From 422530946f437b6cfb73a09d3932bc0f3ac8af80 Mon Sep 17 00:00:00 2001
From: Benoit Steiner <benoit.steiner.goog@gmail.com>
Date: Fri, 30 Sep 2016 08:22:10 -0700
Subject: Renamed the SYCL tests to follow the standard naming convention.

---
 unsupported/test/cxx11_tensor_forced_eval_sycl.cpp | 68 ++++++++++++++++++++++
 1 file changed, 68 insertions(+)
 create mode 100644 unsupported/test/cxx11_tensor_forced_eval_sycl.cpp

(limited to 'unsupported/test/cxx11_tensor_forced_eval_sycl.cpp')

diff --git a/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp b/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp
new file mode 100644
index 000000000..59fe743e0
--- /dev/null
+++ b/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp
@@ -0,0 +1,68 @@
+// 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_sycl_forced_eval
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_SYCL
+
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+void test_sycl_gpu() {
+	cl::sycl::gpu_selector s;
+  cl::sycl::queue q(s, [=](cl::sycl::exception_list l) {
+    for (const auto& e : l) {
+      try {
+        std::rethrow_exception(e);
+      } catch (cl::sycl::exception e) {
+        std::cout << e.what() << std::endl;
+      }
+    }
+  });
+	SyclDevice sycl_device(q);
+
+  int sizeDim1 = 100;
+  int sizeDim2 = 200;
+  int sizeDim3 = 200;
+  Eigen::array<int, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}};
+  Eigen::Tensor<float, 3> in1(tensorRange);
+  Eigen::Tensor<float, 3> in2(tensorRange);
+  Eigen::Tensor<float, 3> out(tensorRange);
+
+  in1 = in1.random() + in1.constant(10.0f);
+  in2 = in2.random() + in2.constant(10.0f);
+
+	// creating TensorMap from tensor
+  Eigen::TensorMap<Eigen::Tensor<float, 3>> gpu_in1(in1.data(), tensorRange);
+  Eigen::TensorMap<Eigen::Tensor<float, 3>> gpu_in2(in2.data(), tensorRange);
+  Eigen::TensorMap<Eigen::Tensor<float, 3>> gpu_out(out.data(), tensorRange);
+
+  /// c=(a+b)*b
+	gpu_out.device(sycl_device) =(gpu_in1 + gpu_in2).eval() * gpu_in2;
+	sycl_device.deallocate(out.data());
+  for (int i = 0; i < sizeDim1; ++i) {
+    for (int j = 0; j < sizeDim2; ++j) {
+      for (int k = 0; k < sizeDim3; ++k) {
+        VERIFY_IS_APPROX(out(i, j, k),
+                         (in1(i, j, k) + in2(i, j, k)) * in2(i, j, k));
+      }
+    }
+  }
+	printf("(a+b)*b Test Passed\n");
+}
+
+void test_cxx11_tensor_sycl_forced_eval() { CALL_SUBTEST(test_sycl_gpu()); }
-- 
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