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Adding extra test for non-fixed size to broadcast; Replacing stcl with sycl.
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@ -503,11 +503,11 @@ struct TensorEvaluator<const TensorSlicingOp<StartIndices, Sizes, ArgType>, Devi
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}
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return NULL;
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}
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/// used by stcl
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/// used by sycl
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorEvaluator<ArgType, Device>& impl() const{
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return m_impl;
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}
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/// used by stcl
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/// used by sycl
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const StartIndices& startIndices() const{
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return m_offsets;
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}
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@ -25,7 +25,7 @@ using Eigen::SyclDevice;
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using Eigen::Tensor;
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using Eigen::TensorMap;
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static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){
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static void test_broadcast_sycl_fixed(const Eigen::SyclDevice &sycl_device){
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// BROADCAST test:
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array<int, 4> in_range = {{2, 3, 5, 7}};
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@ -48,7 +48,49 @@ static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){
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float * gpu_out_data = static_cast<float*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(float)));
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TensorMap<TensorFixedSize<float, Sizes<2, 3, 5, 7>>> gpu_in(gpu_in_data, in_range);
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//TensorMap<Tensor<float, 4>> gpu_in(gpu_in_data, in_range);
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TensorMap<Tensor<float, 4>> gpu_out(gpu_out_data, out_range);
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sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(float));
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gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts);
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sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
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for (int i = 0; i < 4; ++i) {
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for (int j = 0; j < 9; ++j) {
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for (int k = 0; k < 5; ++k) {
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for (int l = 0; l < 28; ++l) {
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VERIFY_IS_APPROX(input(i%2,j%3,k%5,l%7), out(i,j,k,l));
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}
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}
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}
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}
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printf("Broadcast Test with fixed size Passed\n");
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sycl_device.deallocate(gpu_in_data);
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sycl_device.deallocate(gpu_out_data);
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}
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static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){
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// BROADCAST test:
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array<int, 4> in_range = {{2, 3, 5, 7}};
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array<int, 4> broadcasts = {{2, 3, 1, 4}};
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array<int, 4> out_range; // = in_range * broadcasts
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for (size_t i = 0; i < out_range.size(); ++i)
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out_range[i] = in_range[i] * broadcasts[i];
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Tensor<float, 4> input(in_range);
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Tensor<float, 4> out(out_range);
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for (size_t i = 0; i < in_range.size(); ++i)
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VERIFY_IS_EQUAL(out.dimension(i), out_range[i]);
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for (int i = 0; i < input.size(); ++i)
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input(i) = static_cast<float>(i);
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float * gpu_in_data = static_cast<float*>(sycl_device.allocate(input.dimensions().TotalSize()*sizeof(float)));
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float * gpu_out_data = static_cast<float*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(float)));
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TensorMap<Tensor<float, 4>> gpu_in(gpu_in_data, in_range);
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TensorMap<Tensor<float, 4>> gpu_out(gpu_out_data, out_range);
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sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(float));
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gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts);
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@ -68,8 +110,10 @@ static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){
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sycl_device.deallocate(gpu_out_data);
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}
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void test_cxx11_tensor_broadcast_sycl() {
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cl::sycl::gpu_selector s;
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Eigen::SyclDevice sycl_device(s);
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CALL_SUBTEST(test_broadcast_sycl_fixed(sycl_device));
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CALL_SUBTEST(test_broadcast_sycl(sycl_device));
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}
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