diff options
Diffstat (limited to 'src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp')
| -rw-r--r-- | src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp | 2158 |
1 files changed, 1130 insertions, 1028 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp index 29476e522a..e9932c81ef 100644 --- a/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp @@ -6,6 +6,7 @@ #include "ConcatTestImpl.hpp" #include <Permute.hpp> +#include <QuantizeHelper.hpp> #include <ResolveType.hpp> #include <armnn/ArmNN.hpp> @@ -15,22 +16,25 @@ #include <test/TensorHelpers.hpp> +using namespace armnn; +using namespace armnnUtils; + // // Helper functions and templates // -armnn::OriginsDescriptor CreateDescriptorForConcat( - const std::vector<armnn::TensorInfo> & inputTensorInfos, +OriginsDescriptor CreateDescriptorForConcat( + const std::vector<TensorInfo> & inputTensorInfos, unsigned int concatDim) { - std::vector<armnn::TensorShape> shapes; + std::vector<TensorShape> shapes; shapes.reserve(inputTensorInfos.size()); - for (const armnn::TensorInfo& it: inputTensorInfos) + for (const TensorInfo& it: inputTensorInfos) { shapes.push_back(it.GetShape()); } - return armnn::CreateDescriptorForConcatenation(shapes.begin(), shapes.end(), concatDim); + return CreateDescriptorForConcatenation(shapes.begin(), shapes.end(), concatDim); } // @@ -40,7 +44,7 @@ armnn::OriginsDescriptor CreateDescriptorForConcat( // bool NeedPermuteForConcat( - const std::vector<armnn::TensorInfo> & inputTensorInfos, + const std::vector<TensorInfo> & inputTensorInfos, unsigned int concatDim) { // See note above. Additionally we expect the input shapes to have the @@ -65,7 +69,7 @@ bool NeedPermuteForConcat( return (nDimensions < 3 || (nDimensions == 3 && (nDimensions-concatDim) < 3 && (nDimensions-concatDim) != 1)); } -armnn::TensorShape ExpandTensorShapeTo3dForPermute(const armnn::TensorShape & inputShape) +TensorShape ExpandTensorShapeTo3dForPermute(const TensorShape & inputShape) { unsigned int numDims = inputShape.GetNumDimensions(); if (numDims >= 3) @@ -80,13 +84,13 @@ armnn::TensorShape ExpandTensorShapeTo3dForPermute(const armnn::TensorShape & in { newDims[expandedBy+i] = inputShape[i]; } - return armnn::TensorShape(3u, &newDims[0]); + return TensorShape(3u, &newDims[0]); } void Generate3dPermuteVectorForConcat( unsigned int numDimensions, unsigned int & concatDim, - std::pair<armnn::PermutationVector, armnn::PermutationVector> & permutations) + std::pair<PermutationVector, PermutationVector> & permutations) { BOOST_ASSERT_MSG(numDimensions <= 3, "Only dimensions 1,2 and 3 are supported by this helper"); @@ -96,15 +100,15 @@ void Generate3dPermuteVectorForConcat( if (expandedConcatAxis == 2) { concatDim = 0; - armnn::PermutationVector forwardPermutation({1, 2, 0}); - armnn::PermutationVector reversePermutation({2, 0, 1}); + PermutationVector forwardPermutation({1, 2, 0}); + PermutationVector reversePermutation({2, 0, 1}); permutations = std::make_pair(forwardPermutation, reversePermutation); } else if (expandedConcatAxis == 1) { concatDim = 0; - armnn::PermutationVector forwardPermutation({2, 0, 1}); - armnn::PermutationVector reversePermutation({1, 2, 0}); + PermutationVector forwardPermutation({2, 0, 1}); + PermutationVector reversePermutation({1, 2, 0}); permutations = std::make_pair(forwardPermutation, reversePermutation); } else @@ -115,10 +119,10 @@ void Generate3dPermuteVectorForConcat( } template<typename T> void PermuteTensorData( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::PermutationVector& mappings, - armnn::TensorInfo & inputTensorInfo, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const PermutationVector& mappings, + TensorInfo & inputTensorInfo, const T * inputData, std::vector<T>& outputData) { @@ -131,18 +135,18 @@ template<typename T> void PermuteTensorData( return; } - armnn::TensorInfo outputTensorInfo = armnnUtils::Permuted(inputTensorInfo, mappings); + TensorInfo outputTensorInfo = armnnUtils::Permuted(inputTensorInfo, mappings); - std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); - std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + