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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
//
// 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 <Eigen/CXX11/Tensor>
using Eigen::Tensor;
using Eigen::TensorMap;
static void test_assign()
{
std::string data1[6];
TensorMap<Tensor<std::string, 2>> mat1(data1, 2, 3);
std::string data2[6];
const TensorMap<Tensor<const std::string, 2>> mat2(data2, 2, 3);
for (int i = 0; i < 6; ++i) {
std::ostringstream s1;
s1 << "abc" << i*3;
data1[i] = s1.str();
std::ostringstream s2;
s2 << "def" << i*5;
data2[i] = s2.str();
}
Tensor<std::string, 2> rslt1;
rslt1 = mat1;
Tensor<std::string, 2> rslt2;
rslt2 = mat2;
Tensor<std::string, 2> rslt3 = mat1;
Tensor<std::string, 2> rslt4 = mat2;
Tensor<std::string, 2> rslt5(mat1);
Tensor<std::string, 2> rslt6(mat2);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
VERIFY_IS_EQUAL(rslt1(i,j), data1[i+2*j]);
VERIFY_IS_EQUAL(rslt2(i,j), data2[i+2*j]);
VERIFY_IS_EQUAL(rslt3(i,j), data1[i+2*j]);
VERIFY_IS_EQUAL(rslt4(i,j), data2[i+2*j]);
VERIFY_IS_EQUAL(rslt5(i,j), data1[i+2*j]);
VERIFY_IS_EQUAL(rslt6(i,j), data2[i+2*j]);
}
}
}
static void test_concat()
{
Tensor<std::string, 2> t1(2, 3);
Tensor<std::string, 2> t2(2, 3);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
std::ostringstream s1;
s1 << "abc" << i + j*2;
t1(i, j) = s1.str();
std::ostringstream s2;
s2 << "def" << i*5 + j*32;
t2(i, j) = s2.str();
}
}
Tensor<std::string, 2> result = t1.concatenate(t2, 1);
VERIFY_IS_EQUAL(result.dimension(0), 2);
VERIFY_IS_EQUAL(result.dimension(1), 6);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
VERIFY_IS_EQUAL(result(i, j), t1(i, j));
VERIFY_IS_EQUAL(result(i, j+3), t2(i, j));
}
}
}
static void test_slices()
{
Tensor<std::string, 2> data(2, 6);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
std::ostringstream s1;
s1 << "abc" << i + j*2;
data(i, j) = s1.str();
}
}
const Eigen::DSizes<ptrdiff_t, 2> half_size(2, 3);
const Eigen::DSizes<ptrdiff_t, 2> first_half(0, 0);
const Eigen::DSizes<ptrdiff_t, 2> second_half(0, 3);
Tensor<std::string, 2> t1 = data.slice(first_half, half_size);
Tensor<std::string, 2> t2 = data.slice(second_half, half_size);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
VERIFY_IS_EQUAL(data(i, j), t1(i, j));
VERIFY_IS_EQUAL(data(i, j+3), t2(i, j));
}
}
}
static void test_additions()
{
Tensor<std::string, 1> data1(3);
Tensor<std::string, 1> data2(3);
for (int i = 0; i < 3; ++i) {
data1(i) = "abc";
std::ostringstream s1;
s1 << i;
data2(i) = s1.str();
}
Tensor<std::string, 1> sum = data1 + data2;
for (int i = 0; i < 3; ++i) {
std::ostringstream concat;
concat << "abc" << i;
std::string expected = concat.str();
VERIFY_IS_EQUAL(sum(i), expected);
}
}
static void test_initialization()
{
Tensor<std::string, 2> a(2, 3);
a.setConstant(std::string("foo"));
for (int i = 0; i < 2*3; ++i) {
VERIFY_IS_EQUAL(a(i), std::string("foo"));
}
}
void test_cxx11_tensor_of_strings()
{
// Beware: none of this is likely to ever work on a GPU.
CALL_SUBTEST(test_assign());
CALL_SUBTEST(test_concat());
CALL_SUBTEST(test_slices());
CALL_SUBTEST(test_additions());
CALL_SUBTEST(test_initialization());
}
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