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593 lines
17 KiB
C++
593 lines
17 KiB
C++
// Copyright (c) 2018 Cem Bassoy
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//
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// Distributed under the Boost Software License, Version 1.0. (See
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// accompanying file LICENSE_1_0.txt or copy at
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// http://www.boost.org/LICENSE_1_0.txt)
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//
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// The authors gratefully acknowledge the support of
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// Fraunhofer and Google in producing this work
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// which started as a Google Summer of Code project.
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//
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#include <random>
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#include <boost/test/unit_test.hpp>
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#include "utility.hpp"
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#include <boost/numeric/ublas/tensor/tensor.hpp>
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#include <boost/numeric/ublas/tensor/tags.hpp>
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#include <boost/numeric/ublas/tensor/subtensor.hpp>
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#include <boost/numeric/ublas/tensor/span.hpp>
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BOOST_AUTO_TEST_SUITE ( subtensor_testsuite )
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using test_types = zip<int,float,std::complex<float>>::with_t<boost::numeric::ublas::layout::first_order, boost::numeric::ublas::layout::last_order>;
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struct fixture_shape
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{
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using shape = boost::numeric::ublas::extents<>;
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fixture_shape() : extents{
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shape{}, // 0
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shape{1,1}, // 1
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shape{1,2}, // 2
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shape{2,1}, // 3
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shape{2,3}, // 4
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shape{2,3,1}, // 5
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shape{4,1,3}, // 6
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shape{1,2,3}, // 7
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shape{4,2,3}, // 8
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shape{4,2,3,5} // 9
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}
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{}
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std::vector<shape> extents;
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};
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BOOST_FIXTURE_TEST_CASE_TEMPLATE( subtensor_ctor1_test, value, test_types, fixture_shape )
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{
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namespace ublas = boost::numeric::ublas;
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using value_type = typename value::first_type;
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using layout_type = typename value::second_type;
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using tensor_type = ublas::tensor_dynamic<value_type, layout_type>;
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using subtensor_type = ublas::subtensor<tensor_type>;
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auto check = [](auto const& e) {
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auto t = tensor_type(e);
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auto s = subtensor_type(t);
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BOOST_CHECK_EQUAL ( s.size() , t.size() );
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BOOST_CHECK_EQUAL ( s.rank() , t.rank() );
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if(ublas::empty(e)) {
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BOOST_CHECK_EQUAL ( s.empty(), t.empty() );
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BOOST_CHECK_EQUAL ( s. data(), t. data() );
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}
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else{
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BOOST_CHECK_EQUAL ( !s.empty(), !t.empty() );
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BOOST_CHECK_EQUAL ( s. data(), t. data() );
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}
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};
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for(auto const& e : extents)
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check(e);
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}
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BOOST_AUTO_TEST_CASE_TEMPLATE( subtensor_ctor2_test, value, test_types )
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{
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namespace ub = boost::numeric::ublas;
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using value_type = typename value::first_type;
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using layout_type = typename value::second_type;
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using tensor_type = ub::tensor_dynamic<value_type, layout_type>;
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using subtensor_type = ub::subtensor<tensor_type>;
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using span_type = typename subtensor_type::span_type;
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{
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auto A = tensor_type{};
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auto Asub = subtensor_type( A );
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BOOST_CHECK( Asub.span_strides() == A.strides() );
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BOOST_CHECK( Asub.strides() == A.strides() );
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BOOST_CHECK( Asub.getExtents()() == A.extents() );
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BOOST_CHECK( Asub.data() == A.data() );
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}
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{
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auto A = tensor_type{1,1};
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auto Asub = subtensor_type( A, 0, 0 );
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BOOST_CHECK( Asub.span_strides() == A.strides() );
