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79 lines
2.5 KiB
Plaintext
79 lines
2.5 KiB
Plaintext
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// 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) 2016 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_FUNC cxx11_tensor_complex
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#define EIGEN_USE_GPU
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#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
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#include <cuda_fp16.h>
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#endif
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#include "main.h"
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#include <unsupported/Eigen/CXX11/Tensor>
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using Eigen::Tensor;
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void test_cuda_nullary() {
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Tensor<std::complex<float>, 1, 0, int> in1(2);
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Tensor<std::complex<float>, 1, 0, int> in2(2);
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in1.setRandom();
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in2.setRandom();
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std::size_t float_bytes = in1.size() * sizeof(float);
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std::size_t complex_bytes = in1.size() * sizeof(std::complex<float>);
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std::complex<float>* d_in1;
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std::complex<float>* d_in2;
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float* d_out2;
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cudaMalloc((void**)(&d_in1), complex_bytes);
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cudaMalloc((void**)(&d_in2), complex_bytes);
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cudaMalloc((void**)(&d_out2), float_bytes);
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cudaMemcpy(d_in1, in1.data(), complex_bytes, cudaMemcpyHostToDevice);
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cudaMemcpy(d_in2, in2.data(), complex_bytes, cudaMemcpyHostToDevice);
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Eigen::CudaStreamDevice stream;
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Eigen::GpuDevice gpu_device(&stream);
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Eigen::TensorMap<Eigen::Tensor<std::complex<float>, 1, 0, int>, Eigen::Aligned> gpu_in1(
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d_in1, 2);
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Eigen::TensorMap<Eigen::Tensor<std::complex<float>, 1, 0, int>, Eigen::Aligned> gpu_in2(
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d_in2, 2);
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Eigen::TensorMap<Eigen::Tensor<float, 1, 0, int>, Eigen::Aligned> gpu_out2(
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d_out2, 2);
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gpu_in1.device(gpu_device) = gpu_in1.constant(std::complex<float>(3.14f, 2.7f));
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gpu_out2.device(gpu_device) = gpu_in2.abs();
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Tensor<std::complex<float>, 1, 0, int> new1(2);
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Tensor<float, 1, 0, int> new2(2);
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assert(cudaMemcpyAsync(new1.data(), d_in1, complex_bytes, cudaMemcpyDeviceToHost,
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gpu_device.stream()) == cudaSuccess);
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assert(cudaMemcpyAsync(new2.data(), d_out2, float_bytes, cudaMemcpyDeviceToHost,
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gpu_device.stream()) == cudaSuccess);
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assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
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for (int i = 0; i < 2; ++i) {
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VERIFY_IS_APPROX(new1(i), std::complex<float>(3.14f, 2.7f));
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VERIFY_IS_APPROX(new2(i), std::abs(in2(i)));
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}
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cudaFree(d_in1);
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cudaFree(d_in2);
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cudaFree(d_out2);
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}
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void test_cxx11_tensor_complex()
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{
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CALL_SUBTEST(test_cuda_nullary());
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}
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