# torch.det¶

torch.det(input) → Tensor

Calculates determinant of a square matrix or batches of square matrices.

Note

torch.det() is deprecated. Please use torch.linalg.det() instead.

Note

Backward through $det$ internally uses SVD results when input is not invertible. In this case, double backward through $det$ will be unstable when input doesn’t have distinct singular values. See $~torch.svd$ 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])