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Adding TensorFixsize; adding sycl device memcpy; adding insial stage of slicing.

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Mehdi Goli
2016-11-14 17:51:57 +00:00
parent a5c3f15682
commit f8ca893976
11 changed files with 251 additions and 27 deletions
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1
unsupported/test/CMakeLists.txt
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@@ -146,6 +146,7 @@ if(EIGEN_TEST_CXX11)
ei_add_test_sycl(cxx11_tensor_broadcast_sycl "-std=c++11")
ei_add_test_sycl(cxx11_tensor_device_sycl "-std=c++11")
ei_add_test_sycl(cxx11_tensor_reduction_sycl "-std=c++11")
ei_add_test_sycl(cxx11_tensor_morphing_sycl "-std=c++11")
endif(EIGEN_TEST_SYCL)
# It should be safe to always run these tests as there is some fallback code for
# older compiler that don't support cxx11.

3
unsupported/test/cxx11_tensor_broadcast_sycl.cpp
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@@ -47,7 +47,8 @@ static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){
float * gpu_in_data = static_cast<float*>(sycl_device.allocate(input.dimensions().TotalSize()*sizeof(float)));
float * gpu_out_data = static_cast<float*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(float)));
TensorMap<Tensor<float, 4>> gpu_in(gpu_in_data, in_range);
TensorMap<TensorFixedSize<float, Sizes<2, 3, 5, 7>>> gpu_in(gpu_in_data, in_range);
//TensorMap<Tensor<float, 4>> gpu_in(gpu_in_data, in_range);
TensorMap<Tensor<float, 4>> gpu_out(gpu_out_data, out_range);
sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(float));
gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts);

84
unsupported/test/cxx11_tensor_morphing_sycl.cpp Normal file
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@@ -0,0 +1,84 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2016
// Mehdi Goli Codeplay Software Ltd.
// Ralph Potter Codeplay Software Ltd.
// Luke Iwanski Codeplay Software Ltd.
// Contact: <eigen@codeplay.com>
// 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_morphing_sycl
#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
#define EIGEN_USE_SYCL
#include "main.h"
#include <unsupported/Eigen/CXX11/Tensor>
using Eigen::array;
using Eigen::SyclDevice;
using Eigen::Tensor;
using Eigen::TensorMap;
static void test_simple_slice(const Eigen::SyclDevice &sycl_device)
{
int sizeDim1 = 2;
int sizeDim2 = 3;
int sizeDim3 = 5;
int sizeDim4 = 7;
int sizeDim5 = 11;
array<int, 5> tensorRange = {{sizeDim1, sizeDim2, sizeDim3, sizeDim4, sizeDim5}};
Tensor<float, 5> tensor(tensorRange);
tensor.setRandom();
array<int, 5> slice1_range ={{1, 1, 1, 1, 1}};
Tensor<float, 5> slice1(slice1_range);
float* gpu_data1 = static_cast<float*>(sycl_device.allocate(tensor.size()*sizeof(float)));
float* gpu_data2 = static_cast<float*>(sycl_device.allocate(slice1.size()*sizeof(float)));
TensorMap<Tensor<float, 5>> gpu1(gpu_data1, tensorRange);
TensorMap<Tensor<float, 5>> gpu2(gpu_data2, slice1_range);
Eigen::DSizes<ptrdiff_t, 5> indices(1,2,3,4,5);
Eigen::DSizes<ptrdiff_t, 5> sizes(1,1,1,1,1);
sycl_device.memcpyHostToDevice(gpu_data1, tensor.data(),(tensor.size())*sizeof(float));
gpu2.device(sycl_device)=gpu1.slice(indices, sizes);
sycl_device.memcpyDeviceToHost(slice1.data(), gpu_data2,(slice1.size())*sizeof(float));
VERIFY_IS_EQUAL(slice1(0,0,0,0,0), tensor(1,2,3,4,5));
array<int, 5> slice2_range ={{1,1,2,2,3}};
Tensor<float, 5> slice2(slice2_range);
float* gpu_data3 = static_cast<float*>(sycl_device.allocate(slice2.size()*sizeof(float)));
TensorMap<Tensor<float, 5>> gpu3(gpu_data3, slice2_range);
Eigen::DSizes<ptrdiff_t, 5> indices2(1,1,3,4,5);
Eigen::DSizes<ptrdiff_t, 5> sizes2(1,1,2,2,3);
gpu3.device(sycl_device)=gpu1.slice(indices2, sizes2);
sycl_device.memcpyDeviceToHost(slice2.data(), gpu_data3,(slice2.size())*sizeof(float));
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 2; ++j) {
for (int k = 0; k < 3; ++k) {
VERIFY_IS_EQUAL(slice2(0,0,i,j,k), tensor(1,1,3+i,4+j,5+k));
}
}
}
sycl_device.deallocate(gpu_data1);
sycl_device.deallocate(gpu_data2);
sycl_device.deallocate(gpu_data3);
}
void test_cxx11_tensor_morphing_sycl()
{
/// Currentlly it only works on cpu. Adding GPU cause LLVM ERROR in cunstructing OpenCL Kernel at runtime.
cl::sycl::cpu_selector s;
Eigen::SyclDevice sycl_device(s);
CALL_SUBTEST(test_simple_slice(sycl_device));
}