diff options
Diffstat (limited to 'unsupported/test/cxx11_tensor_morphing_sycl.cpp')
-rw-r--r-- | unsupported/test/cxx11_tensor_morphing_sycl.cpp | 114 |
1 files changed, 112 insertions, 2 deletions
diff --git a/unsupported/test/cxx11_tensor_morphing_sycl.cpp b/unsupported/test/cxx11_tensor_morphing_sycl.cpp index 9074c8331..d7f4e8cff 100644 --- a/unsupported/test/cxx11_tensor_morphing_sycl.cpp +++ b/unsupported/test/cxx11_tensor_morphing_sycl.cpp @@ -29,6 +29,112 @@ using Eigen::Tensor; using Eigen::TensorMap; template <typename DataType, int DataLayout> +static void test_simple_reshape(const Eigen::SyclDevice& sycl_device) +{ + typename Tensor<DataType, 5 ,DataLayout>::Dimensions dim1(2,3,1,7,1); + typename Tensor<DataType, 3 ,DataLayout>::Dimensions dim2(2,3,7); + typename Tensor<DataType, 2 ,DataLayout>::Dimensions dim3(6,7); + typename Tensor<DataType, 2 ,DataLayout>::Dimensions dim4(2,21); + + Tensor<DataType, 5, DataLayout> tensor1(dim1); + Tensor<DataType, 3, DataLayout> tensor2(dim2); + Tensor<DataType, 2, DataLayout> tensor3(dim3); + Tensor<DataType, 2, DataLayout> tensor4(dim4); + + 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_data3 = static_cast<DataType*>(sycl_device.allocate(tensor3.size()*sizeof(DataType))); + DataType* gpu_data4 = static_cast<DataType*>(sycl_device.allocate(tensor4.size()*sizeof(DataType))); + + TensorMap<Tensor<DataType, 5,DataLayout>> gpu1(gpu_data1, dim1); + TensorMap<Tensor<DataType, 3,DataLayout>> gpu2(gpu_data2, dim2); + TensorMap<Tensor<DataType, 2,DataLayout>> gpu3(gpu_data3, dim3); + TensorMap<Tensor<DataType, 2,DataLayout>> gpu4(gpu_data4, dim4); + + sycl_device.memcpyHostToDevice(gpu_data1, tensor1.data(),(tensor1.size())*sizeof(DataType)); + + gpu2.device(sycl_device)=gpu1.reshape(dim2); + sycl_device.memcpyDeviceToHost(tensor2.data(), gpu_data2,(tensor1.size())*sizeof(DataType)); + + gpu3.device(sycl_device)=gpu1.reshape(dim3); + sycl_device.memcpyDeviceToHost(tensor3.data(), gpu_data3,(tensor3.size())*sizeof(DataType)); + + gpu4.device(sycl_device)=gpu1.reshape(dim2).reshape(dim4); + sycl_device.memcpyDeviceToHost(tensor4.data(), gpu_data4,(tensor4.size())*sizeof(DataType)); + for (int i = 0; i < 2; ++i){ + for (int j = 0; j < 3; ++j){ + for (int k = 0; k < 7; ++k){ + VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor2(i,j,k)); ///ColMajor + if (static_cast<int>(DataLayout) == static_cast<int>(ColMajor)) { + VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor3(i+2*j,k)); ///ColMajor + VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor4(i,j+3*k)); ///ColMajor + } + else{ + //VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor2(i,j,k)); /// RowMajor + VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor4(i,j*7 +k)); /// RowMajor + VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor3(i*3 +j,k)); /// RowMajor + } + } + } + } + sycl_device.deallocate(gpu_data1); + sycl_device.deallocate(gpu_data2); + sycl_device.deallocate(gpu_data3); + sycl_device.deallocate(gpu_data4); +} + + +template<typename