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https://github.com/open-mmlab/mmclassification.git
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08dc8c75d3
* remove basehead * add moco series * add byol simclr simsiam * add ut * update configs * add simsiam hook * add and refactor beit * update ut * add cae * update extract_feat * refactor cae * add mae * refactor data preprocessor * update heads * add maskfeat * add milan * add simmim * add mixmim * fix lint * fix ut * fix lint * add eva * add densecl * add barlowtwins * add swav * fix lint * update readtherdocs rst * update docs * update * Decrease UT memory usage * Fix docstring * update DALLEEncoder * Update model docs * refactor dalle encoder * update docstring * fix ut * fix config error * add val_cfg and test_cfg * refactor clip generator * fix lint * pass check * fix ut * add lars * update type of BEiT in configs * Use MMEngine style momentum in EMA. * apply mmpretrain solarize --------- Co-authored-by: mzr1996 <mzr1996@163.com>
34 lines
958 B
Python
34 lines
958 B
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from .beitv2_neck import BEiTV2Neck
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from .cae_neck import CAENeck
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from .densecl_neck import DenseCLNeck
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from .gap import GlobalAveragePooling
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from .gem import GeneralizedMeanPooling
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from .hr_fuse import HRFuseScales
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from .linear_neck import LinearNeck
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from .mae_neck import ClsBatchNormNeck, MAEPretrainDecoder
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from .milan_neck import MILANPretrainDecoder
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from .mixmim_neck import MixMIMPretrainDecoder
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from .mocov2_neck import MoCoV2Neck
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from .nonlinear_neck import NonLinearNeck
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from .simmim_neck import SimMIMLinearDecoder
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from .swav_neck import SwAVNeck
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__all__ = [
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'GlobalAveragePooling',
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'GeneralizedMeanPooling',
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'HRFuseScales',
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'LinearNeck',
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'BEiTV2Neck',
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'CAENeck',
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'DenseCLNeck',
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'MAEPretrainDecoder',
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'ClsBatchNormNeck',
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'MILANPretrainDecoder',
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'MixMIMPretrainDecoder',
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'MoCoV2Neck',
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'NonLinearNeck',
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'SimMIMLinearDecoder',
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'SwAVNeck',
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]
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