std::unique_ptr<ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); + std::unique_ptr<ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); - armnn::PermuteQueueDescriptor queueDescriptor; - queueDescriptor.m_Parameters = armnn::PermuteDescriptor{mappings}; - armnn::WorkloadInfo workloadInfo; + PermuteQueueDescriptor queueDescriptor; + queueDescriptor.m_Parameters = PermuteDescriptor{mappings}; + WorkloadInfo workloadInfo; AddInputToWorkload(queueDescriptor, workloadInfo, inputTensorInfo, inputHandle.get()); AddOutputToWorkload(queueDescriptor, workloadInfo, outputTensorInfo, outputHandle.get()); - std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePermute(queueDescriptor, workloadInfo); + std::unique_ptr<IWorkload> workload = workloadFactory.CreatePermute(queueDescriptor, workloadInfo); inputHandle->Allocate(); outputHandle->Allocate(); @@ -164,23 +168,23 @@ template<typename T> void PermuteTensorData( // of the permuted concatenated tensor is going to be. // template<typename T> void PermuteInputsForConcat( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - std::vector<armnn::TensorInfo> & inputTensorInfos, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + std::vector<TensorInfo> & inputTensorInfos, std::vector<T *> & inputData, std::vector<std::vector<T>> & inputDataStorage, - armnn::PermutationVector & permuteVector, + PermutationVector & permuteVector, unsigned int & concatDim, - armnn::TensorInfo & outputTensorInfo) + TensorInfo & outputTensorInfo) { BOOST_ASSERT_MSG(inputTensorInfos.size() > 1, "Expecting more than one tensor to be concatenated here"); unsigned int numDims = 0; unsigned int nthInput = 0; - const armnn::PermutationVector identity({0, 1, 2}); + const PermutationVector identity({0, 1, 2}); - std::pair<armnn::PermutationVector, armnn::PermutationVector> permutations = + std::pair<PermutationVector, PermutationVector> permutations = std::make_pair(identity, identity); inputDataStorage.resize(inputData.size()); @@ -203,7 +207,7 @@ template<typename T> void PermuteInputsForConcat( "All inputs must have the same number of dimensions"); } - armnn::TensorInfo newTensorInfo = tensorInfo; + TensorInfo newTensorInfo = tensorInfo; newTensorInfo.SetShape(ExpandTensorShapeTo3dForPermute(tensorInfo.GetShape())); PermuteTensorData<T>(workloadFactory, @@ -231,11 +235,11 @@ template<typename T> void PermuteInputsForConcat( // output. // template <typename T> void PermuteOutputForConcat( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::TensorInfo & tensorInfo, - const armnn::PermutationVector & permuteVector, - std::unique_ptr<armnn::ITensorHandle> && inputDataHandle, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const TensorInfo & tensorInfo, + const PermutationVector & permuteVector, + std::unique_ptr<ITensorHandle> && inputDataHandle, T * data) { BOOST_ASSERT_MSG(data != nullptr, "data must not be null"); @@ -247,7 +251,7 @@ template <typename T> void PermuteOutputForConcat( return; } - armnn::TensorInfo resultTensorInfo = tensorInfo; + TensorInfo resultTensorInfo = tensorInfo; std::vector<T> inputData(tensorInfo.GetNumElements()); std::vector<T> outputData; @@ -264,11 +268,11 @@ template <typename T> void PermuteOutputForConcat( } template<typename T> void Concatenate( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - std::initializer_list<const armnn::TensorInfo> inputTensorInfosOrig, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + std::initializer_list<const TensorInfo> inputTensorInfosOrig, std::initializer_list<T *> inputsOrig, - const armnn::TensorInfo& outputTensorInfoOrig, + const TensorInfo& outputTensorInfoOrig, T * output, unsigned int concatDim, bool useSubtensor) @@ -283,11 +287,11 @@ template<typename T> void Concatenate( } // Saves a copy of the parameters which we might need to change. - std::vector<armnn::TensorInfo> inputTensorInfos(inputTensorInfosOrig.begin(), inputTensorInfosOrig.end()); + std::vector<TensorInfo> inputTensorInfos(inputTensorInfosOrig.begin(), inputTensorInfosOrig.end()); std::vector<T *> inputs = inputsOrig; - armnn::TensorInfo outputTensorInfo = outputTensorInfoOrig; + TensorInfo outputTensorInfo = outputTensorInfoOrig; - armnn::PermutationVector permuteVector{0, 1, 2}; + PermutationVector permuteVector{0, 1, 2}; // Holds and automatically releases memory for the reshaped input data. std::vector<std::vector<T>> tmpInputDataStorage; @@ -312,15 +316,15 @@ template<typename T> void Concatenate( outputTensorInfo); } - armnn::WorkloadInfo workloadInfo; + WorkloadInfo workloadInfo; - std::vector<std::unique_ptr<armnn::ITensorHandle>> inputHandles; + std::vector<std::unique_ptr<ITensorHandle>> inputHandles; inputHandles.reserve(inputCount); - std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + std::unique_ptr<ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); - armnn::ConcatQueueDescriptor queueDescriptor; - armnn::OriginsDescriptor viewsDescriptor = CreateDescriptorForConcat(inputTensorInfos, concatDim); + ConcatQueueDescriptor queueDescriptor; + OriginsDescriptor viewsDescriptor = CreateDescriptorForConcat(inputTensorInfos, concatDim); queueDescriptor.m_Parameters = viewsDescriptor; if (useSubtensor) @@ -337,8 +341,8 @@ template<typename T> void Concatenate( const bool subTensorsSupported = workloadFactory.SupportsSubTensors(); for (unsigned int i = 0; i < inputCount; ++i) { - const armnn::TensorInfo& inputTensorInfo = inputTensorInfos[i]; - std::unique_ptr<armnn::ITensorHandle> inputHandle = + const TensorInfo& inputTensorInfo = inputTensorInfos[i]; + std::unique_ptr<ITensorHandle> inputHandle = subTensorsSupported ? workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo.GetShape(), @@ -353,7 +357,7 @@ template<typename T> void Concatenate( { for (unsigned int i = 0; i < inputCount; ++i) { - std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfos[i]); + std::unique_ptr<ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfos[i]); inputHandles.emplace_back(std::move(inputHandle)); } } @@ -365,7 +369,7 @@ template<typename T> void Concatenate( AddOutputToWorkload(queueDescriptor, workloadInfo, outputTensorInfo, outputHandle.get()); - std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConcat(queueDescriptor, workloadInfo); + std::unique_ptr<IWorkload> workload = workloadFactory.CreateConcat(queueDescriptor, workloadInfo); for (auto& inputHandle : inputHandles) { @@ -403,20 +407,20 @@ template<typename T> void Concatenate( // Implementation templates // -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 1> Concat1dTestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - armnn::TensorInfo inputTensorInfo({ 3 }, ArmnnType, qScale, qOffset); + TensorInfo inputTensorInfo({ 3 }, ArmnnType, qScale, qOffset); - auto input0 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { 1.0f, 2.0f, 3.0f })); - auto input1 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { 4.0f, 5.0f, 6.0f })); - auto input2 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { 7.0f, 8.0f, 9.0f })); + auto input0 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>({ 1.0f, 2.0f, 3.0f }, qScale, qOffset)); + auto input1 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>({ 4.0f, 5.0f, 6.0f }, qScale, qOffset)); + auto input2 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>({ 7.0f, 8.0f, 9.0f }, qScale, qOffset)); - armnn::TensorInfo outputTensorInfo({ 9 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 9 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 1> result(outputTensorInfo); @@ -430,48 +434,56 @@ LayerTestResult<T, 1> Concat1dTestImpl( 0, true); - result.output = MakeTensor<T, 1>(outputTensorInfo, output); - result.outputExpected = MakeTensor<T, 1>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f - })); + result.output = MakeTensor<T, 1>(outputTensorInfo, output); + result.outputExpected = MakeTensor<T, 1>(outputTensorInfo, QuantizedVector<T>( + { + 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 2> Concat2dTestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::TensorInfo& outputTensorInfo, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const TensorInfo& outputTensorInfo, unsigned int dimension, const float qScale, const int32_t qOffset) { - armnn::TensorInfo inputTensorInfo({ 2, 3 }, ArmnnType, qScale, qOffset); + TensorInfo inputTensorInfo({ 