Pytorch torch.linalg example | Newbedev
https://newbedev.com/pytorch/linalgtorch.linalg.cond (input, p=None, *, out=None) → Tensor Computes the condition number of a matrix input, or of each matrix in a batched input, using the matrix norm defined by p. For norms {‘fro’, ‘nuc’, inf, -inf, 1, -1} this is defined as the matrix norm of input times the matrix norm of the inverse of input computed using torch.linalg.norm ().
Releases · pytorch/pytorch · GitHub
github.com › pytorch › pytorchNote: You can verify if the conj bit is set by calling tensor.is_conj().The conjugation can be resolved, i.e., you can obtain a new tensor that doesn’t share storage with the input tensor at any time by calling conjugated_tensor.clone() or conjugated_tensor.resolve_conj().
torch.linalg.cond — PyTorch 1.10.1 documentation
https://pytorch.org/docs/stable/generated/torch.linalg.cond.htmltorch.linalg.lstsq () for a function that solves linear systems of general matrices. Parameters A ( Tensor) – tensor of shape (*, m, n) where * is zero or more batch dimensions for p in (2, -2), and of shape (*, n, n) where every matrix is invertible for p in (‘fro’, ‘nuc’, inf, -inf, 1, -1).