30 lines
1.5 KiB
Python
30 lines
1.5 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from .attention import (BEiTAttention, ChannelMultiheadAttention, LeAttention,
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MultiheadAttention, ShiftWindowMSA, WindowMSA,
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WindowMSAV2)
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from .batch_augments import CutMix, Mixup, RandomBatchAugment, ResizeMix
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from .channel_shuffle import channel_shuffle
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from .data_preprocessor import ClsDataPreprocessor
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from .embed import (HybridEmbed, PatchEmbed, PatchMerging, resize_pos_embed,
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resize_relative_position_bias_table)
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from .helpers import is_tracing, to_2tuple, to_3tuple, to_4tuple, to_ntuple
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from .inverted_residual import InvertedResidual
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from .layer_scale import LayerScale
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from .make_divisible import make_divisible
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from .norm import GRN, LayerNorm2d, build_norm_layer
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from .position_encoding import (ConditionalPositionEncoding,
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PositionEncodingFourier)
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from .se_layer import SELayer
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__all__ = [
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'channel_shuffle', 'make_divisible', 'InvertedResidual', 'SELayer',
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'to_ntuple', 'to_2tuple', 'to_3tuple', 'to_4tuple', 'PatchEmbed',
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'PatchMerging', 'HybridEmbed', 'RandomBatchAugment', 'ShiftWindowMSA',
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'is_tracing', 'MultiheadAttention', 'ConditionalPositionEncoding',
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'resize_pos_embed', 'resize_relative_position_bias_table',
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'ClsDataPreprocessor', 'Mixup', 'CutMix', 'ResizeMix', 'BEiTAttention',
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'LayerScale', 'WindowMSA', 'WindowMSAV2', 'ChannelMultiheadAttention',
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'PositionEncodingFourier', 'LeAttention', 'GRN', 'LayerNorm2d',
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'build_norm_layer'
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]
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