Linear Algebra#

Matrix and vector products#

`maxframe.tensor.dot`	Dot product of two arrays.
`maxframe.tensor.vdot`	Return the dot product of two vectors.
`maxframe.tensor.inner`	Returns the inner product of a and b for arrays of floating point types.
`maxframe.tensor.matmul`	Matrix product of two tensors.
`maxframe.tensor.tensordot`	Compute tensor dot product along specified axes for tensors >= 1-D.
`maxframe.tensor.einsum`	Evaluates the Einstein summation convention on the operands.

Decompositions#

`maxframe.tensor.linalg.cholesky`	Cholesky decomposition.
`maxframe.tensor.linalg.lu`	LU decomposition
`maxframe.tensor.linalg.qr`	Compute the qr factorization of a matrix.
`maxframe.tensor.linalg.svd`	Singular Value Decomposition.

Norms and other numbers#

`maxframe.tensor.linalg.matrix_norm`	Computes the matrix norm of a matrix (or a stack of matrices) `x`.
`maxframe.tensor.linalg.norm`	Matrix or vector norm.
`maxframe.tensor.linalg.vector_norm`	Computes the vector norm of a vector (or batch of vectors) `x`.

Solving equations and inverting matrices#

`maxframe.tensor.linalg.inv`	Compute the (multiplicative) inverse of a matrix.
`maxframe.tensor.linalg.lstsq`	Return the least-squares solution to a linear matrix equation.
`maxframe.tensor.linalg.solve`	Solve the equation `a x = b` for `x`.
`maxframe.tensor.linalg.solve_triangular`	Solve the equation a x = b for x, assuming a is a triangular matrix.