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@IMvision12 IMvision12 commented Apr 25, 2024

@fchollet

Sorry Last PR got messed up!

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codecov-commenter commented Apr 25, 2024

Codecov Report

Attention: Patch coverage is 73.46939% with 13 lines in your changes are missing coverage. Please review.

Project coverage is 78.27%. Comparing base (63586fa) to head (0d31ae1).

Files Patch % Lines
keras/src/ops/nn.py 80.00% 2 Missing and 1 partial ⚠️
keras/src/backend/jax/nn.py 71.42% 1 Missing and 1 partial ⚠️
keras/src/backend/numpy/nn.py 71.42% 1 Missing and 1 partial ⚠️
keras/src/backend/tensorflow/nn.py 75.00% 1 Missing and 1 partial ⚠️
keras/src/backend/torch/nn.py 75.00% 1 Missing and 1 partial ⚠️
keras/api/_tf_keras/keras/ops/__init__.py 0.00% 1 Missing ⚠️
keras/api/_tf_keras/keras/ops/nn/__init__.py 0.00% 1 Missing ⚠️
Additional details and impacted files
@@            Coverage Diff             @@
##           master   #19616      +/-   ##
==========================================
- Coverage   78.27%   78.27%   -0.01%     
==========================================
  Files         498      498              
  Lines       45308    45357      +49     
  Branches     8346     8352       +6     
==========================================
+ Hits        35466    35502      +36     
- Misses       8095     8103       +8     
- Partials     1747     1752       +5     
Flag Coverage Δ
keras 78.12% <73.46%> (-0.01%) ⬇️
keras-jax 62.28% <42.85%> (-0.03%) ⬇️
keras-numpy 56.66% <44.89%> (-0.02%) ⬇️
keras-tensorflow 63.68% <44.89%> (-0.03%) ⬇️
keras-torch 62.29% <44.89%> (-0.02%) ⬇️

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Thanks for the update -- LGTM!

@google-ml-butler google-ml-butler bot added kokoro:force-run ready to pull Ready to be merged into the codebase labels Apr 25, 2024
@fchollet fchollet merged commit 74df926 into keras-team:master Apr 25, 2024
@google-ml-butler google-ml-butler bot removed ready to pull Ready to be merged into the codebase kokoro:force-run labels Apr 25, 2024
@IMvision12 IMvision12 deleted the psnr branch April 26, 2024 01:57
fchollet added a commit that referenced this pull request May 3, 2024
* Introduce float8 training (#19488)

* Add float8 training support

* Add tests for fp8 training

* Add `quantize_and_dequantize` test

* Fix bugs and add float8 correctness tests

* Cleanup

* Address comments and cleanup

* Add docstrings and some minor refactoring

* Add `QuantizedFloat8DTypePolicy`

* Add dtype policy setter

* Fix torch dynamo issue by using `self._dtype_policy`

* Improve test coverage

* Add LoRA to ConvND layers (#19516)

* Add LoRA to `BaseConv`

* Add tests

* Fix typo

* Fix tests

* Fix tests

* Add path to run keras on dm-tree when optree is not available.

* feat(losses): add Tversky loss implementation (#19511)

* feat(losses): add Tversky loss implementation

* adjusted documentation

* Update KLD docs

* Models and layers now return owned metrics recursively. (#19522)

- added `Layer.metrics` to return all metrics owned by the layer and its sub-layers recursively.
- `Layer.metrics_variables` now returns variables from all metrics recursively, not just the layer and its direct sub-layers.
- `Model.metrics` now returns all metrics recursively, not just the model level metrics.
- `Model.metrics_variables` now returns variables from all metrics recursively, not just the model level metrics.
- added test coverage to test metrics and variables 2 levels deep.

This is consistent with the Keras 2 behavior and how `Model/Layer.variables` and `Model/Layer.weights` work.

