Linear Algebra

Matrix and vector products

`dpnp.dot`	Dot product of a and b.
`dpnp.linalg.multi_dot`	Compute the dot product of two or more arrays in a single function call.
`dpnp.vdot`	Return the dot product of two vectors.
`dpnp.inner`	Returns the inner product of two arrays.
`dpnp.outer`	Returns the outer product of two arrays.
`dpnp.matmul`	Matrix product of two arrays.
`dpnp.tensordot`	Compute tensor dot product along specified axes.
`dpnp.einsum`	Evaluates the Einstein summation convention on the operands.
`dpnp.einsum_path`	Evaluates the lowest cost contraction order for an einsum expression by considering the creation of intermediate arrays.
`dpnp.linalg.matrix_power`	Raise a square matrix to the (integer) power n.
`dpnp.kron`	Kronecker product of two arrays.

`dpnp.linalg.cholesky`	Cholesky decomposition.
`dpnp.linalg.qr`	Compute the qr factorization of a matrix.
`dpnp.linalg.svd`	Singular Value Decomposition.

`dpnp.linalg.eig`	Compute the eigenvalues and right eigenvectors of a square array.
`dpnp.linalg.eigh`	Return the eigenvalues and eigenvectors of a complex Hermitian (conjugate symmetric) or a real symmetric matrix.
`dpnp.linalg.eigvals`	Compute the eigenvalues of a general matrix.
`dpnp.linalg.eigvalsh`	Compute the eigenvalues of a complex Hermitian or real symmetric matrix.

`dpnp.linalg.norm`	Matrix or vector norm.
`dpnp.linalg.cond`	Compute the condition number of a matrix.
`dpnp.linalg.det`	Compute the determinant of an array.
`dpnp.linalg.matrix_rank`	Return matrix rank of array using SVD method.
`dpnp.linalg.slogdet`	Compute the sign and (natural) logarithm of the determinant of an array.
`dpnp.trace`	Return the sum along diagonals of the array.

`dpnp.linalg.solve`	Solve a linear matrix equation, or system of linear scalar equations.
`dpnp.linalg.tensorsolve`	Solve the tensor equation `a x = b` for x.
`dpnp.linalg.lstsq`	Return the least-squares solution to a linear matrix equation.
`dpnp.linalg.inv`	Compute the (multiplicative) inverse of a matrix.
`dpnp.linalg.pinv`	Compute the (Moore-Penrose) pseudo-inverse of a matrix.
`dpnp.linalg.tensorinv`	Compute the 'inverse' of an N-dimensional array.