Updates to Watson Machine Learning Support for TensorFlow

1 min read

Watson Machine Learning will support TensorFlow versions 1.15 in deployment and training runtimes.

Additionally, due to a recent security vulnerability for multiple TensorFlow versions, Watson Machine Learning (WML) will deprecate unsecure TensorFlow versions, including 1.13 and 1.14.

At the same time, Keras 2.1.6 and Keras 2.2.4 support will also be deprecated together with TensorFlow 1.13 and 1.14. Users will need to upgrade to Keras 2.2.5 and switch to TensorFlow 1.15 backend.

Upgrade options

If you are training or deploying the following impacted models:

  • TensorFlow 1.13
  • TensorFlow 1.14
  • Keras 2.1.6 with TensorFlow 1.13 backend
  • Keras 2.2.4 with TensorFlow 1.14 backend

You have the following upgrade options:

  • TensorFlow 1.15
  • Keras 2.2.5 with TensorFlow 1.15 backend

Depending on the implementation of the code or model, you may need to make minor modifications based on the TensorFlow version compatibility guide for a smooth transition. In many cases, TensorFlow is backward compatible.

You can read more about working with Watson Machine Learning runtimes, including the new TensorFlow 1.15 runtime, in our documentation.

Dates you need to know

  • TensorFlow 1.15 runtimes available: March 3, 2020
  • Deprecate unsecure TensorFlow versions announcement: March 3, 2020
  • End of Life for unsecure TensorFlow versions: April 2, 2020 

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