| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| |
| package AI::MXNet::LinAlg; |
| use strict; |
| use warnings; |
| use AI::MXNet::NS; |
| use AI::MXNet::LinAlg::Symbol; |
| use AI::MXNet::LinAlg::NDArray; |
| |
| =head1 NAME |
| |
| AI::MXNet::LinAlg - Linear Algebra routines for NDArray and Symbol. |
| =cut |
| |
| =head1 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|http://mxnet.incubator.apache.org/api/python/ndarray/linalg.html> |
| L<Symbol Python Docs|http://mxnet.incubator.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]]) |
| )); |
| |
| =cut |
| |
| sub sym { 'AI::MXNet::LinAlg::Symbol' } |
| sub symbol { 'AI::MXNet::LinAlg::Symbol' } |
| sub nd { 'AI::MXNet::LinAlg::NDArray' } |
| sub ndarray { 'AI::MXNet::LinAlg::NDArray' } |
| |
| 1; |