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Core.h
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1 /*
2  * Copyright (c) The Shogun Machine Learning Toolbox
3  * Written (w) 2014 Soumyajit De
4  * Written (w) 2014 Khaled Nasr
5  * All rights reserved.
6  *
7  * Redistribution and use in source and binary forms, with or without
8  * modification, are permitted provided that the following conditions are met:
9  *
10  * 1. Redistributions of source code must retain the above copyright notice, this
11  * list of conditions and the following disclaimer.
12  * 2. Redistributions in binary form must reproduce the above copyright notice,
13  * this list of conditions and the following disclaimer in the documentation
14  * and/or other materials provided with the distribution.
15  *
16  * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
17  * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
18  * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
19  * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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21  * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
22  * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
23  * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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30  */
31 
32 #ifndef CORE_H_
33 #define CORE_H_
34 
40 
41 namespace shogun
42 {
43 
44 namespace linalg
45 {
46 
57 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
58 void matrix_product(Matrix A, Matrix B, Matrix C,
59  bool transpose_A=false, bool transpose_B=false, bool overwrite=true)
60 {
61  implementation::matrix_product<backend, Matrix>::compute(A, B, C, transpose_A, transpose_B, overwrite);
62 }
63 
65 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
66 void add(Matrix A, Matrix B, Matrix C,
67  typename Matrix::Scalar alpha=1.0, typename Matrix::Scalar beta=1.0)
68 {
70 }
71 
73 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
74 void subtract(Matrix A, Matrix B, Matrix C,
75  typename Matrix::Scalar alpha=1.0, typename Matrix::Scalar beta=1.0)
76 {
77  implementation::add<backend, Matrix>::compute(A, B, C, alpha, -1*beta);
78 }
79 
81 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
82 void scale(Matrix A, Matrix B, typename Matrix::Scalar alpha)
83 {
85 }
86 
88 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
89 void elementwise_product(Matrix A, Matrix B, Matrix C)
90 {
92 }
93 
102 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
103 typename implementation::elementwise_square<backend,Matrix>::ReturnType elementwise_square(Matrix m)
104 {
106 }
107 
115 template <Backend backend=linalg_traits<Core>::backend,class Matrix, class ResultMatrix>
116 void elementwise_square(Matrix m, ResultMatrix result)
117 {
119 }
120 
121 }
122 
123 }
124 #endif // CORE_H_
static void compute(Matrix A, Matrix B, Matrix C)
implementation::elementwise_square< backend, Matrix >::ReturnType elementwise_square(Matrix m)
Definition: Core.h:103
static void compute(Matrix A, Matrix B, Matrix C, bool transpose_A, bool transpose_B, bool overwrite)
void add(Matrix A, Matrix B, Matrix C, typename Matrix::Scalar alpha=1.0, typename Matrix::Scalar beta=1.0)
Definition: Core.h:66
static void compute(Matrix A, Matrix B, Matrix C, T alpha, T beta)
void elementwise_product(Matrix A, Matrix B, Matrix C)
Definition: Core.h:89
void matrix_product(Matrix A, Matrix B, Matrix C, bool transpose_A=false, bool transpose_B=false, bool overwrite=true)
Definition: Core.h:58
void subtract(Matrix A, Matrix B, Matrix C, typename Matrix::Scalar alpha=1.0, typename Matrix::Scalar beta=1.0)
Definition: Core.h:74
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
void scale(Matrix A, Matrix B, typename Matrix::Scalar alpha)
Definition: Core.h:82
static void compute(Matrix A, Matrix B, Matrix C, T alpha, T beta)

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