Mmpretrain

Highlights

- New API to get pre-defined models of MMClassification. See [1236](https://github.com/open-mmlab/mmclassification/pull/1236) for more details.
- Refactor BEiT backbone and support v1/v2 inference. See [1144](https://github.com/open-mmlab/mmclassification/pull/1144).

New Features

- Support getting models from the name defined in the model-index file. ([1236](https://github.com/open-mmlab/mmclassification/pull/1236))

Improvements

- Support evaluation on both EMA and non-EMA models. ([1204](https://github.com/open-mmlab/mmclassification/pull/1204))
- Refactor BEiT backbone and support v1/v2 inference. ([1144](https://github.com/open-mmlab/mmclassification/pull/1144))

Bug Fixes

- Fix `reparameterize_model.py` doesn't save meta info. ([1221](https://github.com/open-mmlab/mmclassification/pull/1221))
- Fix dict update in BEiT. ([1234](https://github.com/open-mmlab/mmclassification/pull/1234))

Docs Update

- Update install tutorial. ([1223](https://github.com/open-mmlab/mmclassification/pull/1223))
- Update MobileNetv2 & MobileNetv3 readme. ([1222](https://github.com/open-mmlab/mmclassification/pull/1222))
- Add version selection in the banner. ([1217](https://github.com/open-mmlab/mmclassification/pull/1217))

Contributors
A total of 4 developers contributed to this release.

techmonsterwang mzr1996 fangyixiao18 kitecats

Highlights

- Add **Switch Recipe** Hook, Now we can modify training pipeline, mixup and loss settings during training, see [1101](https://github.com/open-mmlab/mmclassification/pull/1101).
- Add **TIMM and HuggingFace** wrappers. Now you can train/use models in TIMM/HuggingFace directly, see [1102](https://github.com/open-mmlab/mmclassification/pull/1102).
- Support **retrieval tasks**, see [1055](https://github.com/open-mmlab/mmclassification/pull/1055).
- Reproduce **MobileOne** training accuracy. See [1191](https://github.com/open-mmlab/mmclassification/pull/1191).

New Features

- Add checkpoints from EfficientNets NoisyStudent & L2. ([1122](https://github.com/open-mmlab/mmclassification/pull/1122))
- Migrate CSRA head to 1.x. ([1177](https://github.com/open-mmlab/mmclassification/pull/1177))
- Support RepLKnet backbone. ([1129](https://github.com/open-mmlab/mmclassification/pull/1129))
- Add Switch Recipe Hook. ([1101](https://github.com/open-mmlab/mmclassification/pull/1101))
- Add adan optimizer. ([1180](https://github.com/open-mmlab/mmclassification/pull/1180))
- Support DaViT. ([1105](https://github.com/open-mmlab/mmclassification/pull/1105))
- Support Activation Checkpointing for ConvNeXt. ([1153](https://github.com/open-mmlab/mmclassification/pull/1153))
- Add TIMM and HuggingFace wrappers to build classifiers from them directly. ([1102](https://github.com/open-mmlab/mmclassification/pull/1102))
- Add reduction for neck ([978](https://github.com/open-mmlab/mmclassification/pull/978))
- Support HorNet Backbone for dev1.x. ([1094](https://github.com/open-mmlab/mmclassification/pull/1094))
- Add arcface head. ([926](https://github.com/open-mmlab/mmclassification/pull/926))
- Add Base Retriever and Image2Image Retriever for retrieval tasks. ([1055](https://github.com/open-mmlab/mmclassification/pull/1055))
- Support MobileViT backbone. ([1068](https://github.com/open-mmlab/mmclassification/pull/1068))

