Keras 3.5.0

What's Changed

• Add integration with the Hugging Face Hub. You can now save models to Hugging Face Hub directly from keras.Model.save() and load .keras models directly from Hugging Face Hub with keras.saving.load_model().
• Ensure compatibility with NumPy 2.0.
• Add keras.optimizers.Lamb optimizer.
• Improve keras.distribution API support for very large models.
• Add keras.ops.associative_scan op.
• Add keras.ops.searchsorted op.
• Add keras.utils.PyDataset.on_epoch_begin() method.
• Add data_format argument to keras.layers.ZeroPadding1D layer.
• Bug fixes and performance improvements.

Full Changelog: v3.4.1...v3.5.0

Keras 3.4.1

This is a minor bugfix release.

Keras 3.4.0

Highlights

• Add support for arbitrary, deeply nested input/output structures in Functional models (e.g. dicts of dicts of lists of inputs or outputs...)
• Add support for optional Functional inputs.
• Introduce keras.dtype_policies.DTypePolicyMap for easy configuration of dtype policies of nested sublayers of a subclassed layer/model.
• New ops:
  • keras.ops.argpartition
  • keras.ops.scan
  • keras.ops.lstsq
  • keras.ops.switch
  • keras.ops.dtype
  • keras.ops.map
  • keras.ops.image.rgb_to_hsv
  • keras.ops.image.hsv_to_rgb

What's changed

• Add support for float8 inference for Dense and EinsumDense layers.
• Add custom name argument in all Keras Applications models.
• Add axis argument in keras.losses.Dice.
• Enable keras.utils.FeatureSpace to be used in a tf.data pipeline even when the backend isn't TensorFlow.
• StringLookup layer can now take tf.SparseTensor as input.
• Metric.variables is now recursive.
• Add training argument to Model.compute_loss().
• Add dtype argument to all losses.
• keras.utils.split_dataset now supports nested structures in dataset.
• Bugs fixes and performance improvements.

Full Changelog: v3.3.3...v3.4.0

Keras 3.3.3

This is a minor bugfix release.

Keras 3.3.2

This is a simple fix release that re-surfaces legacy Keras 2 APIs that aren't part of Keras package proper, but that are still featured in tf.keras. No other content has changed.

Keras 3.3.1

This is a simple fix release that moves the legacy _tf_keras API directory to the root of the Keras pip package. This is done in order to preserve import paths like from tensorflow.keras import layers without making any changes to the TensorFlow API files.

No other content has changed.

Keras 3.3.0

What's Changed

• Introduce float8 training.
• Add LoRA to ConvND layers.
• Add keras.ops.ctc_decode for JAX and TensorFlow.
• Add keras.ops.vectorize, keras.ops.select.
• Add keras.ops.image.rgb_to_grayscale.
• Add keras.losses.Tversky loss.
• Add full bincount and digitize sparse support.
• Models and layers now return owned metrics recursively.
• Add pickling support for Keras models. Note that pickling is not recommended, prefer using Keras saving APIs.
• Bug fixes and performance improvements.

In addition, the codebase structure has evolved:

• All source files are now in keras/src/.
• All API files are now in keras/api/.
• The codebase structure stays unchanged when building the Keras pip package. This means you can pip install Keras directly from the GitHub sources.

New Contributors

• @kapoor1992 made their first contribution in #19484
• @IMvision12 made their first contribution in #19393
• @alanwilter made their first contribution in #19438
• @chococigar made their first contribution in #19323
• @LukeWood made their first contribution in #19555
• @AlexanderLavelle made their first contribution in #19575

Full Changelog: v3.2.1...v3.3.0

Keras 3.2.1

What's Changed

This is a minor bugfix release.

Full Changelog: v3.2.0...v3.2.1

Keras 3.2.0

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

Keras 3.1.1

This is a minor bugfix release over 3.1.0.

What's Changed

• Unwrap variable values in all stateless calls. by @hertschuh in #19287
• Fix draw_seed causing device discrepancy issue during torch's symbolic execution by @KhawajaAbaid in #19289
• Fix TestCase.run_layer_test for multi-output layers by @shkarupa-alex in #19293
• Sine docstring by @grasskin in #19295
• Fix keras.ops.softmax for the tensorflow backend by @tirthasheshpatel in #19300
• Fix mixed precision check in TestCase.run_layer_test: compare with output_spec dtype instead of hardcoded float16 by @shkarupa-alex in #19297
• ArrayDataAdapter no longer converts to NumPy and supports sparse tens… by @hertschuh in #19298
• add token to codecov by @haifeng-jin in #19312
• Add Tensorflow support for variable scatter_update in optimizers. by @hertschuh in #19313
• Replace dm-tree with optree by @james77777778 in #19306
• downgrade codecov to v3 by @haifeng-jin in #19319
• Allow tensors in tf.Datasets to have different dimensions. by @hertschuh in #19318
• update codecov setting by @haifeng-jin in #19320
• Set dtype policy for uint8 by @sampathweb in #19327
• Use Value dim shape for Attention compute_output_shape by @sampathweb in #19284

New Contributors

• @tirthasheshpatel made their first contribution in #19300

Full Changelog: v3.1.0...v3.1.1