* Update IoU ignore_class handling

* Fix `RandomBrightness`, Enhance `IndexLookup` Initialization and Expand Test Coverage for `Preprocessing Layers` (#19513)

* Add tests for CategoryEncoding class in category_encoding_test.py

* fix

* Fix IndexLookup class initialization and add test cases

* Add test case for IndexLookupLayerTest without vocabulary

* Fix IndexLookup class initialization

* Add normalization test cases

* Add test cases for Hashing class

* Fix value range validation error in RandomBrightness class

* Refactor IndexLookup class initialization and add test cases

* Reffix ndexLookup class initialization and afix est cases

* Add test for spectral norm

* Add missing test decorator

* Fix torch test

* Fix code format

* Generate API (#19530)

* API Generator for Keras

* API Generator for Keras

* Generates API Gen via api_gen.sh

* Remove recursive import of _tf_keras

* Generate API Files via api_gen.sh

* Update APIs

* Added metrics from custom `train_step`/`test_step` are now returned. (#19529)

This works the same way as in Keras 2, whereby the metrics are returned directly from the logs if the set of keys doesn't match the model metrics.

* Use temp dir and abs path in `api_gen.py` (#19533)

* Use temp dir and abs path

* Use temp dir and abs path

* Update Readme

* Update API

* Fix gradient accumulation when using `overwrite_with_gradient` during float8 training (#19534)

* Fix gradient accumulation with `overwrite_with_gradient` in float8 training

* Add comments

* Fix annotation

* Update code path in ignore path (#19537)

* Add operations per run (#19538)

* Include input shapes in model visualization.

* Add pad_to_aspect_ratio feature in ops.image.resize

* Add pad_to_aspect_ratio feature in Resizing layer.

* Fix incorrect usage of `quantize` (#19541)

* Add logic to prevent double quantization

* Add detailed info for double quantization error

* Update error msg

* Add eigh op.

* Add keepdim in argmax/argmin.

* Fix small bug in model.save_weights (#19545)

* Update public APIs.

* eigh should work on JAX GPU

* Copy init to keras/__init__.py (#19551)

* Revert "Copy init to keras/__init__.py (#19551)" (#19552)

This reverts commit da9af61.

* sum-reduce inlined losses

* Remove the dependency on `tensorflow.experimental.numpy` and support negative indices for `take` and `take_along_axis` (#19556)

* Remove `tfnp`

* Update numpy api

* Improve test coverage

* Improve test coverage

* Fix `Tri` and `Eye` and increase test converage

* Update `round` test

* Fix `jnp.round`

* Fix `diag` bug for iou_metrics

* Add op.select.

* Add new API for select

* Make `ops.abs` and `ops.absolute` consistent between backends. (#19563)

- The TensorFlow implementation was missing `convert_to_tensor`
- The sparse annotation was unnecessarily applied twice
- Now `abs` calls `absolute` in all backends

Also fixed TensorFlow `ops.select`.

* Add pickle support for Keras model (#19555)

* Implement unit tests for pickling

* Reformat model_test

* Reformat model_test

* Rename depickle to unpickle

* Rename depickle to unpickle

* Reformat

* remove a comment

* Ellipsis Serialization and tests (#19564)

* Serialization and tests

* Serialization and tests

* Serialization and tests

* Make TF one_hot input dtype less strict.

* Fix einsum `_int8_call` (#19570)

* CTC Decoding for JAX and Tensorflow (#19366)

* Tensorflow OP for CTC decoding

* JAX op for CTC greedy decoding

* Update CTC decoding documentation

* Fix linting issues

* Fix trailing whitespace

* Simplify returns in tensorflow CTC wrapper

* Fix CTC decoding error messages

* Fix line too long

* Bug fixes to JAX CTC greedy decoder

* Force int typecast in TF CTC decoder

* Unit tests for CTC greedy decoding

* Add unit test for CTC beam search decoding

* Fix mask index set location in JAX CTC decoding

* CTC beam search decoding for JAX

* Fix unhandled token repetitions in ctc_beam_search_decode

* Fix merge_repeated bug in CTC beam search decode

* Fix beam storage and repetition bugs in JAX ctc_decode

* Remove trailing whitespace

* Fix ordering bug for ties in JAX CTC beam search

* Cast sequence lengths to integers in JAX ctc_decode

* Remove line break in docstring

* CTC beam search decoding for JAX

* Fix unhandled token repetitions in ctc_beam_search_decode

* Fix merge_repeated bug in CTC beam search decode

* Fix beam storage and repetition bugs in JAX ctc_decode

* Fix ordering bug for ties in JAX CTC beam search

* Generate public api directory

* Add not implemented errors for NumPy and Torch CTC decoding

* Remove unused redefinition of JAX ctc_beam_search_decode

* Docstring edits

* Expand nan_to_num args.

