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diff --git a/unsupported/test/cxx11_tensor_concatenation_sycl.cpp b/unsupported/test/cxx11_tensor_concatenation_sycl.cpp
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+++ b/unsupported/test/cxx11_tensor_concatenation_sycl.cpp
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+// 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>
+//
+// 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_concatenation_sycl
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_SYCL
+
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template<typename DataType, int DataLayout, typename Index>
+static void test_simple_concatenation(const Eigen::SyclDevice& sycl_device)
+{
+ Index leftDim1 = 2;
+ Index leftDim2 = 3;
+ Index leftDim3 = 1;
+ Eigen::array<Index, 3> leftRange = {{leftDim1, leftDim2, leftDim3}};
+ Index rightDim1 = 2;
+ Index rightDim2 = 3;
+ Index rightDim3 = 1;
+ Eigen::array<Index, 3> rightRange = {{rightDim1, rightDim2, rightDim3}};
+
+ //Index concatDim1 = 3;
+// Index concatDim2 = 3;
+// Index concatDim3 = 1;
+ //Eigen::array<Index, 3> concatRange = {{concatDim1, concatDim2, concatDim3}};
+
+ Tensor<DataType, 3, DataLayout, Index> left(leftRange);
+ Tensor<DataType, 3, DataLayout, Index> right(rightRange);
+ left.setRandom();
+ right.setRandom();
+
+ DataType * gpu_in1_data = static_cast<DataType*>(sycl_device.allocate(left.dimensions().TotalSize()*sizeof(DataType)));
+ DataType * gpu_in2_data = static_cast<DataType*>(sycl_device.allocate(right.dimensions().TotalSize()*sizeof(DataType)));
+
+ Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, Index>> gpu_in1(gpu_in1_data, leftRange);
+ Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, Index>> gpu_in2(gpu_in2_data, rightRange);
+ sycl_device.memcpyHostToDevice(gpu_in1_data, left.data(),(left.dimensions().TotalSize())*sizeof(DataType));
+ sycl_device.memcpyHostToDevice(gpu_in2_data, right.data(),(right.dimensions().TotalSize())*sizeof(DataType));
+ ///
+ Tensor<DataType, 3, DataLayout, Index> concatenation1(leftDim1+rightDim1, leftDim2, leftDim3);
+ DataType * gpu_out_data1 = static_cast<DataType*>(sycl_device.allocate(concatenation1.dimensions().TotalSize()*sizeof(DataType)));
+ Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, Index>> gpu_out1(gpu_out_data1, concatenation1.dimensions());
+
+ //concatenation = left.concatenate(right, 0);
+ gpu_out1.device(sycl_device) =gpu_in1.concatenate(gpu_in2, 0);
+ sycl_device.memcpyDeviceToHost(concatenation1.data(), gpu_out_data1,(concatenation1.dimensions().TotalSize())*sizeof(DataType));
+
+ VERIFY_IS_EQUAL(concatenation1.dimension(0), 4);
+ VERIFY_IS_EQUAL(concatenation1.dimension(1), 3);
+ VERIFY_IS_EQUAL(concatenation1.dimension(2), 1);
+ for (int j = 0; j < 3; ++j) {
+ for (int i = 0; i < 2; ++i) {
+ VERIFY_IS_EQUAL(concatenation1(i, j, 0), left(i, j, 0));
+ }
+ for (int i = 2; i < 4; ++i) {
+ VERIFY_IS_EQUAL(concatenation1(i, j, 0), right(i - 2, j, 0));
+ }
+ }
+
+ sycl_device.deallocate(gpu_out_data1);
+ Tensor<DataType, 3, DataLayout, Index> concatenation2(leftDim1, leftDim2 +rightDim2, leftDim3);
+ DataType * gpu_out_data2 = static_cast<DataType*>(sycl_device.allocate(concatenation2.dimensions().TotalSize()*sizeof(DataType)));
+ Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, Index>> gpu_out2(gpu_out_data2, concatenation2.dimensions());
+ gpu_out2.device(sycl_device) =gpu_in1.concatenate(gpu_in2, 1);
+ sycl_device.memcpyDeviceToHost(concatenation2.data(), gpu_out_data2,(concatenation2.dimensions().TotalSize())*sizeof(DataType));
+
+ //concatenation = left.concatenate(right, 1);
+ VERIFY_IS_EQUAL(concatenation2.dimension(0), 2);
+ VERIFY_IS_EQUAL(concatenation2.dimension(1), 6);
+ VERIFY_IS_EQUAL(concatenation2.dimension(2), 1);
+ for (int i = 0; i < 2; ++i) {
+ for (int j = 0; j < 3; ++j) {
+ VERIFY_IS_EQUAL(concatenation2(i, j, 0), left(i, j, 0));
+ }
+ for (int j = 3; j < 6; ++j) {
+ VERIFY_IS_EQUAL(concatenation2(i, j, 0), right(i, j - 3, 0));
+ }
+ }
