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231ba5f730
Auxiliary functions for extents and strides were using different functions. Additionally, many tags were used to distinguish between different tensor types. This patch simplifies interfaces of different core functions and unifies functions that can process different types of extent and stride types.
199 lines
6.1 KiB
C++
199 lines
6.1 KiB
C++
//
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// Copyright (c) 2018-2020, Cem Bassoy, cem.bassoy@gmail.com
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// Copyright (c) 2019-2020, Amit Singh, amitsingh19975@gmail.com
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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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// Google and Fraunhofer IOSB, Ettlingen, Germany
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//
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#include <boost/numeric/ublas/tensor.hpp>
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#include <boost/test/unit_test.hpp>
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#include <boost/multiprecision/cpp_bin_float.hpp>
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#include "utility.hpp"
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BOOST_AUTO_TEST_SUITE(test_tensor_static_comparison)
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using double_extended = boost::multiprecision::cpp_bin_float_double_extended;
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using test_types = zip<int,float,double_extended>::with_t<boost::numeric::ublas::layout::first_order, boost::numeric::ublas::layout::last_order>;
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struct fixture {
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template<size_t... N>
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using extents_type = boost::numeric::ublas::extents<N...>;
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fixture()= default;
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std::tuple<
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extents_type<1,1>, // 1
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extents_type<2,3>, // 2
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extents_type<4,1,3>, // 3
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extents_type<4,2,3>, // 4
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extents_type<4,2,3,5> // 5
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> extents;
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};
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BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_comparison, value, test_types, fixture)
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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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auto check = [](auto const& /*unused*/, auto& e)
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{
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using extents_type = std::decay_t<decltype(e)>;
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using tensor_type = ublas::tensor_static<value_type, extents_type, layout_type>;
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auto t = tensor_type ();
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auto t2 = tensor_type ();
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auto v = value_type {};
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std::iota(t.begin(), t.end(), v);
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std::iota(t2.begin(), t2.end(), v+2);
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BOOST_CHECK( t == t );
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BOOST_CHECK( t != t2 );
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if(t.empty())
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return;
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BOOST_CHECK(!(t < t));
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BOOST_CHECK(!(t > t));
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BOOST_CHECK( t < t2 );
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BOOST_CHECK( t2 > t );
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BOOST_CHECK( t <= t );
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BOOST_CHECK( t >= t );
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BOOST_CHECK( t <= t2 );
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BOOST_CHECK( t2 >= t );
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BOOST_CHECK( t2 >= t2 );
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BOOST_CHECK( t2 >= t );
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};
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for_each_in_tuple(extents,check);
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}
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BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_comparison_with_tensor_expressions, value, test_types, fixture)
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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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auto check = [](auto const& /*unused*/, auto& e)
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{
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using extents_type = std::decay_t<decltype(e)>;
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using tensor_type = ublas::tensor_static<value_type, extents_type, layout_type>;
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auto t = tensor_type ();
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auto t2 = tensor_type ();
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auto v = value_type {};
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std::iota(t.begin(), t.end(), v);
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std::iota(t2.begin(), t2.end(), v+2);
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BOOST_CHECK( t == t );
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BOOST_CHECK( t != t2 );
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if(t.empty())
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return;
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BOOST_CHECK( !(t < t) );
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BOOST_CHECK( !(t > t) );
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BOOST_CHECK( t < (t2+t) );
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BOOST_CHECK( (t2+t) > t );
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BOOST_CHECK( t <= (t+t) );
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BOOST_CHECK( (t+t2) >= t );
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BOOST_CHECK( (t2+t2+2) >= t);
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BOOST_CHECK( 2*t2 > t );
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BOOST_CHECK( t < 2*t2 );
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BOOST_CHECK( 2*t2 > t);
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BOOST_CHECK( 2*t2 >= t2 );
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BOOST_CHECK( t2 <= 2*t2);
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BOOST_CHECK( 3*t2 >= t );
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};
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for_each_in_tuple(extents,check);
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}
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BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_comparison_with_scalar, value, test_types, fixture)
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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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for_each_in_tuple(extents,[](auto const& /*unused*/, auto& e)
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{
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using extents_type = std::decay_t<decltype(e)>;
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using tensor_type = ublas::tensor_static<value_type, extents_type, layout_type>;
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BOOST_CHECK( tensor_type(value_type{2}) == tensor_type(value_type{2}) );
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BOOST_CHECK( tensor_type(value_type{2}) != tensor_type(value_type{1}) );
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if(ublas::empty(e))
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return;
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BOOST_CHECK( !(tensor_type(2) < 2) );
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BOOST_CHECK( !(tensor_type(2) > 2) );
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BOOST_CHECK( (tensor_type(2) >= 2) );
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BOOST_CHECK( (tensor_type(2) <= 2) );
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BOOST_CHECK( (tensor_type(2) == 2) );
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BOOST_CHECK( (tensor_type(2) != 3) );
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BOOST_CHECK( !(2 > tensor_type(2)) );
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BOOST_CHECK( !(2 < tensor_type(2)) );
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BOOST_CHECK( (2 <= tensor_type(2)) );
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BOOST_CHECK( (2 >= tensor_type(2)) );
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BOOST_CHECK( (2 == tensor_type(2)) );
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BOOST_CHECK( (3 != tensor_type(2)) );
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BOOST_CHECK( !( tensor_type(2)+3 < 5) );
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BOOST_CHECK( !( tensor_type(2)+3 > 5) );
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BOOST_CHECK( ( tensor_type(2)+3 >= 5) );
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BOOST_CHECK( ( tensor_type(2)+3 <= 5) );
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BOOST_CHECK( ( tensor_type(2)+3 == 5) );
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BOOST_CHECK( ( tensor_type(2)+3 != 6) );
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BOOST_CHECK( !( 5 > tensor_type(2)+3) );
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BOOST_CHECK( !( 5 < tensor_type(2)+3) );
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BOOST_CHECK( ( 5 >= tensor_type(2)+3) );
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BOOST_CHECK( ( 5 <= tensor_type(2)+3) );
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BOOST_CHECK( ( 5 == tensor_type(2)+3) );
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BOOST_CHECK( ( 6 != tensor_type(2)+3) );
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BOOST_CHECK( !( tensor_type(2)+tensor_type(3) < 5) );
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BOOST_CHECK( !( tensor_type(2)+tensor_type(3) > 5) );
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BOOST_CHECK( ( tensor_type(2)+tensor_type(3) >= 5) );
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BOOST_CHECK( ( tensor_type(2)+tensor_type(3) <= 5) );
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BOOST_CHECK( ( tensor_type(2)+tensor_type(3) == 5) );
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BOOST_CHECK( ( tensor_type(2)+tensor_type(3) != 6) );
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BOOST_CHECK( !( 5 > tensor_type(2)+tensor_type(3)) );
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BOOST_CHECK( !( 5 < tensor_type(2)+tensor_type(3)) );
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BOOST_CHECK( ( 5 >= tensor_type(2)+tensor_type(3)) );
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BOOST_CHECK( ( 5 <= tensor_type(2)+tensor_type(3)) );
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BOOST_CHECK( ( 5 == tensor_type(2)+tensor_type(3)) );
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BOOST_CHECK( ( 6 != tensor_type(2)+tensor_type(3)) );
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});
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}
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BOOST_AUTO_TEST_SUITE_END()
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