From 79ebc8f76137f151c78b4f61cd99fae62bf6c34f Mon Sep 17 00:00:00 2001 From: Mehdi Goli Date: Mon, 20 Feb 2017 12:11:05 +0000 Subject: Adding Sycl backend for TensorImagePatchOP.h; adding Sycl backend for TensorInflation.h. --- unsupported/test/cxx11_tensor_inflation_sycl.cpp | 136 +++++++++++++++++++++++ 1 file changed, 136 insertions(+) create mode 100644 unsupported/test/cxx11_tensor_inflation_sycl.cpp (limited to 'unsupported/test/cxx11_tensor_inflation_sycl.cpp') diff --git a/unsupported/test/cxx11_tensor_inflation_sycl.cpp b/unsupported/test/cxx11_tensor_inflation_sycl.cpp new file mode 100644 index 000000000..f2f87f7ed --- /dev/null +++ b/unsupported/test/cxx11_tensor_inflation_sycl.cpp @@ -0,0 +1,136 @@ +// 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: +// +// 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_inflation_sycl +#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int64_t +#define EIGEN_USE_SYCL + +#include "main.h" +#include + +using Eigen::Tensor; + +// Inflation Defenition for each dimention the inflated val would be +//((dim-1)*strid[dim] +1) + +// for 1 dimnention vector of size 3 with value (4,4,4) with the inflated stride value of 3 would be changed to +// tensor of size (2*3) +1 = 7 with the value of +// (4, 0, 0, 4, 0, 0, 4). + +template +void test_simple_inflation_sycl(const Eigen::SyclDevice &sycl_device) { + + + IndexType sizeDim1 = 2; + IndexType sizeDim2 = 3; + IndexType sizeDim3 = 5; + IndexType sizeDim4 = 7; + array tensorRange = {{sizeDim1, sizeDim2, sizeDim3, sizeDim4}}; + Tensor tensor(tensorRange); + Tensor no_stride(tensorRange); + tensor.setRandom(); + + array strides; + strides[0] = 1; + strides[1] = 1; + strides[2] = 1; + strides[3] = 1; + + + const size_t tensorBuffSize =tensor.size()*sizeof(DataType); + DataType* gpu_data_tensor = static_cast(sycl_device.allocate(tensorBuffSize)); + DataType* gpu_data_no_stride = static_cast(sycl_device.allocate(tensorBuffSize)); + + TensorMap> gpu_tensor(gpu_data_tensor, tensorRange); + TensorMap> gpu_no_stride(gpu_data_no_stride, tensorRange); + + sycl_device.memcpyHostToDevice(gpu_data_tensor, tensor.data(), tensorBuffSize); + gpu_no_stride.device(sycl_device)=gpu_tensor.inflate(strides); + sycl_device.memcpyDeviceToHost(no_stride.data(), gpu_data_no_stride, tensorBuffSize); + + VERIFY_IS_EQUAL(no_stride.dimension(0), sizeDim1); + VERIFY_IS_EQUAL(no_stride.dimension(1), sizeDim2); + VERIFY_IS_EQUAL(no_stride.dimension(2), sizeDim3); + VERIFY_IS_EQUAL(no_stride.dimension(3), sizeDim4); + + for (IndexType i = 0; i < 2; ++i) { + for (IndexType j = 0; j < 3; ++j) { + for (IndexType k = 0; k < 5; ++k) { + for (IndexType l = 0; l < 7; ++l) { + VERIFY_IS_EQUAL(tensor(i,j,k,l), no_stride(i,j,k,l)); + } + } + } + } + + + strides[0] = 2; + strides[1] = 4; + strides[2] = 2; + strides[3] = 3; + + IndexType inflatedSizeDim1 = 3; + IndexType inflatedSizeDim2 = 9; + IndexType inflatedSizeDim3 = 9; + IndexType inflatedSizeDim4 = 19; + array inflatedTensorRange = {{inflatedSizeDim1, inflatedSizeDim2, inflatedSizeDim3, inflatedSizeDim4}}; + + Tensor inflated(inflatedTensorRange); + + const size_t inflatedTensorBuffSize =inflated.size()*sizeof(DataType); + DataType* gpu_data_inflated = static_cast(sycl_device.allocate(inflatedTensorBuffSize)); + TensorMap> gpu_inflated(gpu_data_inflated, inflatedTensorRange); + gpu_inflated.device(sycl_device)=gpu_tensor.inflate(strides); + sycl_device.memcpyDeviceToHost(inflated.data(), gpu_data_inflated, inflatedTensorBuffSize); + + VERIFY_IS_EQUAL(inflated.dimension(0), inflatedSizeDim1); + VERIFY_IS_EQUAL(inflated.dimension(1), inflatedSizeDim2); + VERIFY_IS_EQUAL(inflated.dimension(2), inflatedSizeDim3); + VERIFY_IS_EQUAL(inflated.dimension(3), inflatedSizeDim4); + + for (IndexType i = 0; i < inflatedSizeDim1; ++i) { + for (IndexType j = 0; j < inflatedSizeDim2; ++j) { + for (IndexType k = 0; k < inflatedSizeDim3; ++k) { + for (IndexType l = 0; l < inflatedSizeDim4; ++l) { + if (i % strides[0] == 0 && + j % strides[1] == 0 && + k % strides[2] == 0 && + l % strides[3] == 0) { + VERIFY_IS_EQUAL(inflated(i,j,k,l), + tensor(i/strides[0], j/strides[1], k/strides[2], l/strides[3])); + } else { + VERIFY_IS_EQUAL(0, inflated(i,j,k,l)); + } + } + } + } + } + sycl_device.deallocate(gpu_data_tensor); + sycl_device.deallocate(gpu_data_no_stride); + sycl_device.deallocate(gpu_data_inflated); +} + +template void sycl_inflation_test_per_device(dev_Selector s){ + QueueInterface queueInterface(s); + auto sycl_device = Eigen::SyclDevice(&queueInterface); + test_simple_inflation_sycl(sycl_device); + test_simple_inflation_sycl(sycl_device); +} +void test_cxx11_tensor_inflation_sycl() +{ + for (const auto& device :Eigen::get_sycl_supported_devices()) { + CALL_SUBTEST(sycl_inflation_test_per_device(device)); + } +} -- cgit v1.2.3