I am not sure what is your programming style in Pytorch. As people recommended and in most tutorials I see the sequential approach, where a small mistake of data preprocessing would lead to clueless errors in a completely irrelevant line.
YOLO is a quite standard feed-forward model in my opinion. I mean the math part, which I am more concerned with.
I have never used Theano before, my idea from it is that Tensorflow followed its static graph approach.
For using models it may note matter that much (though, again read YOLO in TF and PyTorch and then decide which is cleaner :)).
For new models which go beyond a standard ConvNet/LSTM... well, PyTorch is heaven, Theano sounds like a torture.