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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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57
unsupported/test/cxx11_tensor_layout_swap_sycl.cpp
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@@ -25,33 +25,30 @@
using Eigen::Tensor;
template <typename DataType, typename IndexType>
static void test_simple_swap_sycl(const Eigen::SyclDevice& sycl_device)
{
static void test_simple_swap_sycl(const Eigen::SyclDevice& sycl_device) {
IndexType sizeDim1 = 2;
IndexType sizeDim2 = 3;
IndexType sizeDim3 = 7;
array<IndexType, 3> tensorColRange = {{sizeDim1, sizeDim2, sizeDim3}};
array<IndexType, 3> tensorRowRange = {{sizeDim3, sizeDim2, sizeDim1}};
Tensor<DataType, 3, ColMajor, IndexType> tensor1(tensorColRange);
Tensor<DataType, 3, RowMajor, IndexType> tensor2(tensorRowRange);
tensor1.setRandom();
DataType* gpu_data1 = static_cast<DataType*>(sycl_device.allocate(tensor1.size()*sizeof(DataType)));
DataType* gpu_data2 = static_cast<DataType*>(sycl_device.allocate(tensor2.size()*sizeof(DataType)));
DataType* gpu_data1 = static_cast<DataType*>(sycl_device.allocate(tensor1.size() * sizeof(DataType)));
DataType* gpu_data2 = static_cast<DataType*>(sycl_device.allocate(tensor2.size() * sizeof(DataType)));
TensorMap<Tensor<DataType, 3, ColMajor, IndexType>> gpu1(gpu_data1, tensorColRange);
TensorMap<Tensor<DataType, 3, RowMajor, IndexType>> gpu2(gpu_data2, tensorRowRange);
sycl_device.memcpyHostToDevice(gpu_data1, tensor1.data(),(tensor1.size())*sizeof(DataType));
gpu2.device(sycl_device)=gpu1.swap_layout();
sycl_device.memcpyDeviceToHost(tensor2.data(), gpu_data2,(tensor2.size())*sizeof(DataType));
sycl_device.memcpyHostToDevice(gpu_data1, tensor1.data(), (tensor1.size()) * sizeof(DataType));
gpu2.device(sycl_device) = gpu1.swap_layout();
sycl_device.memcpyDeviceToHost(tensor2.data(), gpu_data2, (tensor2.size()) * sizeof(DataType));
// Tensor<float, 3, ColMajor> tensor(2,3,7);
// tensor.setRandom();
// Tensor<float, 3, ColMajor> tensor(2,3,7);
//tensor.setRandom();
// Tensor<float, 3, RowMajor> tensor2 = tensor.swap_layout();
// Tensor<float, 3, RowMajor> tensor2 = tensor.swap_layout();
VERIFY_IS_EQUAL(tensor1.dimension(0), tensor2.dimension(2));
VERIFY_IS_EQUAL(tensor1.dimension(1), tensor2.dimension(1));
VERIFY_IS_EQUAL(tensor1.dimension(2), tensor2.dimension(0));
@@ -59,7 +56,7 @@ static void test_simple_swap_sycl(const Eigen::SyclDevice& sycl_device)
for (IndexType i = 0; i < 2; ++i) {
for (IndexType j = 0; j < 3; ++j) {
for (IndexType k = 0; k < 7; ++k) {
VERIFY_IS_EQUAL(tensor1(i,j,k), tensor2(k,j,i));
VERIFY_IS_EQUAL(tensor1(i, j, k), tensor2(k, j, i));
}
}
}
@@ -68,9 +65,7 @@ static void test_simple_swap_sycl(const Eigen::SyclDevice& sycl_device)
}
template <typename DataType, typename IndexType>
static void test_swap_as_lvalue_sycl(const Eigen::SyclDevice& sycl_device)
{
static void test_swap_as_lvalue_sycl(const Eigen::SyclDevice& sycl_device) {
IndexType sizeDim1 = 2;
