It should, if you find that converted model doesn't work, it is a bug, please file it with PyTorch and/or Caffe2.

Implementation details of course differ between frameworks, but luckily neural networks are very robust to noise. In my experience, changes like using Winograd/Fourier for convolutions, or even running the whole thing in FP16 do not result in noticeable artifacts, and these are among the biggest differences you could have between frameworks.