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Test broadcasting on OpenCL devices with 64 bit indexing

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This commit is contained in:
Benoit Steiner 2016-11-18 13:44:20 -08:00
parent 37c2c516a6
commit b5e3285e16
1 changed files with 52 additions and 47 deletions
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99
unsupported/test/cxx11_tensor_broadcast_sycl.cpp
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@ -14,7 +14,7 @@
#define EIGEN_TEST_NO_LONGDOUBLE #define EIGEN_TEST_NO_LONGDOUBLE
#define EIGEN_TEST_NO_COMPLEX #define EIGEN_TEST_NO_COMPLEX
#define EIGEN_TEST_FUNC cxx11_tensor_broadcast_sycl #define EIGEN_TEST_FUNC cxx11_tensor_broadcast_sycl
#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int #define EIGEN_DEFAULT_DENSE_INDEX_TYPE int64_t
#define EIGEN_USE_SYCL #define EIGEN_USE_SYCL
#include "main.h" #include "main.h"
@ -25,47 +25,47 @@ using Eigen::SyclDevice;
using Eigen::Tensor; using Eigen::Tensor;
using Eigen::TensorMap; using Eigen::TensorMap;
template <typename DataType, int DataLayout> template <typename DataType, int DataLayout, typename IndexType>
static void test_broadcast_sycl_fixed(const Eigen::SyclDevice &sycl_device){ static void test_broadcast_sycl_fixed(const Eigen::SyclDevice &sycl_device){
// BROADCAST test: // BROADCAST test:
int inDim1=2; IndexType inDim1=2;
int inDim2=3; IndexType inDim2=3;
int inDim3=5; IndexType inDim3=5;
int inDim4=7; IndexType inDim4=7;
int bDim1=2; IndexType bDim1=2;
int bDim2=3; IndexType bDim2=3;
int bDim3=1; IndexType bDim3=1;
int bDim4=4; IndexType bDim4=4;
array<int, 4> in_range = {{inDim1, inDim2, inDim3, inDim4}}; array<IndexType, 4> in_range = {{inDim1, inDim2, inDim3, inDim4}};
array<int, 4> broadcasts = {{bDim1, bDim2, bDim3, bDim4}}; array<IndexType, 4> broadcasts = {{bDim1, bDim2, bDim3, bDim4}};
array<int, 4> out_range; // = in_range * broadcasts array<IndexType, 4> out_range; // = in_range * broadcasts
for (size_t i = 0; i < out_range.size(); ++i) for (size_t i = 0; i < out_range.size(); ++i)
out_range[i] = in_range[i] * broadcasts[i]; out_range[i] = in_range[i] * broadcasts[i];
Tensor<DataType, 4, DataLayout> input(in_range); Tensor<DataType, 4, DataLayout, IndexType> input(in_range);
Tensor<DataType, 4, DataLayout> out(out_range); Tensor<DataType, 4, DataLayout, IndexType> out(out_range);
for (size_t i = 0; i < in_range.size(); ++i) for (size_t i = 0; i < in_range.size(); ++i)
VERIFY_IS_EQUAL(out.dimension(i), out_range[i]); VERIFY_IS_EQUAL(out.dimension(i), out_range[i]);
for (int i = 0; i < input.size(); ++i) for (IndexType i = 0; i < input.size(); ++i)
input(i) = static_cast<DataType>(i); input(i) = static_cast<DataType>(i);
DataType * gpu_in_data = static_cast<DataType*>(sycl_device.allocate(input.dimensions().TotalSize()*sizeof(DataType))); DataType * gpu_in_data = static_cast<DataType*>(sycl_device.allocate(input.dimensions().TotalSize()*sizeof(DataType)));
DataType * gpu_out_data = static_cast<DataType*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(DataType))); DataType * gpu_out_data = static_cast<DataType*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(DataType)));
TensorMap<TensorFixedSize<DataType, Sizes<2, 3, 5, 7>, DataLayout>> gpu_in(gpu_in_data, in_range); TensorMap<TensorFixedSize<DataType, Sizes<2, 3, 5, 7>, DataLayout, IndexType>> gpu_in(gpu_in_data, in_range);
TensorMap<Tensor<DataType, 4, DataLayout>> gpu_out(gpu_out_data, out_range); TensorMap<Tensor<DataType, 4, DataLayout, IndexType>> gpu_out(gpu_out_data, out_range);
sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(DataType)); sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(DataType));
gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts); gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts);
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(DataType)); sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(DataType));
for (int i = 0; i < inDim1*bDim1; ++i) { for (IndexType i = 0; i < inDim1*bDim1; ++i) {
for (int j = 0; j < inDim2*bDim2; ++j) { for (IndexType j = 0; j < inDim2*bDim2; ++j) {
for (int k = 0; k < inDim3*bDim3; ++k) { for (IndexType k = 0; k < inDim3*bDim3; ++k) {
for (int l = 0; l < inDim4*bDim4; ++l) { for (IndexType l = 0; l < inDim4*bDim4; ++l) {
VERIFY_IS_APPROX(input(i%2,j%3,k%5,l%7), out(i,j,k,l)); VERIFY_IS_APPROX(input(i%2,j%3,k%5,l%7), out(i,j,k,l));
} }
} }
@ -76,47 +76,47 @@ static void test_broadcast_sycl_fixed(const Eigen::SyclDevice &sycl_device){
sycl_device.deallocate(gpu_out_data); sycl_device.deallocate(gpu_out_data);
} }
