|TensorFlow Reaches Version 1|
|Written by Alex Armstrong|
|Thursday, 16 February 2017|
Google's computational package aimed at making AI easier, TensorFlow, is a little over a year old. Even so, at the TensorFlow Developer Summit, it has been deemed grown up enough to be called 1.0. It also has some new toys.
There is no doubt that TensorFlow has changed the overall feel of AI. Neural networks were something you only got into if you were prepared to commit very large resources. You still have to commit fairly large chunks of time and computing power using TensorFlow, but it seems so much more accessible. Of course there are other frameworks that will let you implement a neural network and some have specific advantages, but TensorFlow is the generalist and the one that non-specialist programmers try first.
The big new feature in version 1.0 is XLA - Accelerated Linear Algebra. This makes things go faster. The blog announcement says:
We'll soon publish updated implementations of several popular models to show how to take full advantage of TensorFlow 1.0 - including a 7.3x speedup on 8 GPUs for Inception v3 and 58x speedup for distributed Inception v3 training on 64 GPUs!
At the moment there are two backend modules. One generates code for multiple cpus and the other for multiple GPUs. The supported CPUs are x86-64 and ARM and NVIDIA GPUs.
The documentation states that the main objectives are:
At the other end of the scale we have a set of new high-level APIs - tf.layers, tf.metrics and tf.losses - which make it easier to create networks. For example, the layers API has a conv2d function which sets up a convolution layer in one call. Similarly the losses APi has lots of measures of how accurate the network is - false positives, cosine distance, rms error and so on and the losses has more complex measures used in training such as cross entropy. There is also a new tf.keras module which provides compatibility with Keras, another well known neural network library.
The new version also promises Python API stability making it more suitable for production. Note that the other language APIs- C, and the new Go and Java API - are not supported in this way and liable to change.
If you would like to see the videos from the 2017 Summit then there is a Playlist that you can spend many happy hours watching:
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|Last Updated ( Thursday, 16 February 2017 )|