TensorFlow 1.8.0 is released with numerous feature changes and bug fixes

  

TensorFlow 1.8.0 is released, this release has made a lot of feature changes and bug fixes.

Main features and performance improvements:

• tf.contrib.distribute.MirroredStrategy() can now be passed to tf.estimator.RunConfig() to run Estimator models on multiple GPUs on a single machine.

• Added tf.contrib.data.prefetch_to_device() to support prefetching GPU memory.

• Added gradient boosted trees: BoostedTreesClassifier and BoostedTreesRegressor.

• Added third-generation pipeline configuration for cloud TPUs for improved performance and availability.    
  

• tf.contrib.bayesflow moved to its own repo.

• Added tf.contrib. {proto,rpc} to allow generic prototype parsing and RPC communication.

bug fix:

• tf.data:

• Added tf.contrib.data.prefetch_to_device to prefetch dataset elements to GPU memory.

• Adds tf.contrib.data.AUTOTUNE, which allows the tf.data runtime to automatically adjust the prefetch buffer size based on your system and environment.

• Add tf.contrib.data.make_csv_dataset to build a dataset of CSV files.

• Eager Execution:

• Automatic device placement is enabled.
  

• tf.GradientTape has been moved out of contrib.

• tf.keras:

• Added fashion mnist dataset

• New data preprocessing functions:  image/random_brightness, sequence/TimeseriesGenerator, and text/hashing_trick

See the announcement for details .

download link:

•  Source code (zip)

•  Source code  (tar.gz)