torch.linalg.ldl_solve¶
- torch.linalg.ldl_solve(LD, pivots, B, *, hermitian=False, out=None) Tensor ¶
Computes the solution of a system of linear equations using the LDL factorization.
LD
andpivots
are the compact representation of the LDL factorization and are expected to be computed bytorch.linalg.ldl_factor_ex()
.hermitian
argument to this function should be the same as the corresponding arguments intorch.linalg.ldl_factor_ex()
.Supports input of float, double, cfloat and cdouble dtypes. Also supports batches of matrices, and if
A
is a batch of matrices then the output has the same batch dimensions.Warning
This function is “experimental” and it may change in a future PyTorch release.
- Parameters
- Keyword Arguments
hermitian (bool, optional) – whether to consider the decomposed matrix to be Hermitian or symmetric. For real-valued matrices, this switch has no effect. Default: False.
out (tuple, optional) – output tensor. B may be passed as out and the result is computed in-place on B. Ignored if None. Default: None.
Examples:
>>> A = torch.randn(2, 3, 3) >>> A = A @ A.mT # make symmetric >>> LD, pivots, info = torch.linalg.ldl_factor_ex(A) >>> B = torch.randn(2, 3, 4) >>> X = torch.linalg.ldl_solve(LD, pivots, B) >>> torch.linalg.norm(A @ X - B) >>> tensor(0.0001)