Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Update dependency keras to v3 #26

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Conversation

renovate[bot]
Copy link

@renovate renovate bot commented Nov 28, 2023

Mend Renovate

This PR contains the following updates:

Package Change Age Adoption Passing Confidence
keras ==2.4.3 -> ==3.3.3 age adoption passing confidence

Release Notes

keras-team/keras (keras)

v3.3.3: Kears 3.3.3

Compare Source

This is a minor bugfix release.

v3.3.2: Keras 3.3.2

Compare Source

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.

v3.3.1: Keras 3.3.1

Compare Source

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.

v3.3.0: Keras 3.3.0

Compare Source

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

Full Changelog: keras-team/keras@v3.2.1...v3.3.0

v3.2.1: Keras 3.2.1

Compare Source

What's Changed

This is a minor bugfix release.

Full Changelog: keras-team/keras@v3.2.0...v3.2.1

v3.2.0: Keras 3.2.0

Compare Source

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

Full Changelog: keras-team/keras@v3.1.1...v3.2.0

v3.1.1: Keras 3.1.1

Compare Source

This is a minor bugfix release over 3.1.0.

What's Changed

New Contributors

Full Changelog: keras-team/keras@v3.1.0...v3.1.1

v3.1.0: Keras 3.1.0

Compare Source

New features

  • Add support for 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.
  • Add keras.config.set_backend(backend) utility to reload a different backend.
  • Add keras.layers.MelSpectrogram layer for turning raw audio data into Mel spectrogram representation.
  • Add keras.ops.custom_gradient decorator (only for JAX and TensorFlow).
  • Add keras.ops.image.crop_images.
  • Add pad_to_aspect_ratio argument to image_dataset_from_directory.
  • Add keras.random.binomial and keras.random.beta functions.
  • Enable keras.ops.einsum to run with int8 x int8 inputs and int32 output.
  • Add verbose argument in all dataset-creation utilities.

Notable fixes

  • Fix Functional model slicing
  • Fix for TF XLA compilation error for SpectralNormalization
  • Refactor axis logic across all backends and add support for multiple axes in expand_dims and squeeze

New Contributors

Full Changelog: keras-team/keras@v3.0.5...v3.1.0

v3.0.5: Keras 3.0.5

Compare Source

This release brings many bug fixes and performance improvements, new linear algebra ops, and sparse tensor support for the JAX backend.

Highlights

  • Add support for sparse tensors with the JAX backend.
  • Add support for saving/loading in bfloat16.
  • Add linear algebra ops in keras.ops.linalg.
  • Support nested structures in while_loop op.
  • Add erfinv op.
  • Add normalize op.
  • Add support for IterableDataset to TorchDataLoaderAdapter.

New Contributors

Full Changelog: keras-team/keras@v3.0.4...v3.0.5

v3.0.4: Keras 3.0.4

Compare Source

This is a minor release with improvements to the LoRA API required by the next release of KerasNLP.

Full Changelog: keras-team/keras@v3.0.3...v3.0.4

v3.0.3: Keras 3.0.3 release

Compare Source

This is a minor Keras release.

What's Changed

  • Add built-in LoRA (low-rank adaptation) API to all relevant layers (Dense, EinsumDense, Embedding).
  • Add SwapEMAWeights callback to make it easier to evaluate model metrics using EMA weights during training.
  • All DataAdapters now create a native iterator for each backend, improving performance.
  • Add built-in prefetching for JAX, improving performance.
  • The bfloat16 dtype is now allowed in the global set_dtype configuration utility.
  • Bug fixes and performance improvements.

New Contributors

Full Changelog: keras-team/keras@v3.0.2...v3.0.3

v3.0.2: Keras 3.0.2

Compare Source

Breaking changes

There are no known breaking changes in this release compared to 3.0.1.

API changes

  • Add keras.random.binomial and keras.random.beta RNG functions.
  • Add masking support to BatchNormalization.
  • Add keras.losses.CTC (loss function for sequence-to-sequence tasks) as well as the lower-level operation keras.ops.ctc_loss.
  • Add ops.random.alpha_dropout and layers.AlphaDropout.
  • Add gradient accumulation support for all backends, and enable optimizer EMA for JAX and torch

Full Changelog: keras-team/keras@v3.0.1...v3.0.2

v3.0.1: Keras 3.0.1

Compare Source

This is a minor release focused on bug fixes and performance improvements.

What's Changed

  • Bug fixes and performance improvements.
  • Add stop_evaluating and stop_predicting model attributes for callbacks, similar to stop_training.
  • Add keras.device() scope for managing device placement in a multi-backend way.
  • Support dict items in PyDataset.
  • Add hard_swish activation and op.
  • Fix cuDNN LSTM performance on TensorFlow backend.
  • Add a force_download arg to get_file to force cache invalidation.

Full Changelog: keras-team/keras@v3.0.0...v3.0.1

v3.0.0: Keras 3.0.0

Compare Source

Major updates

See the release announcement for a detailed list of major changes. Main highlights compared to Keras 2 are:

  • Keras can now be run on top of JAX, PyTorch, TensorFlow, and even NumPy (note that the NumPy backend is inference-only).
  • New low-level keras.ops API for building cross-framework components.
  • New large-scale model distribution keras.distribution based on JAX.
  • New stateless API for layers, models, optimizers, and metrics.

Breaking changes

See this thread for a complete list of breaking changes, as well as the Keras 3 migration guide.

v2.15.0: Keras Release 2.15.0

Compare Source

What's Changed

New Contributors

Full Changelog: keras-team/keras@v2.14.0...v2.15.0

v2.14.0: Keras Release 2.14.0

Compare Source

What's Changed

New Contributors

Full Changelog: keras-team/keras@v2.13.1...v2.14.0

v2.13.1: Keras Release 2.13.1

Compare Source

What's Changed

New Contributors

Full Changelog: keras-team/keras@v2.12.0...v2.13.1

v2.12.0: Keras Release 2.12.0

Compare Source

Please see the release history at https://github.com/tensorflow/tensorflow/releases/tag/v2.12.0 for more details.

What's Changed


Configuration

📅 Schedule: Branch creation - At any time (no schedule defined), Automerge - At any time (no schedule defined).

🚦 Automerge: Disabled by config. Please merge this manually once you are satisfied.

Rebasing: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox.

🔕 Ignore: Close this PR and you won't be reminded about this update again.


  • If you want to rebase/retry this PR, check this box

This PR has been generated by Mend Renovate. View repository job log here.

@renovate renovate bot force-pushed the renovate/keras-3.x branch 2 times, most recently from 568d275 to 24a784b Compare January 20, 2024 22:54
@renovate renovate bot force-pushed the renovate/keras-3.x branch 2 times, most recently from 3951775 to 737d088 Compare March 19, 2024 20:19
@renovate renovate bot force-pushed the renovate/keras-3.x branch 2 times, most recently from a66e1e4 to cbd120f Compare April 10, 2024 21:56
@renovate renovate bot force-pushed the renovate/keras-3.x branch 2 times, most recently from 170d603 to 739c5f4 Compare April 23, 2024 00:22
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

None yet

0 participants