Update tensorflow requirement from !=2.6.0,!=2.6.1,<2.13.0,>=2.2.0 to >=2.2.0,!=2.6.0,!=2.6.1,<2.14.0

[dependabot]

Updates the requirements on tensorflow to permit the latest version.

Release notes

Sourced from tensorflow's releases.

TensorFlow 2.13.0

Release 2.13.0

TensorFlow

Breaking Changes

• The LMDB kernels have been changed to return an error. This is in preparation for completely removing them from TensorFlow. The LMDB dependency that these kernels are bringing to TensorFlow has been dropped, thus making the build slightly faster and more secure.

Major Features and Improvements

• tf.lite

  • Added 16-bit and 64-bit float type support for built-in op cast.
  • The Python TF Lite Interpreter bindings now have an option experimental_disable_delegate_clustering to turn-off delegate clustering.
  • Added int16x8 support for the built-in op exp
  • Added int16x8 support for the built-in op mirror_pad
  • Added int16x8 support for the built-in ops space_to_batch_nd and batch_to_space_nd
  • Added 16-bit int type support for built-in op less, greater_than, equal
  • Added 8-bit and 16-bit support for floor_div and floor_mod.
  • Added 16-bit and 32-bit int support for the built-in op bitcast.
  • Added 8-bit/16-bit/32-bit int/uint support for the built-in op bitwise_xor
  • Added int16 indices support for built-in op gather and gather_nd.
  • Added 8-bit/16-bit/32-bit int/uint support for the built-in op right_shift
  • Added reference implementation for 16-bit int unquantized add.
  • Added reference implementation for 16-bit int and 32-bit unsigned int unquantized mul.
  • add_op supports broadcasting up to 6 dimensions.
  • Added 16-bit support for top_k.

• tf.function

  • ConcreteFunction (tf.types.experimental.ConcreteFunction) as generated through get_concrete_function now performs holistic input validation similar to calling tf.function directly. This can cause breakages where existing calls pass Tensors with the wrong shape or omit certain non-Tensor arguments (including default values).

• tf.nn

  • tf.nn.embedding_lookup_sparse and tf.nn.safe_embedding_lookup_sparse now support ids and weights described by tf.RaggedTensors.
  • Added a new boolean argument allow_fast_lookup to tf.nn.embedding_lookup_sparse and tf.nn.safe_embedding_lookup_sparse, which enables a simplified and typically faster lookup procedure.

• tf.data

  • tf.data.Dataset.zip now supports Python-style zipping, i.e. Dataset.zip(a, b, c).
  • tf.data.Dataset.shuffle now supports tf.data.UNKNOWN_CARDINALITY When doing a "full shuffle" using dataset = dataset.shuffle(dataset.cardinality()). But remember, a "full shuffle" will load the full dataset into memory so that it can be shuffled, so make sure to only use this with small datasets or datasets of small objects (like filenames).

• tf.math

  • tf.nn.top_k now supports specifying the output index type via parameter index_type. Supported types are tf.int16, tf.int32 (default), and tf.int64.

• tf.SavedModel

  • Introduced class method tf.saved_model.experimental.Fingerprint.from_proto(proto), which can be used to construct a Fingerprint object directly from a protobuf.

... (truncated)

Changelog

Sourced from tensorflow's changelog.

Release 2.13.0

Breaking Changes

• tf.keras

  • Removed the Keras scikit-learn API wrappers (KerasClassifier and KerasRegressor), which had been deprecated in August 2021. We recommend using SciKeras instead.
  • The default Keras model saving format is now the Keras v3 format: calling model.save("xyz.keras") will no longer create a H5 file, it will create a native Keras model file. This will only be breaking for you if you were manually inspecting or modifying H5 files saved by Keras under a .keras extension. If this breaks you, simply add save_format="h5" to your .save() call to revert back to the prior behavior.
  • Added keras.utils.TimedThread utility to run a timed thread every x seconds. It can be used to run a threaded function alongside model training or any other snippet of code.
  • In the keras PyPI package, accessible symbols are now restricted to symbols that are intended to be public. This may affect your code if you were using import keras and you used keras functions that were not public APIs, but were accessible in earlier versions with direct imports. In those cases, please use the following guideline:
    • The API may be available in the public Keras API under a different name, so make sure to look for it on keras.io or TensorFlow docs and switch to the public version.
    • It could also be a simple python or TF utility that you could easily copy over to your own codebase. In those case, just make it your own!
    • If you believe it should definitely be a public Keras API, please open a feature request in keras GitHub repo.
    • As a workaround, you could import the same private symbol keras keras.src, but keep in mind the src namespace is not stable and those APIs may change or be removed in the future.

• The LMDB kernels have been changed to return an error. This is in preparation for completely removing them from TensorFlow. The LMDB dependency that these kernels are bringing to TensorFlow has been dropped, thus making the build slightly faster and more secure.

Known Caveats

... (truncated)

Commits

• 1cb1a03 updating release notes with security fixes (#61119)
• bd4c381 Merge pull request #61102 from tensorflow/venkat-patch-123
• 2a17745 update estimator and keras versions
• 71a2f7f Merge pull request #61097 from tensorflow-jenkins/version-numbers-2.13.0-1179
• 3e6e3ce Update version numbers to 2.13.0
• 6657f49 Merge pull request #61075 from elfringham/limit_numpy
• 90389e9 Fix unit test failure caused by numpy update
• 5b6abc8 Merge pull request #60904 from tensorflow/venkat-patch-22
• 5763bc3 Fix TPUExecute for TPU embedding operations. Create temporary device memory
• 1c27a49 Merge pull request #60888 from tensorflow/venkat-patch-16
• Additional commits viewable in compare view

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[codecov]

Codecov Report

Merging #824 (c7b3df3) into master (8219ec3) will increase coverage by 0.01%.
The diff coverage is n/a.

Additional details and impacted files

@@            Coverage Diff             @@
##           master     #824      +/-   ##
==========================================
+ Coverage   81.87%   81.89%   +0.01%     
==========================================
  Files         159      159              
  Lines       10336    10336              
==========================================
+ Hits         8463     8465       +2     
+ Misses       1873     1871       -2     

see 1 file with indirect coverage changes

[ascillitoe]

TODO: Run notebook tests once #841 and #842 merged.

[jklaise]

@dependabot rebase

[jklaise]

Tests running here: https://github.com/SeldonIO/alibi-detect/actions/runs/5588718443

[jklaise]

Most jobs time-out on one notebook, Windows job stopped for some other reason, have re-triggered.

[jklaise]

All pass with the exception of one timeout on MacOS, will merge.