In large part, in the CPU section, it _is_ working in numpy. I think of the neural network libraries, Chainer is made by the people who like actually coding the

In large part, in the CPU section, it _is_ working in numpy. I think of the neural network libraries, Chainer is made by the people who like actually coding the most. I mean, for example, lots of the TensorFlow type checking gets done in Eigen, where it's done by C++ template metaprogramming (that's how it worked when I looked at it, anyhow): Chainer type stuff just gets done by runtime inspection. Which one is faster? TF, by far. Which one would you rather have in _your_ codebase? Edit: after reading the damned thing, they add in more runtime type stuff. And after looking over TF back again, they still have this hybrid thing going on where it's some Eigen stuff and some runtime stuff. I mean....