* Add vectorize op.

* list insert requires index (#19575)

* Add signature and exclude args to knp.vectorize.

* Fix the apis of `dtype_polices` (#19580)

* Fix api of `dtype_polices`

* Update docstring

* Increase test coverage

* Fix format

* Fix keys of `save_own_variables` and `load_own_variables` (#19581)

* Fix JAX CTC test.

* Fix loss_weights handling in single output case

* Fix JAX vectorize.

* Move _tf_keras directory to the root of the pip package.

* One time fix to _tf_keras API.

* Convert return type imdb.load_data to nparray (#19598)

Convert return type imdb.load_data to Numpy array. Currently X_train and X-test returned as list.

* Fix typo

* fix api_gen.py for legacy (#19590)

* fix api_gen.py for legacy

* merge api and legacy for _tf_keras

* Improve int8 for `Embedding` (#19595)

* pin torch < 2.3.0 (#19603)

* Clean up duplicated `inputs_quantizer` (#19604)

* Cleanup duplicated `inputs_quantizer` and add type check for `input_spec` and `supports_masking`

* Revert setter

* output format changes and errors in github (#19608)

* Provide write permission to action for cache management. (#19606)

* Pickle support for all saveables (#19592)

* Pickle support

* Add keras pickleable mixin

* Reformat

* Implement pickle all over

* reformat

* Reformat

* Keras saveable

* Keras saveable

* Keras saveable

* Keras saveable

* Keras saveable

* obj_type

* Update pickleable

* Saveable logic touchups

* Add slogdet op.

* Update APIs

* Remove unused import

* Refactor CTC APIs (#19611)

* Add `ctc_loss` and `ctc_decode` for numpy backend, improve imports and tests

* Support "beam_search" strategy for torch's `ctc_decode`

* Improve `ctc_loss`

* Cleanup

* Refactor `ctc_decode`

* Update docstring

* Update docstring

* Add `CTCDecode` operation and ensure dtype inference of `ctc_decode`

* Fix `name` of `losses.CTC`

* update the namex version requirements (#19617)

* Add `PSNR` API (#19616)

* PSNR

* Fix

* Docstring format

* Remove `PYTORCH_ENABLE_MPS_FALLBACK` flag requirement for mps (#19618)

* Remove `PYTORCH_ENABLE_MPS_FALLBACK` flag requirement for mps

* Formatting

* Implement custom layer insertion in clone_model. (#19610)

* Implement custom layer insertion in clone_model.

* Add recursive arg and tests.

* Add nested sequential cloning test

* Fix bidir lstm saving issue.

* Fix CI

* Fix cholesky tracing with jax

* made extract_patches dtype agnostic (#19621)

* Simplify Bidirectional implementation

* Add support for infinite `PyDataset`s. (#19624)

`PyDataset` now uses the `num_batches` property instead of `__len__` to support `None`, which is how one indicates the dataset is infinite. Note that infinite datasets are not shuffled.

Fixes #19528

Also added exception reporting when using multithreading / multiprocessing. Previously, the program would just hang with no error reported.

* Fix dataset shuffling issue.

* Update version string.

* Minor fix

* Restore version string resolution in pip_build.

* Speed up `DataAdapter` tests by testing only the current backend. (#19625)

There is no use case for using an iterator for a different backend than the current backend.

Also:
- limit the number of tests using multiprocessing, the threading tests give us good coverage.
- fixed the `test_exception_reported` test, which was not actually exercising the multiprocessing / multithreading cases.
- removed unused `init_pool` method.

* feat(ops): support np.argpartition (#19588)

* feat(ops): support np.argpartition

* updated documentation, type-casting, and tf implementation

* fixed tf implementation

* added torch cast to int32

* updated torch type and API generated files

* added torch output type cast

* test(trainers): add test_errors implementation for ArrayDataAdapter class (#19626)

* Fix torch GPU CI

* Fix argmax/argmin keepdims with defined axis in TF

* Misc fixes in TF backend ops.

