Rate this Page
★★★★★

torch.linalg.ldl_factor_ex#

torch.linalg.ldl_factor_ex(A,*,hermitian=False,check_errors=False,out=None)#

This is a version ofldl_factor() that does not perform error checks unlesscheck_errors= True.It also returns theinfo tensor returned byLAPACK’s sytrf.info stores integer error codes from the backend library.A positive integer indicates the diagonal element ofDD that is zero.Division by 0 will occur if the result is used for solving a system of linear equations.info filled with zeros indicates that the factorization was successful.Ifcheck_errors=True andinfo contains positive integers, then aRuntimeError is thrown.

Note

When the inputs are on a CUDA device, this function synchronizes only whencheck_errors= True.

Warning

This function is “experimental” and it may change in a future PyTorch release.

Parameters

A (Tensor) – tensor of shape(*, n, n) where* is zero or more batch dimensionsconsisting of symmetric or Hermitian matrices.

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 ofinfo and raisean error if it is non-zero. Default:False.

  • out (tuple,optional) – tuple of three tensors to write the output to. Ignored ifNone. Default:None.

Returns

A named tuple(LD, pivots, info).

Examples:

>>>A=torch.randn(3,3)>>>A=A@A.mT# make symmetric>>>Atensor([[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)>>>LDtensor([[ 7.2079,  0.0000,  0.0000],        [ 0.5884,  0.9595,  0.0000],        [ 0.2695, -0.8513,  0.1633]])>>>pivotstensor([1, 2, 3], dtype=torch.int32)>>>infotensor(0, dtype=torch.int32)