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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
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31 
32 #ifndef CORE_H_
33 #define CORE_H_
34 
43 
44 namespace shogun
45 {
46 
47 namespace linalg
48 {
49 
65 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
66 void add(Matrix A, Matrix B, Matrix C, typename Matrix::Scalar alpha=1.0,
67  typename Matrix::Scalar beta=1.0)
68 {
70 }
71 
85 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
86 Matrix add(Matrix A, Matrix B, typename Matrix::Scalar alpha=1.0,
87  typename Matrix::Scalar beta=1.0)
88 {
89  return implementation::add<backend, Matrix>::compute(A, B, alpha, beta);
90 }
91 
93 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
94 void scale(Matrix A, Matrix B, typename Matrix::Scalar alpha)
95 {
97 }
98 
100 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
101 void scale(Matrix A, typename Matrix::Scalar alpha)
102 {
104 }
105 
110 template <Backend backend=linalg_traits<Core>::backend, class Matrix>
111 void range_fill(Matrix A, typename Matrix::Scalar start=0.0)
112 {
114 }
115 
121 template <Backend backend=linalg_traits<Core>::backend, class Matrix>
122 void range_fill(Matrix A, index_t len, typename Matrix::Scalar start=0.0)
123 {
125 }
126 
127 #ifdef HAVE_LINALG_LIB
128 
140 template <Backend backend=linalg_traits<Core>::backend,class Matrix,class Vector>
141 void apply(Matrix A, Vector b, Vector x, bool transpose=false)
142 {
143  implementation::apply<backend,Matrix,Vector>::compute(A, b, x, transpose);
144 }
145 
156 template <Backend backend=linalg_traits<Core>::backend,class Matrix,class Vector>
157 Vector apply(Matrix A, Vector b, bool transpose=false)
158 {
159  return implementation::apply<backend,Matrix,Vector>::compute(A, b, transpose);
160 }
161 
176 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
177 void matrix_product(Matrix A, Matrix B, Matrix C,
178  bool transpose_A=false, bool transpose_B=false, bool overwrite=true)
179 {
180  implementation::matrix_product<backend, Matrix>::compute(A, B, C, transpose_A, transpose_B, overwrite);
181 }
182 
193 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
194 typename implementation::matrix_product<backend,Matrix>::ReturnType matrix_product(Matrix A, Matrix B,
195  bool transpose_A=false, bool transpose_B=false)
196 {
197  return implementation::matrix_product<backend, Matrix>::compute(A, B, transpose_A, transpose_B);
198 }
199 
201 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
202 void subtract(Matrix A, Matrix B, Matrix C,
203  typename Matrix::Scalar alpha=1.0, typename Matrix::Scalar beta=1.0)
204 {
205  implementation::add<backend, Matrix>::compute(A, B, C, alpha, -1*beta);
206 }
207 
220 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
221 void elementwise_product(Matrix A, Matrix B, Matrix C)
222 {
224 }
225 
236 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
237 typename implementation::elementwise_product<backend,Matrix>::ReturnType elementwise_product(Matrix A, Matrix B)
238 {
240 }
241 
250 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
251 typename implementation::elementwise_square<backend,Matrix>::ReturnType elementwise_square(Matrix m)
252 {
254 }
255 
263 template <Backend backend=linalg_traits<Core>::backend,class Matrix, class ResultMatrix>
264 void elementwise_square(Matrix m, ResultMatrix result)
265 {
267 }
268 
285 template <Backend backend=linalg_traits<Core>::backend,class Matrix>
286 void convolve(Matrix X, Matrix W, Matrix Y, bool flip = false,
287  bool overwrite=true, int32_t stride_x=1, int32_t stride_y=1)
288 {
289  implementation::convolve<backend, Matrix>::compute(X, W, Y, flip, overwrite, stride_x, stride_y);
290 }
291 #endif // HAVE_LINALG_LIB
292 
293 }
294 
295 }
296 #endif // CORE_H_
int32_t index_t
Definition: common.h:62
static void compute(Matrix A, Matrix B, Matrix C)
void range_fill(Matrix A, typename Matrix::Scalar start=0.0)
Definition: Core.h:111
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)
static void compute(Matrix X, Matrix W, Matrix Y, bool flip, bool overwrite, int32_t stride_x, int32_t stride_y)
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:94
static void compute(Matrix A, Matrix B, Matrix C, T alpha, T beta)
static void compute(Matrix A, T start)

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