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BOOST_CHECK( Asub.strides() == A.strides() );
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BOOST_CHECK( Asub.getExtents()() == A.extents() );
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BOOST_CHECK( Asub.data() == A.data() );
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}
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{
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auto A = tensor_type{1,2};
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auto Asub = subtensor_type( A, 0, span_type{} );
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BOOST_CHECK( Asub.span_strides() == A.strides() );
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BOOST_CHECK( Asub.strides() == A.strides() );
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BOOST_CHECK( Asub.getExtents()() == A.extents() );
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BOOST_CHECK( Asub.data() == A.data() );
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}
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{
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auto A = tensor_type{1,2};
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auto Asub = subtensor_type( A, 0, 1 );
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BOOST_CHECK_EQUAL( Asub.span_strides().at(0), A.strides().at(0) );
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BOOST_CHECK_EQUAL( Asub.span_strides().at(1), A.strides().at(1) );
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BOOST_CHECK_EQUAL( Asub.strides().at(0), 1 );
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BOOST_CHECK_EQUAL( Asub.strides().at(1), 1 );
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BOOST_CHECK_EQUAL( Asub.getExtents()().at(0) , 1 );
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BOOST_CHECK_EQUAL( Asub.getExtents()().at(1) , 1 );
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BOOST_CHECK_EQUAL( Asub.data() , A.data()+
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Asub.spans().at(0).first()*A.strides().at(0) +
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Asub.spans().at(1).first()*A.strides().at(1) );
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}
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{
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auto A = tensor_type{2,3};
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auto Asub = subtensor_type( A, 0, 1 );
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auto B = tensor_type(Asub.getExtents()());
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BOOST_CHECK_EQUAL( Asub.span_strides().at(0), A.strides().at(0) );
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BOOST_CHECK_EQUAL( Asub.span_strides().at(1), A.strides().at(1) );
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BOOST_CHECK_EQUAL( Asub.getExtents()().at(0) , 1 );
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BOOST_CHECK_EQUAL( Asub.getExtents()().at(1) , 1 );
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BOOST_CHECK_EQUAL( Asub.strides().at(0), B.strides().at(0) );
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BOOST_CHECK_EQUAL( Asub.strides().at(1), B.strides().at(1) );
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BOOST_CHECK_EQUAL( Asub.data() , A.data()+
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Asub.spans().at(0).first()*A.strides().at(0) +
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Asub.spans().at(1).first()*A.strides().at(1) );
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}
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{
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auto A = tensor_type{4,3};
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auto Asub = subtensor_type( A, span_type(1,2), span_type(1,span_type::max) );
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auto B = tensor_type(Asub.getExtents()());
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BOOST_CHECK_EQUAL( Asub.span_strides().at(0), A.strides().at(0) );
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BOOST_CHECK_EQUAL( Asub.span_strides().at(1), A.strides().at(1) );
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BOOST_CHECK_EQUAL( Asub.getExtents()().at(0) , 2 );
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BOOST_CHECK_EQUAL( Asub.getExtents()().at(1) , 2 );
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BOOST_CHECK_EQUAL( Asub.strides().at(0), B.strides().at(0) );
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BOOST_CHECK_EQUAL( Asub.strides().at(1), B.strides().at(1) );
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BOOST_CHECK_EQUAL( Asub.data() , A.data()+
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Asub.spans().at(0).first()*A.strides().at(0) +
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Asub.spans().at(1).first()*A.strides().at(1) );
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}
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{
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auto A = tensor_type{4,3,5};
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auto Asub = subtensor_type( A, span_type(1,2), span_type(1,span_type::max), span_type(2,4) );
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auto B = tensor_type(Asub.getExtents()());
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BOOST_CHECK_EQUAL( Asub.span_strides().at(0), A.strides().at(0) );
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BOOST_CHECK_EQUAL( Asub.span_strides().at(1), A.strides().at(1) );
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BOOST_CHECK_EQUAL( Asub.span_strides().at(2), A.strides().at(2) );
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BOOST_CHECK_EQUAL( Asub.getExtents()().at(0) , 2 );
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BOOST_CHECK_EQUAL( Asub.getExtents()().at(1) , 2 );
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BOOST_CHECK_EQUAL( Asub.getExtents()().at(2) , 3 );
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BOOST_CHECK_EQUAL( Asub.strides().at(0), B.strides().at(0) );
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BOOST_CHECK_EQUAL( Asub.strides().at(1), B.strides().at(1) );
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BOOST_CHECK_EQUAL( Asub.strides().at(2), B.strides().at(2) );
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BOOST_CHECK_EQUAL( Asub.data() , A.data()+
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Asub.spans().at(0).first()*A.strides().at(0) +
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Asub.spans().at(1).first()*A.strides().at(1)+
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Asub.spans().at(2).first()*A.strides().at(2));
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}
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}
