Operations involving complex numbers in PyTorch are optimized to use
vectorized assembly instructions and specialized kernels (e.g. LAPACK,
cuBlas).
Note:
Spectral operations in the torch.fft module support native complex
  tensors.
Warning:
Complex tensors is a beta feature and subject to change.
Creating Complex Tensors
We support two complex dtypes: torch.cfloat and torch.cdouble



x = torch.randn(2,2, dtype=torch.cfloat)
x
   tensor([[-0.4621-0.0303j, -0.2438-0.5874j],
        [ 0.7706+0.1421j,  1.2110+0.1918j]])



Note:
The default dtype for complex tensors is determined by the default
  floating point dtype. If the default floating point dtype is
  torch.float64 then complex numbers are inferred to have a dtype of
  torch.complex128, otherwise they are assumed to have a dtype of
  torch.complex64.
All factory functions apart from "torch.linspace()",
"torch.logspace()", and "torch.arange()" are supported for complex
tensors.