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86 lines
2.3 KiB
Plaintext
86 lines
2.3 KiB
Plaintext
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#define EIGEN_TEST_NO_LONGDOUBLE
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#define EIGEN_TEST_NO_COMPLEX
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#define EIGEN_TEST_FUNC cxx11_tensor_random_cuda
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#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
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#define EIGEN_USE_GPU
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#include "main.h"
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#include <Eigen/CXX11/Tensor>
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void test_cuda_random_uniform()
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{
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Tensor<float, 2> out(72,97);
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out.setZero();
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std::size_t out_bytes = out.size() * sizeof(float);
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float* d_out;
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cudaMalloc((void**)(&d_out), out_bytes);
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Eigen::CudaStreamDevice stream;
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Eigen::GpuDevice gpu_device(&stream);
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Eigen::TensorMap<Eigen::Tensor<float, 2> > gpu_out(d_out, 72,97);
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gpu_out.device(gpu_device) = gpu_out.random();
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assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
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assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
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// For now we just check thes code doesn't crash.
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// TODO: come up with a valid test of randomness
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}
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void test_cuda_random_normal()
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{
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Tensor<float, 2> out(72,97);
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out.setZero();
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std::size_t out_bytes = out.size() * sizeof(float);
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float* d_out;
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cudaMalloc((void**)(&d_out), out_bytes);
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Eigen::CudaStreamDevice stream;
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Eigen::GpuDevice gpu_device(&stream);
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Eigen::TensorMap<Eigen::Tensor<float, 2> > gpu_out(d_out, 72,97);
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Eigen::internal::NormalRandomGenerator<float> gen(true);
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gpu_out.device(gpu_device) = gpu_out.random(gen);
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assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
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assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
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}
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static void test_complex()
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{
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Tensor<std::complex<float>, 1> vec(6);
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vec.setRandom();
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// Fixme: we should check that the generated numbers follow a uniform
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// distribution instead.
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for (int i = 1; i < 6; ++i) {
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VERIFY_IS_NOT_EQUAL(vec(i), vec(i-1));
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}
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}
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void test_cxx11_tensor_random_cuda()
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{
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CALL_SUBTEST(test_cuda_random_uniform());
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CALL_SUBTEST(test_cuda_random_normal());
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CALL_SUBTEST(test_complex());
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}
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