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Misc improvements and cleanups

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This commit is contained in:
Benoit Steiner
2014-10-13 17:02:09 -07:00
parent 4c70b0a762
commit 99d75235a9
29 changed files with 779 additions and 140 deletions
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232
unsupported/test/cxx11_tensor_thread_pool.cpp
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@@ -9,22 +9,23 @@
#define EIGEN_USE_THREADS
#include <iostream>
#include "main.h"
#include <Eigen/CXX11/Tensor>
using Eigen::Tensor;
void test_cxx11_tensor_thread_pool()
static void test_multithread_elementwise()
{
Eigen::Tensor<float, 3> in1(2,3,7);
Eigen::Tensor<float, 3> in2(2,3,7);
Eigen::Tensor<float, 3> out(2,3,7);
Tensor<float, 3> in1(2,3,7);
Tensor<float, 3> in2(2,3,7);
Tensor<float, 3> out(2,3,7);
in1.setRandom();
in2.setRandom();
Eigen::ThreadPoolDevice thread_pool_device(3);
Eigen::ThreadPoolDevice thread_pool_device(internal::random<int>(3, 11));
out.device(thread_pool_device) = in1 + in2 * 3.14f;
for (int i = 0; i < 2; ++i) {
@@ -35,3 +36,222 @@ void test_cxx11_tensor_thread_pool()
}
}
}
static void test_multithread_compound_assignment()
{
Tensor<float, 3> in1(2,3,7);
Tensor<float, 3> in2(2,3,7);
Tensor<float, 3> out(2,3,7);
in1.setRandom();
in2.setRandom();
Eigen::ThreadPoolDevice thread_pool_device(internal::random<int>(3, 11));
out.device(thread_pool_device) = in1;
out.device(thread_pool_device) += in2 * 3.14f;
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(i,j,k), in1(i,j,k) + in2(i,j,k) * 3.14f);
}
}
}
}
static void test_multithread_contraction()
{
Tensor<float, 4> t_left(30, 50, 37, 31);
Tensor<float, 5> t_right(37, 31, 70, 2, 10);
Tensor<float, 5> t_result(30, 50, 70, 2, 10);
t_left.setRandom();
t_right.setRandom();
// this contraction should be equivalent to a single matrix multiplication
typedef Tensor<float, 1>::DimensionPair DimPair;
Eigen::array<DimPair, 2> dims({{DimPair(2, 0), DimPair(3, 1)}});
typedef Map<MatrixXf> MapXf;
MapXf m_left(t_left.data(), 1500, 1147);
MapXf m_right(t_right.data(), 1147, 1400);
MatrixXf m_result(1500, 1400);
Eigen::ThreadPoolDevice thread_pool_device(4);
// compute results by separate methods
t_result.device(thread_pool_device) = t_left.contract(t_right, dims);
m_result = m_left * m_right;
for (ptrdiff_t i = 0; i < t_result.size(); i++) {
VERIFY(&t_result.data()[i] != &m_result.data()[i]);
if (fabs(t_result.data()[i] - m_result.data()[i]) >= 1e-4) {
std::cout << "mismatch detected: " << t_result.data()[i] << " vs " << m_result.data()[i] << std::endl;
assert(false);
}
}
}
static void test_contraction_corner_cases()
{
Tensor<float, 2> t_left(32, 500);
Tensor<float, 2> t_right(32, 28*28);
Tensor<float, 2> t_result(500, 28*28);
t_left = (t_left.constant(-0.5f) + t_left.random()) * 2.0f;
t_right = (t_right.constant(-0.6f) + t_right.random()) * 2.0f;
t_result = t_result.constant(NAN);
// this contraction should be equivalent to a single matrix multiplication
typedef Tensor<float, 1>::DimensionPair DimPair;
Eigen::array<DimPair, 1> dims{{DimPair(0, 0)}};
typedef Map<MatrixXf> MapXf;
MapXf m_left(t_left.data(), 32, 500);
MapXf m_right(t_right.data(), 32, 28*28);
MatrixXf m_result(500, 28*28);
Eigen::ThreadPoolDevice thread_pool_device(12);
// compute results by separate methods
t_result.device(thread_pool_device) = t_left.contract(t_right, dims);
m_result = m_left.transpose() * m_right;
for (ptrdiff_t i = 0; i < t_result.size(); i++) {
assert(!isnan(t_result.data()[i]));
if (fabs(t_result.data()[i] - m_result.data()[i]) >= 1e-4) {
std::cout << "mismatch detected at index " << i << " : " << t_result.data()[i] << " vs " << m_result.data()[i] << std::endl;
assert(false);
}
}
t_left.resize(32, 1);
t_left = (t_left.constant(-0.5f) + t_left.random()) * 2.0f;
t_result.resize (1, 28*28);
t_result = t_result.constant(NAN);
