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()
totf.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:
). BothDataset.__iter__()
andDataset.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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