1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
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_FUNC cxx11_tensor_complex
#define EIGEN_USE_GPU
#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
#include <cuda_fp16.h>
#endif
#include "main.h"
#include <unsupported/Eigen/CXX11/Tensor>
using Eigen::Tensor;
void test_cuda_nullary() {
Tensor<std::complex<float>, 1, 0, int> in1(2);
Tensor<std::complex<float>, 1, 0, int> in2(2);
in1.setRandom();
in2.setRandom();
std::size_t float_bytes = in1.size() * sizeof(float);
std::size_t complex_bytes = in1.size() * sizeof(std::complex<float>);
std::complex<float>* d_in1;
std::complex<float>* d_in2;
float* d_out2;
cudaMalloc((void**)(&d_in1), complex_bytes);
cudaMalloc((void**)(&d_in2), complex_bytes);
cudaMalloc((void**)(&d_out2), float_bytes);
cudaMemcpy(d_in1, in1.data(), complex_bytes, cudaMemcpyHostToDevice);
cudaMemcpy(d_in2, in2.data(), complex_bytes, cudaMemcpyHostToDevice);
Eigen::CudaStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
Eigen::TensorMap<Eigen::Tensor<std::complex<float>, 1, 0, int>, Eigen::Aligned> gpu_in1(
d_in1, 2);
Eigen::TensorMap<Eigen::Tensor<std::complex<float>, 1, 0, int>, Eigen::Aligned> gpu_in2(
d_in2, 2);
Eigen::TensorMap<Eigen::Tensor<float, 1, 0, int>, Eigen::Aligned> gpu_out2(
d_out2, 2);
gpu_in1.device(gpu_device) = gpu_in1.constant(std::complex<float>(3.14f, 2.7f));
gpu_out2.device(gpu_device) = gpu_in2.abs();
Tensor<std::complex<float>, 1, 0, int> new1(2);
Tensor<float, 1, 0, int> new2(2);
assert(cudaMemcpyAsync(new1.data(), d_in1, complex_bytes, cudaMemcpyDeviceToHost,
gpu_device.stream()) == cudaSuccess);
assert(cudaMemcpyAsync(new2.data(), d_out2, float_bytes, cudaMemcpyDeviceToHost,
gpu_device.stream()) == cudaSuccess);
assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
for (int i = 0; i < 2; ++i) {
VERIFY_IS_APPROX(new1(i), std::complex<float>(3.14f, 2.7f));
VERIFY_IS_APPROX(new2(i), std::abs(in2(i)));
}
cudaFree(d_in1);
cudaFree(d_in2);
cudaFree(d_out2);
}
void test_cxx11_tensor_complex()
{
CALL_SUBTEST(test_cuda_nullary());
}
|
