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Clang-format tests, examples, libraries, benchmarks, etc.

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This commit is contained in:
Antonio Sánchez
2023-12-05 21:22:55 +00:00
committed by Rasmus Munk Larsen
parent 3252ecc7a4
commit 46e9cdb7fe
876 changed files with 33453 additions and 37795 deletions
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105
unsupported/test/cxx11_tensor_patch_sycl.cpp
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@@ -25,8 +25,7 @@
using Eigen::Tensor;
template <typename DataType, int DataLayout, typename IndexType>
static void test_simple_patch_sycl(const Eigen::SyclDevice& sycl_device){
static void test_simple_patch_sycl(const Eigen::SyclDevice& sycl_device) {
IndexType sizeDim1 = 2;
IndexType sizeDim2 = 3;
IndexType sizeDim3 = 5;
@@ -34,13 +33,13 @@ static void test_simple_patch_sycl(const Eigen::SyclDevice& sycl_device){
array<IndexType, 4> tensorRange = {{sizeDim1, sizeDim2, sizeDim3, sizeDim4}};
array<IndexType, 5> patchTensorRange;
if (DataLayout == ColMajor) {
patchTensorRange = {{1, 1, 1, 1, sizeDim1*sizeDim2*sizeDim3*sizeDim4}};
}else{
patchTensorRange = {{sizeDim1*sizeDim2*sizeDim3*sizeDim4,1, 1, 1, 1}};
patchTensorRange = {{1, 1, 1, 1, sizeDim1 * sizeDim2 * sizeDim3 * sizeDim4}};
} else {
patchTensorRange = {{sizeDim1 * sizeDim2 * sizeDim3 * sizeDim4, 1, 1, 1, 1}};
}
Tensor<DataType, 4, DataLayout,IndexType> tensor(tensorRange);
Tensor<DataType, 5, DataLayout,IndexType> no_patch(patchTensorRange);
Tensor<DataType, 4, DataLayout, IndexType> tensor(tensorRange);
Tensor<DataType, 5, DataLayout, IndexType> no_patch(patchTensorRange);
tensor.setRandom();
@@ -50,16 +49,16 @@ static void test_simple_patch_sycl(const Eigen::SyclDevice& sycl_device){
patch_dims[2] = 1;
patch_dims[3] = 1;
const size_t tensorBuffSize =tensor.size()*sizeof(DataType);
size_t patchTensorBuffSize =no_patch.size()*sizeof(DataType);
DataType* gpu_data_tensor = static_cast<DataType*>(sycl_device.allocate(tensorBuffSize));
DataType* gpu_data_no_patch = static_cast<DataType*>(sycl_device.allocate(patchTensorBuffSize));
const size_t tensorBuffSize = tensor.size() * sizeof(DataType);
size_t patchTensorBuffSize = no_patch.size() * sizeof(DataType);
DataType* gpu_data_tensor = static_cast<DataType*>(sycl_device.allocate(tensorBuffSize));
DataType* gpu_data_no_patch = static_cast<DataType*>(sycl_device.allocate(patchTensorBuffSize));
TensorMap<Tensor<DataType, 4, DataLayout,IndexType>> gpu_tensor(gpu_data_tensor, tensorRange);
TensorMap<Tensor<DataType, 5, DataLayout,IndexType>> gpu_no_patch(gpu_data_no_patch, patchTensorRange);
TensorMap<Tensor<DataType, 4, DataLayout, IndexType>> gpu_tensor(gpu_data_tensor, tensorRange);
TensorMap<Tensor<DataType, 5, DataLayout, IndexType>> gpu_no_patch(gpu_data_no_patch, patchTensorRange);
sycl_device.memcpyHostToDevice(gpu_data_tensor, tensor.data(), tensorBuffSize);
gpu_no_patch.device(sycl_device)=gpu_tensor.extract_patches(patch_dims);
gpu_no_patch.device(sycl_device) = gpu_tensor.extract_patches(patch_dims);
sycl_device.memcpyDeviceToHost(no_patch.data(), gpu_data_no_patch, patchTensorBuffSize);
if (DataLayout == ColMajor) {
@@ -86,16 +85,16 @@ static void test_simple_patch_sycl(const Eigen::SyclDevice& sycl_device){
patch_dims[3] = 7;
if (DataLayout == ColMajor) {
patchTensorRange = {{sizeDim1,sizeDim2,sizeDim3,sizeDim4,1}};
}else{
patchTensorRange = {{1,sizeDim1,sizeDim2,sizeDim3,sizeDim4}};
