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 using Eigen::Tensor;
20
test_gpu_conversion()21 void test_gpu_conversion() {
22 Eigen::GpuStreamDevice stream;
23 Eigen::GpuDevice gpu_device(&stream);
24 int num_elem = 101;
25
26 Tensor<float, 1> floats(num_elem);
27 floats.setRandom();
28
29 float* d_float = (float*)gpu_device.allocate(num_elem * sizeof(float));
30 Eigen::half* d_half = (Eigen::half*)gpu_device.allocate(num_elem * sizeof(Eigen::half));
31 float* d_conv = (float*)gpu_device.allocate(num_elem * sizeof(float));
32
33 Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float(
34 d_float, num_elem);
35 Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_half(
36 d_half, num_elem);
37 Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_conv(
38 d_conv, num_elem);
39
40 gpu_device.memcpyHostToDevice(d_float, floats.data(), num_elem*sizeof(float));
41
42 gpu_half.device(gpu_device) = gpu_float.cast<Eigen::half>();
43 gpu_conv.device(gpu_device) = gpu_half.cast<float>();
44
45 Tensor<float, 1> initial(num_elem);
46 Tensor<float, 1> final(num_elem);
47 gpu_device.memcpyDeviceToHost(initial.data(), d_float, num_elem*sizeof(float));
48 gpu_device.memcpyDeviceToHost(final.data(), d_conv, num_elem*sizeof(float));
49 gpu_device.synchronize();
50
51 for (int i = 0; i < num_elem; ++i) {
52 VERIFY_IS_APPROX(initial(i), final(i));
53 }
54
55 gpu_device.deallocate(d_float);
56 gpu_device.deallocate(d_half);
57 gpu_device.deallocate(d_conv);
58 }
59
60
test_fallback_conversion()61 void test_fallback_conversion() {
62 int num_elem = 101;
63 Tensor<float, 1> floats(num_elem);
64 floats.setRandom();
65
66 Eigen::Tensor<Eigen::half, 1> halfs = floats.cast<Eigen::half>();
67 Eigen::Tensor<float, 1> conv = halfs.cast<float>();
68
69 for (int i = 0; i < num_elem; ++i) {
70 VERIFY_IS_APPROX(floats(i), conv(i));
71 }
72 }
73
74
EIGEN_DECLARE_TEST(cxx11_tensor_cast_float16_gpu)75 EIGEN_DECLARE_TEST(cxx11_tensor_cast_float16_gpu)
76 {
77 CALL_SUBTEST(test_gpu_conversion());
78 CALL_SUBTEST(test_fallback_conversion());
79 }
80