* Refactor Mobilenetv3 structure and add ConvClsHead.
* Change model's name from 'MobileNetv3' to 'MobileNetV3'
* Modify configs for MobileNetV3 on CIFAR10.
And add MobileNetV3 configs for imagenet
* Fix activate setting bugs in MobileNetV3.
And remove bias in SELayer.
* Modify unittest
* Remove useless config and file.
* Fix mobilenetv3-large arch setting
* Add dropout option in ConvClsHead
* Fix MobilenetV3 structure according to torchvision version.
1. Remove with_expand_conv option in InvertedResidual, it should be decided by channels.
2. Revert activation function, should before SE layer.
* Format code.
* Rename MobilenetV3 arch "big" to "large".
* Add mobilenetv3_small torchvision training recipe
* Modify default `out_indices` of MobilenetV3, now it will change
according to `arch` if not specified.
* Add MobilenetV3 large config.
* Add mobilenetv3 README
* Modify InvertedResidual unit test.
* Refactor ConvClsHead to StackedLinearClsHead, and add unit tests.
* Add unit test for `simple_test` of `StackedLinearClsHead`.
* Fix typo
Co-authored-by: Yidi Shao <ydshao@smail.nju.edu.cn>
* 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
* add mytrain.py for test
* test before layers
* test attr in layers
* test classifier
* delete mytrain.py
* register custom_hooks in runner
* set custom_hooks_config to cfg.get(custom_hooks, None)
* add mytrain.py for test
* test before layers
* test attr in layers
* test classifier
* delete mytrain.py
* move init_cfg to parameter
* isort
* Use a sentinel value to denote the default init_cfg
* Refector label smooth loss, now support mode `original`, `classy_vision`
and `multi_label`.
* Add unittests for label smooth loss.
* Improve docstring of LSR
* add increasing in solarize and posterize
* fix linting
* Revert "add increasing in solarize and posterize"
This reverts commit 128af36e9b.
* revise according to comments
* Add paramater magnitude_std in RandAugment to allow randomly movement of magnitude_value
* Add unittest for magnitude_std
* Improve docstring of magnitude_std
* GlabelAveragePooling support 1d, 2d and 3d by param, and add neck test
* Imporve neck test
* Change 'mode' attribute in GAP to 'dim', and add docstring
* add mytrain.py for test
* test before layers
* test attr in layers
* test classifier
* delete mytrain.py
* set cal_acc in ClsHead defaults to False
* set cal_acc defaults to False
* use *args, **kwargs instead
* change bs16 to 3 in test_image_classifier_vit
* fix some comments
* change cal_acc=True
* test LinearClsHead
Ma Zerun
whcao
AllentDan
WRH
q.yao
David de la Iglesia Castro
LXXXXR
Miao Zheng
Mingqiang Ning
Yinhao Li
Y. Xiong
Wenwei Zhang
Forsaken
RangiLyu
mzr1996
QingChuanWS