does pytorch support complex numbers?
Minimum (not) working example

kernel = Conv2d(in_channels=1, out_channels=1, kernel_size=(3, 2))
data = torch.rand(1, 1, 100, 100).type(torch.complex64)
kernel(data)

yields RuntimeError: &quot;unfolded2d_copy&quot; not implemented for 'ComplexDouble' for 64 and 128 bit complex numbers, while for 32 bit, i get RuntimeError: &quot;copy_&quot; not implemented for 'ComplexHalf'.
Am I missing something, or is pytorch missing support for complex numbers??
note: I'm on macbook, using cpu only.

Currently (@ latest stable version - 1.9.0) Pytorch is missing support for such operations on complex tensors (which are a beta feature). See this feature request at Native implementation of convolution for complex numbers
Splitting into convolution on real &amp; image separately, though not ideal, is the way to go for now.
