- torch.linalg.ldl_factor_ex(A, *, hermitian=False, check_errors=False, out=None)¶
This is a version of
ldl_factor()that does not perform error checks unless
check_errors= True. It also returns the
infotensor returned by LAPACK’s sytrf.
infostores integer error codes from the backend library. A positive integer indicates the diagonal element of that is zero. Division by 0 will occur if the result is used for solving a system of linear equations.
infofilled with zeros indicates that the factorization was successful. If
infocontains positive integers, then a RuntimeError is thrown.
When the inputs are on a CUDA device, this function synchronizes only when
This function is “experimental” and it may change in a future PyTorch release.
A (Tensor) – tensor of shape (, n, n) where * is zero or more batch dimensions consisting of symmetric or Hermitian matrices. `(, n, n)` where * is one or more batch dimensions.
- Keyword Arguments:
hermitian (bool, optional) – whether to consider the input to be Hermitian or symmetric. For real-valued matrices, this switch has no effect. Default: False.
check_errors (bool, optional) – controls whether to check the content of
infoand raise an error if it is non-zero. Default: False.
out (tuple, optional) – tuple of three tensors to write the output to. Ignored if None. Default: None.
A named tuple (LD, pivots, info).
>>> A = torch.randn(3, 3) >>> A = A @ A.mT # make symmetric >>> A tensor([[7.2079, 4.2414, 1.9428], [4.2414, 3.4554, 0.3264], [1.9428, 0.3264, 1.3823]]) >>> LD, pivots, info = torch.linalg.ldl_factor_ex(A) >>> LD tensor([[ 7.2079, 0.0000, 0.0000], [ 0.5884, 0.9595, 0.0000], [ 0.2695, -0.8513, 0.1633]]) >>> pivots tensor([1, 2, 3], dtype=torch.int32) >>> info tensor(0, dtype=torch.int32)