Keras Core 0.1.3 release
Highlights
- Add compatibility with legacy whole-model
h5
saving and loading - Add
keras_core.ops.fft
andkeras_core.ops.fft2
- Add
keras_core.ops.image.affine_transform
- Add
keras_core.ops.image.extract_patches
- Bug fixes and performance improvements
- Now compatible with TensorFlow versions 2.8 to 2.13
What's Changed
- Add Nadam for torch backend by @haifeng-jin in #551
- Fix multi-dimension sample weights passed to mean metrics by @mattdangerw in #552
- Update operation_utils.py - Added docstrings by @sqali in #514
- Node test by @kamathis4 in #557
- Add
affine_transform
op to all backends by @james77777778 in #477 - Add FFT Ops by @abheesht17 in #480
- Added CategoryEncoding to keras_core.ops.nn by @hazemessamm in #490
- Symbolic Args test by @kamathis4 in #536
- Converted to Keras Core: DeepLabV3Plus by @anas-rz in #545
- test and move backend agnostic example by @anas-rz in #567
- Port few shot learning with reptile by @anas-rz in #564
- Add some additional TF SavedModel tests by @nkovela1 in #569
- Fixes Torch-GPU Test failure on initializers/random_initializers_test.py by @sampathweb in #575
- Keras tensor functions by @kamathis4 in #576
- add fori_loop op to all 3 backends by @GallagherCommaJack in #462
- Fix Module Utils
_available
attribute by @sampathweb in #579 - Add some docstrings to
keras_core/ops/numpy.py
by @guillaumebaquiast in #558 - Add random seed support for torch dropout by @haifeng-jin in #568
- Port Keypoint detection to backend agnostic-keras-core by @anas-rz in #546
- Make random flip backend agnostic by @AmedeoBiolatti in #515
- Convert RandomTranslation to the backend-agnostic implementation by @james77777778 in #572
- doc: DocString for numpy.amax by @pranavvp16 in #582
- Add backend-agnostic video transformers example by @soumik12345 in #583
- Converted cutmix example to Keras Core by @cosmo3769 in #527
- docString for numpy.amin by @pranavvp16 in #586
- Update Tests for specific backend imports by @sampathweb in #591
- implement patch extraction in ops by @anas-rz in #581
- Converted to keras core external attention by @anas-rz in #529
- Backend consistency in handling of empty tensor in
min
andmax
by @guillaumebaquiast in #592 - Fix more spots torch != numpy for reductions by @mattdangerw in #596
- Backend-agnostic port of Image classification with Vision Transformer by @soumik12345 in #589
- More backend agnostic in cutmix and mixup file by @cosmo3769 in #593
- Always install the correct version with pip_build by @mattdangerw in #595
- Export ops.cond by @AmedeoBiolatti in #577
- Convert pretrained word embeddings to Keras Core by @freedomtan in #600
- port gcam backend agnostic by @anas-rz in #601
- Converted NER with transformers example to keras_core by @pranavvp16 in #594
- Add tf.keras backwards compat for nearly all non-experimental symbols by @fchollet in #603
- Cache self.call() signature by @haifeng-jin in #606
- Porting over changes to Torch and JAX keras-core distribution guides … by @hertschuh in #607
- Improve
TensorFlowTrainer
compatibility for TF<2.9 by @taehoonlee in #598 - Convert RandomZoom to backend-agnostic and improve
affine_transform
by @james77777778 in #574 - Add the unstack operation to keras core by @tirthasheshpatel in #597
- Port digit addition rnn example to keras-core by @anas-rz in #614
- Set Jit compile only if Model supports it by @sampathweb in #616
- Port big transfer to keras core by @anas-rz in #615
- Implements H5 legacy saving for Keras Core by @nkovela1 in #605
- Add docstrings in numpy by @guillaumebaquiast in #617
New Contributors
- @james77777778 made their first contribution in #477
- @hazemessamm made their first contribution in #490
- @GallagherCommaJack made their first contribution in #462
- @guillaumebaquiast made their first contribution in #558
- @AmedeoBiolatti made their first contribution in #515
- @pranavvp16 made their first contribution in #582
- @cosmo3769 made their first contribution in #527
- @freedomtan made their first contribution in #600
- @taehoonlee made their first contribution in #598
Full Changelog: v0.1.2...v0.1.3