* Fix `argpartition` cuda bug in torch (#19634)

* fix(ops): specify NonZero output dtype and add test coverage (#19635)

* Fix `ops.ctc_decode` (#19633)

* Fix greedy ctc decode

* Remove print

* Fix `tf.nn.ctc_beam_search_decoder`

* Change default `mask_index` to `0`

* Fix losses test

* Update

* Ensure the same rule applies for np arrays in autocasting (#19636)

* Ensure the same rule applies for np arrays in autocasting

* Trigger CI by adding docstring

* Update

* Update docstring

* Fix `istft` and add class `TestMathErrors` in `ops/math_test.py` (#19594)

* Fix and test math functions for jax backend

* run /workspaces/keras/shell/format.sh

* refix

* fix

* fix _get_complex_tensor_from_tuple

* fix

* refix

* Fix istft function to handle inputs with less than 2 dimensions

* fix

* Fix ValueError in istft function for inputs with less than 2 dimensions

* Return a tuple from `ops.shape` with the Torch backend. (#19640)

With Torch, `x.shape` returns a `torch.Size`, which is a subclass of `tuple` but can cause different behaviors. In particular `convert_to_tensor` does not work on `torch.Size`.

This fixes #18900

* support conv3d on cpu for TF (#19641)

* Enable cudnn rnns when dropout is set (#19645)

* Enable cudnn rnns when dropout is set

* Fix

* Fix plot_model for input dicts.

* Fix deprecation warning in torch

* Bump the github-actions group with 2 updates (#19653)

Bumps the github-actions group with 2 updates: [actions/upload-artifact](https://github.com/actions/upload-artifact) and [github/codeql-action](https://github.com/github/codeql-action).


Updates `actions/upload-artifact` from 4.3.1 to 4.3.3
- [Release notes](https://github.com/actions/upload-artifact/releases)
- [Commits](actions/upload-artifact@5d5d22a...6546280)

Updates `github/codeql-action` from 3.24.9 to 3.25.3
- [Release notes](https://github.com/github/codeql-action/releases)
- [Changelog](https://github.com/github/codeql-action/blob/main/CHANGELOG.md)
- [Commits](github/codeql-action@1b1aada...d39d31e)

---
updated-dependencies:
- dependency-name: actions/upload-artifact
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: github-actions
- dependency-name: github/codeql-action
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] <[email protected]>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* Bump the python group with 2 updates (#19654)

Bumps the python group with 2 updates: torch and torchvision.


Updates `torch` from 2.2.1+cu121 to 2.3.0+cu121

Updates `torchvision` from 0.17.1+cu121 to 0.18.0+cu121

---
updated-dependencies:
- dependency-name: torch
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: python
- dependency-name: torchvision
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: python
...

Signed-off-by: dependabot[bot] <[email protected]>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* Revert "Bump the python group with 2 updates (#19654)" (#19655)

This reverts commit 09133f4.

---------

Signed-off-by: dependabot[bot] <[email protected]>
Co-authored-by: james77777778 <[email protected]>
Co-authored-by: Francois Chollet <[email protected]>
Co-authored-by: Luca Pizzini <[email protected]>
Co-authored-by: hertschuh <[email protected]>
Co-authored-by: Faisal Alsrheed <[email protected]>
Co-authored-by: Ramesh Sampath <[email protected]>
Co-authored-by: Sachin Prasad <[email protected]>
Co-authored-by: Uwe Schmidt <[email protected]>
Co-authored-by: Luke Wood <[email protected]>
Co-authored-by: Maanas Arora <[email protected]>
Co-authored-by: AlexanderLavelle <[email protected]>
Co-authored-by: Surya <[email protected]>
Co-authored-by: Shivam Mishra <[email protected]>
Co-authored-by: Haifeng Jin <[email protected]>
Co-authored-by: IMvision12 <[email protected]>
Co-authored-by: Gabriel Rasskin <[email protected]>
Co-authored-by: Vachan V Y <[email protected]>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
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