// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2014 Benoit Steiner // // This Source Code Form is subject to the terms of the Mozilla // Public License v. 2.0. If a copy of the MPL was not distributed // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. #include "main.h" #include using Eigen::Tensor; using Eigen::DefaultDevice; static void test_evals() { Tensor input(3, 3); Tensor kernel(2); input.setRandom(); kernel.setRandom(); Tensor result(2,3); result.setZero(); Eigen::array::Index, 1> dims3({0}); typedef TensorEvaluator Evaluator; Evaluator eval(input.convolve(kernel, dims3), DefaultDevice()); eval.evalTo(result.data()); EIGEN_STATIC_ASSERT(Evaluator::NumDims==2ul, YOU_MADE_A_PROGRAMMING_MISTAKE); VERIFY_IS_EQUAL(eval.dimensions()[0], 2); VERIFY_IS_EQUAL(eval.dimensions()[1], 3); VERIFY_IS_APPROX(result(0,0), input(0,0)*kernel(0) + input(1,0)*kernel(1)); // index 0 VERIFY_IS_APPROX(result(0,1), input(0,1)*kernel(0) + input(1,1)*kernel(1)); // index 2 VERIFY_IS_APPROX(result(0,2), input(0,2)*kernel(0) + input(1,2)*kernel(1)); // index 4 VERIFY_IS_APPROX(result(1,0), input(1,0)*kernel(0) + input(2,0)*kernel(1)); // index 1 VERIFY_IS_APPROX(result(1,1), input(1,1)*kernel(0) + input(2,1)*kernel(1)); // index 3 VERIFY_IS_APPROX(result(1,2), input(1,2)*kernel(0) + input(2,2)*kernel(1)); // index 5 } static void test_expr() { Tensor input(3, 3); Tensor kernel(2, 2); input.setRandom(); kernel.setRandom(); Tensor result(2,2); Eigen::array dims({0, 1}); result = input.convolve(kernel, dims); VERIFY_IS_APPROX(result(0,0), input(0,0)*kernel(0,0) + input(0,1)*kernel(0,1) + input(1,0)*kernel(1,0) + input(1,1)*kernel(1,1)); VERIFY_IS_APPROX(result(0,1), input(0,1)*kernel(0,0) + input(0,2)*kernel(0,1) + input(1,1)*kernel(1,0) + input(1,2)*kernel(1,1)); VERIFY_IS_APPROX(result(1,0), input(1,0)*kernel(0,0) + input(1,1)*kernel(0,1) + input(2,0)*kernel(1,0) + input(2,1)*kernel(1,1)); VERIFY_IS_APPROX(result(1,1), input(1,1)*kernel(0,0) + input(1,2)*kernel(0,1) + input(2,1)*kernel(1,0) + input(2,2)*kernel(1,1)); } void test_cxx11_tensor_convolution() { CALL_SUBTEST(test_evals()); CALL_SUBTEST(test_expr()); }