Serialization
Complex tensors can be serialized, allowing data to be saved as
complex values.



torch.save(y, 'complex_tensor.pt')
torch.load('complex_tensor.pt')
   tensor([ 0.6125-0.1681j, -0.3773+1.3487j, -0.0861-0.7981j])



Autograd
PyTorch supports autograd for complex tensors. The gradient computed
is the Conjugate Wirtinger derivative, the negative of which is
precisely the direction of steepest descent used in Gradient Descent
algorithm. Thus, all the existing optimizers work out of the box with
complex parameters. For more details, check out the note Autograd for
Complex Numbers.
We do not fully support the following subsystems:


Quantization


JIT


Sparse Tensors


Distributed


If any of these would help your use case, please search if an issue
has already been filed and if not, file one.