TensorFlow meets PyTorch with Eager execution. – Yaroslav Bulatov – Medium

One of the main user complaints about TensorFlow was the constraint imposed by having to structure your computations as a static graph. Relaxing this requirement was one of my projects when I was at Google Brain, eventually open-sourced as imperative mode. However it relied on private/unstable APIs which became too costly to maintain over time. Luckily, PyTorch coming out crystallized researcher needs/wants, and there has been a concerted effort to support this kind of mode as a first-class citizen. It's still under active development but the version available in nightly release is quite usable, to try it out: Note that there's no longer need to deal with graph or session and execution happens immediately.