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Reducing warnings in Sycl backend.

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This commit is contained in:
Mehdi Goli
2017-02-01 15:29:53 +00:00
parent 48a20b7d95
commit bab29936a1
19 changed files with 666 additions and 672 deletions
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106
unsupported/test/cxx11_tensor_concatenation_sycl.cpp
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@@ -14,7 +14,7 @@
#define EIGEN_TEST_NO_LONGDOUBLE
#define EIGEN_TEST_NO_COMPLEX
#define EIGEN_TEST_FUNC cxx11_tensor_concatenation_sycl
#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int64_t
#define EIGEN_USE_SYCL
#include "main.h"
@@ -22,39 +22,39 @@
using Eigen::Tensor;
template<typename DataType, int DataLayout, typename Index>
template<typename DataType, int DataLayout, typename IndexType>
static void test_simple_concatenation(const Eigen::SyclDevice& sycl_device)
{
Index leftDim1 = 2;
Index leftDim2 = 3;
Index leftDim3 = 1;
Eigen::array<Index, 3> leftRange = {{leftDim1, leftDim2, leftDim3}};
Index rightDim1 = 2;
Index rightDim2 = 3;
Index rightDim3 = 1;
Eigen::array<Index, 3> rightRange = {{rightDim1, rightDim2, rightDim3}};
IndexType leftDim1 = 2;
IndexType leftDim2 = 3;
IndexType leftDim3 = 1;
Eigen::array<IndexType, 3> leftRange = {{leftDim1, leftDim2, leftDim3}};
IndexType rightDim1 = 2;
IndexType rightDim2 = 3;
IndexType rightDim3 = 1;
Eigen::array<IndexType, 3> rightRange = {{rightDim1, rightDim2, rightDim3}};
//Index concatDim1 = 3;
// Index concatDim2 = 3;
// Index concatDim3 = 1;
//Eigen::array<Index, 3> concatRange = {{concatDim1, concatDim2, concatDim3}};
//IndexType concatDim1 = 3;
// IndexType concatDim2 = 3;
// IndexType concatDim3 = 1;
//Eigen::array<IndexType, 3> concatRange = {{concatDim1, concatDim2, concatDim3}};
Tensor<DataType, 3, DataLayout, Index> left(leftRange);
Tensor<DataType, 3, DataLayout, Index> right(rightRange);
Tensor<DataType, 3, DataLayout, IndexType> left(leftRange);
Tensor<DataType, 3, DataLayout, IndexType> right(rightRange);
left.setRandom();
right.setRandom();
DataType * gpu_in1_data = static_cast<DataType*>(sycl_device.allocate(left.dimensions().TotalSize()*sizeof(DataType)));
DataType * gpu_in2_data = static_cast<DataType*>(sycl_device.allocate(right.dimensions().TotalSize()*sizeof(DataType)));
Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, Index>> gpu_in1(gpu_in1_data, leftRange);
Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, Index>> gpu_in2(gpu_in2_data, rightRange);
Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, IndexType>> gpu_in1(gpu_in1_data, leftRange);
Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, IndexType>> gpu_in2(gpu_in2_data, rightRange);
sycl_device.memcpyHostToDevice(gpu_in1_data, left.data(),(left.dimensions().TotalSize())*sizeof(DataType));
sycl_device.memcpyHostToDevice(gpu_in2_data, right.data(),(right.dimensions().TotalSize())*sizeof(DataType));
///
Tensor<DataType, 3, DataLayout, Index> concatenation1(leftDim1+rightDim1, leftDim2, leftDim3);
Tensor<DataType, 3, DataLayout, IndexType> concatenation1(leftDim1+rightDim1, leftDim2, leftDim3);
DataType * gpu_out_data1 = static_cast<DataType*>(sycl_device.allocate(concatenation1.dimensions().TotalSize()*sizeof(DataType)));
Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, Index>> gpu_out1(gpu_out_data1, concatenation1.dimensions());
Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, IndexType>> gpu_out1(gpu_out_data1, concatenation1.dimensions());
