Renamed the SYCL tests to follow the standard naming convention.

1 files changed, 79 insertions, 0 deletions

diff --git a/unsupported/test/cxx11_tensor_broadcast_sycl.cpp b/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
new file mode 100644
index 000000000..5da77981c
--- /dev/null
+++ b/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
@@ -0,0 +1,79 @@
+// 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_broadcast
+#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;
+
+// Types used in tests:
+using TestTensor = Tensor<float, 3>;
+using TestTensorMap = TensorMap<Tensor<float, 3>>;
+static void test_sycl_broadcast(){
+
+	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);
+	// BROADCAST test:
+	array<int, 4> in_range   = {{2, 3, 5, 7}};
+	array<int, in_range.size()> broadcasts = {{2, 3, 1, 4}};
+	array<int, in_range.size()> out_range;  // = in_range * broadcasts
+	for (size_t i = 0; i < out_range.size(); ++i)
+		out_range[i] = in_range[i] * broadcasts[i];
+
+	Tensor<float, in_range.size()>  input(in_range);
+	Tensor<float, out_range.size()> output(out_range);
+
+	for (int i = 0; i < input.size(); ++i)
+		input(i) = static_cast<float>(i);
+
+	TensorMap<decltype(input)>  gpu_in(input.data(), in_range);
+	TensorMap<decltype(output)> gpu_out(output.data(), out_range);
+		gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts);
+		sycl_device.deallocate(output.data());
+
+	for (size_t i = 0; i < in_range.size(); ++i)
+		VERIFY_IS_EQUAL(output.dimension(i), out_range[i]);
+
+	for (int i = 0; i < 4; ++i) {
+		for (int j = 0; j < 9; ++j) {
+			for (int k = 0; k < 5; ++k) {
+				for (int l = 0; l < 28; ++l) {
+					VERIFY_IS_APPROX(input(i%2,j%3,k%5,l%7), output(i,j,k,l));
+				}
+			}
+		}
+	}
+	printf("Broadcast Test Passed\n");
+}
+
+void test_cxx11_tensor_sycl_broadcast() {
+  CALL_SUBTEST(test_sycl_broadcast());
+}