Refer to this discussion on integrating complex numbers in pytorch link 720.
As far as TF and torch are concerned. You should prefer TF when you want to code in Swift, Go, JavaScript, Java and some others. You can also use TF when you want to make mobile applications (but pytorch provides it through onnux). Although, it is highly recommended to deploy model on cloud and make the mobile interact with the cloud.
Apart from these there is not much difference in TF and torch, except the code base. TF is lot more cluttered in the sense way too many deprecations and too complex to learn (not true for TF 2.0).
At the end I think it comes to your preference I think, fastai a very useful library is build on PyTorch. Also, you can use tensorboard on PyTorch also.
In case you want to work on cloud TPUs your only option as of now is TF (PyTorch support is coming soon).