+ sycl_device.deallocate(gpu_out_data2);
+ Tensor<DataType, 3, DataLayout, Index> concatenation3(leftDim1, leftDim2, leftDim3+rightDim3);
+ DataType * gpu_out_data3 = static_cast<DataType*>(sycl_device.allocate(concatenation3.dimensions().TotalSize()*sizeof(DataType)));
+ Eigen::TensorMap<Eigen::Tensor<DataType, 3, DataLayout, Index>> gpu_out3(gpu_out_data3, concatenation3.dimensions());
+ gpu_out3.device(sycl_device) =gpu_in1.concatenate(gpu_in2, 2);
+ sycl_device.memcpyDeviceToHost(concatenation3.data(), gpu_out_data3,(concatenation3.dimensions().TotalSize())*sizeof(DataType));
+
+ //concatenation = left.concatenate(right, 2);
+ VERIFY_IS_EQUAL(concatenation3.dimension(0), 2);
+ VERIFY_IS_EQUAL(concatenation3.dimension(1), 3);
+ VERIFY_IS_EQUAL(concatenation3.dimension(2), 2);
+ for (int i = 0; i < 2; ++i) {
+ for (int j = 0; j < 3; ++j) {
+ VERIFY_IS_EQUAL(concatenation3(i, j, 0), left(i, j, 0));
+ VERIFY_IS_EQUAL(concatenation3(i, j, 1), right(i, j, 0));
+ }
+ }
+ sycl_device.deallocate(gpu_out_data3);
+ sycl_device.deallocate(gpu_in1_data);
+ sycl_device.deallocate(gpu_in2_data);
+}
+template<typename DataType, int DataLayout, typename Index>
+static void test_concatenation_as_lvalue(const Eigen::SyclDevice& sycl_device)
+{
+
+ Index leftDim1 = 2;
+ Index leftDim2 = 3;
+ Eigen::array<Index, 2> leftRange = {{leftDim1, leftDim2}};
+
+ Index rightDim1 = 2;
+ Index rightDim2 = 3;
+ Eigen::array<Index, 2> rightRange = {{rightDim1, rightDim2}};
+
+ Index concatDim1 = 4;
+ Index concatDim2 = 3;
+ Eigen::array<Index, 2> resRange = {{concatDim1, concatDim2}};
+
+ Tensor<DataType, 2, DataLayout, Index> left(leftRange);
+ Tensor<DataType, 2, DataLayout, Index> right(rightRange);
+ Tensor<DataType, 2, DataLayout, Index> result(resRange);
+
+ left.setRandom();
+ right.setRandom();
+ result.setRandom();
+
+ DataType * gpu_in1_data = static_cast<DataType*>(sycl_device.allocate(left.dimensions().TotalSize()*sizeof(DataType)));
+ DataType * gpu_in2_data = static_cast<DataType*>(sycl_device.allocate(right.dimensions().TotalSize()*sizeof(DataType)));
+ DataType * gpu_out_data = static_cast<DataType*>(sycl_device.allocate(result.dimensions().TotalSize()*sizeof(DataType)));
+
+
+ Eigen::TensorMap<Eigen::Tensor<DataType, 2, DataLayout, Index>> gpu_in1(gpu_in1_data, leftRange);
+ Eigen::TensorMap<Eigen::Tensor<DataType, 2, DataLayout, Index>> gpu_in2(gpu_in2_data, rightRange);
+ Eigen::TensorMap<Eigen::Tensor<DataType, 2, DataLayout, Index>> gpu_out(gpu_out_data, resRange);
+
+ sycl_device.memcpyHostToDevice(gpu_in1_data, left.data(),(left.dimensions().TotalSize())*sizeof(DataType));
+ sycl_device.memcpyHostToDevice(gpu_in2_data, right.data(),(right.dimensions().TotalSize())*sizeof(DataType));
+ sycl_device.memcpyHostToDevice(gpu_out_data, result.data(),(result.dimensions().TotalSize())*sizeof(DataType));
+
+// t1.concatenate(t2, 0) = result;
+ gpu_in1.concatenate(gpu_in2, 0).device(sycl_device) =gpu_out;
+ sycl_device.memcpyDeviceToHost(left.data(), gpu_in1_data,(left.dimensions().TotalSize())*sizeof(DataType));
+ sycl_device.memcpyDeviceToHost(right.data(), gpu_in2_data,(right.dimensions().TotalSize())*sizeof(DataType));
+
+ for (int i = 0; i < 2; ++i) {
+ for (int j = 0; j < 3; ++j) {
+ VERIFY_IS_EQUAL(left(i, j), result(i, j));
+ VERIFY_IS_EQUAL(right(i, j), result(i+2, j));
+ }
+ }
+ sycl_device.deallocate(gpu_in1_data);
+ sycl_device.deallocate(gpu_in2_data);
+ sycl_device.deallocate(gpu_out_data);
+}
+
+
+template <typename DataType, typename Dev_selector> void tensorConcat_perDevice(Dev_selector s){
+ QueueInterface queueInterface(s);
+ auto sycl_device = Eigen::SyclDevice(&queueInterface);
+ test_simple_concatenation<DataType, RowMajor, int>(sycl_device);
+ test_simple_concatenation<DataType, ColMajor, int>(sycl_device);
+ test_concatenation_as_lvalue<DataType, ColMajor, int>(sycl_device);
+}
+void test_cxx11_tensor_concatenation_sycl() {
+ for (const auto& device :Eigen::get_sycl_supported_devices()) {
+ CALL_SUBTEST(tensorConcat_perDevice<float>(device));
+ }
+}