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.