torch.slogdet¶

torch.slogdet(input) -> (Tensor, Tensor)¶

Calculates the sign and log absolute value of the determinant(s) of a square matrix or batches of square matrices.

Note

If input has zero determinant, this returns (0, -inf).

Note

Backward through slogdet() internally uses SVD results when input is not invertible. In this case, double backward through slogdet() will be unstable in when input doesn’t have distinct singular values. See svd() for details.

Parameters

input (Tensor) – the input tensor of size (*, n, n) where * is zero or more batch dimensions.

Returns

A namedtuple (sign, logabsdet) containing the sign of the determinant, and the log value of the absolute determinant.

Example:

>>> A = torch.randn(3, 3)
>>> A
tensor([[ 0.0032, -0.2239, -1.1219],
        [-0.6690,  0.1161,  0.4053],
        [-1.6218, -0.9273, -0.0082]])
>>> torch.det(A)
tensor(-0.7576)
>>> torch.logdet(A)
tensor(nan)
>>> torch.slogdet(A)
torch.return_types.slogdet(sign=tensor(-1.), logabsdet=tensor(-0.2776))