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Added regression test for float16
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unsupported/test/cxx11_tensor_of_float16_cuda.cu
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unsupported/test/cxx11_tensor_of_float16_cuda.cu
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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_NO_COMPLEX
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#define EIGEN_TEST_FUNC cxx11_tensor_of_float16_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 <unsupported/Eigen/CXX11/Tensor>
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using Eigen::Tensor;
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void test_cuda_conversion() {
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Eigen::CudaStreamDevice stream;
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Eigen::GpuDevice gpu_device(&stream);
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int num_elem = 101;
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float* d_float = (float*)gpu_device.allocate(num_elem * sizeof(float));
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half* d_half = (half*)gpu_device.allocate(num_elem * sizeof(half));
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float* d_conv = (float*)gpu_device.allocate(num_elem * sizeof(float));
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Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float(
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d_float, num_elem);
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Eigen::TensorMap<Eigen::Tensor<half, 1>, Eigen::Aligned> gpu_half(
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d_half, num_elem);
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Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_conv(
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d_conv, num_elem);
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gpu_float.device(gpu_device) = gpu_float.random();
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gpu_half.device(gpu_device) = gpu_float.cast<half>();
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gpu_conv.device(gpu_device) = gpu_half.cast<float>();
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Tensor<float, 1> initial(num_elem);
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Tensor<float, 1> final(num_elem);
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gpu_device.memcpyDeviceToHost(initial.data(), d_float, num_elem*sizeof(float));
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gpu_device.memcpyDeviceToHost(final.data(), d_conv, num_elem*sizeof(float));
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for (int i = 0; i < num_elem; ++i) {
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VERIFY_IS_APPROX(initial(i), final(i));
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}
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gpu_device.deallocate(d_float);
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gpu_device.deallocate(d_half);
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gpu_device.deallocate(d_conv);
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}
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void test_cxx11_tensor_of_float16_cuda()
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{
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CALL_SUBTEST_1(test_cuda_conversion());
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}
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