aboutsummaryrefslogtreecommitdiff
path: root/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
diff options
context:
space:
mode:
Diffstat (limited to 'unsupported/test/cxx11_tensor_broadcast_sycl.cpp')
-rw-r--r--unsupported/test/cxx11_tensor_broadcast_sycl.cpp118
1 files changed, 94 insertions, 24 deletions
diff --git a/unsupported/test/cxx11_tensor_broadcast_sycl.cpp b/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
index 7201bfe37..20f84b8e0 100644
--- a/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
+++ b/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
@@ -13,8 +13,8 @@
#define EIGEN_TEST_NO_LONGDOUBLE
#define EIGEN_TEST_NO_COMPLEX
-#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
#include "main.h"
@@ -25,50 +25,120 @@ using Eigen::SyclDevice;
using Eigen::Tensor;
using Eigen::TensorMap;
-static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){
+template <typename DataType, int DataLayout, typename IndexType>
+static void test_broadcast_sycl_fixed(const Eigen::SyclDevice &sycl_device){
// BROADCAST test:
- array<int, 4> in_range = {{2, 3, 5, 7}};
- array<int, 4> broadcasts = {{2, 3, 1, 4}};
- array<int, 4> out_range; // = in_range * broadcasts
+ IndexType inDim1=2;
+ IndexType inDim2=3;
+ IndexType inDim3=5;
+ IndexType inDim4=7;
+ IndexType bDim1=2;
+ IndexType bDim2=3;
+ IndexType bDim3=1;
+ IndexType bDim4=4;
+ array<IndexType, 4> in_range = {{inDim1, inDim2, inDim3, inDim4}};
+ array<IndexType, 4> broadcasts = {{bDim1, bDim2, bDim3, bDim4}};
+ array<IndexType, 4> out_range; // = in_range * broadcasts
for (size_t i = 0; i < out_range.size(); ++i)
out_range[i] = in_range[i] * broadcasts[i];
- Tensor<float, 4> input(in_range);
- Tensor<float, 4> out(out_range);
+ Tensor<DataType, 4, DataLayout, IndexType> input(in_range);
+ Tensor<DataType, 4, DataLayout, IndexType> out(out_range);
for (size_t i = 0; i < in_range.size(); ++i)
VERIFY_IS_EQUAL(out.dimension(i), out_range[i]);
- for (int i = 0; i < input.size(); ++i)
- input(i) = static_cast<float>(i);
+ for (IndexType i = 0; i < input.size(); ++i)
+ input(i) = static_cast<DataType>(i);
- float * gpu_in_data = static_cast<float*>(sycl_device.allocate(input.dimensions().TotalSize()*sizeof(float)));
- float * gpu_out_data = static_cast<float*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(float)));
+ 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)));
- TensorMap<Tensor<float, 4>> gpu_in(gpu_in_data, in_range);
- TensorMap<Tensor<float, 4>> gpu_out(gpu_out_data, out_range);
- sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(float));
+ TensorMap<TensorFixedSize<DataType, Sizes<2, 3, 5, 7>, DataLayout, IndexType>> gpu_in(gpu_in_data, in_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));
gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts);
- sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
+ sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(DataType));
- for (int i = 0; i < 4; ++i) {
- for (int j = 0; j < 9; ++j) {
- for (int k = 0; k < 5; ++k) {
- for (int l = 0; l < 28; ++l) {
+ for (IndexType i = 0; i < inDim1*bDim1; ++i) {
+ for (IndexType j = 0; j < inDim2*bDim2; ++j) {
+ for (IndexType k = 0; k < inDim3*bDim3; ++k) {
+ 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));
}
}
}
}
+ printf("Broadcast Test with fixed size Passed\n");
+ sycl_device.deallocate(gpu_in_data);
+ sycl_device.deallocate(gpu_out_data);
+}
+
+template <typename DataType, int DataLayout, typename IndexType>
+static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){
+
+ // BROADCAST test:
+ IndexType inDim1=2;
+ IndexType inDim2=3;
+ IndexType inDim3=5;
+ IndexType inDim4=7;
+ IndexType bDim1=2;
+ IndexType bDim2=3;
+ IndexType bDim3=1;
+ IndexType bDim4=4;
+ array<IndexType, 4> in_range = {{inDim1, inDim2, inDim3, inDim4}};
+ array<IndexType, 4> broadcasts = {{bDim1, bDim2, bDim3, bDim4}};
+ array<IndexType, 4> out_range; // = in_range * broadcasts
+ for (size_t i = 0; i < out_range.size(); ++i)
+ out_range[i] = in_range[i] * broadcasts[i];
+
+ Tensor<DataType, 4, DataLayout, IndexType> input(in_range);
+ Tensor<DataType, 4, DataLayout, IndexType> out(out_range);
+
+ for (size_t i = 0; i < in_range.size(); ++i)
+ VERIFY_IS_EQUAL(out.dimension(i), out_range[i]);
+
+
+ for (IndexType i = 0; i < input.size(); ++i)
+ input(i) = static_cast<DataType>(i);
+
+ 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)));
+
+ TensorMap<Tensor<DataType, 4, DataLayout, IndexType>> gpu_in(gpu_in_data, in_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));
+ gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts);
+ sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(DataType));
+
+ for (IndexType i = 0; i < inDim1*bDim1; ++i) {
+ for (IndexType j = 0; j < inDim2*bDim2; ++j) {
+ for (IndexType k = 0; k < inDim3*bDim3; ++k) {
+ 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));
+ }
+ }
+ }
+ }
printf("Broadcast Test Passed\n");
sycl_device.deallocate(gpu_in_data);
sycl_device.deallocate(gpu_out_data);
}
-void test_cxx11_tensor_broadcast_sycl() {
- cl::sycl::gpu_selector s;
- Eigen::SyclDevice sycl_device(s);
- CALL_SUBTEST(test_broadcast_sycl(sycl_device));
+template<typename DataType> void sycl_broadcast_test_per_device(const cl::sycl::device& d){
+ std::cout << "Running on " << d.template get_info<cl::sycl::info::device::name>() << std::endl;
+ QueueInterface queueInterface(d);
+ auto sycl_device = Eigen::SyclDevice(&queueInterface);
+ test_broadcast_sycl<DataType, RowMajor, int64_t>(sycl_device);
+ test_broadcast_sycl<DataType, ColMajor, int64_t>(sycl_device);
+ test_broadcast_sycl_fixed<DataType, RowMajor, int64_t>(sycl_device);
+ test_broadcast_sycl_fixed<DataType, ColMajor, int64_t>(sycl_device);
+}
+
+EIGEN_DECLARE_TEST(cxx11_tensor_broadcast_sycl) {
+ for (const auto& device :Eigen::get_sycl_supported_devices()) {
+ CALL_SUBTEST(sycl_broadcast_test_per_device<float>(device));
+ }
}
generated by cgit v1.2.3 (git 2.25.1) at 2024-05-10 05:43:50 +0000