t_result.device(thread_pool_device) = t_left.contract(t_right, dims);
new(&m_left) MapXf(t_left.data(), 32, 1);
m_result = m_left.transpose() * m_right;
for (ptrdiff_t i = 0; i < t_result.size(); i++) {
assert(!isnan(t_result.data()[i]));
if (fabs(t_result.data()[i] - m_result.data()[i]) >= 1e-4) {
std::cout << "mismatch detected: " << t_result.data()[i] << " vs " << m_result.data()[i] << std::endl;
assert(false);
}
}
t_left.resize(32, 500);
t_right.resize(32, 4);
t_left = (t_left.constant(-0.5f) + t_left.random()) * 2.0f;
t_right = (t_right.constant(-0.6f) + t_right.random()) * 2.0f;
t_result.resize (500, 4);
t_result = t_result.constant(NAN);
t_result.device(thread_pool_device) = t_left.contract(t_right, dims);
new(&m_left) MapXf(t_left.data(), 32, 500);
new(&m_right) MapXf(t_right.data(), 32, 4);
m_result = m_left.transpose() * m_right;
for (ptrdiff_t i = 0; i < t_result.size(); i++) {
assert(!isnan(t_result.data()[i]));
if (fabs(t_result.data()[i] - m_result.data()[i]) >= 1e-4) {
std::cout << "mismatch detected: " << t_result.data()[i] << " vs " << m_result.data()[i] << std::endl;
assert(false);
}
}
t_left.resize(32, 1);
t_right.resize(32, 4);
t_left = (t_left.constant(-0.5f) + t_left.random()) * 2.0f;
t_right = (t_right.constant(-0.6f) + t_right.random()) * 2.0f;
t_result.resize (1, 4);
t_result = t_result.constant(NAN);
t_result.device(thread_pool_device) = t_left.contract(t_right, dims);
new(&m_left) MapXf(t_left.data(), 32, 1);
new(&m_right) MapXf(t_right.data(), 32, 4);
m_result = m_left.transpose() * m_right;
for (ptrdiff_t i = 0; i < t_result.size(); i++) {
assert(!isnan(t_result.data()[i]));
if (fabs(t_result.data()[i] - m_result.data()[i]) >= 1e-4) {
std::cout << "mismatch detected: " << t_result.data()[i] << " vs " << m_result.data()[i] << std::endl;
assert(false);
}
}
}
static void test_multithread_contraction_agrees_with_singlethread() {
int contract_size = internal::random<int>(1, 5000);
Tensor<float, 3> left(internal::random<int>(1, 80),
contract_size,
internal::random<int>(1, 100));
Tensor<float, 4> right(internal::random<int>(1, 25),
internal::random<int>(1, 37),
contract_size,
internal::random<int>(1, 51));
left.setRandom();
right.setRandom();
// add constants to shift values away from 0 for more precision
left += left.constant(1.5f);
right += right.constant(1.5f);
typedef Tensor<float, 1>::DimensionPair DimPair;
Eigen::array<DimPair, 1> dims({{DimPair(1, 2)}});
Eigen::ThreadPoolDevice thread_pool_device(internal::random<int>(2, 11));
Tensor<float, 5> st_result;
st_result = left.contract(right, dims);
Tensor<float, 5> tp_result(st_result.dimensions());
tp_result.device(thread_pool_device) = left.contract(right, dims);
VERIFY(internal::dimensions_match(st_result.dimensions(), tp_result.dimensions()));
for (ptrdiff_t i = 0; i < st_result.size(); i++) {
// if both of the values are very small, then do nothing (because the test will fail
// due to numerical precision issues when values are small)
if (fabs(st_result.data()[i] - tp_result.data()[i]) >= 1e-4) {
VERIFY_IS_APPROX(st_result.data()[i], tp_result.data()[i]);
}
}
}
static void test_memcpy() {
for (int i = 0; i < 5; ++i) {
const int num_threads = internal::random<int>(3, 11);
Eigen::ThreadPoolDevice thread_pool_device(num_threads);
const int size = internal::random<int>(13, 7632);
Tensor<float, 1> t1(size);
t1.setRandom();
std::vector<float> result(size);
thread_pool_device.memcpy(&result[0], t1.data(), size*sizeof(float));
for (int i = 0; i < size; i++) {
VERIFY_IS_EQUAL(t1(i), result[i]);
}
}
}
void test_cxx11_tensor_thread_pool()
{
CALL_SUBTEST(test_multithread_elementwise());
CALL_SUBTEST(test_multithread_compound_assignment());
CALL_SUBTEST(test_multithread_contraction());
CALL_SUBTEST(test_multithread_contraction_agrees_with_singlethread());
// Exercise various cases that have been problematic in the past.
CALL_SUBTEST(test_contraction_corner_cases());
CALL_SUBTEST(test_memcpy());
}