# What's new in TensorFlow 2.13 and Keras 2.13?

DevFeed: [What's new in TensorFlow 2.13 and Keras 2.13?](<https://devfeed.tech/articles/what-s-new-in-tensorflow-2-13-and-keras-2-13-7377.md>)

Original publisher: [Read original article](<https://blog.tensorflow.org/2023/07/whats-new-in-tensorflow-213-and-keras-213.html>)

Author: TensorFlow Blog (noreply@blogger.com)

Published: 2023-07-25T16:00:00Z

Content type: release

Language: en

Sources: [The TensorFlow Blog](<https://devfeed.tech/sources/the-tensorflow-blog.md>)

Topics: [TensorFlow Core](<https://devfeed.tech/topics/tensorflow-core.md>), [Keras](<https://devfeed.tech/topics/keras.md>), [TensorFlow Lite](<https://devfeed.tech/topics/tensorflow-lite.md>), [datasets](<https://devfeed.tech/topics/datasets.md>), [API](<https://devfeed.tech/topics/api.md>)

Tags: [apple](<https://devfeed.tech/tags/apple.md>), [datasets](<https://devfeed.tech/tags/datasets.md>), [google](<https://devfeed.tech/tags/google.md>), [keras](<https://devfeed.tech/tags/keras.md>), [mac](<https://devfeed.tech/tags/mac.md>), [python](<https://devfeed.tech/tags/python.md>), [quantization](<https://devfeed.tech/tags/quantization.md>), [release](<https://devfeed.tech/tags/release.md>), [tensorflow](<https://devfeed.tech/tags/tensorflow.md>), [tensorflow-core](<https://devfeed.tech/tags/tensorflow-core.md>), [tensorflow-lite](<https://devfeed.tech/tags/tensorflow-lite.md>), [usability](<https://devfeed.tech/tags/usability.md>)

## AI overview

TensorFlow 2.13 and Keras 2.13 introduce Apple Silicon wheels, make the Keras V3 format the default for .keras files, and add improvements to TensorFlow Lite, tf.data, dataset padding, and CPU BF16 execution.

## Source excerpt

Posted by the TensorFlow and Keras Teams TensorFlow 2.13 and Keras 2.13 have been released! Highlights of this release include publishing Apple Silicon wheels, the new Keras V3 format being default for .keras extension files and many more! TensorFlow Core Apple Silicon wheels for TensorFlow TensorFlow 2.13 is the first version to provide Apple Silicon wheels, which means when you install TensorFlow on an Apple Silicon Mac, you will be able to use the latest version of TensorFlow. The nightly builds for Apple Silicon wheels were released in March 2023 and this new support will enable more fine-grained testing, thanks to technical collaboration between Apple, MacStadium, and Google. tf.lite The Python TensorFlow Lite Interpreter bindings now have an option to use experimental_disable_delegate_clustering flag to turn-off delegate clustering during delegate graph partitioning phase. You can set this flag in TensorFlow Lite interpreter Python API interpreter = new Interpreter(file_of_a_tensorflowlite_model, experimental_preserve_all_tensors=False) The flag is set to False by default. This is an advanced feature in experimental that is designed for people who insert explicit control dependencies via with tf.control_dependencies() or need to change graph execution order. Besides, there are several operator improvements in TensorFlow Lite in 2.13 add operation now supports broadcasting up to 6 dimensions. This will remove explicit broadcast ops from many models. The new implementation is also much faster than the current one which calculates the entire index for both inputs the the input instead of only calculating the part that changes. Improve the coverage for 16x8 quantization by enabling int16x8 ops for exp, mirror_pad, space_to_batch_nd, batch_to_space_nd Increase the coverage of integer data types enabled int16 for less, greater_than, equal, bitcast, bitwise_xor, right_shift, top_k, mul, and int16 indices for gather and gather_nd enabled int8 for floor_div and floor_m