TensorFlow 1.7.0 released: updates and improvements

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Early this month, TensorFlow released its major version 1.6.0. Soon after that they announced rc-0 and rc-1 for TensorFlow 1.7.0. And to our surprise, TensorFlow 1.7.0 has arrived much sooner than expected! Clearly moving quickly is essential to the TensorFlow team.

Both the rc-0 and rc-1 gave us a starter on what might be expected in the TF 1.7.0. This major release contains with some major improvements, features, bug fixes, and other changes.

Major features and improvements in TensorFlow 1.7.0:

Eager mode is moving out of contrib, try tf.enable_eager_execution().
EGraph rewrites emulating fixed-point quantization compatible with TensorFlow Lite are now supported by new tf.contrib.quantize package.
Easy customize gradient computation are now available with tf.custom_gradient.
TensorBoard Debugger Plugin, the graphical user interface (GUI) of TensorFlow Debugger (tfdbg), is now in alpha.
Experimental support for reading a sqlite database as a Dataset with new tf.contrib.data.SqlDataset.
Distributed Mutex / CriticalSection added to tf.contrib.framework.CriticalSection.
Better text processing with tf.regex_replace.
Easy, efficient sequence input with tf.contrib.data.bucket_by_sequence_length

Bug fixes in TF 1.7.0 version include:

- Added MaxPoolGradGrad support for XLA and disabled CSE pass from Tensorflow in XLA.
- Added support for building C++ Dataset op kernels as external libraries, using the tf.load_op_library() mechanism.
- Added support for scalars in tf.contrib.all_reduce.
- Deprecated tf.contrib.learn.

Additional changes are:

Added library for statistical testing of samplers and helpers to stream data from the GCE VM to a Cloud TPU.
Added TensorSpec to represent the specification of Tensors.
Integrated TPUClusterResolver with GKE’s integration for Cloud TPUs and also ClusterResolvers with TPUEstimator.
Fixed MomentumOptimizer lambda
Constant folding pass is now deterministic.
A support for float16 dtype in tf.linalg.*

Read full coverage about the version release on TensorFlow’s GitHub Repository.

Savia Lobo

A Data science fanatic. Loves to be updated with the tech happenings around the globe. Loves singing and composing songs. Believes in putting the art in smart.