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mmpretrain/mmcls/models/utils/__init__.py

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[Docs] Add Copyright information. (#413)
2021-08-17 19:52:42 +08:00
# Copyright (c) OpenMMLab. All rights reserved.
[Refactor] Refator ViT (Continue #295) (#395) * [Squash] Refator ViT (from #295) * Use base variable to simplify auto_aug setting * Use common PatchEmbed, remove HybridEmbed and refactor ViT init structure. * Add `output_cls_token` option and change the output format of ViT and input format of ViT head. * Update unit tests and add test for `output_cls_token`. * Support out_indices. * Standardize config files * Support resize position embedding. * Add readme file of vit * Rename config file * Improve docs about ViT. * Update docstring * Use local version `MultiheadAttention` instead of mmcv version. * Fix MultiheadAttention * Support `qk_scale` argument in `MultiheadAttention` * Improve docs and change `layer_cfg` to `layer_cfgs` and support sequence. * Use init_cfg to init Linear layer in VisionTransformerHead * update metafile * Update checkpoints and configs * Imporve docstring. * Update README * Revert GAP modification.
2021-10-18 16:07:00 +08:00
from .attention import MultiheadAttention, ShiftWindowMSA
[Feature]Add augments to models/utils (#278) * add mytrain.py for test * test before layers * test attr in layers * test classifier * delete mytrain.py * add rand_bbox_minmax rand_bbox and cutmix_bbox_and_lam to BaseCutMixLayer * add mixup_prob to BatchMixupLayer * add cutmixup * add cutmixup to __init__ * test classifier with cutmixup * delete some comments * set mixup_prob default to 1.0 * add cutmixup to classifier * use cutmixup * use cutmixup * fix bugs * test cutmixup * move mixup and cutmix to augment * inherit from BaseAugment * add BaseAugment * inherit from BaseAugment * rename identity.py * add @ * build augment * register module * rename to augment.py * delete cutmixup.py * do not inherit from BaseAugment * add augments * use augments in classifier * prob default to 1.0 * add comments * use augments * use augments * assert sum of augmentation probabilities should equal to 1 * augmentation probabilities equal to 1 * calculate Identity prob * replace xxx with self.xxx * add comments * sync with augments * for BC-breaking * delete useless comments in mixup.py
2021-06-20 09:44:51 +08:00
from .augment.augments import Augments
Dev/backbone utils
2020-06-15 16:42:15 +08:00
from .channel_shuffle import channel_shuffle
[Feature] Add swin-transformer model. (#271) * 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.
2021-07-01 09:30:42 +08:00
from .embed import HybridEmbed, PatchEmbed, PatchMerging
Add `is_tracing` helper function to fix a tracing bug in PyTorch 1.6 (#347)
2021-07-07 11:55:53 +08:00
from .helpers import is_tracing, to_2tuple, to_3tuple, to_4tuple, to_ntuple
Dev mobilenetv3
2020-06-30 15:50:36 +08:00
from .inverted_residual import InvertedResidual
Dev/backbone utils
2020-06-15 16:42:15 +08:00
from .make_divisible import make_divisible
Dev mobilenetv3
2020-06-30 15:50:36 +08:00
from .se_layer import SELayer
Dev/backbone utils
2020-06-15 16:42:15 +08:00
[Feature] Add "mixup" from Bag of Tricks (#160) * Add mixup option * Modify the structure of mixup and add configs * Clean configs * Add test for mixup and SoftCrossEntropyLoss * Add simple test for ImageClassifier * Fix bug in test_losses.py * Add assertion in CrossEntropyLoss
2021-02-25 14:06:58 +08:00
__all__ = [
[Feature]Add augments to models/utils (#278) * add mytrain.py for test * test before layers * test attr in layers * test classifier * delete mytrain.py * add rand_bbox_minmax rand_bbox and cutmix_bbox_and_lam to BaseCutMixLayer * add mixup_prob to BatchMixupLayer * add cutmixup * add cutmixup to __init__ * test classifier with cutmixup * delete some comments * set mixup_prob default to 1.0 * add cutmixup to classifier * use cutmixup * use cutmixup * fix bugs * test cutmixup * move mixup and cutmix to augment * inherit from BaseAugment * add BaseAugment * inherit from BaseAugment * rename identity.py * add @ * build augment * register module * rename to augment.py * delete cutmixup.py * do not inherit from BaseAugment * add augments * use augments in classifier * prob default to 1.0 * add comments * use augments * use augments * assert sum of augmentation probabilities should equal to 1 * augmentation probabilities equal to 1 * calculate Identity prob * replace xxx with self.xxx * add comments * sync with augments * for BC-breaking * delete useless comments in mixup.py
2021-06-20 09:44:51 +08:00
'channel_shuffle', 'make_divisible', 'InvertedResidual', 'SELayer',
[Feature] Add swin-transformer model. (#271) * 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.
2021-07-01 09:30:42 +08:00
'to_ntuple', 'to_2tuple', 'to_3tuple', 'to_4tuple', 'PatchEmbed',
[Refactor] Refator ViT (Continue #295) (#395) * [Squash] Refator ViT (from #295) * Use base variable to simplify auto_aug setting * Use common PatchEmbed, remove HybridEmbed and refactor ViT init structure. * Add `output_cls_token` option and change the output format of ViT and input format of ViT head. * Update unit tests and add test for `output_cls_token`. * Support out_indices. * Standardize config files * Support resize position embedding. * Add readme file of vit * Rename config file * Improve docs about ViT. * Update docstring * Use local version `MultiheadAttention` instead of mmcv version. * Fix MultiheadAttention * Support `qk_scale` argument in `MultiheadAttention` * Improve docs and change `layer_cfg` to `layer_cfgs` and support sequence. * Use init_cfg to init Linear layer in VisionTransformerHead * update metafile * Update checkpoints and configs * Imporve docstring. * Update README * Revert GAP modification.
2021-10-18 16:07:00 +08:00
'PatchMerging', 'HybridEmbed', 'Augments', 'ShiftWindowMSA', 'is_tracing',
'MultiheadAttention'
[Feature] Add "mixup" from Bag of Tricks (#160) * Add mixup option * Modify the structure of mixup and add configs * Clean configs * Add test for mixup and SoftCrossEntropyLoss * Add simple test for ImageClassifier * Fix bug in test_losses.py * Add assertion in CrossEntropyLoss
2021-02-25 14:06:58 +08:00
]