patchTensorRange = {{sizeDim1, sizeDim2, sizeDim3, sizeDim4, 1}};
} else {
patchTensorRange = {{1, sizeDim1, sizeDim2, sizeDim3, sizeDim4}};
}
Tensor<DataType, 5, DataLayout,IndexType> single_patch(patchTensorRange);
patchTensorBuffSize =single_patch.size()*sizeof(DataType);
DataType* gpu_data_single_patch = static_cast<DataType*>(sycl_device.allocate(patchTensorBuffSize));
TensorMap<Tensor<DataType, 5, DataLayout,IndexType>> gpu_single_patch(gpu_data_single_patch, patchTensorRange);
Tensor<DataType, 5, DataLayout, IndexType> single_patch(patchTensorRange);
patchTensorBuffSize = single_patch.size() * sizeof(DataType);
DataType* gpu_data_single_patch = static_cast<DataType*>(sycl_device.allocate(patchTensorBuffSize));
TensorMap<Tensor<DataType, 5, DataLayout, IndexType>> gpu_single_patch(gpu_data_single_patch, patchTensorRange);
gpu_single_patch.device(sycl_device)=gpu_tensor.extract_patches(patch_dims);
gpu_single_patch.device(sycl_device) = gpu_tensor.extract_patches(patch_dims);
sycl_device.memcpyDeviceToHost(single_patch.data(), gpu_data_single_patch, patchTensorBuffSize);
if (DataLayout == ColMajor) {
@@ -119,18 +118,18 @@ static void test_simple_patch_sycl(const Eigen::SyclDevice& sycl_device){
patch_dims[1] = 2;
patch_dims[2] = 2;
patch_dims[3] = 1;
if (DataLayout == ColMajor) {
patchTensorRange = {{1,2,2,1,2*2*4*7}};
}else{
patchTensorRange = {{2*2*4*7, 1, 2,2,1}};
}
Tensor<DataType, 5, DataLayout,IndexType> twod_patch(patchTensorRange);
patchTensorBuffSize =twod_patch.size()*sizeof(DataType);
DataType* gpu_data_twod_patch = static_cast<DataType*>(sycl_device.allocate(patchTensorBuffSize));
TensorMap<Tensor<DataType, 5, DataLayout,IndexType>> gpu_twod_patch(gpu_data_twod_patch, patchTensorRange);
gpu_twod_patch.device(sycl_device)=gpu_tensor.extract_patches(patch_dims);
if (DataLayout == ColMajor) {
patchTensorRange = {{1, 2, 2, 1, 2 * 2 * 4 * 7}};
} else {
patchTensorRange = {{2 * 2 * 4 * 7, 1, 2, 2, 1}};
}
Tensor<DataType, 5, DataLayout, IndexType> twod_patch(patchTensorRange);
patchTensorBuffSize = twod_patch.size() * sizeof(DataType);
DataType* gpu_data_twod_patch = static_cast<DataType*>(sycl_device.allocate(patchTensorBuffSize));
TensorMap<Tensor<DataType, 5, DataLayout, IndexType>> gpu_twod_patch(gpu_data_twod_patch, patchTensorRange);
gpu_twod_patch.device(sycl_device) = gpu_tensor.extract_patches(patch_dims);
sycl_device.memcpyDeviceToHost(twod_patch.data(), gpu_data_twod_patch, patchTensorBuffSize);
if (DataLayout == ColMajor) {
@@ -138,9 +137,9 @@ static void test_simple_patch_sycl(const Eigen::SyclDevice& sycl_device){
VERIFY_IS_EQUAL(twod_patch.dimension(1), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(2), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(3), 1);
VERIFY_IS_EQUAL(twod_patch.dimension(4), 2*2*4*7);
VERIFY_IS_EQUAL(twod_patch.dimension(4), 2 * 2 * 4 * 7);
} else {
VERIFY_IS_EQUAL(twod_patch.dimension(0), 2*2*4*7);
VERIFY_IS_EQUAL(twod_patch.dimension(0), 2 * 2 * 4 * 7);
VERIFY_IS_EQUAL(twod_patch.dimension(1), 1);
VERIFY_IS_EQUAL(twod_patch.dimension(2), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(3), 2);
@@ -160,9 +159,9 @@ static void test_simple_patch_sycl(const Eigen::SyclDevice& sycl_device){
for (int x = 0; x < 2; ++x) {
for (int y = 0; y < 2; ++y) {
if (DataLayout == ColMajor) {
VERIFY_IS_EQUAL(tensor(i,j+x,k+y,l), twod_patch(0,x,y,0,patch_loc));
VERIFY_IS_EQUAL(tensor(i, j + x, k + y, l), twod_patch(0, x, y, 0, patch_loc));
} else {
VERIFY_IS_EQUAL(tensor(i,j+x,k+y,l), twod_patch(patch_loc,0,x,y,0));
