Update keras to 3.4.1

[pyup-bot]

This PR updates keras from 2.13.1 to 3.4.1.

Changelog

3.4.1

This is a minor bugfix release.

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**: https://github.com/keras-team/keras/compare/v3.3.3...v3.4.0

3.3.3

This is a minor bugfix release.

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.

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.

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 https://github.com/keras-team/keras/pull/19484
* IMvision12 made their first contribution in https://github.com/keras-team/keras/pull/19393
* alanwilter made their first contribution in https://github.com/keras-team/keras/pull/19438
* chococigar made their first contribution in https://github.com/keras-team/keras/pull/19323
* LukeWood made their first contribution in https://github.com/keras-team/keras/pull/19555
* AlexanderLavelle made their first contribution in https://github.com/keras-team/keras/pull/19575

**Full Changelog**: https://github.com/keras-team/keras/compare/v3.2.1...v3.3.0

3.2.1

What's Changed

This is a minor bugfix release.


**Full Changelog**: https://github.com/keras-team/keras/compare/v3.2.0...v3.2.1

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 https://github.com/keras-team/keras/pull/19302
* qaqland made their first contribution in https://github.com/keras-team/keras/pull/19378
* tvogel made their first contribution in https://github.com/keras-team/keras/pull/19310
* lpizzinidev made their first contribution in https://github.com/keras-team/keras/pull/19409
* Murhaf made their first contribution in https://github.com/keras-team/keras/pull/19444

**Full Changelog**: https://github.com/keras-team/keras/compare/v3.1.1...v3.2.0

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

New Contributors
* tirthasheshpatel made their first contribution in https://github.com/keras-team/keras/pull/19300

**Full Changelog**: https://github.com/keras-team/keras/compare/v3.1.0...v3.1.1

3.1.0

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
* mykolaskrynnyk made their first contribution in https://github.com/keras-team/keras/pull/19190
* chicham made their first contribution in https://github.com/keras-team/keras/pull/19201
* joycebrum made their first contribution in https://github.com/keras-team/keras/pull/19214
* EtiNL made their first contribution in https://github.com/keras-team/keras/pull/19228

**Full Changelog**: https://github.com/keras-team/keras/compare/v3.0.5...v3.1.0

3.0.5

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
* frazane made their first contribution in https://github.com/keras-team/keras/pull/19107
* SamanehSaadat made their first contribution in https://github.com/keras-team/keras/pull/19111
* sitamgithub-MSIT made their first contribution in https://github.com/keras-team/keras/pull/19142
* timotheeMM made their first contribution in https://github.com/keras-team/keras/pull/19169

**Full Changelog**: https://github.com/keras-team/keras/compare/v3.0.4...v3.0.5

3.0.4

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

3.0.3

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

* kiraksi made their first contribution in https://github.com/keras-team/keras/pull/18977
* dugujiujian1999 made their first contribution in https://github.com/keras-team/keras/pull/19010
* neo-alex made their first contribution in https://github.com/keras-team/keras/pull/18997
* anas-rz made their first contribution in https://github.com/keras-team/keras/pull/19057

**Full Changelog**: https://github.com/keras-team/keras/compare/v3.0.2...v3.0.3

3.0.2

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**: https://github.com/keras-team/keras/compare/v3.0.1...v3.0.2

3.0.1

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**: https://github.com/keras-team/keras/compare/v3.0.0...v3.0.1

3.0.0

Major updates

See the [release announcement](https://keras.io/keras_3/) 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](https://github.com/keras-team/keras/issues/18467) for a complete list of breaking changes, as well as the [Keras 3 migration guide](https://keras.io/guides/migrating_to_keras_3/).

2.15.0

What's Changed
* Typofixes for `StringLookup` documentation by cw118 in https://github.com/keras-team/keras/pull/18333
* Fix ModelCheckpoint trained-on batch counting when using steps_per_execution>1 by jasnyj in https://github.com/keras-team/keras/pull/17632
* Fix legacy optimizer handling in `compile_from_config()`. by nkovela1 in https://github.com/keras-team/keras/pull/18492
* Remove options arg from ModelCheckpoint callback for Keras V3 saving, streamline ModelCheckpoint saving flow. Parameterize associated tests. by nkovela1 in https://github.com/keras-team/keras/pull/18545
* Use TENSORFLOW_VERSION when available during pip_build script by sampathweb in https://github.com/keras-team/keras/pull/18739

New Contributors
* cw118 made their first contribution in https://github.com/keras-team/keras/pull/18333
* jasnyj made their first contribution in https://github.com/keras-team/keras/pull/17632

