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Created additional unit tests for the tensor code and improved existing ones.

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This commit is contained in:
Benoit Steiner 2014-06-13 10:20:28 -07:00
parent f80c8e17eb
commit 774c3c1e0a
4 changed files with 143 additions and 2 deletions
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3
unsupported/test/CMakeLists.txt
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@ -105,7 +105,10 @@ if(EIGEN_TEST_CXX11)
ei_add_test(cxx11_tensor_contraction "-std=c++0x")
ei_add_test(cxx11_tensor_convolution "-std=c++0x")
ei_add_test(cxx11_tensor_expr "-std=c++0x")
# ei_add_test(cxx11_tensor_fixed_size "-std=c++0x")
ei_add_test(cxx11_tensor_lvalue "-std=c++0x")
ei_add_test(cxx11_tensor_map "-std=c++0x")
ei_add_test(cxx11_tensor_morphing "-std=c++0x")
# ei_add_test(cxx11_tensor_device "-std=c++0x")
# ei_add_test(cxx11_tensor_fixed_size "-std=c++0x")
# ei_add_test(cxx11_tensor_thread_pool "-std=c++0x")

28
unsupported/test/cxx11_tensor_device.cpp
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@ -65,6 +65,12 @@ static void test_contextual_eval(Context* context)
context->out() = context->in1() + context->in2() * 3.14f + context->in1().constant(2.718f);
}
template <typename Context>
static void test_forced_contextual_eval(Context* context)
{
context->out() = (context->in1() + context->in2()).eval() * 3.14f + context->in1().constant(2.718f);
}
static void test_cpu() {
Eigen::Tensor<float, 3> in1(Eigen::array<int, 3>(2,3,7));
Eigen::Tensor<float, 3> in2(Eigen::array<int, 3>(2,3,7));
@ -72,9 +78,9 @@ static void test_cpu() {
in1.setRandom();
in2.setRandom();
CPUContext context(in1, in2, out);
test_contextual_eval(&context);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
@ -82,6 +88,15 @@ static void test_cpu() {
}
}
}
test_forced_contextual_eval(&context);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
VERIFY_IS_APPROX(out(Eigen::array<int, 3>(i,j,k)), (in1(Eigen::array<int, 3>(i,j,k)) + in2(Eigen::array<int, 3>(i,j,k))) * 3.14f + 2.718f);
}
}
}
}
static void test_gpu() {
@ -111,7 +126,6 @@ static void test_gpu() {
GPUContext context(gpu_in1, gpu_in2, gpu_out);
test_contextual_eval(&context);
cudaMemcpy(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
@ -120,6 +134,16 @@ static void test_gpu() {
}
}
}
test_forced_contextual_eval(&context);
cudaMemcpy(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
VERIFY_IS_APPROX(out(Eigen::array<int, 3>(i,j,k)), (in1(Eigen::array<int, 3>(i,j,k)) + in2(Eigen::array<int, 3>(i,j,k))) * 3.14f + 2.718f);
}
}
}
}

42
unsupported/test/cxx11_tensor_lvalue.cpp Normal file
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@ -0,0 +1,42 @@
// 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::RowMajor;
static void test_compound_assignment()
{
Tensor<float, 3> mat1(2,3,7);
Tensor<float, 3> mat2(2,3,7);
Tensor<float, 3> mat3(2,3,7);
mat1.setRandom();
mat2.setRandom();
mat3 = mat1;
mat3 += mat2;
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
VERIFY_IS_APPROX(mat3(i,j,k), mat1(i,j,k) + mat2(i,j,k));
}
}
}
}
void test_cxx11_tensor_lvalue()
{
CALL_SUBTEST(test_compound_assignment());
}

72
unsupported/test/cxx11_tensor_morphing.cpp Normal file
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@ -0,0 +1,72 @@
// 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;
static void test_simple_reshape()
{
Tensor<float, 5> tensor1(2,3,1,7,1);
tensor1.setRandom();
Tensor<float, 3> tensor2(2,3,7);
Tensor<float, 2> tensor3(6,7);
Tensor<float, 2> tensor4(2,21);
Tensor<float, 3>::Dimensions dim1{{2,3,7}};
tensor2 = tensor1.reshape(dim1);
Tensor<float, 2>::Dimensions dim2{{6,7}};
tensor3 = tensor1.reshape(dim2);
Tensor<float, 2>::Dimensions dim3{{2,21}};
tensor4 = tensor1.reshape(dim1).reshape(dim3);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor2(i,j,k));
VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor3(i+2*j,k));
VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor4(i,j+3*k));
}
}
}
}
static void test_reshape_in_expr() {
MatrixXf m1(2,3*5*7*11);
MatrixXf m2(3*5*7*11,13);
m1.setRandom();
m2.setRandom();
MatrixXf m3 = m1 * m2;
TensorMap<Tensor<float, 5>> tensor1(m1.data(), 2,3,5,7,11);
TensorMap<Tensor<float, 5>> tensor2(m2.data(), 3,5,7,11,13);
Tensor<float, 2>::Dimensions newDims1{{2,3*5*7*11}};
Tensor<float, 2>::Dimensions newDims2{{3*5*7*11,13}};
typedef Tensor<float, 1>::DimensionPair DimPair;
array<DimPair, 1> contract_along{{DimPair(1, 0)}};
Tensor<float, 2> tensor3(2,13);
tensor3 = tensor1.reshape(newDims1).contract(tensor2.reshape(newDims2), contract_along);
Map<MatrixXf> res(tensor3.data(), 2, 13);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 13; ++j) {
VERIFY_IS_APPROX(res(i,j), m3(i,j));
}
}
}
void test_cxx11_tensor_morphing()
{
CALL_SUBTEST(test_simple_reshape());
CALL_SUBTEST(test_reshape_in_expr());
}