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| author |  Luke Iwanski <luke@codeplay.com> | 2016-11-18 11:16:42 +0000 |
|---|---|---|
| committer | Luke Iwanski <luke@codeplay.com> | 2016-11-18 11:16:42 +0000 |
| commit | 927bd62d2a1ecfe05d500121f1a92d8502be2d3e (patch) | |
| tree | 83f24f945c91d9a534099e0f6bc238838678d8ef /unsupported/test/cxx11_tensor_builtins_sycl.cpp | |
| parent | 7c30078b9f62f1f49ab3fe82b74ff461c1c3109c (diff) | |
Now testing out (+=, =) in.FUNC() and out (+=, =) out.FUNC()
Diffstat (limited to 'unsupported/test/cxx11_tensor_builtins_sycl.cpp')
| -rw-r--r-- | unsupported/test/cxx11_tensor_builtins_sycl.cpp | 74 |
1 files changed, 52 insertions, 22 deletions
diff --git a/unsupported/test/cxx11_tensor_builtins_sycl.cpp b/unsupported/test/cxx11_tensor_builtins_sycl.cpp index 0cf3ab2a2..0a284e95c 100644 --- a/unsupported/test/cxx11_tensor_builtins_sycl.cpp +++ b/unsupported/test/cxx11_tensor_builtins_sycl.cpp @@ -32,11 +32,14 @@ template <typename T> T cube(T x) { return x * x * x; } template <typename T> T inverse(T x) { return 1 / x; } } -#define TEST_UNARY_BUILTINS_FOR_SCALAR(FUNC, SCALAR) \ +#define TEST_UNARY_BUILTINS_FOR_SCALAR(FUNC, SCALAR, OPERATOR) \ { \ + /* out OPERATOR in.FUNC() */ \ Tensor<SCALAR, 3> in(tensorRange); \ Tensor<SCALAR, 3> out(tensorRange); \ in = in.random() + static_cast<SCALAR>(0.01); \ + out = out.random() + static_cast<SCALAR>(0.01); \ + Tensor<SCALAR, 3> reference(out); \ SCALAR *gpu_data = static_cast<SCALAR *>( \ sycl_device.allocate(in.size() * sizeof(SCALAR))); \ SCALAR *gpu_data_out = static_cast<SCALAR *>( \ @@ -45,41 +48,68 @@ template <typename T> T inverse(T x) { return 1 / x; } TensorMap<Tensor<SCALAR, 3>> gpu_out(gpu_data_out, tensorRange); \ sycl_device.memcpyHostToDevice(gpu_data, in.data(), \ (in.size()) * sizeof(SCALAR)); \ - gpu_out.device(sycl_device) = gpu.FUNC(); \ + sycl_device.memcpyHostToDevice(gpu_data_out, out.data(), \ + (out.size()) * sizeof(SCALAR)); \ + gpu_out.device(sycl_device) OPERATOR gpu.FUNC(); \ sycl_device.memcpyDeviceToHost(out.data(), gpu_data_out, \ (out.size()) * sizeof(SCALAR)); \ - for (int i = 0; i < in.size(); ++i) { \ - VERIFY_IS_APPROX(out(i), std::FUNC(in(i))); \ + for (int i = 0; i < out.size(); ++i) { \ + SCALAR ver = reference(i); \ + ver OPERATOR std::FUNC(in(i)); \ + VERIFY_IS_APPROX(out(i), ver); \ } \ sycl_device.deallocate(gpu_data); \ sycl_device.deallocate(gpu_data_out); \ + } \ + { \ + /* out OPERATOR out.FUNC() */ \ + Tensor<SCALAR, 3> out(tensorRange); \ + out = out.random() + static_cast<SCALAR>(0.01); \ + Tensor<SCALAR, 3> reference(out); \ + SCALAR *gpu_data_out = static_cast<SCALAR *>( \ + sycl_device.allocate(out.size() * sizeof(SCALAR))); \ + TensorMap<Tensor<SCALAR, 3>> gpu_out(gpu_data_out, tensorRange); \ + sycl_device.memcpyHostToDevice(gpu_data_out, out.data(), \ + (out.size()) * sizeof(SCALAR)); \ + gpu_out.device(sycl_device) OPERATOR gpu_out.FUNC(); \ + sycl_device.memcpyDeviceToHost(out.data(), gpu_data_out, \ + (out.size()) * sizeof(SCALAR)); \ + for (int i = 0; i < out.size(); ++i) { \ + SCALAR ver = reference(i); \ + ver OPERATOR std::FUNC(reference(i)); \ + VERIFY_IS_APPROX(out(i), ver); \ + } \ + sycl_device.deallocate(gpu_data_out); \ } +#define TEST_UNARY_BUILTINS_OPERATOR(SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(abs, SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(sqrt, SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(rsqrt, SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(square, SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(cube, SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(inverse, SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(tanh, SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(exp, SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(log, SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(abs, SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(ceil, SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(floor, SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(round, SCALAR, OPERATOR) \ + TEST_UNARY_BUILTINS_FOR_SCALAR(log1p, SCALAR, OPERATOR) + #define TEST_UNARY_BUILTINS(SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(abs, SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(sqrt, SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(rsqrt, SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(square, SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(cube, SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(inverse, SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(tanh, SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(exp, SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(log, SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(abs, SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(ceil, SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(floor, SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(round, SCALAR) \ - TEST_UNARY_BUILTINS_FOR_SCALAR(log1p, SCALAR) + TEST_UNARY_BUILTINS_OPERATOR(SCALAR, += ) \ + TEST_UNARY_BUILTINS_OPERATOR(SCALAR, = ) static void test_builtin_unary_sycl(const Eigen::SyclDevice &sycl_device) { - int sizeDim1 = 100; - int sizeDim2 = 100; - int sizeDim3 = 100; + int sizeDim1 = 10; + int sizeDim2 = 10; + int sizeDim3 = 10; array<int, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}}; TEST_UNARY_BUILTINS(float) TEST_UNARY_BUILTINS(double) - } void test_cxx11_tensor_builtins_sycl() { |