torch.det¶
-
torch.
det
(input) → Tensor¶ Calculates determinant of a square matrix or batches of square matrices.
Note
torch.det()
is deprecated. Please usetorch.linalg.det()
instead.Note
Backward through internally uses SVD results when
input
is not invertible. In this case, double backward through will be unstable wheninput
doesn’t have distinct singular values. See for details.- Parameters
input (Tensor) – the input tensor of size
(*, n, n)
where*
is zero or more batch dimensions.
Example:
>>> A = torch.randn(3, 3) >>> torch.det(A) tensor(3.7641) >>> A = torch.randn(3, 2, 2) >>> A tensor([[[ 0.9254, -0.6213], [-0.5787, 1.6843]], [[ 0.3242, -0.9665], [ 0.4539, -0.0887]], [[ 1.1336, -0.4025], [-0.7089, 0.9032]]]) >>> A.det() tensor([1.1990, 0.4099, 0.7386])