TensorFlow 1.8.0-rc0 发布，此版本包括很多性能改进和bug修复。主要特性和改进包括： 主要特性和改进 Can now pass tf.contrib.distribute.MirroredStrategy() to tf.estimator.RunConfig() to run an Estimator model on multiple GPUs on one machine. Add tf.contrib.data.prefetch_to_device(), which supports prefetching to GPU memory. Added Gradient Boosted Trees as pre-made Estimators: BoostedTreesClassifier, BoostedTreesRegressor. Add 3rd generation pipeline config for Cloud TPUs which improves performance and usability. tf.contrib.bayesflow is moving out to it's own repo. Added tf.contrib.{proto,rpc} to allow generic proto parsing and RPC communication. Bug 修复和其他改变 tf.data: Add tf.contrib.data.prefetch_to_device, which enables prefetching dataset elements to GPU memory. Add tf.contrib.data.AUTOTUNE, which allows the tf.data runtime to automatically tune the prefetch buffer sizes based on your system and environment. Add tf.contrib.data.make_csv_dataset for building datasets of CSV files. Eager Execution: With eager execution Datasets can now be used as standard python iterators (for batch in dataset. Both Dataset.__iter__() and Dataset.make_one_shot_iterator() can now be used to create iterators when eager execution is enabled. Automatic device placement has been enabled (i.e., use a GPU if available automatically, without requiring an explicit with tf.device(“/gpu:0”)) (Fixes #14133) tf.GradientTape has moved out of contrib. 完整内容请查看发布主页。 下载地址： Source code (zip) Source code (tar.gz) TensorFlow 1.8.0-rc0 发布，bug 修复版本 下载地址
