Tensorflow 1.7.0-rc0 arrives close on the heels of Tensorflow 1.6.0!

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.