* Add API inference in the docs and fix readthedocs config.
* Replace some relative link in docs.
* Format docstring for reStructuredText syntax.
* Fix vit paper link
* Fix docstring of `show_results` function in `BaseClassifier`.
* 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.
* Move tools docs to `tools` folder.
* Fix link error in model_serving.md
* Fix typo in CONTRIBUTING.md
* Add Chinese translation of CONTRIBUTING.md
* Add translation of `onnx2tensorrt.md`, `pytorch2onnx.md`,
`model_serving.md` and `pytorch2torchscript.md`.
* Improve tools docs.
* Add docs about installing mmcls via mim.
* add mytrain.py for test
* test before layers
* test attr in layers
* test classifier
* delete mytrain.py
* add imagenet_bs4096_AdamW.py
* delete 2 lines of comments
* change bs to 64
* fix bug
* add vit to model_zoo.md
* rename
* Add Citation in README
Add Citation and mmgeneration in README
* Merge inference and test section in getting_start.md and other small chagne.
* Fix code type in install.md
* Add Chinese Readme
* README and docs improvement.
* add pytorch2onnx and onnx2trt doc
* fix the typo in deploy doc
* fix bug of onnx2trt.md
* Remove redundant install steps in onnx2trt.md
* update doc based on code review
* update index.rst
* add bce loss for multilabel task
* minor change
* apply class wise sum
* fix docstring
* do not apply sum over classes and fix docstring
* fix docstring
* fix weight shape
* fix weight shape
* fix docstring
* fix linting issue
Co-authored-by: Y. Xiong <xiongyuxy@gmail.com>
* Use build_runner in train api
* Support iter in eval_hook
* Add runner section
* Add test_eval_hook
* Pin mmcv version in install docs
* Replace max_iters with max_epochs
* Set by_epoch=True as default
* Remove trailing space
* Replace DeprecationWarning with UserWarning
* pre-commit
* Fix tests
* add model inference on single image
* rm --eval
* revise doc
* add inference tool and demo
* fix linting
* rename inference_image to inference_model
* infer pred_label and pred_score
* fix linting
* add docstr for inference
* add remove_keys
* add doc for inference
* dump results rather than outputs
* add class_names
* add related infer scripts
* add demo image and the first part of colab tutorial
* conduct evaluation in dataset
* return lst in simple_test
* compuate topk accuracy with numpy
* return outputs in test api
* merge inference and evaluation tool
* fix typo
* rm gt_labels in test conifg
* get gt_labels during evaluation
* sperate the ipython notebook to another PR
* return tensor for onnx_export
* detach var in simple_test
* rm inference script
* rm inference script
* construct data dict to replace LoadImage
* print first predicted result if args.out is None
* modify test_pipeline in inference
* refactor class_names of imagenet
* set class_to_idx as a property in base dataset
* output pred_class during inference
* remove unused docstr
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