Improvements

- [Enhance] Enhance ArcFaceClsHead. ([1181](https://github.com/open-mmlab/mmclassification/pull/1181))
- [Refactor] Refactor to use new fileio API in MMEngine. ([1176](https://github.com/open-mmlab/mmclassification/pull/1176))
- [Enhance] Reproduce mobileone training accuracy. ([1191](https://github.com/open-mmlab/mmclassification/pull/1191))
- [Enhance] add deleting params info in swinv2. ([1142](https://github.com/open-mmlab/mmclassification/pull/1142))
- [Enhance] Add more mobilenetv3 pretrains. ([1154](https://github.com/open-mmlab/mmclassification/pull/1154))
- [Enhancement] RepVGG for YOLOX-PAI for dev-1.x. ([1126](https://github.com/open-mmlab/mmclassification/pull/1126))
- [Improve] Speed up data preprocessor. ([1064](https://github.com/open-mmlab/mmclassification/pull/1064))

Bug Fixes

- Fix the torchserve. ([1143](https://github.com/open-mmlab/mmclassification/pull/1143))
- Fix configs due to api refactor of `num_classes`. ([1184](https://github.com/open-mmlab/mmclassification/pull/1184))
- Update mmcls2torchserve. ([1189](https://github.com/open-mmlab/mmclassification/pull/1189))
- Fix for `inference_model` cannot get classes information in checkpoint. ([1093](https://github.com/open-mmlab/mmclassification/pull/1093))

Docs Update

- Add not-found page extension. ([1207](https://github.com/open-mmlab/mmclassification/pull/1207))
- update visualization doc. ([1160](https://github.com/open-mmlab/mmclassification/pull/1160))
- Support sort and search the Model Summary table. ([1100](https://github.com/open-mmlab/mmclassification/pull/1100))
- Improve the ResNet model page. ([1118](https://github.com/open-mmlab/mmclassification/pull/1118))
- update the readme of convnext. ([1156](https://github.com/open-mmlab/mmclassification/pull/1156))
- Fix the installation docs link in README. ([1164](https://github.com/open-mmlab/mmclassification/pull/1164))
- Improve ViT and MobileViT model pages. ([1155](https://github.com/open-mmlab/mmclassification/pull/1155))
- Improve Swin Doc and Add Tabs enxtation. ([1145](https://github.com/open-mmlab/mmclassification/pull/1145))
- Add MMEval projects link in README. ([1162](https://github.com/open-mmlab/mmclassification/pull/1162))
- Add runtime configuration docs. ([1128](https://github.com/open-mmlab/mmclassification/pull/1128))
- Add custom evaluation docs ([1130](https://github.com/open-mmlab/mmclassification/pull/1130))
- Add custom pipeline docs. ([1124](https://github.com/open-mmlab/mmclassification/pull/1124))
- Add MMYOLO projects link in MMCLS1.x. ([1117](https://github.com/open-mmlab/mmclassification/pull/1117))

Contributors
A total of 14 developers contributed to this release.

austinmw Ezra-Yu nijkah yingfhu techmonsterwang mzr1996 sanbuphy tonysy XingyuXie gaoyang07 kitecats marouaneamz okotaku zzc98

New Features

- Support DeiT3. ([1065](https://github.com/open-mmlab/mmclassification/pull/1065))

Improvements

- Update `analyze_results.py` for dev-1.x. ([1071](https://github.com/open-mmlab/mmclassification/pull/1071))
- Get scores from inference api. ([1070](https://github.com/open-mmlab/mmclassification/pull/1070))

Bug Fixes

- Update requirements. ([1083](https://github.com/open-mmlab/mmclassification/pull/1083))

Docs Update

- Add 1x docs schedule. ([1015](https://github.com/open-mmlab/mmclassification/pull/1015))

Contributors
A total of 3 developers contributed to this release.

mzr1996 okotaku yingfhu

Highlights

- Support MViT, EdgeNeXt, Swin-Transformer V2, EfficientFormer and MobileOne.
- Support BEiT type transformer layer.

