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What’s new in TensorFlow 2.16

TensorFlow 2.16 has been released! Highlights of this release (and 2.15) include Clang as default compiler for building TensorFlow CPU wheels on Windows, Keras 3 as default version, support for Python 3.12, and much more! For the full release note, please click here.

Note: Release updates on the new multi-backend Keras will be published on keras.io starting with Keras 3.0. For more information, please see https://keras.io/keras_3/.

TensorFlow Core

Clang 17

Clang is now the preferred 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, as has been the case before. Intel owned the implementation and delivery of this change within the 3P Official Build program.

Keras 3

Keras 3 will be the default Keras version for TensorFlow 2.16 onwards. You may need to update your script to use Keras 3. Please refer to the new Keras documentation for Keras 3 (https://keras.io/keras_3). Keras 2 will continue to be released alongside TensorFlow as tf_keras. To continue using Keras 2 with TensorFlow 2.16+:

  • Install tf-keras vía pip install tf-keras~=2.16
  • Switch tf.keras to use Keras 2 (tf-keras), by setting environment variable TF_USE_LEGACY_KERAS=1 directly or in your Python program by doing import os;os.environ["TF_USE_LEGACY_KERAS"]=”1”. Please note that this needs to be set before importing TensorFlow and will set it for all packages in your Python runtime program.

Estimator API

tf.estimator API is removed. If you need to use the estimator API, you need to use TF 2.15 or an earlier version.

Apple Silicon

If you previously installed TensorFlow using pip install tensorflow-macos, please update your installation method. Use pip install tensorflow from now on. tensorflow-macos package will no longer receive updates. Future updates will be released to tensorflow.

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