Module: tf.linalg

Defined in tensorflow/linalg/

Operations for linear algebra.


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.


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.

inv(...): Computes the inverse of one or more square invertible matrices or their

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.

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.

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