Operations for linear algebra.

`experimental`

module: Public API for tf.linalg.experimental namespace.

`class LinearOperator`

: Base class defining a [batch of] linear operator[s].

`class LinearOperatorAdjoint`

: `LinearOperator`

representing the adjoint of another operator.

`class LinearOperatorBlockDiag`

: Combines one or more `LinearOperators`

in to a Block Diagonal matrix.

`class LinearOperatorBlockLowerTriangular`

: Combines `LinearOperators`

into a blockwise lower-triangular 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 LinearOperatorHouseholder`

: `LinearOperator`

acting like a [batch] of Householder transformations.

`class LinearOperatorIdentity`

: `LinearOperator`

acting like a [batch] square identity matrix.

`class LinearOperatorInversion`

: `LinearOperator`

representing the inverse of another operator.

`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 LinearOperatorPermutation`

: `LinearOperator`

acting like a [batch] of permutation matrices.

`class LinearOperatorScaledIdentity`

: `LinearOperator`

acting like a scaled [batch] identity matrix `A = c I`

.

`class LinearOperatorToeplitz`

: `LinearOperator`

acting like a [batch] of toeplitz matrices.

`class LinearOperatorTridiag`

: `LinearOperator`

acting like a [batch] square tridiagonal matrix.

`class LinearOperatorZeros`

: `LinearOperator`

acting like a [batch] zero matrix.

`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 to zero.

`banded_triangular_solve(...)`

: Solve triangular systems of equations with a banded solver.

`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 given batched diagonal values.

`diag_part(...)`

: Returns the batched diagonal part of a batched tensor.

`eig(...)`

: Computes the eigen decomposition of a batch of matrices.

`eigh(...)`

: Computes the eigen decomposition of a batch of self-adjoint matrices.

`eigvals(...)`

: Computes the eigenvalues of one or more matrices.

`eigvalsh(...)`

: Computes the eigenvalues of one or more self-adjoint matrices.

`einsum(...)`

: Tensor contraction over specified indices and outer product.

`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 adjoints (conjugate transposes).

`l2_normalize(...)`

: Normalizes along dimension `axis`

using an L2 norm.

`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.

`lu_matrix_inverse(...)`

: Computes the inverse given the LU decomposition(s) of one or more matrices.

`lu_reconstruct(...)`

: The reconstruct one or more matrices from their LU decomposition(s).

`lu_solve(...)`

: Solves systems of linear eqns `A X = RHS`

, given LU factorizations.

`matmul(...)`

: Multiplies matrix `a`

by matrix `b`

, producing `a`

* `b`

.

`matrix_rank(...)`

: Compute the matrix rank of one or more matrices.

`matrix_transpose(...)`

: Transposes last two dimensions of tensor `a`

.

`matvec(...)`

: Multiplies matrix `a`

by vector `b`

, producing `a`

* `b`

.

`norm(...)`

: Computes the norm of vectors, matrices, and tensors.

`normalize(...)`

: Normalizes `tensor`

along dimension `axis`

using specified norm.

`pinv(...)`

: Compute the Moore-Penrose pseudo-inverse of one or more matrices.

`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 and outer product.

`trace(...)`

: Compute the trace of a tensor `x`

.

`triangular_solve(...)`

: Solve systems of linear equations with upper or lower triangular matrices.

`tridiagonal_matmul(...)`

: Multiplies tridiagonal matrix by matrix.

`tridiagonal_solve(...)`

: Solves tridiagonal systems of equations.

© 2020 The TensorFlow Authors. All rights reserved.

Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/linalg