TensorFlow is a powerful, programmable system for machine learning. This paper aims
to provide the basics of a conceptual framework for understanding the behavior of
TensorFlow models during training and inference: it describes an operational
semantics, of the kind common in the literature on programming languages. More
broadly, the paper suggests that a programming-language perspective is fruitful in
designing and in explaining systems such as TensorFlow.