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This is a minor bugfix release.
Full Changelog: https://github.com/keras-team/keras/compare/v3.2.0...v3.2.1
Published by fchollet 6 months ago
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
Published by fchollet 7 months ago
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
Published by fchollet 7 months ago
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
Published by fchollet 8 months ago
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
Published by fchollet 9 months ago
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
Published by fchollet 9 months ago
This is a minor Keras release.
Dense
, EinsumDense
, Embedding
).SwapEMAWeights
callback to make it easier to evaluate model metrics using EMA weights during training.DataAdapters
now create a native iterator for each backend, improving performance.bfloat16
dtype is now allowed in the global set_dtype
configuration utility.Full Changelog: https://github.com/keras-team/keras/compare/v3.0.2...v3.0.3
Published by fchollet 10 months ago
There are no known breaking changes in this release compared to 3.0.1.
keras.random.binomial
and keras.random.beta
RNG functions.BatchNormalization
.keras.losses.CTC
(loss function for sequence-to-sequence tasks) as well as the lower-level operation keras.ops.ctc_loss
.ops.random.alpha_dropout
and layers.AlphaDropout
.Full Changelog: https://github.com/keras-team/keras/compare/v3.0.1...v3.0.2
Published by qlzh727 10 months ago
StringLookup
documentation by @cw118 in https://github.com/keras-team/keras/pull/18333
compile_from_config()
. by @nkovela1 in https://github.com/keras-team/keras/pull/18492
Full Changelog: https://github.com/keras-team/keras/compare/v2.14.0...v2.15.0
Published by fchollet 11 months ago
This is a minor release focused on bug fixes and performance improvements.
stop_evaluating
and stop_predicting
model attributes for callbacks, similar to stop_training
.keras.device()
scope for managing device placement in a multi-backend way.PyDataset
.hard_swish
activation and op.force_download
arg to get_file
to force cache invalidation.Full Changelog: https://github.com/keras-team/keras/compare/v3.0.0...v3.0.1
Published by fchollet 11 months ago
See the release announcement for a detailed list of major changes. Main highlights compared to Keras 2 are:
keras.ops
API for building cross-framework components.keras.distribution
based on JAX.See this thread for a complete list of breaking changes, as well as the Keras 3 migration guide.
Published by qlzh727 about 1 year ago
is None
checks on measure_performance
by @SamuelMarks in https://github.com/keras-team/keras/pull/17980
Full Changelog: https://github.com/keras-team/keras/compare/v2.13.1...v2.14.0
Published by qlzh727 about 1 year ago
is None
checks on measure_performance
by @SamuelMarks in https://github.com/keras-team/keras/pull/17980
Full Changelog: https://github.com/keras-team/keras/compare/v2.13.1...v2.14.0-rc0
Published by qlzh727 over 1 year ago
Full Changelog: https://github.com/keras-team/keras/compare/v2.12.0...v2.13.1
Published by qlzh727 over 1 year ago
Full Changelog: https://github.com/keras-team/keras/compare/v2.13.1-rc0...v2.13.1-rc1
Published by qlzh727 over 1 year ago
Full Changelog: https://github.com/keras-team/keras/compare/v2.12.0...v2.13.1-rc0
Published by qlzh727 over 1 year ago
Please see the release history at https://github.com/tensorflow/tensorflow/releases/tag/v2.12.0 for more details.
amsgrad
argument in SGD by @lgeiger in https://github.com/keras-team/keras/pull/17197
finalize_variable_values
in LossScaleOptimizerV3
by @lgeiger in https://github.com/keras-team/keras/pull/17225
use_causal_mask=True
with RaggedTensor
bug by @haifeng-jin in https://github.com/keras-team/keras/pull/17231
to_ordinal
feature for ordinal regression/classification by @awsaf49 in https://github.com/keras-team/keras/pull/17419
to_ordinal
by @awsaf49 in https://github.com/keras-team/keras/pull/17485
Full Changelog: https://github.com/keras-team/keras/compare/v2.11.0...v2.12.0
Published by qlzh727 over 1 year ago
Please see the release history at https://github.com/tensorflow/tensorflow/releases/tag/v2.12.0-rc0 for more details.
amsgrad
argument in SGD by @lgeiger in https://github.com/keras-team/keras/pull/17197
finalize_variable_values
in LossScaleOptimizerV3
by @lgeiger in https://github.com/keras-team/keras/pull/17225
use_causal_mask=True
with RaggedTensor
bug by @haifeng-jin in https://github.com/keras-team/keras/pull/17231
to_ordinal
feature for ordinal regression/classification by @awsaf49 in https://github.com/keras-team/keras/pull/17419
to_ordinal
by @awsaf49 in https://github.com/keras-team/keras/pull/17485
Full Changelog: https://github.com/keras-team/keras/compare/v2.11.0...v2.12.0-rc1
Published by qlzh727 almost 2 years ago
Please see the release history at https://github.com/tensorflow/tensorflow/releases/tag/v2.11.0 for more details.
Full Changelog: https://github.com/keras-team/keras/compare/v2.10.0...v2.11.0
Published by qlzh727 almost 2 years ago
Full Changelog: https://github.com/keras-team/keras/compare/v2.11.0-rc2...v2.11.0-rc3