diff options
Diffstat (limited to 'src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.cpp')
| -rw-r--r-- | src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.cpp | 50 |
1 files changed, 25 insertions, 25 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.cpp index 227ac63941..e242fd31d3 100644 --- a/src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.cpp @@ -30,7 +30,7 @@ LayerTestResult<T, 4> L2NormalizationTestImpl( const std::vector<float>& inputValues, float outScale, int32_t outOffset, - const std::vector<float>& expectedOutputValues, + std::vector<float>& expectedOutputValues, const armnn::DataLayout layout, float epsilon = 1e-12f) { @@ -48,26 +48,23 @@ LayerTestResult<T, 4> L2NormalizationTestImpl( inputData = tmp; } - auto inputTensor = MakeTensor<T, 4>(inputTensorInfo, - armnnUtils::QuantizedVector<T>(inputData, - inputTensorInfo.GetQuantizationScale(), - inputTensorInfo.GetQuantizationOffset())); + auto inputTensor = armnnUtils::QuantizedVector<T>(inputData, + inputTensorInfo.GetQuantizationScale(), + inputTensorInfo.GetQuantizationOffset()); + + std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); - std::vector<float> expectedOutputData = expectedOutputValues; if (layout == armnn::DataLayout::NHWC) { - std::vector<float> tmp(expectedOutputData.size()); - armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, expectedOutputData.data(), tmp.data(), + std::vector<float> tmp(expectedOutputValues.size()); + armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, expectedOutputValues.data(), tmp.data(), sizeof(float)); - expectedOutputData = tmp; + expectedOutputValues = tmp; } - LayerTestResult<T, 4> result(outputTensorInfo); - result.outputExpected = - MakeTensor<T, 4>(outputTensorInfo, - armnnUtils::QuantizedVector<T>(expectedOutputData, - outputTensorInfo.GetQuantizationScale(), - outputTensorInfo.GetQuantizationOffset())); + std::vector<T> expectedOutputData = armnnUtils::QuantizedVector<T>(expectedOutputValues, + outputTensorInfo.GetQuantizationScale(), + outputTensorInfo.GetQuantizationOffset()); std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); @@ -85,14 +82,17 @@ LayerTestResult<T, 4> L2NormalizationTestImpl( inputHandle->Allocate(); outputHandle->Allocate(); - CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0][0]); + CopyDataToITensorHandle(inputHandle.get(), inputTensor.data()); workload->PostAllocationConfigure(); ExecuteWorkload(*workload, memoryManager); - CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); + CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); - return result; + return LayerTestResult<T, 4>(actualOutput, + expectedOutputData, + outputHandle->GetShape(), + outputTensorInfo.GetShape()); } float CalcInvL2Norm(std::initializer_list<float> elements) @@ -725,10 +725,7 @@ LayerTestResult<float, 2> L2Normalization2dShapeTest( 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, inputData); - - LayerTestResult<float, 2> result(outputTensorInfo); - result.outputExpected = MakeTensor<float, 2>(outputTensorInfo, expectedOutputData); + std::vector<float> actualOutput(outputTensorInfo.GetNumElements()); std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); @@ -746,14 +743,17 @@ LayerTestResult<float, 2> L2Normalization2dShapeTest( inputHandle->Allocate(); outputHandle->Allocate(); - CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]); + CopyDataToITensorHandle(inputHandle.get(), inputData.data()); workload->PostAllocationConfigure(); ExecuteWorkload(*workload, memoryManager); - CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get()); + CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); - return result; + return LayerTestResult<float, 2>(actualOutput, + expectedOutputData, + outputHandle->GetShape(), + outputTensorInfo.GetShape()); } LayerTestResult<float, 4> L2Normalization3dTest( |