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1 // This file is part of Eigen, a lightweight C++ template library
2 // for linear algebra.
3 //
4 // Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
5 //
6 // This Source Code Form is subject to the terms of the Mozilla
7 // Public License v. 2.0. If a copy of the MPL was not distributed
8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9 
10 #define EIGEN_TEST_NO_LONGDOUBLE
11 #define EIGEN_TEST_NO_COMPLEX
12 
13 #define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
14 #define EIGEN_USE_GPU
15 
16 #include "main.h"
17 #include <unsupported/Eigen/CXX11/Tensor>
18 
19 #include <Eigen/CXX11/src/Tensor/TensorGpuHipCudaDefines.h>
20 
21 using Eigen::Tensor;
22 typedef Tensor<float, 1>::DimensionPair DimPair;
23 
24 template<int DataLayout>
test_gpu_cumsum(int m_size,int k_size,int n_size)25 void test_gpu_cumsum(int m_size, int k_size, int n_size)
26 {
27   std::cout << "Testing for (" << m_size << "," << k_size << "," << n_size << ")" << std::endl;
28   Tensor<float, 3, DataLayout> t_input(m_size, k_size, n_size);
29   Tensor<float, 3, DataLayout> t_result(m_size, k_size, n_size);
30   Tensor<float, 3, DataLayout> t_result_gpu(m_size, k_size, n_size);
31 
32   t_input.setRandom();
33 
34   std::size_t t_input_bytes = t_input.size()  * sizeof(float);
35   std::size_t t_result_bytes = t_result.size() * sizeof(float);
36 
37   float* d_t_input;
38   float* d_t_result;
39 
40   gpuMalloc((void**)(&d_t_input), t_input_bytes);
41   gpuMalloc((void**)(&d_t_result), t_result_bytes);
42 
43   gpuMemcpy(d_t_input, t_input.data(), t_input_bytes, gpuMemcpyHostToDevice);
44 
45   Eigen::GpuStreamDevice stream;
46   Eigen::GpuDevice gpu_device(&stream);
47 
48   Eigen::TensorMap<Eigen::Tensor<float, 3, DataLayout> >
49       gpu_t_input(d_t_input, Eigen::array<int, 3>(m_size, k_size, n_size));
50   Eigen::TensorMap<Eigen::Tensor<float, 3, DataLayout> >
51       gpu_t_result(d_t_result, Eigen::array<int, 3>(m_size, k_size, n_size));
52 
53   gpu_t_result.device(gpu_device) = gpu_t_input.cumsum(1);
54   t_result = t_input.cumsum(1);
55 
56   gpuMemcpy(t_result_gpu.data(), d_t_result, t_result_bytes, gpuMemcpyDeviceToHost);
57   for (DenseIndex i = 0; i < t_result.size(); i++) {
58     if (fabs(t_result(i) - t_result_gpu(i)) < 1e-4f) {
59       continue;
60     }
61     if (Eigen::internal::isApprox(t_result(i), t_result_gpu(i), 1e-4f)) {
62       continue;
63     }
64     std::cout << "mismatch detected at index " << i << ": " << t_result(i)
65               << " vs " <<  t_result_gpu(i) << std::endl;
66     assert(false);
67   }
68 
69   gpuFree((void*)d_t_input);
70   gpuFree((void*)d_t_result);
71 }
72 
73 
EIGEN_DECLARE_TEST(cxx11_tensor_scan_gpu)74 EIGEN_DECLARE_TEST(cxx11_tensor_scan_gpu)
75 {
76   CALL_SUBTEST_1(test_gpu_cumsum<ColMajor>(128, 128, 128));
77   CALL_SUBTEST_2(test_gpu_cumsum<RowMajor>(128, 128, 128));
78 }
79