cxx11_tensor_cast_float16_gpu.cu (2420B)
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 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 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 75 EIGEN_DECLARE_TEST(cxx11_tensor_cast_float16_gpu) 76 { 77 CALL_SUBTEST(test_gpu_conversion()); 78 CALL_SUBTEST(test_fallback_conversion()); 79 }