Caffe2 seems to be engineered for efficiency as opposed to flexibility. For example, Caffe2 is apparently Facebook's go-to choice for mobile edge device deployment for applications such as style transfer.
I mean, it uses a static graph definition instead of dynamic graphs (allows for deployment optimizations), but is there anything Caffe2-specific that would give it a leg up over Theano/TensorFlow/whatever other static graph library?
Efficient how ? In terms of memory management ?
TPUs are smaller in terms of Si real estate and burn less power. Also, they can be made much faster.