Facebook & Google's LazyTensor Enables Expressive Domain-Specific Compilers

Facebook and Google researchers have united to introduce a novel technique that combines eager execution and domain-specific compilers (DSCs) to exploit the benefits of both. The proposed "LazyTensor" enables the full use of all host programming language features throughout the Tensor portion of users' programs. Eager execution is an imperative, define-by-run interface that is both expressive and easy to debug and forms the basis for most widely-adopted programming languages. Optimizing DSCs, meanwhile, is a proven way to improve the performance of machine learning (ML) models, but suffers from a "language subset problem" that makes it less expressive. The two are made to work together in the new paper LazyTensor: Combining Eager Execution with Domain-Specific Compilers.