_384,73.300,26.700,92.000,8.000,22.20,384,1.000,bicubic,-10.500,-5.100,-5 +resmlp_big_24_distilled_224,73.290,26.710,91.160,8.840,129.14,224,0.875,bicubic,-10.298,-5.488,+5 +swinv2_small_window16_256,73.270,26.730,91.270,8.730,49.73,256,0.900,bicubic,-10.940,-5.600,-36 +xcit_small_24_p16_224_dist,73.260,26.740,91.460,8.540,47.67,224,1.000,bicubic,-10.610,-5.272,-17 +deit_base_distilled_patch16_224,73.240,26.760,91.000,9.000,87.34,224,0.900,bicubic,-10.148,-5.488,+11 +resnetrs152,73.200,26.800,91.260,8.740,86.62,320,1.000,bicubic,-10.514,-5.354,-4 +xcit_medium_24_p8_224,73.150,26.850,90.280,9.720,84.32,224,1.000,bicubic,-10.588,-6.114,-7 +vit_base_patch32_384,73.130,26.870,91.240,8.760,88.30,384,1.000,bicubic,-10.222,-5.596,+10 +jx_nest_base,73.120,26.880,91.060,8.940,67.72,224,0.875,bicubic,-10.434,-5.304,-1 +swinv2_small_window8_256,73.110,26.890,90.930,9.070,49.73,256,0.900,bicubic,-10.744,-5.712,-22 +cs3se_edgenet_x,73.100,26.900,91.260,8.740,50.72,320,1.000,bicubic,-10.448,-5.406,-2 +deit3_small_patch16_384,73.090,26.910,91.240,8.760,22.21,384,1.000,bicubic,-10.338,-5.436,0 +xcit_small_24_p8_224,73.080,26.920,91.140,8.860,47.63,224,1.000,bicubic,-10.760,-5.496,-22 +cait_s24_224,73.070,26.930,91.120,8.880,46.92,224,1.000,bicubic,-10.388,-5.442,-3 +crossvit_15_dagger_408,72.950,27.050,91.090,8.910,28.50,408,1.000,bicubic,-10.888,-5.690,-23 +resnetv2_152x2_bit_teacher_384,72.900,27.100,91.550,8.450,236.34,384,1.000,bicubic,-10.944,-5.566,-27 +regnetv_040,72.880,27.120,91.110,8.890,20.64,288,1.000,bicubic,-10.318,-5.554,+8 +dm_nfnet_f0,72.880,27.120,91.080,8.920,71.49,256,0.900,bicubic,-10.504,-5.494,-1 +tf_efficientnet_b4_ap,72.880,27.120,90.980,9.020,19.34,380,0.922,bicubic,-10.368,-5.412,+3 +convnext_tiny_384_in22ft1k,72.850,27.150,91.560,8.440,28.59,384,1.000,bicubic,-11.226,-5.598,-46 +swinv2_cr_small_ns_224,72.800,27.200,90.800,9.200,49.70,224,0.900,bicubic,-10.686,-5.684,-11 +xception65p,72.790,27.210,90.910,9.090,39.82,299,0.940,bicubic,-10.340,-5.570,+10 +regnety_032,72.760,27.240,90.960,9.040,19.44,288,1.000,bicubic,-9.964,-5.462,+30 +regnety_040,72.720,27.280,90.730,9.270,20.65,288,1.000,bicubic,-10.316,-5.780,+14 +swin_s3_small_224,72.690,27.310,90.560,9.440,49.74,224,0.900,bicubic,-11.084,-5.892,-27 +resnext101_64x4d,72.620,27.380,90.840,9.160,83.46,288,1.000,bicubic,-10.524,-5.534,+2 +xcit_small_12_p8_224,72.620,27.380,90.670,9.330,26.21,224,1.000,bicubic,-10.720,-5.810,-6 +nfnet_l0,72.610,27.390,91.000,9.000,35.07,288,1.000,bicubic,-10.142,-5.518,+24 +pnasnet5large,72.610,27.390,90.510,9.490,86.06,331,0.911,bicubic,-10.172,-5.532,+21 +xception65,72.600,27.400,90.820,9.180,39.92,299,0.940,bicubic,-10.574,-5.772,-4 +resnest101e,72.580,27.420,90.820,9.180,48.28,256,0.875,bilinear,-10.308,-5.500,+13 +twins_pcpvt_large,72.570,27.430,90.700,9.300,60.99,224,0.900,bicubic,-10.566,-5.904,-1 +swsl_resnext50_32x4d,72.560,27.440,90.850,9.150,25.03,224,0.875,bilinear,-9.616,-5.382,+66 +gc_efficientnetv2_rw_t,72.550,27.450,90.830,9.170,13.68,288,1.000,bicubic,-9.916,-5.468,+38 +twins_svt_base,72.550,27.450,90.450,9.550,56.07,224,0.900,bicubic,-10.588,-5.970,-6 +tresnet_xl_448,72.550,27.450,90.310,9.690,78.44,448,0.875,bilinear,-10.498,-5.860,+1 +deit_base_patch16_384,72.540,27.460,90.270,9.730,86.86,384,1.000,bicubic,-10.566,-6.100,-3 +resnetv2_50x3_bitm,72.520,27.480,91.760,8.240,217.32,448,1.000,bilinear,-11.492,-5.366,-57 +xcit_small_12_p16_224_dist,72.500,27.500,91.110,8.890,26.25,224,1.000,bicubic,-10.846,-5.308,-19 +xcit_tiny_24_p8_224_dist,72.430,27.570,90.920,9.080,12.11,224,1.000,bicubic,-10.130,-5.248,+27 +resnet101d,72.420,27.580,90.650,9.350,44.57,320,1.000,bicubic,-10.602,-5.796,-1 +sequencer2d_m,72.410,27.590,90.710,9.290,38.31,224,0.875,bicubic,-10.398,-5.558,+7 +cs3sedarknet_x,72.380,27.620,91.020,8.980,35.40,288,1.000,bicubic,-10.274,-5.326,+14 +jx_nest_small,72.360,27.640,90.690,9.310,38.35,224,0.875,bicubic,-10.760,-5.640,-11 +convnext_small,72.330,27.670,90.850,9.150,50.22,224,0.875,bicubic,-10.820,-5.580,-18 +regnetz_c16,72.310,27.690,90.820,9.180,13.46,320,0.940,bicubic,-10.210,-5.540,+22 tf_efficientnet_b4,72.290,27.710,90.590,9.410,19.34,380,0.922,bicubic,-10.734,-5.710,-8 -tf_efficientnet_b2_ns,72.280,27.720,91.090,8.910,9.11,260,0.890,bicubic,-10.100,-5.158,+19 -resnetv2_50x1_bit_distilled,72.260,27.740,91.010,8.990,25.55,224,0.875,bicubic,-10.562,-5.518,-5 -tresnet_m,72.260,27.740,90.230,9.770,31.39,224,0.875,bilinear,-10.810,-5.890,-14 -crossvit_18_240,72.250,27.750,90.270,9.730,43.27,240,0.875,bicubic,-10.148,-5.788,+14 -efficientnetv2_rw_t,72.250,27.750,90.420,9.580,13.65,288,1.000,bicubic,-10.094,-5.776,+18 -nasnetalarge,72.230,27.770,90.460,9.540,88.75,331,0.911,bicubic,-10.396,-5.586,0 -regnetz_c16_evos,72.230,27.770,91.220,8.780,13.49,320,0.950,bicubic,-10.402,-5.256,-2 -cait_xxs36_384,72.190,27.810,90.840,9.160,17.37,384,1.000,bicubic,-10.004,-5.304,+26 -twins_pcpvt_base,72.190,27.810,90.510,9.490,43.83,224,0.900,bicubic,-10.518,-5.840,-7 -crossvit_18_dagger_240,72.140,27.860,90.070,9.930,44.27,240,0.875,bicubic,-10.380,-6.000,+3 -xcit_tiny_24_p16_384_dist,72.080,27.920,90.580,9.420,12.12,384,1.000,bicubic,-10.492,-5.708,-1 -resnet152,72.060,27.940,90.320,9.680,60.19,224,0.950,bicubic,-10.760,-5.810,-14 -eca_nfnet_l0,71.840,28.160,91.110,8.890,24.14,288,1.000,bicubic,-10.736,-5.380,-4 -swin_small_patch4_window7_224,71.740,28.260,90.240,9.760,49.61,224,0.900,bicubic,-11.476,-6.084,-35 -pit_b_224,71.720,28.280,89.250,10.750,73.76,224,0.900,bicubic,-10.726,-6.460,+2 -swsl_resnet50,71.700,28.300,90.480,9.520,25.56,224,0.875,bilinear,-9.474,-5.498,+70 -xcit_large_24_p16_224,71.700,28.300,89.170,10.830,189.10,224,1.000,bicubic,-11.194,-6.712,-23 -resnet61q,71.680,28.320,90.280,9.720,36.85,288,1.000,bicubic,-10.846,-5.854,-6 -tresnet_xl,71.660,28.340,89.630,10.370,78.44,224,0.875,bilinear,-10.398,-6.306,+23 -convit_base,71.610,28.390,90.160,9.840,86.54,224,0.875,bicubic,-10.676,-5.778,+9 -tresnet_l_448,71.590,28.410,90.060,9.940,55.99,448,0.875,bilinear,-10.678,-5.922,+9 -xcit_tiny_12_p8_384_dist,71.580,28.420,90.710,9.290,6.71,384,1.000,bicubic,-10.814,-5.510,-3 -poolformer_m48,71.550,28.450,89.760,10.240,73.47,224,0.950,bicubic,-10.912,-6.198,-7 -crossvit_15_dagger_240,71.510,28.490,89.860,10.140,28.21,240,0.875,bicubic,-10.820,-6.098,+1 -ssl_resnext101_32x8d,71.510,28.490,90.470,9.530,88.79,224,0.875,bilinear,-10.098,-5.572,+37 -fbnetv3_g,71.490,28.510,90.370,9.630,16.62,288,0.950,bilinear,-10.556,-5.694,+17 -efficientnet_b3,71.480,28.520,90.060,9.940,12.23,320,1.000,bicubic,-10.760,-6.054,+4 -ecaresnet101d,71.470,28.530,90.330,9.670,44.57,224,0.875,bicubic,-10.702,-5.716,+8 -ssl_resnext101_32x16d,71.430,28.570,90.520,9.480,194.03,224,0.875,bilinear,-10.424,-5.576,+25 -resnet51q,71.420,28.580,90.180,9.820,35.70,288,1.000,bilinear,-10.942,-6.000,-9 -pit_s_distilled_224,71.370,28.630,89.780,10.220,24.04,224,0.900,bicubic,-10.624,-6.018,+15 -xcit_tiny_24_p8_224,71.330,28.670,90.240,9.760,12.11,224,1.000,bicubic,-10.562,-5.736,+20 -mixer_b16_224_miil,71.310,28.690,89.650,10.350,59.88,224,0.875,bilinear,-10.998,-6.068,-7 -resnetv2_152x2_bit_teacher,71.290,28.710,90.430,9.570,236.34,224,0.875,bicubic,-11.582,-6.140,-38 -convnext_tiny_hnf,71.280,28.720,89.400,10.600,28.59,224,0.950,bicubic,-10.942,-6.466,-3 -resnetv2_101,71.260,28.740,89.920,10.080,44.54,224,0.950,bicubic,-10.782,-5.944,+7 -ecaresnet50t,71.260,28.740,90.420,9.580,25.57,320,0.950,bicubic,-11.088,-5.718,-14 -convmixer_1536_20,71.230,28.770,89.440,10.560,51.63,224,0.960,bicubic,-10.136,-6.174,+39 -xcit_small_12_p16_224,71.210,28.790,89.750,10.250,26.25,224,1.000,bicubic,-10.766,-6.068,+9 -deit_base_patch16_224,71.190,28.810,89.190,10.810,86.57,224,0.900,bicubic,-10.806,-6.542,+5 -crossvit_base_240,71.180,28.820,89.830,10.170,105.03,240,0.875,bicubic,-11.036,-6.004,-8 -swin_s3_tiny_224,71.130,28.870,89.720,10.280,28.33,224,0.900,bicubic,-10.996,-6.230,-5 -resnetv2_50d_evos,71.120,28.880,90.010,9.990,25.59,288,0.950,bicubic,-10.860,-5.900,+4 -halo2botnet50ts_256,71.100,28.900,89.630,10.370,22.64,256,0.950,bicubic,-10.960,-6.012,-3 -xcit_tiny_12_p8_224_dist,71.030,28.970,89.880,10.120,6.71,224,1.000,bicubic,-10.178,-5.720,+40 -xcit_medium_24_p16_224,71.020,28.980,89.520,10.480,84.40,224,1.000,bicubic,-11.618,-6.454,-42 -visformer_small,71.010,28.990,89.450,10.550,40.22,224,0.900,bicubic,-11.096,-6.424,-8 -lamhalobotnet50ts_256,71.000,29.000,89.070,10.930,22.57,256,0.950,bicubic,-10.546,-6.432,+15 -xcit_small_24_p16_224,71.000,29.000,89.700,10.300,47.67,224,1.000,bicubic,-11.580,-6.306,-41 -resnetv2_50d_gn,70.990,29.010,89.770,10.230,25.57,288,0.950,bicubic,-10.828,-6.152,+6 -resnetv2_101x1_bitm,70.990,29.010,91.090,8.910,44.54,448,1.000,bilinear,-11.346,-5.426,-27 -tresnet_m_448,70.990,29.010,88.680,11.320,31.39,448,0.875,bilinear,-10.714,-6.892,+5 -wide_resnet50_2,70.940,29.060,89.230,10.770,68.88,224,0.875,bicubic,-10.512,-6.300,+17 -tnt_s_patch16_224,70.930,29.070,89.590,10.410,23.76,224,0.900,bicubic,-10.590,-6.154,+10 -convnext_tiny,70.930,29.070,89.750,10.250,28.59,224,0.875,bicubic,-11.134,-6.102,-14 -resnest50d_4s2x40d,70.930,29.070,89.710,10.290,30.42,224,0.875,bicubic,-10.180,-5.854,+35 -tf_efficientnet_b3_ap,70.920,29.080,89.430,10.570,12.23,300,0.904,bicubic,-10.906,-6.192,-2 -vit_small_patch16_224,70.910,29.090,90.150,9.850,22.05,224,0.900,bicubic,-10.486,-5.982,+16 -resnet101,70.870,29.130,89.520,10.480,44.55,224,0.950,bicubic,-11.062,-6.250,-8 -vit_large_patch32_384,70.870,29.130,90.570,9.430,306.63,384,1.000,bicubic,-10.636,-5.524,+8 -jx_nest_tiny,70.860,29.140,89.940,10.060,17.06,224,0.875,bicubic,-10.560,-5.678,+11 -resnetrs101,70.860,29.140,89.830,10.170,63.62,288,0.940,bicubic,-11.428,-6.180,-34 -tf_efficientnet_b1_ns,70.860,29.140,90.120,9.880,7.79,240,0.882,bicubic,-10.528,-5.616,+12 -rexnet_200,70.840,29.160,89.710,10.290,16.37,224,0.875,bicubic,-10.790,-5.958,-3 -tresnet_l,70.840,29.160,89.620,10.380,55.99,224,0.875,bilinear,-10.652,-6.004,+4 -tf_efficientnetv2_b3,70.830,29.170,89.510,10.490,14.36,300,0.904,bicubic,-11.136,-6.270,-17 -poolformer_m36,70.800,29.200,89.510,10.490,56.17,224,0.950,bicubic,-11.312,-6.180,-29 -coat_lite_small,70.790,29.210,89.570,10.430,19.84,224,0.900,bicubic,-11.514,-6.278,-41 -levit_384,70.750,29.250,89.300,10.700,39.13,224,0.900,bicubic,-11.838,-6.722,-62 -tf_efficientnet_b3,70.640,29.360,89.440,10.560,12.23,300,0.904,bicubic,-10.996,-6.278,-10 -gluon_senet154,70.620,29.380,88.920,11.080,115.09,224,0.875,bicubic,-10.612,-6.428,+12 -crossvit_small_240,70.610,29.390,89.360,10.640,26.86,240,0.875,bicubic,-10.408,-6.096,+24 -cait_xxs24_384,70.600,29.400,89.720,10.280,12.03,384,1.000,bicubic,-10.366,-5.926,+27 -convit_small,70.590,29.410,89.580,10.420,27.78,224,0.875,bicubic,-10.830,-6.160,-3 -twins_pcpvt_small,70.560,29.440,89.080,10.920,24.11,224,0.900,bicubic,-10.530,-6.560,+18 -ssl_resnext101_32x4d,70.530,29.470,89.780,10.220,44.18,224,0.875,bilinear,-10.394,-5.946,+27 -deit_small_distilled_patch16_224,70.530,29.470,89.470,10.530,22.44,224,0.900,bicubic,-10.678,-5.904,+8 -legacy_senet154,70.520,29.480,89.000,11.000,115.09,224,0.875,bilinear,-10.790,-6.496,+2 -vit_small_r26_s32_224,70.510,29.490,90.110,9.890,36.43,224,0.900,bicubic,-11.346,-5.910,-26 -halonet50ts,70.490,29.510,89.330,10.670,22.73,256,0.940,bicubic,-11.170,-6.282,-21 -regnetz_b16,70.450,29.550,89.530,10.470,9.72,288,0.940,bicubic,-10.264,-5.948,+32 -gluon_seresnext101_64x4d,70.440,29.560,89.350,10.650,88.23,224,0.875,bicubic,-10.438,-5.948,+23 -twins_svt_small,70.440,29.560,89.350,10.650,24.06,224,0.900,bicubic,-11.240,-6.320,-26 -crossvit_15_240,70.440,29.560,89.540,10.460,27.53,240,0.875,bicubic,-11.102,-6.150,-18 -tf_efficientnet_lite4,70.430,29.570,89.110,10.890,13.01,380,0.920,bilinear,-11.106,-6.558,-20 -resnest50d,70.420,29.580,88.760,11.240,27.48,224,0.875,bilinear,-10.562,-6.620,+13 -seresnext50_32x4d,70.410,29.590,89.110,10.890,27.56,224,0.875,bicubic,-10.848,-6.520,-5 -resnest50d_1s4x24d,70.390,29.610,89.230,10.770,25.68,224,0.875,bicubic,-10.600,-6.094,+10 -gernet_l,70.360,29.640,88.980,11.020,31.08,256,0.875,bilinear,-10.984,-6.552,-11 -gluon_resnet152_v1s,70.300,29.700,88.850,11.150,60.32,224,0.875,bicubic,-10.716,-6.562,+7 -repvgg_b3,70.250,29.750,88.740,11.260,123.09,224,0.875,bilinear,-10.246,-6.524,+29 -xception41p,70.210,29.790,89.100,10.900,26.91,299,0.940,bicubic,-11.750,-6.694,-43 -coat_mini,70.210,29.790,89.450,10.550,10.34,224,0.900,bicubic,-11.056,-5.944,-11 -sebotnet33ts_256,70.150,29.850,88.800,11.200,13.70,256,0.940,bicubic,-11.006,-6.370,-7 -inception_resnet_v2,70.120,29.880,88.690,11.310,55.84,299,0.897,bicubic,-10.340,-6.618,+29 -ecaresnet101d_pruned,70.110,29.890,89.590,10.410,24.88,224,0.875,bicubic,-10.704,-6.040,+12 -efficientnet_el,70.110,29.890,89.290,10.710,10.59,300,0.904,bicubic,-11.200,-6.240,-18 -haloregnetz_b,70.100,29.900,88.860,11.140,11.68,224,0.940,bicubic,-10.950,-6.336,-4 -resmlp_36_distilled_224,70.100,29.900,89.100,10.900,44.69,224,0.875,bicubic,-11.054,-6.388,-11 -gluon_seresnext101_32x4d,70.040,29.960,88.910,11.090,48.96,224,0.875,bicubic,-10.866,-6.384,+5 -poolformer_s36,70.030,29.970,89.200,10.800,30.86,224,0.900,bicubic,-11.388,-6.250,-28 -sehalonet33ts,70.020,29.980,88.700,11.300,13.69,256,0.940,bicubic,-10.944,-6.572,-1 -regnety_320,69.990,30.010,88.880,11.120,145.05,224,0.875,bicubic,-10.820,-6.364,+6 -gluon_resnet152_v1d,69.970,30.030,88.490,11.510,60.21,224,0.875,bicubic,-10.506,-6.714,+18 -levit_256,69.950,30.050,89.240,10.760,18.89,224,0.900,bicubic,-11.556,-6.252,-38 -pit_s_224,69.890,30.110,88.930,11.070,23.46,224,0.900,bicubic,-11.210,-6.400,-14 -ecaresnet50d,69.840,30.160,89.390,10.610,25.58,224,0.875,bicubic,-10.760,-5.930,+10 -ssl_resnext50_32x4d,69.720,30.280,89.440,10.560,25.03,224,0.875,bilinear,-10.596,-5.970,+26 -gluon_resnext101_64x4d,69.700,30.300,88.270,11.730,83.46,224,0.875,bicubic,-10.904,-6.722,+7 -xcit_tiny_24_p16_224_dist,69.700,30.300,88.720,11.280,12.12,224,1.000,bicubic,-10.746,-6.496,+16 -xcit_tiny_12_p16_384_dist,69.690,30.310,89.020,10.980,6.72,384,1.000,bicubic,-11.254,-6.392,-10 -lambda_resnet50ts,69.690,30.310,88.830,11.170,21.54,256,0.950,bicubic,-11.456,-6.272,-22 -resmlp_24_distilled_224,69.680,30.320,89.050,10.950,30.02,224,0.875,bicubic,-11.084,-6.174,-3 -resnext50_32x4d,69.670,30.330,88.650,11.350,25.03,224,0.950,bicubic,-11.438,-6.676,-23 -efficientnet_b3_pruned,69.580,30.420,88.980,11.020,9.86,300,0.904,bicubic,-11.278,-6.264,-8 -gernet_m,69.550,30.450,88.690,11.310,21.14,224,0.875,bilinear,-11.194,-6.494,-5 -nf_resnet50,69.540,30.460,88.730,11.270,25.56,288,0.940,bicubic,-11.114,-6.604,-3 -gcresnext50ts,69.530,30.470,88.840,11.160,15.67,256,0.900,bicubic,-11.048,-6.330,0 -repvgg_b3g4,69.520,30.480,88.450,11.550,83.83,224,0.875,bilinear,-10.692,-6.656,+26 -efficientnet_el_pruned,69.510,30.490,88.930,11.070,10.59,300,0.904,bicubic,-10.792,-6.098,+18 -ens_adv_inception_resnet_v2,69.510,30.490,88.510,11.490,55.84,299,0.897,bicubic,-10.468,-6.428,+37 -efficientnet_b2,69.500,30.500,88.670,11.330,9.11,288,1.000,bicubic,-11.114,-6.646,-7 -gcresnet50t,69.500,30.500,89.060,10.940,25.90,256,0.900,bicubic,-11.442,-6.394,-20 -rexnet_150,69.470,30.530,88.980,11.020,9.73,224,0.875,bicubic,-10.840,-6.186,+12 -swin_tiny_patch4_window7_224,69.450,30.550,89.020,10.980,28.29,224,0.900,bicubic,-11.924,-6.524,-49 -regnetx_320,69.440,30.560,88.280,11.720,107.81,224,0.875,bicubic,-10.800,-6.742,+17 -vit_base_patch32_224,69.410,30.590,89.440,10.560,88.22,224,0.900,bicubic,-11.312,-6.126,-15 -convmixer_768_32,69.400,30.600,88.870,11.130,21.11,224,0.960,bicubic,-10.764,-6.202,+20 -inception_v4,69.360,30.640,88.780,11.220,42.68,299,0.875,bicubic,-10.802,-6.186,+20 -legacy_seresnext101_32x4d,69.360,30.640,88.060,11.940,48.96,224,0.875,bilinear,-10.864,-6.950,+14 -ecaresnetlight,69.340,30.660,89.230,10.770,30.16,224,0.875,bicubic,-11.112,-6.020,-6 -resnet50d,69.340,30.660,88.230,11.770,25.58,224,0.875,bicubic,-11.182,-6.932,-13 -xception71,69.320,30.680,88.270,11.730,42.34,299,0.903,bicubic,-10.556,-6.652,+30 -vit_small_patch32_384,69.280,30.720,89.820,10.180,22.92,384,1.000,bicubic,-11.204,-5.780,-13 -gluon_xception65,69.160,30.840,88.080,11.920,39.92,299,0.903,bicubic,-10.556,-6.780,+37 -gluon_resnet152_v1c,69.150,30.850,87.860,12.140,60.21,224,0.875,bicubic,-10.758,-6.988,+25 -mixnet_xl,69.120,30.880,88.310,11.690,11.90,224,0.875,bicubic,-11.354,-6.624,-14 -seresnet33ts,69.100,30.900,88.490,11.510,19.78,256,0.900,bicubic,-11.250,-6.616,-7 -tf_efficientnetv2_b2,69.090,30.910,88.220,11.780,10.10,260,0.890,bicubic,-11.116,-6.822,+7 -resnetv2_50,69.070,30.930,88.440,11.560,25.55,224,0.950,bicubic,-11.350,-6.576,-13 -gluon_resnet101_v1d,69.010,30.990,88.100,11.900,44.57,224,0.875,bicubic,-11.410,-6.974,-13 -repvgg_b2g4,69.000,31.000,88.350,11.650,61.76,224,0.875,bilinear,-10.370,-6.338,+48 -gcresnet33ts,68.990,31.010,88.470,11.530,19.88,256,0.900,bicubic,-11.090,-6.530,+9 -gluon_resnext101_32x4d,68.950,31.050,88.360,11.640,44.18,224,0.875,bicubic,-11.394,-6.566,-12 -seresnet50,68.950,31.050,88.700,11.300,28.09,224,0.875,bicubic,-11.314,-6.372,-5 -tf_efficientnet_b2_ap,68.950,31.050,88.350,11.650,9.11,260,0.890,bicubic,-11.352,-6.866,-9 -cspdarknet53,68.920,31.080,88.600,11.400,27.64,256,0.887,bilinear,-11.142,-6.484,+7 -regnety_120,68.870,31.130,88.330,11.670,51.82,224,0.875,bicubic,-11.506,-6.286,-18 -resnet50_gn,68.850,31.150,88.420,11.580,25.56,224,0.940,bicubic,-11.204,-6.528,+6 -gluon_resnet152_v1b,68.830,31.170,87.710,12.290,60.19,224,0.875,bicubic,-10.850,-7.028,+26 -eca_resnet33ts,68.810,31.190,88.580,11.420,19.68,256,0.900,bicubic,-11.270,-6.390,0 -cspresnext50,68.790,31.210,87.940,12.060,20.57,224,0.875,bilinear,-11.260,-7.006,+4 -dpn131,68.760,31.240,87.440,12.560,79.25,224,0.875,bicubic,-11.064,-7.268,+15 -gmlp_s16_224,68.760,31.240,88.080,11.920,19.42,224,0.875,bicubic,-10.880,-6.544,+25 -poolformer_s24,68.760,31.240,88.210,11.790,21.39,224,0.900,bicubic,-11.554,-6.836,-20 -tf_efficientnet_b2,68.740,31.260,87.980,12.020,9.11,260,0.890,bicubic,-11.340,-6.928,-3 -resnext50d_32x4d,68.730,31.270,88.300,11.700,25.05,224,0.875,bicubic,-10.940,-6.564,+20 -resnet50,68.720,31.280,87.660,12.340,25.56,224,0.950,bicubic,-11.656,-7.466,-29 -gluon_resnet101_v1s,68.710,31.290,87.910,12.090,44.67,224,0.875,bicubic,-11.588,-7.254,-20 -deit_small_patch16_224,68.700,31.300,88.210,11.790,22.05,224,0.900,bicubic,-11.160,-6.836,+4 -dpn107,68.700,31.300,88.140,11.860,86.92,224,0.875,bicubic,-11.472,-6.766,-14 -gluon_seresnext50_32x4d,68.670,31.330,88.320,11.680,27.56,224,0.875,bicubic,-11.244,-6.512,-2 -hrnet_w64,68.650,31.350,88.050,11.950,128.06,224,0.875,bilinear,-10.822,-6.602,+22 -dpn98,68.610,31.390,87.660,12.340,61.57,224,0.875,bicubic,-11.036,-6.936,+14 -xcit_tiny_12_p8_224,68.580,31.420,88.690,11.310,6.71,224,1.000,bicubic,-11.110,-6.364,+9 -regnetx_160,68.530,31.470,88.450,11.550,54.28,224,0.875,bicubic,-11.320,-6.380,-1 -rexnet_130,68.460,31.540,88.040,11.960,7.56,224,0.875,bicubic,-11.040,-6.644,+16 -cspresnet50,68.440,31.560,87.970,12.030,21.62,256,0.887,bilinear,-11.142,-6.734,+13 -tf_efficientnet_el,68.430,31.570,88.210,11.790,10.59,300,0.904,bicubic,-11.820,-6.912,-28 -xcit_tiny_24_p16_224,68.430,31.570,88.290,11.710,12.12,224,1.000,bicubic,-11.014,-6.594,+18 -ecaresnet50d_pruned,68.410,31.590,88.370,11.630,19.94,224,0.875,bicubic,-11.298,-6.510,+2 -cait_xxs36_224,68.400,31.600,88.630,11.370,17.30,224,1.000,bicubic,-11.348,-6.236,-1 -skresnext50_32x4d,68.370,31.630,87.560,12.440,27.48,224,0.875,bicubic,-11.782,-7.084,-23 -ssl_resnet50,68.360,31.640,88.530,11.470,25.56,224,0.875,bilinear,-10.866,-6.306,+30 -fbnetv3_d,68.340,31.660,88.450,11.550,10.31,256,0.950,bilinear,-11.342,-6.498,-1 -dla102x2,68.340,31.660,87.890,12.110,41.28,224,0.875,bilinear,-11.106,-6.742,+12 -efficientnet_b2_pruned,68.320,31.680,88.100,11.900,8.31,260,0.890,bicubic,-11.596,-6.754,-18 -resmlp_big_24_224,68.320,31.680,87.530,12.470,129.14,224,0.875,bicubic,-12.712,-7.490,-83 -gluon_resnext50_32x4d,68.310,31.690,87.300,12.700,25.03,224,0.875,bicubic,-11.054,-7.126,+12 -vit_base_patch16_224_sam,68.260,31.740,87.730,12.270,86.57,224,0.900,bicubic,-11.982,-7.024,-38 -ecaresnet26t,68.230,31.770,88.790,11.210,16.01,320,0.950,bicubic,-11.618,-6.296,-15 -tf_efficientnet_lite3,68.230,31.770,87.740,12.260,8.20,300,0.904,bilinear,-11.590,-7.172,-13 -ese_vovnet39b,68.200,31.800,88.260,11.740,24.57,224,0.875,bicubic,-11.112,-6.454,+10 -fbnetv3_b,68.180,31.820,87.930,12.070,8.60,256,0.950,bilinear,-10.968,-6.816,+25 -regnetx_120,68.170,31.830,87.660,12.340,46.11,224,0.875,bicubic,-11.422,-7.074,-5 -resmlp_36_224,68.060,31.940,88.190,11.810,44.69,224,0.875,bicubic,-11.708,-6.696,-16 -resnetrs50,68.030,31.970,87.710,12.290,35.69,224,0.910,bicubic,-11.856,-7.256,-25 -pit_xs_distilled_224,68.000,32.000,87.720,12.280,11.00,224,0.900,bicubic,-11.306,-6.644,+6 -dpn92,67.960,32.040,87.560,12.440,37.67,224,0.875,bicubic,-12.056,-7.264,-32 -nf_regnet_b1,67.960,32.040,88.200,11.800,10.22,288,0.900,bicubic,-11.328,-6.548,+9 -gluon_resnet50_v1d,67.950,32.050,87.130,12.870,25.58,224,0.875,bicubic,-11.126,-7.342,+22 -resnetv2_50x1_bitm,67.920,32.080,89.290,10.710,25.55,448,1.000,bilinear,-12.422,-6.390,-59 -levit_192,67.900,32.100,87.890,12.110,10.95,224,0.900,bicubic,-11.932,-6.896,-26 -tf_efficientnetv2_b1,67.890,32.110,87.790,12.210,8.14,240,0.882,bicubic,-11.574,-6.934,-8 -regnetx_080,67.880,32.120,86.990,13.010,39.57,224,0.875,bicubic,-11.322,-7.564,+12 -resnext101_32x8d,67.860,32.140,87.490,12.510,88.79,224,0.875,bilinear,-11.456,-7.028,-4 -legacy_seresnext50_32x4d,67.850,32.150,87.620,12.380,27.56,224,0.875,bilinear,-11.218,-6.814,+17 -efficientnet_em,67.830,32.170,88.120,11.880,6.90,240,0.882,bicubic,-11.420,-6.674,+5 -lambda_resnet26t,67.820,32.180,87.770,12.230,10.96,256,0.940,bicubic,-11.278,-6.818,+12 -resmlp_24_224,67.800,32.200,87.620,12.380,30.02,224,0.875,bicubic,-11.582,-6.926,-11 -hrnet_w48,67.770,32.230,87.410,12.590,77.47,224,0.875,bilinear,-11.532,-7.102,-3 -hrnet_w44,67.740,32.260,87.560,12.440,67.06,224,0.875,bilinear,-11.160,-6.814,+20 -coat_lite_mini,67.710,32.290,87.680,12.320,11.01,224,0.900,bicubic,-11.386,-6.924,+9 -tf_efficientnet_b0_ns,67.700,32.300,88.070,11.930,5.29,224,0.875,bicubic,-10.958,-6.308,+27 -regnetx_064,67.680,32.320,87.530,12.470,26.21,224,0.875,bicubic,-11.386,-6.928,+10 -eca_botnext26ts_256,67.670,32.330,87.050,12.950,10.59,256,0.950,bicubic,-11.604,-7.566,-5 -xception,67.670,32.330,87.580,12.420,22.86,299,0.897,bicubic,-11.380,-6.812,+9 -dla169,67.630,32.370,87.590,12.410,53.39,224,0.875,bilinear,-11.062,-6.750,+22 -dpn68b,67.630,32.370,87.670,12.330,12.61,224,0.875,bicubic,-11.590,-6.748,-4 -halonet26t,67.630,32.370,87.240,12.760,12.48,256,0.950,bicubic,-11.486,-7.070,0 -gluon_inception_v3,67.590,32.410,87.470,12.530,23.83,299,0.875,bicubic,-11.214,-6.900,+14 -hrnet_w40,67.580,32.420,87.130,12.870,57.56,224,0.875,bilinear,-11.336,-7.344,+8 -gluon_resnet101_v1c,67.580,32.420,87.180,12.820,44.57,224,0.875,bicubic,-11.954,-7.400,-30 -legacy_seresnet152,67.530,32.470,87.400,12.600,66.82,224,0.875,bilinear,-11.122,-6.970,+18 -tf_efficientnet_b1_ap,67.520,32.480,87.760,12.240,7.79,240,0.882,bicubic,-11.760,-6.544,-15 -eca_halonext26ts,67.470,32.530,87.230,12.770,10.76,256,0.940,bicubic,-12.020,-7.368,-32 -gluon_resnet101_v1b,67.470,32.530,87.240,12.760,44.55,224,0.875,bicubic,-11.832,-7.280,-20 -efficientnet_b1,67.460,32.540,87.510,12.490,7.79,256,1.000,bicubic,-11.336,-6.832,+8 -res2net50_26w_8s,67.460,32.540,87.280,12.720,48.40,224,0.875,bilinear,-11.520,-7.014,-1 -resnetblur50,67.460,32.540,87.440,12.560,25.56,224,0.875,bicubic,-11.844,-7.194,-24 -tf_efficientnet_cc_b1_8e,67.450,32.550,87.320,12.680,39.72,240,0.882,bicubic,-11.856,-7.052,-27 -res2net101_26w_4s,67.450,32.550,87.010,12.990,45.21,224,0.875,bilinear,-11.746,-7.426,-13 -resnet33ts,67.370,32.630,87.580,12.420,19.68,256,0.900,bicubic,-11.840,-6.992,-17 -cait_xxs24_224,67.340,32.660,87.510,12.490,11.96,224,1.000,bicubic,-11.044,-6.800,+23 -regnetx_032,67.290,32.710,86.990,13.010,15.30,224,0.875,bicubic,-10.882,-7.098,+33 -coat_tiny,67.260,32.740,87.290,12.710,5.50,224,0.900,bicubic,-11.170,-6.750,+18 -xception41,67.250,32.750,87.210,12.790,26.97,299,0.903,bicubic,-11.260,-7.068,+9 -resnest26d,67.190,32.810,87.170,12.830,17.07,224,0.875,bilinear,-11.286,-7.122,+11 -legacy_seresnet101,67.160,32.840,87.050,12.950,49.33,224,0.875,bilinear,-11.228,-7.214,+17 -repvgg_b2,67.160,32.840,87.330,12.670,89.02,224,0.875,bilinear,-11.632,-7.088,-3 -botnet26t_256,67.130,32.870,87.530,12.470,12.49,256,0.950,bicubic,-12.122,-6.998,-29 -dla60x,67.100,32.900,87.180,12.820,17.35,224,0.875,bilinear,-11.144,-6.838,+22 -gluon_resnet50_v1s,67.070,32.930,86.860,13.140,25.68,224,0.875,bicubic,-11.642,-7.380,-4 -tv_resnet152,67.040,32.960,87.550,12.450,60.19,224,0.875,bilinear,-11.276,-6.484,+16 -dla102x,67.030,32.970,86.790,13.210,26.31,224,0.875,bilinear,-11.486,-7.436,0 -dla60_res2net,67.020,32.980,87.160,12.840,20.85,224,0.875,bilinear,-11.442,-7.046,+4 -xcit_tiny_12_p16_224_dist,67.010,32.990,87.420,12.580,6.72,224,1.000,bicubic,-11.566,-6.776,-4 -lambda_resnet26rpt_256,66.970,33.030,87.130,12.870,10.99,256,0.940,bicubic,-11.998,-7.298,-18 -mixnet_l,66.940,33.060,86.920,13.080,7.33,224,0.875,bicubic,-12.036,-7.258,-20 -res2net50_26w_6s,66.920,33.080,86.860,13.140,37.05,224,0.875,bilinear,-11.646,-7.274,-6 -pit_xs_224,66.910,33.090,87.290,12.710,10.62,224,0.900,bicubic,-11.276,-6.874,+16 -repvgg_b1,66.910,33.090,86.790,13.210,57.42,224,0.875,bilinear,-11.458,-7.306,+6 -tf_efficientnet_b1,66.890,33.110,87.010,12.990,7.79,240,0.882,bicubic,-11.938,-7.188,-19 -xcit_nano_12_p8_384_dist,66.870,33.130,87.110,12.890,3.05,384,1.000,bicubic,-10.948,-6.934,+34 -efficientnet_es,66.860,33.140,86.710,13.290,5.44,224,0.875,bicubic,-11.196,-7.226,+17 -mobilevit_s,66.860,33.140,87.080,12.920,5.58,256,0.900,bicubic,-11.452,-7.072,+5 -regnetx_040,66.840,33.160,86.730,13.270,22.12,224,0.875,bicubic,-11.642,-7.514,-9 -resnet32ts,66.830,33.170,87.260,12.740,17.96,256,0.900,bicubic,-12.182,-7.098,-31 -tf_mixnet_l,66.790,33.210,86.460,13.540,7.33,224,0.875,bicubic,-11.984,-7.536,-21 -hrnet_w30,66.780,33.220,86.780,13.220,37.71,224,0.875,bilinear,-11.418,-7.444,+6 -hrnet_w32,66.750,33.250,87.310,12.690,41.23,224,0.875,bilinear,-11.698,-6.884,-10 -selecsls60b,66.730,33.270,86.520,13.480,32.77,224,0.875,bicubic,-11.682,-7.654,-7 -wide_resnet101_2,66.710,33.290,87.030,12.970,126.89,224,0.875,bilinear,-12.144,-7.260,-30 -tf_efficientnetv2_b0,66.690,33.310,86.710,13.290,7.14,224,0.875,bicubic,-11.670,-7.310,-5 -adv_inception_v3,66.660,33.340,86.540,13.460,23.83,299,0.875,bicubic,-10.922,-7.196,+31 -dla60_res2next,66.640,33.360,87.030,12.970,17.03,224,0.875,bilinear,-11.800,-7.120,-14 -vit_tiny_patch16_384,66.580,33.420,87.270,12.730,5.79,384,1.000,bicubic,-11.854,-7.272,-14 -levit_128,66.570,33.430,86.750,13.250,9.21,224,0.900,bicubic,-11.922,-7.256,-21 -gluon_resnet50_v1c,66.550,33.450,86.180,13.820,25.58,224,0.875,bicubic,-11.462,-7.810,+6 -dla102,66.530,33.470,86.910,13.090,33.27,224,0.875,bilinear,-11.500,-7.038,+4 -gmixer_24_224,66.430,33.570,86.160,13.840,24.72,224,0.875,bicubic,-11.606,-7.510,+2 -tf_inception_v3,66.410,33.590,86.660,13.340,23.83,299,0.875,bicubic,-11.446,-6.980,+13 -bat_resnext26ts,66.390,33.610,86.830,13.170,10.73,256,0.900,bicubic,-11.860,-7.268,-10 -hardcorenas_f,66.380,33.620,86.200,13.800,8.20,224,0.875,bilinear,-11.718,-7.602,-3 -coat_lite_tiny,66.300,33.700,86.980,13.020,5.72,224,0.900,bicubic,-11.214,-6.936,+24 -efficientnet_b0,66.300,33.700,85.980,14.020,5.29,224,0.875,bicubic,-11.390,-7.550,+14 -legacy_seresnet50,66.260,33.740,86.340,13.660,28.09,224,0.875,bilinear,-11.370,-7.410,+15 -selecsls60,66.200,33.800,86.330,13.670,30.67,224,0.875,bicubic,-11.776,-7.416,-1 -tf_efficientnet_em,66.180,33.820,86.360,13.640,6.90,240,0.882,bicubic,-11.952,-7.684,-9 -tv_resnext50_32x4d,66.170,33.830,86.040,13.960,25.03,224,0.875,bilinear,-11.446,-7.660,+13 -tf_efficientnet_cc_b0_8e,66.160,33.840,86.240,13.760,24.01,224,0.875,bicubic,-11.746,-7.416,0 -res2net50_26w_4s,66.140,33.860,86.590,13.410,25.70,224,0.875,bilinear,-11.820,-7.262,-4 -resmlp_12_distilled_224,66.140,33.860,86.620,13.380,15.35,224,0.875,bicubic,-11.802,-6.938,-4 -inception_v3,66.130,33.870,86.320,13.680,23.83,299,0.875,bicubic,-11.308,-7.154,+18 -efficientnet_b1_pruned,66.090,33.910,86.570,13.430,6.33,240,0.882,bicubic,-12.150,-7.264,-20 -rexnet_100,66.080,33.920,86.500,13.500,4.80,224,0.875,bicubic,-11.778,-7.370,-3 -regnety_016,66.080,33.920,86.370,13.630,11.20,224,0.875,bicubic,-11.780,-7.352,-3 -gluon_resnet50_v1b,66.070,33.930,86.260,13.740,25.56,224,0.875,bicubic,-11.510,-7.462,+9 -res2net50_14w_8s,66.010,33.990,86.250,13.750,25.06,224,0.875,bilinear,-12.134,-7.598,-20 -tinynet_a,66.010,33.990,85.790,14.210,6.19,192,0.875,bicubic,-11.640,-7.746,+1 -gcresnext26ts,65.950,34.050,85.920,14.080,10.48,256,0.900,bicubic,-11.870,-7.910,-4 -seresnext26t_32x4d,65.880,34.120,85.670,14.330,16.81,224,0.875,bicubic,-12.096,-8.160,-16 -res2next50,65.860,34.140,85.840,14.160,24.67,224,0.875,bilinear,-12.392,-8.046,-31 -densenet161,65.850,34.150,86.450,13.550,28.68,224,0.875,bicubic,-11.504,-7.186,+11 -hardcorenas_e,65.840,34.160,85.980,14.020,8.07,224,0.875,bilinear,-11.954,-7.716,-6 -repvgg_b1g4,65.840,34.160,86.120,13.880,39.97,224,0.875,bilinear,-11.746,-7.710,-1 -resnet34d,65.790,34.210,86.720,13.280,21.82,224,0.875,bicubic,-11.324,-6.660,+16 -eca_resnext26ts,65.780,34.220,85.840,14.160,10.30,256,0.900,bicubic,-11.674,-7.726,+3 -xcit_tiny_12_p16_224,65.770,34.230,86.220,13.780,6.72,224,1.000,bicubic,-11.356,-7.496,+13 -mobilenetv3_large_100_miil,65.760,34.240,85.200,14.800,5.48,224,0.875,bilinear,-12.156,-7.706,-20 -skresnet34,65.740,34.260,85.970,14.030,22.28,224,0.875,bicubic,-11.164,-7.350,+22 -tv_resnet101,65.690,34.310,85.980,14.020,44.55,224,0.875,bilinear,-11.688,-7.562,+2 -seresnext26ts,65.650,34.350,86.160,13.840,10.39,256,0.900,bicubic,-12.202,-7.630,-17 -hardcorenas_d,65.630,34.370,85.460,14.540,7.50,224,0.875,bilinear,-11.800,-8.022,-1 -selecsls42b,65.620,34.380,85.810,14.190,32.46,224,0.875,bicubic,-11.554,-7.582,+6 -poolformer_s12,65.590,34.410,86.130,13.870,11.92,224,0.900,bicubic,-11.646,-7.374,+4 -tf_efficientnet_b0_ap,65.490,34.510,85.590,14.410,5.29,224,0.875,bicubic,-11.604,-7.666,+8 -seresnext26d_32x4d,65.420,34.580,85.970,14.030,16.81,224,0.875,bicubic,-12.184,-7.638,-14 -convmixer_1024_20_ks9_p14,65.410,34.590,85.590,14.410,24.38,224,0.960,bicubic,-11.532,-7.766,+11 -resnet26t,65.390,34.610,86.110,13.890,16.01,256,0.940,bicubic,-12.472,-7.734,-28 -res2net50_48w_2s,65.380,34.620,85.960,14.040,25.29,224,0.875,bilinear,-12.140,-7.592,-13 -tf_efficientnet_lite2,65.380,34.620,86.000,14.000,6.09,260,0.890,bicubic,-12.088,-7.756,-12 -densenet201,65.290,34.710,85.680,14.320,20.01,224,0.875,bicubic,-12.000,-7.798,-5 -densenetblur121d,65.290,34.710,85.700,14.300,8.00,224,0.875,bicubic,-11.294,-7.492,+19 -dla60,65.200,34.800,85.760,14.240,22.04,224,0.875,bilinear,-11.830,-7.560,+1 -crossvit_9_dagger_240,65.200,34.800,86.600,13.400,8.78,240,0.875,bicubic,-11.782,-7.010,+3 -ese_vovnet19b_dw,65.190,34.810,85.460,14.540,6.54,224,0.875,bicubic,-11.612,-7.812,+8 -tf_efficientnet_cc_b0_4e,65.150,34.850,85.140,14.860,13.31,224,0.875,bicubic,-12.152,-8.194,-12 -gernet_s,65.130,34.870,85.520,14.480,8.17,224,0.875,bilinear,-11.778,-7.612,+3 -legacy_seresnext26_32x4d,65.060,34.940,85.640,14.360,16.79,224,0.875,bicubic,-12.046,-7.678,-6 -mobilenetv2_120d,65.010,34.990,85.950,14.050,5.83,224,0.875,bicubic,-12.284,-7.546,-14 -hrnet_w18,64.930,35.070,85.740,14.260,21.30,224,0.875,bilinear,-11.824,-7.700,+5 -hardcorenas_c,64.850,35.150,85.240,14.760,5.52,224,0.875,bilinear,-12.200,-7.918,-7 -densenet169,64.760,35.240,85.240,14.760,14.15,224,0.875,bicubic,-11.138,-7.790,+22 -mixnet_m,64.700,35.300,85.460,14.540,5.01,224,0.875,bicubic,-12.564,-7.964,-16 -resnet26d,64.680,35.320,85.110,14.890,16.01,224,0.875,bicubic,-12.024,-8.040,+2 -levit_128s,64.590,35.410,84.750,15.250,7.78,224,0.900,bicubic,-11.930,-8.122,+9 -resnext26ts,64.590,35.410,85.110,14.890,10.30,256,0.900,bicubic,-12.190,-8.018,-2 -xcit_nano_12_p8_224_dist,64.560,35.440,85.980,14.020,3.05,224,1.000,bicubic,-11.760,-7.108,+9 -repvgg_a2,64.440,35.560,85.140,14.860,28.21,224,0.875,bilinear,-12.018,-7.870,+7 -xcit_nano_12_p16_384_dist,64.430,35.570,85.310,14.690,3.05,384,1.000,bicubic,-11.026,-7.380,+24 -hardcorenas_b,64.410,35.590,84.860,15.140,5.18,224,0.875,bilinear,-12.126,-7.894,+2 -tf_efficientnet_lite1,64.390,35.610,85.480,14.520,5.42,240,0.882,bicubic,-12.250,-7.740,-3 -regnetx_016,64.370,35.630,85.460,14.540,9.19,224,0.875,bicubic,-12.580,-7.962,-15 -resmlp_12_224,64.350,35.650,85.590,14.410,15.35,224,0.875,bicubic,-12.306,-7.590,-6 -tf_efficientnet_b0,64.300,35.700,85.280,14.720,5.29,224,0.875,bicubic,-12.544,-7.948,-12 -tf_mixnet_m,64.270,35.730,85.090,14.910,5.01,224,0.875,bicubic,-12.672,-8.064,-16 -dpn68,64.240,35.760,85.180,14.820,12.61,224,0.875,bicubic,-12.066,-7.794,+2 -tf_efficientnet_es,64.230,35.770,84.740,15.260,5.44,224,0.875,bicubic,-12.366,-8.464,-7 -regnety_008,64.150,35.850,85.280,14.720,6.26,224,0.875,bicubic,-12.160,-7.790,-1 -vit_small_patch32_224,64.060,35.940,85.560,14.440,22.88,224,0.900,bicubic,-11.926,-7.710,+2 -mobilenetv2_140,64.050,35.950,85.030,14.970,6.11,224,0.875,bicubic,-12.472,-7.966,-7 -densenet121,63.740,36.260,84.600,15.400,7.98,224,0.875,bicubic,-11.844,-8.052,+7 -hardcorenas_a,63.710,36.290,84.400,15.600,5.26,224,0.875,bilinear,-12.210,-8.120,+1 -resnest14d,63.610,36.390,84.260,15.740,10.61,224,0.875,bilinear,-11.894,-8.260,+7 -tf_mixnet_s,63.560,36.440,84.270,15.730,4.13,224,0.875,bicubic,-12.090,-8.358,+2 -resnet26,63.450,36.550,84.260,15.740,16.00,224,0.875,bicubic,-11.850,-8.318,+10 -mixnet_s,63.380,36.620,84.740,15.260,4.13,224,0.875,bicubic,-12.612,-8.058,-6 -mobilenetv3_large_100,63.350,36.650,84.080,15.920,5.48,224,0.875,bicubic,-12.416,-8.464,-2 -vit_tiny_r_s16_p8_384,63.340,36.660,85.270,14.730,6.36,384,1.000,bicubic,-12.614,-7.994,-7 -tv_resnet50,63.340,36.660,84.660,15.340,25.56,224,0.875,bilinear,-12.794,-8.208,-9 -efficientnet_es_pruned,63.310,36.690,84.950,15.050,5.44,224,0.875,bicubic,-11.686,-7.490,+13 -mixer_b16_224,63.280,36.720,83.320,16.680,59.88,224,0.875,bicubic,-13.332,-8.908,-22 -efficientnet_lite0,63.240,36.760,84.440,15.560,4.65,224,0.875,bicubic,-12.236,-8.072,-1 -mobilenetv3_rw,63.230,36.770,84.510,15.490,5.48,224,0.875,bicubic,-12.402,-8.198,-6 -semnasnet_100,63.160,36.840,84.530,15.470,3.89,224,0.875,bicubic,-12.290,-8.070,0 -pit_ti_distilled_224,63.140,36.860,83.960,16.040,5.10,224,0.900,bicubic,-11.392,-8.136,+17 -vit_tiny_patch16_224,63.110,36.890,84.850,15.150,5.72,224,0.900,bicubic,-12.352,-7.994,-4 -regnety_006,63.100,36.900,84.260,15.740,6.06,224,0.875,bicubic,-12.150,-8.274,-1 -tv_densenet121,62.950,37.050,84.250,15.750,7.98,224,0.875,bicubic,-11.794,-7.902,+9 -mobilevit_xs,62.940,37.060,84.830,15.170,2.32,256,0.900,bicubic,-11.704,-7.526,+10 -resnet34,62.870,37.130,84.130,15.870,21.80,224,0.875,bilinear,-12.244,-8.154,0 -legacy_seresnet34,62.840,37.160,84.220,15.780,21.96,224,0.875,bilinear,-11.968,-7.906,+5 -mobilenetv2_110d,62.820,37.180,84.490,15.510,4.52,224,0.875,bicubic,-12.218,-7.694,-1 -deit_tiny_distilled_patch16_224,62.800,37.200,83.920,16.080,5.91,224,0.900,bicubic,-11.712,-7.966,+10 -hrnet_w18_small_v2,62.790,37.210,83.990,16.010,15.60,224,0.875,bilinear,-12.328,-8.426,-5 -swsl_resnet18,62.770,37.230,84.300,15.700,11.69,224,0.875,bilinear,-10.506,-7.436,+21 -repvgg_b0,62.730,37.270,83.860,16.140,15.82,224,0.875,bilinear,-12.430,-8.558,-9 -tinynet_b,62.730,37.270,84.250,15.750,3.73,188,0.875,bicubic,-12.246,-7.934,-3 -gluon_resnet34_v1b,62.570,37.430,83.990,16.010,21.80,224,0.875,bicubic,-12.018,-7.998,+3 -xcit_nano_12_p8_224,62.550,37.450,84.200,15.800,3.05,224,1.000,bicubic,-11.360,-7.968,+10 -tf_efficientnet_lite0,62.540,37.460,84.220,15.780,4.65,224,0.875,bicubic,-12.292,-7.954,-5 +tf_efficientnet_b2_ns,72.280,27.720,91.090,8.910,9.11,260,0.890,bicubic,-10.104,-5.156,+30 +tresnet_m,72.260,27.740,90.230,9.770,31.39,224,0.875,bilinear,-10.814,-5.890,-13 +resnetv2_50x1_bit_distilled,72.250,27.750,91.010,8.990,25.55,224,0.875,bicubic,-10.572,-5.512,-4 +crossvit_18_240,72.250,27.750,90.270,9.730,43.27,240,0.875,bicubic,-10.148,-5.784,+25 +regnetz_c16_evos,72.230,27.770,91.230,8.770,13.49,320,0.950,bicubic,-10.402,-5.246,+7 +nasnetalarge,72.230,27.770,90.460,9.540,88.75,331,0.911,bicubic,-10.388,-5.584,+7 +efficientnetv2_rw_t,72.230,27.770,90.410,9.590,13.65,288,1.000,bicubic,-10.114,-5.786,+27 +cait_xxs36_384,72.200,27.800,90.840,9.160,17.37,384,1.000,bicubic,-9.992,-5.304,+43 +twins_pcpvt_base,72.190,27.810,90.510,9.490,43.83,224,0.900,bicubic,-10.518,-5.840,-1 +crossvit_18_dagger_240,72.130,27.870,90.070,9.930,44.27,240,0.875,bicubic,-10.390,-5.998,+12 +xcit_tiny_24_p16_384_dist,72.080,27.920,90.590,9.410,12.12,384,1.000,bicubic,-10.492,-5.698,+7 +resnet152,72.060,27.940,90.340,9.660,60.19,224,0.950,bicubic,-10.758,-5.792,-12 +mobilevitv2_200_384_in22ft1k,72.000,28.000,90.630,9.370,18.45,384,1.000,bicubic,-11.400,-5.952,-45 +vit_relpos_base_patch16_clsgap_224,72.000,28.000,90.250,9.750,86.43,224,0.900,bicubic,-10.760,-5.924,-10 +vit_relpos_medium_patch16_cls_224,71.990,28.010,90.290,9.710,38.76,224,0.900,bicubic,-10.572,-5.776,+4 +sequencer2d_s,71.940,28.060,90.490,9.510,27.65,224,0.875,bicubic,-10.404,-5.544,+19 +swinv2_cr_small_224,71.880,28.120,90.260,9.740,49.70,224,0.900,bicubic,-11.258,-5.838,-34 +eca_nfnet_l0,71.840,28.160,91.110,8.890,24.14,288,1.000,bicubic,-10.738,-5.380,-1 +convnext_tiny_in22ft1k,71.830,28.170,90.920,9.080,28.59,224,0.875,bicubic,-11.082,-5.704,-24 +vit_relpos_base_patch16_224,71.830,28.170,90.260,9.740,86.43,224,0.900,bicubic,-10.656,-5.882,+4 +mobilevitv2_175_384_in22ft1k,71.810,28.190,90.780,9.220,14.25,384,1.000,bicubic,-11.124,-5.650,-27 +cs3edgenet_x,71.810,28.190,90.360,9.640,47.82,288,1.000,bicubic,-10.912,-6.016,-15 +swin_small_patch4_window7_224,71.750,28.250,90.240,9.760,49.61,224,0.900,bicubic,-11.468,-6.086,-46 +pit_b_224,71.710,28.290,89.250,10.750,73.76,224,0.900,bicubic,-10.734,-6.462,+4 +xcit_large_24_p16_224,71.700,28.300,89.170,10.830,189.10,224,1.000,bicubic,-11.192,-6.708,-29 +swsl_resnet50,71.690,28.310,90.470,9.530,25.56,224,0.875,bilinear,-9.490,-5.510,+87 +resnet61q,71.670,28.330,90.270,9.730,36.85,288,1.000,bicubic,-10.848,-5.860,-4 +tresnet_xl,71.660,28.340,89.630,10.370,78.44,224,0.875,bilinear,-10.402,-6.306,+30 +tresnet_l_448,71.610,28.390,90.060,9.940,55.99,448,0.875,bilinear,-10.660,-5.920,+15 +convit_base,71.590,28.410,90.160,9.840,86.54,224,0.875,bicubic,-10.702,-5.778,+12 +xcit_tiny_12_p8_384_dist,71.580,28.420,90.710,9.290,6.71,384,1.000,bicubic,-10.806,-5.512,-1 +swinv2_tiny_window16_256,71.570,28.430,90.350,9.650,28.35,256,0.900,bicubic,-11.240,-5.880,-31 +poolformer_m48,71.550,28.450,89.760,10.240,73.47,224,0.950,bicubic,-10.910,-6.198,-6 +fbnetv3_g,71.520,28.480,90.380,9.620,16.62,288,0.950,bilinear,-10.514,-5.686,+27 +crossvit_15_dagger_240,71.520,28.480,89.860,10.140,28.21,240,0.875,bicubic,-10.806,-6.096,+3 +ssl_resnext101_32x8d,71.510,28.490,90.470,9.530,88.79,224,0.875,bilinear,-10.098,-5.572,+48 +efficientnet_b3,71.480,28.520,90.060,9.940,12.23,320,1.000,bicubic,-10.760,-6.058,+8 +ecaresnet101d,71.470,28.530,90.330,9.670,44.57,224,0.875,bicubic,-10.700,-5.718,+15 +mobilevitv2_150_384_in22ft1k,71.460,28.540,90.420,9.580,10.59,384,1.000,bicubic,-11.130,-5.896,-25 +ssl_resnext101_32x16d,71.430,28.570,90.520,9.480,194.03,224,0.875,bilinear,-10.426,-5.576,+32 +resnet51q,71.420,28.580,90.180,9.820,35.70,288,1.000,bilinear,-10.938,-5.998,-9 +vit_relpos_medium_patch16_224,71.370,28.630,89.950,10.050,38.75,224,0.900,bicubic,-11.092,-6.136,-16 +pit_s_distilled_224,71.360,28.640,89.780,10.220,24.04,224,0.900,bicubic,-10.634,-6.016,+19 +xcit_tiny_24_p8_224,71.330,28.670,90.240,9.760,12.11,224,1.000,bicubic,-10.566,-5.734,+26 +mixer_b16_224_miil,71.310,28.690,89.650,10.350,59.88,224,0.875,bilinear,-10.994,-6.070,-5 +resnetv2_152x2_bit_teacher,71.290,28.710,90.430,9.570,236.34,224,0.875,bicubic,-11.578,-6.138,-48 +resnetv2_101,71.280,28.720,89.940,10.060,44.54,224,0.950,bicubic,-10.766,-5.922,+13 +convnext_tiny_hnf,71.280,28.720,89.400,10.600,28.59,224,0.950,bicubic,-10.940,-6.466,0 +ecaresnet50t,71.260,28.740,90.420,9.580,25.57,320,0.950,bicubic,-11.088,-5.718,-16 +convmixer_1536_20,71.230,28.770,89.440,10.560,51.63,224,0.960,bicubic,-10.140,-6.172,+54 +xcit_small_12_p16_224,71.200,28.800,89.750,10.250,26.25,224,1.000,bicubic,-10.772,-6.062,+14 +deit_base_patch16_224,71.200,28.800,89.200,10.800,86.57,224,0.900,bicubic,-10.794,-6.532,+11 +crossvit_base_240,71.180,28.820,89.840,10.160,105.03,240,0.875,bicubic,-11.036,-5.992,-4 +vit_relpos_medium_patch16_rpn_224,71.170,28.830,90.090,9.910,38.73,224,0.900,bicubic,-11.124,-5.882,-13 +mobilevitv2_200_in22ft1k,71.140,28.860,89.680,10.320,18.45,256,0.888,bicubic,-11.194,-6.258,-19 +resnetv2_50d_evos,71.120,28.880,90.030,9.970,25.59,288,0.950,bicubic,-10.858,-5.882,+8 +swin_s3_tiny_224,71.120,28.880,89.720,10.280,28.33,224,0.900,bicubic,-11.004,-6.230,-3 +halo2botnet50ts_256,71.110,28.890,89.630,10.370,22.64,256,0.950,bicubic,-10.958,-6.012,-1 +cs3darknet_x,71.080,28.920,90.150,9.850,35.05,288,1.000,bicubic,-11.144,-6.080,-12 +cs3sedarknet_l,71.070,28.930,90.350,9.650,21.91,288,0.950,bicubic,-10.706,-5.620,+17 +xcit_small_24_p16_224,71.040,28.960,89.700,10.300,47.67,224,1.000,bicubic,-11.544,-6.300,-45 +xcit_tiny_12_p8_224_dist,71.030,28.970,89.890,10.110,6.71,224,1.000,bicubic,-10.178,-5.716,+49 +xcit_medium_24_p16_224,71.010,28.990,89.520,10.480,84.40,224,1.000,bicubic,-11.628,-6.458,-52 +visformer_small,71.000,29.000,89.450,10.550,40.22,224,0.900,bicubic,-11.108,-6.426,-9 +resnetv2_101x1_bitm,70.990,29.010,91.090,8.910,44.54,448,1.000,bilinear,-11.342,-5.426,-28 +edgenext_small,70.990,29.010,89.870,10.130,5.59,320,1.000,bicubic,-10.584,-5.844,+19 +resnetv2_50d_gn,70.990,29.010,89.770,10.230,25.57,288,0.950,bicubic,-10.834,-6.154,+6 +lamhalobotnet50ts_256,70.990,29.010,89.070,10.930,22.57,256,0.950,bicubic,-10.562,-6.434,+18 +tresnet_m_448,70.990,29.010,88.690,11.310,31.39,448,0.875,bilinear,-10.716,-6.882,+9 +resnest50d_4s2x40d,70.950,29.050,89.720,10.280,30.42,224,0.875,bicubic,-10.158,-5.842,+48 +tnt_s_patch16_224,70.950,29.050,89.600,10.400,23.76,224,0.900,bicubic,-10.568,-6.146,+18 +wide_resnet50_2,70.940,29.060,89.230,10.770,68.88,224,0.875,bicubic,-10.516,-6.300,+23 +convnext_tiny,70.930,29.070,89.750,10.250,28.59,224,0.875,bicubic,-11.132,-6.104,-14 +tf_efficientnet_b3_ap,70.920,29.080,89.430,10.570,12.23,300,0.904,bicubic,-10.904,-6.194,0 +vit_small_patch16_224,70.910,29.090,90.150,9.850,22.05,224,0.900,bicubic,-10.486,-5.988,+25 +vit_srelpos_medium_patch16_224,70.910,29.090,89.960,10.040,38.74,224,0.900,bicubic,-11.326,-5.974,-30 +vit_base_patch16_rpn_224,70.870,29.130,89.770,10.230,86.54,224,0.900,bicubic,-11.330,-6.226,-27 +resnet101,70.870,29.130,89.510,10.490,44.55,224,0.950,bicubic,-11.060,-6.256,-9 +vit_large_patch32_384,70.860,29.140,90.570,9.430,306.63,384,1.000,bicubic,-10.648,-5.520,+12 +tf_efficientnet_b1_ns,70.860,29.140,90.140,9.860,7.79,240,0.882,bicubic,-10.526,-5.596,+21 +jx_nest_tiny,70.860,29.140,89.940,10.060,17.06,224,0.875,bicubic,-10.558,-5.678,+17 +resnetrs101,70.860,29.140,89.830,10.170,63.62,288,0.940,bicubic,-11.424,-6.178,-39 +rexnet_200,70.850,29.150,89.710,10.290,16.37,224,0.875,bicubic,-10.778,-5.958,-1 +tresnet_l,70.840,29.160,89.630,10.370,55.99,224,0.875,bilinear,-10.650,-5.996,+8 +tf_efficientnetv2_b3,70.830,29.170,89.510,10.490,14.36,300,0.904,bicubic,-11.136,-6.272,-18 +poolformer_m36,70.800,29.200,89.510,10.490,56.17,224,0.950,bicubic,-11.308,-6.180,-30 +coat_lite_small,70.780,29.220,89.580,10.420,19.84,224,0.900,bicubic,-11.524,-6.270,-48 +deit3_small_patch16_224,70.760,29.240,89.440,10.560,22.06,224,0.900,bicubic,-10.622,-6.010,+14 +levit_384,70.760,29.240,89.290,10.710,39.13,224,0.900,bicubic,-11.828,-6.728,-74 +convnext_nano,70.730,29.270,89.350,10.650,15.59,288,1.000,bicubic,-10.746,-6.310,+3 +swinv2_cr_tiny_ns_224,70.720,29.280,89.380,10.620,28.33,224,0.900,bicubic,-11.066,-6.442,-15 +vit_relpos_small_patch16_224,70.710,29.290,90.000,10.000,21.98,224,0.900,bicubic,-10.744,-5.828,+4 +mobilevitv2_175_in22ft1k,70.660,29.340,89.710,10.290,14.25,256,0.888,bicubic,-11.280,-6.080,-25 +tf_efficientnet_b3,70.640,29.360,89.450,10.550,12.23,300,0.904,bicubic,-10.998,-6.268,-13 +gluon_senet154,70.620,29.380,88.920,11.080,115.09,224,0.875,bicubic,-10.610,-6.426,+15 +crossvit_small_240,70.610,29.390,89.360,10.640,26.86,240,0.875,bicubic,-10.406,-6.096,+29 +cait_xxs24_384,70.600,29.400,89.720,10.280,12.03,384,1.000,bicubic,-10.362,-5.924,+33 +convit_small,70.590,29.410,89.580,10.420,27.78,224,0.875,bicubic,-10.838,-6.162,-1 +twins_pcpvt_small,70.560,29.440,89.070,10.930,24.11,224,0.900,bicubic,-10.530,-6.572,+23 +swinv2_tiny_window8_256,70.540,29.460,89.490,10.510,28.35,256,0.900,bicubic,-11.270,-6.504,-25 +ssl_resnext101_32x4d,70.530,29.470,89.760,10.240,44.18,224,0.875,bilinear,-10.394,-5.966,+32 +vit_small_r26_s32_224,70.520,29.480,90.110,9.890,36.43,224,0.900,bicubic,-11.342,-5.912,-31 +deit_small_distilled_patch16_224,70.520,29.480,89.470,10.530,22.44,224,0.900,bicubic,-10.688,-5.904,+9 +legacy_senet154,70.500,29.500,89.010,10.990,115.09,224,0.875,bilinear,-10.808,-6.486,+2 +halonet50ts,70.490,29.510,89.330,10.670,22.73,256,0.940,bicubic,-11.162,-6.282,-25 +regnetz_b16,70.460,29.540,89.540,10.460,9.72,288,0.940,bicubic,-10.252,-5.934,+39 +crossvit_15_240,70.450,29.550,89.530,10.470,27.53,240,0.875,bicubic,-11.094,-6.160,-20 +gluon_seresnext101_64x4d,70.440,29.560,89.360,10.640,88.23,224,0.875,bicubic,-10.440,-5.936,+28 +twins_svt_small,70.440,29.560,89.350,10.650,24.06,224,0.900,bicubic,-11.242,-6.316,-30 +tf_efficientnet_lite4,70.430,29.570,89.110,10.890,13.01,380,0.920,bilinear,-11.104,-6.556,-22 +resnetaa50,70.410,29.590,89.970,10.030,25.56,288,1.000,bicubic,-11.208,-5.840,-28 +resnest50d,70.410,29.590,88.760,11.240,27.48,224,0.875,bilinear,-10.564,-6.620,+16 +resnest50d_1s4x24d,70.400,29.600,89.240,10.760,25.68,224,0.875,bicubic,-10.584,-6.084,+14 +seresnext50_32x4d,70.390,29.610,89.110,10.890,27.56,224,0.875,bicubic,-10.872,-6.518,-5 +cs3darknet_l,70.370,29.630,89.750,10.250,21.16,288,0.950,bicubic,-10.516,-5.918,+20 +gernet_l,70.360,29.640,88.980,11.020,31.08,256,0.875,bilinear,-10.990,-6.556,-11 +vit_srelpos_small_patch16_224,70.290,29.710,89.580,10.420,21.97,224,0.900,bicubic,-10.808,-5.992,+2 +gluon_resnet152_v1s,70.290,29.710,88.850,11.150,60.32,224,0.875,bicubic,-10.724,-6.564,+8 +repvgg_b3,70.250,29.750,88.740,11.260,123.09,224,0.875,bilinear,-10.246,-6.524,+36 +coat_mini,70.210,29.790,89.450,10.550,10.34,224,0.900,bicubic,-11.056,-5.942,-12 +xception41p,70.200,29.800,89.090,10.910,26.91,299,0.940,bicubic,-11.768,-6.704,-55 +sebotnet33ts_256,70.150,29.850,88.800,11.200,13.70,256,0.940,bicubic,-11.004,-6.366,-7 +efficientnet_el,70.120,29.880,89.290,10.710,10.59,300,0.904,bicubic,-11.186,-6.244,-16 +inception_resnet_v2,70.120,29.880,88.700,11.300,55.84,299,0.897,bicubic,-10.340,-6.606,+35 +resmlp_36_distilled_224,70.110,29.890,89.100,10.900,44.69,224,0.875,bicubic,-11.046,-6.386,-11 +ecaresnet101d_pruned,70.100,29.900,89.580,10.420,24.88,224,0.875,bicubic,-10.710,-6.048,+14 +haloregnetz_b,70.070,29.930,88.870,11.130,11.68,224,0.940,bicubic,-10.974,-6.328,-4 +poolformer_s36,70.030,29.970,89.190,10.810,30.86,224,0.900,bicubic,-11.388,-6.258,-29 +gluon_seresnext101_32x4d,70.030,29.970,88.910,11.090,48.96,224,0.875,bicubic,-10.876,-6.386,+5 +sehalonet33ts,70.020,29.980,88.710,11.290,13.69,256,0.940,bicubic,-10.952,-6.562,-1 +regnety_320,70.010,29.990,88.890,11.110,145.05,224,0.875,bicubic,-10.794,-6.354,+10 +gluon_resnet152_v1d,69.970,30.030,88.490,11.510,60.21,224,0.875,bicubic,-10.506,-6.710,+26 +levit_256,69.950,30.050,89.240,10.760,18.89,224,0.900,bicubic,-11.566,-6.250,-43 +pit_s_224,69.890,30.110,88.930,11.070,23.46,224,0.900,bicubic,-11.208,-6.402,-14 +ecaresnet50d,69.840,30.160,89.390,10.610,25.58,224,0.875,bicubic,-10.758,-5.928,+14 +mobilevitv2_150_in22ft1k,69.830,30.170,89.160,10.840,10.59,256,0.888,bicubic,-11.640,-6.508,-42 +mobilevitv2_200,69.760,30.240,88.620,11.380,18.45,256,0.888,bicubic,-11.380,-6.748,-20 +ssl_resnext50_32x4d,69.730,30.270,89.430,10.570,25.03,224,0.875,bilinear,-10.596,-5.982,+33 +gluon_resnext101_64x4d,69.710,30.290,88.270,11.730,83.46,224,0.875,bicubic,-10.894,-6.722,+9 +lambda_resnet50ts,69.700,30.300,88.820,11.180,21.54,256,0.950,bicubic,-11.452,-6.282,-24 +xcit_tiny_24_p16_224_dist,69.700,30.300,88.710,11.290,12.12,224,1.000,bicubic,-10.748,-6.502,+21 +xcit_tiny_12_p16_384_dist,69.690,30.310,89.010,10.990,6.72,384,1.000,bicubic,-11.252,-6.398,-11 +resnext50_32x4d,69.680,30.320,88.660,11.340,25.03,224,0.950,bicubic,-11.416,-6.666,-22 +resmlp_24_distilled_224,69.670,30.330,89.050,10.950,30.02,224,0.875,bicubic,-11.094,-6.172,-2 +efficientnet_b3_pruned,69.590,30.410,88.980,11.020,9.86,300,0.904,bicubic,-11.268,-6.264,-6 +gernet_m,69.560,30.440,88.700,11.300,21.14,224,0.875,bilinear,-11.170,-6.486,-3 +nf_resnet50,69.540,30.460,88.730,11.270,25.56,288,0.940,bicubic,-11.114,-6.604,-1 +gcresnext50ts,69.530,30.470,88.840,11.160,15.67,256,0.900,bicubic,-11.048,-6.330,+2 +efficientnet_el_pruned,69.520,30.480,88.930,11.070,10.59,300,0.904,bicubic,-10.778,-6.284,+26 +repvgg_b3g4,69.520,30.480,88.450,11.550,83.83,224,0.875,bilinear,-10.696,-6.658,+32 +gcresnet50t,69.510,30.490,89.050,10.950,25.90,256,0.900,bicubic,-11.424,-6.404,-19 +ens_adv_inception_resnet_v2,69.510,30.490,88.520,11.480,55.84,299,0.897,bicubic,-10.464,-6.422,+42 +efficientnet_b2,69.490,30.510,88.690,11.310,9.11,288,1.000,bicubic,-11.126,-6.626,-6 +rexnet_150,69.460,30.540,88.980,11.020,9.73,224,0.875,bicubic,-10.854,-6.186,+19 +regnetx_320,69.450,30.550,88.270,11.730,107.81,224,0.875,bicubic,-10.794,-6.750,+24 +swin_tiny_patch4_window7_224,69.440,30.560,89.020,10.980,28.29,224,0.900,bicubic,-11.936,-6.522,-53 +vit_base_patch32_224,69.420,30.580,89.430,10.570,88.22,224,0.900,bicubic,-11.304,-6.136,-13 +cspresnext50,69.420,30.580,88.610,11.390,20.57,256,0.887,bilinear,-11.124,-6.714,-7 +convmixer_768_32,69.400,30.600,88.870,11.130,21.11,224,0.960,bicubic,-10.764,-6.202,+27 +darknet53,69.370,30.630,88.760,11.240,41.61,288,1.000,bicubic,-11.168,-6.660,-8 +legacy_seresnext101_32x4d,69.370,30.630,88.060,11.940,48.96,224,0.875,bilinear,-10.852,-6.954,+20 +inception_v4,69.360,30.640,88.780,11.220,42.68,299,0.875,bicubic,-10.808,-6.184,+22 +ecaresnetlight,69.350,30.650,89.230,10.770,30.16,224,0.875,bicubic,-11.106,-6.016,-3 +resnet50d,69.350,30.650,88.230,11.770,25.58,224,0.875,bicubic,-11.178,-6.938,-11 +cs3darknet_focus_l,69.330,30.670,89.440,10.560,21.15,288,0.950,bicubic,-11.544,-6.252,-28 +xception71,69.320,30.680,88.270,11.730,42.34,299,0.903,bicubic,-10.550,-6.654,+33 +mobilevitv2_175,69.300,30.700,88.940,11.060,14.25,256,0.888,bicubic,-11.562,-6.322,-29 +vit_small_patch32_384,69.290,30.710,89.820,10.180,22.92,384,1.000,bicubic,-11.200,-5.780,-12 +edgenext_small_rw,69.210,30.790,88.760,11.240,7.83,320,1.000,bicubic,-11.242,-6.430,-8 +gluon_xception65,69.160,30.840,88.080,11.920,39.92,299,0.903,bicubic,-10.562,-6.780,+38 +gluon_resnet152_v1c,69.150,30.850,87.870,12.130,60.21,224,0.875,bicubic,-10.762,-6.972,+25 +mixnet_xl,69.110,30.890,88.310,11.690,11.90,224,0.875,bicubic,-11.368,-6.624,-15 +seresnet33ts,69.100,30.900,88.490,11.510,19.78,256,0.900,bicubic,-11.254,-6.616,-5 +tf_efficientnetv2_b2,69.100,30.900,88.220,11.780,10.10,260,0.890,bicubic,-11.108,-6.824,+9 +resnetv2_50,69.070,30.930,88.440,11.560,25.55,224,0.950,bicubic,-11.342,-6.632,-11 +gcresnet33ts,69.010,30.990,88.470,11.530,19.88,256,0.900,bicubic,-11.066,-6.524,+14 +gluon_resnet101_v1d,69.010,30.990,88.100,11.900,44.57,224,0.875,bicubic,-11.408,-6.914,-14 +repvgg_b2g4,69.000,31.000,88.340,11.660,61.76,224,0.875,bilinear,-10.366,-6.348,+50 +seresnet50,68.950,31.050,88.700,11.300,28.09,224,0.875,bicubic,-11.316,-6.370,-2 +gluon_resnext101_32x4d,68.950,31.050,88.370,11.630,44.18,224,0.875,bicubic,-11.390,-6.556,-10 +cspdarknet53,68.930,31.070,88.600,11.400,27.64,256,0.887,bilinear,-11.126,-6.486,+11 +tf_efficientnet_b2_ap,68.930,31.070,88.350,11.650,9.11,260,0.890,bicubic,-11.372,-6.678,-8 +regnety_120,68.870,31.130,88.330,11.670,51.82,224,0.875,bicubic,-11.506,-6.792,-18 +mobilevitv2_150,68.850,31.150,88.080,11.920,10.59,256,0.888,bicubic,-11.518,-6.984,-17 +resnet50_gn,68.840,31.160,88.420,11.580,25.56,224,0.940,bicubic,-11.220,-6.528,+6 +gluon_resnet152_v1b,68.820,31.180,87.720,12.280,60.19,224,0.875,bicubic,-10.862,-7.016,+26 +eca_resnet33ts,68.800,31.200,88.580,11.420,19.68,256,0.900,bicubic,-11.280,-6.392,+2 +gmlp_s16_224,68.760,31.240,88.080,11.920,19.42,224,0.875,bicubic,-10.880,-6.544,+28 +dpn131,68.760,31.240,87.460,12.540,79.25,224,0.875,bicubic,-11.066,-7.248,+15 +poolformer_s24,68.750,31.250,88.210,11.790,21.39,224,0.900,bicubic,-11.566,-6.832,-18 +darknetaa53,68.740,31.260,88.720,11.280,36.02,288,1.000,bilinear,-11.782,-6.606,-37 +tf_efficientnet_b2,68.740,31.260,87.980,12.020,9.11,260,0.890,bicubic,-11.348,-6.928,-4 +resnet50,68.740,31.260,87.680,12.320,25.56,224,0.950,bicubic,-11.634,-6.934,-27 +resnext50d_32x4d,68.730,31.270,88.300,11.700,25.05,224,0.875,bicubic,-10.946,-6.566,+20 +deit_small_patch16_224,68.710,31.290,88.200,11.800,22.05,224,0.900,bicubic,-11.154,-6.848,+5 +gluon_resnet101_v1s,68.710,31.290,87.910,12.090,44.67,224,0.875,bicubic,-11.588,-7.252,-20 +dpn107,68.700,31.300,88.140,11.860,86.92,224,0.875,bicubic,-11.468,-6.766,-12 +gluon_seresnext50_32x4d,68.680,31.320,88.330,11.670,27.56,224,0.875,bicubic,-11.232,-6.502,-1 +hrnet_w64,68.630,31.370,88.050,11.950,128.06,224,0.875,bilinear,-10.840,-6.604,+24 +dpn98,68.600,31.400,87.660,12.340,61.57,224,0.875,bicubic,-11.044,-6.940,+15 +xcit_tiny_12_p8_224,68.570,31.430,88.690,11.310,6.71,224,1.000,bicubic,-11.124,-6.358,+9 +regnetx_160,68.530,31.470,88.440,11.560,54.28,224,0.875,bicubic,-11.324,-6.390,-1 +xcit_tiny_24_p16_224,68.440,31.560,88.290,11.710,12.12,224,1.000,bicubic,-11.004,-6.598,+22 +rexnet_130,68.440,31.560,88.040,11.960,7.56,224,0.875,bicubic,-11.062,-6.642,+16 +tf_efficientnet_el,68.430,31.570,88.210,11.790,10.59,300,0.904,bicubic,-11.824,-6.918,-27 +cspresnet50,68.420,31.580,87.970,12.030,21.62,256,0.887,bilinear,-11.162,-6.738,+12 +cait_xxs36_224,68.400,31.600,88.640,11.360,17.30,224,1.000,bicubic,-11.348,-6.228,0 +ecaresnet50d_pruned,68.400,31.600,88.370,11.630,19.94,224,0.875,bicubic,-11.318,-6.506,+1 +dla102x2,68.380,31.620,87.890,12.110,41.28,224,0.875,bilinear,-11.062,-6.756,+17 +skresnext50_32x4d,68.370,31.630,87.560,12.440,27.48,224,0.875,bicubic,-11.784,-7.086,-23 +ssl_resnet50,68.360,31.640,88.530,11.470,25.56,224,0.875,bilinear,-10.864,-6.300,+31 +fbnetv3_d,68.350,31.650,88.450,11.550,10.31,256,0.950,bilinear,-11.330,-6.490,+1 +efficientnet_b2_pruned,68.320,31.680,88.100,11.900,8.31,260,0.890,bicubic,-11.598,-6.750,-18 +resmlp_big_24_224,68.320,31.680,87.520,12.480,129.14,224,0.875,bicubic,-12.710,-7.500,-90 +gluon_resnext50_32x4d,68.310,31.690,87.300,12.700,25.03,224,0.875,bicubic,-11.050,-7.126,+14 +vit_base_patch16_224_sam,68.270,31.730,87.730,12.270,86.57,224,0.900,bicubic,-11.974,-7.024,-36 +ecaresnet26t,68.230,31.770,88.800,11.200,16.01,320,0.950,bicubic,-11.622,-6.284,-15 +tf_efficientnet_lite3,68.230,31.770,87.740,12.260,8.20,300,0.904,bilinear,-11.588,-7.174,-13 +ese_vovnet39b,68.200,31.800,88.260,11.740,24.57,224,0.875,bicubic,-11.112,-6.454,+13 +fbnetv3_b,68.190,31.810,87.930,12.070,8.60,256,0.950,bilinear,-10.952,-6.820,+27 +regnetx_120,68.170,31.830,87.660,12.340,46.11,224,0.875,bicubic,-11.422,-7.074,-4 +resmlp_36_224,68.060,31.940,88.190,11.810,44.69,224,0.875,bicubic,-11.710,-6.696,-16 +resnetrs50,68.030,31.970,87.710,12.290,35.69,224,0.910,bicubic,-11.856,-7.260,-25 +pit_xs_distilled_224,68.000,32.000,87.720,12.280,11.00,224,0.900,bicubic,-11.308,-6.646,+9 +nf_regnet_b1,67.970,32.030,88.190,11.810,10.22,288,0.900,bicubic,-11.330,-6.564,+10 +dpn92,67.970,32.030,87.540,12.460,37.67,224,0.875,bicubic,-12.050,-7.290,-33 +gluon_resnet50_v1d,67.950,32.050,87.130,12.870,25.58,224,0.875,bicubic,-11.120,-7.336,+26 +resnetv2_50x1_bitm,67.930,32.070,89.290,10.710,25.55,448,1.000,bilinear,-12.412,-6.396,-59 +levit_192,67.900,32.100,87.900,12.100,10.95,224,0.900,bicubic,-11.936,-6.890,-26 +tf_efficientnetv2_b1,67.890,32.110,87.800,12.200,8.14,240,0.882,bicubic,-11.576,-6.922,-6 +regnetx_080,67.880,32.120,86.990,13.010,39.57,224,0.875,bicubic,-11.322,-7.562,+14 +resnext101_32x8d,67.860,32.140,87.490,12.510,88.79,224,0.875,bilinear,-11.456,-7.028,-2 +efficientnet_em,67.840,32.160,88.120,11.880,6.90,240,0.882,bicubic,-11.412,-6.672,+8 +legacy_seresnext50_32x4d,67.840,32.160,87.620,12.380,27.56,224,0.875,bilinear,-11.236,-6.814,+17 +lambda_resnet26t,67.810,32.190,87.780,12.220,10.96,256,0.940,bicubic,-11.288,-6.810,+14 +resmlp_24_224,67.800,32.200,87.600,12.400,30.02,224,0.875,bicubic,-11.578,-6.946,-9 +hrnet_w48,67.770,32.230,87.410,12.590,77.47,224,0.875,bilinear,-11.530,-7.104,-1 +hrnet_w44,67.740,32.260,87.550,12.450,67.06,224,0.875,bilinear,-11.156,-6.820,+22 +tf_efficientnet_b0_ns,67.720,32.280,88.060,11.940,5.29,224,0.875,bicubic,-10.944,-6.316,+30 +coat_lite_mini,67.720,32.280,87.700,12.300,11.01,224,0.900,bicubic,-11.368,-6.908,+10 +eca_botnext26ts_256,67.690,32.310,87.050,12.950,10.59,256,0.950,bicubic,-11.586,-7.566,-3 +xception,67.680,32.320,87.580,12.420,22.86,299,0.897,bicubic,-11.364,-6.814,+12 +regnetx_064,67.670,32.330,87.540,12.460,26.21,224,0.875,bicubic,-11.404,-6.920,+9 +halonet26t,67.620,32.380,87.260,12.740,12.48,256,0.950,bicubic,-11.492,-7.054,+4 +dpn68b,67.610,32.390,87.670,12.330,12.61,224,0.875,bicubic,-11.606,-6.744,-2 +dla169,67.600,32.400,87.550,12.450,53.39,224,0.875,bilinear,-11.082,-6.786,+22 +gluon_inception_v3,67.590,32.410,87.470,12.530,23.83,299,0.875,bicubic,-11.216,-6.900,+16 +gluon_resnet101_v1c,67.580,32.420,87.180,12.820,44.57,224,0.875,bicubic,-11.956,-7.398,-29 +hrnet_w40,67.550,32.450,87.140,12.860,57.56,224,0.875,bilinear,-11.372,-7.330,+10 +legacy_seresnet152,67.530,32.470,87.400,12.600,66.82,224,0.875,bilinear,-11.122,-6.970,+20 +tf_efficientnet_b1_ap,67.520,32.480,87.760,12.240,7.79,240,0.882,bicubic,-11.754,-6.548,-12 +eca_halonext26ts,67.480,32.520,87.240,12.760,10.76,256,0.940,bicubic,-12.008,-7.364,-31 +efficientnet_b1,67.470,32.530,87.500,12.500,7.79,256,1.000,bicubic,-11.318,-6.846,+12 +gluon_resnet101_v1b,67.470,32.530,87.230,12.770,44.55,224,0.875,bicubic,-11.834,-7.290,-20 +mobilevitv2_125,67.460,32.540,87.570,12.430,7.48,256,0.888,bicubic,-12.222,-7.278,-44 +resnetblur50,67.460,32.540,87.440,12.560,25.56,224,0.875,bicubic,-11.834,-7.194,-19 +tf_efficientnet_cc_b1_8e,67.460,32.540,87.310,12.690,39.72,240,0.882,bicubic,-11.854,-7.060,-26 +res2net101_26w_4s,67.460,32.540,87.010,12.990,45.21,224,0.875,bilinear,-11.736,-7.426,-12 +res2net50_26w_8s,67.430,32.570,87.270,12.730,48.40,224,0.875,bilinear,-11.522,-7.036,-1 +resnet33ts,67.380,32.620,87.590,12.410,19.68,256,0.900,bicubic,-11.828,-6.984,-16 +cait_xxs24_224,67.350,32.650,87.520,12.480,11.96,224,1.000,bicubic,-11.036,-6.788,+23 +regnetx_032,67.290,32.710,87.000,13.000,15.30,224,0.875,bicubic,-10.894,-7.088,+34 +xception41,67.250,32.750,87.210,12.790,26.97,299,0.903,bicubic,-11.266,-7.070,+10 +coat_tiny,67.240,32.760,87.280,12.720,5.50,224,0.900,bicubic,-11.196,-6.758,+17 +resnest26d,67.190,32.810,87.170,12.830,17.07,224,0.875,bilinear,-11.294,-7.124,+11 +repvgg_b2,67.160,32.840,87.330,12.670,89.02,224,0.875,bilinear,-11.634,-7.088,-2 +legacy_seresnet101,67.140,32.860,87.040,12.960,49.33,224,0.875,bilinear,-11.240,-7.222,+18 +botnet26t_256,67.130,32.870,87.530,12.470,12.49,256,0.950,bicubic,-12.128,-6.998,-28 +vit_relpos_base_patch32_plus_rpn_256,67.130,32.870,86.500,13.500,119.42,256,0.900,bicubic,-12.356,-7.640,-47 +dla60x,67.080,32.920,87.180,12.820,17.35,224,0.875,bilinear,-11.148,-6.844,+23 +gluon_resnet50_v1s,67.060,32.940,86.860,13.140,25.68,224,0.875,bicubic,-11.646,-7.378,-4 +tv_resnet152,67.030,32.970,87.550,12.450,60.19,224,0.875,bilinear,-11.290,-6.484,+16 +dla60_res2net,67.030,32.970,87.160,12.840,20.85,224,0.875,bilinear,-11.428,-7.036,+5 +xcit_tiny_12_p16_224_dist,67.010,32.990,87.410,12.590,6.72,224,1.000,bicubic,-11.568,-6.788,-3 +dla102x,66.980,33.020,86.770,13.230,26.31,224,0.875,bilinear,-11.532,-7.458,-1 +lambda_resnet26rpt_256,66.960,33.040,87.130,12.870,10.99,256,0.940,bicubic,-12.004,-7.296,-19 +mixnet_l,66.960,33.040,86.920,13.080,7.33,224,0.875,bicubic,-12.016,-7.258,-21 +pit_xs_224,66.920,33.080,87.290,12.710,10.62,224,0.900,bicubic,-11.270,-6.876,+17 +res2net50_26w_6s,66.920,33.080,86.860,13.140,37.05,224,0.875,bilinear,-11.650,-7.264,-7 +repvgg_b1,66.900,33.100,86.790,13.210,57.42,224,0.875,bilinear,-11.468,-7.304,+6 +tf_efficientnet_b1,66.890,33.110,87.020,12.980,7.79,240,0.882,bicubic,-11.938,-7.178,-19 +xcit_nano_12_p8_384_dist,66.880,33.120,87.110,12.890,3.05,384,1.000,bicubic,-10.936,-6.936,+34 +efficientnet_es,66.870,33.130,86.730,13.270,5.44,224,0.875,bicubic,-11.188,-7.214,+18 +mobilevit_s,66.860,33.140,87.080,12.920,5.58,256,0.900,bicubic,-11.450,-7.072,+5 +resnet32ts,66.850,33.150,87.260,12.740,17.96,256,0.900,bicubic,-12.164,-7.096,-30 +regnetx_040,66.830,33.170,86.740,13.260,22.12,224,0.875,bicubic,-11.658,-7.498,-11 +tf_mixnet_l,66.780,33.220,86.460,13.540,7.33,224,0.875,bicubic,-11.998,-7.538,-21 +hrnet_w32,66.770,33.230,87.310,12.690,41.23,224,0.875,bilinear,-11.682,-6.878,-8 +hrnet_w30,66.770,33.230,86.790,13.210,37.71,224,0.875,bilinear,-11.428,-7.434,+5 +selecsls60b,66.750,33.250,86.530,13.470,32.77,224,0.875,bicubic,-11.654,-7.642,-7 +wide_resnet101_2,66.720,33.280,87.020,12.980,126.89,224,0.875,bilinear,-12.132,-7.268,-30 +tf_efficientnetv2_b0,66.690,33.310,86.710,13.290,7.14,224,0.875,bicubic,-11.662,-7.316,-5 +adv_inception_v3,66.650,33.350,86.540,13.460,23.83,299,0.875,bicubic,-10.928,-7.198,+34 +dla60_res2next,66.640,33.360,87.030,12.970,17.03,224,0.875,bilinear,-11.816,-7.116,-15 +mobilevitv2_100,66.590,33.410,87.020,12.980,4.90,256,0.888,bicubic,-11.496,-7.140,+5 +vit_tiny_patch16_384,66.570,33.430,87.270,12.730,5.79,384,1.000,bicubic,-11.860,-7.274,-14 +levit_128,66.570,33.430,86.750,13.250,9.21,224,0.900,bicubic,-11.912,-7.262,-20 +cs3darknet_m,66.560,33.440,87.180,12.820,9.31,288,0.950,bicubic,-11.066,-6.834,+24 +gluon_resnet50_v1c,66.560,33.440,86.180,13.820,25.58,224,0.875,bicubic,-11.448,-7.810,+5 +dla102,66.520,33.480,86.910,13.090,33.27,224,0.875,bilinear,-11.508,-7.040,+3 +gmixer_24_224,66.430,33.570,86.160,13.840,24.72,224,0.875,bicubic,-11.606,-7.510,+1 +tf_inception_v3,66.410,33.590,86.660,13.340,23.83,299,0.875,bicubic,-11.442,-6.980,+13 +bat_resnext26ts,66.380,33.620,86.830,13.170,10.73,256,0.900,bicubic,-11.868,-7.266,-12 +hardcorenas_f,66.380,33.620,86.190,13.810,8.20,224,0.875,bilinear,-11.722,-7.612,-5 +coat_lite_tiny,66.310,33.690,86.980,13.020,5.72,224,0.900,bicubic,-11.206,-6.934,+24 +efficientnet_b0,66.290,33.710,85.960,14.040,5.29,224,0.875,bicubic,-11.410,-7.572,+13 +cs3darknet_focus_m,66.260,33.740,87.090,12.910,9.30,288,0.950,bicubic,-11.022,-6.882,+32 +legacy_seresnet50,66.260,33.740,86.310,13.690,28.09,224,0.875,bilinear,-11.372,-7.440,+13 +selecsls60,66.200,33.800,86.340,13.660,30.67,224,0.875,bicubic,-11.784,-7.492,-4 +tf_efficientnet_em,66.170,33.830,86.360,13.640,6.90,240,0.882,bicubic,-11.956,-7.686,-12 +tf_efficientnet_cc_b0_8e,66.170,33.830,86.220,13.780,24.01,224,0.875,bicubic,-11.730,-7.438,-1 +tv_resnext50_32x4d,66.160,33.840,86.040,13.960,25.03,224,0.875,bilinear,-11.458,-7.660,+11 +inception_v3,66.150,33.850,86.330,13.670,23.83,299,0.875,bicubic,-11.288,-7.146,+19 +resmlp_12_distilled_224,66.130,33.870,86.620,13.380,15.35,224,0.875,bicubic,-11.816,-6.940,-6 +res2net50_26w_4s,66.130,33.870,86.590,13.410,25.70,224,0.875,bilinear,-11.832,-7.262,-8 +regnety_016,66.100,33.900,86.380,13.620,11.20,224,0.875,bicubic,-11.756,-7.340,-2 +efficientnet_b1_pruned,66.080,33.920,86.570,13.430,6.33,240,0.882,bicubic,-12.164,-7.264,-25 +gluon_resnet50_v1b,66.080,33.920,86.260,13.740,25.56,224,0.875,bicubic,-11.504,-7.460,+8 +rexnet_100,66.060,33.940,86.490,13.510,4.80,224,0.875,bicubic,-11.800,-7.384,-7 +tinynet_a,66.020,33.980,85.790,14.210,6.19,192,0.875,bicubic,-11.628,-7.746,0 +res2net50_14w_8s,66.010,33.990,86.250,13.750,25.06,224,0.875,bilinear,-12.134,-7.602,-24 +gcresnext26ts,65.970,34.030,85.910,14.090,10.48,256,0.900,bicubic,-11.844,-7.926,-5 +seresnext26t_32x4d,65.880,34.120,85.670,14.330,16.81,224,0.875,bicubic,-12.088,-8.078,-17 +res2next50,65.850,34.150,85.830,14.170,24.67,224,0.875,bilinear,-12.408,-8.058,-34 +repvgg_b1g4,65.840,34.160,86.110,13.890,39.97,224,0.875,bilinear,-11.748,-7.720,0 +densenet161,65.830,34.170,86.450,13.550,28.68,224,0.875,bicubic,-11.524,-7.186,+9 +hardcorenas_e,65.810,34.190,85.980,14.020,8.07,224,0.875,bilinear,-11.976,-7.724,-9 +resnet34d,65.790,34.210,86.720,13.280,21.82,224,0.875,bicubic,-11.326,-6.662,+16 +xcit_tiny_12_p16_224,65.770,34.230,86.230,13.770,6.72,224,1.000,bicubic,-11.354,-7.482,+14 +eca_resnext26ts,65.770,34.230,85.840,14.160,10.30,256,0.900,bicubic,-11.688,-7.728,+1 +skresnet34,65.740,34.260,85.960,14.040,22.28,224,0.875,bicubic,-11.164,-7.360,+23 +mobilenetv3_large_100_miil,65.740,34.260,85.170,14.830,5.48,224,0.875,bilinear,-12.182,-7.750,-23 +tv_resnet101,65.690,34.310,85.980,14.020,44.55,224,0.875,bilinear,-11.690,-7.564,+1 +seresnext26ts,65.650,34.350,86.150,13.850,10.39,256,0.900,bicubic,-12.208,-7.640,-21 +hardcorenas_d,65.620,34.380,85.470,14.530,7.50,224,0.875,bilinear,-11.810,-8.014,-2 +selecsls42b,65.600,34.400,85.790,14.210,32.46,224,0.875,bicubic,-11.578,-7.602,+6 +poolformer_s12,65.580,34.420,86.130,13.870,11.92,224,0.900,bicubic,-11.658,-7.376,+4 +tf_efficientnet_b0_ap,65.500,34.500,85.580,14.420,5.29,224,0.875,bicubic,-11.588,-7.678,+8 +seresnext26d_32x4d,65.410,34.590,85.960,14.040,16.81,224,0.875,bicubic,-12.196,-7.646,-15 +convmixer_1024_20_ks9_p14,65.410,34.590,85.590,14.410,24.38,224,0.960,bicubic,-11.532,-7.768,+12 +resnet26t,65.400,34.600,86.110,13.890,16.01,256,0.940,bicubic,-12.464,-7.732,-30 +tf_efficientnet_lite2,65.390,34.610,85.990,14.010,6.09,260,0.890,bicubic,-12.076,-7.768,-12 +res2net50_48w_2s,65.370,34.630,85.960,14.040,25.29,224,0.875,bilinear,-12.154,-7.590,-15 +densenetblur121d,65.290,34.710,85.700,14.300,8.00,224,0.875,bicubic,-11.290,-7.488,+20 +densenet201,65.290,34.710,85.670,14.330,20.01,224,0.875,bicubic,-11.998,-7.810,-7 +dla60,65.210,34.790,85.740,14.260,22.04,224,0.875,bilinear,-11.812,-7.580,+2 +crossvit_9_dagger_240,65.200,34.800,86.590,13.410,8.78,240,0.875,bicubic,-11.778,-7.024,+2 +ese_vovnet19b_dw,65.190,34.810,85.460,14.540,6.54,224,0.875,bicubic,-11.604,-7.806,+8 +tf_efficientnet_cc_b0_4e,65.140,34.860,85.160,14.840,13.31,224,0.875,bicubic,-12.170,-8.180,-13 +gernet_s,65.130,34.870,85.520,14.480,8.17,224,0.875,bilinear,-11.786,-7.614,+3 +legacy_seresnext26_32x4d,65.070,34.930,85.640,14.360,16.79,224,0.875,bicubic,-12.034,-7.676,-6 +mobilenetv2_120d,65.000,35.000,85.960,14.040,5.83,224,0.875,bicubic,-12.290,-7.540,-15 +hrnet_w18,64.920,35.080,85.740,14.260,21.30,224,0.875,bilinear,-11.840,-7.704,+5 +hardcorenas_c,64.880,35.120,85.260,14.740,5.52,224,0.875,bilinear,-12.172,-7.900,-7 +densenet169,64.750,35.250,85.260,14.740,14.15,224,0.875,bicubic,-11.154,-7.764,+22 +mixnet_m,64.710,35.290,85.450,14.550,5.01,224,0.875,bicubic,-12.552,-7.972,-16 +resnet26d,64.680,35.320,85.100,14.900,16.01,224,0.875,bicubic,-12.022,-8.052,+2 +resnext26ts,64.590,35.410,85.120,14.880,10.30,256,0.900,bicubic,-12.190,-8.012,-1 +levit_128s,64.590,35.410,84.730,15.270,7.78,224,0.900,bicubic,-11.924,-8.140,+7 +xcit_nano_12_p8_224_dist,64.550,35.450,85.990,14.010,3.05,224,1.000,bicubic,-11.778,-7.104,+9 +repvgg_a2,64.430,35.570,85.130,14.870,28.21,224,0.875,bilinear,-12.030,-7.880,+7 +xcit_nano_12_p16_384_dist,64.420,35.580,85.310,14.690,3.05,384,1.000,bicubic,-11.036,-7.380,+25 +hardcorenas_b,64.410,35.590,84.900,15.100,5.18,224,0.875,bilinear,-12.126,-7.854,+2 +tf_efficientnet_lite1,64.400,35.600,85.490,14.510,5.42,240,0.882,bicubic,-12.238,-7.734,-3 +regnetx_016,64.370,35.630,85.450,14.550,9.19,224,0.875,bicubic,-12.572,-7.974,-14 +resmlp_12_224,64.350,35.650,85.580,14.420,15.35,224,0.875,bicubic,-12.306,-7.600,-6 +tf_efficientnet_b0,64.320,35.680,85.280,14.720,5.29,224,0.875,bicubic,-12.520,-7.938,-12 +tf_mixnet_m,64.270,35.730,85.100,14.900,5.01,224,0.875,bicubic,-12.676,-8.052,-18 +dpn68,64.240,35.760,85.180,14.820,12.61,224,0.875,bicubic,-12.070,-7.798,+2 +tf_efficientnet_es,64.230,35.770,84.740,15.260,5.44,224,0.875,bicubic,-12.368,-8.464,-7 +regnety_008,64.140,35.860,85.280,14.720,6.26,224,0.875,bicubic,-12.174,-7.790,-1 +vit_small_patch32_224,64.070,35.930,85.570,14.430,22.88,224,0.900,bicubic,-11.920,-7.698,+2 +mobilenetv2_140,64.040,35.960,85.040,14.960,6.11,224,0.875,bicubic,-12.472,-7.958,-6 +densenet121,63.740,36.260,84.610,15.390,7.98,224,0.875,bicubic,-11.840,-8.038,+8 +hardcorenas_a,63.710,36.290,84.400,15.600,5.26,224,0.875,bilinear,-12.220,-8.110,+1 +resnest14d,63.610,36.390,84.250,15.750,10.61,224,0.875,bilinear,-11.898,-8.274,+8 +mobilevitv2_075,63.590,36.410,84.950,15.050,2.87,256,0.888,bicubic,-12.018,-7.808,+4 +tf_mixnet_s,63.560,36.440,84.280,15.720,4.13,224,0.875,bicubic,-12.092,-8.346,+1 +resnet26,63.450,36.550,84.250,15.750,16.00,224,0.875,bicubic,-11.850,-8.330,+10 +mixnet_s,63.390,36.610,84.750,15.250,4.13,224,0.875,bicubic,-12.606,-8.050,-7 +mobilenetv3_large_100,63.360,36.640,84.060,15.940,5.48,224,0.875,bicubic,-12.416,-8.480,-3 +vit_tiny_r_s16_p8_384,63.340,36.660,85.270,14.730,6.36,384,1.000,bicubic,-12.612,-7.992,-7 +tv_resnet50,63.340,36.660,84.650,15.350,25.56,224,0.875,bilinear,-12.794,-8.218,-11 +efficientnet_es_pruned,63.300,36.700,84.960,15.040,5.44,224,0.875,bicubic,-11.700,-7.482,+13 +efficientnet_lite0,63.270,36.730,84.440,15.560,4.65,224,0.875,bicubic,-12.198,-8.076,0 +mixer_b16_224,63.250,36.750,83.310,16.690,59.88,224,0.875,bicubic,-13.360,-8.920,-24 +mobilenetv3_rw,63.240,36.760,84.500,15.500,5.48,224,0.875,bicubic,-12.394,-8.208,-7 +semnasnet_100,63.160,36.840,84.540,15.460,3.89,224,0.875,bicubic,-12.290,-8.060,0 +pit_ti_distilled_224,63.140,36.860,83.950,16.050,5.10,224,0.900,bicubic,-11.394,-8.146,+18 +vit_tiny_patch16_224,63.100,36.900,84.850,15.150,5.72,224,0.900,bicubic,-12.364,-7.994,-4 +regnety_006,63.090,36.910,84.260,15.740,6.06,224,0.875,bicubic,-12.162,-8.272,-1 +mobilevit_xs,62.930,37.070,84.830,15.170,2.32,256,0.900,bicubic,-11.704,-7.516,+12 +tv_densenet121,62.930,37.070,84.250,15.750,7.98,224,0.875,bicubic,-11.810,-7.898,+9 +resnet34,62.860,37.140,84.130,15.870,21.80,224,0.875,bilinear,-12.252,-8.154,-1 +mobilenetv2_110d,62.840,37.160,84.500,15.500,4.52,224,0.875,bicubic,-12.196,-7.692,0 +legacy_seresnet34,62.840,37.160,84.220,15.780,21.96,224,0.875,bilinear,-11.970,-7.906,+5 +hrnet_w18_small_v2,62.800,37.200,83.970,16.030,15.60,224,0.875,bilinear,-12.310,-8.446,-3 +deit_tiny_distilled_patch16_224,62.800,37.200,83.920,16.080,5.91,224,0.900,bicubic,-11.712,-7.970,+10 +swsl_resnet18,62.760,37.240,84.300,15.700,11.69,224,0.875,bilinear,-10.514,-7.436,+22 +tinynet_b,62.730,37.270,84.250,15.750,3.73,188,0.875,bicubic,-12.244,-7.932,-2 +repvgg_b0,62.730,37.270,83.880,16.120,15.82,224,0.875,bilinear,-12.424,-8.536,-10 +xcit_nano_12_p8_224,62.570,37.430,84.200,15.800,3.05,224,1.000,bicubic,-11.346,-7.968,+12 +gluon_resnet34_v1b,62.570,37.430,83.990,16.010,21.80,224,0.875,bicubic,-12.022,-7.998,+3 +tf_efficientnet_lite0,62.550,37.450,84.230,15.770,4.65,224,0.875,bicubic,-12.282,-7.944,-4 regnetx_008,62.490,37.510,84.020,15.980,7.26,224,0.875,bicubic,-12.544,-8.320,-9 -dla34,62.480,37.520,83.910,16.090,15.74,224,0.875,bilinear,-12.140,-8.162,-2 -fbnetc_100,62.470,37.530,83.380,16.620,5.57,224,0.875,bilinear,-12.660,-9.006,-15 -tf_mobilenetv3_large_100,62.460,37.540,83.970,16.030,5.48,224,0.875,bilinear,-13.058,-8.634,-25 -crossvit_9_240,62.260,37.740,84.240,15.760,8.55,240,0.875,bicubic,-11.700,-7.728,+3 -crossvit_tiny_240,62.070,37.930,83.610,16.390,7.01,240,0.875,bicubic,-11.262,-8.304,+8 -mnasnet_100,61.890,38.110,83.710,16.290,4.38,224,0.875,bicubic,-12.768,-8.402,-9 -regnety_004,61.860,38.140,83.420,16.580,4.34,224,0.875,bicubic,-12.164,-8.334,-2 -vgg19_bn,61.860,38.140,83.450,16.550,143.68,224,0.875,bilinear,-12.354,-8.398,-5 -convit_tiny,61.570,38.430,84.130,15.870,5.71,224,0.875,bicubic,-11.544,-7.584,+7 -ssl_resnet18,61.470,38.530,83.310,16.690,11.69,224,0.875,bilinear,-11.138,-8.114,+11 -regnetx_006,61.370,38.630,83.450,16.550,6.20,224,0.875,bicubic,-12.490,-8.222,-2 -spnasnet_100,61.210,38.790,82.790,17.210,4.42,224,0.875,bilinear,-12.874,-9.030,-8 -tv_resnet34,61.190,38.810,82.720,17.280,21.80,224,0.875,bilinear,-12.116,-8.704,+1 -pit_ti_224,60.960,39.040,83.860,16.140,4.85,224,0.900,bicubic,-11.952,-7.546,+6 -skresnet18,60.850,39.150,82.880,17.120,11.96,224,0.875,bicubic,-12.186,-8.288,+2 -ghostnet_100,60.830,39.170,82.360,17.640,5.18,224,0.875,bilinear,-13.144,-9.100,-10 +dla34,62.470,37.530,83.900,16.100,15.74,224,0.875,bilinear,-12.154,-8.172,-1 +fbnetc_100,62.470,37.530,83.380,16.620,5.57,224,0.875,bilinear,-12.646,-9.006,-15 +tf_mobilenetv3_large_100,62.450,37.550,83.950,16.050,5.48,224,0.875,bilinear,-13.062,-8.656,-25 +crossvit_9_240,62.270,37.730,84.240,15.760,8.55,240,0.875,bicubic,-11.690,-7.724,+4 +edgenext_x_small,62.160,37.840,84.050,15.950,2.34,256,0.900,bicubic,-12.704,-8.250,-11 +crossvit_tiny_240,62.070,37.930,83.610,16.390,7.01,240,0.875,bicubic,-11.268,-8.304,+8 +mnasnet_100,61.920,38.080,83.690,16.310,4.38,224,0.875,bicubic,-12.730,-8.424,-9 +regnety_004,61.860,38.140,83.410,16.590,4.34,224,0.875,bicubic,-12.164,-8.346,-2 +vgg19_bn,61.850,38.150,83.450,16.550,143.68,224,0.875,bilinear,-12.364,-8.394,-5 +convit_tiny,61.560,38.440,84.120,15.880,5.71,224,0.875,bicubic,-11.554,-7.600,+7 +ssl_resnet18,61.470,38.530,83.300,16.700,11.69,224,0.875,bilinear,-11.134,-8.124,+11 +regnetx_006,61.360,38.640,83.460,16.540,6.20,224,0.875,bicubic,-12.496,-8.212,-2 +spnasnet_100,61.250,38.750,82.790,17.210,4.42,224,0.875,bilinear,-12.840,-9.026,-8 +tv_resnet34,61.190,38.810,82.730,17.270,21.80,224,0.875,bilinear,-12.118,-8.694,+1 +pit_ti_224,60.970,39.030,83.860,16.140,4.85,224,0.900,bicubic,-11.942,-7.546,+6 +skresnet18,60.880,39.120,82.870,17.130,11.96,224,0.875,bicubic,-12.154,-8.296,+2 +ghostnet_100,60.830,39.170,82.370,17.630,5.18,224,0.875,bilinear,-13.150,-9.088,-10 vgg16_bn,60.760,39.240,82.950,17.050,138.37,224,0.875,bilinear,-12.590,-8.554,-5 -semnasnet_075,60.710,39.290,82.510,17.490,2.91,224,0.875,bicubic,-12.262,-8.626,0 -tf_mobilenetv3_large_075,60.390,39.610,81.950,18.050,3.99,224,0.875,bilinear,-13.046,-9.394,-8 -xcit_nano_12_p16_224_dist,60.250,39.750,82.490,17.510,3.05,224,1.000,bicubic,-12.052,-8.368,+5 -mobilenetv2_100,60.190,39.810,82.240,17.760,3.50,224,0.875,bicubic,-12.780,-8.780,-2 -resnet18d,60.180,39.820,82.310,17.690,11.71,224,0.875,bicubic,-12.070,-8.378,+4 -vit_base_patch32_224_sam,60.000,40.000,81.230,18.770,88.22,224,0.900,bicubic,-13.694,-9.780,-13 -deit_tiny_patch16_224,59.860,40.140,82.660,17.340,5.72,224,0.900,bicubic,-12.312,-8.454,+4 -legacy_seresnet18,59.810,40.190,81.690,18.310,11.78,224,0.875,bicubic,-11.932,-8.642,+7 -vgg19,59.710,40.290,81.450,18.550,143.67,224,0.875,bilinear,-12.656,-9.420,-3 -regnetx_004,59.420,40.580,81.690,18.310,5.16,224,0.875,bicubic,-12.972,-9.142,-5 -tf_mobilenetv3_large_minimal_100,59.080,40.920,81.150,18.850,3.92,224,0.875,bilinear,-13.170,-9.480,-1 -vit_tiny_r_s16_p8_224,59.070,40.930,81.760,18.240,6.34,224,0.900,bicubic,-12.722,-9.062,+2 -vgg13_bn,59.000,41.000,81.080,18.920,133.05,224,0.875,bilinear,-12.594,-9.296,+3 -hrnet_w18_small,58.970,41.030,81.350,18.650,13.19,224,0.875,bilinear,-13.368,-9.330,-7 -lcnet_100,58.860,41.140,81.190,18.810,2.95,224,0.875,bicubic,-13.244,-9.186,-3 -vgg16,58.840,41.160,81.660,18.340,138.36,224,0.875,bilinear,-12.750,-8.722,+1 -xcit_nano_12_p16_224,58.350,41.650,80.890,19.110,3.05,224,1.000,bicubic,-11.604,-8.864,+5 -gluon_resnet18_v1b,58.320,41.680,80.970,19.030,11.69,224,0.875,bicubic,-12.514,-8.792,+1 -tinynet_c,58.170,41.830,80.280,19.720,2.46,184,0.875,bicubic,-13.058,-9.470,-1 -vgg11_bn,57.410,42.590,80.020,19.980,132.87,224,0.875,bilinear,-12.950,-9.782,0 -resnet18,57.170,42.830,80.200,19.800,11.69,224,0.875,bilinear,-12.574,-8.882,+3 -mobilevit_xxs,57.150,42.850,79.730,20.270,1.27,256,0.900,bicubic,-11.770,-9.214,+4 -vgg13,57.140,42.860,79.550,20.450,133.05,224,0.875,bilinear,-12.786,-9.696,0 -regnety_002,56.990,43.010,79.860,20.140,3.16,224,0.875,bicubic,-13.264,-9.672,-3 -mixer_l16_224,56.680,43.320,75.980,24.020,208.20,224,0.875,bicubic,-15.374,-11.682,-12 -regnetx_002,56.060,43.940,79.220,20.780,2.68,224,0.875,bicubic,-12.696,-9.336,+2 -dla60x_c,56.000,44.000,78.930,21.070,1.32,224,0.875,bilinear,-11.892,-9.496,+3 -vgg11,55.800,44.200,78.840,21.160,132.86,224,0.875,bilinear,-13.228,-9.786,-3 -lcnet_075,55.420,44.580,78.300,21.700,2.36,224,0.875,bicubic,-13.396,-10.070,-2 -mobilenetv3_small_100,54.700,45.300,77.770,22.230,2.54,224,0.875,bicubic,-12.956,-9.864,+1 -tf_mobilenetv3_small_100,54.530,45.470,77.060,22.940,2.54,224,0.875,bilinear,-13.394,-10.604,-2 -tinynet_d,53.420,46.580,76.350,23.650,2.34,152,0.875,bicubic,-13.538,-10.714,0 -mnasnet_small,53.270,46.730,75.890,24.110,2.03,224,0.875,bicubic,-12.936,-10.618,0 -dla46x_c,53.050,46.950,76.870,23.130,1.07,224,0.875,bilinear,-12.920,-10.110,0 -mobilenetv2_050,52.850,47.150,75.430,24.570,1.97,224,0.875,bicubic,-13.092,-10.652,0 -tf_mobilenetv3_small_075,52.150,47.850,75.480,24.520,2.04,224,0.875,bilinear,-13.564,-10.654,0 -dla46_c,52.130,47.870,75.690,24.310,1.30,224,0.875,bilinear,-12.736,-10.604,+1 -mobilenetv3_small_075,51.920,48.080,74.730,25.270,2.04,224,0.875,bicubic,-13.322,-10.708,-1 -lcnet_050,49.990,50.010,73.460,26.540,1.88,224,0.875,bicubic,-13.110,-10.922,0 -tf_mobilenetv3_small_minimal_100,49.500,50.500,73.050,26.950,2.04,224,0.875,bilinear,-13.408,-11.184,0 -tinynet_e,46.700,53.300,70.360,29.640,2.04,106,0.875,bicubic,-13.156,-11.404,0 +semnasnet_075,60.700,39.300,82.510,17.490,2.91,224,0.875,bicubic,-12.274,-8.624,0 +tf_mobilenetv3_large_075,60.390,39.610,81.940,18.060,3.99,224,0.875,bilinear,-13.050,-9.408,-8 +xcit_nano_12_p16_224_dist,60.260,39.740,82.500,17.500,3.05,224,1.000,bicubic,-12.042,-8.362,+6 +mobilenetv2_100,60.190,39.810,82.220,17.780,3.50,224,0.875,bicubic,-12.766,-8.790,-2 +resnet18d,60.170,39.830,82.300,17.700,11.71,224,0.875,bicubic,-12.088,-8.388,+5 +vit_base_patch32_224_sam,60.010,39.990,81.240,18.760,88.22,224,0.900,bicubic,-13.682,-9.772,-13 +deit_tiny_patch16_224,59.850,40.150,82.680,17.320,5.72,224,0.900,bicubic,-12.324,-8.434,+5 +legacy_seresnet18,59.810,40.190,81.690,18.310,11.78,224,0.875,bicubic,-11.930,-8.640,+8 +vgg19,59.710,40.290,81.450,18.550,143.67,224,0.875,bilinear,-12.656,-9.422,-3 +regnetx_004,59.400,40.600,81.700,18.300,5.16,224,0.875,bicubic,-12.996,-9.138,-5 +vit_tiny_r_s16_p8_224,59.070,40.930,81.770,18.230,6.34,224,0.900,bicubic,-12.724,-9.048,+4 +tf_mobilenetv3_large_minimal_100,59.070,40.930,81.160,18.840,3.92,224,0.875,bilinear,-13.180,-9.460,-1 +vgg13_bn,59.000,41.000,81.080,18.920,133.05,224,0.875,bilinear,-12.598,-9.296,+4 +hrnet_w18_small,58.960,41.040,81.340,18.660,13.19,224,0.875,bilinear,-13.376,-9.340,-6 +lcnet_100,58.880,41.120,81.180,18.820,2.95,224,0.875,bicubic,-13.230,-9.198,-2 +vgg16,58.840,41.160,81.660,18.340,138.36,224,0.875,bilinear,-12.750,-8.722,+2 +xcit_nano_12_p16_224,58.340,41.660,80.880,19.120,3.05,224,1.000,bicubic,-11.614,-8.876,+8 +gluon_resnet18_v1b,58.330,41.670,80.970,19.030,11.69,224,0.875,bicubic,-12.508,-8.792,+3 +edgenext_xx_small,58.170,41.830,81.350,18.650,1.33,256,0.900,bicubic,-12.936,-8.682,+1 +tinynet_c,58.150,41.850,80.290,19.710,2.46,184,0.875,bicubic,-13.078,-9.458,-1 +resnet14t,57.800,42.200,79.910,20.090,10.08,224,0.950,bilinear,-14.556,-10.430,-14 +mobilevitv2_050,57.730,42.270,80.920,19.080,1.37,256,0.888,bicubic,-12.410,-9.010,+2 +vgg11_bn,57.410,42.590,80.020,19.980,132.87,224,0.875,bilinear,-12.950,-9.782,-1 +resnet18,57.170,42.830,80.200,19.800,11.69,224,0.875,bilinear,-12.578,-8.884,+3 +mobilevit_xxs,57.150,42.850,79.740,20.260,1.27,256,0.900,bicubic,-11.770,-9.206,+4 +vgg13,57.150,42.850,79.550,20.450,133.05,224,0.875,bilinear,-12.776,-9.696,0 +regnety_002,56.980,43.020,79.850,20.150,3.16,224,0.875,bicubic,-13.276,-9.684,-4 +mixer_l16_224,56.690,43.310,75.990,24.010,208.20,224,0.875,bicubic,-15.376,-11.676,-14 +regnetx_002,56.050,43.950,79.230,20.770,2.68,224,0.875,bicubic,-12.704,-9.326,+2 +dla60x_c,56.030,43.970,78.920,21.080,1.32,224,0.875,bilinear,-11.850,-9.514,+4 +vgg11,55.790,44.210,78.840,21.160,132.86,224,0.875,bilinear,-13.238,-9.788,-3 +resnet10t,55.660,44.340,78.020,21.980,5.44,224,0.950,bilinear,-12.648,-10.060,0 +lcnet_075,55.360,44.640,78.310,21.690,2.36,224,0.875,bicubic,-13.454,-10.054,-3 +mobilenetv3_small_100,54.700,45.300,77.780,22.220,2.54,224,0.875,bicubic,-12.958,-9.854,+1 +tf_mobilenetv3_small_100,54.510,45.490,77.070,22.930,2.54,224,0.875,bilinear,-13.416,-10.598,-2 +tinynet_d,53.420,46.580,76.350,23.650,2.34,152,0.875,bicubic,-13.542,-10.714,0 +mnasnet_small,53.270,46.730,75.890,24.110,2.03,224,0.875,bicubic,-12.936,-10.616,0 +dla46x_c,53.060,46.940,76.850,23.150,1.07,224,0.875,bilinear,-12.892,-10.136,0 +mobilenetv2_050,52.850,47.150,75.420,24.580,1.97,224,0.875,bicubic,-13.094,-10.660,0 +tf_mobilenetv3_small_075,52.160,47.840,75.480,24.520,2.04,224,0.875,bilinear,-13.552,-10.650,0 +dla46_c,52.120,47.880,75.680,24.320,1.30,224,0.875,bilinear,-12.752,-10.622,+1 +mobilenetv3_small_075,51.890,48.110,74.730,25.270,2.04,224,0.875,bicubic,-13.348,-10.710,-1 +lcnet_050,49.980,50.020,73.430,26.570,1.88,224,0.875,bicubic,-13.114,-10.952,0 +tf_mobilenetv3_small_minimal_100,49.490,50.510,73.030,26.970,2.04,224,0.875,bilinear,-13.410,-11.204,0 +tinynet_e,46.700,53.300,70.360,29.640,2.04,106,0.875,bicubic,-13.156,-11.406,0 mobilenetv3_small_050,44.890,55.110,67.670,32.330,1.59,224,0.875,bicubic,-13.000,-12.524,0 diff --git a/results/results-sketch.csv b/results/results-sketch.csv index 7c07cd79..b9024991 100644 --- a/results/results-sketch.csv +++ b/results/results-sketch.csv @@ -1,591 +1,669 @@ -model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation,top1_diff,top5_diff,rank_diff -ig_resnext101_32x48d,58.812,41.188,81.094,18.906,828.41,224,0.875,bilinear,-26.624,-16.482,+45 -ig_resnext101_32x32d,58.382,41.618,80.381,19.619,468.53,224,0.875,bilinear,-26.718,-17.053,+57 -ig_resnext101_32x16d,57.680,42.320,79.909,20.091,194.03,224,0.875,bilinear,-26.490,-17.289,+98 -swsl_resnext101_32x16d,57.460,42.540,80.373,19.627,194.03,224,0.875,bilinear,-25.890,-16.471,+137 -beit_large_patch16_384,56.892,43.108,79.225,20.775,305.00,384,1.000,bicubic,-31.511,-19.383,-3 -beit_large_patch16_512,56.753,43.247,78.897,21.103,305.67,512,1.000,bicubic,-31.847,-19.759,-5 -swsl_resnext101_32x8d,56.431,43.569,78.939,21.061,88.79,224,0.875,bilinear,-27.859,-18.242,+86 -beit_large_patch16_224,54.953,45.047,77.608,22.392,304.43,224,0.900,bicubic,-32.521,-20.696,-2 -ig_resnext101_32x8d,54.931,45.069,77.535,22.465,88.79,224,0.875,bilinear,-27.769,-19.095,+162 -convnext_xlarge_384_in22ft1k,53.662,46.338,75.895,24.105,350.20,384,1.000,bicubic,-33.884,-22.591,-5 -swsl_resnext101_32x4d,53.603,46.397,76.343,23.657,44.18,224,0.875,bilinear,-29.633,-20.421,+135 -vit_large_patch16_384,52.752,47.248,74.698,25.302,304.72,384,1.000,bicubic,-34.328,-23.602,-3 -convnext_xlarge_in22ft1k,52.565,47.435,74.401,25.599,350.20,224,0.875,bicubic,-34.437,-23.811,-2 -vit_large_r50_s32_384,52.041,47.959,73.562,26.438,329.09,384,1.000,bicubic,-34.141,-24.358,+11 -vit_large_patch16_224,51.836,48.164,73.690,26.310,304.33,224,0.900,bicubic,-34.002,-24.130,+19 -convnext_large_384_in22ft1k,51.738,48.262,73.894,26.106,197.77,384,1.000,bicubic,-35.658,-24.474,-9 -tf_efficientnet_l2_ns_475,51.490,48.510,73.928,26.072,480.31,475,0.936,bicubic,-36.742,-24.618,-13 -swsl_resnext50_32x4d,50.429,49.571,73.360,26.640,25.03,224,0.875,bilinear,-31.747,-22.872,+185 -convnext_base_384_in22ft1k,50.425,49.575,73.562,26.438,88.59,384,1.000,bicubic,-36.119,-24.628,-2 -swin_large_patch4_window12_384,50.404,49.596,72.564,27.436,196.74,384,1.000,bicubic,-36.746,-25.676,-12 -convnext_large_in22ft1k,49.944,50.056,72.206,27.794,197.77,224,0.875,bicubic,-36.692,-25.822,-5 -swsl_resnet50,49.529,50.471,72.326,27.674,25.56,224,0.875,bilinear,-31.645,-23.652,+232 -swin_large_patch4_window7_224,48.993,51.007,71.391,28.609,196.53,224,0.900,bicubic,-37.321,-26.501,0 -convnext_base_in22ft1k,48.791,51.209,71.943,28.057,88.59,224,0.875,bicubic,-37.033,-25.923,+11 -beit_base_patch16_384,48.665,51.335,72.086,27.914,86.74,384,1.000,bicubic,-38.133,-26.050,-11 -swin_base_patch4_window12_384,48.541,51.459,71.821,28.179,87.90,384,1.000,bicubic,-37.891,-26.235,-5 -vit_large_r50_s32_224,48.201,51.799,70.864,29.136,328.99,224,0.900,bicubic,-36.223,-26.302,+60 -tf_efficientnet_b7_ns,47.808,52.192,69.640,30.360,66.35,600,0.949,bicubic,-39.030,-28.456,-15 -tf_efficientnet_b6_ns,47.763,52.237,69.968,30.032,43.04,528,0.942,bicubic,-38.691,-27.914,-9 -tf_efficientnetv2_xl_in21ft1k,47.745,52.255,70.117,29.883,208.12,512,1.000,bicubic,-38.673,-27.749,-8 -vit_base_patch8_224,47.745,52.255,70.929,29.071,86.58,224,0.900,bicubic,-38.049,-26.865,+7 -tf_efficientnet_l2_ns,47.570,52.430,70.019,29.981,480.31,800,0.960,bicubic,-40.778,-28.629,-29 -tf_efficientnetv2_l_in21ft1k,46.938,53.062,70.310,29.690,118.52,480,1.000,bicubic,-39.367,-27.668,-9 -beit_base_patch16_224,46.244,53.756,69.897,30.103,86.53,224,0.900,bicubic,-38.984,-27.761,+21 -vit_base_patch16_384,45.904,54.096,68.561,31.439,86.86,384,1.000,bicubic,-40.106,-29.441,-4 -tf_efficientnet_b8_ap,45.768,54.232,67.912,32.087,87.41,672,0.954,bicubic,-39.604,-29.380,+15 -tf_efficientnet_b5_ns,45.615,54.385,67.842,32.158,30.39,456,0.934,bicubic,-40.475,-29.908,-10 -tf_efficientnetv2_m_in21ft1k,45.578,54.422,69.143,30.857,54.14,480,1.000,bicubic,-40.012,-28.601,+3 -swin_base_patch4_window7_224,45.550,54.450,68.514,31.486,87.77,224,0.900,bicubic,-39.698,-29.048,+14 -volo_d5_512,44.570,55.430,65.759,34.241,296.09,512,1.150,bicubic,-42.472,-32.209,-30 -cait_m48_448,44.239,55.761,64.654,35.346,356.46,448,1.000,bicubic,-42.247,-33.098,-22 -volo_d5_448,44.096,55.904,65.067,34.933,295.91,448,1.150,bicubic,-42.856,-32.873,-30 -vit_base_r50_s16_384,43.518,56.482,66.779,33.221,98.95,384,1.000,bicubic,-41.452,-30.511,+26 -tf_efficientnet_b4_ns,43.444,56.556,65.511,34.489,19.34,380,0.922,bicubic,-41.718,-31.959,+13 -volo_d5_224,43.255,56.745,64.071,35.929,295.46,224,0.960,bicubic,-42.817,-33.507,-17 -vit_base_patch16_224,43.231,56.769,65.714,34.286,86.57,224,0.900,bicubic,-41.297,-31.580,+34 -volo_d4_448,43.137,56.863,64.114,35.886,193.41,448,1.150,bicubic,-43.653,-33.768,-32 -xcit_large_24_p8_384_dist,42.828,57.172,63.405,36.595,188.93,384,1.000,bicubic,-43.170,-34.279,-16 -xcit_large_24_p8_224_dist,42.561,57.439,63.096,36.904,188.93,224,1.000,bicubic,-42.837,-34.314,+1 -tf_efficientnet_b8,42.504,57.496,64.861,35.139,87.41,672,0.954,bicubic,-42.864,-32.529,+2 -cait_m36_384,42.398,57.602,63.324,36.676,271.22,384,1.000,bicubic,-43.654,-34.406,-22 -volo_d4_224,42.284,57.716,63.006,36.994,192.96,224,0.960,bicubic,-43.590,-34.462,-19 -tf_efficientnet_b7_ap,41.433,58.567,62.876,37.124,66.35,600,0.949,bicubic,-43.687,-34.376,+5 -tf_efficientnet_b7,41.431,58.569,63.022,36.978,66.35,600,0.949,bicubic,-43.505,-34.182,+16 -tf_efficientnet_b5_ap,41.416,58.584,62.080,37.920,30.39,456,0.934,bicubic,-42.840,-34.896,+41 -resnetv2_152x4_bitm,41.304,58.696,64.303,35.697,936.53,480,1.000,bilinear,-43.612,-33.139,+16 -tf_efficientnet_b6_ap,41.099,58.901,62.357,37.643,43.04,528,0.942,bicubic,-43.687,-34.781,+18 -xcit_large_24_p16_384_dist,41.025,58.975,61.245,38.755,189.10,384,1.000,bicubic,-44.729,-36.293,-19 -xcit_large_24_p16_224_dist,40.956,59.044,61.320,38.680,189.10,224,1.000,bicubic,-43.966,-35.812,+12 -tf_efficientnetv2_s_in21ft1k,40.954,59.046,63.849,36.151,21.46,384,1.000,bicubic,-43.344,-33.405,+31 -xcit_medium_24_p8_224_dist,40.494,59.506,60.500,39.500,84.32,224,1.000,bicubic,-44.578,-36.780,+1 -tf_efficientnet_b4_ap,40.484,59.516,61.717,38.283,19.34,380,0.922,bicubic,-42.768,-34.677,+83 -vit_small_r26_s32_384,40.478,59.522,62.740,37.260,36.47,384,1.000,bicubic,-43.564,-34.588,+46 -vit_base_patch16_224_miil,40.176,59.824,60.889,39.111,86.54,224,0.875,bilinear,-44.096,-35.913,+31 -regnetz_e8,40.144,59.856,61.324,38.676,57.70,320,1.000,bicubic,-44.886,-35.940,+1 -convnext_large,40.117,59.883,60.096,39.904,197.77,224,0.875,bicubic,-44.175,-36.799,+26 -xcit_medium_24_p8_384_dist,40.036,59.964,60.453,39.547,84.32,384,1.000,bicubic,-45.778,-37.139,-30 -xcit_medium_24_p16_384_dist,39.903,60.097,60.115,39.885,84.40,384,1.000,bicubic,-45.519,-37.217,-21 -tf_efficientnetv2_l,39.828,60.172,60.807,39.193,118.52,480,1.000,bicubic,-45.662,-36.565,-25 -dm_nfnet_f3,39.816,60.184,60.610,39.390,254.92,416,0.940,bicubic,-45.706,-36.852,-27 -cait_s36_384,39.757,60.243,60.475,39.525,68.37,384,1.000,bicubic,-45.705,-37.005,-26 -volo_d3_448,39.708,60.292,59.760,40.240,86.63,448,1.000,bicubic,-46.788,-37.950,-54 -efficientnetv2_rw_m,39.671,60.329,59.683,40.317,53.24,416,1.000,bicubic,-45.141,-37.463,+1 -xception65,39.645,60.355,60.911,39.089,39.92,299,0.940,bicubic,-43.535,-35.681,+75 -ecaresnet269d,39.590,60.410,60.341,39.659,102.09,352,1.000,bicubic,-45.386,-36.885,-7 -dm_nfnet_f6,39.582,60.418,60.911,39.089,438.36,576,0.956,bicubic,-46.560,-36.819,-50 -tf_efficientnet_b3_ns,39.580,60.420,61.457,38.543,12.23,300,0.904,bicubic,-44.468,-35.451,+31 -dm_nfnet_f5,39.508,60.492,60.225,39.775,377.21,544,0.954,bicubic,-46.308,-37.261,-42 -volo_d3_224,39.492,60.508,59.868,40.132,86.33,224,0.960,bicubic,-45.920,-37.412,-30 -xcit_small_24_p8_224_dist,39.309,60.691,59.410,40.590,47.63,224,1.000,bicubic,-45.567,-37.778,-7 -xcit_medium_24_p16_224_dist,39.254,60.746,59.465,40.535,84.40,224,1.000,bicubic,-45.020,-37.475,+13 -efficientnet_b4,39.069,60.931,59.604,40.396,19.34,384,1.000,bicubic,-44.355,-36.992,+56 -xcit_small_24_p8_384_dist,38.997,61.003,59.176,40.824,47.63,384,1.000,bicubic,-46.559,-38.396,-41 -resnetv2_152x2_bit_teacher_384,38.971,61.029,62.442,37.558,236.34,384,1.000,bicubic,-44.873,-34.676,+34 -vit_base_patch32_384,38.796,61.204,60.333,39.667,88.30,384,1.000,bicubic,-44.552,-36.501,+58 -eca_nfnet_l2,38.663,61.337,59.439,40.561,56.72,384,1.000,bicubic,-46.033,-37.825,-8 -xcit_small_12_p8_384_dist,38.543,61.457,58.800,41.200,26.21,384,1.000,bicubic,-46.537,-38.480,-26 -xcit_small_24_p16_384_dist,38.498,61.502,58.384,41.616,47.67,384,1.000,bicubic,-46.596,-38.926,-28 -xcit_small_12_p8_224_dist,38.366,61.634,58.791,41.209,26.21,224,1.000,bicubic,-45.870,-38.083,+8 -tf_efficientnet_b5,38.352,61.648,59.911,40.089,30.39,456,0.934,bicubic,-45.460,-36.837,+33 -deit_base_distilled_patch16_384,38.256,61.744,57.791,42.209,87.63,384,1.000,bicubic,-47.166,-39.616,-43 -convnext_base,38.236,61.764,58.227,41.773,88.59,224,0.875,bicubic,-45.602,-38.523,+27 -dm_nfnet_f4,38.228,61.772,58.626,41.374,316.07,512,0.951,bicubic,-47.486,-38.896,-53 -xcit_large_24_p8_224,38.116,61.884,57.883,42.117,188.93,224,1.000,bicubic,-46.278,-38.773,-5 -resnetv2_152x2_bitm,37.985,62.015,61.131,38.869,236.34,448,1.000,bilinear,-46.521,-36.303,-13 -cait_s24_384,37.867,62.133,58.081,41.919,47.06,384,1.000,bicubic,-47.179,-39.265,-32 -resnet152d,37.857,62.143,58.360,41.640,60.21,320,1.000,bicubic,-45.821,-38.378,+37 -tf_efficientnetv2_m,37.822,62.178,58.710,41.290,54.14,480,1.000,bicubic,-47.216,-38.568,-33 -resnetrs420,37.751,62.249,58.209,41.791,191.89,416,1.000,bicubic,-47.259,-38.915,-32 -xcit_small_24_p16_224_dist,37.719,62.281,57.360,42.640,47.67,224,1.000,bicubic,-46.149,-39.364,+17 -resnetrs350,37.682,62.318,58.087,41.913,163.96,384,1.000,bicubic,-47.036,-38.901,-25 -pit_b_distilled_224,37.586,62.414,57.232,42.768,74.79,224,0.900,bicubic,-46.554,-39.624,+1 -xcit_small_12_p16_384_dist,37.580,62.420,57.765,42.235,26.25,384,1.000,bicubic,-47.130,-39.353,-26 -resnet200d,37.505,62.495,58.305,41.695,64.69,320,1.000,bicubic,-46.459,-38.519,+9 -resnetv2_152x2_bit_teacher,37.328,62.672,59.396,40.604,236.34,224,0.875,bicubic,-45.544,-37.174,+59 -resnest269e,37.315,62.685,57.472,42.528,110.93,416,0.928,bicubic,-47.205,-39.514,-25 -resmlp_big_24_224_in22ft1k,37.242,62.758,58.181,41.819,129.14,224,0.875,bicubic,-47.152,-38.939,-19 -vit_small_r26_s32_224,37.230,62.770,59.058,40.942,36.43,224,0.900,bicubic,-44.626,-36.962,+113 -cait_s24_224,37.155,62.845,56.733,43.267,46.92,224,1.000,bicubic,-46.303,-39.831,+28 -vit_base_patch32_224,37.079,62.921,59.290,40.710,88.22,224,0.900,bicubic,-43.643,-36.276,+170 -volo_d1_384,37.077,62.923,57.132,42.868,26.78,384,1.000,bicubic,-48.171,-40.082,-57 -tf_efficientnet_b3_ap,37.055,62.945,57.236,42.764,12.23,300,0.904,bicubic,-44.771,-38.386,+111 -convnext_small,37.051,62.949,57.103,42.897,50.22,224,0.875,bicubic,-46.099,-39.329,+37 -efficientnetv2_rw_s,37.047,62.953,56.814,43.186,23.94,384,1.000,bicubic,-46.763,-39.908,+10 -xcit_small_12_p16_224_dist,36.977,63.023,56.733,43.267,26.25,224,1.000,bicubic,-46.373,-39.681,+27 -regnetz_040h,36.961,63.039,57.278,42.722,28.94,320,1.000,bicubic,-47.535,-39.728,-33 -volo_d1_224,36.878,63.122,56.639,43.361,26.63,224,0.960,bicubic,-47.284,-40.137,-15 -seresnet152d,36.788,63.212,56.721,43.279,66.84,320,1.000,bicubic,-47.572,-40.319,-28 -volo_d2_224,36.605,63.395,56.462,43.538,58.68,224,0.960,bicubic,-48.589,-40.726,-63 -xception65p,36.556,63.444,56.421,43.579,39.82,299,0.940,bicubic,-46.570,-40.057,+34 -regnetz_d32,36.442,63.558,57.372,42.628,27.58,320,0.950,bicubic,-47.580,-39.494,-11 -cait_xs24_384,36.420,63.580,56.940,43.060,26.67,384,1.000,bicubic,-47.642,-39.950,-17 -efficientnet_b3,36.419,63.581,56.845,43.155,12.23,320,1.000,bicubic,-45.821,-39.269,+76 -volo_d2_384,36.414,63.586,56.315,43.685,58.87,384,1.000,bicubic,-49.626,-41.257,-94 -deit_base_distilled_patch16_224,36.399,63.601,56.619,43.381,87.34,224,0.900,bicubic,-46.993,-39.867,+14 -resnetv2_101x3_bitm,36.385,63.615,59.064,40.936,387.93,448,1.000,bilinear,-48.057,-38.318,-42 -resnetrs270,36.324,63.676,56.568,43.432,129.86,352,1.000,bicubic,-48.112,-40.402,-41 -tresnet_m,36.283,63.717,55.790,44.210,31.39,224,0.875,bilinear,-46.787,-40.330,+29 -mixer_b16_224_miil,36.261,63.739,55.963,44.037,59.88,224,0.875,bilinear,-46.047,-39.755,+65 -tf_efficientnet_b2_ns,36.187,63.813,57.549,42.451,9.11,260,0.890,bicubic,-46.193,-38.699,+58 -resnet152,36.084,63.916,55.544,44.456,60.19,224,0.950,bicubic,-46.736,-40.586,+35 -regnetz_040,36.053,63.947,55.751,44.249,27.12,320,1.000,bicubic,-48.181,-41.181,-34 -ecaresnet101d,36.014,63.986,56.157,43.843,44.57,224,0.875,bicubic,-46.158,-39.889,+71 -dm_nfnet_f2,36.008,63.992,55.458,44.542,193.78,352,0.920,bicubic,-49.054,-41.782,-71 -resnest200e,35.933,64.067,55.847,44.153,70.20,320,0.909,bicubic,-47.895,-41.045,-13 -swsl_resnet18,35.864,64.136,58.459,41.541,11.69,224,0.875,bilinear,-37.412,-33.277,+410 -eca_nfnet_l1,35.819,64.181,55.951,44.049,41.41,320,1.000,bicubic,-48.193,-41.077,-25 -xcit_small_24_p8_224,35.554,64.446,54.792,45.208,47.63,224,1.000,bicubic,-48.284,-41.844,-18 -xcit_large_24_p16_224,35.524,64.476,54.762,45.238,189.10,224,1.000,bicubic,-47.370,-41.120,+23 -xcit_small_12_p8_224,35.522,64.478,55.503,44.497,26.21,224,1.000,bicubic,-47.822,-40.977,+4 -vit_small_patch16_384,35.473,64.527,57.541,42.459,22.20,384,1.000,bicubic,-48.331,-39.561,-16 -xcit_medium_24_p8_224,35.450,64.550,54.827,45.173,84.32,224,1.000,bicubic,-48.286,-41.567,-14 -resnest101e,35.375,64.625,55.786,44.214,48.28,256,0.875,bilinear,-47.515,-40.532,+20 -convit_base,35.310,64.690,54.929,45.071,86.54,224,0.875,bicubic,-46.976,-41.009,+53 -convnext_tiny_hnf,35.279,64.721,53.852,46.148,28.59,224,0.950,bicubic,-46.943,-42.014,+55 -xcit_tiny_24_p8_224_dist,35.247,64.753,55.254,44.746,12.11,224,1.000,bicubic,-47.317,-40.916,+33 -twins_svt_large,35.092,64.908,54.721,45.279,99.27,224,0.900,bicubic,-48.588,-41.873,-14 -repvgg_b3,35.051,64.949,54.558,45.442,123.09,224,0.875,bilinear,-45.445,-40.706,+140 -repvgg_b3g4,35.041,64.959,54.770,45.230,83.83,224,0.875,bilinear,-45.171,-40.336,+164 -regnetz_d8,34.994,65.006,55.945,44.055,23.37,320,1.000,bicubic,-49.058,-41.049,-43 -dm_nfnet_f1,34.984,65.016,54.116,45.884,132.63,320,0.910,bicubic,-49.640,-42.984,-72 -xcit_tiny_24_p8_384_dist,34.923,65.077,55.151,44.849,12.11,384,1.000,bicubic,-48.819,-41.559,-25 -regnetz_d8_evos,34.896,65.104,55.246,44.754,23.46,320,0.950,bicubic,-49.158,-41.750,-47 -resnet101d,34.874,65.126,54.198,45.802,44.57,320,1.000,bicubic,-48.148,-42.250,+7 -swin_s3_base_224,34.793,65.207,53.695,46.305,71.13,224,0.900,bicubic,-49.139,-42.965,-41 -seresnext101_32x8d,34.791,65.209,53.450,46.550,93.57,288,1.000,bicubic,-49.413,-43.426,-57 -resmlp_big_24_distilled_224,34.785,65.215,54.639,45.361,129.14,224,0.875,bicubic,-48.802,-42.009,-22 -vit_large_patch32_384,34.673,65.326,55.729,44.271,306.63,384,1.000,bicubic,-46.833,-40.365,+78 -resnet101,34.666,65.334,54.299,45.701,44.55,224,0.950,bicubic,-47.266,-41.471,+60 -dm_nfnet_f0,34.620,65.380,54.664,45.336,71.49,256,0.900,bicubic,-48.766,-41.910,-20 -ssl_resnext101_32x16d,34.609,65.391,55.931,44.069,194.03,224,0.875,bilinear,-47.245,-40.165,+61 -resnetv2_101,34.587,65.413,53.143,46.857,44.54,224,0.950,bicubic,-47.455,-42.721,+50 -repvgg_b2g4,34.579,65.421,54.776,45.224,61.76,224,0.875,bilinear,-44.791,-39.912,+195 -resnetrs200,34.510,65.490,54.291,45.709,93.21,320,1.000,bicubic,-49.928,-42.789,-79 -resnest50d_4s2x40d,34.359,65.641,54.731,45.269,30.42,224,0.875,bicubic,-46.751,-40.833,+93 -resnetrs152,34.355,65.645,53.568,46.432,86.62,320,1.000,bicubic,-49.359,-43.178,-36 -crossvit_18_dagger_408,34.253,65.747,53.090,46.910,44.61,408,1.000,bicubic,-49.941,-43.728,-67 -xcit_medium_24_p16_224,34.239,65.761,53.167,46.833,84.40,224,1.000,bicubic,-48.399,-42.807,+4 -tf_efficientnet_b1_ns,34.163,65.837,55.489,44.511,7.79,240,0.882,bicubic,-47.225,-40.247,+74 -efficientnetv2_rw_t,34.153,65.847,53.129,46.871,13.65,288,1.000,bicubic,-48.191,-43.067,+21 -twins_pcpvt_large,34.108,65.892,54.126,45.874,60.99,224,0.900,bicubic,-49.026,-42.478,-18 -tf_efficientnet_b4,34.060,65.940,54.196,45.804,19.34,380,0.922,bicubic,-48.964,-42.104,-12 -ssl_resnext101_32x8d,34.029,65.971,55.601,44.399,88.79,224,0.875,bilinear,-47.579,-40.441,+57 -tf_efficientnet_b6,34.003,65.997,54.540,45.460,43.04,528,0.942,bicubic,-50.107,-42.348,-70 -nfnet_l0,33.999,66.001,54.359,45.641,35.07,288,1.000,bicubic,-48.752,-42.159,-7 -xcit_small_24_p16_224,33.998,66.002,53.288,46.712,47.67,224,1.000,bicubic,-48.582,-42.718,-1 -efficientnet_b3_pruned,33.998,66.002,54.104,45.896,9.86,300,0.904,bicubic,-46.861,-41.140,+99 -regnety_160,33.972,66.028,53.542,46.458,83.59,288,1.000,bicubic,-49.718,-43.234,-46 -gc_efficientnetv2_rw_t,33.950,66.050,53.222,46.778,13.68,288,1.000,bicubic,-48.516,-43.074,+4 -pit_s_distilled_224,33.935,66.065,53.267,46.733,24.04,224,0.900,bicubic,-48.059,-42.531,+34 -convnext_tiny,33.836,66.164,53.654,46.346,28.59,224,0.875,bicubic,-48.228,-42.198,+27 -resnext101_64x4d,33.825,66.175,52.174,47.826,83.46,288,1.000,bicubic,-49.315,-44.196,-31 -xcit_small_12_p16_224,33.770,66.230,53.237,46.763,26.25,224,1.000,bicubic,-48.206,-42.581,+33 -swin_s3_small_224,33.695,66.305,52.391,47.609,49.74,224,0.900,bicubic,-50.073,-44.061,-58 -resnetv2_50x3_bitm,33.663,66.337,55.880,44.120,217.32,448,1.000,bilinear,-50.350,-41.244,-74 -resnet51q,33.561,66.439,53.019,46.981,35.70,288,1.000,bilinear,-48.801,-43.161,+3 -xcit_tiny_24_p16_384_dist,33.508,66.492,52.766,47.234,12.12,384,1.000,bicubic,-49.064,-43.522,-9 -regnety_080,33.469,66.531,52.943,47.057,39.18,288,1.000,bicubic,-50.457,-43.945,-73 -convmixer_1536_20,33.424,66.576,53.031,46.969,51.63,224,0.960,bicubic,-47.942,-42.583,+56 -regnety_032,33.412,66.588,52.766,47.234,19.44,288,1.000,bicubic,-49.314,-43.658,-21 -crossvit_18_240,33.400,66.600,52.241,47.759,43.27,240,0.875,bicubic,-48.998,-43.817,-5 -gernet_l,33.357,66.643,51.911,48.089,31.08,256,0.875,bilinear,-47.987,-43.621,+54 -crossvit_15_dagger_408,33.325,66.674,52.184,47.816,28.50,408,1.000,bicubic,-50.511,-44.600,-72 -crossvit_18_dagger_240,33.282,66.718,52.202,47.798,44.27,240,0.875,bicubic,-49.238,-43.868,-13 -tresnet_xl,33.259,66.741,52.292,47.708,78.44,224,0.875,bilinear,-48.799,-43.644,+15 -jx_nest_base,33.212,66.788,51.813,48.187,67.72,224,0.875,bicubic,-50.344,-44.549,-60 -resnest50d_1s4x24d,33.153,66.847,52.850,47.150,25.68,224,0.875,bicubic,-47.837,-42.474,+69 -resnet61q,33.109,66.891,51.758,48.242,36.85,288,1.000,bicubic,-49.417,-44.376,-18 -jx_nest_small,33.046,66.954,51.064,48.936,38.35,224,0.875,bicubic,-50.072,-45.266,-44 -crossvit_base_240,33.037,66.963,51.380,48.620,105.03,240,0.875,bicubic,-49.179,-44.454,+1 -twins_pcpvt_base,33.027,66.973,52.489,47.511,43.83,224,0.900,bicubic,-49.681,-43.861,-31 -xcit_tiny_24_p16_224_dist,32.989,67.011,52.056,47.944,12.12,224,1.000,bicubic,-47.457,-43.160,+92 -rexnet_200,32.986,67.014,52.935,47.065,16.37,224,0.875,bicubic,-48.644,-42.733,+26 -resnest50d,32.980,67.020,52.713,47.287,27.48,224,0.875,bilinear,-48.002,-42.667,+63 -convit_small,32.915,67.085,52.119,47.881,27.78,224,0.875,bicubic,-48.505,-43.621,+34 -crossvit_15_dagger_240,32.905,67.095,51.783,48.217,28.21,240,0.875,bicubic,-49.425,-44.175,-13 -tf_efficientnetv2_s,32.903,67.097,51.724,48.276,21.46,384,1.000,bicubic,-50.983,-44.972,-91 -vit_small_patch16_224,32.871,67.129,53.927,46.073,22.05,224,0.900,bicubic,-48.525,-42.205,+34 -tf_efficientnet_b3,32.862,67.138,52.955,47.045,12.23,300,0.904,bicubic,-48.774,-42.764,+19 -pnasnet5large,32.850,67.150,50.500,49.500,86.06,331,0.911,bicubic,-49.940,-45.540,-43 -twins_svt_base,32.832,67.168,51.567,48.433,56.07,224,0.900,bicubic,-50.306,-44.853,-59 -regnetz_c16,32.826,67.174,53.748,46.252,13.46,320,0.940,bicubic,-49.690,-42.612,-31 -regnetv_064,32.826,67.174,52.856,47.144,30.58,288,1.000,bicubic,-50.888,-43.758,-81 -nasnetalarge,32.773,67.227,50.141,49.859,88.75,331,0.911,bicubic,-49.853,-45.906,-40 -gernet_m,32.756,67.244,51.919,48.081,21.14,224,0.875,bilinear,-47.988,-43.265,+64 -inception_resnet_v2,32.738,67.262,50.650,49.350,55.84,299,0.897,bicubic,-47.722,-44.659,+76 -gluon_resnet152_v1d,32.734,67.266,51.084,48.916,60.21,224,0.875,bicubic,-47.742,-44.120,+73 -pit_b_224,32.724,67.276,49.854,50.146,73.76,224,0.900,bicubic,-49.722,-45.856,-33 -tf_efficientnet_b2_ap,32.685,67.315,52.237,47.763,9.11,260,0.890,bicubic,-47.617,-42.979,+86 -fbnetv3_g,32.630,67.370,52.894,47.106,16.62,288,0.950,bilinear,-49.416,-43.170,-9 -tresnet_l,32.561,67.439,51.135,48.865,55.99,224,0.875,bilinear,-48.931,-44.489,+16 -cait_xxs36_384,32.541,67.459,52.233,47.767,17.37,384,1.000,bicubic,-49.653,-43.911,-20 -regnetz_c16_evos,32.532,67.468,52.919,47.081,13.49,320,0.950,bicubic,-50.100,-43.557,-50 -wide_resnet50_2,32.435,67.565,51.455,48.545,68.88,224,0.875,bicubic,-49.017,-44.075,+14 -gmlp_s16_224,32.418,67.582,51.817,48.183,19.42,224,0.875,bicubic,-47.222,-42.807,+122 -ens_adv_inception_resnet_v2,32.376,67.624,50.419,49.581,55.84,299,0.897,bicubic,-47.602,-44.519,+100 -deit_base_patch16_224,32.361,67.639,50.997,49.003,86.57,224,0.900,bicubic,-49.635,-44.735,-14 -swin_small_patch4_window7_224,32.347,67.653,50.913,49.087,49.61,224,0.900,bicubic,-50.869,-45.411,-81 -gluon_resnet152_v1s,32.339,67.661,50.533,49.467,60.32,224,0.875,bicubic,-48.677,-44.879,+36 -deit_small_distilled_patch16_224,32.282,67.718,52.111,47.889,22.44,224,0.900,bicubic,-48.926,-43.262,+22 -xcit_tiny_24_p8_224,32.266,67.734,51.897,48.103,12.11,224,1.000,bicubic,-49.626,-44.079,-11 -gluon_seresnext101_64x4d,32.194,67.806,50.307,49.693,88.23,224,0.875,bicubic,-48.684,-44.991,+42 -coat_lite_small,32.125,67.875,49.934,50.066,19.84,224,0.900,bicubic,-50.179,-45.914,-38 -gluon_seresnext101_32x4d,32.107,67.893,51.233,48.767,48.96,224,0.875,bicubic,-48.799,-44.061,+39 -deit_base_patch16_384,31.985,68.015,50.549,49.451,86.86,384,1.000,bicubic,-51.121,-45.819,-79 -seresnext50_32x4d,31.970,68.030,51.225,48.775,27.56,224,0.875,bicubic,-49.288,-44.405,+14 -xcit_tiny_12_p8_224_dist,31.944,68.056,51.406,48.594,6.71,224,1.000,bicubic,-49.264,-44.194,+16 -levit_384,31.873,68.127,50.598,49.402,39.13,224,0.900,bicubic,-50.715,-45.424,-63 -resnetrs101,31.856,68.144,51.017,48.983,63.62,288,0.940,bicubic,-50.432,-44.993,-43 -cspresnext50,31.814,68.186,51.618,48.382,20.57,224,0.875,bilinear,-48.236,-43.328,+84 -poolformer_m48,31.702,68.298,49.885,50.115,73.47,224,0.950,bicubic,-50.760,-46.073,-57 -tnt_s_patch16_224,31.634,68.366,51.147,48.853,23.76,224,0.900,bicubic,-49.886,-44.597,-8 -eca_nfnet_l0,31.610,68.390,51.610,48.390,24.14,288,1.000,bicubic,-50.966,-44.880,-66 -resnetv2_50x1_bit_distilled,31.582,68.418,51.272,48.728,25.55,224,0.875,bicubic,-51.240,-45.256,-79 -xception41p,31.516,68.484,50.370,49.630,26.91,299,0.940,bicubic,-50.444,-45.424,-27 -regnety_064,31.474,68.526,50.528,49.472,30.58,288,1.000,bicubic,-52.246,-46.194,-117 -poolformer_m36,31.449,68.551,50.032,49.968,56.17,224,0.950,bicubic,-50.663,-45.658,-41 -ssl_resnext101_32x4d,31.423,68.577,52.127,47.873,44.18,224,0.875,bilinear,-49.501,-43.599,+24 -inception_v4,31.378,68.622,49.246,50.754,42.68,299,0.875,bicubic,-48.784,-45.720,+68 -rexnet_150,31.370,68.630,51.286,48.714,9.73,224,0.875,bicubic,-48.940,-43.880,+54 -crossvit_15_240,31.339,68.661,50.170,49.830,27.53,240,0.875,bicubic,-50.203,-45.520,-19 -pit_s_224,31.335,68.665,49.665,50.335,23.46,224,0.900,bicubic,-49.765,-45.665,+8 -crossvit_small_240,31.278,68.722,50.196,49.804,26.86,240,0.875,bicubic,-49.740,-45.261,+11 -cspresnet50,31.268,68.732,51.221,48.779,21.62,256,0.887,bilinear,-48.314,-43.483,+95 -cait_xxs36_224,31.266,68.734,50.614,49.386,17.30,224,1.000,bicubic,-48.482,-44.252,+84 -convmixer_768_32,31.250,68.750,50.950,49.050,21.11,224,0.960,bicubic,-48.914,-44.122,+60 -swin_s3_tiny_224,31.241,68.760,49.714,50.286,28.33,224,0.900,bicubic,-50.886,-46.236,-52 -regnetv_040,31.217,68.783,50.113,49.887,20.64,288,1.000,bicubic,-51.983,-46.549,-110 -coat_mini,31.207,68.793,49.775,50.225,10.34,224,0.900,bicubic,-50.059,-45.619,-10 -xcit_tiny_12_p8_384_dist,31.186,68.814,50.528,49.472,6.71,384,1.000,bicubic,-51.209,-45.692,-73 -ecaresnetlight,31.125,68.875,50.243,49.757,30.16,224,0.875,bicubic,-49.327,-45.007,+32 -gluon_resnet101_v1s,31.113,68.887,49.793,50.207,44.67,224,0.875,bicubic,-49.185,-45.371,+45 -tf_efficientnet_cc_b0_8e,31.087,68.913,50.761,49.239,24.01,224,0.875,bicubic,-46.819,-42.895,+176 -resmlp_36_distilled_224,31.072,68.928,49.688,50.312,44.69,224,0.875,bicubic,-50.082,-45.800,-8 -ecaresnet50d,31.060,68.940,50.854,49.146,25.58,224,0.875,bicubic,-49.540,-44.466,+20 -ecaresnet50t,31.060,68.940,50.573,49.427,25.57,320,0.950,bicubic,-51.288,-45.565,-76 -resnet50d,31.020,68.980,49.806,50.194,25.58,224,0.875,bicubic,-49.502,-45.356,+20 -cspdarknet53,31.018,68.981,50.396,49.604,27.64,256,0.887,bilinear,-49.043,-44.688,+54 -gcresnet50t,31.009,68.991,50.121,49.879,25.90,256,0.900,bicubic,-49.933,-45.333,+2 -gluon_resnet152_v1c,30.997,69.003,48.924,51.076,60.21,224,0.875,bicubic,-48.911,-45.924,+59 -gluon_resnext101_64x4d,30.995,69.005,48.555,51.445,83.46,224,0.875,bicubic,-49.609,-46.437,+13 -twins_svt_small,30.975,69.025,49.223,50.777,24.06,224,0.900,bicubic,-50.705,-46.447,-46 -resnext50_32x4d,30.930,69.070,49.258,50.742,25.03,224,0.950,bicubic,-50.178,-46.068,-14 -resmlp_24_distilled_224,30.903,69.097,50.176,49.824,30.02,224,0.875,bicubic,-49.861,-45.048,+4 -ecaresnet101d_pruned,30.897,69.103,50.013,49.987,24.88,224,0.875,bicubic,-49.917,-45.617,+1 -tf_efficientnet_cc_b1_8e,30.897,69.103,50.078,49.922,39.72,240,0.882,bicubic,-48.409,-44.294,+87 -gluon_resnext101_32x4d,30.875,69.125,48.545,51.455,44.18,224,0.875,bicubic,-49.469,-46.381,+23 -tf_efficientnetv2_b3,30.861,69.139,49.814,50.186,14.36,300,0.904,bicubic,-51.105,-45.966,-61 -tf_efficientnet_lite4,30.830,69.170,50.390,49.610,13.01,380,0.920,bilinear,-50.706,-45.278,-46 -nf_resnet50,30.708,69.292,49.958,50.042,25.56,288,0.940,bicubic,-49.946,-45.376,+2 -dpn107,30.678,69.322,48.808,51.192,86.92,224,0.875,bicubic,-49.493,-46.098,+34 -xcit_tiny_24_p16_224,30.677,69.323,50.408,49.592,12.12,224,1.000,bicubic,-48.767,-44.476,+74 -poolformer_s36,30.669,69.331,49.435,50.565,30.86,224,0.900,bicubic,-50.749,-46.015,-42 -ese_vovnet39b,30.665,69.335,49.877,50.123,24.57,224,0.875,bicubic,-48.647,-44.837,+77 -tresnet_xl_448,30.616,69.384,49.072,50.928,78.44,448,0.875,bilinear,-52.438,-47.100,-127 -gluon_resnet152_v1b,30.610,69.390,48.519,51.481,60.19,224,0.875,bicubic,-49.070,-46.219,+58 -haloregnetz_b,30.604,69.396,49.005,50.995,11.68,224,0.940,bicubic,-50.446,-46.191,-25 -ssl_resnext50_32x4d,30.596,69.404,50.661,49.339,25.03,224,0.875,bilinear,-49.720,-44.749,+14 -dpn68b,30.525,69.475,49.164,50.836,12.61,224,0.875,bicubic,-48.695,-45.254,+84 -gluon_resnet101_v1d,30.521,69.479,47.951,52.049,44.57,224,0.875,bicubic,-49.899,-47.123,+6 -resnest26d,30.484,69.516,50.671,49.329,17.07,224,0.875,bilinear,-47.992,-43.621,+116 -efficientnet_b2,30.437,69.563,49.688,50.312,9.11,288,1.000,bicubic,-50.177,-45.628,-9 -tf_efficientnet_b1_ap,30.419,69.581,49.549,50.451,7.79,240,0.882,bicubic,-48.861,-44.755,+75 -xcit_tiny_12_p16_384_dist,30.403,69.597,50.123,49.877,6.72,384,1.000,bicubic,-50.541,-45.289,-24 -twins_pcpvt_small,30.384,69.616,49.392,50.608,24.11,224,0.900,bicubic,-50.706,-46.248,-34 -resnetv2_50,30.378,69.622,48.834,51.166,25.55,224,0.950,bicubic,-50.042,-46.182,-1 -visformer_small,30.331,69.669,48.291,51.709,40.22,224,0.900,bicubic,-51.775,-47.583,-90 -pit_xs_distilled_224,30.280,69.720,49.836,50.164,11.00,224,0.900,bicubic,-49.026,-44.528,+64 -regnety_040,30.254,69.746,48.918,51.082,20.65,288,1.000,bicubic,-52.782,-47.588,-140 -convmixer_1024_20_ks9_p14,30.097,69.903,49.934,50.066,24.38,224,0.960,bicubic,-46.845,-43.422,+178 -seresnet50,30.073,69.927,49.282,50.718,28.09,224,0.875,bicubic,-50.191,-45.790,+7 -dpn98,30.064,69.936,48.244,51.756,61.57,224,0.875,bicubic,-49.582,-46.352,+44 -tf_efficientnet_b2,30.026,69.974,49.582,50.418,9.11,260,0.890,bicubic,-50.054,-45.326,+18 -efficientnet_el,30.024,69.976,48.834,51.166,10.59,300,0.904,bicubic,-51.286,-46.696,-57 -dpn131,30.018,69.982,48.126,51.874,79.25,224,0.875,bicubic,-49.806,-46.582,+31 -legacy_senet154,30.005,69.996,48.040,51.960,115.09,224,0.875,bilinear,-51.306,-47.456,-58 -xcit_tiny_12_p16_224_dist,29.997,70.003,49.649,50.351,6.72,224,1.000,bicubic,-48.579,-44.547,+94 -halo2botnet50ts_256,29.981,70.019,48.376,51.624,22.64,256,0.950,bicubic,-52.079,-47.266,-99 -dpn92,29.953,70.047,49.174,50.826,37.67,224,0.875,bicubic,-50.063,-45.650,+16 -resnetv2_101x1_bitm,29.895,70.106,51.125,48.875,44.54,448,1.000,bilinear,-52.441,-45.391,-118 -gluon_senet154,29.879,70.121,47.892,52.108,115.09,224,0.875,bicubic,-51.353,-47.456,-60 -xception,29.857,70.143,48.676,51.324,22.86,299,0.897,bicubic,-49.193,-45.715,+72 -adv_inception_v3,29.816,70.184,47.843,52.157,23.83,299,0.875,bicubic,-47.766,-45.893,+141 -gluon_xception65,29.779,70.222,47.757,52.243,39.92,299,0.903,bicubic,-49.937,-47.103,+26 -fbnetv3_d,29.743,70.257,49.476,50.524,10.31,256,0.950,bilinear,-49.939,-45.472,+28 -lamhalobotnet50ts_256,29.741,70.259,48.339,51.661,22.57,256,0.950,bicubic,-51.805,-47.163,-85 -resmlp_36_224,29.694,70.306,48.971,51.029,44.69,224,0.875,bicubic,-50.074,-45.915,+21 -resnet50,29.639,70.361,46.743,53.257,25.56,224,0.950,bicubic,-50.737,-48.383,-21 -resnetblur50,29.611,70.388,48.252,51.748,25.56,224,0.875,bicubic,-49.693,-46.382,+45 -resnetv2_50d_gn,29.610,70.391,47.790,52.210,25.57,288,0.950,bicubic,-52.209,-48.132,-96 -jx_nest_tiny,29.545,70.455,46.990,53.010,17.06,224,0.875,bicubic,-51.875,-48.627,-81 -resnet50_gn,29.537,70.463,48.303,51.697,25.56,224,0.940,bicubic,-50.517,-46.645,+1 -efficientnet_em,29.478,70.522,48.938,51.062,6.90,240,0.882,bicubic,-49.772,-45.856,+48 -resnext101_32x8d,29.439,70.561,48.488,51.512,88.79,224,0.875,bilinear,-49.877,-46.030,+36 -coat_lite_mini,29.431,70.569,47.727,52.273,11.01,224,0.900,bicubic,-49.665,-46.877,+55 -gcresnext50ts,29.427,70.573,47.900,52.100,15.67,256,0.900,bicubic,-51.151,-47.270,-40 -sebotnet33ts_256,29.425,70.575,47.156,52.844,13.70,256,0.940,bicubic,-51.731,-48.014,-72 -deit_small_patch16_224,29.423,70.577,48.240,51.760,22.05,224,0.900,bicubic,-50.437,-46.806,+4 -ssl_resnet50,29.415,70.585,49.803,50.197,25.56,224,0.875,bilinear,-49.811,-45.033,+43 -cait_xxs24_384,29.391,70.609,48.757,51.243,12.03,384,1.000,bicubic,-51.575,-46.889,-62 -nf_regnet_b1,29.391,70.609,49.427,50.573,10.22,288,0.900,bicubic,-49.897,-45.321,+36 -resnet34d,29.332,70.668,48.415,51.585,21.82,224,0.875,bicubic,-47.782,-44.965,+139 -swin_tiny_patch4_window7_224,29.331,70.669,47.608,52.392,28.29,224,0.900,bicubic,-52.043,-47.936,-89 -cait_xxs24_224,29.303,70.697,48.527,51.473,11.96,224,1.000,bicubic,-49.081,-45.783,+81 -ecaresnet50d_pruned,29.216,70.784,48.439,51.561,19.94,224,0.875,bicubic,-50.492,-46.441,+6 -poolformer_s24,29.163,70.837,48.063,51.937,21.39,224,0.900,bicubic,-51.150,-46.983,-33 -tresnet_l_448,29.162,70.838,47.222,52.778,55.99,448,0.875,bilinear,-53.106,-48.760,-139 -gluon_inception_v3,29.124,70.876,46.957,53.043,23.83,299,0.875,bicubic,-49.680,-47.413,+55 -eca_resnet33ts,29.099,70.901,48.791,51.209,19.68,256,0.900,bicubic,-50.981,-46.179,-20 -lambda_resnet50ts,29.093,70.907,46.977,53.023,21.54,256,0.950,bicubic,-52.053,-48.125,-83 -xception71,29.036,70.964,47.405,52.595,42.34,299,0.903,bicubic,-50.840,-47.517,-10 -hrnet_w64,28.989,71.011,47.138,52.862,128.06,224,0.875,bilinear,-50.483,-47.514,+11 -xcit_tiny_12_p8_224,28.959,71.041,47.517,52.483,6.71,224,1.000,bicubic,-50.731,-47.537,-1 -regnetz_b16,28.943,71.057,47.248,52.752,9.72,288,0.940,bicubic,-51.771,-48.230,-63 -tf_efficientnet_b0_ns,28.900,71.100,49.003,50.997,5.29,224,0.875,bicubic,-49.758,-45.375,+54 -tf_efficientnet_b1,28.886,71.114,47.503,52.497,7.79,240,0.882,bicubic,-49.942,-46.695,+46 -gluon_resnet101_v1b,28.877,71.123,46.379,53.621,44.55,224,0.875,bicubic,-50.425,-48.141,+18 -vit_small_patch32_384,28.877,71.123,48.889,51.111,22.92,384,1.000,bicubic,-51.607,-46.711,-59 -resnetv2_50d_evos,28.869,71.131,46.672,53.328,25.59,288,0.950,bicubic,-53.111,-49.238,-134 -skresnext50_32x4d,28.823,71.177,46.493,53.507,27.48,224,0.875,bicubic,-51.329,-48.151,-32 -sehalonet33ts,28.776,71.224,46.580,53.420,13.69,256,0.940,bicubic,-52.188,-48.692,-82 -levit_256,28.747,71.253,46.717,53.283,18.89,224,0.900,bicubic,-52.759,-48.775,-117 -tf_efficientnet_lite3,28.662,71.338,47.348,52.652,8.20,300,0.904,bilinear,-51.158,-47.564,-16 -skresnet34,28.654,71.346,47.947,52.053,22.28,224,0.875,bicubic,-48.249,-45.372,+127 -gluon_seresnext50_32x4d,28.651,71.349,46.440,53.560,27.56,224,0.875,bicubic,-51.263,-48.392,-27 -hrnet_w40,28.639,71.361,47.458,52.542,57.56,224,0.875,bilinear,-50.277,-47.016,+33 -halonet50ts,28.578,71.422,46.179,53.821,22.73,256,0.940,bicubic,-53.082,-49.433,-130 -tf_efficientnetv2_b0,28.574,71.426,47.077,52.923,7.14,224,0.875,bicubic,-49.786,-46.943,+59 -tv_resnet152,28.531,71.469,47.114,52.886,60.19,224,0.875,bilinear,-49.785,-46.920,+59 -xcit_tiny_12_p16_224,28.523,71.477,47.405,52.595,6.72,224,1.000,bicubic,-48.603,-46.311,+110 -repvgg_b2,28.430,71.570,47.040,52.960,89.02,224,0.875,bilinear,-50.362,-47.378,+34 -hrnet_w48,28.413,71.587,47.576,52.424,77.47,224,0.875,bilinear,-50.889,-46.936,+4 -gluon_resnext50_32x4d,28.383,71.617,45.316,54.684,25.03,224,0.875,bicubic,-50.981,-49.110,-4 -efficientnet_b2_pruned,28.360,71.640,47.051,52.949,8.31,260,0.890,bicubic,-51.556,-47.803,-37 -tf_efficientnet_b0_ap,28.352,71.648,47.531,52.469,5.29,224,0.875,bicubic,-48.742,-45.725,+108 -seresnet33ts,28.346,71.654,47.751,52.249,19.78,256,0.900,bicubic,-52.004,-47.355,-67 -dla102x2,28.317,71.683,46.763,53.237,41.28,224,0.875,bilinear,-51.129,-47.869,-12 -dla169,28.317,71.683,47.389,52.611,53.39,224,0.875,bilinear,-50.375,-46.951,+30 -tf_efficientnet_cc_b0_4e,28.313,71.687,47.368,52.632,13.31,224,0.875,bicubic,-48.989,-45.966,+95 -mixnet_xl,28.289,71.711,46.698,53.302,11.90,224,0.875,bicubic,-52.185,-48.236,-79 -gluon_resnet50_v1d,28.248,71.752,45.876,54.124,25.58,224,0.875,bicubic,-50.828,-48.596,+10 -wide_resnet101_2,28.106,71.894,46.409,53.591,126.89,224,0.875,bilinear,-50.748,-47.881,+19 -gluon_resnet101_v1c,28.104,71.896,45.961,54.039,44.57,224,0.875,bicubic,-51.430,-48.619,-23 -regnetx_320,28.087,71.913,45.126,54.874,107.81,224,0.875,bicubic,-52.153,-49.896,-63 -densenet161,28.085,71.915,46.641,53.359,28.68,224,0.875,bicubic,-49.269,-46.995,+88 -regnety_320,28.061,71.939,45.452,54.548,145.05,224,0.875,bicubic,-52.749,-49.792,-99 -gernet_s,28.034,71.966,46.735,53.265,8.17,224,0.875,bilinear,-48.874,-46.397,+103 -levit_192,28.032,71.968,45.882,54.118,10.95,224,0.900,bicubic,-51.800,-48.904,-43 -efficientnet_el_pruned,28.018,71.982,46.790,53.210,10.59,300,0.904,bicubic,-52.284,-48.238,-73 -xception41,27.886,72.114,45.886,54.114,26.97,299,0.903,bicubic,-50.624,-48.392,+24 -regnetx_160,27.823,72.177,45.625,54.375,54.28,224,0.875,bicubic,-52.027,-49.205,-48 -tf_inception_v3,27.778,72.222,45.717,54.283,23.83,299,0.875,bicubic,-50.078,-47.923,+61 -res2net101_26w_4s,27.772,72.228,45.167,54.833,45.21,224,0.875,bilinear,-51.424,-49.269,-7 -tf_efficientnetv2_b1,27.756,72.243,46.578,53.422,8.14,240,0.882,bicubic,-51.707,-48.146,-30 -vit_base_patch16_224_sam,27.713,72.287,45.108,54.892,86.57,224,0.900,bicubic,-52.529,-49.646,-75 -fbnetv3_b,27.670,72.330,46.983,53.017,8.60,256,0.950,bilinear,-51.478,-47.763,-9 -repvgg_b1,27.652,72.348,46.521,53.479,57.42,224,0.875,bilinear,-50.716,-47.575,+29 -hrnet_w44,27.617,72.383,45.837,54.163,67.06,224,0.875,bilinear,-51.283,-48.537,+2 -gcresnet33ts,27.587,72.412,46.197,53.803,19.88,256,0.900,bicubic,-52.492,-48.803,-69 -inception_v3,27.556,72.444,45.271,54.729,23.83,299,0.875,bicubic,-49.882,-48.203,+70 -resmlp_24_224,27.523,72.477,45.700,54.300,30.02,224,0.875,bicubic,-51.859,-48.847,-34 -pit_xs_224,27.493,72.507,45.906,54.094,10.62,224,0.900,bicubic,-50.693,-48.258,+33 -regnetx_080,27.393,72.607,45.006,54.994,39.57,224,0.875,bicubic,-51.809,-49.548,-18 -hrnet_w30,27.387,72.613,46.542,53.458,37.71,224,0.875,bilinear,-50.811,-47.682,+30 -hrnet_w32,27.363,72.636,45.982,54.018,41.23,224,0.875,bilinear,-51.084,-48.212,+14 -gluon_resnet50_v1s,27.322,72.678,45.226,54.774,25.68,224,0.875,bicubic,-51.390,-49.014,+1 -res2net50_26w_8s,27.312,72.688,44.835,55.165,48.40,224,0.875,bilinear,-51.668,-49.459,-11 -densenet201,27.265,72.735,46.218,53.782,20.01,224,0.875,bicubic,-50.025,-47.260,+68 -densenetblur121d,27.232,72.768,46.293,53.707,8.00,224,0.875,bicubic,-49.352,-46.899,+92 -efficientnet_b1_pruned,27.181,72.819,45.864,54.136,6.33,240,0.882,bicubic,-51.059,-47.970,+23 -tf_efficientnetv2_b2,27.161,72.839,44.572,55.428,10.10,260,0.890,bicubic,-53.045,-50.471,-87 -resnet33ts,27.128,72.872,45.330,54.670,19.68,256,0.900,bicubic,-52.082,-49.242,-28 -rexnet_130,27.102,72.898,45.933,54.067,7.56,224,0.875,bicubic,-52.398,-48.751,-52 -resnetrs50,27.100,72.900,45.025,54.975,35.69,224,0.910,bicubic,-52.786,-49.941,-74 -dla102x,27.057,72.943,45.479,54.521,26.31,224,0.875,bilinear,-51.459,-48.747,-2 -resnet32ts,27.047,72.953,45.271,54.729,17.96,256,0.900,bicubic,-51.965,-49.087,-21 -gmixer_24_224,27.033,72.967,44.369,55.631,24.72,224,0.875,bicubic,-51.003,-49.301,+24 -tv_resnet101,26.959,73.041,45.226,54.774,44.55,224,0.875,bilinear,-50.419,-48.316,+54 -regnetx_120,26.870,73.130,44.676,55.324,46.11,224,0.875,bicubic,-52.722,-50.058,-61 -resnext50d_32x4d,26.864,73.136,44.448,55.552,25.05,224,0.875,bicubic,-52.806,-50.416,-65 -rexnet_100,26.837,73.163,45.365,54.635,4.80,224,0.875,bicubic,-51.021,-48.505,+31 -densenet169,26.829,73.171,45.379,54.621,14.15,224,0.875,bicubic,-49.069,-47.651,+92 -legacy_seresnext101_32x4d,26.817,73.183,43.502,56.498,48.96,224,0.875,bilinear,-53.407,-51.508,-101 -tinynet_a,26.805,73.195,45.104,54.896,6.19,192,0.875,bicubic,-50.845,-48.432,+35 -regnetx_064,26.790,73.210,44.921,55.079,26.21,224,0.875,bicubic,-52.276,-49.537,-32 -regnety_120,26.786,73.214,44.442,55.558,51.82,224,0.875,bicubic,-53.590,-50.174,-118 -regnetx_032,26.705,73.295,45.238,54.762,15.30,224,0.875,bicubic,-51.467,-48.850,+9 -densenet121,26.674,73.326,45.890,54.110,7.98,224,0.875,bicubic,-48.910,-46.762,+90 -legacy_seresnet152,26.670,73.330,43.949,56.051,66.82,224,0.875,bilinear,-51.982,-50.421,-19 -efficientnet_es,26.609,73.391,45.114,54.886,5.44,224,0.875,bicubic,-51.447,-48.822,+10 -res2net50_26w_6s,26.593,73.407,43.996,56.004,37.05,224,0.875,bilinear,-51.973,-50.138,-19 -repvgg_b1g4,26.579,73.421,45.088,54.912,39.97,224,0.875,bilinear,-51.007,-48.742,+31 -dla60x,26.558,73.442,45.025,54.975,17.35,224,0.875,bilinear,-51.686,-48.993,-1 -coat_lite_tiny,26.507,73.493,44.644,55.356,5.72,224,0.900,bicubic,-51.007,-49.272,+33 -tf_efficientnet_b0,26.487,73.513,45.650,54.350,5.29,224,0.875,bicubic,-50.357,-47.578,+56 -mobilenetv3_large_100_miil,26.487,73.513,44.479,55.521,5.48,224,0.875,bilinear,-51.429,-48.427,+13 -res2net50_14w_8s,26.475,73.525,44.375,55.625,25.06,224,0.875,bilinear,-51.669,-49.473,0 -gluon_resnet50_v1b,26.436,73.564,44.039,55.961,25.56,224,0.875,bicubic,-51.144,-49.683,+27 -tf_efficientnet_el,26.353,73.647,44.178,55.822,10.59,300,0.904,bicubic,-53.897,-50.944,-120 -lambda_resnet26t,26.338,73.662,44.414,55.586,10.96,256,0.940,bicubic,-52.760,-50.174,-51 -levit_128,26.328,73.672,44.120,55.880,9.21,224,0.900,bicubic,-52.164,-49.886,-26 -resmlp_big_24_224,26.316,73.684,43.557,56.443,129.14,224,0.875,bicubic,-54.716,-51.462,-169 -resmlp_12_distilled_224,26.314,73.686,44.870,55.130,15.35,224,0.875,bicubic,-51.628,-48.688,+4 -regnetx_040,26.235,73.764,44.440,55.560,22.12,224,0.875,bicubic,-52.246,-49.804,-28 -crossvit_9_dagger_240,26.175,73.825,44.540,55.460,8.78,240,0.875,bicubic,-50.807,-49.070,+41 -vit_small_patch32_224,26.163,73.837,45.112,54.888,22.88,224,0.900,bicubic,-49.823,-48.158,+65 -dpn68,26.133,73.867,44.230,55.770,12.61,224,0.875,bicubic,-50.173,-48.744,+61 -efficientnet_b1,26.057,73.943,44.078,55.922,7.79,256,1.000,bicubic,-52.739,-50.264,-44 -lambda_resnet26rpt_256,26.015,73.985,44.184,55.816,10.99,256,0.940,bicubic,-52.953,-50.244,-51 -hrnet_w18,25.982,74.018,44.811,55.189,21.30,224,0.875,bilinear,-50.772,-48.629,+45 -hardcorenas_f,25.951,74.049,44.222,55.778,8.20,224,0.875,bilinear,-52.147,-49.580,-12 -resnet34,25.890,74.110,43.986,56.014,21.80,224,0.875,bilinear,-49.224,-48.298,+78 -res2net50_26w_4s,25.862,74.138,43.155,56.845,25.70,224,0.875,bilinear,-52.098,-50.697,-7 -tresnet_m_448,25.860,74.140,42.874,57.126,31.39,448,0.875,bilinear,-55.844,-52.698,-219 -resnet26t,25.858,74.142,43.951,56.049,16.01,256,0.940,bicubic,-52.004,-49.893,-5 -coat_tiny,25.850,74.150,43.276,56.724,5.50,224,0.900,bicubic,-52.580,-50.764,-34 -hardcorenas_c,25.821,74.179,44.766,55.234,5.52,224,0.875,bilinear,-51.229,-48.392,+27 -gluon_resnet50_v1c,25.782,74.218,43.023,56.977,25.58,224,0.875,bicubic,-52.230,-50.967,-15 -halonet26t,25.772,74.228,43.224,56.776,12.48,256,0.950,bicubic,-53.344,-51.087,-71 -selecsls60,25.730,74.269,44.066,55.934,30.67,224,0.875,bicubic,-52.245,-49.679,-15 -hardcorenas_e,25.666,74.334,43.410,56.590,8.07,224,0.875,bilinear,-52.128,-50.286,-4 -dla60_res2net,25.654,74.346,43.595,56.405,20.85,224,0.875,bilinear,-52.808,-50.611,-44 -dla60_res2next,25.636,74.364,43.666,56.334,17.03,224,0.875,bilinear,-52.804,-50.484,-43 -poolformer_s12,25.634,74.366,44.137,55.863,11.92,224,0.900,bicubic,-51.602,-49.367,+14 -ecaresnet26t,25.534,74.466,43.666,56.334,16.01,320,0.950,bicubic,-54.314,-51.420,-121 -resmlp_12_224,25.520,74.480,44.340,55.660,15.35,224,0.875,bicubic,-51.136,-48.840,+31 -mixnet_l,25.514,74.486,43.461,56.539,7.33,224,0.875,bicubic,-53.462,-50.717,-70 -tf_efficientnet_lite1,25.506,74.493,43.579,56.421,5.42,240,0.882,bicubic,-51.133,-49.641,+30 -eca_halonext26ts,25.467,74.533,43.196,56.804,10.76,256,0.940,bicubic,-54.023,-51.402,-107 -bat_resnext26ts,25.465,74.535,43.204,56.796,10.73,256,0.900,bicubic,-52.785,-50.894,-39 -tv_resnext50_32x4d,25.453,74.547,42.781,57.219,25.03,224,0.875,bilinear,-52.163,-50.919,-10 -botnet26t_256,25.448,74.552,42.636,57.364,12.49,256,0.950,bicubic,-53.804,-51.892,-92 -repvgg_a2,25.436,74.564,43.947,56.053,28.21,224,0.875,bilinear,-51.022,-49.063,+32 -tf_mixnet_l,25.422,74.578,42.534,57.466,7.33,224,0.875,bicubic,-53.352,-51.462,-68 -hardcorenas_b,25.402,74.598,44.188,55.812,5.18,224,0.875,bilinear,-51.134,-48.566,+27 -res2next50,25.391,74.609,42.504,57.496,24.67,224,0.875,bilinear,-52.861,-51.382,-46 -selecsls60b,25.337,74.662,43.563,56.437,32.77,224,0.875,bicubic,-53.075,-50.611,-54 -legacy_seresnet101,25.332,74.668,42.823,57.177,49.33,224,0.875,bilinear,-53.056,-51.441,-54 -dla102,25.316,74.684,43.825,56.175,33.27,224,0.875,bilinear,-52.714,-50.123,-37 -resnetv2_50x1_bitm,25.314,74.686,45.356,54.644,25.55,448,1.000,bilinear,-55.028,-50.324,-169 -hardcorenas_d,25.310,74.690,43.121,56.879,7.50,224,0.875,bilinear,-52.120,-50.361,-10 -resnest14d,25.277,74.723,44.096,55.904,10.61,224,0.875,bilinear,-50.227,-48.424,+38 -legacy_seresnext50_32x4d,25.210,74.790,41.938,58.062,27.56,224,0.875,bilinear,-53.858,-52.496,-91 -mixer_b16_224,25.121,74.879,41.219,58.781,59.88,224,0.875,bicubic,-51.491,-51.009,+15 -res2net50_48w_2s,25.033,74.967,42.198,57.802,25.29,224,0.875,bilinear,-52.487,-51.354,-19 -efficientnet_b0,25.013,74.987,42.791,57.209,5.29,224,0.875,bicubic,-52.677,-50.739,-28 -gluon_resnet34_v1b,24.937,75.063,42.239,57.761,21.80,224,0.875,bicubic,-49.651,-49.749,+54 -mobilenetv2_120d,24.937,75.063,43.060,56.940,5.83,224,0.875,bicubic,-52.357,-50.436,-13 -dla60,24.933,75.067,43.304,56.696,22.04,224,0.875,bilinear,-52.097,-50.016,-4 -eca_botnext26ts_256,24.862,75.138,42.960,57.040,10.59,256,0.950,bicubic,-54.412,-51.656,-111 -regnety_016,24.823,75.177,42.618,57.382,11.20,224,0.875,bicubic,-53.037,-51.104,-40 -xcit_nano_12_p8_224_dist,24.805,75.195,43.072,56.928,3.05,224,1.000,bicubic,-51.515,-50.016,+14 -seresnext26ts,24.689,75.311,43.108,56.892,10.39,256,0.900,bicubic,-53.163,-50.683,-39 -eca_resnext26ts,24.662,75.338,42.846,57.154,10.30,256,0.900,bicubic,-52.792,-50.720,-25 -tf_efficientnet_lite2,24.532,75.468,42.280,57.720,6.09,260,0.890,bicubic,-52.936,-51.476,-27 -skresnet18,24.489,75.511,42.542,57.458,11.96,224,0.875,bicubic,-48.547,-48.626,+62 -regnetx_016,24.477,75.523,42.506,57.494,9.19,224,0.875,bicubic,-52.473,-50.916,-10 -pit_ti_distilled_224,24.404,75.596,42.732,57.268,5.10,224,0.900,bicubic,-50.128,-49.364,+44 -tf_efficientnet_lite0,24.381,75.620,42.490,57.510,4.65,224,0.875,bicubic,-50.451,-49.684,+36 -hardcorenas_a,24.361,75.639,43.284,56.716,5.26,224,0.875,bilinear,-51.559,-49.236,+13 -tv_resnet50,24.082,75.918,41.312,58.688,25.56,224,0.875,bilinear,-52.052,-51.556,+8 -levit_128s,24.060,75.940,41.003,58.997,7.78,224,0.900,bicubic,-52.460,-51.869,+2 -legacy_seresnet34,24.027,75.973,41.903,58.097,21.96,224,0.875,bilinear,-50.781,-50.223,+33 -xcit_nano_12_p16_384_dist,24.003,75.997,42.320,57.680,3.05,384,1.000,bicubic,-51.453,-50.370,+19 -xcit_nano_12_p8_384_dist,23.960,76.040,41.938,58.062,3.05,384,1.000,bicubic,-53.858,-52.106,-49 -gcresnext26ts,23.948,76.052,41.355,58.645,10.48,256,0.900,bicubic,-53.872,-52.475,-51 -resnet18d,23.930,76.070,42.300,57.700,11.71,224,0.875,bicubic,-48.320,-48.388,+60 -efficientnet_lite0,23.909,76.091,42.088,57.912,4.65,224,0.875,bicubic,-51.567,-50.424,+13 -resnext26ts,23.866,76.134,41.105,58.895,10.30,256,0.900,bicubic,-52.914,-52.023,-15 -tv_densenet121,23.850,76.150,41.921,58.079,7.98,224,0.875,bicubic,-50.894,-50.231,+27 -efficientnet_es_pruned,23.830,76.170,41.999,58.001,5.44,224,0.875,bicubic,-51.166,-50.441,+22 -mobilenetv2_140,23.718,76.282,41.478,58.522,6.11,224,0.875,bicubic,-52.804,-51.517,-9 -mixnet_m,23.710,76.290,41.142,58.858,5.01,224,0.875,bicubic,-53.554,-52.282,-36 -dla34,23.671,76.329,41.547,58.453,15.74,224,0.875,bilinear,-50.949,-50.525,+26 -legacy_seresnet50,23.655,76.345,40.091,59.909,28.09,224,0.875,bilinear,-53.975,-53.659,-55 -ese_vovnet19b_dw,23.534,76.466,41.286,58.714,6.54,224,0.875,bicubic,-53.268,-51.986,-23 -tf_mixnet_m,23.483,76.517,40.989,59.011,5.01,224,0.875,bicubic,-53.459,-52.165,-28 -tv_resnet34,23.469,76.531,41.364,58.636,21.80,224,0.875,bilinear,-49.837,-50.060,+37 -selecsls42b,23.366,76.633,40.677,59.323,32.46,224,0.875,bicubic,-53.808,-52.715,-40 -tf_efficientnet_em,23.363,76.637,40.402,59.598,6.90,240,0.882,bicubic,-54.769,-53.642,-82 -repvgg_b0,23.319,76.681,41.180,58.820,15.82,224,0.875,bilinear,-51.841,-51.238,+6 -xcit_nano_12_p16_224_dist,23.259,76.742,41.363,58.637,3.05,224,1.000,bicubic,-49.044,-49.495,+44 -mobilenetv2_110d,23.068,76.932,40.720,59.280,4.52,224,0.875,bicubic,-51.970,-51.464,+8 -vit_base_patch32_224_sam,23.048,76.952,39.572,60.428,88.22,224,0.900,bicubic,-50.646,-51.438,+27 -tinynet_b,23.015,76.985,40.970,59.030,3.73,188,0.875,bicubic,-51.961,-51.214,+9 -deit_tiny_distilled_patch16_224,22.722,77.278,40.773,59.227,5.91,224,0.900,bicubic,-51.790,-51.113,+17 -mobilenetv3_large_100,22.655,77.345,40.777,59.223,5.48,224,0.875,bicubic,-53.111,-51.767,-12 -mobilenetv3_rw,22.634,77.366,40.372,59.628,5.48,224,0.875,bicubic,-52.998,-52.336,-11 -tf_mobilenetv3_large_100,22.561,77.439,39.763,60.237,5.48,224,0.875,bilinear,-52.957,-52.841,-10 -mobilevit_s,22.480,77.520,38.641,61.359,5.58,256,0.900,bicubic,-55.832,-55.511,-101 -tf_efficientnet_es,22.413,77.587,39.091,60.909,5.44,224,0.875,bicubic,-54.183,-54.113,-31 -xcit_nano_12_p8_224,22.406,77.594,40.653,59.347,3.05,224,1.000,bicubic,-51.504,-51.515,+17 -hrnet_w18_small_v2,22.341,77.659,39.877,60.123,15.60,224,0.875,bilinear,-52.777,-52.539,-4 -convit_tiny,22.280,77.720,39.669,60.331,5.71,224,0.875,bicubic,-50.834,-52.045,+23 -regnety_008,22.117,77.883,38.895,61.105,6.26,224,0.875,bicubic,-54.193,-54.175,-28 -seresnext26t_32x4d,21.987,78.013,38.486,61.514,16.81,224,0.875,bicubic,-55.989,-55.344,-92 -regnety_006,21.983,78.017,38.955,61.045,6.06,224,0.875,bicubic,-53.267,-53.579,-11 -vit_tiny_r_s16_p8_384,21.958,78.042,39.411,60.589,6.36,384,1.000,bicubic,-53.996,-53.853,-26 +model,top1,top1_err,top5,top5_err,param_count,img_size,crop_pct,interpolation,top1_diff,top5_diff,rank_diff +ig_resnext101_32x48d,58.820,41.180,81.094,18.906,828.41,224,0.875,bilinear,-26.616,-16.482,+56 +ig_resnext101_32x32d,58.382,41.618,80.383,19.617,468.53,224,0.875,bilinear,-26.718,-17.051,+69 +ig_resnext101_32x16d,57.686,42.314,79.909,20.091,194.03,224,0.875,bilinear,-26.484,-17.289,+119 +swsl_resnext101_32x16d,57.464,42.536,80.373,19.627,194.03,224,0.875,bilinear,-25.886,-16.471,+167 +beit_large_patch16_384,56.892,43.108,79.227,20.773,305.00,384,1.000,bicubic,-31.514,-19.379,-3 +beit_large_patch16_512,56.753,43.247,78.897,21.103,305.67,512,1.000,bicubic,-31.849,-19.759,-5 +swsl_resnext101_32x8d,56.431,43.569,78.939,21.061,88.79,224,0.875,bilinear,-27.859,-18.243,+105 +deit3_huge_patch14_224_in21ft1k,55.763,44.237,77.622,22.378,632.13,224,1.000,bicubic,-31.417,-20.638,+2 +beit_large_patch16_224,54.955,45.045,77.606,22.394,304.43,224,0.900,bicubic,-32.521,-20.698,-2 +ig_resnext101_32x8d,54.931,45.069,77.535,22.465,88.79,224,0.875,bilinear,-27.767,-19.097,+198 +deit3_large_patch16_384_in21ft1k,54.878,45.122,77.370,22.630,304.76,384,1.000,bicubic,-32.838,-21.142,-6 +deit3_large_patch16_224_in21ft1k,54.361,45.639,76.563,23.437,304.37,224,1.000,bicubic,-32.621,-21.675,+4 +convnext_xlarge_384_in22ft1k,53.658,46.342,75.895,24.105,350.20,384,1.000,bicubic,-33.886,-22.591,-7 +swsl_resnext101_32x4d,53.601,46.399,76.353,23.648,44.18,224,0.875,bilinear,-29.639,-20.407,+161 +vit_large_patch16_384,52.756,47.244,74.696,25.304,304.72,384,1.000,bicubic,-34.324,-23.604,-2 +convnext_xlarge_in22ft1k,52.565,47.435,74.403,25.597,350.20,224,0.875,bicubic,-34.437,-23.809,-1 +swinv2_large_window12to24_192to384_22kft1k,52.298,47.702,74.411,25.589,196.74,384,1.000,bicubic,-35.158,-23.841,-9 +vit_large_r50_s32_384,52.041,47.959,73.566,26.434,329.09,384,1.000,bicubic,-34.139,-24.354,+15 +vit_large_patch16_224,51.831,48.169,73.692,26.308,304.33,224,0.900,bicubic,-34.013,-24.130,+23 +convnext_large_384_in22ft1k,51.738,48.262,73.896,26.104,197.77,384,1.000,bicubic,-35.658,-24.470,-11 +tf_efficientnet_l2_ns_475,51.489,48.511,73.928,26.072,480.31,475,0.936,bicubic,-36.743,-24.618,-17 +swinv2_base_window12to24_192to384_22kft1k,50.978,49.022,73.311,26.689,87.92,384,1.000,bicubic,-36.130,-24.925,-10 +swinv2_large_window12to16_192to256_22kft1k,50.441,49.559,72.760,27.240,196.74,256,0.900,bicubic,-36.505,-25.350,-5 +swsl_resnext50_32x4d,50.437,49.563,73.356,26.644,25.03,224,0.875,bilinear,-31.739,-22.876,+227 +convnext_base_384_in22ft1k,50.429,49.571,73.562,26.438,88.59,384,1.000,bicubic,-36.113,-24.628,-1 +swin_large_patch4_window12_384,50.402,49.598,72.568,27.432,196.74,384,1.000,bicubic,-36.750,-25.672,-15 +convnext_large_in22ft1k,49.940,50.060,72.206,27.794,197.77,224,0.875,bicubic,-36.696,-25.822,-4 +swsl_resnet50,49.527,50.473,72.324,27.676,25.56,224,0.875,bilinear,-31.653,-23.656,+284 +swin_large_patch4_window7_224,48.991,51.009,71.389,28.611,196.53,224,0.900,bicubic,-37.329,-26.503,+1 +convnext_base_in22ft1k,48.794,51.206,71.941,28.059,88.59,224,0.875,bicubic,-37.030,-25.925,+13 +swinv2_base_window12to16_192to256_22kft1k,48.788,51.212,71.385,28.615,87.92,256,0.900,bicubic,-37.482,-26.511,+1 +beit_base_patch16_384,48.663,51.337,72.084,27.916,86.74,384,1.000,bicubic,-38.135,-26.052,-12 +swin_base_patch4_window12_384,48.543,51.457,71.823,28.177,87.90,384,1.000,bicubic,-37.889,-26.233,-5 +vit_large_r50_s32_224,48.209,51.791,70.872,29.128,328.99,224,0.900,bicubic,-36.221,-26.294,+71 +tf_efficientnet_b7_ns,47.792,52.208,69.626,30.374,66.35,600,0.949,bicubic,-39.040,-28.470,-16 +tf_efficientnet_b6_ns,47.757,52.243,69.966,30.034,43.04,528,0.942,bicubic,-38.693,-27.920,-9 +tf_efficientnetv2_xl_in21ft1k,47.747,52.253,70.119,29.881,208.12,512,1.000,bicubic,-38.673,-27.749,-8 +vit_base_patch8_224,47.741,52.259,70.931,29.069,86.58,224,0.900,bicubic,-38.049,-26.861,+9 +deit3_base_patch16_384_in21ft1k,47.663,52.337,69.750,30.250,86.88,384,1.000,bicubic,-39.079,-28.362,-17 +tf_efficientnet_l2_ns,47.572,52.428,70.021,29.979,480.31,800,0.960,bicubic,-40.778,-28.629,-37 +deit3_base_patch16_224_in21ft1k,47.370,52.630,69.772,30.229,86.59,224,1.000,bicubic,-38.346,-27.972,+9 +tf_efficientnetv2_l_in21ft1k,46.943,53.057,70.308,29.692,118.52,480,1.000,bicubic,-39.361,-27.672,-11 +beit_base_patch16_224,46.242,53.758,69.901,30.099,86.53,224,0.900,bicubic,-38.986,-27.755,+23 +vit_base_patch16_384,45.902,54.098,68.553,31.447,86.86,384,1.000,bicubic,-40.104,-29.451,-5 +convnext_small_384_in22ft1k,45.792,54.208,68.494,31.506,50.22,384,1.000,bicubic,-39.932,-29.370,+4 +tf_efficientnet_b8_ap,45.768,54.232,67.907,32.093,87.41,672,0.954,bicubic,-39.604,-29.387,+16 +tf_efficientnet_b5_ns,45.607,54.393,67.842,32.158,30.39,456,0.934,bicubic,-40.481,-29.910,-12 +tf_efficientnetv2_m_in21ft1k,45.574,54.426,69.135,30.865,54.14,480,1.000,bicubic,-40.012,-28.611,+4 +swin_base_patch4_window7_224,45.564,54.436,68.504,31.496,87.77,224,0.900,bicubic,-39.686,-29.058,+15 +volo_d5_512,44.572,55.428,65.753,34.247,296.09,512,1.150,bicubic,-42.468,-32.215,-36 +cait_m48_448,44.245,55.755,64.653,35.347,356.46,448,1.000,bicubic,-42.243,-33.097,-25 +deit3_large_patch16_384,44.175,55.825,64.853,35.147,304.76,384,1.000,bicubic,-41.631,-32.743,-6 +volo_d5_448,44.098,55.902,65.063,34.937,295.91,448,1.150,bicubic,-42.856,-32.877,-36 +deit3_huge_patch14_224,43.795,56.205,64.348,35.652,632.13,224,0.900,bicubic,-41.411,-33.010,+13 +convnext_small_in22ft1k,43.607,56.393,66.582,33.418,50.22,224,0.875,bicubic,-40.961,-30.814,+42 +deit3_large_patch16_224,43.520,56.480,63.572,36.428,304.37,224,0.900,bicubic,-41.242,-33.466,+34 +vit_base_r50_s16_384,43.518,56.482,66.783,33.217,98.95,384,1.000,bicubic,-41.458,-30.507,+24 +tf_efficientnet_b4_ns,43.446,56.554,65.515,34.485,19.34,380,0.922,bicubic,-41.714,-31.955,+11 +volo_d5_224,43.259,56.741,64.077,35.923,295.46,224,0.960,bicubic,-42.811,-33.501,-23 +vit_base_patch16_224,43.229,56.771,65.710,34.290,86.57,224,0.900,bicubic,-41.301,-31.586,+38 +volo_d4_448,43.139,56.861,64.114,35.886,193.41,448,1.150,bicubic,-43.653,-33.768,-40 +xcit_large_24_p8_384_dist,42.828,57.172,63.403,36.597,188.93,384,1.000,bicubic,-43.170,-34.281,-22 +xcit_large_24_p8_224_dist,42.563,57.437,63.100,36.900,188.93,224,1.000,bicubic,-42.835,-34.310,-2 +tf_efficientnet_b8,42.502,57.498,64.867,35.133,87.41,672,0.954,bicubic,-42.866,-32.525,-1 +cait_m36_384,42.400,57.600,63.326,36.674,271.22,384,1.000,bicubic,-43.654,-34.404,-28 +volo_d4_224,42.284,57.716,63.010,36.990,192.96,224,0.960,bicubic,-43.592,-34.458,-25 +deit3_small_patch16_384_in21ft1k,41.956,58.044,64.550,35.450,22.21,384,1.000,bicubic,-42.868,-32.934,+20 +tf_efficientnet_b7_ap,41.431,58.569,62.870,37.130,66.35,600,0.949,bicubic,-43.689,-34.382,+2 +tf_efficientnet_b7,41.425,58.575,63.020,36.980,66.35,600,0.949,bicubic,-43.509,-34.186,+14 +tf_efficientnet_b5_ap,41.416,58.584,62.084,37.916,30.39,456,0.934,bicubic,-42.838,-34.894,+46 +resnetv2_152x4_bitm,41.308,58.692,64.305,35.695,936.53,480,1.000,bilinear,-43.610,-33.137,+14 +tf_efficientnet_b6_ap,41.099,58.901,62.355,37.645,43.04,528,0.942,bicubic,-43.687,-34.783,+17 +xcit_large_24_p16_384_dist,41.034,58.966,61.241,38.759,189.10,384,1.000,bicubic,-44.718,-36.297,-25 +xcit_large_24_p16_224_dist,40.956,59.044,61.320,38.680,189.10,224,1.000,bicubic,-43.964,-35.812,+10 +tf_efficientnetv2_s_in21ft1k,40.952,59.048,63.851,36.149,21.46,384,1.000,bicubic,-43.344,-33.403,+35 +xcit_medium_24_p8_224_dist,40.494,59.506,60.502,39.498,84.32,224,1.000,bicubic,-44.576,-36.778,-1 +vit_small_r26_s32_384,40.482,59.518,62.740,37.260,36.47,384,1.000,bicubic,-43.566,-34.588,+53 +tf_efficientnet_b4_ap,40.482,59.518,61.721,38.279,19.34,380,0.922,bicubic,-42.766,-34.671,+96 +deit3_base_patch16_224,40.374,59.626,60.186,39.814,86.59,224,0.900,bicubic,-43.418,-36.398,+70 +vit_base_patch16_224_miil,40.170,59.830,60.889,39.111,86.54,224,0.875,bilinear,-44.102,-35.913,+34 +deit3_small_patch16_224_in21ft1k,40.160,59.840,61.866,38.134,22.06,224,1.000,bicubic,-42.916,-34.910,+106 +regnetz_e8,40.146,59.854,61.322,38.678,57.70,320,1.000,bicubic,-44.884,-35.942,-3 +convnext_large,40.119,59.881,60.092,39.908,197.77,224,0.875,bicubic,-44.177,-36.802,+28 +xcit_medium_24_p8_384_dist,40.040,59.960,60.455,39.545,84.32,384,1.000,bicubic,-45.776,-37.137,-40 +xcit_medium_24_p16_384_dist,39.903,60.097,60.115,39.885,84.40,384,1.000,bicubic,-45.519,-37.291,-27 +tf_efficientnetv2_l,39.826,60.174,60.807,39.193,118.52,480,1.000,bicubic,-45.662,-36.565,-31 +dm_nfnet_f3,39.816,60.184,60.610,39.390,254.92,416,0.940,bicubic,-45.706,-36.852,-33 +cait_s36_384,39.755,60.245,60.475,39.525,68.37,384,1.000,bicubic,-45.705,-37.003,-32 +volo_d3_448,39.712,60.288,59.760,40.240,86.63,448,1.000,bicubic,-46.784,-37.950,-64 +efficientnetv2_rw_m,39.673,60.327,59.687,40.313,53.24,416,1.000,bicubic,-45.139,-37.459,-2 +xception65,39.645,60.355,60.907,39.093,39.92,299,0.940,bicubic,-43.529,-35.685,+87 +tf_efficientnet_b3_ns,39.590,60.410,61.451,38.549,12.23,300,0.904,bicubic,-44.458,-35.461,+39 +ecaresnet269d,39.584,60.416,60.343,39.657,102.09,352,1.000,bicubic,-45.390,-36.883,-11 +dm_nfnet_f6,39.578,60.422,60.911,39.089,438.36,576,0.956,bicubic,-46.564,-36.819,-60 +dm_nfnet_f5,39.504,60.496,60.227,39.773,377.21,544,0.954,bicubic,-46.312,-37.259,-50 +volo_d3_224,39.490,60.510,59.871,40.129,86.33,224,0.960,bicubic,-45.922,-37.409,-36 +deit3_base_patch16_384,39.405,60.595,58.946,41.054,86.88,384,1.000,bicubic,-45.671,-38.308,-23 +xcit_small_24_p8_224_dist,39.309,60.691,59.414,40.586,47.63,224,1.000,bicubic,-45.567,-37.774,-12 +xcit_medium_24_p16_224_dist,39.262,60.738,59.463,40.537,84.40,224,1.000,bicubic,-45.016,-37.477,+14 +efficientnet_b4,39.075,60.925,59.606,40.394,19.34,384,1.000,bicubic,-44.349,-36.992,+65 +xcit_small_24_p8_384_dist,38.999,61.001,59.174,40.826,47.63,384,1.000,bicubic,-46.555,-38.398,-48 +resnetv2_152x2_bit_teacher_384,38.977,61.023,62.436,37.564,236.34,384,1.000,bicubic,-44.867,-34.680,+39 +convnext_tiny_384_in22ft1k,38.922,61.078,60.728,39.272,28.59,384,1.000,bicubic,-45.154,-36.430,+23 +vit_base_patch32_384,38.798,61.202,60.327,39.673,88.30,384,1.000,bicubic,-44.554,-36.509,+66 +eca_nfnet_l2,38.661,61.339,59.441,40.559,56.72,384,1.000,bicubic,-46.035,-37.823,-12 +xcit_small_12_p8_384_dist,38.545,61.455,58.803,41.197,26.21,384,1.000,bicubic,-46.535,-38.477,-33 +xcit_small_24_p16_384_dist,38.503,61.497,58.390,41.610,47.67,384,1.000,bicubic,-46.585,-38.918,-35 +convnext_tiny_in22ft1k,38.470,61.530,60.481,39.519,28.59,224,0.875,bicubic,-44.442,-36.143,+86 +xcit_small_12_p8_224_dist,38.370,61.630,58.799,41.201,26.21,224,1.000,bicubic,-45.860,-38.075,+9 +tf_efficientnet_b5,38.358,61.642,59.917,40.083,30.39,456,0.934,bicubic,-45.456,-36.831,+36 +deit_base_distilled_patch16_384,38.256,61.744,57.788,42.212,87.63,384,1.000,bicubic,-47.166,-39.544,-52 +dm_nfnet_f4,38.234,61.766,58.628,41.372,316.07,512,0.951,bicubic,-47.480,-38.892,-61 +convnext_base,38.234,61.766,58.225,41.775,88.59,224,0.875,bicubic,-45.606,-38.525,+29 +xcit_large_24_p8_224,38.118,61.882,57.885,42.115,188.93,224,1.000,bicubic,-46.274,-38.773,-7 +resnetv2_152x2_bitm,37.985,62.015,61.135,38.865,236.34,448,1.000,bilinear,-46.525,-36.299,-15 +cait_s24_384,37.865,62.135,58.079,41.921,47.06,384,1.000,bicubic,-47.185,-39.269,-39 +resnet152d,37.853,62.147,58.356,41.644,60.21,320,1.000,bicubic,-45.825,-38.384,+41 +tf_efficientnetv2_m,37.822,62.178,58.712,41.288,54.14,480,1.000,bicubic,-47.214,-38.566,-40 +resnetrs420,37.753,62.247,58.215,41.785,191.89,416,1.000,bicubic,-47.255,-38.909,-39 +xcit_small_24_p16_224_dist,37.700,62.300,57.358,42.642,47.67,224,1.000,bicubic,-46.170,-39.374,+19 +resnetrs350,37.676,62.324,58.089,41.911,163.96,384,1.000,bicubic,-47.036,-38.901,-30 +xcit_small_12_p16_384_dist,37.582,62.418,57.773,42.227,26.25,384,1.000,bicubic,-47.126,-39.343,-30 +pit_b_distilled_224,37.582,62.418,57.232,42.768,74.79,224,0.900,bicubic,-46.560,-39.624,+1 +resnet200d,37.505,62.495,58.303,41.697,64.69,320,1.000,bicubic,-46.455,-38.521,+11 +resnetv2_152x2_bit_teacher,37.322,62.678,59.406,40.594,236.34,224,0.875,bicubic,-45.546,-37.162,+72 +resnest269e,37.311,62.689,57.470,42.530,110.93,416,0.928,bicubic,-47.207,-39.516,-27 +vit_small_r26_s32_224,37.242,62.758,59.068,40.932,36.43,224,0.900,bicubic,-44.620,-36.954,+143 +resmlp_big_24_224_in22ft1k,37.242,62.758,58.180,41.820,129.14,224,0.875,bicubic,-47.156,-38.938,-22 +cait_s24_224,37.153,62.847,56.729,43.271,46.92,224,1.000,bicubic,-46.305,-39.833,+34 +vit_base_patch32_224,37.081,62.919,59.286,40.714,88.22,224,0.900,bicubic,-43.643,-36.280,+213 +volo_d1_384,37.075,62.925,57.132,42.868,26.78,384,1.000,bicubic,-48.175,-40.082,-66 +convnext_small,37.055,62.945,57.105,42.895,50.22,224,0.875,bicubic,-46.095,-39.325,+47 +tf_efficientnet_b3_ap,37.049,62.951,57.238,42.762,12.23,300,0.904,bicubic,-44.775,-38.386,+140 +efficientnetv2_rw_s,37.049,62.951,56.810,43.190,23.94,384,1.000,bicubic,-46.761,-39.914,+13 +swinv2_base_window16_256,36.992,63.008,56.128,43.872,87.92,256,0.900,bicubic,-47.600,-40.946,-40 +xcit_small_12_p16_224_dist,36.971,63.029,56.733,43.267,26.25,224,1.000,bicubic,-46.375,-39.685,+36 +regnetz_040h,36.965,63.035,57.280,42.720,28.94,320,1.000,bicubic,-47.531,-39.726,-36 +volo_d1_224,36.880,63.120,56.633,43.367,26.63,224,0.960,bicubic,-47.284,-40.141,-15 +seresnet152d,36.788,63.212,56.718,43.282,66.84,320,1.000,bicubic,-47.576,-40.326,-31 +seresnext101d_32x8d,36.637,63.363,56.328,43.672,93.59,288,1.000,bicubic,-47.725,-40.590,-31 +volo_d2_224,36.601,63.399,56.466,43.534,58.68,224,0.960,bicubic,-48.593,-40.722,-73 +xception65p,36.554,63.446,56.423,43.577,39.82,299,0.940,bicubic,-46.576,-40.057,+42 +seresnextaa101d_32x8d,36.527,63.473,56.403,43.597,93.59,288,1.000,bicubic,-48.045,-40.667,-47 +regnetz_d32,36.444,63.556,57.370,42.630,27.58,320,0.950,bicubic,-47.580,-39.498,-12 +cait_xs24_384,36.420,63.580,56.940,43.060,26.67,384,1.000,bicubic,-47.644,-39.950,-18 +volo_d2_384,36.419,63.581,56.313,43.687,58.87,384,1.000,bicubic,-49.617,-41.261,-108 +efficientnet_b3,36.411,63.589,56.843,43.157,12.23,320,1.000,bicubic,-45.829,-39.275,+97 +deit_base_distilled_patch16_224,36.399,63.601,56.621,43.379,87.34,224,0.900,bicubic,-46.989,-39.867,+20 +resnetv2_101x3_bitm,36.385,63.615,59.066,40.934,387.93,448,1.000,bilinear,-48.059,-38.316,-47 +resnetrs270,36.318,63.682,56.566,43.434,129.86,352,1.000,bicubic,-48.118,-40.408,-46 +tresnet_m,36.289,63.711,55.796,44.204,31.39,224,0.875,bilinear,-46.785,-40.324,+37 +mixer_b16_224_miil,36.267,63.733,55.967,44.033,59.88,224,0.875,bilinear,-46.037,-39.753,+87 +deit3_small_patch16_384,36.185,63.815,55.566,44.434,22.21,384,1.000,bicubic,-47.243,-41.110,+11 +tf_efficientnet_b2_ns,36.179,63.821,57.551,42.449,9.11,260,0.890,bicubic,-46.205,-38.695,+76 +resnet152,36.084,63.916,55.566,44.434,60.19,224,0.950,bicubic,-46.734,-40.566,+44 +regnetz_040,36.047,63.953,55.747,44.253,27.12,320,1.000,bicubic,-48.189,-41.185,-39 +ecaresnet101d,36.010,63.990,56.161,43.839,44.57,224,0.875,bicubic,-46.160,-39.887,+95 +dm_nfnet_f2,36.006,63.994,55.458,44.542,193.78,352,0.920,bicubic,-49.060,-41.784,-82 +resnest200e,35.937,64.063,55.841,44.159,70.20,320,0.909,bicubic,-47.891,-41.051,-14 +swsl_resnet18,35.862,64.138,58.457,41.543,11.69,224,0.875,bilinear,-37.412,-33.279,+460 +eca_nfnet_l1,35.823,64.177,55.961,44.039,41.41,320,1.000,bicubic,-48.189,-41.071,-27 +sequencer2d_l,35.819,64.181,55.719,44.281,54.30,224,0.875,bicubic,-47.587,-40.781,+4 +vit_relpos_medium_patch16_cls_224,35.735,64.265,54.923,45.077,38.76,224,0.900,bicubic,-46.827,-41.143,+55 +xcit_small_24_p8_224,35.556,64.444,54.782,45.218,47.63,224,1.000,bicubic,-48.284,-41.854,-21 +xcit_large_24_p16_224,35.524,64.476,54.762,45.238,189.10,224,1.000,bicubic,-47.368,-41.116,+30 +xcit_small_12_p8_224,35.520,64.480,55.505,44.495,26.21,224,1.000,bicubic,-47.820,-40.975,+7 +vit_small_patch16_384,35.473,64.527,57.541,42.459,22.20,384,1.000,bicubic,-48.327,-39.559,-19 +xcit_medium_24_p8_224,35.452,64.548,54.825,45.175,84.32,224,1.000,bicubic,-48.286,-41.569,-16 +swinv2_base_window8_256,35.444,64.556,54.611,45.389,87.92,256,0.900,bicubic,-48.818,-42.311,-54 +swinv2_small_window16_256,35.430,64.570,54.637,45.363,49.73,256,0.900,bicubic,-48.780,-42.233,-51 +resnest101e,35.375,64.625,55.794,44.206,48.28,256,0.875,bilinear,-47.513,-40.526,+25 +convit_base,35.314,64.686,54.931,45.069,86.54,224,0.875,bicubic,-46.978,-41.007,+69 +convnext_tiny_hnf,35.279,64.721,53.849,46.151,28.59,224,0.950,bicubic,-46.941,-42.017,+74 +xcit_tiny_24_p8_224_dist,35.255,64.745,55.254,44.746,12.11,224,1.000,bicubic,-47.305,-40.914,+45 +twins_svt_large,35.088,64.912,54.719,45.281,99.27,224,0.900,bicubic,-48.592,-41.875,-18 +repvgg_b3,35.051,64.949,54.558,45.442,123.09,224,0.875,bilinear,-45.445,-40.706,+178 +repvgg_b3g4,35.039,64.961,54.774,45.226,83.83,224,0.875,bilinear,-45.177,-40.334,+204 +regnetz_d8,34.996,65.004,55.941,44.059,23.37,320,1.000,bicubic,-49.056,-41.055,-50 +dm_nfnet_f1,34.986,65.014,54.110,45.890,132.63,320,0.910,bicubic,-49.638,-42.988,-85 +xcit_tiny_24_p8_384_dist,34.931,65.069,55.151,44.849,12.11,384,1.000,bicubic,-48.815,-41.561,-29 +regnetz_d8_evos,34.894,65.106,55.258,44.742,23.46,320,0.950,bicubic,-49.156,-41.738,-52 +resnet101d,34.870,65.130,54.194,45.806,44.57,320,1.000,bicubic,-48.152,-42.252,+10 +seresnext101_32x8d,34.791,65.209,53.448,46.552,93.57,288,1.000,bicubic,-49.413,-43.426,-63 +resmlp_big_24_distilled_224,34.788,65.213,54.637,45.363,129.14,224,0.875,bicubic,-48.800,-42.011,-25 +swin_s3_base_224,34.788,65.213,53.693,46.307,71.13,224,0.900,bicubic,-49.144,-42.967,-49 +vit_relpos_base_patch16_clsgap_224,34.725,65.275,54.218,45.782,86.43,224,0.900,bicubic,-48.035,-41.956,+17 +vit_base_patch16_rpn_224,34.711,65.289,54.662,45.338,86.54,224,0.900,bicubic,-47.489,-41.334,+62 +sequencer2d_m,34.705,65.295,54.010,45.990,38.31,224,0.875,bicubic,-48.103,-42.258,+13 +deit3_small_patch16_224,34.675,65.325,53.163,46.837,22.06,224,0.900,bicubic,-46.707,-42.287,+112 +vit_large_patch32_384,34.670,65.330,55.731,44.269,306.63,384,1.000,bicubic,-46.838,-40.359,+100 +resnet101,34.658,65.342,54.297,45.703,44.55,224,0.950,bicubic,-47.272,-41.469,+77 +dm_nfnet_f0,34.624,65.376,54.672,45.328,71.49,256,0.900,bicubic,-48.760,-41.902,-23 +vit_relpos_base_patch16_224,34.613,65.387,54.291,45.709,86.43,224,0.900,bicubic,-47.873,-41.851,+30 +ssl_resnext101_32x16d,34.605,65.395,55.937,44.063,194.03,224,0.875,bilinear,-47.251,-40.159,+77 +repvgg_b2g4,34.587,65.413,54.778,45.222,61.76,224,0.875,bilinear,-44.779,-39.910,+232 +resnetv2_101,34.581,65.419,53.153,46.847,44.54,224,0.950,bicubic,-47.465,-42.709,+63 +resnetrs200,34.507,65.493,54.291,45.709,93.21,320,1.000,bicubic,-49.933,-42.789,-94 +resnest50d_4s2x40d,34.357,65.643,54.733,45.267,30.42,224,0.875,bicubic,-46.751,-40.829,+119 +resnetrs152,34.357,65.643,53.562,46.438,86.62,320,1.000,bicubic,-49.357,-43.052,-45 +crossvit_18_dagger_408,34.253,65.747,53.088,46.912,44.61,408,1.000,bicubic,-49.941,-43.730,-79 +xcit_medium_24_p16_224,34.237,65.763,53.165,46.835,84.40,224,1.000,bicubic,-48.401,-42.813,+9 +tf_efficientnet_b1_ns,34.165,65.835,55.495,44.505,7.79,240,0.882,bicubic,-47.221,-40.241,+98 +efficientnetv2_rw_t,34.155,65.845,53.137,46.863,13.65,288,1.000,bicubic,-48.189,-43.059,+30 +twins_pcpvt_large,34.106,65.894,54.126,45.874,60.99,224,0.900,bicubic,-49.030,-42.478,-21 +tf_efficientnet_b4,34.064,65.936,54.196,45.804,19.34,380,0.922,bicubic,-48.960,-42.104,-14 +ssl_resnext101_32x8d,34.029,65.971,55.601,44.399,88.79,224,0.875,bilinear,-47.579,-40.441,+77 +nfnet_l0,34.005,65.995,54.361,45.639,35.07,288,1.000,bicubic,-48.747,-42.157,-3 +xcit_small_24_p16_224,34.005,65.995,53.271,46.729,47.67,224,1.000,bicubic,-48.579,-42.729,+7 +efficientnet_b3_pruned,33.994,66.006,54.106,45.894,9.86,300,0.904,bicubic,-46.864,-41.138,+129 +tf_efficientnet_b6,33.992,66.008,54.542,45.458,43.04,528,0.942,bicubic,-50.116,-42.346,-85 +regnety_160,33.972,66.028,53.540,46.460,83.59,288,1.000,bicubic,-49.720,-43.236,-55 +gc_efficientnetv2_rw_t,33.960,66.040,53.222,46.778,13.68,288,1.000,bicubic,-48.506,-43.076,+12 +pit_s_distilled_224,33.935,66.065,53.267,46.733,24.04,224,0.900,bicubic,-48.059,-42.529,+48 +convnext_tiny,33.838,66.162,53.656,46.344,28.59,224,0.875,bicubic,-48.224,-42.198,+44 +swinv2_cr_small_ns_224,33.836,66.164,52.618,47.382,49.70,224,0.900,bicubic,-49.650,-43.866,-53 +resnext101_64x4d,33.827,66.173,52.172,47.828,83.46,288,1.000,bicubic,-49.317,-44.202,-36 +xcit_small_12_p16_224,33.768,66.232,53.233,46.767,26.25,224,1.000,bicubic,-48.204,-42.579,+47 +swin_s3_small_224,33.701,66.299,52.391,47.609,49.74,224,0.900,bicubic,-50.073,-44.061,-68 +resnetv2_50x3_bitm,33.663,66.337,55.882,44.118,217.32,448,1.000,bilinear,-50.349,-41.244,-86 +swinv2_small_window8_256,33.636,66.364,52.821,47.179,49.73,256,0.900,bicubic,-50.218,-43.821,-80 +resnet51q,33.551,66.448,53.023,46.977,35.70,288,1.000,bilinear,-48.807,-43.155,+10 +xcit_tiny_24_p16_384_dist,33.512,66.488,52.768,47.232,12.12,384,1.000,bicubic,-49.060,-43.520,-5 +vit_relpos_medium_patch16_224,33.500,66.500,52.603,47.397,38.75,224,0.900,bicubic,-48.962,-43.483,+2 +regnety_080,33.469,66.531,52.939,47.061,39.18,288,1.000,bicubic,-50.459,-43.949,-87 +cs3edgenet_x,33.463,66.537,52.939,47.061,47.82,288,1.000,bicubic,-49.259,-43.437,-19 +sequencer2d_s,33.434,66.566,52.404,47.596,27.65,224,0.875,bicubic,-48.910,-43.630,+8 +convmixer_1536_20,33.428,66.572,53.029,46.971,51.63,224,0.960,bicubic,-47.942,-42.583,+76 +regnety_032,33.406,66.594,52.758,47.242,19.44,288,1.000,bicubic,-49.318,-43.664,-23 +crossvit_18_240,33.396,66.604,52.243,47.757,43.27,240,0.875,bicubic,-49.002,-43.811,-1 +vit_srelpos_medium_patch16_224,33.373,66.627,52.453,47.547,38.74,224,0.900,bicubic,-48.863,-43.481,+15 +gernet_l,33.361,66.639,51.909,48.091,31.08,256,0.875,bilinear,-47.989,-43.627,+73 +crossvit_15_dagger_408,33.331,66.669,52.190,47.810,28.50,408,1.000,bicubic,-50.507,-44.590,-88 +crossvit_18_dagger_240,33.284,66.716,52.202,47.798,44.27,240,0.875,bicubic,-49.236,-43.866,-12 +tresnet_xl,33.261,66.739,52.294,47.706,78.44,224,0.875,bilinear,-48.801,-43.642,+23 +jx_nest_base,33.214,66.787,51.809,48.191,67.72,224,0.875,bicubic,-50.340,-44.555,-75 +resnest50d_1s4x24d,33.149,66.851,52.852,47.148,25.68,224,0.875,bicubic,-47.835,-42.472,+90 +vit_relpos_medium_patch16_rpn_224,33.109,66.891,52.347,47.653,38.73,224,0.900,bicubic,-49.185,-43.625,+3 +resnet61q,33.099,66.900,51.758,48.242,36.85,288,1.000,bicubic,-49.419,-44.372,-16 +jx_nest_small,33.048,66.952,51.062,48.938,38.35,224,0.875,bicubic,-50.072,-45.268,-54 +crossvit_base_240,33.037,66.963,51.384,48.616,105.03,240,0.875,bicubic,-49.179,-44.448,+8 +twins_pcpvt_base,33.023,66.977,52.489,47.511,43.83,224,0.900,bicubic,-49.685,-43.861,-34 +xcit_tiny_24_p16_224_dist,32.987,67.013,52.056,47.944,12.12,224,1.000,bicubic,-47.461,-43.156,+119 +rexnet_200,32.980,67.020,52.935,47.065,16.37,224,0.875,bicubic,-48.648,-42.733,+38 +resnest50d,32.976,67.024,52.711,47.289,27.48,224,0.875,bilinear,-47.998,-42.669,+83 +convit_small,32.909,67.091,52.123,47.877,27.78,224,0.875,bicubic,-48.519,-43.619,+51 +crossvit_15_dagger_240,32.907,67.093,51.783,48.217,28.21,240,0.875,bicubic,-49.419,-44.173,-9 +tf_efficientnetv2_s,32.907,67.093,51.730,48.270,21.46,384,1.000,bicubic,-50.977,-44.968,-109 +vit_small_patch16_224,32.877,67.123,53.917,46.083,22.05,224,0.900,bicubic,-48.519,-42.221,+51 +tf_efficientnet_b3,32.862,67.138,52.955,47.045,12.23,300,0.904,bicubic,-48.776,-42.763,+31 +pnasnet5large,32.850,67.150,50.506,49.494,86.06,331,0.911,bicubic,-49.932,-45.536,-48 +twins_svt_base,32.832,67.168,51.563,48.437,56.07,224,0.900,bicubic,-50.306,-44.857,-70 +regnetv_064,32.830,67.170,52.854,47.146,30.58,288,1.000,bicubic,-50.882,-43.892,-97 +regnetz_c16,32.828,67.172,53.750,46.250,13.46,320,0.940,bicubic,-49.692,-42.610,-33 +nasnetalarge,32.773,67.227,50.141,49.859,88.75,331,0.911,bicubic,-49.845,-45.903,-42 +gernet_m,32.744,67.256,51.907,48.093,21.14,224,0.875,bilinear,-47.986,-43.279,+87 +inception_resnet_v2,32.736,67.264,50.653,49.347,55.84,299,0.897,bicubic,-47.724,-44.653,+102 +gluon_resnet152_v1d,32.732,67.268,51.088,48.912,60.21,224,0.875,bicubic,-47.744,-44.112,+100 +pit_b_224,32.718,67.282,49.854,50.146,73.76,224,0.900,bicubic,-49.726,-45.858,-31 +tf_efficientnet_b2_ap,32.685,67.315,52.237,47.763,9.11,260,0.890,bicubic,-47.617,-42.791,+114 +fbnetv3_g,32.634,67.366,52.888,47.112,16.62,288,0.950,bilinear,-49.400,-43.178,0 +tresnet_l,32.559,67.441,51.139,48.861,55.99,224,0.875,bilinear,-48.931,-44.487,+30 +cait_xxs36_384,32.543,67.457,52.233,47.767,17.37,384,1.000,bicubic,-49.649,-43.911,-12 +regnetz_c16_evos,32.530,67.470,52.923,47.077,13.49,320,0.950,bicubic,-50.102,-43.553,-52 +wide_resnet50_2,32.435,67.565,51.453,48.547,68.88,224,0.875,bicubic,-49.021,-44.077,+30 +gmlp_s16_224,32.420,67.580,51.819,48.181,19.42,224,0.875,bicubic,-47.220,-42.805,+150 +ens_adv_inception_resnet_v2,32.374,67.626,50.419,49.581,55.84,299,0.897,bicubic,-47.600,-44.523,+127 +deit_base_patch16_224,32.363,67.637,50.997,49.003,86.57,224,0.900,bicubic,-49.631,-44.735,-5 +swin_small_patch4_window7_224,32.349,67.651,50.911,49.089,49.61,224,0.900,bicubic,-50.869,-45.415,-92 +gluon_resnet152_v1s,32.335,67.665,50.528,49.472,60.32,224,0.875,bicubic,-48.679,-44.886,+56 +deit_small_distilled_patch16_224,32.286,67.714,52.109,47.891,22.44,224,0.900,bicubic,-48.922,-43.265,+41 +xcit_tiny_24_p8_224,32.278,67.722,51.903,48.097,12.11,224,1.000,bicubic,-49.618,-44.071,-2 +gluon_seresnext101_64x4d,32.196,67.804,50.306,49.694,88.23,224,0.875,bicubic,-48.684,-44.990,+63 +coat_lite_small,32.121,67.879,49.934,50.066,19.84,224,0.900,bicubic,-50.183,-45.916,-35 +gluon_seresnext101_32x4d,32.109,67.891,51.235,48.765,48.96,224,0.875,bicubic,-48.797,-44.061,+59 +deit_base_patch16_384,31.989,68.011,50.549,49.451,86.86,384,1.000,bicubic,-51.117,-45.821,-89 +seresnext50_32x4d,31.971,68.028,51.227,48.773,27.56,224,0.875,bicubic,-49.291,-44.401,+32 +xcit_tiny_12_p8_224_dist,31.938,68.062,51.394,48.606,6.71,224,1.000,bicubic,-49.270,-44.212,+33 +levit_384,31.865,68.135,50.593,49.407,39.13,224,0.900,bicubic,-50.723,-45.425,-64 +resnetrs101,31.850,68.150,51.019,48.981,63.62,288,0.940,bicubic,-50.434,-44.989,-37 +cs3se_edgenet_x,31.797,68.203,50.763,49.237,50.72,320,1.000,bicubic,-51.751,-45.903,-119 +vit_relpos_small_patch16_224,31.787,68.213,50.628,49.372,21.98,224,0.900,bicubic,-49.667,-45.200,+14 +poolformer_m48,31.698,68.302,49.889,50.111,73.47,224,0.950,bicubic,-50.762,-46.069,-56 +tnt_s_patch16_224,31.643,68.357,51.137,48.863,23.76,224,0.900,bicubic,-49.875,-44.609,+5 +eca_nfnet_l0,31.604,68.396,51.608,48.392,24.14,288,1.000,bicubic,-50.974,-44.882,-68 +resnetv2_50x1_bit_distilled,31.567,68.433,51.268,48.732,25.55,224,0.875,bicubic,-51.255,-45.254,-87 +mobilevitv2_200_in22ft1k,31.527,68.473,51.772,48.228,18.45,256,0.888,bicubic,-50.807,-44.166,-51 +xception41p,31.510,68.490,50.374,49.626,26.91,299,0.940,bicubic,-50.458,-45.420,-22 +regnety_064,31.472,68.528,50.524,49.476,30.58,288,1.000,bicubic,-52.248,-46.202,-135 +poolformer_m36,31.449,68.551,50.034,49.966,56.17,224,0.950,bicubic,-50.659,-45.656,-34 +ssl_resnext101_32x4d,31.415,68.585,52.133,47.867,44.18,224,0.875,bilinear,-49.509,-43.593,+42 +inception_v4,31.380,68.620,49.242,50.758,42.68,299,0.875,bicubic,-48.788,-45.722,+92 +rexnet_150,31.372,68.628,51.276,48.724,9.73,224,0.875,bicubic,-48.942,-43.890,+80 +crossvit_15_240,31.339,68.661,50.168,49.832,27.53,240,0.875,bicubic,-50.205,-45.522,-7 +pit_s_224,31.335,68.665,49.665,50.335,23.46,224,0.900,bicubic,-49.763,-45.667,+25 +swinv2_tiny_window16_256,31.303,68.697,49.645,50.355,28.35,256,0.900,bicubic,-51.507,-46.585,-95 +crossvit_small_240,31.284,68.716,50.196,49.804,26.86,240,0.875,bicubic,-49.732,-45.260,+28 +cspresnet50,31.278,68.722,51.221,48.779,21.62,256,0.887,bilinear,-48.304,-43.487,+120 +vit_srelpos_small_patch16_224,31.278,68.722,50.247,49.753,21.97,224,0.900,bicubic,-49.820,-45.325,+20 +cait_xxs36_224,31.264,68.736,50.612,49.388,17.30,224,1.000,bicubic,-48.484,-44.256,+107 +swinv2_cr_small_224,31.262,68.738,48.737,51.263,49.70,224,0.900,bicubic,-51.876,-47.361,-118 +convmixer_768_32,31.250,68.750,50.950,49.050,21.11,224,0.960,bicubic,-48.914,-44.122,+84 +swin_s3_tiny_224,31.239,68.761,49.718,50.282,28.33,224,0.900,bicubic,-50.885,-46.232,-49 +cspresnext50,31.221,68.779,50.885,49.115,20.57,256,0.887,bilinear,-49.323,-44.439,+47 +regnetv_040,31.213,68.787,50.111,49.889,20.64,288,1.000,bicubic,-51.985,-46.553,-127 +coat_mini,31.203,68.797,49.773,50.227,10.34,224,0.900,bicubic,-50.063,-45.619,+2 +xcit_tiny_12_p8_384_dist,31.188,68.812,50.524,49.476,6.71,384,1.000,bicubic,-51.198,-45.698,-77 +ecaresnetlight,31.125,68.875,50.239,49.761,30.16,224,0.875,bicubic,-49.331,-45.007,+52 +gluon_resnet101_v1s,31.119,68.881,49.799,50.201,44.67,224,0.875,bicubic,-49.179,-45.363,+67 +edgenext_small,31.101,68.899,50.129,49.871,5.59,320,1.000,bicubic,-50.473,-45.585,-25 +tf_efficientnet_cc_b0_8e,31.091,68.909,50.775,49.225,24.01,224,0.875,bicubic,-46.809,-42.883,+199 +resmlp_36_distilled_224,31.072,68.928,49.691,50.309,44.69,224,0.875,bicubic,-50.084,-45.795,+2 +ecaresnet50t,31.052,68.948,50.577,49.423,25.57,320,0.950,bicubic,-51.296,-45.561,-80 +ecaresnet50d,31.048,68.952,50.844,49.156,25.58,224,0.875,bicubic,-49.550,-44.474,+35 +cspdarknet53,31.018,68.981,50.394,49.606,27.64,256,0.887,bilinear,-49.038,-44.692,+77 +resnet50d,31.018,68.981,49.808,50.192,25.58,224,0.875,bicubic,-49.510,-45.360,+37 +cs3sedarknet_x,31.015,68.985,50.144,49.856,35.40,288,1.000,bicubic,-51.639,-46.202,-107 +gcresnet50t,31.011,68.989,50.121,49.879,25.90,256,0.900,bicubic,-49.923,-45.333,+14 +gluon_resnext101_64x4d,30.993,69.007,48.553,51.447,83.46,224,0.875,bicubic,-49.611,-46.439,+29 +gluon_resnet152_v1c,30.991,69.009,48.934,51.066,60.21,224,0.875,bicubic,-48.921,-45.908,+76 +twins_svt_small,30.975,69.025,49.223,50.777,24.06,224,0.900,bicubic,-50.707,-46.443,-42 +resnext50_32x4d,30.922,69.078,49.266,50.734,25.03,224,0.950,bicubic,-50.174,-46.060,-1 +ecaresnet101d_pruned,30.903,69.097,50.003,49.997,24.88,224,0.875,bicubic,-49.907,-45.625,+17 +resmlp_24_distilled_224,30.899,69.101,50.178,49.822,30.02,224,0.875,bicubic,-49.865,-45.044,+18 +tf_efficientnet_cc_b1_8e,30.897,69.103,50.080,49.920,39.72,240,0.882,bicubic,-48.417,-44.290,+106 +gluon_resnext101_32x4d,30.885,69.115,48.547,51.453,44.18,224,0.875,bicubic,-49.455,-46.379,+44 +tf_efficientnetv2_b3,30.861,69.139,49.820,50.180,14.36,300,0.904,bicubic,-51.105,-45.962,-60 +tf_efficientnet_lite4,30.830,69.170,50.394,49.606,13.01,380,0.920,bilinear,-50.704,-45.272,-40 +nf_resnet50,30.700,69.300,49.956,50.044,25.56,288,0.940,bicubic,-49.954,-45.378,+17 +dpn107,30.680,69.320,48.812,51.188,86.92,224,0.875,bicubic,-49.488,-46.094,+55 +poolformer_s36,30.678,69.322,49.433,50.567,30.86,224,0.900,bicubic,-50.740,-46.015,-32 +xcit_tiny_24_p16_224,30.675,69.325,50.416,49.584,12.12,224,1.000,bicubic,-48.769,-44.472,+93 +ese_vovnet39b,30.667,69.333,49.879,50.121,24.57,224,0.875,bicubic,-48.645,-44.835,+99 +tresnet_xl_448,30.620,69.380,49.068,50.932,78.44,448,0.875,bilinear,-52.428,-47.102,-144 +gluon_resnet152_v1b,30.610,69.390,48.515,51.485,60.19,224,0.875,bicubic,-49.072,-46.221,+77 +haloregnetz_b,30.606,69.394,49.013,50.987,11.68,224,0.940,bicubic,-50.438,-46.185,-13 +ssl_resnext50_32x4d,30.596,69.404,50.655,49.345,25.03,224,0.875,bilinear,-49.730,-44.757,+34 +dpn68b,30.525,69.475,49.172,50.828,12.61,224,0.875,bicubic,-48.691,-45.242,+105 +gluon_resnet101_v1d,30.521,69.479,47.953,52.047,44.57,224,0.875,bicubic,-49.897,-47.061,+24 +mobilevitv2_200_384_in22ft1k,30.498,69.502,50.567,49.433,18.45,384,1.000,bicubic,-52.902,-46.015,-172 +resnest26d,30.490,69.510,50.667,49.333,17.07,224,0.875,bilinear,-47.994,-43.627,+135 +efficientnet_b2,30.439,69.561,49.693,50.307,9.11,288,1.000,bicubic,-50.177,-45.623,+5 +tf_efficientnet_b1_ap,30.421,69.579,49.559,50.441,7.79,240,0.882,bicubic,-48.853,-44.749,+96 +xcit_tiny_12_p16_384_dist,30.403,69.597,50.127,49.873,6.72,384,1.000,bicubic,-50.539,-45.281,-13 +cs3darknet_x,30.398,69.603,49.195,50.805,35.05,288,1.000,bicubic,-51.826,-47.035,-98 +twins_pcpvt_small,30.384,69.616,49.388,50.612,24.11,224,0.900,bicubic,-50.706,-46.254,-24 +resnetv2_50,30.384,69.616,48.828,51.172,25.55,224,0.950,bicubic,-50.028,-46.244,+17 +visformer_small,30.335,69.665,48.291,51.709,40.22,224,0.900,bicubic,-51.773,-47.585,-93 +pit_xs_distilled_224,30.278,69.722,49.838,50.162,11.00,224,0.900,bicubic,-49.030,-44.528,+84 +regnety_040,30.252,69.748,48.918,51.082,20.65,288,1.000,bicubic,-52.784,-47.592,-159 +mobilevitv2_175_in22ft1k,30.213,69.787,49.024,50.976,14.25,256,0.888,bicubic,-51.727,-46.766,-83 +vit_relpos_base_patch32_plus_rpn_256,30.211,69.789,48.700,51.300,119.42,256,0.900,bicubic,-49.275,-45.440,+70 +convmixer_1024_20_ks9_p14,30.101,69.899,49.934,50.066,24.38,224,0.960,bicubic,-46.841,-43.424,+199 +seresnet50,30.073,69.927,49.288,50.712,28.09,224,0.875,bicubic,-50.193,-45.782,+23 +dpn98,30.061,69.939,48.254,51.746,61.57,224,0.875,bicubic,-49.583,-46.346,+60 +tf_efficientnet_b2,30.030,69.970,49.581,50.419,9.11,260,0.890,bicubic,-50.058,-45.327,+32 +efficientnet_el,30.022,69.978,48.832,51.168,10.59,300,0.904,bicubic,-51.284,-46.702,-50 +dpn131,30.016,69.984,48.128,51.872,79.25,224,0.875,bicubic,-49.810,-46.580,+46 +legacy_senet154,30.005,69.996,48.042,51.958,115.09,224,0.875,bilinear,-51.303,-47.454,-53 +xcit_tiny_12_p16_224_dist,30.001,69.999,49.643,50.357,6.72,224,1.000,bicubic,-48.577,-44.555,+111 +halo2botnet50ts_256,29.985,70.015,48.374,51.626,22.64,256,0.950,bicubic,-52.083,-47.268,-104 +mobilevitv2_150_in22ft1k,29.957,70.043,49.219,50.781,10.59,256,0.888,bicubic,-51.513,-46.449,-68 +dpn92,29.955,70.045,49.176,50.824,37.67,224,0.875,bicubic,-50.065,-45.654,+30 +resnetv2_101x1_bitm,29.896,70.104,51.127,48.873,44.54,448,1.000,bilinear,-52.436,-45.389,-127 +gluon_senet154,29.877,70.123,47.892,52.108,115.09,224,0.875,bicubic,-51.353,-47.454,-55 +xception,29.863,70.137,48.681,51.319,22.86,299,0.897,bicubic,-49.181,-45.713,+88 +adv_inception_v3,29.820,70.180,47.843,52.157,23.83,299,0.875,bicubic,-47.758,-45.895,+160 +cs3sedarknet_l,29.812,70.188,48.985,51.015,21.91,288,0.950,bicubic,-51.964,-46.985,-91 +resnetaa50,29.794,70.206,48.018,51.982,25.56,288,1.000,bicubic,-51.824,-47.792,-86 +gluon_xception65,29.786,70.214,47.765,52.235,39.92,299,0.903,bicubic,-49.936,-47.095,+38 +lamhalobotnet50ts_256,29.745,70.255,48.339,51.661,22.57,256,0.950,bicubic,-51.807,-47.165,-85 +fbnetv3_d,29.737,70.263,49.453,50.547,10.31,256,0.950,bilinear,-49.943,-45.487,+41 +resmlp_36_224,29.696,70.304,48.969,51.031,44.69,224,0.875,bicubic,-50.074,-45.917,+33 +convnext_nano,29.694,70.306,47.930,52.070,15.59,288,1.000,bicubic,-51.782,-47.730,-81 +resnet50,29.631,70.369,46.745,53.255,25.56,224,0.950,bicubic,-50.743,-47.869,-9 +resnetblur50,29.610,70.391,48.254,51.746,25.56,224,0.875,bicubic,-49.684,-46.380,+61 +resnetv2_50d_gn,29.608,70.392,47.792,52.208,25.57,288,0.950,bicubic,-52.216,-48.132,-104 +jx_nest_tiny,29.543,70.457,46.985,53.015,17.06,224,0.875,bicubic,-51.875,-48.633,-80 +resnet50_gn,29.535,70.465,48.301,51.699,25.56,224,0.940,bicubic,-50.525,-46.647,+12 +efficientnet_em,29.476,70.524,48.942,51.058,6.90,240,0.882,bicubic,-49.776,-45.850,+61 +cs3darknet_l,29.470,70.530,48.215,51.785,21.16,288,0.950,bicubic,-51.416,-47.453,-46 +resnext101_32x8d,29.439,70.561,48.488,51.512,88.79,224,0.875,bilinear,-49.877,-46.030,+48 +gcresnext50ts,29.429,70.571,47.902,52.098,15.67,256,0.900,bicubic,-51.149,-47.268,-33 +coat_lite_mini,29.429,70.571,47.729,52.271,11.01,224,0.900,bicubic,-49.659,-46.879,+66 +deit_small_patch16_224,29.423,70.577,48.258,51.742,22.05,224,0.900,bicubic,-50.441,-46.790,+15 +sebotnet33ts_256,29.423,70.577,47.146,52.854,13.70,256,0.940,bicubic,-51.731,-48.020,-71 +ssl_resnet50,29.405,70.595,49.787,50.213,25.56,224,0.875,bilinear,-49.819,-45.043,+55 +nf_regnet_b1,29.391,70.609,49.411,50.589,10.22,288,0.900,bicubic,-49.909,-45.343,+47 +cait_xxs24_384,29.387,70.612,48.747,51.253,12.03,384,1.000,bicubic,-51.575,-46.897,-59 +edgenext_small_rw,29.350,70.650,48.737,51.263,7.83,320,1.000,bicubic,-51.102,-46.453,-29 +resnet34d,29.332,70.668,48.411,51.589,21.82,224,0.875,bicubic,-47.784,-44.971,+153 +swin_tiny_patch4_window7_224,29.332,70.668,47.611,52.389,28.29,224,0.900,bicubic,-52.044,-47.931,-89 +cait_xxs24_224,29.303,70.697,48.527,51.473,11.96,224,1.000,bicubic,-49.083,-45.781,+91 +ecaresnet50d_pruned,29.209,70.791,48.443,51.557,19.94,224,0.875,bicubic,-50.509,-46.433,+15 +poolformer_s24,29.175,70.825,48.062,51.938,21.39,224,0.900,bicubic,-51.141,-46.980,-23 +tresnet_l_448,29.165,70.835,47.226,52.774,55.99,448,0.875,bilinear,-53.105,-48.754,-152 +gluon_inception_v3,29.120,70.880,46.955,53.045,23.83,299,0.875,bicubic,-49.686,-47.415,+66 +eca_resnet33ts,29.105,70.895,48.796,51.204,19.68,256,0.900,bicubic,-50.975,-46.176,-9 +lambda_resnet50ts,29.097,70.903,46.981,53.019,21.54,256,0.950,bicubic,-52.055,-48.121,-83 +xception71,29.040,70.960,47.411,52.589,42.34,299,0.903,bicubic,-50.830,-47.513,-1 +hrnet_w64,28.991,71.010,47.130,52.870,128.06,224,0.875,bilinear,-50.479,-47.524,+22 +xcit_tiny_12_p8_224,28.957,71.043,47.511,52.489,6.71,224,1.000,bicubic,-50.737,-47.537,+8 +regnetz_b16,28.943,71.057,47.246,52.754,9.72,288,0.940,bicubic,-51.769,-48.228,-58 +cs3darknet_focus_l,28.926,71.074,47.629,52.371,21.15,288,0.950,bicubic,-51.948,-48.063,-67 +tf_efficientnet_b1,28.886,71.114,47.498,52.502,7.79,240,0.882,bicubic,-49.942,-46.700,+57 +tf_efficientnet_b0_ns,28.884,71.116,48.997,51.003,5.29,224,0.875,bicubic,-49.780,-45.379,+63 +resnetv2_50d_evos,28.878,71.121,46.672,53.328,25.59,288,0.950,bicubic,-53.100,-49.240,-143 +vit_small_patch32_384,28.875,71.125,48.889,51.111,22.92,384,1.000,bicubic,-51.615,-46.711,-52 +gluon_resnet101_v1b,28.873,71.127,46.389,53.611,44.55,224,0.875,bicubic,-50.431,-48.131,+25 +mobilevitv2_150_384_in22ft1k,28.869,71.131,47.916,52.084,10.59,384,1.000,bicubic,-53.721,-48.400,-196 +skresnext50_32x4d,28.826,71.174,46.487,53.513,27.48,224,0.875,bicubic,-51.328,-48.159,-24 +sehalonet33ts,28.778,71.222,46.582,53.418,13.69,256,0.940,bicubic,-52.194,-48.690,-83 +levit_256,28.751,71.249,46.721,53.279,18.89,224,0.900,bicubic,-52.765,-48.769,-123 +tf_efficientnet_lite3,28.660,71.340,47.346,52.654,8.20,300,0.904,bilinear,-51.158,-47.568,-9 +skresnet34,28.654,71.346,47.953,52.047,22.28,224,0.875,bicubic,-48.250,-45.367,+139 +gluon_seresnext50_32x4d,28.649,71.351,46.442,53.558,27.56,224,0.875,bicubic,-51.263,-48.390,-19 +darknetaa53,28.647,71.353,46.949,53.051,36.02,288,1.000,bilinear,-51.875,-48.377,-63 +hrnet_w40,28.635,71.365,47.452,52.548,57.56,224,0.875,bilinear,-50.287,-47.018,+41 +swinv2_tiny_window8_256,28.611,71.389,46.171,53.829,28.35,256,0.900,bicubic,-53.199,-49.823,-144 +mobilevitv2_175_384_in22ft1k,28.605,71.395,47.126,52.874,14.25,384,1.000,bicubic,-54.329,-49.304,-226 +halonet50ts,28.580,71.420,46.169,53.831,22.73,256,0.940,bicubic,-53.072,-49.443,-141 +tf_efficientnetv2_b0,28.570,71.430,47.075,52.925,7.14,224,0.875,bicubic,-49.782,-46.951,+65 +tv_resnet152,28.531,71.469,47.116,52.884,60.19,224,0.875,bilinear,-49.789,-46.918,+65 +xcit_tiny_12_p16_224,28.519,71.481,47.403,52.597,6.72,224,1.000,bicubic,-48.605,-46.309,+119 +repvgg_b2,28.430,71.570,47.038,52.962,89.02,224,0.875,bilinear,-50.364,-47.380,+39 +hrnet_w48,28.409,71.591,47.586,52.414,77.47,224,0.875,bilinear,-50.891,-46.928,+10 +gluon_resnext50_32x4d,28.379,71.621,45.316,54.684,25.03,224,0.875,bicubic,-50.981,-49.110,+2 +swinv2_cr_tiny_ns_224,28.373,71.626,45.920,54.080,28.33,224,0.900,bicubic,-53.413,-49.902,-152 +efficientnet_b2_pruned,28.362,71.638,47.050,52.950,8.31,260,0.890,bicubic,-51.556,-47.800,-34 +seresnet33ts,28.338,71.662,47.753,52.247,19.78,256,0.900,bicubic,-52.016,-47.353,-62 +tf_efficientnet_b0_ap,28.338,71.662,47.527,52.473,5.29,224,0.875,bicubic,-48.750,-45.731,+115 +dla169,28.322,71.678,47.393,52.607,53.39,224,0.875,bilinear,-50.360,-46.943,+36 +dla102x2,28.315,71.685,46.770,53.230,41.28,224,0.875,bilinear,-51.127,-47.876,-7 +tf_efficientnet_cc_b0_4e,28.313,71.687,47.360,52.640,13.31,224,0.875,bicubic,-48.997,-45.980,+102 +darknet53,28.313,71.687,46.873,53.127,41.61,288,1.000,bicubic,-52.225,-48.547,-83 +mixnet_xl,28.291,71.709,46.700,53.300,11.90,224,0.875,bicubic,-52.187,-48.234,-79 +gluon_resnet50_v1d,28.240,71.760,45.867,54.133,25.58,224,0.875,bicubic,-50.830,-48.599,+16 +wide_resnet101_2,28.112,71.888,46.411,53.589,126.89,224,0.875,bilinear,-50.740,-47.877,+23 +gluon_resnet101_v1c,28.104,71.896,45.959,54.041,44.57,224,0.875,bicubic,-51.432,-48.619,-20 +regnetx_320,28.093,71.907,45.120,54.880,107.81,224,0.875,bicubic,-52.151,-49.900,-61 +densenet161,28.081,71.919,46.639,53.361,28.68,224,0.875,bicubic,-49.273,-46.997,+94 +regnety_320,28.061,71.939,45.452,54.548,145.05,224,0.875,bicubic,-52.743,-49.792,-101 +gernet_s,28.038,71.963,46.733,53.267,8.17,224,0.875,bilinear,-48.878,-46.401,+110 +mobilevitv2_175,28.034,71.966,46.085,53.915,14.25,256,0.888,bicubic,-52.828,-49.177,-106 +efficientnet_el_pruned,28.018,71.982,46.788,53.212,10.59,300,0.904,bicubic,-52.280,-48.426,-70 +levit_192,28.014,71.986,45.872,54.128,10.95,224,0.900,bicubic,-51.822,-48.918,-43 +xception41,27.888,72.112,45.896,54.104,26.97,299,0.903,bicubic,-50.628,-48.384,+26 +regnetx_160,27.817,72.183,45.623,54.377,54.28,224,0.875,bicubic,-52.037,-49.207,-47 +tf_inception_v3,27.778,72.222,45.717,54.283,23.83,299,0.875,bicubic,-50.074,-47.923,+66 +res2net101_26w_4s,27.774,72.226,45.167,54.833,45.21,224,0.875,bilinear,-51.422,-49.269,-4 +tf_efficientnetv2_b1,27.762,72.238,46.574,53.426,8.14,240,0.882,bicubic,-51.704,-48.148,-27 +vit_base_patch16_224_sam,27.709,72.291,45.112,54.888,86.57,224,0.900,bicubic,-52.535,-49.642,-72 +fbnetv3_b,27.672,72.328,46.981,53.019,8.60,256,0.950,bilinear,-51.470,-47.769,-6 +repvgg_b1,27.648,72.352,46.521,53.479,57.42,224,0.875,bilinear,-50.720,-47.573,+32 +mobilevitv2_200,27.629,72.371,45.766,54.234,18.45,256,0.888,bicubic,-53.511,-49.602,-138 +hrnet_w44,27.623,72.377,45.845,54.155,67.06,224,0.875,bilinear,-51.273,-48.525,+4 +gcresnet33ts,27.585,72.415,46.199,53.801,19.88,256,0.900,bicubic,-52.491,-48.795,-67 +inception_v3,27.556,72.444,45.265,54.735,23.83,299,0.875,bicubic,-49.882,-48.211,+74 +resmlp_24_224,27.534,72.466,45.697,54.303,30.02,224,0.875,bicubic,-51.844,-48.849,-32 +pit_xs_224,27.497,72.503,45.904,54.096,10.62,224,0.900,bicubic,-50.693,-48.262,+35 +regnetx_080,27.393,72.607,45.002,54.998,39.57,224,0.875,bicubic,-51.809,-49.550,-16 +hrnet_w30,27.389,72.611,46.548,53.452,37.71,224,0.875,bilinear,-50.809,-47.676,+32 +hrnet_w32,27.369,72.631,45.990,54.010,41.23,224,0.875,bilinear,-51.083,-48.198,+17 +gluon_resnet50_v1s,27.322,72.678,45.224,54.776,25.68,224,0.875,bicubic,-51.384,-49.014,+3 +res2net50_26w_8s,27.310,72.690,44.823,55.177,48.40,224,0.875,bilinear,-51.642,-49.483,-7 +densenet201,27.259,72.741,46.220,53.780,20.01,224,0.875,bicubic,-50.029,-47.260,+72 +densenetblur121d,27.228,72.772,46.293,53.707,8.00,224,0.875,bicubic,-49.352,-46.895,+97 +efficientnet_b1_pruned,27.181,72.819,45.872,54.128,6.33,240,0.882,bicubic,-51.063,-47.962,+24 +tf_efficientnetv2_b2,27.173,72.827,44.572,55.428,10.10,260,0.890,bicubic,-53.035,-50.472,-86 +resnet33ts,27.136,72.865,45.332,54.668,19.68,256,0.900,bicubic,-52.072,-49.242,-26 +resnetrs50,27.098,72.902,45.029,54.971,35.69,224,0.910,bicubic,-52.788,-49.941,-73 +rexnet_130,27.096,72.904,45.941,54.059,7.56,224,0.875,bicubic,-52.406,-48.741,-52 +resnet32ts,27.045,72.955,45.263,54.737,17.96,256,0.900,bicubic,-51.969,-49.093,-18 +dla102x,27.039,72.961,45.485,54.515,26.31,224,0.875,bilinear,-51.473,-48.743,0 +gmixer_24_224,27.033,72.967,44.369,55.631,24.72,224,0.875,bicubic,-51.003,-49.301,+27 +tv_resnet101,26.963,73.037,45.236,54.764,44.55,224,0.875,bilinear,-50.417,-48.308,+58 +regnetx_120,26.870,73.130,44.676,55.324,46.11,224,0.875,bicubic,-52.722,-50.058,-60 +resnext50d_32x4d,26.866,73.134,44.446,55.554,25.05,224,0.875,bicubic,-52.810,-50.420,-64 +rexnet_100,26.831,73.169,45.377,54.623,4.80,224,0.875,bicubic,-51.029,-48.497,+33 +densenet169,26.827,73.173,45.385,54.615,14.15,224,0.875,bicubic,-49.077,-47.639,+97 +tinynet_a,26.817,73.183,45.106,54.894,6.19,192,0.875,bicubic,-50.831,-48.430,+39 +legacy_seresnext101_32x4d,26.815,73.185,43.501,56.499,48.96,224,0.875,bilinear,-53.407,-51.513,-101 +regnetx_064,26.790,73.210,44.919,55.081,26.21,224,0.875,bicubic,-52.284,-49.541,-31 +regnety_120,26.784,73.216,44.442,55.558,51.82,224,0.875,bicubic,-53.592,-50.680,-119 +regnetx_032,26.707,73.293,45.228,54.772,15.30,224,0.875,bicubic,-51.477,-48.860,+11 +densenet121,26.674,73.326,45.890,54.110,7.98,224,0.875,bicubic,-48.906,-46.758,+96 +legacy_seresnet152,26.672,73.328,43.953,56.047,66.82,224,0.875,bilinear,-51.980,-50.417,-17 +efficientnet_es,26.619,73.381,45.122,54.878,5.44,224,0.875,bicubic,-51.439,-48.822,+13 +res2net50_26w_6s,26.597,73.403,43.998,56.002,37.05,224,0.875,bilinear,-51.973,-50.126,-17 +repvgg_b1g4,26.581,73.419,45.086,54.914,39.97,224,0.875,bilinear,-51.007,-48.744,+35 +dla60x,26.554,73.446,45.008,54.992,17.35,224,0.875,bilinear,-51.674,-49.016,+2 +coat_lite_tiny,26.509,73.491,44.646,55.354,5.72,224,0.900,bicubic,-51.007,-49.268,+37 +mobilenetv3_large_100_miil,26.507,73.493,44.491,55.509,5.48,224,0.875,bilinear,-51.415,-48.429,+16 +res2net50_14w_8s,26.483,73.517,44.371,55.629,25.06,224,0.875,bilinear,-51.661,-49.481,+3 +tf_efficientnet_b0,26.477,73.523,45.650,54.350,5.29,224,0.875,bicubic,-50.363,-47.568,+60 +gluon_resnet50_v1b,26.440,73.560,44.043,55.957,25.56,224,0.875,bicubic,-51.144,-49.677,+30 +tf_efficientnet_el,26.357,73.643,44.175,55.825,10.59,300,0.904,bicubic,-53.897,-50.953,-119 +lambda_resnet26t,26.342,73.658,44.412,55.588,10.96,256,0.940,bicubic,-52.756,-50.178,-49 +levit_128,26.328,73.672,44.114,55.886,9.21,224,0.900,bicubic,-52.154,-49.898,-22 +resmlp_big_24_224,26.320,73.680,43.557,56.443,129.14,224,0.875,bicubic,-54.710,-51.463,-176 +resmlp_12_distilled_224,26.306,73.694,44.870,55.130,15.35,224,0.875,bicubic,-51.640,-48.690,+7 +regnetx_040,26.241,73.759,44.442,55.558,22.12,224,0.875,bicubic,-52.247,-49.796,-27 +mobilevitv2_150,26.190,73.810,43.768,56.232,10.59,256,0.888,bicubic,-54.178,-51.296,-136 +crossvit_9_dagger_240,26.175,73.825,44.538,55.462,8.78,240,0.875,bicubic,-50.803,-49.076,+45 +vit_small_patch32_224,26.161,73.839,45.110,54.890,22.88,224,0.900,bicubic,-49.829,-48.158,+69 +dpn68,26.135,73.865,44.228,55.772,12.61,224,0.875,bicubic,-50.175,-48.750,+65 +efficientnet_b1,26.061,73.939,44.076,55.924,7.79,256,1.000,bicubic,-52.727,-50.270,-42 +mobilevitv2_125,26.025,73.975,43.666,56.334,7.48,256,0.888,bicubic,-53.657,-51.182,-97 +lambda_resnet26rpt_256,26.017,73.983,44.182,55.818,10.99,256,0.940,bicubic,-52.947,-50.244,-52 +hrnet_w18,25.988,74.012,44.817,55.183,21.30,224,0.875,bilinear,-50.772,-48.627,+48 +hardcorenas_f,25.941,74.059,44.212,55.788,8.20,224,0.875,bilinear,-52.161,-49.590,-12 +resnet34,25.890,74.110,43.988,56.012,21.80,224,0.875,bilinear,-49.222,-48.296,+81 +tresnet_m_448,25.862,74.138,42.872,57.128,31.39,448,0.875,bilinear,-55.844,-52.700,-235 +resnet26t,25.860,74.140,43.953,56.047,16.01,256,0.940,bicubic,-52.004,-49.889,-3 +res2net50_26w_4s,25.858,74.142,43.155,56.845,25.70,224,0.875,bilinear,-52.104,-50.697,-8 +coat_tiny,25.848,74.152,43.279,56.721,5.50,224,0.900,bicubic,-52.588,-50.759,-35 +hardcorenas_c,25.821,74.179,44.770,55.230,5.52,224,0.875,bilinear,-51.231,-48.390,+30 +gluon_resnet50_v1c,25.780,74.220,43.025,56.975,25.58,224,0.875,bicubic,-52.228,-50.965,-14 +halonet26t,25.766,74.234,43.231,56.769,12.48,256,0.950,bicubic,-53.346,-51.083,-71 +selecsls60,25.727,74.273,44.065,55.935,30.67,224,0.875,bicubic,-52.257,-49.767,-15 +hardcorenas_e,25.664,74.336,43.404,56.596,8.07,224,0.875,bilinear,-52.122,-50.300,-3 +dla60_res2next,25.656,74.344,43.664,56.336,17.03,224,0.875,bilinear,-52.800,-50.482,-43 +dla60_res2net,25.646,74.354,43.583,56.417,20.85,224,0.875,bilinear,-52.812,-50.613,-45 +poolformer_s12,25.636,74.364,44.137,55.863,11.92,224,0.900,bicubic,-51.602,-49.369,+17 +ecaresnet26t,25.540,74.460,43.666,56.334,16.01,320,0.950,bicubic,-54.312,-51.418,-123 +resmlp_12_224,25.520,74.480,44.340,55.660,15.35,224,0.875,bicubic,-51.136,-48.840,+34 +mixnet_l,25.514,74.486,43.463,56.537,7.33,224,0.875,bicubic,-53.462,-50.715,-71 +tf_efficientnet_lite1,25.503,74.497,43.579,56.421,5.42,240,0.882,bicubic,-51.135,-49.645,+33 +cs3darknet_focus_m,25.485,74.515,43.762,56.238,9.30,288,0.950,bicubic,-51.797,-50.210,+10 +bat_resnext26ts,25.467,74.533,43.206,56.794,10.73,256,0.900,bicubic,-52.781,-50.890,-39 +eca_halonext26ts,25.455,74.545,43.194,56.806,10.76,256,0.940,bicubic,-54.033,-51.410,-110 +botnet26t_256,25.455,74.545,42.638,57.362,12.49,256,0.950,bicubic,-53.803,-51.890,-92 +tv_resnext50_32x4d,25.450,74.550,42.781,57.219,25.03,224,0.875,bilinear,-52.168,-50.919,-10 +repvgg_a2,25.434,74.566,43.941,56.059,28.21,224,0.875,bilinear,-51.026,-49.069,+34 +tf_mixnet_l,25.420,74.580,42.538,57.462,7.33,224,0.875,bicubic,-53.358,-51.460,-69 +hardcorenas_b,25.400,74.600,44.192,55.808,5.18,224,0.875,bilinear,-51.136,-48.562,+29 +res2next50,25.387,74.613,42.498,57.502,24.67,224,0.875,bilinear,-52.871,-51.390,-47 +legacy_seresnet101,25.334,74.666,42.823,57.177,49.33,224,0.875,bilinear,-53.046,-51.439,-53 +selecsls60b,25.332,74.668,43.559,56.441,32.77,224,0.875,bicubic,-53.072,-50.613,-56 +hardcorenas_d,25.324,74.676,43.123,56.877,7.50,224,0.875,bilinear,-52.106,-50.361,-7 +dla102,25.320,74.680,43.846,56.154,33.27,224,0.875,bilinear,-52.708,-50.104,-38 +resnetv2_50x1_bitm,25.316,74.684,45.358,54.642,25.55,448,1.000,bilinear,-55.026,-50.328,-173 +resnest14d,25.275,74.725,44.090,55.910,10.61,224,0.875,bilinear,-50.233,-48.434,+41 +legacy_seresnext50_32x4d,25.214,74.786,41.942,58.058,27.56,224,0.875,bilinear,-53.862,-52.492,-93 +mixer_b16_224,25.117,74.883,41.217,58.783,59.88,224,0.875,bicubic,-51.493,-51.013,+17 +efficientnet_b0,25.027,74.973,42.795,57.205,5.29,224,0.875,bicubic,-52.673,-50.737,-27 +res2net50_48w_2s,25.025,74.975,42.206,57.794,25.29,224,0.875,bilinear,-52.499,-51.344,-19 +gluon_resnet34_v1b,24.935,75.065,42.241,57.759,21.80,224,0.875,bicubic,-49.657,-49.747,+58 +mobilenetv2_120d,24.931,75.069,43.051,56.949,5.83,224,0.875,bicubic,-52.359,-50.449,-12 +dla60,24.911,75.089,43.294,56.706,22.04,224,0.875,bilinear,-52.111,-50.026,-2 +eca_botnext26ts_256,24.868,75.132,42.950,57.050,10.59,256,0.950,bicubic,-54.408,-51.666,-113 +regnety_016,24.817,75.183,42.610,57.390,11.20,224,0.875,bicubic,-53.039,-51.110,-38 +xcit_nano_12_p8_224_dist,24.811,75.189,43.072,56.928,3.05,224,1.000,bicubic,-51.517,-50.022,+16 +seresnext26ts,24.689,75.311,43.106,56.894,10.39,256,0.900,bicubic,-53.169,-50.684,-41 +eca_resnext26ts,24.658,75.342,42.850,57.150,10.30,256,0.900,bicubic,-52.800,-50.718,-24 +cs3darknet_m,24.630,75.370,42.970,57.030,9.31,288,0.950,bicubic,-52.996,-51.044,-34 +mobilevitv2_100,24.547,75.453,42.919,57.081,4.90,256,0.888,bicubic,-53.539,-51.241,-57 +tf_efficientnet_lite2,24.528,75.472,42.280,57.720,6.09,260,0.890,bicubic,-52.938,-51.478,-28 +regnetx_016,24.487,75.513,42.510,57.490,9.19,224,0.875,bicubic,-52.455,-50.914,-8 +skresnet18,24.483,75.517,42.540,57.460,11.96,224,0.875,bicubic,-48.551,-48.626,+63 +pit_ti_distilled_224,24.408,75.592,42.734,57.266,5.10,224,0.900,bicubic,-50.126,-49.362,+46 +hardcorenas_a,24.371,75.629,43.292,56.708,5.26,224,0.875,bilinear,-51.559,-49.218,+14 +tf_efficientnet_lite0,24.367,75.633,42.504,57.496,4.65,224,0.875,bicubic,-50.465,-49.670,+37 +tv_resnet50,24.084,75.916,41.313,58.687,25.56,224,0.875,bilinear,-52.050,-51.555,+8 +levit_128s,24.056,75.944,41.005,58.995,7.78,224,0.900,bicubic,-52.458,-51.865,+1 +legacy_seresnet34,24.029,75.971,41.905,58.095,21.96,224,0.875,bilinear,-50.781,-50.221,+35 +xcit_nano_12_p16_384_dist,24.011,75.989,42.327,57.673,3.05,384,1.000,bicubic,-51.445,-50.363,+20 +xcit_nano_12_p8_384_dist,23.956,76.044,41.946,58.054,3.05,384,1.000,bicubic,-53.860,-52.100,-52 +gcresnext26ts,23.950,76.050,41.359,58.641,10.48,256,0.900,bicubic,-53.864,-52.477,-52 +resnet18d,23.933,76.067,42.298,57.702,11.71,224,0.875,bicubic,-48.325,-48.390,+63 +efficientnet_lite0,23.907,76.093,42.084,57.916,4.65,224,0.875,bicubic,-51.561,-50.432,+14 +resnext26ts,23.868,76.132,41.109,58.891,10.30,256,0.900,bicubic,-52.912,-52.023,-15 +tv_densenet121,23.840,76.160,41.921,58.079,7.98,224,0.875,bicubic,-50.900,-50.227,+29 +efficientnet_es_pruned,23.838,76.162,41.989,58.011,5.44,224,0.875,bicubic,-51.162,-50.453,+23 +mobilenetv2_140,23.714,76.286,41.477,58.523,6.11,224,0.875,bicubic,-52.798,-51.521,-8 +mixnet_m,23.714,76.286,41.148,58.852,5.01,224,0.875,bicubic,-53.548,-52.274,-36 +dla34,23.679,76.321,41.539,58.461,15.74,224,0.875,bilinear,-50.945,-50.533,+28 +legacy_seresnet50,23.651,76.349,40.091,59.909,28.09,224,0.875,bilinear,-53.981,-53.659,-57 +ese_vovnet19b_dw,23.528,76.472,41.284,58.716,6.54,224,0.875,bicubic,-53.266,-51.982,-23 +tf_mixnet_m,23.484,76.516,41.001,58.999,5.01,224,0.875,bicubic,-53.462,-52.151,-30 +tv_resnet34,23.469,76.531,41.364,58.636,21.80,224,0.875,bilinear,-49.839,-50.060,+39 +tf_efficientnet_em,23.361,76.639,40.400,59.600,6.90,240,0.882,bicubic,-54.765,-53.646,-84 +selecsls42b,23.355,76.645,40.675,59.325,32.46,224,0.875,bicubic,-53.823,-52.717,-41 +repvgg_b0,23.319,76.681,41.172,58.828,15.82,224,0.875,bilinear,-51.835,-51.244,+7 +xcit_nano_12_p16_224_dist,23.264,76.736,41.382,58.618,3.05,224,1.000,bicubic,-49.038,-49.480,+47 +mobilenetv2_110d,23.076,76.924,40.748,59.252,4.52,224,0.875,bicubic,-51.960,-51.444,+9 +vit_base_patch32_224_sam,23.048,76.952,39.574,60.426,88.22,224,0.900,bicubic,-50.644,-51.438,+29 +tinynet_b,23.023,76.977,40.968,59.032,3.73,188,0.875,bicubic,-51.951,-51.214,+10 +deit_tiny_distilled_patch16_224,22.726,77.274,40.773,59.227,5.91,224,0.900,bicubic,-51.786,-51.117,+19 +mobilenetv3_large_100,22.655,77.345,40.775,59.225,5.48,224,0.875,bicubic,-53.121,-51.765,-12 +mobilenetv3_rw,22.626,77.374,40.380,59.620,5.48,224,0.875,bicubic,-53.008,-52.328,-11 +tf_mobilenetv3_large_100,22.565,77.435,39.761,60.239,5.48,224,0.875,bilinear,-52.947,-52.845,-9 +mobilevit_s,22.476,77.524,38.643,61.357,5.58,256,0.900,bicubic,-55.834,-55.509,-104 +tf_efficientnet_es,22.416,77.585,39.093,60.907,5.44,224,0.875,bicubic,-54.182,-54.111,-31 +xcit_nano_12_p8_224,22.412,77.588,40.657,59.343,3.05,224,1.000,bicubic,-51.504,-51.511,+19 +hrnet_w18_small_v2,22.337,77.663,39.869,60.131,15.60,224,0.875,bilinear,-52.773,-52.547,-2 +convit_tiny,22.276,77.724,39.665,60.335,5.71,224,0.875,bicubic,-50.838,-52.055,+25 +edgenext_x_small,22.199,77.801,39.075,60.925,2.34,256,0.900,bicubic,-52.665,-53.225,+1 +regnety_008,22.119,77.881,38.891,61.109,6.26,224,0.875,bicubic,-54.195,-54.179,-29 +seresnext26t_32x4d,21.983,78.017,38.486,61.514,16.81,224,0.875,bicubic,-55.985,-55.262,-94 +regnety_006,21.981,78.019,38.950,61.050,6.06,224,0.875,bicubic,-53.271,-53.582,-11 +vit_tiny_r_s16_p8_384,21.958,78.042,39.403,60.597,6.36,384,1.000,bicubic,-53.994,-53.859,-27 regnetx_008,21.942,78.058,38.926,61.074,7.26,224,0.875,bicubic,-53.092,-53.414,-7 -resnet26d,21.909,78.091,38.615,61.385,16.01,224,0.875,bicubic,-54.795,-54.535,-44 -semnasnet_100,21.899,78.101,38.600,61.400,3.89,224,0.875,bicubic,-53.551,-54.000,-17 -pit_ti_224,21.865,78.135,39.545,60.455,4.85,224,0.900,bicubic,-51.047,-51.861,+19 -regnetx_006,21.738,78.263,38.916,61.084,6.20,224,0.875,bicubic,-52.123,-52.756,+7 -vit_tiny_patch16_384,21.720,78.280,39.327,60.673,5.79,384,1.000,bicubic,-56.714,-55.215,-123 -crossvit_9_240,21.688,78.312,39.274,60.726,8.55,240,0.875,bicubic,-52.272,-52.694,+3 -vgg19_bn,21.628,78.373,39.280,60.720,143.68,224,0.875,bilinear,-52.587,-52.568,-2 -ghostnet_100,21.622,78.378,38.692,61.308,5.18,224,0.875,bilinear,-52.352,-52.768,0 -semnasnet_075,21.570,78.430,38.924,61.076,2.91,224,0.875,bicubic,-51.401,-52.212,+11 -gluon_resnet18_v1b,21.551,78.449,38.887,61.113,11.69,224,0.875,bicubic,-49.283,-50.875,+28 -fbnetc_100,21.490,78.510,38.161,61.839,5.57,224,0.875,bilinear,-53.640,-54.224,-22 -xcit_nano_12_p16_224,21.433,78.567,39.796,60.204,3.05,224,1.000,bicubic,-48.521,-49.958,+29 -mnasnet_100,21.358,78.642,37.717,62.283,4.38,224,0.875,bicubic,-53.300,-54.395,-14 -resnet26,21.288,78.713,38.020,61.980,16.00,224,0.875,bicubic,-54.012,-54.558,-28 -lcnet_100,21.284,78.716,38.849,61.151,2.95,224,0.875,bicubic,-50.820,-51.527,+16 -ssl_resnet18,21.282,78.718,39.111,60.889,11.69,224,0.875,bilinear,-51.326,-52.313,+7 -mixnet_s,21.254,78.746,38.189,61.811,4.13,224,0.875,bicubic,-54.738,-54.609,-46 -seresnext26d_32x4d,21.250,78.750,37.313,62.687,16.81,224,0.875,bicubic,-56.354,-56.295,-95 -legacy_seresnext26_32x4d,21.091,78.909,37.639,62.361,16.79,224,0.875,bicubic,-56.015,-55.679,-76 -crossvit_tiny_240,21.048,78.952,38.055,61.945,7.01,240,0.875,bicubic,-52.284,-53.859,-5 -regnetx_004,20.900,79.100,37.568,62.432,5.16,224,0.875,bicubic,-51.492,-53.264,+3 -spnasnet_100,20.863,79.137,37.896,62.104,4.42,224,0.875,bilinear,-53.221,-53.924,-16 -legacy_seresnet18,20.841,79.159,37.615,62.385,11.78,224,0.875,bicubic,-50.901,-52.717,+11 -mobilenetv2_100,20.769,79.231,37.761,62.239,3.50,224,0.875,bicubic,-52.201,-53.259,-3 -tf_mixnet_s,20.474,79.526,36.605,63.395,4.13,224,0.875,bicubic,-55.176,-56.023,-48 -vit_tiny_patch16_224,20.454,79.546,37.605,62.395,5.72,224,0.900,bicubic,-55.008,-55.239,-43 -regnety_004,20.411,79.589,36.996,63.004,4.34,224,0.875,bicubic,-53.613,-54.758,-20 -hrnet_w18_small,20.368,79.632,37.090,62.910,13.19,224,0.875,bilinear,-51.970,-53.590,-2 -tf_mobilenetv3_large_075,20.366,79.634,36.772,63.228,3.99,224,0.875,bilinear,-53.070,-54.572,-16 -resnet18,20.228,79.772,37.258,62.742,11.69,224,0.875,bilinear,-49.516,-51.824,+13 -mixer_l16_224,20.167,79.833,32.944,67.056,208.20,224,0.875,bicubic,-51.887,-54.718,+1 -deit_tiny_patch16_224,20.162,79.838,37.556,62.444,5.72,224,0.900,bicubic,-52.010,-53.558,-2 -tf_mobilenetv3_large_minimal_100,20.124,79.876,36.902,63.098,3.92,224,0.875,bilinear,-52.126,-53.728,-4 -vgg16_bn,19.957,80.043,36.303,63.697,138.37,224,0.875,bilinear,-53.393,-55.202,-20 -vit_tiny_r_s16_p8_224,19.340,80.660,36.053,63.947,6.34,224,0.900,bicubic,-52.452,-54.769,-2 -tinynet_c,19.254,80.746,35.994,64.006,2.46,184,0.875,bicubic,-51.974,-53.756,+1 -mobilevit_xs,18.289,81.711,33.214,66.787,2.32,256,0.900,bicubic,-56.355,-59.142,-37 -lcnet_075,18.163,81.837,34.410,65.590,2.36,224,0.875,bicubic,-50.653,-53.960,+8 -vgg19,17.929,82.071,33.054,66.946,143.67,224,0.875,bilinear,-54.437,-57.816,-14 -vgg13_bn,17.802,82.198,34.039,65.961,133.05,224,0.875,bilinear,-53.792,-56.337,-5 +resnet26d,21.907,78.094,38.621,61.379,16.01,224,0.875,bicubic,-54.795,-54.531,-45 +semnasnet_100,21.897,78.103,38.602,61.398,3.89,224,0.875,bicubic,-53.553,-53.998,-17 +pit_ti_224,21.869,78.131,39.543,60.457,4.85,224,0.900,bicubic,-51.043,-51.863,+20 +regnetx_006,21.738,78.263,38.916,61.084,6.20,224,0.875,bicubic,-52.118,-52.756,+8 +vit_tiny_patch16_384,21.714,78.286,39.327,60.673,5.79,384,1.000,bicubic,-56.716,-55.217,-126 +crossvit_9_240,21.688,78.312,39.278,60.722,8.55,240,0.875,bicubic,-52.272,-52.686,+4 +vgg19_bn,21.625,78.374,39.280,60.720,143.68,224,0.875,bilinear,-52.589,-52.564,-1 +ghostnet_100,21.614,78.386,38.696,61.304,5.18,224,0.875,bilinear,-52.366,-52.762,+1 +semnasnet_075,21.570,78.430,38.934,61.066,2.91,224,0.875,bicubic,-51.404,-52.200,+12 +gluon_resnet18_v1b,21.557,78.443,38.887,61.113,11.69,224,0.875,bicubic,-49.281,-50.875,+31 +mobilevitv2_075,21.535,78.465,38.635,61.365,2.87,256,0.888,bicubic,-54.073,-54.123,-33 +fbnetc_100,21.508,78.492,38.158,61.842,5.57,224,0.875,bilinear,-53.608,-54.228,-23 +xcit_nano_12_p16_224,21.437,78.563,39.798,60.202,3.05,224,1.000,bicubic,-48.517,-49.958,+32 +mnasnet_100,21.362,78.638,37.721,62.279,4.38,224,0.875,bicubic,-53.288,-54.393,-14 +lcnet_100,21.290,78.710,38.849,61.151,2.95,224,0.875,bicubic,-50.820,-51.529,+18 +resnet26,21.285,78.715,38.020,61.980,16.00,224,0.875,bicubic,-54.015,-54.560,-30 +ssl_resnet18,21.278,78.722,39.107,60.893,11.69,224,0.875,bilinear,-51.326,-52.317,+7 +mixnet_s,21.256,78.744,38.183,61.817,4.13,224,0.875,bicubic,-54.740,-54.617,-48 +seresnext26d_32x4d,21.250,78.750,37.319,62.681,16.81,224,0.875,bicubic,-56.356,-56.287,-98 +legacy_seresnext26_32x4d,21.091,78.909,37.629,62.371,16.79,224,0.875,bicubic,-56.013,-55.687,-78 +crossvit_tiny_240,21.050,78.950,38.053,61.947,7.01,240,0.875,bicubic,-52.288,-53.861,-5 +regnetx_004,20.898,79.102,37.568,62.432,5.16,224,0.875,bicubic,-51.498,-53.270,+3 +spnasnet_100,20.865,79.135,37.888,62.112,4.42,224,0.875,bilinear,-53.225,-53.928,-16 +legacy_seresnet18,20.841,79.159,37.613,62.387,11.78,224,0.875,bicubic,-50.899,-52.717,+12 +mobilenetv2_100,20.777,79.223,37.764,62.236,3.50,224,0.875,bicubic,-52.179,-53.246,-3 +tf_mixnet_s,20.462,79.538,36.615,63.385,4.13,224,0.875,bicubic,-55.190,-56.011,-50 +vit_tiny_patch16_224,20.458,79.542,37.603,62.397,5.72,224,0.900,bicubic,-55.006,-55.241,-44 +regnety_004,20.415,79.585,37.002,62.998,4.34,224,0.875,bicubic,-53.609,-54.754,-20 +hrnet_w18_small,20.364,79.636,37.089,62.911,13.19,224,0.875,bilinear,-51.972,-53.591,-1 +tf_mobilenetv3_large_075,20.364,79.636,36.770,63.230,3.99,224,0.875,bilinear,-53.076,-54.578,-16 +resnet18,20.224,79.776,37.256,62.744,11.69,224,0.875,bilinear,-49.524,-51.828,+16 +mixer_l16_224,20.169,79.831,32.942,67.058,208.20,224,0.875,bicubic,-51.897,-54.724,+2 +deit_tiny_patch16_224,20.166,79.835,37.560,62.440,5.72,224,0.900,bicubic,-52.008,-53.554,-1 +tf_mobilenetv3_large_minimal_100,20.108,79.891,36.906,63.094,3.92,224,0.875,bilinear,-52.142,-53.714,-3 +vgg16_bn,19.957,80.043,36.303,63.697,138.37,224,0.875,bilinear,-53.393,-55.201,-20 +vit_tiny_r_s16_p8_224,19.324,80.676,36.051,63.949,6.34,224,0.900,bicubic,-52.470,-54.767,-1 +tinynet_c,19.260,80.740,35.988,64.012,2.46,184,0.875,bicubic,-51.968,-53.760,+2 +edgenext_xx_small,18.580,81.420,34.693,65.307,1.33,256,0.900,bicubic,-52.526,-55.339,+2 +mobilevit_xs,18.303,81.697,33.227,66.773,2.32,256,0.900,bicubic,-56.331,-59.119,-38 +lcnet_075,18.161,81.839,34.406,65.594,2.36,224,0.875,bicubic,-50.653,-53.958,+10 +vgg19,17.929,82.071,33.054,66.946,143.67,224,0.875,bilinear,-54.437,-57.818,-15 +vgg13_bn,17.803,82.197,34.039,65.961,133.05,224,0.875,bilinear,-53.795,-56.337,-5 vgg16,17.540,82.460,32.769,67.231,138.36,224,0.875,bilinear,-54.050,-57.613,-5 -regnety_002,17.462,82.538,32.443,67.557,3.16,224,0.875,bicubic,-52.793,-57.089,-2 -vgg11_bn,17.403,82.597,33.009,66.991,132.87,224,0.875,bilinear,-52.957,-56.793,-4 -regnetx_002,16.953,83.047,32.227,67.773,2.68,224,0.875,bicubic,-51.803,-56.329,+3 -mobilenetv3_small_100,16.809,83.191,32.522,67.478,2.54,224,0.875,bicubic,-50.847,-55.112,+5 -tinynet_d,16.677,83.323,32.455,67.545,2.34,152,0.875,bicubic,-50.281,-54.609,+5 -mobilenetv2_050,16.670,83.330,31.952,68.048,1.97,224,0.875,bicubic,-49.272,-54.130,+7 -mnasnet_small,16.636,83.364,31.921,68.079,2.03,224,0.875,bicubic,-49.570,-54.587,+4 -dla60x_c,16.310,83.690,31.761,68.239,1.32,224,0.875,bilinear,-51.582,-56.665,0 -tf_mobilenetv3_small_100,16.227,83.772,31.225,68.775,2.54,224,0.875,bilinear,-51.697,-56.439,-2 -vgg13,16.104,83.896,30.983,69.017,133.05,224,0.875,bilinear,-53.822,-58.263,-9 -vgg11,15.730,84.270,30.453,69.547,132.86,224,0.875,bilinear,-53.298,-58.173,-8 -mobilenetv3_small_075,14.956,85.044,29.737,70.263,2.04,224,0.875,bicubic,-50.286,-55.701,+3 -tf_mobilenetv3_small_075,14.944,85.056,29.570,70.430,2.04,224,0.875,bilinear,-50.770,-56.564,+1 -dla46_c,14.657,85.343,29.378,70.622,1.30,224,0.875,bilinear,-50.209,-56.916,+2 -mobilevit_xxs,14.508,85.492,28.670,71.330,1.27,256,0.900,bicubic,-54.412,-60.274,-11 -dla46x_c,14.382,85.618,29.191,70.809,1.07,224,0.875,bilinear,-51.588,-57.789,-4 -lcnet_050,14.310,85.690,28.645,71.355,1.88,224,0.875,bicubic,-48.790,-55.737,0 -tf_mobilenetv3_small_minimal_100,13.962,86.038,27.986,72.014,2.04,224,0.875,bilinear,-48.946,-56.248,0 -tinynet_e,12.671,87.329,26.391,73.609,2.04,106,0.875,bicubic,-47.185,-55.373,0 +regnety_002,17.458,82.542,32.431,67.569,3.16,224,0.875,bicubic,-52.798,-57.103,-1 +vgg11_bn,17.403,82.597,33.009,66.991,132.87,224,0.875,bilinear,-52.957,-56.793,-3 +mobilevitv2_050,17.302,82.698,32.999,67.001,1.37,256,0.888,bicubic,-52.838,-56.931,-2 +resnet10t,17.281,82.719,33.070,66.930,5.44,224,0.950,bilinear,-51.027,-55.010,+5 +regnetx_002,16.962,83.038,32.223,67.777,2.68,224,0.875,bicubic,-51.792,-56.333,+3 +mobilenetv3_small_100,16.815,83.185,32.535,67.465,2.54,224,0.875,bicubic,-50.843,-55.099,+6 +tinynet_d,16.675,83.325,32.459,67.541,2.34,152,0.875,bicubic,-50.287,-54.605,+6 +mobilenetv2_050,16.675,83.325,31.952,68.048,1.97,224,0.875,bicubic,-49.269,-54.128,+8 +mnasnet_small,16.636,83.364,31.922,68.078,2.03,224,0.875,bicubic,-49.570,-54.584,+5 +resnet14t,16.471,83.529,30.722,69.278,10.08,224,0.950,bilinear,-55.885,-59.618,-26 +dla60x_c,16.320,83.680,31.752,68.249,1.32,224,0.875,bilinear,-51.560,-56.682,0 +tf_mobilenetv3_small_100,16.227,83.772,31.225,68.775,2.54,224,0.875,bilinear,-51.699,-56.443,-2 +vgg13,16.104,83.896,30.983,69.017,133.05,224,0.875,bilinear,-53.822,-58.263,-10 +vgg11,15.730,84.270,30.453,69.547,132.86,224,0.875,bilinear,-53.298,-58.175,-9 +mobilenetv3_small_075,14.954,85.046,29.735,70.265,2.04,224,0.875,bicubic,-50.284,-55.705,+3 +tf_mobilenetv3_small_075,14.948,85.052,29.576,70.424,2.04,224,0.875,bilinear,-50.764,-56.554,+1 +dla46_c,14.671,85.329,29.374,70.626,1.30,224,0.875,bilinear,-50.201,-56.928,+2 +mobilevit_xxs,14.508,85.492,28.670,71.330,1.27,256,0.900,bicubic,-54.412,-60.276,-12 +dla46x_c,14.382,85.618,29.179,70.821,1.07,224,0.875,bilinear,-51.570,-57.807,-4 +lcnet_050,14.306,85.694,28.647,71.353,1.88,224,0.875,bicubic,-48.788,-55.735,0 +tf_mobilenetv3_small_minimal_100,13.958,86.042,27.979,72.022,2.04,224,0.875,bilinear,-48.942,-56.255,0 +tinynet_e,12.669,87.331,26.389,73.611,2.04,106,0.875,bicubic,-47.187,-55.377,0 mobilenetv3_small_050,11.034,88.966,23.471,76.529,1.59,224,0.875,bicubic,-46.856,-56.723,0 diff --git a/tests/test_models.py b/tests/test_models.py index 7ea9af6e..94744483 100644 --- a/tests/test_models.py +++ b/tests/test_models.py @@ -4,6 +4,8 @@ import platform import os import fnmatch +_IS_MAC = platform.system() == 'Darwin' + try: from torchvision.models.feature_extraction import create_feature_extractor, get_graph_node_names, NodePathTracer has_fx_feature_extraction = True @@ -322,157 +324,160 @@ def test_model_forward_features(model_name, batch_size): assert not torch.isnan(o).any() -def _create_fx_model(model, train=False): - # This block of code does a bit of juggling to handle any case where there are multiple outputs in train mode - # So we trace once and look at the graph, and get the indices of the nodes that lead into the original fx output - # node. Then we use those indices to select from train_nodes returned by torchvision get_graph_node_names - tracer_kwargs = dict( - leaf_modules=list(_leaf_modules), - autowrap_functions=list(_autowrap_functions), - #enable_cpatching=True, - param_shapes_constant=True - ) - train_nodes, eval_nodes = get_graph_node_names(model, tracer_kwargs=tracer_kwargs) - - eval_return_nodes = [eval_nodes[-1]] - train_return_nodes = [train_nodes[-1]] - if train: - tracer = NodePathTracer(**tracer_kwargs) - graph = tracer.trace(model) - graph_nodes = list(reversed(graph.nodes)) - output_node_names = [n.name for n in graph_nodes[0]._input_nodes.keys()] - graph_node_names = [n.name for n in graph_nodes] - output_node_indices = [-graph_node_names.index(node_name) for node_name in output_node_names] - train_return_nodes = [train_nodes[ix] for ix in output_node_indices] - - fx_model = create_feature_extractor( - model, - train_return_nodes=train_return_nodes, - eval_return_nodes=eval_return_nodes, - tracer_kwargs=tracer_kwargs, - ) - return fx_model - - -EXCLUDE_FX_FILTERS = ['vit_gi*'] -# not enough memory to run fx on more models than other tests -if 'GITHUB_ACTIONS' in os.environ: - EXCLUDE_FX_FILTERS += [ - 'beit_large*', - 'mixer_l*', - '*nfnet_f2*', - '*resnext101_32x32d', - 'resnetv2_152x2*', - 'resmlp_big*', - 'resnetrs270', - 'swin_large*', - 'vgg*', - 'vit_large*', - 'vit_base_patch8*', - 'xcit_large*', - ] +if not _IS_MAC: + # MACOS test runners are really slow, only running tests below this point if not on a Darwin runner... + + def _create_fx_model(model, train=False): + # This block of code does a bit of juggling to handle any case where there are multiple outputs in train mode + # So we trace once and look at the graph, and get the indices of the nodes that lead into the original fx output + # node. Then we use those indices to select from train_nodes returned by torchvision get_graph_node_names + tracer_kwargs = dict( + leaf_modules=list(_leaf_modules), + autowrap_functions=list(_autowrap_functions), + #enable_cpatching=True, + param_shapes_constant=True + ) + train_nodes, eval_nodes = get_graph_node_names(model, tracer_kwargs=tracer_kwargs) + + eval_return_nodes = [eval_nodes[-1]] + train_return_nodes = [train_nodes[-1]] + if train: + tracer = NodePathTracer(**tracer_kwargs) + graph = tracer.trace(model) + graph_nodes = list(reversed(graph.nodes)) + output_node_names = [n.name for n in graph_nodes[0]._input_nodes.keys()] + graph_node_names = [n.name for n in graph_nodes] + output_node_indices = [-graph_node_names.index(node_name) for node_name in output_node_names] + train_return_nodes = [train_nodes[ix] for ix in output_node_indices] + + fx_model = create_feature_extractor( + model, + train_return_nodes=train_return_nodes, + eval_return_nodes=eval_return_nodes, + tracer_kwargs=tracer_kwargs, + ) + return fx_model + + + EXCLUDE_FX_FILTERS = ['vit_gi*'] + # not enough memory to run fx on more models than other tests + if 'GITHUB_ACTIONS' in os.environ: + EXCLUDE_FX_FILTERS += [ + 'beit_large*', + 'mixer_l*', + '*nfnet_f2*', + '*resnext101_32x32d', + 'resnetv2_152x2*', + 'resmlp_big*', + 'resnetrs270', + 'swin_large*', + 'vgg*', + 'vit_large*', + 'vit_base_patch8*', + 'xcit_large*', + ] -@pytest.mark.timeout(120) -@pytest.mark.parametrize('model_name', list_models(exclude_filters=EXCLUDE_FILTERS + EXCLUDE_FX_FILTERS)) -@pytest.mark.parametrize('batch_size', [1]) -def test_model_forward_fx(model_name, batch_size): - """ - Symbolically trace each model and run single forward pass through the resulting GraphModule - Also check that the output of a forward pass through the GraphModule is the same as that from the original Module - """ - if not has_fx_feature_extraction: - pytest.skip("Can't test FX. Torch >= 1.10 and Torchvision >= 0.11 are required.") + @pytest.mark.timeout(120) + @pytest.mark.parametrize('model_name', list_models(exclude_filters=EXCLUDE_FILTERS + EXCLUDE_FX_FILTERS)) + @pytest.mark.parametrize('batch_size', [1]) + def test_model_forward_fx(model_name, batch_size): + """ + Symbolically trace each model and run single forward pass through the resulting GraphModule + Also check that the output of a forward pass through the GraphModule is the same as that from the original Module + """ + if not has_fx_feature_extraction: + pytest.skip("Can't test FX. Torch >= 1.10 and Torchvision >= 0.11 are required.") - model = create_model(model_name, pretrained=False) - model.eval() + model = create_model(model_name, pretrained=False) + model.eval() - input_size = _get_input_size(model=model, target=TARGET_FWD_FX_SIZE) - if max(input_size) > MAX_FWD_FX_SIZE: - pytest.skip("Fixed input size model > limit.") - with torch.no_grad(): - inputs = torch.randn((batch_size, *input_size)) - outputs = model(inputs) - if isinstance(outputs, tuple): - outputs = torch.cat(outputs) + input_size = _get_input_size(model=model, target=TARGET_FWD_FX_SIZE) + if max(input_size) > MAX_FWD_FX_SIZE: + pytest.skip("Fixed input size model > limit.") + with torch.no_grad(): + inputs = torch.randn((batch_size, *input_size)) + outputs = model(inputs) + if isinstance(outputs, tuple): + outputs = torch.cat(outputs) - model = _create_fx_model(model) - fx_outputs = tuple(model(inputs).values()) - if isinstance(fx_outputs, tuple): - fx_outputs = torch.cat(fx_outputs) + model = _create_fx_model(model) + fx_outputs = tuple(model(inputs).values()) + if isinstance(fx_outputs, tuple): + fx_outputs = torch.cat(fx_outputs) - assert torch.all(fx_outputs == outputs) - assert outputs.shape[0] == batch_size - assert not torch.isnan(outputs).any(), 'Output included NaNs' + assert torch.all(fx_outputs == outputs) + assert outputs.shape[0] == batch_size + assert not torch.isnan(outputs).any(), 'Output included NaNs' -@pytest.mark.timeout(120) -@pytest.mark.parametrize('model_name', list_models( - exclude_filters=EXCLUDE_FILTERS + EXCLUDE_FX_FILTERS, name_matches_cfg=True)) -@pytest.mark.parametrize('batch_size', [2]) -def test_model_backward_fx(model_name, batch_size): - """Symbolically trace each model and run single backward pass through the resulting GraphModule""" - if not has_fx_feature_extraction: - pytest.skip("Can't test FX. Torch >= 1.10 and Torchvision >= 0.11 are required.") + @pytest.mark.timeout(120) + @pytest.mark.parametrize('model_name', list_models( + exclude_filters=EXCLUDE_FILTERS + EXCLUDE_FX_FILTERS, name_matches_cfg=True)) + @pytest.mark.parametrize('batch_size', [2]) + def test_model_backward_fx(model_name, batch_size): + """Symbolically trace each model and run single backward pass through the resulting GraphModule""" + if not has_fx_feature_extraction: + pytest.skip("Can't test FX. Torch >= 1.10 and Torchvision >= 0.11 are required.") - input_size = _get_input_size(model_name=model_name, target=TARGET_BWD_FX_SIZE) - if max(input_size) > MAX_BWD_FX_SIZE: - pytest.skip("Fixed input size model > limit.") + input_size = _get_input_size(model_name=model_name, target=TARGET_BWD_FX_SIZE) + if max(input_size) > MAX_BWD_FX_SIZE: + pytest.skip("Fixed input size model > limit.") - model = create_model(model_name, pretrained=False, num_classes=42) - model.train() - num_params = sum([x.numel() for x in model.parameters()]) - if 'GITHUB_ACTIONS' in os.environ and num_params > 100e6: - pytest.skip("Skipping FX backward test on model with more than 100M params.") + model = create_model(model_name, pretrained=False, num_classes=42) + model.train() + num_params = sum([x.numel() for x in model.parameters()]) + if 'GITHUB_ACTIONS' in os.environ and num_params > 100e6: + pytest.skip("Skipping FX backward test on model with more than 100M params.") - model = _create_fx_model(model, train=True) - outputs = tuple(model(torch.randn((batch_size, *input_size))).values()) - if isinstance(outputs, tuple): - outputs = torch.cat(outputs) - outputs.mean().backward() - for n, x in model.named_parameters(): - assert x.grad is not None, f'No gradient for {n}' - num_grad = sum([x.grad.numel() for x in model.parameters() if x.grad is not None]) + model = _create_fx_model(model, train=True) + outputs = tuple(model(torch.randn((batch_size, *input_size))).values()) + if isinstance(outputs, tuple): + outputs = torch.cat(outputs) + outputs.mean().backward() + for n, x in model.named_parameters(): + assert x.grad is not None, f'No gradient for {n}' + num_grad = sum([x.grad.numel() for x in model.parameters() if x.grad is not None]) - assert outputs.shape[-1] == 42 - assert num_params == num_grad, 'Some parameters are missing gradients' - assert not torch.isnan(outputs).any(), 'Output included NaNs' + assert outputs.shape[-1] == 42 + assert num_params == num_grad, 'Some parameters are missing gradients' + assert not torch.isnan(outputs).any(), 'Output included NaNs' -if 'GITHUB_ACTIONS' not in os.environ: - # FIXME this test is causing GitHub actions to run out of RAM and abruptly kill the test process + if 'GITHUB_ACTIONS' not in os.environ: + # FIXME this test is causing GitHub actions to run out of RAM and abruptly kill the test process - # reason: model is scripted after fx tracing, but beit has torch.jit.is_scripting() control flow - EXCLUDE_FX_JIT_FILTERS = [ - 'deit_*_distilled_patch16_224', - 'levit*', - 'pit_*_distilled_224', - ] + EXCLUDE_FX_FILTERS + # reason: model is scripted after fx tracing, but beit has torch.jit.is_scripting() control flow + EXCLUDE_FX_JIT_FILTERS = [ + 'deit_*_distilled_patch16_224', + 'levit*', + 'pit_*_distilled_224', + ] + EXCLUDE_FX_FILTERS - @pytest.mark.timeout(120) - @pytest.mark.parametrize( - 'model_name', list_models( - exclude_filters=EXCLUDE_FILTERS + EXCLUDE_JIT_FILTERS + EXCLUDE_FX_JIT_FILTERS, name_matches_cfg=True)) - @pytest.mark.parametrize('batch_size', [1]) - def test_model_forward_fx_torchscript(model_name, batch_size): - """Symbolically trace each model, script it, and run single forward pass""" - if not has_fx_feature_extraction: - pytest.skip("Can't test FX. Torch >= 1.10 and Torchvision >= 0.11 are required.") + @pytest.mark.timeout(120) + @pytest.mark.parametrize( + 'model_name', list_models( + exclude_filters=EXCLUDE_FILTERS + EXCLUDE_JIT_FILTERS + EXCLUDE_FX_JIT_FILTERS, name_matches_cfg=True)) + @pytest.mark.parametrize('batch_size', [1]) + def test_model_forward_fx_torchscript(model_name, batch_size): + """Symbolically trace each model, script it, and run single forward pass""" + if not has_fx_feature_extraction: + pytest.skip("Can't test FX. Torch >= 1.10 and Torchvision >= 0.11 are required.") - input_size = _get_input_size(model_name=model_name, target=TARGET_JIT_SIZE) - if max(input_size) > MAX_JIT_SIZE: - pytest.skip("Fixed input size model > limit.") + input_size = _get_input_size(model_name=model_name, target=TARGET_JIT_SIZE) + if max(input_size) > MAX_JIT_SIZE: + pytest.skip("Fixed input size model > limit.") - with set_scriptable(True): - model = create_model(model_name, pretrained=False) - model.eval() + with set_scriptable(True): + model = create_model(model_name, pretrained=False) + model.eval() - model = torch.jit.script(_create_fx_model(model)) - with torch.no_grad(): - outputs = tuple(model(torch.randn((batch_size, *input_size))).values()) - if isinstance(outputs, tuple): - outputs = torch.cat(outputs) + model = torch.jit.script(_create_fx_model(model)) + with torch.no_grad(): + outputs = tuple(model(torch.randn((batch_size, *input_size))).values()) + if isinstance(outputs, tuple): + outputs = torch.cat(outputs) - assert outputs.shape[0] == batch_size - assert not torch.isnan(outputs).any(), 'Output included NaNs' + assert outputs.shape[0] == batch_size + assert not torch.isnan(outputs).any(), 'Output included NaNs' diff --git a/timm/models/beit.py b/timm/models/beit.py index a56653dd..a2083a4a 100644 --- a/timm/models/beit.py +++ b/timm/models/beit.py @@ -182,8 +182,8 @@ class Block(nn.Module): self.mlp = Mlp(in_features=dim, hidden_features=mlp_hidden_dim, act_layer=act_layer, drop=drop) if init_values: - self.gamma_1 = nn.Parameter(init_values * torch.ones(dim), requires_grad=True) - self.gamma_2 = nn.Parameter(init_values * torch.ones(dim), requires_grad=True) + self.gamma_1 = nn.Parameter(init_values * torch.ones(dim)) + self.gamma_2 = nn.Parameter(init_values * torch.ones(dim)) else: self.gamma_1, self.gamma_2 = None, None diff --git a/timm/models/cait.py b/timm/models/cait.py index bcc91497..c0892099 100644 --- a/timm/models/cait.py +++ b/timm/models/cait.py @@ -122,8 +122,8 @@ class LayerScaleBlockClassAttn(nn.Module): self.norm2 = norm_layer(dim) mlp_hidden_dim = int(dim * mlp_ratio) self.mlp = mlp_block(in_features=dim, hidden_features=mlp_hidden_dim, act_layer=act_layer, drop=drop) - self.gamma_1 = nn.Parameter(init_values * torch.ones((dim)), requires_grad=True) - self.gamma_2 = nn.Parameter(init_values * torch.ones((dim)), requires_grad=True) + self.gamma_1 = nn.Parameter(init_values * torch.ones(dim)) + self.gamma_2 = nn.Parameter(init_values * torch.ones(dim)) def forward(self, x, x_cls): u = torch.cat((x_cls, x), dim=1) @@ -189,8 +189,8 @@ class LayerScaleBlock(nn.Module): self.norm2 = norm_layer(dim) mlp_hidden_dim = int(dim * mlp_ratio) self.mlp = mlp_block(in_features=dim, hidden_features=mlp_hidden_dim, act_layer=act_layer, drop=drop) - self.gamma_1 = nn.Parameter(init_values * torch.ones((dim)), requires_grad=True) - self.gamma_2 = nn.Parameter(init_values * torch.ones((dim)), requires_grad=True) + self.gamma_1 = nn.Parameter(init_values * torch.ones(dim)) + self.gamma_2 = nn.Parameter(init_values * torch.ones(dim)) def forward(self, x): x = x + self.drop_path(self.gamma_1 * self.attn(self.norm1(x))) diff --git a/timm/models/convnext.py b/timm/models/convnext.py index be0c9a66..4b22c929 100644 --- a/timm/models/convnext.py +++ b/timm/models/convnext.py @@ -42,11 +42,15 @@ default_cfgs = dict( convnext_base=_cfg(url="https://dl.fbaipublicfiles.com/convnext/convnext_base_1k_224_ema.pth"), convnext_large=_cfg(url="https://dl.fbaipublicfiles.com/convnext/convnext_large_1k_224_ema.pth"), + # timm specific variants + convnext_nano=_cfg( + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-rsb-weights/convnext_nano_d1h-7eb4bdea.pth', + crop_pct=0.95, test_input_size=(3, 288, 288), test_crop_pct=1.0), convnext_nano_hnf=_cfg(url=''), convnext_nano_ols=_cfg(url=''), convnext_tiny_hnf=_cfg( url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-rsb-weights/convnext_tiny_hnf_a2h-ab7e9df2.pth', - crop_pct=0.95), + crop_pct=0.95, test_input_size=(3, 288, 288), test_crop_pct=1.0), convnext_tiny_in22ft1k=_cfg( url='https://dl.fbaipublicfiles.com/convnext/convnext_tiny_22k_1k_224.pth'), @@ -109,6 +113,7 @@ class ConvNeXtBlock(nn.Module): dim, dim_out=None, stride=1, + dilation=1, mlp_ratio=4, conv_mlp=False, conv_bias=True, @@ -124,7 +129,8 @@ class ConvNeXtBlock(nn.Module): mlp_layer = ConvMlp if conv_mlp else Mlp self.use_conv_mlp = conv_mlp - self.conv_dw = create_conv2d(dim, dim_out, kernel_size=7, stride=stride, depthwise=True, bias=conv_bias) + self.conv_dw = create_conv2d( + dim, dim_out, kernel_size=7, stride=stride, dilation=dilation, depthwise=True, bias=conv_bias) self.norm = norm_layer(dim_out) self.mlp = mlp_layer(dim_out, int(mlp_ratio * dim_out), act_layer=act_layer) self.gamma = nn.Parameter(ls_init_value * torch.ones(dim_out)) if ls_init_value > 0 else None @@ -156,6 +162,7 @@ class ConvNeXtStage(nn.Module): out_chs, stride=2, depth=2, + dilation=(1, 1), drop_path_rates=None, ls_init_value=1.0, conv_mlp=False, @@ -166,10 +173,14 @@ class ConvNeXtStage(nn.Module): super().__init__() self.grad_checkpointing = False - if in_chs != out_chs or stride > 1: + if in_chs != out_chs or stride > 1 or dilation[0] != dilation[1]: + ds_ks = 2 if stride > 1 or dilation[0] != dilation[1] else 1 + pad = 'same' if dilation[1] > 1 else 0 # same padding needed if dilation used self.downsample = nn.Sequential( norm_layer(in_chs), - nn.Conv2d(in_chs, out_chs, kernel_size=stride, stride=stride, bias=conv_bias), + create_conv2d( + in_chs, out_chs, kernel_size=ds_ks, stride=stride, + dilation=dilation[0], padding=pad, bias=conv_bias), ) in_chs = out_chs else: @@ -181,6 +192,7 @@ class ConvNeXtStage(nn.Module): stage_blocks.append(ConvNeXtBlock( dim=in_chs, dim_out=out_chs, + dilation=dilation[1], drop_path=drop_path_rates[i], ls_init_value=ls_init_value, conv_mlp=conv_mlp, @@ -235,7 +247,7 @@ class ConvNeXt(nn.Module): drop_path_rate=0., ): super().__init__() - assert output_stride == 32 + assert output_stride in (8, 16, 32) if norm_layer is None: norm_layer = partial(LayerNorm2d, eps=1e-6) norm_layer_cl = norm_layer if conv_mlp else partial(nn.LayerNorm, eps=1e-6) @@ -263,22 +275,27 @@ class ConvNeXt(nn.Module): padding=stem_kernel_size // 2, bias=conv_bias), norm_layer(dims[0]), ) - prev_chs = dims[0] - curr_stride = stem_stride self.stages = nn.Sequential() dp_rates = [x.tolist() for x in torch.linspace(0, drop_path_rate, sum(depths)).split(depths)] stages = [] + prev_chs = dims[0] + curr_stride = stem_stride + dilation = 1 # 4 feature resolution stages, each consisting of multiple residual blocks for i in range(4): stride = 2 if curr_stride == 2 or i > 0 else 1 - # FIXME support dilation / output_stride + if curr_stride >= output_stride and stride > 1: + dilation *= stride + stride = 1 curr_stride *= stride + first_dilation = 1 if dilation in (1, 2) else 2 out_chs = dims[i] stages.append(ConvNeXtStage( prev_chs, out_chs, stride=stride, + dilation=(first_dilation, dilation), depth=depths[i], drop_path_rates=dp_rates[i], ls_init_value=ls_init_value, @@ -397,8 +414,18 @@ def _create_convnext(variant, pretrained=False, **kwargs): return model +@register_model +def convnext_nano(pretrained=False, **kwargs): + # timm nano variant with standard stem and head + model_args = dict( + depths=(2, 2, 8, 2), dims=(80, 160, 320, 640), conv_mlp=True, **kwargs) + model = _create_convnext('convnext_nano', pretrained=pretrained, **model_args) + return model + + @register_model def convnext_nano_hnf(pretrained=False, **kwargs): + # experimental nano variant with normalization before pooling in head (head norm first) model_args = dict( depths=(2, 2, 8, 2), dims=(80, 160, 320, 640), head_norm_first=True, conv_mlp=True, **kwargs) model = _create_convnext('convnext_nano_hnf', pretrained=pretrained, **model_args) @@ -407,23 +434,17 @@ def convnext_nano_hnf(pretrained=False, **kwargs): @register_model def convnext_nano_ols(pretrained=False, **kwargs): + # experimental nano variant with overlapping conv stem model_args = dict( - depths=(2, 2, 8, 2), dims=(80, 160, 320, 640), head_norm_first=True, conv_mlp=True, - conv_bias=False, stem_type='overlap', stem_kernel_size=9, **kwargs) + depths=(2, 2, 8, 2), dims=(80, 160, 320, 640), conv_mlp=True, + stem_type='overlap', stem_kernel_size=9, **kwargs) model = _create_convnext('convnext_nano_ols', pretrained=pretrained, **model_args) return model @register_model def convnext_tiny_hnf(pretrained=False, **kwargs): - model_args = dict( - depths=(3, 3, 9, 3), dims=(96, 192, 384, 768), head_norm_first=True, conv_mlp=True, **kwargs) - model = _create_convnext('convnext_tiny_hnf', pretrained=pretrained, **model_args) - return model - - -@register_model -def convnext_tiny_hnfd(pretrained=False, **kwargs): + # experimental tiny variant with norm before pooling in head (head norm first) model_args = dict( depths=(3, 3, 9, 3), dims=(96, 192, 384, 768), head_norm_first=True, conv_mlp=True, **kwargs) model = _create_convnext('convnext_tiny_hnf', pretrained=pretrained, **model_args) diff --git a/timm/models/cspnet.py b/timm/models/cspnet.py index e8e8910e..2c09e7e3 100644 --- a/timm/models/cspnet.py +++ b/timm/models/cspnet.py @@ -23,7 +23,7 @@ import torch.nn.functional as F from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD from .helpers import build_model_with_cfg, named_apply, MATCH_PREV_GROUP -from .layers import ClassifierHead, ConvNormAct, ConvNormActAa, DropPath, create_attn, create_act_layer, make_divisible +from .layers import ClassifierHead, ConvNormAct, ConvNormActAa, DropPath, get_attn, create_act_layer, make_divisible from .registry import register_model @@ -57,9 +57,10 @@ default_cfgs = { 'sedarknet21': _cfg(url=''), 'darknet53': _cfg( url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/darknet53_256_c2ns-3aeff817.pth', - interpolation='bicubic', test_input_size=(3, 288, 288), test_crop_pct=1.0, - ), - 'darknetaa53': _cfg(url=''), + interpolation='bicubic', test_input_size=(3, 288, 288), test_crop_pct=1.0), + 'darknetaa53': _cfg( + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/darknetaa53_c2ns-5c28ec8a.pth', + test_input_size=(3, 288, 288), test_crop_pct=1.0), 'cs3darknet_s': _cfg( url='', interpolation='bicubic'), @@ -71,7 +72,8 @@ default_cfgs = { url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/cs3darknet_l_c2ns-16220c5d.pth', interpolation='bicubic', test_input_size=(3, 288, 288), test_crop_pct=0.95), 'cs3darknet_x': _cfg( - url=''), + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/cs3darknet_x_c2ns-4e4490aa.pth', + interpolation='bicubic', crop_pct=0.95, test_input_size=(3, 288, 288), test_crop_pct=1.0), 'cs3darknet_focus_s': _cfg( url='', interpolation='bicubic'), @@ -84,8 +86,22 @@ default_cfgs = { 'cs3darknet_focus_x': _cfg( url='', interpolation='bicubic'), + 'cs3sedarknet_l': _cfg( + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/cs3sedarknet_l_c2ns-e8d1dc13.pth', + interpolation='bicubic', test_input_size=(3, 288, 288), test_crop_pct=0.95), + 'cs3sedarknet_x': _cfg( + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/cs3sedarknet_x_c2ns-b4d0abc0.pth', + interpolation='bicubic', test_input_size=(3, 288, 288), test_crop_pct=1.0), + 'cs3sedarknet_xdw': _cfg( url='', interpolation='bicubic'), + + 'cs3edgenet_x': _cfg( + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/cs3edgenet_x_c2-2e1610a9.pth', + interpolation='bicubic', test_input_size=(3, 288, 288), test_crop_pct=1.0), + 'cs3se_edgenet_x': _cfg( + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/cs3se_edgenet_x_c2ns-76f8e3ac.pth', + interpolation='bicubic', crop_pct=0.95, test_input_size=(3, 320, 320), test_crop_pct=1.0), } @@ -119,6 +135,7 @@ class CspStagesCfg: bottle_ratio: Union[float, Tuple[float, ...]] = 1. # bottleneck-ratio of blocks in stage avg_down: Union[bool, Tuple[bool, ...]] = False attn_layer: Optional[Union[str, Tuple[str, ...]]] = None + attn_kwargs: Optional[Union[Dict, Tuple[Dict]]] = None stage_type: Union[str, Tuple[str]] = 'csp' # stage type ('csp', 'cs2', 'dark') block_type: Union[str, Tuple[str]] = 'bottle' # blocks type for stages ('bottle', 'dark') @@ -136,6 +153,7 @@ class CspStagesCfg: self.bottle_ratio = _pad_arg(self.bottle_ratio, n) self.avg_down = _pad_arg(self.avg_down, n) self.attn_layer = _pad_arg(self.attn_layer, n) + self.attn_kwargs = _pad_arg(self.attn_kwargs, n) self.stage_type = _pad_arg(self.stage_type, n) self.block_type = _pad_arg(self.block_type, n) @@ -149,12 +167,22 @@ class CspModelCfg: stem: CspStemCfg stages: CspStagesCfg zero_init_last: bool = True # zero init last weight (usually bn) in residual path - act_layer: str = 'relu' + act_layer: str = 'leaky_relu' norm_layer: str = 'batchnorm' aa_layer: Optional[str] = None # FIXME support string factory for this -def _cs3darknet_cfg(width_multiplier=1.0, depth_multiplier=1.0, avg_down=False, act_layer='silu', focus=False): +def _cs3_cfg( + width_multiplier=1.0, + depth_multiplier=1.0, + avg_down=False, + act_layer='silu', + focus=False, + attn_layer=None, + attn_kwargs=None, + bottle_ratio=1.0, + block_type='dark', +): if focus: stem_cfg = CspStemCfg( out_chs=make_divisible(64 * width_multiplier), @@ -169,11 +197,13 @@ def _cs3darknet_cfg(width_multiplier=1.0, depth_multiplier=1.0, avg_down=False, out_chs=tuple([make_divisible(c * width_multiplier) for c in (128, 256, 512, 1024)]), depth=tuple([int(d * depth_multiplier) for d in (3, 6, 9, 3)]), stride=2, - bottle_ratio=1., + bottle_ratio=bottle_ratio, block_ratio=0.5, avg_down=avg_down, + attn_layer=attn_layer, + attn_kwargs=attn_kwargs, stage_type='cs3', - block_type='dark', + block_type=block_type, ), act_layer=act_layer, ) @@ -201,7 +231,7 @@ model_cfgs = dict( bottle_ratio=0.5, block_ratio=1., cross_linear=True, - ) + ), ), cspresnet50w=CspModelCfg( stem=CspStemCfg(out_chs=(32, 32, 64), kernel_size=3, stride=4, pool='max'), @@ -213,7 +243,7 @@ model_cfgs = dict( bottle_ratio=0.25, block_ratio=0.5, cross_linear=True, - ) + ), ), cspresnext50=CspModelCfg( stem=CspStemCfg(out_chs=64, kernel_size=7, stride=4, pool='max'), @@ -226,7 +256,7 @@ model_cfgs = dict( bottle_ratio=1., block_ratio=0.5, cross_linear=True, - ) + ), ), cspdarknet53=CspModelCfg( stem=CspStemCfg(out_chs=32, kernel_size=3, stride=1, pool=''), @@ -240,7 +270,6 @@ model_cfgs = dict( down_growth=True, block_type='dark', ), - act_layer='leaky_relu', ), darknet17=CspModelCfg( stem=CspStemCfg(out_chs=32, kernel_size=3, stride=1, pool=''), @@ -253,7 +282,6 @@ model_cfgs = dict( stage_type='dark', block_type='dark', ), - act_layer='leaky_relu', ), darknet21=CspModelCfg( stem=CspStemCfg(out_chs=32, kernel_size=3, stride=1, pool=''), @@ -267,7 +295,6 @@ model_cfgs = dict( block_type='dark', ), - act_layer='leaky_relu', ), sedarknet21=CspModelCfg( stem=CspStemCfg(out_chs=32, kernel_size=3, stride=1, pool=''), @@ -282,7 +309,6 @@ model_cfgs = dict( block_type='dark', ), - act_layer='leaky_relu', ), darknet53=CspModelCfg( stem=CspStemCfg(out_chs=32, kernel_size=3, stride=1, pool=''), @@ -295,7 +321,6 @@ model_cfgs = dict( stage_type='dark', block_type='dark', ), - act_layer='leaky_relu', ), darknetaa53=CspModelCfg( stem=CspStemCfg(out_chs=32, kernel_size=3, stride=1, pool=''), @@ -309,18 +334,20 @@ model_cfgs = dict( stage_type='dark', block_type='dark', ), - act_layer='leaky_relu', ), - cs3darknet_s=_cs3darknet_cfg(width_multiplier=0.5, depth_multiplier=0.5), - cs3darknet_m=_cs3darknet_cfg(width_multiplier=0.75, depth_multiplier=0.67), - cs3darknet_l=_cs3darknet_cfg(), - cs3darknet_x=_cs3darknet_cfg(width_multiplier=1.25, depth_multiplier=1.33), + cs3darknet_s=_cs3_cfg(width_multiplier=0.5, depth_multiplier=0.5), + cs3darknet_m=_cs3_cfg(width_multiplier=0.75, depth_multiplier=0.67), + cs3darknet_l=_cs3_cfg(), + cs3darknet_x=_cs3_cfg(width_multiplier=1.25, depth_multiplier=1.33), + + cs3darknet_focus_s=_cs3_cfg(width_multiplier=0.5, depth_multiplier=0.5, focus=True), + cs3darknet_focus_m=_cs3_cfg(width_multiplier=0.75, depth_multiplier=0.67, focus=True), + cs3darknet_focus_l=_cs3_cfg(focus=True), + cs3darknet_focus_x=_cs3_cfg(width_multiplier=1.25, depth_multiplier=1.33, focus=True), - cs3darknet_focus_s=_cs3darknet_cfg(width_multiplier=0.5, depth_multiplier=0.5, focus=True), - cs3darknet_focus_m=_cs3darknet_cfg(width_multiplier=0.75, depth_multiplier=0.67, focus=True), - cs3darknet_focus_l=_cs3darknet_cfg(focus=True), - cs3darknet_focus_x=_cs3darknet_cfg(width_multiplier=1.25, depth_multiplier=1.33, focus=True), + cs3sedarknet_l=_cs3_cfg(attn_layer='se', attn_kwargs=dict(rd_ratio=.25)), + cs3sedarknet_x=_cs3_cfg(attn_layer='se', width_multiplier=1.25, depth_multiplier=1.33), cs3sedarknet_xdw=CspModelCfg( stem=CspStemCfg(out_chs=(32, 64), kernel_size=3, stride=2, pool=''), @@ -333,7 +360,13 @@ model_cfgs = dict( block_ratio=0.5, attn_layer='se', ), + act_layer='silu', ), + + cs3edgenet_x=_cs3_cfg(width_multiplier=1.25, depth_multiplier=1.33, bottle_ratio=1.5, block_type='edge'), + cs3se_edgenet_x=_cs3_cfg( + width_multiplier=1.25, depth_multiplier=1.33, bottle_ratio=1.5, block_type='edge', + attn_layer='se', attn_kwargs=dict(rd_ratio=.25)), ) @@ -352,21 +385,22 @@ class BottleneckBlock(nn.Module): norm_layer=nn.BatchNorm2d, attn_last=False, attn_layer=None, - aa_layer=None, drop_block=None, drop_path=0. ): super(BottleneckBlock, self).