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BOOST_FIXTURE_TEST_CASE_TEMPLATE(subtensor_copy_ctor_test, value, test_types, fixture_shape )
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{
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namespace ublas = boost::numeric::ublas;
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using value_type = typename value::first_type;
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using layout_type = typename value::second_type;
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using tensor_type = ublas::tensor_dynamic<value_type, layout_type>;
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using subtensor_type = ublas::subtensor<tensor_type>;
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using span_type = typename subtensor_type::span_type;
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auto check = [](auto const& e)
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{
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auto A = tensor_type{e};
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value_type i{};
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for(auto & a : A)
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a = i+=value_type{1};
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auto Asub = subtensor_type( A );
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auto Bsub = subtensor_type( A );
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BOOST_CHECK( Asub.span_strides() == A.strides() );
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BOOST_CHECK( Asub.strides() == A.strides() );
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BOOST_CHECK( Asub.getExtents()() == A.extents() );
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BOOST_CHECK( Asub.data() == A.data() );
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BOOST_CHECK( Bsub.span_strides() == A.strides() );
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BOOST_CHECK( Bsub.strides() == A.strides() );
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BOOST_CHECK( Bsub.getExtents() == A.extents() );
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BOOST_CHECK( Bsub.data() == A.data() );
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BOOST_CHECK_EQUAL ( Bsub.size() , A.size() );
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BOOST_CHECK_EQUAL ( Bsub.rank() , A.rank() );
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if(ublas::empty(e)) {
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BOOST_CHECK ( Bsub.empty() );
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BOOST_CHECK_EQUAL ( Bsub.data() , nullptr);
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}
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else{
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BOOST_CHECK ( !Bsub.empty() );
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BOOST_CHECK_NE ( Bsub.data() , nullptr);
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}
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for(auto i = 0ul; i < Asub.size(); ++i)
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BOOST_CHECK_EQUAL( Asub[i], Bsub[i] );
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};
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for(auto const& e : extents)
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check(e);
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}
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#if 0
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BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_copy_ctor_layout, value, test_types, fixture_shape )
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{
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using namespace boost::numeric;
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using value_type = typename value::first_type;
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using layout_type = typename value::second_type;
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using tensor_type = ublas::tensor<value_type, layout_type>;
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using other_layout_type = std::conditional_t<std::is_same<ublas::tag::first_order,layout_type>::value, ublas::tag::last_order, ublas::tag::first_order>;
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using other_tensor_type = ublas::tensor<value_type, other_layout_type>;
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for(auto const& e : extents)
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{
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auto r = tensor_type{e};
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other_tensor_type t = r;
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tensor_type q = t;
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BOOST_CHECK_EQUAL ( t.size() , r.size() );
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BOOST_CHECK_EQUAL ( t.rank() , r.rank() );
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BOOST_CHECK ( t.extents() == r.extents() );
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BOOST_CHECK_EQUAL ( q.size() , r.size() );
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BOOST_CHECK_EQUAL ( q.rank() , r.rank() );
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BOOST_CHECK ( q.strides() == r.strides() );
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BOOST_CHECK ( q.extents() == r.extents() );
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for(auto i = 0ul; i < t.size(); ++i)
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BOOST_CHECK_EQUAL( q[i], r[i] );
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}
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}
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BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_copy_move_ctor, value, test_types, fixture )
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{
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using namespace boost::numeric;
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using value_type = typename value::first_type;
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using layout_type = typename value::second_type;
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using tensor_type = ublas::tensor<value_type, layout_type>;
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auto check = [](auto const& e)
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{
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auto r = tensor_type{e};
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auto t = std::move(r);
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BOOST_CHECK_EQUAL ( t.size() , e.product() );
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BOOST_CHECK_EQUAL ( t.rank() , e.size() );
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if(e.empty()) {
