Defined in tensorflow/_api/v1/linalg/__init__.py.
Operations for linear algebra.
Classes
class LinearOperator: Base class defining a [batch of] linear operator[s].
class LinearOperatorBlockDiag: Combines one or more LinearOperators in to a Block Diagonal matrix.
class LinearOperatorCirculant: LinearOperator acting like a circulant matrix.
class LinearOperatorCirculant2D: LinearOperator acting like a block circulant matrix.
class LinearOperatorCirculant3D: LinearOperator acting like a nested block circulant matrix.
class LinearOperatorComposition: Composes one or more LinearOperators.
class LinearOperatorDiag: LinearOperator acting like a [batch] square diagonal matrix.
class LinearOperatorFullMatrix: LinearOperator that wraps a [batch] matrix.
class LinearOperatorIdentity: LinearOperator acting like a [batch] square identity matrix.
class LinearOperatorKronecker: Kronecker product between two LinearOperators.
class LinearOperatorLowRankUpdate: Perturb a LinearOperator with a rank K update.
class LinearOperatorLowerTriangular: LinearOperator acting like a [batch] square lower triangular matrix.
class LinearOperatorScaledIdentity: LinearOperator acting like a scaled [batch] identity matrix A = c I.
class LinearOperatorZeros: LinearOperator acting like a [batch] zero matrix.
Functions
adjoint(...): Transposes the last two dimensions of and conjugates tensor matrix.
band_part(...): Copy a tensor setting everything outside a central band in each innermost matrix
cholesky(...): Computes the Cholesky decomposition of one or more square matrices.
cholesky_solve(...): Solves systems of linear eqns A X = RHS, given Cholesky factorizations.
cross(...): Compute the pairwise cross product.
det(...): Computes the determinant of one or more square matrices.
diag(...): Returns a batched diagonal tensor with a given batched diagonal values.
diag_part(...): Returns the batched diagonal part of a batched tensor.
eigh(...): Computes the eigen decomposition of a batch of self-adjoint matrices.
eigvalsh(...): Computes the eigenvalues of one or more self-adjoint matrices.
einsum(...): A generalized contraction between tensors of arbitrary dimension.
expm(...): Computes the matrix exponential of one or more square matrices.
eye(...): Construct an identity matrix, or a batch of matrices.
global_norm(...): Computes the global norm of multiple tensors.
inv(...): Computes the inverse of one or more square invertible matrices or their
l2_normalize(...): Normalizes along dimension axis using an L2 norm. (deprecated arguments)
logdet(...): Computes log of the determinant of a hermitian positive definite matrix.
logm(...): Computes the matrix logarithm of one or more square matrices:
lstsq(...): Solves one or more linear least-squares problems.
lu(...): Computes the LU decomposition of one or more square matrices.
matmul(...): Multiplies matrix a by matrix b, producing a * b.
matvec(...): Multiplies matrix a by vector b, producing a * b.
norm(...): Computes the norm of vectors, matrices, and tensors. (deprecated arguments)
qr(...): Computes the QR decompositions of one or more matrices.
set_diag(...): Returns a batched matrix tensor with new batched diagonal values.
slogdet(...): Computes the sign and the log of the absolute value of the determinant of
solve(...): Solves systems of linear equations.
sqrtm(...): Computes the matrix square root of one or more square matrices:
svd(...): Computes the singular value decompositions of one or more matrices.
tensor_diag(...): Returns a diagonal tensor with a given diagonal values.
tensor_diag_part(...): Returns the diagonal part of the tensor.
tensordot(...): Tensor contraction of a and b along specified axes.
trace(...): Compute the trace of a tensor x.
transpose(...): Transposes last two dimensions of tensor a.
triangular_solve(...): Solves systems of linear equations with upper or lower triangular matrices by