Dear @ptrblck!
Performance on the second place. Extensiveness and easiness to use is a prime target.
Why I have chosen PyTorch? Because of it logical modular structure and easy to understand API, well thought extension capabilities, perfect documentation and it sounds not obvious but lack of functions that only few need.
Why I am raising this topic? Mainly because I want to see how PyTorch breathe, where is the source code for Conv2d. And I found a clue in Caffe2. I might be wrong but I looked at the source code after installation of PyTorch and there is nothing there about layers logic in Python code except for Linear but there is a large * caffe2 *.so where I guess the whole logic is. It’s not that PyTorch is closed and we should blame it. In TensorFlow situation is the same. But I want to click on documentation and see how the thing is working. For now it requires a patience to find it out.
Thank you very much for you answer @ptrblck without you people would stuck forever with their code.