Dot.h

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/*
 * Copyright (c) The Shogun Machine Learning Toolbox
 * Written (w) 2014 Soumyajit De
 * Written (w) 2014 Khaled Nasr
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 *
 * 1. Redistributions of source code must retain the above copyright notice, this
 *    list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 *    this list of conditions and the following disclaimer in the documentation
 *    and/or other materials provided with the distribution.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
 * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 *
 * The views and conclusions contained in the software and documentation are those
 * of the authors and should not be interpreted as representing official policies,
 * either expressed or implied, of the Shogun Development Team.
 */

#ifndef DOT_IMPL_H_
#define DOT_IMPL_H_

#include <shogun/lib/config.h>
#include <shogun/lib/SGVector.h>
#include <shogun/io/SGIO.h>

#ifdef HAVE_EIGEN3
#include <shogun/mathematics/eigen3.h>
#endif // HAVE_EIGEN3

#ifdef HAVE_VIENNACL
#include <shogun/lib/GPUVector.h>
#include <viennacl/linalg/inner_prod.hpp>
#endif // HAVE_VIENNACL

namespace shogun
{

namespace linalg
{

namespace implementation
{

template <enum Backend, class Vector>
struct dot
{
    typedef typename Vector::Scalar T;

    static T compute(Vector a, Vector b);
};

template <class Vector>
struct dot<Backend::NATIVE, Vector>
{
    typedef typename Vector::Scalar T;

    static T compute(shogun::SGVector<T> a, shogun::SGVector<T> b)
    {
        REQUIRE(a.vlen == b.vlen, "Vectors should have same length!\n");
        return compute(a.vector, b.vector, a.vlen);
    }

    static T compute(T* a, T* b, index_t len)
    {
        T result=static_cast<T>(0);
        for (index_t i=0; i<len; ++i)
            result+=a[i]*b[i];
        return result;
    }
};

#ifdef HAVE_EIGEN3

template <class Vector>
struct dot<Backend::EIGEN3, Vector>
{
    typedef typename Vector::Scalar T;

    static T compute(shogun::SGVector<T> a, shogun::SGVector<T> b)
    {
        typedef Eigen::Matrix<T, Eigen::Dynamic, 1> VectorXt;
        Eigen::Map<VectorXt> vec_a = a;
        Eigen::Map<VectorXt> vec_b = b;
        return vec_a.dot(vec_b);
    }
};
#endif // HAVE_EIGEN3

#ifdef HAVE_VIENNACL

template <class Vector>
struct dot<Backend::VIENNACL, Vector>
{
    typedef typename Vector::Scalar T;

    static T compute(shogun::CGPUVector<T> a, shogun::CGPUVector<T> b)
    {
        return viennacl::linalg::inner_prod(a.vcl_vector(), b.vcl_vector());
    }
};
#endif // HAVE_VIENNACL

}

}

}
#endif // DOT_IMPL_H_