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BOOST_CHECK ( t.empty() );
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BOOST_CHECK_EQUAL ( t.data() , nullptr);
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}
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else{
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BOOST_CHECK ( !t.empty() );
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BOOST_CHECK_NE ( t.data() , nullptr);
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}
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};
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for(auto const& e : extents)
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check(e);
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}
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BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_ctor_extents_init, value, test_types, fixture )
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{
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using namespace boost::numeric;
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using value_type = typename value::first_type;
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using layout_type = typename value::second_type;
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using tensor_type = ublas::tensor<value_type, layout_type>;
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std::random_device device{};
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std::minstd_rand0 generator(device());
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using distribution_type = std::conditional_t<std::is_integral_v<value_type>, std::uniform_int_distribution<>, std::uniform_real_distribution<> >;
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auto distribution = distribution_type(1,6);
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for(auto const& e : extents){
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auto r = static_cast<value_type>(distribution(generator));
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auto t = tensor_type{e,r};
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for(auto i = 0ul; i < t.size(); ++i)
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BOOST_CHECK_EQUAL( t[i], r );
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}
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}
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BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_ctor_extents_array, value, test_types, fixture)
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{
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using namespace boost::numeric;
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using value_type = typename value::first_type;
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using layout_type = typename value::second_type;
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using tensor_type = ublas::tensor<value_type, layout_type>;
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using array_type = typename tensor_type::array_type;
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for(auto const& e : extents) {
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auto a = array_type(e.product());
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auto v = value_type {};
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for(auto& aa : a){
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aa = v;
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v += value_type{1};
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}
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auto t = tensor_type{e, a};
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v = value_type{};
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for(auto i = 0ul; i < t.size(); ++i, v+=value_type{1})
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BOOST_CHECK_EQUAL( t[i], v);
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}
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}
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BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_read_write_single_index_access, value, test_types, fixture)
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{
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using namespace boost::numeric;
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using value_type = typename value::first_type;
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using layout_type = typename value::second_type;
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using tensor_type = ublas::tensor<value_type, layout_type>;
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for(auto const& e : extents) {
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auto t = tensor_type{e};
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auto v = value_type {};
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for(auto i = 0ul; i < t.size(); ++i, v+=value_type{1}){
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t[i] = v;
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BOOST_CHECK_EQUAL( t[i], v );
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t(i) = v;
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BOOST_CHECK_EQUAL( t(i), v );
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}
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}
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}
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BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_read_write_multi_index_access_at, value, test_types, fixture)
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{
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using namespace boost::numeric;
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using value_type = typename value::first_type;
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using layout_type = typename value::second_type;
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using tensor_type = ublas::tensor<value_type, layout_type>;
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auto check1 = [](const tensor_type& t)
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{
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auto v = value_type{};
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for(auto k = 0ul; k < t.size(); ++k){
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BOOST_CHECK_EQUAL(t[k], v);
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v+=value_type{1};
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}
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};
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auto check2 = [](const tensor_type& t)
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{
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std::array<unsigned,2> k;
