For experimenting, I think the imperative paradigm (define the graph by running it) makes for much faster experimentation and requires a lot less boilerplate co

For experimenting, I think the imperative paradigm (define the graph by running it) makes for much faster experimentation and requires a lot less boilerplate code. All big DL frameworks (TF, PyTorch, MXNet, Chainer) are now either imperative or have an imperative API in the works.