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Announcing TensorFlow 1.0

Wednesday, February 15, 2017

Posted by Amy McDonald Sandjideh, Technical Program Manager, TensorFlowfirst yearlanguage translationearly detection of skin cancerpreventing blindness in diabetics6000 open-source repositories onlineTensorFlow Developer Summitlivestreamed around the worldTensorFlow 1.0It’s faster:XLAtensorflow.orgtips & tricksIt’s more flexible:KerasIt’s more production-ready than ever:hereTensorFlow 1.0

Python APIs have been changed to resemble NumPy more closely. For this and other backwards-incompatible changes made to support API stability going forward, please use our handy migration guide and conversion script.

Experimental APIs for Java and Go

Higher-level API modules tf.layers, tf.metrics, and tf.losses - brought over from tf.contrib.learn after incorporating skflow and TF Slim

Experimental release of XLA, a domain-specific compiler for TensorFlow graphs, that targets CPUs and GPUs. XLA is rapidly evolving - expect to see more progress in upcoming releases.

Introduction of the TensorFlow Debugger (tfdbg), a command-line interface and API for debugging live TensorFlow programs.

New Android demos for object detection and localization, and camera-based image stylization.

Installation improvements: Python 3 docker images have been added, and TensorFlow’s pip packages are now PyPI compliant. This means TensorFlow can now be installed with a simple invocation of pip install tensorflow.

TensorFlow Developer Summit talks on YouTubeXLA
Click here for a link to the livestream and video playlist (individual talks will be posted online later in the day). FoldEmbedding ProjectorTensorFlow ServingGitHub issuesStack Overflow@TensorFlowdiscuss@tensorflow.org