New Features

- Support MViT for MMCLS 1.x ([1023](https://github.com/open-mmlab/mmclassification/pull/1023))
- Add ViT huge architecture. ([1049](https://github.com/open-mmlab/mmclassification/pull/1049))
- Support EdgeNeXt for dev-1.x. ([1037](https://github.com/open-mmlab/mmclassification/pull/1037))
- Support Swin Transformer V2 for MMCLS 1.x. ([1029](https://github.com/open-mmlab/mmclassification/pull/1029))
- Add efficientformer Backbone for MMCls 1.x. ([1031](https://github.com/open-mmlab/mmclassification/pull/1031))
- Add MobileOne Backbone For MMCls 1.x. ([1030](https://github.com/open-mmlab/mmclassification/pull/1030))
- Support BEiT Transformer layer. ([919](https://github.com/open-mmlab/mmclassification/pull/919))

Improvements

- [Refactor] Fix visualization tools. ([1045](https://github.com/open-mmlab/mmclassification/pull/1045))
- [Improve] Update benchmark scripts ([1028](https://github.com/open-mmlab/mmclassification/pull/1028))
- [Imporve] Update tools to enable `pin_memory` and `persistent_workers` by default. ([1024](https://github.com/open-mmlab/mmclassification/pull/1024))
- [CI] Update circle-ci and github workflow. ([1018](https://github.com/open-mmlab/mmclassification/pull/1018))

Bug Fixes

- Fix verify dataset tool in 1.x. ([1062](https://github.com/open-mmlab/mmclassification/pull/1062))
- Fix `loss_weight` in `LabelSmoothLoss`. ([1058](https://github.com/open-mmlab/mmclassification/pull/1058))
- Fix the output position of Swin-Transformer. ([947](https://github.com/open-mmlab/mmclassification/pull/947))

Docs Update

- Fix typo in migration document. ([1063](https://github.com/open-mmlab/mmclassification/pull/1063))
- Auto generate model summary table. ([1010](https://github.com/open-mmlab/mmclassification/pull/1010))
- Refactor new modules tutorial. ([998](https://github.com/open-mmlab/mmclassification/pull/998))

Contributors
A total of 8 developers contributed to this release.

Ezra-Yu yingfhu mzr1996 tonysy fangyixiao18 YuanLiuuuuuu HIT-cwh techmonsterwang

MMClassification 1.0.0rc0 is the first version of MMClassification 1.x, a part of the OpenMMLab 2.0 projects.

Built upon the new [training engine](https://github.com/open-mmlab/mmengine), MMClassification 1.x unifies the interfaces of dataset, models, evaluation, and visualization.

And there are some BC-breaking changes. Please check [the migration tutorial](https://mmclassification.readthedocs.io/en/1.x/migration.html) for more details.

Highlights

- Support MLU backend.
- Add `dist_train_arm.sh` for ARM device.

New Features

- Support MLU backend. ([1159](https://github.com/open-mmlab/mmclassification/pull/1159))
- Support Activation Checkpointing for ConvNeXt. ([1152](https://github.com/open-mmlab/mmclassification/pull/1152))

Improvements

- Add `dist_train_arm.sh` for ARM device and update NPU results. ([1218](https://github.com/open-mmlab/mmclassification/pull/1218))

Bug Fixes

- Fix a bug caused `MMClsWandbHook` stuck. ([1242](https://github.com/open-mmlab/mmclassification/pull/1242))
- Fix the redundant `device_ids` in `tools/test.py`. ([1215](https://github.com/open-mmlab/mmclassification/pull/1215))

Docs Update

- Add version banner and version warning in master docs. ([1216](https://github.com/open-mmlab/mmclassification/pull/1216))
- Update NPU support doc. ([1198](https://github.com/open-mmlab/mmclassification/pull/1198))
- Fixed typo in `pytorch2torchscript.md`. ([1173](https://github.com/open-mmlab/mmclassification/pull/1173))
- Fix typo in `miscellaneous.md`. ([1137](https://github.com/open-mmlab/mmclassification/pull/1137))
- further detail for the doc for `ClassBalancedDataset`. ([901](https://github.com/open-mmlab/mmclassification/pull/901))

Contributors
A total of 7 developers contributed to this release.

nijkah xiaoyuan0203 mzr1996 Qiza-lyhm ganghe74 unseenme wangjiangben-hw