Per the numpy docs, passing y separately should be equivalent to stacking it to “m” or (cat’ing in torch parlance):
numpy.cov — NumPy v1.21 Manual
>>> import torch
>>> x = torch.randn(128,128,dtype=torch.double)
>>> y = torch.randn(128,128,dtype=torch.double)
>>> X = torch.cat((x, y), axis=0)
>>> import numpy as np
>>> np_res = np.cov(x.numpy(), y.numpy())
>>> res = torch.cov(X)
>>> (res.shape, torch.tensor(np_res).shape)
(torch.Size([256, 256]), torch.Size([256, 256]))
>>> torch.allclose(res, torch.tensor(np_res))
True
>>>