/ 
AI-MXNet-1.6
River stage one • 2 direct dependents • 2 total dependents
/ AI::MXNet::LinAlg

NAME

AI::MXNet::LinAlg - Linear Algebra routines for NDArray and Symbol.

DESCRIPTION

The Linear Algebra API, provides imperative/symbolic linear algebra tensor operations on CPU/GPU.

mx->linalg-><sym|nd>->gemm  Performs general matrix multiplication and accumulation.
mx->linalg-><sym|nd>->gemm2 Performs general matrix multiplication.
mx->linalg-><sym|nd>->potrf Performs Cholesky factorization of a symmetric positive-definite matrix.
mx->linalg-><sym|nd>->potri Performs matrix inversion from a Cholesky factorization.
mx->linalg-><sym|nd>->trmm  Performs multiplication with a lower triangular matrix.
mx->linalg-><sym|nd>->trsm  Solves matrix equation involving a lower triangular matrix.
mx->linalg-><sym|nd>->sumlogdiag    Computes the sum of the logarithms of the diagonal elements of a square matrix.
mx->linalg-><sym|nd>->syrk  Multiplication of matrix with its transpose.
mx->linalg-><sym|nd>->gelqf LQ factorization for general matrix.
mx->linalg-><sym|nd>->syevd Eigendecomposition for symmetric matrix.
L<NDArray Python Docs|https://mxnet.apache.org/api/python/ndarray/linalg.html>
L<Symbol Python Docs|https://mxnet.apache.org/api/python/symbol/linalg.html>

Examples:

## NDArray
my $A = mx->nd->array([[1.0, 1.0], [1.0, 1.0]]);
my $B = mx->nd->array([[1.0, 1.0], [1.0, 1.0], [1.0, 1.0]]);
ok(almost_equal(
    mx->nd->linalg->gemm2($A, $B, transpose_b=>1, alpha=>2.0)->aspdl,
    pdl([[4.0, 4.0, 4.0], [4.0, 4.0, 4.0]])
));

## Symbol
my $sym_gemm2 = mx->sym->linalg->gemm2(
    mx->sym->var('A'),
    mx->sym->var('B'),
    transpose_b => 1,
    alpha => 2.0
);
my $A = mx->nd->array([[1.0, 1.0], [1.0, 1.0]]);
my $B = mx->nd->array([[1.0, 1.0], [1.0, 1.0], [1.0, 1.0]]);
ok(almost_equal(
    $sym_gemm2->eval(args => { A => $A, B => $B })->[0]->aspdl,
    pdl([[4.0, 4.0, 4.0], [4.0, 4.0, 4.0]])
));