template <typename DataType, int DataLayout> template <typename DataType, int DataLayout, typename IndexType>
static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){ static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){
// BROADCAST test: // BROADCAST test:
int inDim1=2; IndexType inDim1=2;
int inDim2=3; IndexType inDim2=3;
int inDim3=5; IndexType inDim3=5;
int inDim4=7; IndexType inDim4=7;
int bDim1=2; IndexType bDim1=2;
int bDim2=3; IndexType bDim2=3;
int bDim3=1; IndexType bDim3=1;
int bDim4=4; IndexType bDim4=4;
array<int, 4> in_range = {{inDim1, inDim2, inDim3, inDim4}}; array<IndexType, 4> in_range = {{inDim1, inDim2, inDim3, inDim4}};
array<int, 4> broadcasts = {{bDim1, bDim2, bDim3, bDim4}}; array<IndexType, 4> broadcasts = {{bDim1, bDim2, bDim3, bDim4}};
array<int, 4> out_range; // = in_range * broadcasts array<IndexType, 4> out_range; // = in_range * broadcasts
for (size_t i = 0; i < out_range.size(); ++i) for (size_t i = 0; i < out_range.size(); ++i)
out_range[i] = in_range[i] * broadcasts[i]; out_range[i] = in_range[i] * broadcasts[i];
Tensor<DataType, 4, DataLayout> input(in_range); Tensor<DataType, 4, DataLayout, IndexType> input(in_range);
Tensor<DataType, 4, DataLayout> out(out_range); Tensor<DataType, 4, DataLayout, IndexType> out(out_range);
for (size_t i = 0; i < in_range.size(); ++i) for (size_t i = 0; i < in_range.size(); ++i)
VERIFY_IS_EQUAL(out.dimension(i), out_range[i]); VERIFY_IS_EQUAL(out.dimension(i), out_range[i]);
for (int i = 0; i < input.size(); ++i) for (IndexType i = 0; i < input.size(); ++i)
input(i) = static_cast<DataType>(i); input(i) = static_cast<DataType>(i);
DataType * gpu_in_data = static_cast<DataType*>(sycl_device.allocate(input.dimensions().TotalSize()*sizeof(DataType))); DataType * gpu_in_data = static_cast<DataType*>(sycl_device.allocate(input.dimensions().TotalSize()*sizeof(DataType)));
DataType * gpu_out_data = static_cast<DataType*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(DataType))); DataType * gpu_out_data = static_cast<DataType*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(DataType)));
TensorMap<Tensor<DataType, 4, DataLayout>> gpu_in(gpu_in_data, in_range); TensorMap<Tensor<DataType, 4, DataLayout, IndexType>> gpu_in(gpu_in_data, in_range);
TensorMap<Tensor<DataType, 4, DataLayout>> gpu_out(gpu_out_data, out_range); TensorMap<Tensor<DataType, 4, DataLayout, IndexType>> gpu_out(gpu_out_data, out_range);
sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(DataType)); sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(DataType));
gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts); gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts);
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(DataType)); sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(DataType));
for (int i = 0; i < inDim1*bDim1; ++i) { for (IndexType i = 0; i < inDim1*bDim1; ++i) {
for (int j = 0; j < inDim2*bDim2; ++j) { for (IndexType j = 0; j < inDim2*bDim2; ++j) {
for (int k = 0; k < inDim3*bDim3; ++k) { for (IndexType k = 0; k < inDim3*bDim3; ++k) {
for (int l = 0; l < inDim4*bDim4; ++l) { for (IndexType l = 0; l < inDim4*bDim4; ++l) {
VERIFY_IS_APPROX(input(i%inDim1,j%inDim2,k%inDim3,l%inDim4), out(i,j,k,l)); VERIFY_IS_APPROX(input(i%inDim1,j%inDim2,k%inDim3,l%inDim4), out(i,j,k,l));
} }
} }
@ -130,10 +130,15 @@ static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){
template<typename DataType, typename dev_Selector> void sycl_broadcast_test_per_device(dev_Selector s){ template<typename DataType, typename dev_Selector> void sycl_broadcast_test_per_device(dev_Selector s){
QueueInterface queueInterface(s); QueueInterface queueInterface(s);
auto sycl_device = Eigen::SyclDevice(&queueInterface); auto sycl_device = Eigen::SyclDevice(&queueInterface);
test_broadcast_sycl_fixed<DataType, RowMajor>(sycl_device); test_broadcast_sycl_fixed<DataType, RowMajor, int>(sycl_device);
test_broadcast_sycl<DataType, RowMajor>(sycl_device); test_broadcast_sycl<DataType, RowMajor, int>(sycl_device);
test_broadcast_sycl_fixed<DataType, ColMajor>(sycl_device); test_broadcast_sycl_fixed<DataType, ColMajor, int>(sycl_device);
test_broadcast_sycl<DataType, ColMajor>(sycl_device); test_broadcast_sycl<DataType, ColMajor, int>(sycl_device);
test_broadcast_sycl_fixed<DataType, RowMajor, int64_t>(sycl_device);
test_broadcast_sycl<DataType, RowMajor, int64_t>(sycl_device);
test_broadcast_sycl_fixed<DataType, ColMajor, int64_t>(sycl_device);
test_broadcast_sycl<DataType, ColMajor, int64_t>(sycl_device);
} }
void test_cxx11_tensor_broadcast_sycl() { void test_cxx11_tensor_broadcast_sycl() {