DataType, int DataLayout> +static void test_reshape_as_lvalue(const Eigen::SyclDevice& sycl_device) +{ + typename Tensor<DataType, 3, DataLayout>::Dimensions dim1(2,3,7); + typename Tensor<DataType, 2, DataLayout>::Dimensions dim2(6,7); + typename Tensor<DataType, 5, DataLayout>::Dimensions dim3(2,3,1,7,1); + Tensor<DataType, 3, DataLayout> tensor(dim1); + Tensor<DataType, 2, DataLayout> tensor2d(dim2); + Tensor<DataType, 5, DataLayout> tensor5d(dim3); + + tensor.setRandom(); + + DataType* gpu_data1 = static_cast<DataType*>(sycl_device.allocate(tensor.size()*sizeof(DataType))); + DataType* gpu_data2 = static_cast<DataType*>(sycl_device.allocate(tensor2d.size()*sizeof(DataType))); + DataType* gpu_data3 = static_cast<DataType*>(sycl_device.allocate(tensor5d.size()*sizeof(DataType))); + + TensorMap< Tensor<DataType, 3, DataLayout> > gpu1(gpu_data1, dim1); + TensorMap< Tensor<DataType, 2, DataLayout> > gpu2(gpu_data2, dim2); + TensorMap< Tensor<DataType, 5, DataLayout> > gpu3(gpu_data3, dim3); + + sycl_device.memcpyHostToDevice(gpu_data1, tensor.data(),(tensor.size())*sizeof(DataType)); + + gpu2.reshape(dim1).device(sycl_device)=gpu1; + sycl_device.memcpyDeviceToHost(tensor2d.data(), gpu_data2,(tensor2d.size())*sizeof(DataType)); + + gpu3.reshape(dim1).device(sycl_device)=gpu1; + sycl_device.memcpyDeviceToHost(tensor5d.data(), gpu_data3,(tensor5d.size())*sizeof(DataType)); + + + for (int i = 0; i < 2; ++i){ + for (int j = 0; j < 3; ++j){ + for (int k = 0; k < 7; ++k){ + VERIFY_IS_EQUAL(tensor5d(i,j,0,k,0), tensor(i,j,k)); + if (static_cast<int>(DataLayout) == static_cast<int>(ColMajor)) { + VERIFY_IS_EQUAL(tensor2d(i+2*j,k), tensor(i,j,k)); ///ColMajor + } + else{ + VERIFY_IS_EQUAL(tensor2d(i*3 +j,k),tensor(i,j,k)); /// RowMajor + } + } + } + } + sycl_device.deallocate(gpu_data1); + sycl_device.deallocate(gpu_data2); + sycl_device.deallocate(gpu_data3); +} + + +template <typename DataType, int DataLayout> static void test_simple_slice(const Eigen::SyclDevice &sycl_device) { int sizeDim1 = 2; @@ -74,15 +180,19 @@ static void test_simple_slice(const Eigen::SyclDevice &sycl_device) sycl_device.deallocate(gpu_data3); } -template<typename DataType, typename dev_Selector> void sycl_slicing_test_per_device(dev_Selector s){ +template<typename DataType, typename dev_Selector> void sycl_morphing_test_per_device(dev_Selector s){ QueueInterface queueInterface(s); auto sycl_device = Eigen::SyclDevice(&queueInterface); test_simple_slice<DataType, RowMajor>(sycl_device); test_simple_slice<DataType, ColMajor>(sycl_device); + test_simple_reshape<DataType, RowMajor>(sycl_device); + test_simple_reshape<DataType, ColMajor>(sycl_device); + test_reshape_as_lvalue<DataType, RowMajor>(sycl_device); + test_reshape_as_lvalue<DataType, ColMajor>(sycl_device); } void test_cxx11_tensor_morphing_sycl() { for (const auto& device :Eigen::get_sycl_supported_devices()) { - CALL_SUBTEST(sycl_slicing_test_per_device<float>(device)); + CALL_SUBTEST(sycl_morphing_test_per_device<float>(device)); } } |