//concatenation = left.concatenate(right, 0);
gpu_out1.device(sycl_device) =gpu_in1.concatenate(gpu_in2, 0);
@@ -63,19 +63,19 @@ static void test_simple_concatenation(const Eigen::SyclDevice& sycl_device)
VERIFY_IS_EQUAL(concatenation1.dimension(0), 4);
VERIFY_IS_EQUAL(concatenation1.dimension(1), 3);
VERIFY_IS_EQUAL(concatenation1.dimension(2), 1);
for (int j = 0; j < 3; ++j) {
for (int i = 0; i < 2; ++i) {
for (IndexType j = 0; j < 3; ++j) {
for (IndexType i = 0; i < 2; ++i) {
VERIFY_IS_EQUAL(concatenation1(i, j, 0), left(i, j, 0));
}
for (int i = 2; i < 4; ++i) {
for (IndexType i = 2; i < 4; ++i) {
VERIFY_IS_EQUAL(concatenation1(i, j, 0), right(i - 2, j, 0));
}
}
sycl_device.deallocate(gpu_out_data1);
Tensor<DataType, 3, DataLayout, Index> concatenation2(leftDim1, leftDim2 +rightDim2, leftDim3);
Tensor<DataType, 3, DataLayout, IndexType> concatenation2(leftDim1, leftDim2 +rightDim2, leftDim3);
DataType * gpu_out_data2 = static_cast<DataType*>(sycl_device.allocate(concatenation2.dimensions().TotalSize()*sizeof(DataType)));
Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, Index>> gpu_out2(gpu_out_data2, concatenation2.dimensions());
Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, IndexType>> gpu_out2(gpu_out_data2, concatenation2.dimensions());
gpu_out2.device(sycl_device) =gpu_in1.concatenate(gpu_in2, 1);
sycl_device.memcpyDeviceToHost(concatenation2.data(), gpu_out_data2,(concatenation2.dimensions().TotalSize())*sizeof(DataType));
@@ -83,18 +83,18 @@ static void test_simple_concatenation(const Eigen::SyclDevice& sycl_device)
VERIFY_IS_EQUAL(concatenation2.dimension(0), 2);
VERIFY_IS_EQUAL(concatenation2.dimension(1), 6);
VERIFY_IS_EQUAL(concatenation2.dimension(2), 1);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (IndexType i = 0; i < 2; ++i) {
for (IndexType j = 0; j < 3; ++j) {
VERIFY_IS_EQUAL(concatenation2(i, j, 0), left(i, j, 0));
}
for (int j = 3; j < 6; ++j) {
for (IndexType j = 3; j < 6; ++j) {
VERIFY_IS_EQUAL(concatenation2(i, j, 0), right(i, j - 3, 0));
}
}
sycl_device.deallocate(gpu_out_data2);
Tensor<DataType, 3, DataLayout, Index> concatenation3(leftDim1, leftDim2, leftDim3+rightDim3);
Tensor<DataType, 3, DataLayout, IndexType> concatenation3(leftDim1, leftDim2, leftDim3+rightDim3);
DataType * gpu_out_data3 = static_cast<DataType*>(sycl_device.allocate(concatenation3.dimensions().TotalSize()*sizeof(DataType)));
Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, Index>> gpu_out3(gpu_out_data3, concatenation3.dimensions());
Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, IndexType>> gpu_out3(gpu_out_data3, concatenation3.dimensions());
gpu_out3.device(sycl_device) =gpu_in1.concatenate(gpu_in2, 2);
sycl_device.memcpyDeviceToHost(concatenation3.data(), gpu_out_data3,(concatenation3.dimensions().TotalSize())*sizeof(DataType));
@@ -102,8 +102,8 @@ static void test_simple_concatenation(const Eigen::SyclDevice& sycl_device)
VERIFY_IS_EQUAL(concatenation3.dimension(0), 2);
VERIFY_IS_EQUAL(concatenation3.dimension(1), 3);
VERIFY_IS_EQUAL(concatenation3.dimension(2), 2);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (IndexType i = 0; i < 2; ++i) {
for (IndexType j = 0; j < 3; ++j) {
VERIFY_IS_EQUAL(concatenation3(i, j, 0), left(i, j, 0));
VERIFY_IS_EQUAL(concatenation3(i, j, 1), right(i, j, 0));
}
@@ -112,25 +112,25 @@ static void test_simple_concatenation(const Eigen::SyclDevice& sycl_device)
sycl_device.deallocate(gpu_in1_data);
sycl_device.deallocate(gpu_in2_data);
}
template<typename DataType, int DataLayout, typename Index>