VERIFY_IS_EQUAL(tensor(i, j + x, k + y, l), twod_patch(patch_loc, 0, x, y, 0));
}
}
}
@@ -177,16 +176,16 @@ static void test_simple_patch_sycl(const Eigen::SyclDevice& sycl_device){
patch_dims[3] = 5;
if (DataLayout == ColMajor) {
patchTensorRange = {{1,2,3,5,2*2*3*3}};
}else{
patchTensorRange = {{2*2*3*3, 1, 2,3,5}};
patchTensorRange = {{1, 2, 3, 5, 2 * 2 * 3 * 3}};
} else {
patchTensorRange = {{2 * 2 * 3 * 3, 1, 2, 3, 5}};
}
Tensor<DataType, 5, DataLayout,IndexType> threed_patch(patchTensorRange);
patchTensorBuffSize =threed_patch.size()*sizeof(DataType);
DataType* gpu_data_threed_patch = static_cast<DataType*>(sycl_device.allocate(patchTensorBuffSize));
TensorMap<Tensor<DataType, 5, DataLayout,IndexType>> gpu_threed_patch(gpu_data_threed_patch, patchTensorRange);
Tensor<DataType, 5, DataLayout, IndexType> threed_patch(patchTensorRange);
patchTensorBuffSize = threed_patch.size() * sizeof(DataType);
DataType* gpu_data_threed_patch = static_cast<DataType*>(sycl_device.allocate(patchTensorBuffSize));
TensorMap<Tensor<DataType, 5, DataLayout, IndexType>> gpu_threed_patch(gpu_data_threed_patch, patchTensorRange);
gpu_threed_patch.device(sycl_device)=gpu_tensor.extract_patches(patch_dims);
gpu_threed_patch.device(sycl_device) = gpu_tensor.extract_patches(patch_dims);
sycl_device.memcpyDeviceToHost(threed_patch.data(), gpu_data_threed_patch, patchTensorBuffSize);
if (DataLayout == ColMajor) {
@@ -194,9 +193,9 @@ static void test_simple_patch_sycl(const Eigen::SyclDevice& sycl_device){
VERIFY_IS_EQUAL(threed_patch.dimension(1), 2);
VERIFY_IS_EQUAL(threed_patch.dimension(2), 3);
VERIFY_IS_EQUAL(threed_patch.dimension(3), 5);
VERIFY_IS_EQUAL(threed_patch.dimension(4), 2*2*3*3);
VERIFY_IS_EQUAL(threed_patch.dimension(4), 2 * 2 * 3 * 3);
} else {
VERIFY_IS_EQUAL(threed_patch.dimension(0), 2*2*3*3);
VERIFY_IS_EQUAL(threed_patch.dimension(0), 2 * 2 * 3 * 3);
VERIFY_IS_EQUAL(threed_patch.dimension(1), 1);
VERIFY_IS_EQUAL(threed_patch.dimension(2), 2);
VERIFY_IS_EQUAL(threed_patch.dimension(3), 3);
@@ -217,9 +216,9 @@ static void test_simple_patch_sycl(const Eigen::SyclDevice& sycl_device){
for (int y = 0; y < 3; ++y) {
for (int z = 0; z < 5; ++z) {
if (DataLayout == ColMajor) {
VERIFY_IS_EQUAL(tensor(i,j+x,k+y,l+z), threed_patch(0,x,y,z,patch_loc));
VERIFY_IS_EQUAL(tensor(i, j + x, k + y, l + z), threed_patch(0, x, y, z, patch_loc));
} else {
VERIFY_IS_EQUAL(tensor(i,j+x,k+y,l+z), threed_patch(patch_loc,0,x,y,z));
VERIFY_IS_EQUAL(tensor(i, j + x, k + y, l + z), threed_patch(patch_loc, 0, x, y, z));
}
}
}
@@ -235,15 +234,15 @@ static void test_simple_patch_sycl(const Eigen::SyclDevice& sycl_device){
sycl_device.deallocate(gpu_data_threed_patch);
}
template<typename DataType, typename dev_Selector> void sycl_tensor_patch_test_per_device(dev_Selector s){
template <typename DataType, typename dev_Selector>
void sycl_tensor_patch_test_per_device(dev_Selector s) {
QueueInterface queueInterface(s);
auto sycl_device = Eigen::SyclDevice(&queueInterface);
test_simple_patch_sycl<DataType, RowMajor, int64_t>(sycl_device);
test_simple_patch_sycl<DataType, ColMajor, int64_t>(sycl_device);
}
EIGEN_DECLARE_TEST(cxx11_tensor_patch_sycl)
{
for (const auto& device :Eigen::get_sycl_supported_devices()) {
EIGEN_DECLARE_TEST(cxx11_tensor_patch_sycl) {
for (const auto& device : Eigen::get_sycl_supported_devices()) {
CALL_SUBTEST(sycl_tensor_patch_test_per_device<half>(device));
CALL_SUBTEST(sycl_tensor_patch_test_per_device<float>(device));
}