Linear algebra (cunumeric.linalg)#

Matrix and vector products#

dot(a, b[, out])

Dot product of two arrays.

vdot(a, b[, out])

Return the dot product of two vectors.

inner(a, b[, out])

Inner product of two arrays.

outer(a, b[, out])

Compute the outer product of two vectors.

matmul(a, b, /[, out, casting, dtype])

Matrix product of two arrays.

tensordot(a, b[, axes, out])

Compute tensor dot product along specified axes.

einsum(expr, *operands[, out, dtype, ...])

Evaluates the Einstein summation convention on the operands.

einsum_path(expr, *operands[, optimize])

Evaluates the lowest cost contraction order for an einsum expression by considering the creation of intermediate arrays.

linalg.matrix_power(a, n)

Raise a square matrix to the (integer) power n.

linalg.multi_dot(arrays, *[, out])

Compute the dot product of two or more arrays in a single function call, while automatically selecting the fastest evaluation order.

Decompositions#

linalg.cholesky(a)

Cholesky decomposition.

linalg.qr(a)

Compute the qr factorization of a matrix.

linalg.svd(a)

Singular Value Decomposition.

Norms and other numbers#

linalg.norm(x[, ord, axis, keepdims])

Matrix or vector norm.

trace(a[, offset, axis1, axis2, dtype, out])

Return the sum along diagonals of the array.

Solving equations and inverting matrices#

linalg.solve(a, b[, out])

Solve a linear matrix equation, or system of linear scalar equations.