**Full Changelog**: https://github.com/keras-team/keras/compare/v2.14.0...v2.15.0

2.14.0

What's Changed
* [keras/layers/normalization] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17965
* Update Python ver to 3.9 in Dockerfile by sampathweb in https://github.com/keras-team/keras/pull/18076
* [keras/saving/legacy/saved_model] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17978
* [keras/metrics] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17972
* Update example losses to bce- metrics/confusion_metrics.py by Frightera in https://github.com/keras-team/keras/pull/18045
* [keras/layers/regularization] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17968
* [keras/applications/efficientnet.py]  Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17758
* [keras/models] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17974
* [keras/mixed_precision] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17973
* Update indentation level - losses.py by Frightera in https://github.com/keras-team/keras/pull/18043
* Remove github user sushreebarsa from assignees. by shmishra99 in https://github.com/keras-team/keras/pull/18058
* [keras/preprocessing] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17977
* [keras/testing_infra] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17979
* [keras/benchmarks/benchmark_util.py] Use var rather than string literal for `is None` checks on `measure_performance` by SamuelMarks in https://github.com/keras-team/keras/pull/17980
* Some cleanup // Optimizers by Frightera in https://github.com/keras-team/keras/pull/18124
* [keras/layers/preprocessing] fix comments in RandomWidth, change to 'horizontally' instead of 'vertically' by qibolee in https://github.com/keras-team/keras/pull/18113
* [keras/applications] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17954
* [keras/estimator] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17957
* Fix CategoricalFocalCE documentation by Frightera in https://github.com/keras-team/keras/pull/18144
* [keras/utils] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17953
* [keras/layers/pooling] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17966
* use io_utils.print_msg in datset_utils by pedrobrs in https://github.com/keras-team/keras/pull/18054
* Update indentation level - activations.py by Frightera in https://github.com/keras-team/keras/pull/18036
* [keras/legacy_tf_layers] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17971
* [keras/layers/convolutional] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17963
* [keras/engine] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17956
* [keras/feature_column] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17958
* Fix markdown rendering issue by sachinprasadhs in https://github.com/keras-team/keras/pull/18205
* Consistently use "pickleable" instead of "picklable" by NicoWeio in https://github.com/keras-team/keras/pull/18140
* Use prefetch() after batching // image_dataset.py by Frightera in https://github.com/keras-team/keras/pull/18160
* Update Argument padding for zero_padding1d.py by SuryanarayanaY in https://github.com/keras-team/keras/pull/18223
* RGB image data is not grayscale image data by misterrioes in https://github.com/keras-team/keras/pull/18133
* updated read.me by VaishnaviMudaliar in https://github.com/keras-team/keras/pull/18226
* Fixed the typo in policy.py by tilakrayal in https://github.com/keras-team/keras/pull/18233
* Update example losses  probabilistic_metrics.py by Frightera in https://github.com/keras-team/keras/pull/18234
* Fixed "reset_state" of R2Score metric by pdyakov in https://github.com/keras-team/keras/pull/18251
* Ignore hidden folders for image_dataset_from_directory by sachinprasadhs in https://github.com/keras-team/keras/pull/18177
* Improve error message for input data to fit. by tomrtk in https://github.com/keras-team/keras/pull/18042
* refactor:  _log_epoch_metrics() by arjun-234 in https://github.com/keras-team/keras/pull/18274
* Refactor test cases to improve unit test quality by freddiewanah in https://github.com/keras-team/keras/pull/18303
* typo in disable_interactie_logging by ganeshiva in https://github.com/keras-team/keras/pull/18314
* Removes Python 3.8 support by sampathweb in https://github.com/keras-team/keras/pull/18332
* Update requirements.txt by qlzh727 in https://github.com/keras-team/keras/pull/18382

New Contributors
* sampathweb made their first contribution in https://github.com/keras-team/keras/pull/18076
* shmishra99 made their first contribution in https://github.com/keras-team/keras/pull/18058
* qibolee made their first contribution in https://github.com/keras-team/keras/pull/18113
* pedrobrs made their first contribution in https://github.com/keras-team/keras/pull/18054
* NicoWeio made their first contribution in https://github.com/keras-team/keras/pull/18140
* SuryanarayanaY made their first contribution in https://github.com/keras-team/keras/pull/18223
* misterrioes made their first contribution in https://github.com/keras-team/keras/pull/18133
* VaishnaviMudaliar made their first contribution in https://github.com/keras-team/keras/pull/18226
* pdyakov made their first contribution in https://github.com/keras-team/keras/pull/18251
* tomrtk made their first contribution in https://github.com/keras-team/keras/pull/18042
* arjun-234 made their first contribution in https://github.com/keras-team/keras/pull/18274
* freddiewanah made their first contribution in https://github.com/keras-team/keras/pull/18303
* ganeshiva made their first contribution in https://github.com/keras-team/keras/pull/18314

