Add Swin-Transformer to keras.applications

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System information.

TensorFlow version (you are using): 2.6 Are you willing to contribute it (Yes/No): Yes

Describe the feature and the current behavior/state.

Describe the feature clearly here. Be sure to convey here why the requested feature is needed. Any brief description of the use-case would help.

Paper: Swin Transformer: Hierarchical Vision Transformer using Shifted Windows Original Code: https://github.com/microsoft/Swin-Transformer?utm_source=catalyzex.com

It’s a variant of the transformer model and achieves state-of-the-art performance or comparable performance with the best CNN-based models. It also contains enough citations (~250 at this moment) for addition to the package.

On ImageNet-1K and 22K, below is the comparable results with EfficientNet (CNN) models.

-	Img Size	Top 1K acc	-	Img Size	Top 1K acc	Top 22K acc
E3	300	81.6	EfficientNetV2-S	-	83.9	84.9
E5	456	83.6	EfficientNetV2-M	-	85.1	86.2
E7	600	84.3	EfficientNetV2-L	-	85.7	86.8
-	-	-	EfficientNetV2-XL	-	-	87.3
Swin-T	224	81.3	Swin-B	224	-	85.2
Swin-S	224	83.0	Swin-B	384	-	86.4
Swin-B	224	83.5	Swin-L	384	-	87.3
Swin-B	384	84.5	-	-	-	-

Will this change the current api? How? Yes. It will change as follows

tensorflow.keras.applications.SwinT
tensorflow.keras.applications.SwinS
tensorflow.keras.applications.SwinB
tensorflow.keras.applications.SwinL

Who will benefit from this feature? Keras users.

Contributing

• Do you want to contribute a PR? (yes/no): yes.
• If yes, please read this page for instructions
• Briefly describe your candidate solution(if contributing):

[bhack]

Can we close this for https://github.com/keras-team/keras-cv/issues/671?

[qlzh727]

Sorry for the late reply. We probably have to host this in the keras/application for now. Eventually we will move this to keras-cv, but we are not ready yet. Feel free to send PR if you have any.