TensorFlow 1.8.0-rc0 发布，bug 修复版本

栏目: 软件资讯 · 发布时间: 7年前

内容简介：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 Estim...

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。

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