return workload;
}
+template <typename RsqrtWorkload, armnn::DataType DataType>
+std::unique_ptr<RsqrtWorkload> CreateRsqrtWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ Layer* const layer = graph.AddLayer<RsqrtLayer>("rsqrt");
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo tensorInfo({1, 1}, DataType);
+
+ Connect(input, layer, tensorInfo);
+ Connect(layer, output, tensorInfo);
+
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<RsqrtWorkload>(*layer, graph, factory);
+
+ RsqrtQueueDescriptor queueDescriptor = workload->GetData();
+ BOOST_TEST(queueDescriptor.m_Inputs.size() == 1);
+ BOOST_TEST(queueDescriptor.m_Outputs.size() == 1);
+
+ return workload;
+}
+
template <typename L2NormalizationWorkload, armnn::DataType DataType>
std::unique_ptr<L2NormalizationWorkload> CreateL2NormalizationWorkloadTest(armnn::IWorkloadFactory& factory,
armnn::Graph& graph, DataLayout dataLayout = DataLayout::NCHW)
RefCreateResizeBilinearTest<RefResizeBilinearFloat32Workload, armnn::DataType::Float32>(DataLayout::NHWC);
}
+template <typename RsqrtWorkloadType, armnn::DataType DataType>
+static void RefCreateRsqrtTest()
+{
+ Graph graph;
+ RefWorkloadFactory factory;
+
+ auto workload = CreateRsqrtWorkloadTest<RsqrtWorkloadType, DataType>(factory, graph);
+
+ // Checks that outputs are as we expect them (see definition of CreateRsqrtWorkloadTest).
+ CheckInputOutput(std::move(workload),
+ TensorInfo({ 1, 1 }, DataType),
+ TensorInfo({ 1, 1 }, DataType));
+
+}
+
+BOOST_AUTO_TEST_CASE(CreateRsqrtFloat32)
+{
+ RefCreateRsqrtTest<RefRsqrtFloat32Workload, armnn::DataType::Float32>();
+}
+
template <typename L2NormalizationWorkloadType, armnn::DataType DataType>
static void RefCreateL2NormalizationTest(DataLayout dataLayout)
{