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from .beit import *
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from .byoanet import *
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from .byobnet import *
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from .cait import *
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from .coat import *
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from .convit import *
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from .convmixer import *
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from .convnext import *
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from .crossvit import *
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from .cspnet import *
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from .deit import *
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from .densenet import *
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from .dla import *
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from .dpn import *
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from .edgenext import *
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from .efficientformer import *
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from .efficientnet import *
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from .gcvit import *
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from .ghostnet import *
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from .gluon_resnet import *
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from .gluon_xception import *
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from .hardcorenas import *
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from .hrnet import *
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from .inception_resnet_v2 import *
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from .inception_v3 import *
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from .inception_v4 import *
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from .levit import *
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from .maxxvit import *
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from .mlp_mixer import *
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from .mobilenetv3 import *
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from .mobilevit import *
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from .mvitv2 import *
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from .nasnet import *
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from .nest import *
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from .nfnet import *
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from .pit import *
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from .pnasnet import *
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from .poolformer import *
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from .pvt_v2 import *
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from .regnet import *
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from .res2net import *
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from .resnest import *
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from .resnet import *
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from .resnetv2 import *
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from .rexnet import *
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from .selecsls import *
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from .senet import *
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from .sequencer import *
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from .sknet import *
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from .swin_transformer import *
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from .swin_transformer_v2 import *
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from .swin_transformer_v2_cr import *
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from .tnt import *
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from .tresnet import *
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from .twins import *
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from .vgg import *
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from .visformer import *
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from .vision_transformer import *
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from .vision_transformer_hybrid import *
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from .vision_transformer_relpos import *
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from .volo import *
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Monster commit, activation refactor, VoVNet, norm_act improvements, more
* refactor activations into basic PyTorch, jit scripted, and memory efficient custom auto
* implement hard-mish, better grad for hard-swish
* add initial VovNet V1/V2 impl, fix #151
* VovNet and DenseNet first models to use NormAct layers (support BatchNormAct2d, EvoNorm, InplaceIABN)
* Wrap IABN for any models that use it
* make more models torchscript compatible (DPN, PNasNet, Res2Net, SelecSLS) and add tests
5 years ago
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from .vovnet import *
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from .xception import *
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from .xception_aligned import *
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from .xcit import *
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from .factory import create_model, parse_model_name, safe_model_name
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from .helpers import load_checkpoint, resume_checkpoint, model_parameters
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from .layers import TestTimePoolHead, apply_test_time_pool
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from .layers import convert_splitbn_model, convert_sync_batchnorm
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Monster commit, activation refactor, VoVNet, norm_act improvements, more
* refactor activations into basic PyTorch, jit scripted, and memory efficient custom auto
* implement hard-mish, better grad for hard-swish
* add initial VovNet V1/V2 impl, fix #151
* VovNet and DenseNet first models to use NormAct layers (support BatchNormAct2d, EvoNorm, InplaceIABN)
* Wrap IABN for any models that use it
* make more models torchscript compatible (DPN, PNasNet, Res2Net, SelecSLS) and add tests
5 years ago
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from .layers import is_scriptable, is_exportable, set_scriptable, set_exportable, is_no_jit, set_no_jit
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from .layers import set_fast_norm
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from .pretrained import PretrainedCfg, filter_pretrained_cfg, generate_default_cfgs, split_model_name_tag
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from .registry import register_model, model_entrypoint, list_models, list_pretrained, is_model, list_modules,\
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is_model_in_modules, is_model_pretrained, get_pretrained_cfg, get_pretrained_cfg_value
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