IVGCVSW-3537 Add support for L2 Normalization with < 4 dimensional tensors
* Fix reference L2 Normalization workload to support < 4 dimensional tensors
* Add unit test for L2 Normalization with 2d tensor to Reference, Neon and CL test suites
* Fix typo in StackLayer
Signed-off-by: Matthew Jackson <matthew.jackson@arm.com>
Change-Id: I48a6a1289bcb02955b24f261bc70b467bd1abc23
diff --git a/src/backends/backendsCommon/test/LayerTests.cpp b/src/backends/backendsCommon/test/LayerTests.cpp
index f996eda..4606380 100644
--- a/src/backends/backendsCommon/test/LayerTests.cpp
+++ b/src/backends/backendsCommon/test/LayerTests.cpp
@@ -7179,6 +7179,71 @@
1.f/128, 128, layout);
}
+LayerTestResult<float, 2> L2Normalization2dShapeTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ const armnn::DataLayout layout = armnn::DataLayout::NHWC;
+ const armnn::TensorShape inputOutputTensorShape = armnn::TensorShape({ 5, 2 });
+
+ std::vector<float> inputData
+ {
+ 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f
+ };
+ std::vector<float> expectedOutputData
+ {
+ 1.0f * CalcInvL2Norm({ 1.0f, 2.0f }),
+ 2.0f * CalcInvL2Norm({ 1.0f, 2.0f }),
+ 3.0f * CalcInvL2Norm({ 3.0f, 4.0f }),
+ 4.0f * CalcInvL2Norm({ 3.0f, 4.0f }),
+ 5.0f * CalcInvL2Norm({ 5.0f, 6.0f }),
+ 6.0f * CalcInvL2Norm({ 5.0f, 6.0f }),
+ 7.0f * CalcInvL2Norm({ 7.0f, 8.0f }),
+ 8.0f * CalcInvL2Norm({ 7.0f, 8.0f }),
+ 9.0f * CalcInvL2Norm({ 9.0f, 10.0f }),
+ 10.0f * CalcInvL2Norm({ 9.0f, 10.0f })
+ };
+
+ const armnn::TensorInfo inputTensorInfo(inputOutputTensorShape, armnn::DataType::Float32, 0.f, 0);
+ const armnn::TensorInfo outputTensorInfo(inputOutputTensorShape, armnn::DataType::Float32, 0.f, 0);
+
+ auto inputTensor = MakeTensor<float, 2>(inputTensorInfo, QuantizedVector<float>(
+ inputTensorInfo.GetQuantizationScale(),
+ inputTensorInfo.GetQuantizationOffset(),
+ inputData));
+
+ LayerTestResult<float, 2> result(outputTensorInfo);
+ result.outputExpected = MakeTensor<float, 2>(outputTensorInfo, QuantizedVector<float>(
+ outputTensorInfo.GetQuantizationScale(),
+ outputTensorInfo.GetQuantizationOffset(),
+ expectedOutputData));
+
+ std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+ armnn::L2NormalizationQueueDescriptor descriptor;
+ descriptor.m_Parameters.m_Eps = 1e-12f;
+ descriptor.m_Parameters.m_DataLayout = layout;
+ armnn::WorkloadInfo info;
+
+ AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
+ AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
+
+ std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateL2Normalization(descriptor, info);
+
+ inputHandle->Allocate();
+ outputHandle->Allocate();
+
+ CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]);
+
+ workload->PostAllocationConfigure();
+ ExecuteWorkload(*workload, memoryManager);
+
+ CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get());
+
+ return result;
+}
+
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> L2Normalization3dTestCommon(
armnn::IWorkloadFactory& workloadFactory,