__init__() mid_chs = int(round(out_chs * bottle_ratio)) ckwargs = dict(act_layer=act_layer, norm_layer=norm_layer) + attn_last = attn_layer is not None and attn_last + attn_first = attn_layer is not None and not attn_last self.conv1 = ConvNormAct(in_chs, mid_chs, kernel_size=1, **ckwargs) - self.conv2 = ConvNormActAa( + self.conv2 = ConvNormAct( mid_chs, mid_chs, kernel_size=3, dilation=dilation, groups=groups, - aa_layer=aa_layer, drop_layer=drop_block, **ckwargs) - self.attn2 = create_attn(attn_layer, channels=mid_chs) if not attn_last else None + drop_layer=drop_block, **ckwargs) + self.attn2 = attn_layer(mid_chs, act_layer=act_layer) if attn_first else nn.Identity() self.conv3 = ConvNormAct(mid_chs, out_chs, kernel_size=1, apply_act=False, **ckwargs) - self.attn3 = create_attn(attn_layer, channels=out_chs) if attn_last else None + self.attn3 = attn_layer(out_chs, act_layer=act_layer) if attn_last else nn.Identity() self.drop_path = DropPath(drop_path) if drop_path else nn.Identity() self.act3 = create_act_layer(act_layer) @@ -377,11 +411,9 @@ class BottleneckBlock(nn.Module): shortcut = x x = self.conv1(x) x = self.conv2(x) - if self.attn2 is not None: - x = self.attn2(x) + x = self.attn2(x) x = self.conv3(x) - if self.attn3 is not None: - x = self.attn3(x) + x = self.attn3(x) x = self.drop_path(x) + shortcut # FIXME partial shortcut needed if first block handled as per original, not used for my current impl #x[:, :shortcut.size(1)] += shortcut @@ -403,18 +435,58 @@ class DarkBlock(nn.Module): act_layer=nn.ReLU, norm_layer=nn.BatchNorm2d, attn_layer=None, - aa_layer=None, drop_block=None, drop_path=0. ): super(DarkBlock, self).__init__() mid_chs = int(round(out_chs * bottle_ratio)) ckwargs = dict(act_layer=act_layer, norm_layer=norm_layer) + self.conv1 = ConvNormAct(in_chs, mid_chs, kernel_size=1, **ckwargs) - self.conv2 = ConvNormActAa( + self.attn = attn_layer(mid_chs, act_layer=act_layer) if attn_layer is not None else nn.Identity() + self.conv2 = ConvNormAct( mid_chs, out_chs, kernel_size=3, dilation=dilation, groups=groups, - aa_layer=aa_layer, drop_layer=drop_block, **ckwargs) - self.attn = create_attn(attn_layer, channels=out_chs, act_layer=act_layer) + drop_layer=drop_block, **ckwargs) + self.drop_path = DropPath(drop_path) if drop_path else nn.Identity() + + def zero_init_last(self): + nn.init.zeros_(self.conv2.bn.weight) + + def forward(self, x): + shortcut = x + x = self.conv1(x) + x = self.attn(x) + x = self.conv2(x) + x = self.drop_path(x) + shortcut + return x + + +class EdgeBlock(nn.Module): + """ EdgeResidual / Fused-MBConv / MobileNetV1-like 3x3 + 1x1 block (w/ activated output) + """ + + def __init__( + self, + in_chs, + out_chs, + dilation=1, + bottle_ratio=0.5, + groups=1, + act_layer=nn.ReLU, + norm_layer=nn.BatchNorm2d, + attn_layer=None, + drop_block=None, + drop_path=0. + ): + super(EdgeBlock, self).__init__() + mid_chs = int(round(out_chs * bottle_ratio)) + ckwargs = dict(act_layer=act_layer, norm_layer=norm_layer) + + self.conv1 = ConvNormAct( + in_chs, mid_chs, kernel_size=3, dilation=dilation, groups=groups, + drop_layer=drop_block, **ckwargs) + self.attn = attn_layer(mid_chs, act_layer=act_layer) if attn_layer is not None else nn.Identity() + self.conv2 = ConvNormAct(mid_chs, out_chs, kernel_size=1, **ckwargs) self.drop_path = DropPath(drop_path) if drop_path else nn.Identity() def zero_init_last(self): @@ -423,9 +495,8 @@ class DarkBlock(nn.Module): def forward(self, x): shortcut = x x = self.conv1(x) + x = self.attn(x) x = self.conv2(x) - if self.attn is not None: - x = self.attn(x) x = self.drop_path(x) + shortcut return x @@ -457,6 +528,7 @@ class CrossStage(nn.Module): self.expand_chs = exp_chs = int(round(out_chs * expand_ratio)) block_out_chs = int(round(out_chs * block_ratio)) conv_kwargs = dict(act_layer=block_kwargs.get('act_layer'), norm_layer=block_kwargs.get('norm_layer')) + aa_layer = block_kwargs.pop('aa_layer', None) if stride != 1 or first_dilation != dilation: if avg_down: @@ -467,7 +539,7 @@ class CrossStage(nn.Module): else: self.conv_down = ConvNormActAa( in_chs, down_chs, kernel_size=3, stride=stride, dilation=first_dilation, groups=groups, - aa_layer=block_kwargs.get('aa_layer', None), **conv_kwargs) + aa_layer=aa_layer, **conv_kwargs) prev_chs = down_chs else: self.conv_down = nn.Identity() @@ -535,6 +607,7 @@ class CrossStage3(nn.Module): self.expand_chs = exp_chs = int(round(out_chs * expand_ratio)) block_out_chs = int(round(out_chs * block_ratio)) conv_kwargs = dict(act_layer=block_kwargs.get('act_layer'), norm_layer=block_kwargs.get('norm_layer')) + aa_layer = block_kwargs.pop('aa_layer', None) if stride != 1 or first_dilation != dilation: if avg_down: @@ -545,7 +618,7 @@ class CrossStage3(nn.Module): else: self.conv_down = ConvNormActAa( in_chs, down_chs, kernel_size=3, stride=stride, dilation=first_dilation, groups=groups, - aa_layer=block_kwargs.get('aa_layer', None), **conv_kwargs) + aa_layer=aa_layer, **conv_kwargs) prev_chs = down_chs else: self.conv_down = None @@ -602,6 +675,7 @@ class DarkStage(nn.Module): super(DarkStage, self).__init__() first_dilation = first_dilation or dilation conv_kwargs = dict(act_layer=block_kwargs.get('act_layer'), norm_layer=block_kwargs.get('norm_layer')) + aa_layer = block_kwargs.pop('aa_layer', None) if avg_down: self.conv_down = nn.Sequential( @@ -611,7 +685,7 @@ class DarkStage(nn.Module): else: self.conv_down = ConvNormActAa( in_chs, out_chs, kernel_size=3, stride=stride, dilation=first_dilation, groups=groups, - aa_layer=block_kwargs.get('aa_layer', None), **conv_kwargs) + aa_layer=aa_layer, **conv_kwargs) prev_chs = out_chs block_out_chs = int(round(out_chs * block_ratio)) @@ -688,7 +762,8 @@ def create_csp_stem( return stem, feature_info -def _get_stage_fn(stage_type: str, stage_args): +def _get_stage_fn(stage_args): + stage_type = stage_args.pop('stage_type') assert stage_type in ('dark', 'csp', 'cs3') if stage_type == 'dark': stage_args.pop('expand_ratio', None) @@ -702,14 +777,27 @@ def _get_stage_fn(stage_type: str, stage_args): return stage_fn, stage_args -def _get_block_fn(stage_type: str, stage_args): - assert stage_type in ('dark', 'bottle') - if stage_type == 'dark': +def _get_block_fn(stage_args): + block_type = stage_args.pop('block_type') + assert block_type in ('dark', 'edge', 'bottle') + if block_type == 'dark': return DarkBlock, stage_args + elif block_type == 'edge': + return EdgeBlock, stage_args else: return BottleneckBlock, stage_args +def _get_attn_fn(stage_args): + attn_layer = stage_args.pop('attn_layer') + attn_kwargs = stage_args.pop('attn_kwargs', None) or {} + if attn_layer is not None: + attn_layer = get_attn(attn_layer) + if attn_kwargs: + attn_layer = partial(attn_layer, **attn_kwargs) + return attn_layer, stage_args + + def create_csp_stages( cfg: CspModelCfg, drop_path_rate: float, @@ -724,7 +812,6 @@ def create_csp_stages( block_kwargs = dict( act_layer=cfg.act_layer, norm_layer=cfg.norm_layer, - aa_layer=cfg.aa_layer ) dilation = 1 @@ -734,8 +821,9 @@ def create_csp_stages( feature_info = [] stages = [] for stage_idx, stage_args in enumerate(stage_args): - stage_fn, stage_args = _get_stage_fn(stage_args.pop('stage_type'), stage_args) - block_fn, stage_args = _get_block_fn(stage_args.pop('block_type'), stage_args) + stage_fn, stage_args = _get_stage_fn(stage_args) + block_fn, stage_args = _get_block_fn(stage_args) + attn_fn, stage_args = _get_attn_fn(stage_args) stride = stage_args.pop('stride') if stride != 1 and prev_feat: feature_info.append(prev_feat) @@ -752,6 +840,8 @@ def create_csp_stages( first_dilation=first_dilation, dilation=dilation, block_fn=block_fn, + aa_layer=cfg.aa_layer, + attn_layer=attn_fn, # will be passed through stage as block_kwargs **block_kwargs, )] prev_chs = stage_args['out_chs'] @@ -968,6 +1058,26 @@ def cs3darknet_focus_x(pretrained=False, **kwargs): return _create_cspnet('cs3darknet_focus_x', pretrained=pretrained, **kwargs) +@register_model +def cs3sedarknet_l(pretrained=False, **kwargs): + return _create_cspnet('cs3sedarknet_l', pretrained=pretrained, **kwargs) + + +@register_model +def cs3sedarknet_x(pretrained=False, **kwargs): + return _create_cspnet('cs3sedarknet_x', pretrained=pretrained, **kwargs) + + @register_model def cs3sedarknet_xdw(pretrained=False, **kwargs): return _create_cspnet('cs3sedarknet_xdw', pretrained=pretrained, **kwargs) + + +@register_model +def cs3edgenet_x(pretrained=False, **kwargs): + return _create_cspnet('cs3edgenet_x', pretrained=pretrained, **kwargs) + + +@register_model +def cs3se_edgenet_x(pretrained=False, **kwargs): + return _create_cspnet('cs3se_edgenet_x', pretrained=pretrained, **kwargs) \ No newline at end of file diff --git a/timm/models/deit.py b/timm/models/deit.py index 8cb36bd6..3205b024 100644 --- a/timm/models/deit.py +++ b/timm/models/deit.py @@ -64,6 +64,8 @@ default_cfgs = { 'deit3_small_patch16_384': _cfg( url='https://dl.fbaipublicfiles.com/deit/deit_3_small_384_1k.pth', input_size=(3, 384, 384), crop_pct=1.0), + 'deit3_medium_patch16_224': _cfg( + url='https://dl.fbaipublicfiles.com/deit/deit_3_medium_224_1k.pth'), 'deit3_base_patch16_224': _cfg( url='https://dl.fbaipublicfiles.com/deit/deit_3_base_224_1k.pth'), 'deit3_base_patch16_384': _cfg( @@ -83,6 +85,9 @@ default_cfgs = { 'deit3_small_patch16_384_in21ft1k': _cfg( url='https://dl.fbaipublicfiles.com/deit/deit_3_small_384_21k.pth', input_size=(3, 384, 384), crop_pct=1.0), + 'deit3_medium_patch16_224_in21ft1k': _cfg( + url='https://dl.fbaipublicfiles.com/deit/deit_3_medium_224_21k.pth', + crop_pct=1.0), 'deit3_base_patch16_224_in21ft1k': _cfg( url='https://dl.fbaipublicfiles.com/deit/deit_3_base_224_21k.pth', crop_pct=1.0), @@ -290,6 +295,17 @@ def deit3_small_patch16_384(pretrained=False, **kwargs): return model +@register_model +def deit3_medium_patch16_224(pretrained=False, **kwargs): + """ DeiT-3 medium model @ 224x224 (https://arxiv.org/abs/2012.12877). + ImageNet-1k weights from https://github.com/facebookresearch/deit. + """ + model_kwargs = dict( + patch_size=16, embed_dim=512, depth=12, num_heads=8, no_embed_class=True, init_values=1e-6, **kwargs) + model = _create_deit('deit3_medium_patch16_224', pretrained=pretrained, **model_kwargs) + return model + + @register_model def deit3_base_patch16_224(pretrained=False, **kwargs): """ DeiT-3 base model @ 224x224 from paper (https://arxiv.org/abs/2204.07118). @@ -367,6 +383,17 @@ def deit3_small_patch16_384_in21ft1k(pretrained=False, **kwargs): return model +@register_model +def deit3_medium_patch16_224_in21ft1k(pretrained=False, **kwargs): + """ DeiT-3 medium model @ 224x224 (https://arxiv.org/abs/2012.12877). + ImageNet-1k weights from https://github.com/facebookresearch/deit. + """ + model_kwargs = dict( + patch_size=16, embed_dim=512, depth=12, num_heads=8, no_embed_class=True, init_values=1e-6, **kwargs) + model = _create_deit('deit3_medium_patch16_224_in21ft1k', pretrained=pretrained, **model_kwargs) + return model + + @register_model def deit3_base_patch16_224_in21ft1k(pretrained=False, **kwargs): """ DeiT-3 base model @ 224x224 from paper (https://arxiv.org/abs/2204.07118). diff --git a/timm/models/fx_features.py b/timm/models/fx_features.py index a9c05b0a..b09381b7 100644 --- a/timm/models/fx_features.py +++ b/timm/models/fx_features.py @@ -1,7 +1,7 @@ """ PyTorch FX Based Feature Extraction Helpers Using https://pytorch.org/vision/stable/feature_extraction.html """ -from typing import Callable, List, Dict, Union +from typing import Callable, List, Dict, Union, Type import torch from torch import nn @@ -35,7 +35,7 @@ except ImportError: pass -def register_notrace_module(module: nn.Module): +def register_notrace_module(module: Type[nn.Module]): """ Any module not under timm.models.layers should get this decorator if we don't want to trace through it. """ diff --git a/timm/models/hrnet.py b/timm/models/hrnet.py index 7e9b096f..30860120 100644 --- a/timm/models/hrnet.py +++ b/timm/models/hrnet.py @@ -814,45 +814,45 @@ def _create_hrnet(variant, pretrained, **model_kwargs): @register_model -def hrnet_w18_small(pretrained=True, **kwargs): +def hrnet_w18_small(pretrained=False, **kwargs): return _create_hrnet('hrnet_w18_small', pretrained, **kwargs) @register_model -def hrnet_w18_small_v2(pretrained=True, **kwargs): +def hrnet_w18_small_v2(pretrained=False, **kwargs): return _create_hrnet('hrnet_w18_small_v2', pretrained, **kwargs) @register_model -def hrnet_w18(pretrained=True, **kwargs): +def hrnet_w18(pretrained=False, **kwargs): return _create_hrnet('hrnet_w18', pretrained, **kwargs) @register_model -def hrnet_w30(pretrained=True, **kwargs): +def hrnet_w30(pretrained=False, **kwargs): return _create_hrnet('hrnet_w30', pretrained, **kwargs) @register_model -def hrnet_w32(pretrained=True, **kwargs): +def hrnet_w32(pretrained=False, **kwargs): return _create_hrnet('hrnet_w32', pretrained, **kwargs) @register_model -def hrnet_w40(pretrained=True, **kwargs): +def hrnet_w40(pretrained=False, **kwargs): return _create_hrnet('hrnet_w40', pretrained, **kwargs) @register_model -def hrnet_w44(pretrained=True, **kwargs): +def hrnet_w44(pretrained=False, **kwargs): return _create_hrnet('hrnet_w44', pretrained, **kwargs) @register_model -def hrnet_w48(pretrained=True, **kwargs): +def hrnet_w48(pretrained=False, **kwargs): return _create_hrnet('hrnet_w48', pretrained, **kwargs) @register_model -def hrnet_w64(pretrained=True, **kwargs): +def hrnet_w64(pretrained=False, **kwargs): return _create_hrnet('hrnet_w64', pretrained, **kwargs) diff --git a/timm/models/hub.py b/timm/models/hub.py index dd7870cb..c3d3d15e 100644 --- a/timm/models/hub.py +++ b/timm/models/hub.py @@ -14,11 +14,11 @@ except ImportError: from timm import __version__ try: - from huggingface_hub import HfApi, HfFolder, Repository, cached_download, hf_hub_url - cached_download = partial(cached_download, library_name="timm", library_version=__version__) + from huggingface_hub import HfApi, HfFolder, Repository, hf_hub_download, hf_hub_url + hf_hub_download = partial(hf_hub_download, library_name="timm", library_version=__version__) _has_hf_hub = True except ImportError: - cached_download = None + hf_hub_download = None _has_hf_hub = False _logger = logging.getLogger(__name__) @@ -78,8 +78,7 @@ def load_cfg_from_json(json_file: Union[str, os.PathLike]): def _download_from_hf(model_id: str, filename: str): hf_model_id, hf_revision = hf_split(model_id) - url = hf_hub_url(hf_model_id, filename, revision=hf_revision) - return cached_download(url, cache_dir=get_cache_dir('hf')) + return hf_hub_download(hf_model_id, filename, revision=hf_revision, cache_dir=get_cache_dir('hf')) def load_model_config_from_hf(model_id: str): diff --git a/timm/models/mlp_mixer.py b/timm/models/mlp_mixer.py index ff91def6..e07ea6e5 100644 --- a/timm/models/mlp_mixer.py +++ b/timm/models/mlp_mixer.py @@ -85,11 +85,11 @@ default_cfgs = dict( # Mixer ImageNet-21K-P pretraining mixer_b16_224_miil_in21k=_cfg( url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm/mixer_b16_224_miil_in21k.pth', - mean=(0, 0, 0), std=(1, 1, 1), crop_pct=0.875, interpolation='bilinear', num_classes=11221, + mean=(0., 0., 0.), std=(1., 1., 1.), crop_pct=0.875, interpolation='bilinear', num_classes=11221, ), mixer_b16_224_miil=_cfg( url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm/mixer_b16_224_miil.pth', - mean=(0, 0, 0), std=(1, 1, 1), crop_pct=0.875, interpolation='bilinear', + mean=(0., 0., 0.), std=(1., 1., 1.), crop_pct=0.875, interpolation='bilinear', ), gmixer_12_224=_cfg(mean=IMAGENET_DEFAULT_MEAN, std=IMAGENET_DEFAULT_STD), diff --git a/timm/models/mobilenetv3.py b/timm/models/mobilenetv3.py index 4a791857..62e59f9f 100644 --- a/timm/models/mobilenetv3.py +++ b/timm/models/mobilenetv3.py @@ -41,10 +41,10 @@ default_cfgs = { interpolation='bicubic', url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/mobilenetv3_large_100_ra-f55367f5.pth'), 'mobilenetv3_large_100_miil': _cfg( - interpolation='bilinear', mean=(0, 0, 0), std=(1, 1, 1), + interpolation='bilinear', mean=(0., 0., 0.), std=(1., 1., 1.), url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm/mobilenetv3_large_100_1k_miil_78_0.pth'), 'mobilenetv3_large_100_miil_in21k': _cfg( - interpolation='bilinear', mean=(0, 0, 0), std=(1, 1, 1), + interpolation='bilinear', mean=(0., 0., 0.), std=(1., 1., 1.), url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm/mobilenetv3_large_100_in21k_miil.pth', num_classes=11221), 'mobilenetv3_small_050': _cfg( diff --git a/timm/models/mobilevit.py b/timm/models/mobilevit.py index 2a3ab924..bd5479a7 100644 --- a/timm/models/mobilevit.py +++ b/timm/models/mobilevit.py @@ -34,7 +34,7 @@ def _cfg(url='', **kwargs): return { 'url': url, 'num_classes': 1000, 'input_size': (3, 256, 256), 'pool_size': (8, 8), 'crop_pct': 0.9, 'interpolation': 'bicubic', - 'mean': (0, 0, 0), 'std': (1, 1, 1), + 'mean': (0., 0., 0.), 'std': (1., 1., 1.), 'first_conv': 'stem.conv', 'classifier': 'head.fc', 'fixed_input_size': False, **kwargs diff --git a/timm/models/poolformer.py b/timm/models/poolformer.py index a95195b4..09359bc8 100644 --- a/timm/models/poolformer.py +++ b/timm/models/poolformer.py @@ -117,8 +117,8 @@ class PoolFormerBlock(nn.Module): self.drop_path2 = DropPath(drop_path) if drop_path > 0. else nn.Identity() if layer_scale_init_value: - self.layer_scale_1 = nn.Parameter(layer_scale_init_value * torch.ones(dim), requires_grad=True) - self.layer_scale_2 = nn.Parameter(layer_scale_init_value * torch.ones(dim), requires_grad=True) + self.layer_scale_1 = nn.Parameter(layer_scale_init_value * torch.ones(dim)) + self.layer_scale_2 = nn.Parameter(layer_scale_init_value * torch.ones(dim)) else: self.layer_scale_1 = None self.layer_scale_2 = None diff --git a/timm/models/resnet.py b/timm/models/resnet.py index e5a6b791..0ee964b0 100644 --- a/timm/models/resnet.py +++ b/timm/models/resnet.py @@ -1003,7 +1003,7 @@ def tv_resnext50_32x4d(pretrained=False, **kwargs): @register_model -def ig_resnext101_32x8d(pretrained=True, **kwargs): +def ig_resnext101_32x8d(pretrained=False, **kwargs): """Constructs a ResNeXt-101 32x8 model pre-trained on weakly-supervised data and finetuned on ImageNet from Figure 5 in `"Exploring the Limits of Weakly Supervised Pretraining" `_ @@ -1014,7 +1014,7 @@ def ig_resnext101_32x8d(pretrained=True, **kwargs): @register_model -def ig_resnext101_32x16d(pretrained=True, **kwargs): +def ig_resnext101_32x16d(pretrained=False, **kwargs): """Constructs a ResNeXt-101 32x16 model pre-trained on weakly-supervised data and finetuned on ImageNet from Figure 5 in `"Exploring the Limits of Weakly Supervised Pretraining" `_ @@ -1025,7 +1025,7 @@ def ig_resnext101_32x16d(pretrained=True, **kwargs): @register_model -def ig_resnext101_32x32d(pretrained=True, **kwargs): +def ig_resnext101_32x32d(pretrained=False, **kwargs): """Constructs a ResNeXt-101 32x32 model pre-trained on weakly-supervised data and finetuned on ImageNet from Figure 5 in `"Exploring the Limits of Weakly Supervised Pretraining" `_ @@ -1036,7 +1036,7 @@ def ig_resnext101_32x32d(pretrained=True, **kwargs): @register_model -def ig_resnext101_32x48d(pretrained=True, **kwargs): +def ig_resnext101_32x48d(pretrained=False, **kwargs): """Constructs a ResNeXt-101 32x48 model pre-trained on weakly-supervised data and finetuned on ImageNet from Figure 5 in `"Exploring the Limits of Weakly Supervised Pretraining" `_ @@ -1047,7 +1047,7 @@ def ig_resnext101_32x48d(pretrained=True, **kwargs): @register_model -def ssl_resnet18(pretrained=True, **kwargs): +def ssl_resnet18(pretrained=False, **kwargs): """Constructs a semi-supervised ResNet-18 model pre-trained on YFCC100M dataset and finetuned on ImageNet `"Billion-scale Semi-Supervised Learning for Image Classification" `_ Weights from https://github.com/facebookresearch/semi-supervised-ImageNet1K-models/ @@ -1057,7 +1057,7 @@ def ssl_resnet18(pretrained=True, **kwargs): @register_model -def ssl_resnet50(pretrained=True, **kwargs): +def ssl_resnet50(pretrained=False, **kwargs): """Constructs a semi-supervised ResNet-50 model pre-trained on YFCC100M dataset and finetuned on ImageNet `"Billion-scale Semi-Supervised Learning for Image Classification" `_ Weights from https://github.com/facebookresearch/semi-supervised-ImageNet1K-models/ @@ -1067,7 +1067,7 @@ def ssl_resnet50(pretrained=True, **kwargs): @register_model -def ssl_resnext50_32x4d(pretrained=True, **kwargs): +def ssl_resnext50_32x4d(pretrained=False, **kwargs): """Constructs a semi-supervised ResNeXt-50 32x4 model pre-trained on YFCC100M dataset and finetuned on ImageNet `"Billion-scale Semi-Supervised Learning for Image Classification" `_ Weights from https://github.com/facebookresearch/semi-supervised-ImageNet1K-models/ @@ -1077,7 +1077,7 @@ def ssl_resnext50_32x4d(pretrained=True, **kwargs): @register_model -def ssl_resnext101_32x4d(pretrained=True, **kwargs): +def ssl_resnext101_32x4d(pretrained=False, **kwargs): """Constructs a semi-supervised ResNeXt-101 32x4 model pre-trained on YFCC100M dataset and finetuned on ImageNet `"Billion-scale Semi-Supervised Learning for Image Classification" `_ Weights from https://github.com/facebookresearch/semi-supervised-ImageNet1K-models/ @@ -1087,7 +1087,7 @@ def ssl_resnext101_32x4d(pretrained=True, **kwargs): @register_model -def ssl_resnext101_32x8d(pretrained=True, **kwargs): +def ssl_resnext101_32x8d(pretrained=False, **kwargs): """Constructs a semi-supervised ResNeXt-101 32x8 model pre-trained on YFCC100M dataset and finetuned on ImageNet `"Billion-scale Semi-Supervised Learning for Image Classification" `_ Weights from https://github.com/facebookresearch/semi-supervised-ImageNet1K-models/ @@ -1097,7 +1097,7 @@ def ssl_resnext101_32x8d(pretrained=True, **kwargs): @register_model -def ssl_resnext101_32x16d(pretrained=True, **kwargs): +def ssl_resnext101_32x16d(pretrained=False, **kwargs): """Constructs a semi-supervised ResNeXt-101 32x16 model pre-trained on YFCC100M dataset and finetuned on ImageNet `"Billion-scale Semi-Supervised Learning for Image Classification" `_ Weights from https://github.com/facebookresearch/semi-supervised-ImageNet1K-models/ @@ -1107,7 +1107,7 @@ def ssl_resnext101_32x16d(pretrained=True, **kwargs): @register_model -def swsl_resnet18(pretrained=True, **kwargs): +def swsl_resnet18(pretrained=False, **kwargs): """Constructs a semi-weakly supervised Resnet-18 model pre-trained on 1B weakly supervised image dataset and finetuned on ImageNet. `"Billion-scale Semi-Supervised Learning for Image Classification" `_ @@ -1118,7 +1118,7 @@ def swsl_resnet18(pretrained=True, **kwargs): @register_model -def swsl_resnet50(pretrained=True, **kwargs): +def swsl_resnet50(pretrained=False, **kwargs): """Constructs a semi-weakly supervised ResNet-50 model pre-trained on 1B weakly supervised image dataset and finetuned on ImageNet. `"Billion-scale Semi-Supervised Learning for Image Classification" `_ @@ -1129,7 +1129,7 @@ def swsl_resnet50(pretrained=True, **kwargs): @register_model -def swsl_resnext50_32x4d(pretrained=True, **kwargs): +def swsl_resnext50_32x4d(pretrained=False, **kwargs): """Constructs a semi-weakly supervised ResNeXt-50 32x4 model pre-trained on 1B weakly supervised image dataset and finetuned on ImageNet. `"Billion-scale Semi-Supervised Learning for Image Classification" `_ @@ -1140,7 +1140,7 @@ def swsl_resnext50_32x4d(pretrained=True, **kwargs): @register_model -def swsl_resnext101_32x4d(pretrained=True, **kwargs): +def swsl_resnext101_32x4d(pretrained=False, **kwargs): """Constructs a semi-weakly supervised ResNeXt-101 32x4 model pre-trained on 1B weakly supervised image dataset and finetuned on ImageNet. `"Billion-scale Semi-Supervised Learning for Image Classification" `_ @@ -1151,7 +1151,7 @@ def swsl_resnext101_32x4d(pretrained=True, **kwargs): @register_model -def swsl_resnext101_32x8d(pretrained=True, **kwargs): +def swsl_resnext101_32x8d(pretrained=False, **kwargs): """Constructs a semi-weakly supervised ResNeXt-101 32x8 model pre-trained on 1B weakly supervised image dataset and finetuned on ImageNet. `"Billion-scale Semi-Supervised Learning for Image Classification" `_ @@ -1162,7 +1162,7 @@ def swsl_resnext101_32x8d(pretrained=True, **kwargs): @register_model -def swsl_resnext101_32x16d(pretrained=True, **kwargs): +def swsl_resnext101_32x16d(pretrained=False, **kwargs): """Constructs a semi-weakly supervised ResNeXt-101 32x16 model pre-trained on 1B weakly supervised image dataset and finetuned on ImageNet. `"Billion-scale Semi-Supervised Learning for Image Classification" `_ diff --git a/timm/models/tresnet.py b/timm/models/tresnet.py index 0457acf8..068ada82 100644 --- a/timm/models/tresnet.py +++ b/timm/models/tresnet.py @@ -21,7 +21,7 @@ def _cfg(url='', **kwargs): return { 'url': url, 'num_classes': 1000, 'input_size': (3, 224, 224), 'pool_size': (7, 7), 'crop_pct': 0.875, 'interpolation': 'bilinear', - 'mean': (0, 0, 0), 'std': (1, 1, 1), + 'mean': (0., 0., 0.), 'std': (1., 1., 1.), 'first_conv': 'body.conv1.0', 'classifier': 'head.fc', **kwargs } diff --git a/timm/models/vision_transformer.py b/timm/models/vision_transformer.py index c92c22a3..9602355b 100644 --- a/timm/models/vision_transformer.py +++ b/timm/models/vision_transformer.py @@ -163,12 +163,12 @@ default_cfgs = { # ViT ImageNet-21K-P pretraining by MILL 'vit_base_patch16_224_miil_in21k': _cfg( url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm/vit_base_patch16_224_in21k_miil.pth', - mean=(0, 0, 0), std=(1, 1, 1), crop_pct=0.875, interpolation='bilinear', num_classes=11221, + mean=(0., 0., 0.), std=(1., 1., 1.), crop_pct=0.875, interpolation='bilinear', num_classes=11221, ), 'vit_base_patch16_224_miil': _cfg( url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm' '/vit_base_patch16_224_1k_miil_84_4.pth', - mean=(0, 0, 0), std=(1, 1, 1), crop_pct=0.875, interpolation='bilinear', + mean=(0., 0., 0.), std=(1., 1., 1.), crop_pct=0.875, interpolation='bilinear', ), 'vit_base_patch16_rpn_224': _cfg( @@ -644,7 +644,7 @@ def checkpoint_filter_fn(state_dict, model, adapt_layer_scale=False): v = resize_pos_embed( v, model.pos_embed, - getattr(model, 'num_prefix_tokens', 1), + 0 if getattr(model, 'no_embed_class') else getattr(model, 'num_prefix_tokens', 1), model.patch_embed.grid_size ) elif adapt_layer_scale and 'gamma_' in k: diff --git a/timm/models/xcit.py b/timm/models/xcit.py index 69b97d64..d70500ce 100644 --- a/timm/models/xcit.py +++ b/timm/models/xcit.py @@ -230,8 +230,8 @@ class ClassAttentionBlock(nn.Module): self.mlp = Mlp(in_features=dim, hidden_features=int(dim * mlp_ratio), act_layer=act_layer, drop=drop) if eta is not None: # LayerScale Initialization (no layerscale when None) - self.gamma1 = nn.Parameter(eta * torch.ones(dim), requires_grad=True) - self.gamma2 = nn.Parameter(eta * torch.ones(dim), requires_grad=True) + self.gamma1 = nn.Parameter(eta * torch.ones(dim)) + self.gamma2 = nn.Parameter(eta * torch.ones(dim)) else: self.gamma1, self.gamma2 = 1.0, 1.0 @@ -308,9 +308,9 @@ class XCABlock(nn.Module): self.norm2 = norm_layer(dim) self.mlp = Mlp(in_features=dim, hidden_features=int(dim * mlp_ratio), act_layer=act_layer, drop=drop) - self.gamma1 = nn.Parameter(eta * torch.ones(dim), requires_grad=True) - self.gamma3 = nn.Parameter(eta * torch.ones(dim), requires_grad=True) - self.gamma2 = nn.Parameter(eta * torch.ones(dim), requires_grad=True) + self.gamma1 = nn.Parameter(eta * torch.ones(dim)) + self.gamma3 = nn.Parameter(eta * torch.ones(dim)) + self.gamma2 = nn.Parameter(eta * torch.ones(dim)) def forward(self, x, H: int, W: int): x = x + self.drop_path(self.gamma1 * self.attn(self.norm1(x))) diff --git a/timm/utils/__init__.py b/timm/utils/__init__.py index b8cef321..7b139852 100644 --- a/timm/utils/__init__.py +++ b/timm/utils/__init__.py @@ -2,6 +2,7 @@ from .agc import adaptive_clip_grad from .checkpoint_saver import CheckpointSaver from .clip_grad import dispatch_clip_grad from .cuda import ApexScaler, NativeScaler +from .decay_batch import decay_batch_step, check_batch_size_retry from .distributed import distribute_bn, reduce_tensor from .jit import set_jit_legacy, set_jit_fuser from .log import setup_default_logging, FormatterNoInfo diff --git a/timm/utils/decay_batch.py b/timm/utils/decay_batch.py new file mode 100644 index 00000000..852fa4b8 --- /dev/null +++ b/timm/utils/decay_batch.py @@ -0,0 +1,43 @@ +""" Batch size decay and retry helpers. + +Copyright 2022 Ross Wightman +""" +import math + + +def decay_batch_step(batch_size, num_intra_steps=2, no_odd=False): + """ power of two batch-size decay with intra steps + + Decay by stepping between powers of 2: + * determine power-of-2 floor of current batch size (base batch size) + * divide above value by num_intra_steps to determine step size + * floor batch_size to nearest multiple of step_size (from base batch size) + Examples: + num_steps == 4 --> 64, 56, 48, 40, 32, 28, 24, 20, 16, 14, 12, 10, 8, 7, 6, 5, 4, 3, 2, 1 + num_steps (no_odd=True) == 4 --> 64, 56, 48, 40, 32, 28, 24, 20, 16, 14, 12, 10, 8, 6, 4, 2 + num_steps == 2 --> 64, 48, 32, 24, 16, 12, 8, 6, 4, 3, 2, 1 + num_steps == 1 --> 64, 32, 16, 8, 4, 2, 1 + """ + if batch_size <= 1: + # return 0 for stopping value so easy to use in loop + return 0 + base_batch_size = int(2 ** (math.log(batch_size - 1) // math.log(2))) + step_size = max(base_batch_size // num_intra_steps, 1) + batch_size = base_batch_size + ((batch_size - base_batch_size - 1) // step_size) * step_size + if no_odd and batch_size % 2: + batch_size -= 1 + return batch_size + + +def check_batch_size_retry(error_str): + """ check failure error string for conditions where batch decay retry should not be attempted + """ + error_str = error_str.lower() + if 'required rank' in error_str: + # Errors involving phrase 'required rank' typically happen when a conv is used that's + # not compatible with channels_last memory format. + return False + if 'illegal' in error_str: + # 'Illegal memory access' errors in CUDA typically leave process in unusable state + return False + return True diff --git a/timm/utils/jit.py b/timm/utils/jit.py index a32cbd40..d527411f 100644 --- a/timm/utils/jit.py +++ b/timm/utils/jit.py @@ -28,11 +28,19 @@ def set_jit_fuser(fuser): torch._C._jit_override_can_fuse_on_cpu(False) torch._C._jit_override_can_fuse_on_gpu(True) torch._C._jit_set_texpr_fuser_enabled(True) + try: + torch._C._jit_set_nvfuser_enabled(False) + except Exception: + pass elif fuser == "old" or fuser == "legacy": torch._C._jit_set_profiling_executor(False) torch._C._jit_set_profiling_mode(False) torch._C._jit_override_can_fuse_on_gpu(True) torch._C._jit_set_texpr_fuser_enabled(False) + try: + torch._C._jit_set_nvfuser_enabled(False) + except Exception: + pass elif fuser == "nvfuser" or fuser == "nvf": os.environ['PYTORCH_NVFUSER_DISABLE_FALLBACK'] = '1' #os.environ['PYTORCH_NVFUSER_DISABLE_FMA'] = '1' diff --git a/timm/version.py b/timm/version.py index 7556fbd9..6ab9c039 100644 --- a/timm/version.py +++ b/timm/version.py @@ -1 +1 @@ -__version__ = '0.8.0.dev0' +__version__ = '0.8.1.dev0'