**Full Changelog**: https://github.com/keras-team/keras/compare/v2.13.1...v2.14.0

2.14.0rc0

What's Changed
* [keras/layers/normalization] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17965
* Update Python ver to 3.9 in Dockerfile by sampathweb in https://github.com/keras-team/keras/pull/18076
* [keras/saving/legacy/saved_model] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17978
* [keras/metrics] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17972
* Update example losses to bce- metrics/confusion_metrics.py by Frightera in https://github.com/keras-team/keras/pull/18045
* [keras/layers/regularization] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17968
* [keras/applications/efficientnet.py]  Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17758
* [keras/models] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17974
* [keras/mixed_precision] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17973
* Update indentation level - losses.py by Frightera in https://github.com/keras-team/keras/pull/18043
* Remove github user sushreebarsa from assignees. by shmishra99 in https://github.com/keras-team/keras/pull/18058
* [keras/preprocessing] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17977
* [keras/testing_infra] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17979
* [keras/benchmarks/benchmark_util.py] Use var rather than string literal for `is None` checks on `measure_performance` by SamuelMarks in https://github.com/keras-team/keras/pull/17980
* Some cleanup // Optimizers by Frightera in https://github.com/keras-team/keras/pull/18124
* [keras/layers/preprocessing] fix comments in RandomWidth, change to 'horizontally' instead of 'vertically' by qibolee in https://github.com/keras-team/keras/pull/18113
* [keras/applications] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17954
* [keras/estimator] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17957
* Fix CategoricalFocalCE documentation by Frightera in https://github.com/keras-team/keras/pull/18144
* [keras/utils] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17953
* [keras/layers/pooling] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17966
* use io_utils.print_msg in datset_utils by pedrobrs in https://github.com/keras-team/keras/pull/18054
* Update indentation level - activations.py by Frightera in https://github.com/keras-team/keras/pull/18036
* [keras/legacy_tf_layers] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17971
* [keras/layers/convolutional] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17963
* [keras/engine] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17956
* [keras/feature_column] Standardise docstring usage of "Default to" by SamuelMarks in https://github.com/keras-team/keras/pull/17958
* Fix markdown rendering issue by sachinprasadhs in https://github.com/keras-team/keras/pull/18205
* Consistently use "pickleable" instead of "picklable" by NicoWeio in https://github.com/keras-team/keras/pull/18140
* Use prefetch() after batching // image_dataset.py by Frightera in https://github.com/keras-team/keras/pull/18160
* Update Argument padding for zero_padding1d.py by SuryanarayanaY in https://github.com/keras-team/keras/pull/18223
* RGB image data is not grayscale image data by misterrioes in https://github.com/keras-team/keras/pull/18133
* updated read.me by VaishnaviMudaliar in https://github.com/keras-team/keras/pull/18226
* Fixed the typo in policy.py by tilakrayal in https://github.com/keras-team/keras/pull/18233
* Update example losses  probabilistic_metrics.py by Frightera in https://github.com/keras-team/keras/pull/18234
* Fixed "reset_state" of R2Score metric by pdyakov in https://github.com/keras-team/keras/pull/18251
* Ignore hidden folders for image_dataset_from_directory by sachinprasadhs in https://github.com/keras-team/keras/pull/18177
* Improve error message for input data to fit. by tomrtk in https://github.com/keras-team/keras/pull/18042
* refactor:  _log_epoch_metrics() by arjun-234 in https://github.com/keras-team/keras/pull/18274
* Refactor test cases to improve unit test quality by freddiewanah in https://github.com/keras-team/keras/pull/18303
* typo in disable_interactie_logging by ganeshiva in https://github.com/keras-team/keras/pull/18314
* Removes Python 3.8 support by sampathweb in https://github.com/keras-team/keras/pull/18332

New Contributors
* sampathweb made their first contribution in https://github.com/keras-team/keras/pull/18076
* shmishra99 made their first contribution in https://github.com/keras-team/keras/pull/18058
* qibolee made their first contribution in https://github.com/keras-team/keras/pull/18113
* pedrobrs made their first contribution in https://github.com/keras-team/keras/pull/18054
* NicoWeio made their first contribution in https://github.com/keras-team/keras/pull/18140
* SuryanarayanaY made their first contribution in https://github.com/keras-team/keras/pull/18223
* misterrioes made their first contribution in https://github.com/keras-team/keras/pull/18133
* VaishnaviMudaliar made their first contribution in https://github.com/keras-team/keras/pull/18226
* pdyakov made their first contribution in https://github.com/keras-team/keras/pull/18251
* tomrtk made their first contribution in https://github.com/keras-team/keras/pull/18042
* arjun-234 made their first contribution in https://github.com/keras-team/keras/pull/18274
* freddiewanah made their first contribution in https://github.com/keras-team/keras/pull/18303
* ganeshiva made their first contribution in https://github.com/keras-team/keras/pull/18314

**Full Changelog**: https://github.com/keras-team/keras/compare/v2.13.1...v2.14.0-rc0

Links

• PyPI: https://pypi.org/project/keras
• Changelog: https://data.safetycli.com/changelogs/keras/
• Repo: https://github.com/keras-team/keras