template<typename DataType, int DataLayout, typename IndexType>
static void test_concatenation_as_lvalue(const Eigen::SyclDevice& sycl_device)
{
Index leftDim1 = 2;
Index leftDim2 = 3;
Eigen::array<Index, 2> leftRange = {{leftDim1, leftDim2}};
IndexType leftDim1 = 2;
IndexType leftDim2 = 3;
Eigen::array<IndexType, 2> leftRange = {{leftDim1, leftDim2}};
Index rightDim1 = 2;
Index rightDim2 = 3;
Eigen::array<Index, 2> rightRange = {{rightDim1, rightDim2}};
IndexType rightDim1 = 2;
IndexType rightDim2 = 3;
Eigen::array<IndexType, 2> rightRange = {{rightDim1, rightDim2}};
Index concatDim1 = 4;
Index concatDim2 = 3;
Eigen::array<Index, 2> resRange = {{concatDim1, concatDim2}};
IndexType concatDim1 = 4;
IndexType concatDim2 = 3;
Eigen::array<IndexType, 2> resRange = {{concatDim1, concatDim2}};
Tensor<DataType, 2, DataLayout, Index> left(leftRange);
Tensor<DataType, 2, DataLayout, Index> right(rightRange);
Tensor<DataType, 2, DataLayout, Index> result(resRange);
Tensor<DataType, 2, DataLayout, IndexType> left(leftRange);
Tensor<DataType, 2, DataLayout, IndexType> right(rightRange);
Tensor<DataType, 2, DataLayout, IndexType> result(resRange);
left.setRandom();
right.setRandom();
@@ -141,9 +141,9 @@ static void test_concatenation_as_lvalue(const Eigen::SyclDevice& sycl_device)
DataType * gpu_out_data = static_cast<DataType*>(sycl_device.allocate(result.dimensions().TotalSize()*sizeof(DataType)));
Eigen::TensorMap<Eigen::Tensor<DataType, 2, DataLayout, Index>> gpu_in1(gpu_in1_data, leftRange);
Eigen::TensorMap<Eigen::Tensor<DataType, 2, DataLayout, Index>> gpu_in2(gpu_in2_data, rightRange);
Eigen::TensorMap<Eigen::Tensor<DataType, 2, DataLayout, Index>> gpu_out(gpu_out_data, resRange);
Eigen::TensorMap<Eigen::Tensor<DataType, 2, DataLayout, IndexType>> gpu_in1(gpu_in1_data, leftRange);
Eigen::TensorMap<Eigen::Tensor<DataType, 2, DataLayout, IndexType>> gpu_in2(gpu_in2_data, rightRange);
Eigen::TensorMap<Eigen::Tensor<DataType, 2, DataLayout, IndexType>> gpu_out(gpu_out_data, resRange);
sycl_device.memcpyHostToDevice(gpu_in1_data, left.data(),(left.dimensions().TotalSize())*sizeof(DataType));
sycl_device.memcpyHostToDevice(gpu_in2_data, right.data(),(right.dimensions().TotalSize())*sizeof(DataType));
@@ -154,8 +154,8 @@ static void test_concatenation_as_lvalue(const Eigen::SyclDevice& sycl_device)
sycl_device.memcpyDeviceToHost(left.data(), gpu_in1_data,(left.dimensions().TotalSize())*sizeof(DataType));
sycl_device.memcpyDeviceToHost(right.data(), gpu_in2_data,(right.dimensions().TotalSize())*sizeof(DataType));
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (IndexType i = 0; i < 2; ++i) {
for (IndexType j = 0; j < 3; ++j) {
VERIFY_IS_EQUAL(left(i, j), result(i, j));
VERIFY_IS_EQUAL(right(i, j), result(i+2, j));
}
@@ -169,9 +169,9 @@ static void test_concatenation_as_lvalue(const Eigen::SyclDevice& sycl_device)
template <typename DataType, typename Dev_selector> void tensorConcat_perDevice(Dev_selector s){
QueueInterface queueInterface(s);
auto sycl_device = Eigen::SyclDevice(&queueInterface);
test_simple_concatenation<DataType, RowMajor, int>(sycl_device);
test_simple_concatenation<DataType, ColMajor, int>(sycl_device);
test_concatenation_as_lvalue<DataType, ColMajor, int>(sycl_device);
test_simple_concatenation<DataType, RowMajor, int64_t>(sycl_device);
test_simple_concatenation<DataType, ColMajor, int64_t>(sycl_device);
test_concatenation_as_lvalue<DataType, ColMajor, int64_t>(sycl_device);
}
void test_cxx11_tensor_concatenation_sycl() {
for (const auto& device :Eigen::get_sycl_supported_devices()) {