Announcing Tensor Comprehensions

Today, Facebook AI Research (FAIR) is announcing the release of Tensor Comprehensions, a C library and mathematical language that helps bridge the gap between researchers, who communicate in terms of mathematical operations, and engineers focusing on the practical needs of running large-scale models on various hardware backends. The main differentiating feature of Tensor Comprehensions is that it represents a unique take on Just-In-Time compilation to produce the high-performance codes that the machine learning community needs, automatically and on-demand. As a consequence and over the last few years, the deep learning community has grown to rely on high-performance libraries such as CuBLAS, MKL, and CuDNN to get high-performance code on GPUs and CPUs. Experimenting with ideas that deviate from the primitives provided in these libraries involves a level and magnitude of engineering that can be intimidating to researchers. We anticipate great practical value in open-sourcing a package that shortens this process from days or weeks to minutes.