Keras Core 0.1.6 release

Highlights

• Performance optimizations in normalization layers
• New op: ops.nn.moments
• Add TorchModuleWrapper to make it possible to use PyTorch Modules in Keras Core models with the PyTorch backend. Modules added as attributes of a layer are automatically wrapped (so that their weights are tracked).
• Add ignore_class argument in SparseCategoricalCrossentropy.
• Add new experimental data parallel and model parallel distribution API for JAX.

What's Changed

• Fix where op by @AakashKumarNain in #770
• Add skeleton for the common distribution backend. by @qlzh727 in #765
• Add more H5 backwards compatibility tests and lambda support by @nkovela1 in #775
• Add implementation for Distribution API by @qlzh727 in #776
• Removes tf.keras from transposed conv test by @sampathweb in #782
• Fix channels_first format bug for rescaling layer by @haifeng-jin in #792
• Fix argument order in stft and istft by @james77777778 in #790
• fixed squeeze axis inconsistency by @jackd in #788
• Replace tf.data with tf_data in preprocessing tests by @sampathweb in #787
• Reimplement the data parallel distribution. by @qlzh727 in #785
• Split fix by @jackd in #789
• Fix bug: Softmax function to support tuple axes + Add more tests by @Faisal-Alsrheed in #778
• Add LayoutMap which will be used for model parallelism by @qlzh727 in #793
• Fix bug: Log_Softmax with tuple axes + Add tests by @Faisal-Alsrheed in #794
• Port tab transformer example to keras core by @anas-rz in #621
• Update example losses on docstrings by @Frightera in #795
• Add model parallel distribution. by @qlzh727 in #797
• Increase-test-coverage-in-activations_test.py by @Faisal-Alsrheed in #799
• add ignore_class param to sparse CE loss by @AakashKumarNain in #599
• Convert pretraining_BERT.py example to keras core by @pranavvp16 in #801
• fixed apply_mask bug in losses by @jackd in #802
• Replace tf.keras in center-crop and resize tests by @sampathweb in #804
• Add a check for class_id argument by @Frightera in #796
• Add a dummy init for distribution, so it will be treat as a package. by @qlzh727 in #809
• Allow test using dynamic shapes to run on JAX. by @hertschuh in #810
• Keep "mse" as the metric name in the log by @haifeng-jin in #812
• Fixed misc mixed precision issues by @mattdangerw in #805
• Don't double cast layer norm weights in mixed precision by @mattdangerw in #815
• Add loss attribute for backward compatibility by @haifeng-jin in #813
• Add TorchModuleWrapper by @soumik12345 in #779
• Make sure the Test CI action fails on bad lint by @kiukchung in #818
• Format confusion_metrics_test by @mattdangerw in #821
• Fix the Jax distributed variable load issue. by @qlzh727 in #817
• Always save the build config when building a layer by @mattdangerw in #820
• Uses backend.shape in random preprocessing by @sampathweb in #822
• Don't lock functional models by @mattdangerw in #823
• Refactor conv_transpose padding by @guillaumebaquiast in #811
• Add rank>2 support for stft by @james77777778 in #825
• Fix reduce_shape + Add tests to operation_utils_test.py by @Faisal-Alsrheed in #826
• Fix weird broken test that never ran by @mattdangerw in #827
• Convert "English-to-Spanish translation with KerasNLP" to keras-core by @freedomtan in #777
• Replace assertTrue(isinstance(...)) with assertIsInstance for easier … by @hertschuh in #831
• Improve the flexibility of standardize_dtype and fix pad in torch backend by @james77777778 in #828
• Fix the distribution logic for the JAX trainer. by @qlzh727 in #832
• Add a docstring for compile by @mattdangerw in #838
• Enable codecov by @kiukchung in #840
• Add support for Tensorflow SparseTensors: core classes. by @hertschuh in #839
• bert-mlm port to keras-core with tf backend by @Mrutyunjay01 in #843
• Enable codecov flags and coverage carryover for keras_core and keras_… by @kiukchung in #841
• Update minimum python version to 3.9 to align with TF/JAX by @sampathweb in #848
• Update the eager_build logic for jax trainer. by @qlzh727 in #845
• Update return type for optimizer.apply by @mattdangerw in #850
• Add test,codecov,pypi status badges to README by @kiukchung in #852
• Fix autocast scope again by @mattdangerw in #849
• Add Export for JAX Backend by @nkovela1 in #819
• Increase test coverage + Fixing bug in static_call by @Faisal-Alsrheed in #847
• Add a loss scale optimizer by @mattdangerw in #851
• Increase test coverage in keras_core/utils by @Faisal-Alsrheed in #856
• Increase test coverage in keras_core/trainers by @Faisal-Alsrheed in #860
• Add a note in README.md regarding pre-import of backend by @SuryanarayanaY in #863
• Add optimizer weights to the model summary. by @qlzh727 in #859
• Add support for Tensorflow SparseTensors: core layers. by @hertschuh in #854
• Increase test coverage in keras_core/backend by @Faisal-Alsrheed in #864
• Add support for Tensorflow SparseTensors: reshaping layers. by @hertschuh in #865
• Respect the $KERAS_HOME environment variable for get_file by @mattdangerw in #868
• Don't convert int array input to floatx by @mattdangerw in #867
• run_layer_test also runs symbolic calls when input_data is provided. by @hertschuh in #870
• Increase test coverage in utils + Fix Bug in cast_to_common_dtype by @Faisal-Alsrheed in #875
• Fix stop_gradient in np by @james77777778 in #872
• Add sparseness inference for TensorFlow backend ops and base layer. by @hertschuh in #878
• Fix summary when optimizer is None by @mattdangerw in #879
• Add ops.nn.moments and speed-up normalization layers by @james77777778 in #866
• Don't show optimizer params if not optimizer or not built by @mattdangerw in #885
• Export dtype utils in keras_core.backend by @mattdangerw in #886
• Set actions.yml to run with read-only permissions by @pnacht in #882
• Fix model.save API for legacy H5 format by @nkovela1 in #891
• Add missing dtypes. by @gleize in #887
• Increase tests in utils by @Faisal-Alsrheed in #880
• syntax fix in cct example by @anas-rz in #898
• Use ops.rsqrt, improve normalization layers and enable ops fusion in tflite by @james77777778 in #892
• fixes #550: move torch tensors to cpu before to numpy array by @dkgaraujo in #853

New Contributors

• @kiukchung made their first contribution in #818
• @Mrutyunjay01 made their first contribution in #843
• @SuryanarayanaY made their first contribution in #863
• @pnacht made their first contribution in #882
• @gleize made their first contribution in #887
• @dkgaraujo made their first contribution in #853

Full Changelog: v0.1.5...v0.1.6