2023-05-14 18:51:30 +00:00
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# Keras Core: a new multi-backend Keras
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Keras Core is a new multi-backend implementation of the Keras API, with support for TensorFlow, JAX, and PyTorch.
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2023-06-09 04:53:02 +00:00
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## Local installation
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Run `python3 pip_build.py --install` from the root directory.
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2023-06-09 16:07:04 +00:00
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## Configuring your backend
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You can export the environment variable `KERAS_BACKEND` or you can edit your local config file at `~/.keras/keras.json`
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to configure your backend. Available backend options are: `"tensorflow"`, `"jax"`, `"torch"`. Example:
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```
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export KERAS_BACKEND="jax"
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```
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2023-05-14 18:51:30 +00:00
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## Backwards compatibility
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Keras Core is intend to work as a drop-in replacement for `tf.keras` (when using the TensorFlow backend).
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2023-06-09 01:09:10 +00:00
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If your `tf.keras` model does not include custom compoments, you can start running it on top of JAX or PyTorch immediately.
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If it does include custom components (e.g. custom layers or a custom `train_step()`), it is usually possible to convert it
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to a backend-agnostic implementation in just a few minutes.
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2023-05-14 21:17:39 +00:00
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In addition, Keras models can consume datasets in any format, regardless of the backend you're using:
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you can train your models with your existing tf.data.Dataset pipelines or Torch DataLoaders.
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2023-05-14 18:51:30 +00:00
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## Why use Keras Core?
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2023-06-09 01:09:10 +00:00
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- Run your high-level Keras workflows on top of any framework -- benefiting at will from the advantages of each framework,
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e.g. the scalability and performance of JAX or the production ecosystem options of TensorFlow.
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- Write custom components (e.g. layers, models, metrics) that you can use in low-level workflows in any framework.
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- You can take a Keras model and train it in a training loop written from scratch in native TF, JAX, or PyTorch.
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- You can take a Keras model and use it as part of a PyTorch-native `Module` or as part of a JAX-native model function.
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- Make your ML code future-proof by avoiding framework lock-in.
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- As a PyTorch user: get access to power and usability of Keras, at last!
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- As a JAX user: get access to a fully-featured, battle-tested, well-documented modeling and training library.
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2023-05-14 18:51:30 +00:00
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## Credits
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TODO
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