KerasCV is adding experimental support for Jax and PyTorch backends on top of the Keras Core library. Read the [anouncement](https://keras.io/keras_core/announcement/), and browse the [full library documentation](http://keras.io/keras_core/), including how to specify the backend when running your code.
Support for both Jax and PyTorch is still experimental, expect some rough edges and please give us feedback!
Summary
This release should be equivalent to 0.5.1 with the addition of multi-backend support.
The following API components do not yet support Jax + PyTorch:
- keras_cv.models.StableDiffusion[V2]
- keras_cv.models.MultiHeadCenterPillar
- keras_cv.training.ContrastiveTrainer
- All models under keras_cv.models.legacy
Note that there are two ways you can run on top of Tensorflow.
If you run your scripts/colab without any changes, KerasCV will use tf.keras for all layer and modeling implementations. This should be a no-op from previous releases of the library.
If you run your scripts/colab with KERAS_BACKEND={jax, torch, tensorflow}, you will be trying the new Keras Core library, using the specified backend. This is a great way to test out the future of the library!
Full details on runtime specification is available along with the [Keras Core documentation](http://keras.io/keras_core/).
What's Changed
* Add support for PyTorch and Jax to KerasCV by tirthasheshpatel in https://github.com/keras-team/keras-cv/pull/1925
* Update version to dev release by ianstenbit in https://github.com/keras-team/keras-cv/pull/1927
New Contributors
* tirthasheshpatel made their first contribution in https://github.com/keras-team/keras-cv/pull/1925
**Full Changelog**: https://github.com/keras-team/keras-cv/compare/v0.5.1...v0.6.0.dev0