IndexType sizeDim2 = 3;
IndexType sizeDim3 = 7;
@@ -81,21 +76,20 @@ static void test_swap_as_lvalue_sycl(const Eigen::SyclDevice& sycl_device)
Tensor<DataType, 3, RowMajor, IndexType> tensor2(tensorRowRange);
tensor1.setRandom();
DataType* gpu_data1 = static_cast<DataType*>(sycl_device.allocate(tensor1.size()*sizeof(DataType)));
DataType* gpu_data2 = static_cast<DataType*>(sycl_device.allocate(tensor2.size()*sizeof(DataType)));
DataType* gpu_data1 = static_cast<DataType*>(sycl_device.allocate(tensor1.size() * sizeof(DataType)));
DataType* gpu_data2 = static_cast<DataType*>(sycl_device.allocate(tensor2.size() * sizeof(DataType)));
TensorMap<Tensor<DataType, 3, ColMajor, IndexType>> gpu1(gpu_data1, tensorColRange);
TensorMap<Tensor<DataType, 3, RowMajor, IndexType>> gpu2(gpu_data2, tensorRowRange);
sycl_device.memcpyHostToDevice(gpu_data1, tensor1.data(),(tensor1.size())*sizeof(DataType));
gpu2.swap_layout().device(sycl_device)=gpu1;
sycl_device.memcpyDeviceToHost(tensor2.data(), gpu_data2,(tensor2.size())*sizeof(DataType));
sycl_device.memcpyHostToDevice(gpu_data1, tensor1.data(), (tensor1.size()) * sizeof(DataType));
gpu2.swap_layout().device(sycl_device) = gpu1;
sycl_device.memcpyDeviceToHost(tensor2.data(), gpu_data2, (tensor2.size()) * sizeof(DataType));
// Tensor<float, 3, ColMajor> tensor(2,3,7);
// tensor.setRandom();
// Tensor<float, 3, ColMajor> tensor(2,3,7);
// tensor.setRandom();
//Tensor<float, 3, RowMajor> tensor2(7,3,2);
// tensor2.swap_layout() = tensor;
// Tensor<float, 3, RowMajor> tensor2(7,3,2);
// tensor2.swap_layout() = tensor;
VERIFY_IS_EQUAL(tensor1.dimension(0), tensor2.dimension(2));
VERIFY_IS_EQUAL(tensor1.dimension(1), tensor2.dimension(1));
VERIFY_IS_EQUAL(tensor1.dimension(2), tensor2.dimension(0));
@@ -103,7 +97,7 @@ static void test_swap_as_lvalue_sycl(const Eigen::SyclDevice& sycl_device)
for (IndexType i = 0; i < 2; ++i) {
for (IndexType j = 0; j < 3; ++j) {
for (IndexType k = 0; k < 7; ++k) {
VERIFY_IS_EQUAL(tensor1(i,j,k), tensor2(k,j,i));
VERIFY_IS_EQUAL(tensor1(i, j, k), tensor2(k, j, i));
}
}
}
@@ -111,16 +105,15 @@ static void test_swap_as_lvalue_sycl(const Eigen::SyclDevice& sycl_device)
sycl_device.deallocate(gpu_data2);
}
template<typename DataType, typename dev_Selector> void sycl_tensor_layout_swap_test_per_device(dev_Selector s){
template <typename DataType, typename dev_Selector>
void sycl_tensor_layout_swap_test_per_device(dev_Selector s) {
QueueInterface queueInterface(s);
auto sycl_device = Eigen::SyclDevice(&queueInterface);
test_simple_swap_sycl<DataType, int64_t>(sycl_device);
test_swap_as_lvalue_sycl<DataType, int64_t>(sycl_device);
}
EIGEN_DECLARE_TEST(cxx11_tensor_layout_swap_sycl)
{
for (const auto& device :Eigen::get_sycl_supported_devices()) {
EIGEN_DECLARE_TEST(cxx11_tensor_layout_swap_sycl) {
for (const auto& device : Eigen::get_sycl_supported_devices()) {
CALL_SUBTEST(sycl_tensor_layout_swap_test_per_device<half>(device));
CALL_SUBTEST(sycl_tensor_layout_swap_test_per_device<float>(device));
}