Algorithmia and TensorFlow compatible for model deployment

TensorFlow 2.0 shipped today, 30 September 2019, with new features, such as faster debugging and iteration with Eager Execution, a TensorFlow-enhanced implementation of the Keras API, and simplification and compatibility improvements across its APIs. TensorFlow 2.0 is a major upgrade that should increase performance, streamline workflows, and provide more compatibility for new or updated models.

We offer day 1 support

At Algorithmia, we believe data scientists should be able to deploy and serve models from any framework and keep up with the pace of tool development. To that end, we’re eager to announce that we support model deployments in the TensorFlow 2.0 framework—Google’s latest version that was released today. 

Effective immediately, our Cloud AI Layer customers can host, serve, and deploy pre-trained TensorFlow 2.0 models the same way they do with previous versions

Our Enterprise customers will receive the same support in their next product update.

Accessing TensorFlow 2.0 packageset on Algorithmia

While TensorFlow 2.0 includes a conversion tool for existing 1.x models, those conversions will not be fully automatic. Rest assured that the AI Layer will remain fully backward-compatible with all previous versions of TensorFlow—and the more than 15 other frameworks we support.

What’s next

We won’t stop there. We want to provide users with the freedom to choose the best tool for every job, and that means immediate support for future versions of TensorFlow and other frameworks in development. If you have any questions about framework support or our rollout schedule, please contact your account manager or send us a message.

Happy model deployment!