Hi @fewagner PyTorch recently added complex numbers support so you can make tensors of complex dtype:
torch.randn(4, 4, dtype=torch.float) and perform operations on them. you can also compute compute complex derivatives, i.e. run backward on loss functions with complex valued parameters. for more reading on complex autograd, check out: https://pytorch.org/docs/stable/notes/autograd.html?highlight=complex%20autograd 7