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TensorFlow 1.0.0-rc0 is available – with XLA, TF-DBG, Java API and more

Major Features and Improvements

XLA (experimental): initial release of XLA, a domain-specific compiler for TensorFlow graphs, that targets CPUs and GPUs.
TensorFlow Debugger (tfdbg): command-line interface and API.
New python 3 docker images added.
Made pip packages pypi compliant. TensorFlow can now be installed by pip
install tensorflow command.
Several python API calls have been changed to resemble NumPy more closely.
New (experimental) Java API.
Android: new person detection + tracking demo implementing “Scalable Object Detection using Deep Neural Networks” (with additional YOLO object detector support)
Android: new camera-based image stylization demo based on “A Learned Representation For Artistic Style”
Breaking Changes to the API

To help you upgrade your existing TensorFlow Python code to match the API changes below, we have prepared a conversion script.

TensorFlow/models have been moved to a separate github repository.
Division and modulus operators (/, //, %) now match Python (flooring)
semantics. This applies to tf.div and tf.mod as well. To obtain forced
integer truncation based behaviors you can use


 

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