123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122 |
- // Copyright (c) 2018-2019 Cem Bassoy
- //
- // Distributed under the Boost Software License, Version 1.0. (See
- // accompanying file LICENSE_1_0.txt or copy at
- // http://www.boost.org/LICENSE_1_0.txt)
- //
- // The authors gratefully acknowledge the support of
- // Fraunhofer and Google in producing this work
- // which started as a Google Summer of Code project.
- //
- // And we acknowledge the support from all contributors.
- #include <iostream>
- #include <algorithm>
- #include <boost/numeric/ublas/tensor.hpp>
- #include <boost/test/unit_test.hpp>
- #include "utility.hpp"
- BOOST_AUTO_TEST_SUITE ( test_einstein_notation, * boost::unit_test::depends_on("test_multi_index") )
- using test_types = zip<int,long,float,double,std::complex<float>>::with_t<boost::numeric::ublas::first_order, boost::numeric::ublas::last_order>;
- //using test_types = zip<int>::with_t<boost::numeric::ublas::first_order>;
- BOOST_AUTO_TEST_CASE_TEMPLATE( test_einstein_multiplication, value, test_types )
- {
- using namespace boost::numeric::ublas;
- using value_type = typename value::first_type;
- using layout_type = typename value::second_type;
- using tensor_type = tensor<value_type,layout_type>;
- using namespace boost::numeric::ublas::index;
- {
- auto A = tensor_type{5,3};
- auto B = tensor_type{3,4};
- // auto C = tensor_type{4,5,6};
- for(auto j = 0u; j < A.extents().at(1); ++j)
- for(auto i = 0u; i < A.extents().at(0); ++i)
- A.at( i,j ) = value_type(i+1);
- for(auto j = 0u; j < B.extents().at(1); ++j)
- for(auto i = 0u; i < B.extents().at(0); ++i)
- B.at( i,j ) = value_type(i+1);
- auto AB = A(_,_e) * B(_e,_);
- // std::cout << "A = " << A << std::endl;
- // std::cout << "B = " << B << std::endl;
- // std::cout << "AB = " << AB << std::endl;
- for(auto j = 0u; j < AB.extents().at(1); ++j)
- for(auto i = 0u; i < AB.extents().at(0); ++i)
- BOOST_CHECK_EQUAL( AB.at( i,j ) , value_type(A.at( i,0 ) * ( B.extents().at(0) * (B.extents().at(0)+1) / 2 )) );
- }
- {
- auto A = tensor_type{4,5,3};
- auto B = tensor_type{3,4,2};
- for(auto k = 0u; k < A.extents().at(2); ++k)
- for(auto j = 0u; j < A.extents().at(1); ++j)
- for(auto i = 0u; i < A.extents().at(0); ++i)
- A.at( i,j,k ) = value_type(i+1);
- for(auto k = 0u; k < B.extents().at(2); ++k)
- for(auto j = 0u; j < B.extents().at(1); ++j)
- for(auto i = 0u; i < B.extents().at(0); ++i)
- B.at( i,j,k ) = value_type(i+1);
- auto AB = A(_d,_,_f) * B(_f,_d,_);
- // std::cout << "A = " << A << std::endl;
- // std::cout << "B = " << B << std::endl;
- // std::cout << "AB = " << AB << std::endl;
- // n*(n+1)/2;
- auto const nf = ( B.extents().at(0) * (B.extents().at(0)+1) / 2 );
- auto const nd = ( A.extents().at(0) * (A.extents().at(0)+1) / 2 );
- for(auto j = 0u; j < AB.extents().at(1); ++j)
- for(auto i = 0u; i < AB.extents().at(0); ++i)
- BOOST_CHECK_EQUAL( AB.at( i,j ) , value_type(nf * nd) );
- }
- {
- auto A = tensor_type{4,3};
- auto B = tensor_type{3,4,2};
- for(auto j = 0u; j < A.extents().at(1); ++j)
- for(auto i = 0u; i < A.extents().at(0); ++i)
- A.at( i,j ) = value_type(i+1);
- for(auto k = 0u; k < B.extents().at(2); ++k)
- for(auto j = 0u; j < B.extents().at(1); ++j)
- for(auto i = 0u; i < B.extents().at(0); ++i)
- B.at( i,j,k ) = value_type(i+1);
- auto AB = A(_d,_f) * B(_f,_d,_);
- // n*(n+1)/2;
- auto const nf = ( B.extents().at(0) * (B.extents().at(0)+1) / 2 );
- auto const nd = ( A.extents().at(0) * (A.extents().at(0)+1) / 2 );
- for(auto i = 0u; i < AB.extents().at(0); ++i)
- BOOST_CHECK_EQUAL ( AB.at( i ) , value_type(nf * nd) );
- }
- }
- BOOST_AUTO_TEST_SUITE_END()
|