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Tensorflow Eager Execution

Published : May 15, 2018
NOT ON THE CURRENT EDITION
This blip is not on the current edition of the Radar. If it was on one of the last few editions, it is likely that it is still relevant. If the blip is older, it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the Radar. Understand more
May 2018
Assess ? Worth exploring with the goal of understanding how it will affect your enterprise.

In the last issue we featured PyTorch, a deep-learning modeling framework that allows an imperative programming style. Now TensorFlow Eager Execution provides this imperative style in TensorFlow by enabling execution of modeling statements outside of the context of a session. This improvement could provide the ease of debugging and finer-grained model control of PyTorch with the widespread popularity and performance of TensorFlow models. The feature is still quite new so we’re anxious to see how it performs and how it’ll be received by the TensorFlow community.

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