123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139 |
- //
- // Copyright (c) 2018-2019, Cem Bassoy, cem.bassoy@gmail.com
- //
- // 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 IOSB, Ettlingen, Germany
- //
- #include <boost/numeric/ublas/tensor.hpp>
- #include <boost/numeric/ublas/matrix.hpp>
- #include <boost/numeric/ublas/vector.hpp>
- #include <iostream>
- int main()
- {
- using namespace boost::numeric::ublas;
- using format_t = column_major;
- using value_t = float;
- using tensor_t = tensor<value_t,format_t>;
- using matrix_t = matrix<value_t,format_t>;
- using namespace boost::numeric::ublas::index;
- // Tensor-Vector-Multiplications - Including Transposition
- {
- auto n = shape{3,4,2};
- auto A = tensor_t(n,1);
- auto B1 = matrix_t(n[1],n[2],2);
- auto v1 = tensor_t(shape{n[0],1},2);
- auto v2 = tensor_t(shape{n[1],1},2);
- // auto v3 = tensor_t(shape{n[2],1},2);
- // C1(j,k) = B1(j,k) + A(i,j,k)*v1(i);
- // tensor_t C1 = B1 + prod(A,vector_t(n[0],1),1);
- // tensor_t C1 = B1 + A(_i,_,_) * v1(_i,_);
- // C2(i,k) = A(i,j,k)*v2(j) + 4;
- //tensor_t C2 = prod(A,vector_t(n[1],1),2) + 4;
- // tensor_t C2 = A(_,_i,_) * v2(_i,_) + 4;
- // not yet implemented!
- // C3() = A(i,j,k)*T1(i)*T2(j)*T2(k);
- // tensor_t C3 = prod(prod(prod(A,v1,1),v2,1),v3,1);
- // tensor_t C3 = A(_i,_j,_k) * v1(_i,_) * v2(_j,_) * v3(_k,_);
- // formatted output
- std::cout << "% --------------------------- " << std::endl;
- std::cout << "% --------------------------- " << std::endl << std::endl;
- std::cout << "% C1(j,k) = B1(j,k) + A(i,j,k)*v1(i);" << std::endl << std::endl;
- // std::cout << "C1=" << C1 << ";" << std::endl << std::endl;
- // formatted output
- std::cout << "% --------------------------- " << std::endl;
- std::cout << "% --------------------------- " << std::endl << std::endl;
- std::cout << "% C2(i,k) = A(i,j,k)*v2(j) + 4;" << std::endl << std::endl;
- // std::cout << "C2=" << C2 << ";" << std::endl << std::endl;
- }
- // Tensor-Matrix-Multiplications - Including Transposition
- {
- auto n = shape{3,4,2};
- auto m = 5u;
- auto A = tensor_t(n,2);
- auto B = tensor_t(shape{n[1],n[2],m},2);
- auto B1 = tensor_t(shape{m,n[0]},1);
- auto B2 = tensor_t(shape{m,n[1]},1);
- // C1(l,j,k) = B(j,k,l) + A(i,j,k)*B1(l,i);
- // tensor_t C1 = B + prod(A,B1,1);
- // tensor_t C1 = B + A(_i,_,_) * B1(_,_i);
- // C2(i,l,k) = A(i,j,k)*B2(l,j) + 4;
- // tensor_t C2 = prod(A,B2) + 4;
- // tensor_t C2 = A(_,_j,_) * B2(_,_j) + 4;
- // C3(i,l1,l2) = A(i,j,k)*T1(l1,j)*T2(l2,k);
- // not yet implemented.
- // formatted output
- std::cout << "% --------------------------- " << std::endl;
- std::cout << "% --------------------------- " << std::endl << std::endl;
- std::cout << "% C1(l,j,k) = B(j,k,l) + A(i,j,k)*B1(l,i);" << std::endl << std::endl;
- // std::cout << "C1=" << C1 << ";" << std::endl << std::endl;
- // formatted output
- std::cout << "% --------------------------- " << std::endl;
- std::cout << "% --------------------------- " << std::endl << std::endl;
- std::cout << "% C2(i,l,k) = A(i,j,k)*B2(l,j) + 4;" << std::endl << std::endl;
- // std::cout << "C2=" << C2 << ";" << std::endl << std::endl;
- // // formatted output
- // std::cout << "% --------------------------- " << std::endl;
- // std::cout << "% --------------------------- " << std::endl << std::endl;
- // std::cout << "% C3(i,l1,l2) = A(i,j,k)*T1(l1,j)*T2(l2,k);" << std::endl << std::endl;
- // std::cout << "C3=" << C3 << ";" << std::endl << std::endl;
- }
- // Tensor-Tensor-Multiplications Including Transposition
- {
- auto na = shape{3,4,5};
- auto nb = shape{4,6,3,2};
- auto A = tensor_t(na,2);
- auto B = tensor_t(nb,3);
- auto T1 = tensor_t(shape{na[2],na[2]},2);
- auto T2 = tensor_t(shape{na[2],nb[1],nb[3]},2);
- // C1(j,l) = T1(j,l) + A(i,j,k)*A(i,j,l) + 5;
- // tensor_t C1 = T1 + prod(A,A,perm_t{1,2}) + 5;
- // tensor_t C1 = T1 + A(_i,_j,_m)*A(_i,_j,_l) + 5;
- // formatted output
- std::cout << "% --------------------------- " << std::endl;
- std::cout << "% --------------------------- " << std::endl << std::endl;
- std::cout << "% C1(k,l) = T1(k,l) + A(i,j,k)*A(i,j,l) + 5;" << std::endl << std::endl;
- // std::cout << "C1=" << C1 << ";" << std::endl << std::endl;
- // C2(k,l,m) = T2(k,l,m) + A(i,j,k)*B(j,l,i,m) + 5;
- //tensor_t C2 = T2 + prod(A,B,perm_t{1,2},perm_t{3,1}) + 5;
- // tensor_t C2 = T2 + A(_i,_j,_k)*B(_j,_l,_i,_m) + 5;
- // formatted output
- std::cout << "% --------------------------- " << std::endl;
- std::cout << "% --------------------------- " << std::endl << std::endl;
- std::cout << "% C2(k,l,m) = T2(k,l,m) + A(i,j,k)*B(j,l,i,m) + 5;" << std::endl << std::endl;
- // std::cout << "C2=" << C2 << ";" << std::endl << std::endl;
- }
- }
|