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auto r = std::is_same_v<layout_type,ublas::tag::first_order> ? 1 : 0;
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auto q = std::is_same_v<layout_type,ublas::tag::last_order > ? 1 : 0;
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auto v = value_type{};
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for(k[r] = 0ul; k[r] < t.size(r); ++k[r]){
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for(k[q] = 0ul; k[q] < t.size(q); ++k[q]){
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BOOST_CHECK_EQUAL(t.at(k[0],k[1]), v);
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v+=value_type{1};
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}
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}
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};
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auto check3 = [](const tensor_type& t)
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{
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std::array<unsigned,3> k;
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using op_type = std::conditional_t<std::is_same_v<layout_type,ublas::tag::first_order>, std::minus<>, std::plus<>>;
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auto r = std::is_same_v<layout_type,ublas::tag::first_order> ? 2 : 0;
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auto o = op_type{};
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auto v = value_type{};
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for(k[r] = 0ul; k[r] < t.size(r); ++k[r]){
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for(k[o(r,1)] = 0ul; k[o(r,1)] < t.size(o(r,1)); ++k[o(r,1)]){
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for(k[o(r,2)] = 0ul; k[o(r,2)] < t.size(o(r,2)); ++k[o(r,2)]){
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BOOST_CHECK_EQUAL(t.at(k[0],k[1],k[2]), v);
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v+=value_type{1};
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}
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}
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}
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};
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auto check4 = [](const tensor_type& t)
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{
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std::array<unsigned,4> k;
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using op_type = std::conditional_t<std::is_same_v<layout_type,ublas::tag::first_order>, std::minus<>, std::plus<>>;
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auto r = std::is_same_v<layout_type,ublas::tag::first_order> ? 3 : 0;
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auto o = op_type{};
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auto v = value_type{};
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for(k[r] = 0ul; k[r] < t.size(r); ++k[r]){
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for(k[o(r,1)] = 0ul; k[o(r,1)] < t.size(o(r,1)); ++k[o(r,1)]){
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for(k[o(r,2)] = 0ul; k[o(r,2)] < t.size(o(r,2)); ++k[o(r,2)]){
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for(k[o(r,3)] = 0ul; k[o(r,3)] < t.size(o(r,3)); ++k[o(r,3)]){
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BOOST_CHECK_EQUAL(t.at(k[0],k[1],k[2],k[3]), v);
|
|
v+=value_type{1};
|
|
}
|
|
}
|
|
}
|
|
}
|
|
};
|
|
|
|
auto check = [check1,check2,check3,check4](auto const& e) {
|
|
auto t = tensor_type{e};
|
|
auto v = value_type {};
|
|
for(auto i = 0ul; i < t.size(); ++i){
|
|
t[i] = v;
|
|
v+=value_type{1};
|
|
}
|
|
|
|
if(t.rank() == 1) check1(t);
|
|
else if(t.rank() == 2) check2(t);
|
|
else if(t.rank() == 3) check3(t);
|
|
else if(t.rank() == 4) check4(t);
|
|
|
|
};
|
|
|
|
for(auto const& e : extents)
|
|
check(e);
|
|
}
|
|
|
|
|
|
|
|
|
|
BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_reshape, value, test_types, fixture)
|
|
{
|
|
using namespace boost::numeric;
|
|
using value_type = typename value::first_type;
|
|
using layout_type = typename value::second_type;
|
|
using tensor_type = ublas::tensor<value_type, layout_type>;
|
|
|
|
|
|
for(auto const& efrom : extents){
|
|
for(auto const& eto : extents){
|
|
|
|
auto v = value_type {};
|
|
v+=value_type{1};
|
|
auto t = tensor_type{efrom, v};
|
|
for(auto i = 0ul; i < t.size(); ++i)
|
|
BOOST_CHECK_EQUAL( t[i], v );
|
|
|
|
t.reshape(eto);
|
|
for(auto i = 0ul; i < std::min(efrom.product(),eto.product()); ++i)
|
|
BOOST_CHECK_EQUAL( t[i], v );
|
|
|
|
BOOST_CHECK_EQUAL ( t.size() , eto.product() );
|
|
BOOST_CHECK_EQUAL ( t.rank() , eto.size() );
|
|
BOOST_CHECK ( t.extents() == eto );
|
|
|
|
if(efrom != eto){
|
|
for(auto i = efrom.product(); i < t.size(); ++i)
|
|
BOOST_CHECK_EQUAL( t[i], value_type{} );
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
|
|
|
|
BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_swap, value, test_types, fixture)
|
|
{
|
|
using namespace boost::numeric;
|
|
using value_type = typename value::first_type;
|
|
using layout_type = typename value::second_type;
|
|
using tensor_type = ublas::tensor<value_type, layout_type>;
|
|
|
|
for(auto const& e_t : extents){
|
|
for(auto const& e_r : extents) {
|
|
|
|
auto v = value_type {} + value_type{1};
|
|
auto w = value_type {} + value_type{2};
|
|
auto t = tensor_type{e_t, v};
|
|
auto r = tensor_type{e_r, w};
|
|
|
|
std::swap( r, t );
|
|
|
|
for(auto i = 0ul; i < t.size(); ++i)
|
|
BOOST_CHECK_EQUAL( t[i], w );
|
|
|
|
BOOST_CHECK_EQUAL ( t.size() , e_r.product() );
|
|
BOOST_CHECK_EQUAL ( t.rank() , e_r.size() );
|
|
BOOST_CHECK ( t.extents() == e_r );
|
|
|
|
for(auto i = 0ul; i < r.size(); ++i)
|
|
BOOST_CHECK_EQUAL( r[i], v );
|
|
|
|
BOOST_CHECK_EQUAL ( r.size() , e_t.product() );
|
|
BOOST_CHECK_EQUAL ( r.rank() , e_t.size() );
|
|
BOOST_CHECK ( r.extents() == e_t );
|
|
|
|
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
|
|
BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_standard_iterator, value, test_types, fixture)
|
|
{
|
|
using namespace boost::numeric;
|
|
using value_type = typename value::first_type;
|
|
using layout_type = typename value::second_type;
|
|
using tensor_type = ublas::tensor<value_type, layout_type>;
|
|
|
|
for(auto const& e : extents)
|
|
{
|
|
auto v = value_type {} + value_type{1};
|
|
auto t = tensor_type{e, v};
|
|
|
|
BOOST_CHECK_EQUAL( std::distance(t.begin(), t.end ()), t.size() );
|
|
BOOST_CHECK_EQUAL( std::distance(t.rbegin(), t.rend()), t.size() );
|
|
|
|
BOOST_CHECK_EQUAL( std::distance(t.cbegin(), t.cend ()), t.size() );
|
|
BOOST_CHECK_EQUAL( std::distance(t.crbegin(), t.crend()), t.size() );
|
|
|
|
if(t.size() > 0) {
|
|
BOOST_CHECK( t.data() == std::addressof( *t.begin () ) ) ;
|
|
BOOST_CHECK( t.data() == std::addressof( *t.cbegin() ) ) ;
|
|
}
|
|
}
|
|
}
|
|
|
|
#endif
|
|
|
|
BOOST_AUTO_TEST_SUITE_END()
|