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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.
247 lines
8.1 KiB
C++
247 lines
8.1 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 <boost/numeric/ublas/tensor/operators_comparison.hpp>
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#include <boost/numeric/ublas/tensor/operators_arithmetic.hpp>
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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_comparison/*, * boost::unit_test::depends_on("test_tensor")*/)
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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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using extents_type = boost::numeric::ublas::extents<>;
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fixture()
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: extents{
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// extents_type{}, // 0
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extents_type{1,1}, // 1
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extents_type{1,2}, // 2
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extents_type{2,1}, // 3
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extents_type{2,3}, // 4
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extents_type{2,3,1}, // 5
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extents_type{4,1,3}, // 6
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extents_type{1,2,3}, // 7
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extents_type{4,2,3}, // 8
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extents_type{4,2,3,5}} // 9
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{
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}
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std::vector<extents_type> 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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using tensor_type = ublas::tensor_dynamic<value_type,layout_type>;
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auto check = [](auto const& e)
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{
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auto t = tensor_type (e);
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auto t2 = tensor_type (e);
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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(auto const& e : extents)
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check(e);
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auto e0 = extents.at(0);
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auto e1 = extents.at(1);
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auto e2 = extents.at(2);
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auto b = false;
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BOOST_CHECK_NO_THROW ( b = (tensor_type(e0) == tensor_type(e0)));
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BOOST_CHECK_NO_THROW ( b = (tensor_type(e1) == tensor_type(e2)));
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BOOST_CHECK_NO_THROW ( b = (tensor_type(e0) == tensor_type(e2)));
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BOOST_CHECK_NO_THROW ( b = (tensor_type(e1) != tensor_type(e2)));
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BOOST_CHECK_THROW ( b = (tensor_type(e1) >= tensor_type(e2)), std::runtime_error );
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BOOST_CHECK_THROW ( b = (tensor_type(e1) <= tensor_type(e2)), std::runtime_error );
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BOOST_CHECK_THROW ( b = (tensor_type(e1) < tensor_type(e2)), std::runtime_error );
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BOOST_CHECK_THROW ( b = (tensor_type(e1) > tensor_type(e2)), std::runtime_error );
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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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using tensor_type = ublas::tensor_dynamic<value_type,layout_type>;
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auto check = [](auto const& e)
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{
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auto t = tensor_type (e);
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auto t2 = tensor_type (e);
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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(auto const& e : extents)
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check(e);
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auto e0 = extents.at(0);
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auto e1 = extents.at(1);
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auto e2 = extents.at(2);
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auto b = false;
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BOOST_CHECK_NO_THROW (b = tensor_type(e0) == (tensor_type(e0) + tensor_type(e0)) );
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BOOST_CHECK_NO_THROW (b = tensor_type(e1) == (tensor_type(e2) + tensor_type(e2)) );
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BOOST_CHECK_NO_THROW (b = tensor_type(e0) == (tensor_type(e2) + 2) );
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BOOST_CHECK_NO_THROW (b = tensor_type(e1) != (2 + tensor_type(e2)) );
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BOOST_CHECK_NO_THROW (b = (tensor_type(e0) + tensor_type(e0)) == tensor_type(e0) );
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BOOST_CHECK_NO_THROW (b = (tensor_type(e2) + tensor_type(e2)) == tensor_type(e1) );
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BOOST_CHECK_NO_THROW (b = (tensor_type(e2) + 2) == tensor_type(e0) );
