It will generalize. For the reason being, the matrices returned from cholesky decomposition are triangular matrices. Their determinant should be square root determinant of the original matrix, as the determinants respect matrix multiplication.
>>> x = torch.tensor([[1,2,3],[0,4,5],[0,0,6]]).float()

>>> x.det()
tensor(24.)

>>> x.transpose(0,1).det()
tensor(24.)

>>> torch.det(torch.mul(x, x.transpose(0,1)))
tensor(576.)

I am sorry for the previous answer. I got carried away I guess.