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Diffstat (limited to 'unsupported/test/cxx11_tensor_scan_gpu.cu')
-rw-r--r-- | unsupported/test/cxx11_tensor_scan_gpu.cu | 78 |
1 files changed, 78 insertions, 0 deletions
diff --git a/unsupported/test/cxx11_tensor_scan_gpu.cu b/unsupported/test/cxx11_tensor_scan_gpu.cu new file mode 100644 index 000000000..770a144f1 --- /dev/null +++ b/unsupported/test/cxx11_tensor_scan_gpu.cu @@ -0,0 +1,78 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com> +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#define EIGEN_TEST_NO_LONGDOUBLE +#define EIGEN_TEST_NO_COMPLEX + +#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int +#define EIGEN_USE_GPU + +#include "main.h" +#include <unsupported/Eigen/CXX11/Tensor> + +#include <Eigen/CXX11/src/Tensor/TensorGpuHipCudaDefines.h> + +using Eigen::Tensor; +typedef Tensor<float, 1>::DimensionPair DimPair; + +template<int DataLayout> +void test_gpu_cumsum(int m_size, int k_size, int n_size) +{ + std::cout << "Testing for (" << m_size << "," << k_size << "," << n_size << ")" << std::endl; + Tensor<float, 3, DataLayout> t_input(m_size, k_size, n_size); + Tensor<float, 3, DataLayout> t_result(m_size, k_size, n_size); + Tensor<float, 3, DataLayout> t_result_gpu(m_size, k_size, n_size); + + t_input.setRandom(); + + std::size_t t_input_bytes = t_input.size() * sizeof(float); + std::size_t t_result_bytes = t_result.size() * sizeof(float); + + float* d_t_input; + float* d_t_result; + + gpuMalloc((void**)(&d_t_input), t_input_bytes); + gpuMalloc((void**)(&d_t_result), t_result_bytes); + + gpuMemcpy(d_t_input, t_input.data(), t_input_bytes, gpuMemcpyHostToDevice); + + Eigen::GpuStreamDevice stream; + Eigen::GpuDevice gpu_device(&stream); + + Eigen::TensorMap<Eigen::Tensor<float, 3, DataLayout> > + gpu_t_input(d_t_input, Eigen::array<int, 3>(m_size, k_size, n_size)); + Eigen::TensorMap<Eigen::Tensor<float, 3, DataLayout> > + gpu_t_result(d_t_result, Eigen::array<int, 3>(m_size, k_size, n_size)); + + gpu_t_result.device(gpu_device) = gpu_t_input.cumsum(1); + t_result = t_input.cumsum(1); + + gpuMemcpy(t_result_gpu.data(), d_t_result, t_result_bytes, gpuMemcpyDeviceToHost); + for (DenseIndex i = 0; i < t_result.size(); i++) { + if (fabs(t_result(i) - t_result_gpu(i)) < 1e-4f) { + continue; + } + if (Eigen::internal::isApprox(t_result(i), t_result_gpu(i), 1e-4f)) { + continue; + } + std::cout << "mismatch detected at index " << i << ": " << t_result(i) + << " vs " << t_result_gpu(i) << std::endl; + assert(false); + } + + gpuFree((void*)d_t_input); + gpuFree((void*)d_t_result); +} + + +EIGEN_DECLARE_TEST(cxx11_tensor_scan_gpu) +{ + CALL_SUBTEST_1(test_gpu_cumsum<ColMajor>(128, 128, 128)); + CALL_SUBTEST_2(test_gpu_cumsum<RowMajor>(128, 128, 128)); +} |