TensorFlow 1.8.0-rc0 releases

Major features and improvements in TensorFlow 1.8.0-rc0:

• Adds Gradient Boosted Trees for pre-made Estimators with BoostedTreesClassifier and BoostedTreesRegressor.
• Adds 3rd generation pipeline config for Cloud TPUs for performance improvement and usability.
• Support for running Estimator model on multiple GPUs by passing tf.contrib.distribute.MirroredStrategy() to tf.estimator.RunConfig().
• Support for prefetching GPU memory using tf.contrib.data.prefetch_to_device().
• Moving Bayesian computation tf.contrib.bayesflow to its own dedicated repository.
• Allows generic proto parsing and RPC communication with tf.contrib.{proto,rpc}.

Bug Fixes in TensorFlow 1.8.0-rc0:

• Enabled support for prefetching of dataset elements to GPU memory with tf.contrib.data.prefetch_to_device.
• Allows automatic tuning of prefetch buffer sizes with tf.contrib.data.AUTOTUNE.
• Added support for building datasets of CSV files with tf.contrib.data.make_csv_dataset.
• Provision of creating iterators with Both Dataset.__iter__() and Dataset.make_one_shot_iterator() in eager execution mode.
• Enabled automatic device placement.
• tf.GradientTape voluntarily moved out of future contributions to the library.
• Added new data preprocessing functions and fashion mnist dataset to tf.keras.
• Accelerated Linear Algebra (XLA) with lexicographical feature.
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• Allows exclusion of nodes in tensor-filter operations.
• Fixed spurious background colors in text terminals.
• Fixed batch dimensions reshaping with BatchReshape.
• Support for explicit gradient checkpointing on TPU with tf.contrib.layers.recompute_grad works.

For the complete list of bug fixes and improvements, you can read TensorFlow’s Github page.

Miscellaneous changes:

• Easy calling to TensorFlow C API.
• Description of shapes and pointer noted in tf.distributions.Distribution tutorial notebook.
• Scatter operations extended and updated with tf.scatter_min and tf.scatter_max
• cuDNN RNN operations moved to TensorFlow codebase.
• Added float64 support for Conv2d, Conv2dBackpropInput, Conv2dBackpropFilter and AvgPool/AvgPoolGrad.
• Localised graph name scope thread for multi-threaded environments.
• Updated nsync synchronization library for avoiding slow primitives on Linux.
• Non-uniformity of orthogonal matrices fixed.
• Multi-image Estimator eval summaries displays correctly.

You can download the source code to access all the exciting features of TensorFlow 1.8.0-rc0.