Keras 3.2.0

Keras 3.2.0

on Python PyPI

What changed

• Introduce QLoRA-like technique for LoRA fine-tuning of Dense and EinsumDense layers (thereby any LLM) in int8 precision.
• Extend keras.ops.custom_gradient support to PyTorch.
• Add keras.layers.JaxLayer and keras.layers.FlaxLayer to wrap JAX/Flax modules as Keras layers.
• Allow save_model & load_model to accept a file-like object.
• Add quantization support to the Embedding layer.
• Make it possible to update metrics inside a custom compute_loss method with all backends.
• Make it possible to access self.losses inside a custom compute_loss method with the JAX backend.
• Add keras.losses.Dice loss.
• Add keras.ops.correlate.
• Make it possible to use cuDNN LSTM & GRU with a mask with the TensorFlow backend.
• Better JAX support in model.export(): add support for aliases, finer control over jax2tf options, and dynamic batch shapes.
• Bug fixes and performance improvements.

New Contributors

• @abhaskumarsinha made their first contribution in #19302
• @qaqland made their first contribution in #19378
• @tvogel made their first contribution in #19310
• @lpizzinidev made their first contribution in #19409
• @Murhaf made their first contribution in #19444

Full Changelog: v3.1.1...v3.2.0