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BOOST_CHECK_NO_THROW (b = (2 + tensor_type(e2)) != tensor_type(e1) );
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BOOST_CHECK_THROW (b = tensor_type(e1) >= (tensor_type(e2) + tensor_type(e2)), std::runtime_error );
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BOOST_CHECK_THROW (b = tensor_type(e1) <= (tensor_type(e2) + tensor_type(e2)), std::runtime_error );
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BOOST_CHECK_THROW (b = tensor_type(e1) < (tensor_type(e2) + tensor_type(e2)), std::runtime_error );
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BOOST_CHECK_THROW (b = tensor_type(e1) > (tensor_type(e2) + tensor_type(e2)), std::runtime_error );
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BOOST_CHECK_THROW (b = tensor_type(e1) >= (tensor_type(e2) + 2), std::runtime_error );
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BOOST_CHECK_THROW (b = tensor_type(e1) <= (2 + tensor_type(e2)), std::runtime_error );
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BOOST_CHECK_THROW (b = tensor_type(e1) < (tensor_type(e2) + 3), std::runtime_error );
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BOOST_CHECK_THROW (b = tensor_type(e1) > (4 + tensor_type(e2)), std::runtime_error );
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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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using tensor_type = ublas::tensor_dynamic<value_type,layout_type>;
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auto check = [](auto const& e)
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{
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BOOST_CHECK( tensor_type(e,value_type{2}) == tensor_type(e,value_type{2}) );
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BOOST_CHECK( tensor_type(e,value_type{2}) != tensor_type(e,value_type{1}) );
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if(ublas::empty(e))
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return;
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BOOST_CHECK( !(tensor_type(e,2) < 2) );
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BOOST_CHECK( !(tensor_type(e,2) > 2) );
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BOOST_CHECK( (tensor_type(e,2) >= 2) );
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BOOST_CHECK( (tensor_type(e,2) <= 2) );
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BOOST_CHECK( (tensor_type(e,2) == 2) );
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BOOST_CHECK( (tensor_type(e,2) != 3) );
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BOOST_CHECK( !(2 > tensor_type(e,2)) );
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BOOST_CHECK( !(2 < tensor_type(e,2)) );
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BOOST_CHECK( (2 <= tensor_type(e,2)) );
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BOOST_CHECK( (2 >= tensor_type(e,2)) );
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BOOST_CHECK( (2 == tensor_type(e,2)) );
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BOOST_CHECK( (3 != tensor_type(e,2)) );
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BOOST_CHECK( !( tensor_type(e,2)+3 < 5) );
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BOOST_CHECK( !( tensor_type(e,2)+3 > 5) );
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BOOST_CHECK( ( tensor_type(e,2)+3 >= 5) );
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BOOST_CHECK( ( tensor_type(e,2)+3 <= 5) );
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BOOST_CHECK( ( tensor_type(e,2)+3 == 5) );
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BOOST_CHECK( ( tensor_type(e,2)+3 != 6) );
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BOOST_CHECK( !( 5 > tensor_type(e,2)+3) );
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BOOST_CHECK( !( 5 < tensor_type(e,2)+3) );
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BOOST_CHECK( ( 5 >= tensor_type(e,2)+3) );
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BOOST_CHECK( ( 5 <= tensor_type(e,2)+3) );
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BOOST_CHECK( ( 5 == tensor_type(e,2)+3) );
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BOOST_CHECK( ( 6 != tensor_type(e,2)+3) );
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BOOST_CHECK( !( tensor_type(e,2)+tensor_type(e,3) < 5) );
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BOOST_CHECK( !( tensor_type(e,2)+tensor_type(e,3) > 5) );
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BOOST_CHECK( ( tensor_type(e,2)+tensor_type(e,3) >= 5) );
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BOOST_CHECK( ( tensor_type(e,2)+tensor_type(e,3) <= 5) );
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BOOST_CHECK( ( tensor_type(e,2)+tensor_type(e,3) == 5) );
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BOOST_CHECK( ( tensor_type(e,2)+tensor_type(e,3) != 6) );
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BOOST_CHECK( !( 5 > tensor_type(e,2)+tensor_type(e,3)) );
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BOOST_CHECK( !( 5 < tensor_type(e,2)+tensor_type(e,3)) );
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BOOST_CHECK( ( 5 >= tensor_type(e,2)+tensor_type(e,3)) );
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BOOST_CHECK( ( 5 <= tensor_type(e,2)+tensor_type(e,3)) );
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BOOST_CHECK( ( 5 == tensor_type(e,2)+tensor_type(e,3)) );
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BOOST_CHECK( ( 6 != tensor_type(e,2)+tensor_type(e,3)) );
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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_SUITE_END()
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