Some functions have the same functional, but 2 backends can return different format of results. However, it is not a big issue if we carefully abstract them.
The biggest advantages of adding tensorflow backend is that it significantly speed up the building and running process on CPU. Hence, it helps a lot with the development process.
I am aware that some Agentnet modules are specialised for only Lasagne, however, I think it is possible to adapt all common layers for both frameworks.
we're planning on this (and in fact could use someone help with contributions), so far you can obtain similar speed-ups by compiling with mode "FAST_COMPILE" or "DEBUG_MODE"
The idea comes from lasagne: https://github.com/Lasagne/Lasagne/issues/611
Some functions have the same functional, but 2 backends can return different format of results. However, it is not a big issue if we carefully abstract them.
The biggest advantages of adding tensorflow backend is that it significantly speed up the building and running process on CPU. Hence, it helps a lot with the development process.
I am aware that some Agentnet modules are specialised for only Lasagne, however, I think it is possible to adapt all common layers for both frameworks.