mirror of
https://github.com/open-mmlab/mmclassification.git
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076ee10cac
* Add swin transformer archs S, B and L. * Add SwinTransformer configs * Add train config files of swin. * Align init method with original code * Use nn.Unfold to merge patch * Change all ConfigDict to dict * Add init_cfg for all subclasses of BaseModule. * Use mmcv version init function * Add Swin README * Use safer cfg copy method * Improve docstring and variable name. * Fix some difference in randaug Fix BGR bug, align scheduler config. Fix label smoothing parameter difference. * Fix missing droppath in attn * Fix bug of relative posititon table if window width is not equal to height. * Make `PatchMerging` more general, support kernel, stride, padding and dilation. * Rename `residual` to `identity` in attention and FFN. * Add `auto_pad` option to auto pad feature map * Improve docstring. * Fix bug in ShiftWMSA padding. * Remove unused `key` and `value` in ShiftWMSA * Move `PatchMerging` into utils and use common `PatchEmbed`. * Use latest `LinearClsHead`, train augments and label smooth settings. And remove original `SwinLinearClsHead`. * Mark some configs as "Evalution Only". * Remove useless comment in config * 1. Move ShiftWindowMSA and WindowMSA to `utils/attention.py` 2. Add docstrings of each module. 3. Fix some variables' names. 4. Other small improvement. * Add unit tests of swin-transformer and patchmerging. * Fix some bugs in unit tests. * Fix bug of rel_position_index if window is not square. * Make WindowMSA implicit, and add unit tests. * Add metafile.yml, update readme and model_zoo.
24 lines
810 B
Python
24 lines
810 B
Python
from .alexnet import AlexNet
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from .lenet import LeNet5
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from .mobilenet_v2 import MobileNetV2
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from .mobilenet_v3 import MobileNetV3
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from .regnet import RegNet
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from .resnest import ResNeSt
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from .resnet import ResNet, ResNetV1d
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from .resnet_cifar import ResNet_CIFAR
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from .resnext import ResNeXt
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from .seresnet import SEResNet
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from .seresnext import SEResNeXt
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from .shufflenet_v1 import ShuffleNetV1
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from .shufflenet_v2 import ShuffleNetV2
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from .swin_transformer import SwinTransformer
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from .vgg import VGG
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from .vision_transformer import VisionTransformer
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__all__ = [
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'LeNet5', 'AlexNet', 'VGG', 'RegNet', 'ResNet', 'ResNeXt', 'ResNetV1d',
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'ResNeSt', 'ResNet_CIFAR', 'SEResNet', 'SEResNeXt', 'ShuffleNetV1',
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'ShuffleNetV2', 'MobileNetV2', 'MobileNetV3', 'VisionTransformer',
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'SwinTransformer'
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]
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