Clang is now the default compiler to build TensorFlow CPU wheels on the Windows Platform starting with this release. The currently supported version is LLVM/clang 17. The official Wheels-published on PyPI will be based on Clang; however, users retain the option to build wheels using the MSVC compiler following the steps mentioned in https://www.tensorflow.org/install/source_windows as has been the case before
TensorFlow 2.16 will be released as TF 2.16.1 (instead of 2.16.0). The patch release will be done as 2.16.2 during the next release cycle.
Breaking Changes
tf.summary.trace_on now takes a profiler_outdir argument. This must be set if profiler arg is set to True.
tf.summary.trace_export's profiler_outdir arg is now a no-op. Enabling the profiler now requires setting profiler_outdir in trace_on.
tf.estimator
The tf.estimator API is removed.
To continue using tf.estimator, you will need to use TF 2.15 or an earlier version.
Keras 3.0 will be the default Keras version. You may need to update your script to use Keras 3.0.
To switch tf.keras to use Keras 2 (tf-keras), set the environment variable TF_USE_LEGACY_KERAS=1 directly or in your python program with import os;os.environ["TF_USE_LEGACY_KERAS"]="1". Please note that this will set it for all packages in your Python runtime program
Change the keras import: replace import tensorflow.keras as keras or import keras with import tf_keras as keras. Update any tf.keras references to keras.
Apple Silicon users: If you previously installed TensorFlow using pip install tensorflow-macos, please update your installation method. Use pip install tensorflow from now on.
Mac x86 users: Mac x86 builds are being deprecated and will no longer be
released as a Pip package from TF 2.17 onwards.
Known Caveats
Full aarch64 Linux and Arm64 macOS wheels are now published to the tensorflow pypi repository and no longer redirect to a separate package.
Major Features and Improvements
Support for Python 3.12 has been added.
tensorflow-tpu package is now available for easier TPU based installs.
TensorFlow pip packages are now built with CUDA 12.3 and cuDNN 8.9.7
Added experimental support for float16 auto-mixed precision using the new
AMX-FP16 instruction set on X86 CPUs.
Clang is now the default compiler to build TensorFlow CPU wheels on the Windows Platform starting with this release. The currently supported version is LLVM/clang 17. The official Wheels-published on PyPI will be based on Clang; however, users retain the option to build wheels using the MSVC compiler following the steps mentioned in https://www.tensorflow.org/install/source_windows as has been the case before
TensorFlow 2.16 will be released as TF 2.16.1 (instead of 2.16.0). The patch release will be done as 2.16.2 during the next release cycle.
Breaking Changes
tf.summary.trace_on now takes a profiler_outdir argument. This must be set if profiler arg is set to True.
tf.summary.trace_export's profiler_outdir arg is now a no-op. Enabling the profiler now requires setting profiler_outdir in trace_on.
tf.estimator
The tf.estimator API is removed.
To continue using tf.estimator, you will need to use TF 2.15 or an earlier version.
Keras 3.0 will be the default Keras version. You may need to update your script to use Keras 3.0.
To switch tf.keras to use Keras 2 (tf-keras), set the environment variable TF_USE_LEGACY_KERAS=1 directly or in your python program with import os;os.environ["TF_USE_LEGACY_KERAS"]="1". Please note that this will set it for all packages in your Python runtime program
Change the keras import: replace import tensorflow.keras as keras or import keras with import tf_keras as keras. Update any tf.keras references to keras.
Apple Silicon users: If you previously installed TensorFlow using pip install tensorflow-macos, please update your installation method. Use pip install tensorflow from now on.
Mac x86 users: Mac x86 builds are being deprecated and will no longer be
released as a Pip package from TF 2.17 onwards.
Known Caveats
Full aarch64 Linux and Arm64 macOS wheels are now published to the tensorflow pypi repository and no longer redirect to a separate package.
Major Features and Improvements
Support for Python 3.12 has been added.
tensorflow-tpu package is now available for easier TPU based installs.
TensorFlow pip packages are now built with CUDA 12.3 and cuDNN 8.9.7
Added experimental support for float16 auto-mixed precision using the new
AMX-FP16 instruction set on X86 CPUs.
Bug Fixes and Other Changes
tf.lite
Added support for stablehlo.gather.
... (truncated)
Commits
5bc9d26 Merge pull request #63073 from Intel-tensorflow/kanvi/update-release-notes
086d2cc Merge pull request #63127 from rtg0795/r2.16
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Bumps the tensorflow group with 1 update: tensorflow-cpu.
Updates
tensorflow-cpu
from 2.15.0 to 2.16.1Release notes
Sourced from tensorflow-cpu's releases.
... (truncated)
Changelog
Sourced from tensorflow-cpu's changelog.
... (truncated)
Commits
5bc9d26
Merge pull request #63073 from Intel-tensorflow/kanvi/update-release-notes086d2cc
Merge pull request #63127 from rtg0795/r2.1682cdec2
Update RELEASE.md563129d
Merge pull request #63120 from tensorflow/MarkDaoust-2.16-release-notes152a11b
Merge branch 'r2.16' into MarkDaoust-2.16-release-notes1196a06
Merge pull request #63121 from tensorflow-jenkins/version-numbers-2.16.1-2564946faa44
Update release notes for TensorFlow 2.16.1 (#63117)5fdacf3
Merge pull request #63119 from tensorflow/patch-r2.16-release-notes887bcc9
Update version numbers to 2.16.1f1b3d80
Fix formatting.Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting
@dependabot rebase
.Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot show