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The docs for setting up Google Cloud ML suggest installing Tensorflow version r0.11. I've observed that TensorFlow functions newly available in r0.12 raise exceptions when run on Cloud ML. Is there a timeline for Cloud ML supporting r0.12? Will switching between r0.11 and r0.12 be optional or mandatory?
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TensorFlow Enterprise is a distribution of TensorFlow that has been optimized to run on Google Cloud and includes Long Term Version Support.
It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. TensorFlow was developed by the Google Brain team for internal Google use in research and production. The initial version was released under the Apache License 2.0 in 2015.
Yes, you can specify --runtime-version=0.12 to get a 0.12 build. This is a new feature and is documented at https://cloud.google.com/ml/docs/concepts/runtime-version-list
Note, however, that the 0.12 build is not yet considered stable and the exact Tensorflow build provided may change. Once the 1.0 version of Tensorflow is available, that will also be supported and the pre-1.0 versions of Tensorflow will begin to be deprecated.
(See https://cloud.google.com/sdk/gcloud/reference/beta/ml/jobs/submit/training for usage.)
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