// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2014 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_TEST_FUNC cxx11_tensor_random_cuda #define EIGEN_DEFAULT_DENSE_INDEX_TYPE int #define EIGEN_USE_GPU #if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500 #include <cuda_fp16.h> #endif #include "main.h" #include <Eigen/CXX11/Tensor> void test_cuda_random_uniform() { Tensor<float, 2> out(72,97); out.setZero(); std::size_t out_bytes = out.size() * sizeof(float); float* d_out; cudaMalloc((void**)(&d_out), out_bytes); Eigen::CudaStreamDevice stream; Eigen::GpuDevice gpu_device(&stream); Eigen::TensorMap<Eigen::Tensor<float, 2> > gpu_out(d_out, 72,97); gpu_out.device(gpu_device) = gpu_out.random(); assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess); assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess); // For now we just check thes code doesn't crash. // TODO: come up with a valid test of randomness } void test_cuda_random_normal() { Tensor<float, 2> out(72,97); out.setZero(); std::size_t out_bytes = out.size() * sizeof(float); float* d_out; cudaMalloc((void**)(&d_out), out_bytes); Eigen::CudaStreamDevice stream; Eigen::GpuDevice gpu_device(&stream); Eigen::TensorMap<Eigen::Tensor<float, 2> > gpu_out(d_out, 72,97); Eigen::internal::NormalRandomGenerator<float> gen(true); gpu_out.device(gpu_device) = gpu_out.random(gen); assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess); assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess); } static void test_complex() { Tensor<std::complex<float>, 1> vec(6); vec.setRandom(); // Fixme: we should check that the generated numbers follow a uniform // distribution instead. for (int i = 1; i < 6; ++i) { VERIFY_IS_NOT_EQUAL(vec(i), vec(i-1)); } } void test_cxx11_tensor_random_cuda() { CALL_SUBTEST(test_cuda_random_uniform()); CALL_SUBTEST(test_cuda_random_normal()); CALL_SUBTEST(test_complex()); }