Continuing the recent trend of rapid updates introducing significant fixes and new features, Google have released the first release candidate for Tensorflow 1.10. TensorFlow 1.10 RC0 brings some improvements in model training and evaluation, and also how Tensorflow runs in a local environment.
This is Tensorflow’s fifth update release in just over a month, which includes two major version updates, the previous one being Tensorflow 1.9
What’s new in Tensorflow 1.10 RC0?
- The tf.contrib.distributions module will be deprecated in this version. This module is primarily used to work with statistical distributions
- Upgrade to NCCL 2.2 will be mandatory in order to perform GPU computing with this version of Tensorflow, for added performance and efficiency.
- Model training speed can now be optimized by improving the communication between the model and the Tensorflow resources. For this, the RunConfig function has been updated in this version.
- The Tensorflow development team also announced support for Bazel – a popular build and testing automation software – and deprecated support for cmake starting with Tensorflow 1.11.
- This version also incorporated some bug fixes and performance improvements to the tf.data, tf.estimator and other related modules.
To get full details on the features list of this release candidate, you can check out Tensorflow’s official release page on Github.
No news on Tensorflow 2.0 yet
Many developers were expecting the next major release of Tensorflow, Tensorflow 2.0, to be released in late July or August. However, the announcement of this release candidate and the mention of the next version update (1.11) means they will have to wait for some more time before they get to know more about the next breakthrough release.