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Adding sycl backend for TensorPadding.h; disbaling __unit128 for sycl in TensorIntDiv.h; disabling cashsize for sycl in tensorDeviceDefault.h; adding sycl backend for StrideSliceOP ; removing sycl compiler warning for creating an array of size 0 in CXX11Meta.h; cleaning up the sycl backend code.

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This commit is contained in:
Mehdi Goli
2016-12-01 13:02:27 +00:00
parent a70393fd02
commit 79aa2b784e
17 changed files with 506 additions and 81 deletions
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49
unsupported/test/cxx11_tensor_morphing_sycl.cpp
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@@ -180,6 +180,53 @@ static void test_simple_slice(const Eigen::SyclDevice &sycl_device)
sycl_device.deallocate(gpu_data3);
}
template<typename DataType, int DataLayout, typename IndexType>
static void test_strided_slice_write_sycl(const Eigen::SyclDevice& sycl_device)
{
typedef Tensor<DataType, 2, DataLayout, IndexType> Tensor2f;
typedef Eigen::DSizes<IndexType, 2> Index2;
IndexType sizeDim1 = 7L;
IndexType sizeDim2 = 11L;
array<IndexType, 2> tensorRange = {{sizeDim1, sizeDim2}};
Tensor<DataType, 2, DataLayout, IndexType> tensor(tensorRange),tensor2(tensorRange);
IndexType sliceDim1 = 2;
IndexType sliceDim2 = 3;
array<IndexType, 2> sliceRange = {{sliceDim1, sliceDim2}};
Tensor2f slice(sliceRange);
Index2 strides(1L,1L);
Index2 indicesStart(3L,4L);
Index2 indicesStop(5L,7L);
Index2 lengths(2L,3L);
DataType* gpu_data1 = static_cast<DataType*>(sycl_device.allocate(tensor.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(slice.size()*sizeof(DataType)));
TensorMap<Tensor<DataType, 2,DataLayout,IndexType>> gpu1(gpu_data1, tensorRange);
TensorMap<Tensor<DataType, 2,DataLayout,IndexType>> gpu2(gpu_data2, tensorRange);
TensorMap<Tensor<DataType, 2,DataLayout,IndexType>> gpu3(gpu_data3, sliceRange);
tensor.setRandom();
sycl_device.memcpyHostToDevice(gpu_data1, tensor.data(),(tensor.size())*sizeof(DataType));
gpu2.device(sycl_device)=gpu1;
slice.setRandom();
sycl_device.memcpyHostToDevice(gpu_data3, slice.data(),(slice.size())*sizeof(DataType));
gpu1.slice(indicesStart,lengths).device(sycl_device)=gpu3;
gpu2.stridedSlice(indicesStart,indicesStop,strides).device(sycl_device)=gpu3;
sycl_device.memcpyDeviceToHost(tensor.data(), gpu_data1,(tensor.size())*sizeof(DataType));
sycl_device.memcpyDeviceToHost(tensor2.data(), gpu_data2,(tensor2.size())*sizeof(DataType));
for(int i=0;i<sizeDim1;i++) for(int j=0;j<sizeDim2;j++){
VERIFY_IS_EQUAL(tensor(i,j), tensor2(i,j));
}
sycl_device.deallocate(gpu_data1);
sycl_device.deallocate(gpu_data2);
sycl_device.deallocate(gpu_data3);
}
template<typename DataType, typename dev_Selector> void sycl_morphing_test_per_device(dev_Selector s){
QueueInterface queueInterface(s);
auto sycl_device = Eigen::SyclDevice(&queueInterface);
@@ -189,6 +236,8 @@ template<typename DataType, typename dev_Selector> void sycl_morphing_test_per_d
test_simple_reshape<DataType, ColMajor>(sycl_device);
test_reshape_as_lvalue<DataType, RowMajor>(sycl_device);
test_reshape_as_lvalue<DataType, ColMajor>(sycl_device);
test_strided_slice_write_sycl<DataType, ColMajor, int64_t>(sycl_device);
test_strided_slice_write_sycl<DataType, RowMajor, int64_t>(sycl_device);
}
void test_cxx11_tensor_morphing_sycl()
{