Deep Learning for humans
This is a minor bugfix release.
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.
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.ops.ctc_decode
for JAX and TensorFlow.keras.ops.vectorize
, keras.ops.select
.keras.ops.image.rgb_to_grayscale
.keras.losses.Tversky
loss.bincount
and digitize
sparse support.In addition, the codebase structure has evolved:
keras/src/
.keras/api/
.pip install
Keras directly from the GitHub sources.Full Changelog: https://github.com/keras-team/keras/compare/v3.2.1...v3.3.0
This is a minor bugfix release.
Full Changelog: https://github.com/keras-team/keras/compare/v3.2.0...v3.2.1
Dense
and EinsumDense
layers (thereby any LLM) in int8 precision.keras.ops.custom_gradient
support to PyTorch.keras.layers.JaxLayer
and keras.layers.FlaxLayer
to wrap JAX/Flax modules as Keras layers.save_model
& load_model
to accept a file-like object.Embedding
layer.compute_loss
method with all backends.self.losses
inside a custom compute_loss
method with the JAX backend.keras.losses.Dice
loss.keras.ops.correlate
.model.export()
: add support for aliases, finer control over jax2tf
options, and dynamic batch shapes.Full Changelog: https://github.com/keras-team/keras/compare/v3.1.1...v3.2.0
This is a minor bugfix release over 3.1.0.
draw_seed
causing device discrepancy issue during torch
's symbolic execution by @KhawajaAbaid in https://github.com/keras-team/keras/pull/19289
keras.ops.softmax
for the tensorflow backend by @tirthasheshpatel in https://github.com/keras-team/keras/pull/19300
scatter_update
in optimizers. by @hertschuh in https://github.com/keras-team/keras/pull/19313
dm-tree
with optree
by @james77777778 in https://github.com/keras-team/keras/pull/19306
tf.Dataset
s to have different dimensions. by @hertschuh in https://github.com/keras-team/keras/pull/19318
Full Changelog: https://github.com/keras-team/keras/compare/v3.1.0...v3.1.1
int8
inference. Just call model.quantize("int8")
to do an in-place conversion of a bfloat16 or float32 model to an int8 model. Note that only Dense
and EinsumDense
layers will be converted (this covers LLMs and all Transformers in general). We may add more supported layers over time.keras.config.set_backend(backend)
utility to reload a different backend.keras.layers.MelSpectrogram
layer for turning raw audio data into Mel spectrogram representation.keras.ops.custom_gradient
decorator (only for JAX and TensorFlow).keras.ops.image.crop_images
.pad_to_aspect_ratio
argument to image_dataset_from_directory
.keras.random.binomial
and keras.random.beta
functions.keras.ops.einsum
to run with int8 x int8 inputs and int32 output.verbose
argument in all dataset-creation utilities.SpectralNormalization
axis
logic across all backends and add support for multiple axes in expand_dims
and squeeze
Full Changelog: https://github.com/keras-team/keras/compare/v3.0.5...v3.1.0
This release brings many bug fixes and performance improvements, new linear algebra ops, and sparse tensor support for the JAX backend.
keras.ops.linalg
.while_loop
op.erfinv
op.normalize
op.IterableDataset
to TorchDataLoaderAdapter
.Full Changelog: https://github.com/keras-team/keras/compare/v3.0.4...v3.0.5
This is a minor release with improvements to the LoRA API required by the next release of KerasNLP.
Full Changelog: https://github.com/keras-team/keras/compare/v3.0.3...v3.0.4