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92 lines
2.2 KiB
C++
92 lines
2.2 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include "main.h"
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#include <Eigen/CXX11/Tensor>
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struct Generator1D {
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Generator1D() { }
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float operator()(const array<Eigen::DenseIndex, 1>& coordinates) const {
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return coordinates[0];
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}
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};
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template <int DataLayout>
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static void test_1D()
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{
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Tensor<float, 1> vec(6);
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Tensor<float, 1> result = vec.generate(Generator1D());
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for (int i = 0; i < 6; ++i) {
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VERIFY_IS_EQUAL(result(i), i);
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}
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}
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struct Generator2D {
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Generator2D() { }
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float operator()(const array<Eigen::DenseIndex, 2>& coordinates) const {
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return 3 * coordinates[0] + 11 * coordinates[1];
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}
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};
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template <int DataLayout>
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static void test_2D()
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{
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Tensor<float, 2> matrix(5, 7);
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Tensor<float, 2> result = matrix.generate(Generator2D());
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for (int i = 0; i < 5; ++i) {
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for (int j = 0; j < 5; ++j) {
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VERIFY_IS_EQUAL(result(i, j), 3*i + 11*j);
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}
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}
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}
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template <int DataLayout>
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static void test_gaussian()
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{
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int rows = 32;
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int cols = 48;
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array<float, 2> means;
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means[0] = rows / 2.0f;
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means[1] = cols / 2.0f;
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array<float, 2> std_devs;
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std_devs[0] = 3.14f;
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std_devs[1] = 2.7f;
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internal::GaussianGenerator<float, Eigen::DenseIndex, 2> gaussian_gen(means, std_devs);
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Tensor<float, 2> matrix(rows, cols);
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Tensor<float, 2> result = matrix.generate(gaussian_gen);
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for (int i = 0; i < rows; ++i) {
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for (int j = 0; j < cols; ++j) {
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float g_rows = powf(rows/2.0f - i, 2) / (3.14f * 3.14f) * 0.5f;
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float g_cols = powf(cols/2.0f - j, 2) / (2.7f * 2.7f) * 0.5f;
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float gaussian = expf(-g_rows - g_cols);
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VERIFY_IS_EQUAL(result(i, j), gaussian);
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}
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}
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}
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void test_cxx11_tensor_generator()
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{
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CALL_SUBTEST(test_1D<ColMajor>());
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CALL_SUBTEST(test_1D<RowMajor>());
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CALL_SUBTEST(test_2D<ColMajor>());
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CALL_SUBTEST(test_2D<RowMajor>());
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CALL_SUBTEST(test_gaussian<ColMajor>());
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CALL_SUBTEST(test_gaussian<RowMajor>());
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}
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