Shortcuts

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

Docs

Access comprehensive developer documentation for PyTorch

View Docs

Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials

Resources

Find development resources and get your questions answered

View Resources