Bump version to v1.0.2
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README.md
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README.md
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@ -86,6 +86,10 @@ https://github.com/open-mmlab/mmpretrain/assets/26739999/e4dcd3a2-f895-4d1b-a351
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## What's new
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🌟 v1.0.2 was released in 15/08/2023
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Support MFF self-supervised algorithm and enhance the codebase. More details can be found in the [changelog](https://mmpretrain.readthedocs.io/en/latest/notes/changelog.html).
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🌟 v1.0.1 was released in 28/07/2023
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Fix some bugs and enhance the codebase. Please refer to [changelog](https://mmpretrain.readthedocs.io/en/latest/notes/changelog.html) for more details.
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@ -97,13 +101,7 @@ Fix some bugs and enhance the codebase. Please refer to [changelog](https://mmpr
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- Add [**iTPN**](./configs/itpn/), [**SparK**](./configs/spark/) self-supervised learning algorithms.
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- Provide examples of [New Config](./mmpretrain/configs/) and [DeepSpeed/FSDP with FlexibleRunner](./configs/mae/benchmarks/). Here are the documentation links of [New Config](https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta) and [DeepSpeed/FSDP with FlexibleRunner](https://mmengine.readthedocs.io/en/latest/api/generated/mmengine.runner.FlexibleRunner.html#mmengine.runner.FlexibleRunner).
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🌟 v1.0.0rc8 was released in 22/05/2023
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- Support multiple **multi-modal** algorithms and inferencers. You can explore these features by the [gradio demo](https://github.com/open-mmlab/mmpretrain/tree/main/projects/gradio_demo)!
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- Add EVA-02, Dino-V2, ViT-SAM and GLIP backbones.
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- Register torchvision transforms into MMPretrain, you can now easily integrate torchvision's data augmentations in MMPretrain. See [the doc](https://mmpretrain.readthedocs.io/en/latest/api/data_process.html#torchvision-transforms)
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Update of previous versions
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🌟 Upgrade from MMClassification to MMPreTrain
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- Integrated Self-supervised learning algorithms from **MMSelfSup**, such as **MAE**, **BEiT**, etc.
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- Support **RIFormer**, a simple but effective vision backbone by removing token mixer.
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@ -84,6 +84,10 @@ https://github.com/open-mmlab/mmpretrain/assets/26739999/e4dcd3a2-f895-4d1b-a351
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## 更新日志
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🌟 2023/8/15 发布了 v1.0.2 版本
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支持了 MFF 自监督算法，增强算法库功能。细节请参考 [更新日志](https://mmpretrain.readthedocs.io/zh_CN/latest/notes/changelog.html)。
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🌟 2023/7/28 发布了 v1.0.1 版本
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修复部分 bug 和增强算法库功能。细节请参考 [更新日志](https://mmpretrain.readthedocs.io/zh_CN/latest/notes/changelog.html)。
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@ -95,15 +99,9 @@ https://github.com/open-mmlab/mmpretrain/assets/26739999/e4dcd3a2-f895-4d1b-a351
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- 添加自监督学习算法 [**iTPN**](./configs/itpn/), [**SparK**](./configs/spark/)。
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- 提供[新配置文件](./mmpretrain/configs/)和 [DeepSpeed/FSDP](./configs/mae/benchmarks/) 的样例。这是[新配置文件](https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta) 和 [DeepSpeed/FSDP with FlexibleRunner](https://mmengine.readthedocs.io/en/latest/api/generated/mmengine.runner.FlexibleRunner.html#mmengine.runner.FlexibleRunner) 的文档链接。
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🌟 2023/5/22 发布了 v1.0.0rc8 版本
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🌟 从 MMClassification 升级到 MMPreTrain
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- 支持多种多模态算法和推理器。您可以通过 [gradio demo](https://github.com/open-mmlab/mmpretrain/tree/main/projects/gradio_demo) 探索这些功能!
