2 min read

It’s only been a few days since we witnessed the release of Tensorflow 1.6.0, and now the first release candidate of Tensorflow 1.7.0 is already here!

There are quite a few major features and improvements in this new release candidate. However, no breaking changes are unveiled as such. With Tensorflow 1.7.0-rc0, TensorBoard Debugger Plugin, the graphical user interface (GUI) of TensorFlow Debugger (tfdbg), is now in alpha. Also, Eager mode is moving out of contrib.

Other additional major features include:

  • EGraph rewrites emulating fixed-point quantization compatible with TensorFlow Lite are now supported by new tf.contrib.quantize package.
  • Easily customize gradient computation available with tf.custom_gradient.
  • New tf.contrib.data.SqlDataset provides an experimental support for reading a sqlite database as a Dataset
  • 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

Apart from these, there is a myriad of bug fixes and small changes. Some of these include:

  • MaxPoolGradGrad support is added for Accelerated Linear Algebra (XLA). CSE pass from Tensorflow is now disabled.
  • tf.py_func now reports the full stack trace if an exception occurs.
  • TPUClusterResolver now integrated with GKE’s integration for Cloud TPUs.
  • A new library added for statistical testing of samplers.
  • Helpers added to stream data from the GCE VM to a Cloud TPU.
  • ClusterResolvers are integrated with TPUEstimator.
  • Metropolis_hastings interface unified with HMC kernel.
  • LIBXSMM convolutions moved to a separate –define flag so that they are disabled by default.
  • MomentumOptimizer lambda fixed.
  • tfp.layers boilerplate reduced via programmable docstrings.
  • auc_with_confidence_intervals, a method for computing the AUC and confidence interval with linearithmic time complexity added.
  • regression_head now accepts customized link function, to satisfy the usage that user can define their own link function if the array_ops.identity does not meet the requirement.
  • initialized_value and initial_value behaviors fixed for ResourceVariables created from VariableDef protos.
  • TensorSpec added to represent the specification of Tensors.
  • Constant folding pass is now deterministic.

To know about other bug-fixes and changes visit the Tensorflow 1.7.0-rc0 Github Repo.

Content Marketing Editor at Packt Hub. I blog about new and upcoming tech trends ranging from Data science, Web development, Programming, Cloud & Networking, IoT, Security and Game development.


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