torch.linalg

Common linear algebra operations.

Matrix Properties

`norm`	Computes a vector or matrix norm.
`vector_norm`	Computes a vector norm.
`matrix_norm`	Computes a matrix norm.
`det`	Computes the determinant of a square matrix.
`slogdet`	Computes the sign and natural logarithm of the absolute value of the determinant of a square matrix.
`cond`	Computes the condition number of a matrix with respect to a matrix norm.
`matrix_rank`	Computes the numerical rank of a matrix.

`cholesky`	Computes the Cholesky decomposition of a complex Hermitian or real symmetric positive-definite matrix.
`qr`	Computes the QR decomposition of a matrix.
`eig`	Computes the eigenvalue decomposition of a square matrix if it exists.
`eigvals`	Computes the eigenvalues of a square matrix.
`eigh`	Computes the eigenvalue decomposition of a complex Hermitian or real symmetric matrix.
`eigvalsh`	Computes the eigenvalues of a complex Hermitian or real symmetric matrix.
`svd`	Computes the singular value decomposition (SVD) of a matrix.
`svdvals`	Computes the singular values of a matrix.

Computes the solution of a square system of linear equations with a unique solution.

Computes a solution to the least squares problem of a system of linear equations.

Computes the inverse of a square matrix if it exists.

Computes the pseudoinverse (Moore-Penrose inverse) of a matrix.

`matmul`	Alias for `torch.matmul()`
`matrix_power`	Computes the n-th power of a square matrix for an integer n.
`multi_dot`	Efficiently multiplies two or more matrices by reordering the multiplications so that the fewest arithmetic operations are performed.
`householder_product`	Computes the first n columns of a product of Householder matrices.

Computes the multiplicative inverse of torch.tensordot().

Computes the solution X to the system torch.tensordot(A, X) = B.

Computes the Cholesky decomposition of a complex Hermitian or real symmetric positive-definite matrix.

Computes the inverse of a square matrix if it is invertible.