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- 新增 EVA-02，Dino-V2，ViT-SAM 和 GLIP 主干网络。
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- 将 torchvision 变换注册到 MMPretrain，现在您可以轻松地将 torchvision 的数据增强集成到 MMPretrain 中。
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之前版本更新内容
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- 整和来自 MMSelfSup 的自监督学习算法，例如 `MAE`, `BEiT` 等
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- 整合来自 MMSelfSup 的自监督学习算法，例如 `MAE`, `BEiT` 等
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- 支持了 **RIFormer**，简单但有效的视觉主干网络，却移除了 token mixer
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- 重构数据管道可视化
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- 支持了 **LeViT**, **XCiT**, **ViG**, **ConvNeXt-V2**, **EVA**, **RevViT**, **EfficientnetV2**, **CLIP**, **TinyViT** 和 **MixMIM** 等骨干网络结构
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@ -3,7 +3,7 @@ ARG CUDA="11.3"
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ARG CUDNN="8"
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FROM pytorch/torchserve:latest-gpu
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ARG MMPRE="1.0.0rc8"
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ARG MMPRE="1.0.2"
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ENV PYTHONUNBUFFERED TRUE
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@ -1,5 +1,23 @@
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# Changelog (MMPreTrain)
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## v1.0.2(15/08/2023)
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### New Features
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- Add MFF ([#1725](https://github.com/open-mmlab/mmpretrain/pull/1725))
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- Support training of BLIP2 ([#1700](https://github.com/open-mmlab/mmpretrain/pull/1700))
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### Improvements
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- New Version of config Adapting MAE Algorithm ([#1750](https://github.com/open-mmlab/mmpretrain/pull/1750))
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- New Version of config Adapting ConvNeXt Algorithm ([#1760](https://github.com/open-mmlab/mmpretrain/pull/1760))
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- New version of config adapting BeitV2 Algorithm ([#1755](https://github.com/open-mmlab/mmpretrain/pull/1755))
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- Update `dataset_prepare.md` ([#1732](https://github.com/open-mmlab/mmpretrain/pull/1732))
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- New Version of `config` Adapting Vision Transformer Algorithm ([#1727](https://github.com/open-mmlab/mmpretrain/pull/1727))
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- Support Infographic VQA dataset and ANLS metric. ([#1667](https://github.com/open-mmlab/mmpretrain/pull/1667))
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- Support IconQA dataset. ([#1670](https://github.com/open-mmlab/mmpretrain/pull/1670))
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- Fix typo MIMHIVIT to MAEHiViT ([#1749](https://github.com/open-mmlab/mmpretrain/pull/1749))
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## v1.0.1(28/07/2023)
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### Improvements
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@ -16,7 +16,7 @@ and make sure you fill in all required information in the template.
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| MMPretrain version | MMEngine version | MMCV version |
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| :----------------: | :---------------: | :--------------: |
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| 1.0.1 (main) | mmengine >= 0.8.3 | mmcv >= 2.0.0 |
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| 1.0.2 (main) | mmengine >= 0.8.3 | mmcv >= 2.0.0 |
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| 1.0.0 | mmengine >= 0.8.0 | mmcv >= 2.0.0 |
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| 1.0.0rc8 | mmengine >= 0.7.1 | mmcv >= 2.0.0rc4 |
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| 1.0.0rc7 | mmengine >= 0.5.0 | mmcv >= 2.0.0rc4 |
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@ -13,7 +13,7 @@
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| MMPretrain 版本 | MMEngine 版本 | MMCV 版本 |
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| :-------------: | :---------------: | :--------------: |
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| 1.0.1 (main) | mmengine >= 0.8.3 | mmcv >= 2.0.0 |
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| 1.0.2 (main) | mmengine >= 0.8.3 | mmcv >= 2.0.0 |
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| 1.0.0 | mmengine >= 0.8.0 | mmcv >= 2.0.0 |
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| 1.0.0rc8 | mmengine >= 0.7.1 | mmcv >= 2.0.0rc4 |
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| 1.0.0rc7 | mmengine >= 0.5.0 | mmcv >= 2.0.0rc4 |
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@ -1,6 +1,6 @@
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# Copyright (c) OpenMMLab. All rights reserved
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__version__ = '1.0.1'
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__version__ = '1.0.2'
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def parse_version_info(version_str):
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