2, 3 }, ArmnnType, qScale, qOffset); - auto input0 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0 - 1.0f, 2.0f, 3.0f, + auto input0 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>( + { + // Batch 0 + 1.0f, 2.0f, 3.0f, - // Batch 1 - 10.0f, 11.0f, 12.0f, - })); + // Batch 1 + 10.0f, 11.0f, 12.0f, + }, + qScale, qOffset)); - auto input1 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0 - 4.0f, 5.0f, 6.0f, + auto input1 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>( + { + // Batch 0 + 4.0f, 5.0f, 6.0f, - // Batch 1 - 13.0f, 14.0f, 15.0f, - })); + // Batch 1 + 13.0f, 14.0f, 15.0f, + }, + qScale, qOffset)); - auto input2 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0 - 7.0f, 8.0f, 9.0f, + auto input2 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>( + { + // Batch 0 + 7.0f, 8.0f, 9.0f, - // Batch 1 - 16.0f, 17.0f, 18.0f, - })); + // Batch 1 + 16.0f, 17.0f, 18.0f, + }, + qScale, qOffset)); LayerTestResult<T, 2> result(outputTensorInfo); @@ -489,99 +501,109 @@ LayerTestResult<T, 2> Concat2dTestImpl( return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 2> Concat2dDim0TestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - armnn::TensorInfo outputTensorInfo({ 6, 3 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 6, 3 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 2> result = Concat2dTestImpl<ArmnnType>( workloadFactory, memoryManager, outputTensorInfo, 0, qScale, qOffset); - result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0 - 1.0f, 2.0f, 3.0f, + result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>( + { + // Batch 0 + 1.0f, 2.0f, 3.0f, - // Batch 1 - 10.0f, 11.0f, 12.0f, + // Batch 1 + 10.0f, 11.0f, 12.0f, - // Batch 2 - 4.0f, 5.0f, 6.0f, + // Batch 2 + 4.0f, 5.0f, 6.0f, - // Batch 3 - 13.0f, 14.0f, 15.0f, + // Batch 3 + 13.0f, 14.0f, 15.0f, - // Batch 4 - 7.0f, 8.0f, 9.0f, + // Batch 4 + 7.0f, 8.0f, 9.0f, - // Batch 5 - 16.0f, 17.0f, 18.0f, - })); + // Batch 5 + 16.0f, 17.0f, 18.0f, + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 2> Concat2dDim1TestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - armnn::TensorInfo outputTensorInfo({ 2, 9 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 2, 9 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 2> result = Concat2dTestImpl<ArmnnType>( workloadFactory, memoryManager, outputTensorInfo, 1, qScale, qOffset); - result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0 - 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, + result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>( + { + // Batch 0 + 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, - // Batch 1 - 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f - })); + // Batch 1 + 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 2> Concat2dDim0DiffInputDimsTestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - armnn::TensorInfo input0TensorInfo({ 2, 3 }, ArmnnType, qScale, qOffset); - auto input0 = MakeTensor<T, 2>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0 - 1.0f, 2.0f, 3.0f, + TensorInfo input0TensorInfo({ 2, 3 }, ArmnnType, qScale, qOffset); + auto input0 = MakeTensor<T, 2>(input0TensorInfo, QuantizedVector<T>( + { + // Batch 0 + 1.0f, 2.0f, 3.0f, - // Batch 1 - 10.0f, 11.0f, 12.0f, - })); + // Batch 1 + 10.0f, 11.0f, 12.0f, + }, + qScale, qOffset)); - armnn::TensorInfo input1TensorInfo({ 3, 3 }, ArmnnType, qScale, qOffset); - auto input1 = MakeTensor<T, 2>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0 - 4.0f, 5.0f, 6.0f, + TensorInfo input1TensorInfo({ 3, 3 }, ArmnnType, qScale, qOffset); + auto input1 = MakeTensor<T, 2>(input1TensorInfo, QuantizedVector<T>( + { + // Batch 0 + 4.0f, 5.0f, 6.0f, - // Batch 1 - 13.0f, 14.0f, 15.0f, + // Batch 1 + 13.0f, 14.0f, 15.0f, - // Batch 0 - 7.0f, 8.0f, 9.0f, - })); + // Batch 0 + 7.0f, 8.0f, 9.0f, + }, + qScale, qOffset)); - armnn::TensorInfo input2TensorInfo({ 1, 3 }, ArmnnType, qScale, qOffset); - auto input2 = MakeTensor<T, 2>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 1 - 16.0f, 17.0f, 18.0f, - })); + TensorInfo input2TensorInfo({ 1, 3 }, ArmnnType, qScale, qOffset); + auto input2 = MakeTensor<T, 2>(input2TensorInfo, QuantizedVector<T>( + { + // Batch 1 + 16.0f, 17.0f, 18.0f, + }, + qScale, qOffset)); - armnn::TensorInfo outputTensorInfo({ 6, 3 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 6, 3 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 2> result(outputTensorInfo); std::vector<T> output; @@ -595,64 +617,72 @@ LayerTestResult<T, 2> Concat2dDim0DiffInputDimsTestImpl( true); result.output = MakeTensor<T, 2>(outputTensorInfo, output); - result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0 - 1.0f, 2.0f, 3.0f, + result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>( + { + // Batch 0 + 1.0f, 2.0f, 3.0f, - // Batch 1 - 10.0f, 11.0f, 12.0f, + // Batch 1 + 10.0f, 11.0f, 12.0f, - // Batch 2 - 4.0f, 5.0f, 6.0f, + // Batch 2 + 4.0f, 5.0f, 6.0f, - // Batch 3 - 13.0f, 14.0f, 15.0f, + // Batch 3 + 13.0f, 14.0f, 15.0f, - // Batch 4 - 7.0f, 8.0f, 9.0f, + // Batch 4 + 7.0f, 8.0f, 9.0f, - // Batch 5 - 16.0f, 17.0f, 18.0f, - })); + // Batch 5 + 16.0f, 17.0f, 18.0f, + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 2> Concat2dDim1DiffInputDimsTestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - armnn::TensorInfo input0TensorInfo({ 2, 3 }, ArmnnType, qScale, qOffset); - auto input0 = MakeTensor<T, 2>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0 - 1.0f, 2.0f, 3.0f, + TensorInfo input0TensorInfo({ 2, 3 }, ArmnnType, qScale, qOffset); + auto input0 = MakeTensor<T, 2>(input0TensorInfo, QuantizedVector<T>( + { + // Batch 0 + 1.0f, 2.0f, 3.0f, - // Batch 1 - 10.0f, 11.0f, 12.0f, - })); + // Batch 1 + 10.0f, 11.0f, 12.0f, + }, + qScale, qOffset)); - armnn::TensorInfo input1TensorInfo({ 2, 5 }, ArmnnType, qScale, qOffset); - auto input1 = MakeTensor<T, 2>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0 - 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, + TensorInfo input1TensorInfo({ 2, 5 }, ArmnnType, qScale, qOffset); + auto input1 = MakeTensor<T, 2>(input1TensorInfo, QuantizedVector<T>( + { + // Batch 0 + 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, - // Batch 1 - 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, - })); + // Batch 1 + 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, + }, + qScale, qOffset)); - armnn::TensorInfo input2TensorInfo({ 2, 1 }, ArmnnType, qScale, qOffset); - auto input2 = MakeTensor<T, 2>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0 - 9.0f, + TensorInfo input2TensorInfo({ 2, 1 }, ArmnnType, qScale, qOffset); + auto input2 = MakeTensor<T, 2>(input2TensorInfo, QuantizedVector<T>( + { + // Batch 0 + 9.0f, - // Batch 1 - 18.0f - })); + // Batch 1 + 18.0f + }, + qScale, qOffset)); - armnn::TensorInfo outputTensorInfo({ 2, 9 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 2, 9 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 2> result(outputTensorInfo); std::vector<T> output; @@ -666,88 +696,96 @@ LayerTestResult<T, 2> Concat2dDim1DiffInputDimsTestImpl( true); result.output = MakeTensor<T, 2>(outputTensorInfo, output); - result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0 - 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, + result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>( + { + // Batch 0 + 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, - // Batch 1 - 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, - })); + // Batch 1 + 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 3> Concat3dTestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::TensorInfo& outputTensorInfo, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const TensorInfo& outputTensorInfo, unsigned int dimension, bool useSubtensor, float qScale, int32_t qOffset) { - armnn::TensorInfo inputTensorInfo({ 2, 3, 2 }, ArmnnType, qScale, qOffset); + TensorInfo inputTensorInfo({ 2, 3, 2 }, ArmnnType, qScale, qOffset); - auto input0 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 1.0f, 2.0f, + auto input0 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 1.0f, 2.0f, - // Batch 0, Channel 1 - 3.0f, 4.0f, + // Batch 0, Channel 1 + 3.0f, 4.0f, - // Batch 0, Channel 2 - 5.0f, 6.0f, + // Batch 0, Channel 2 + 5.0f, 6.0f, - // Batch 1, Channel 0 - 19.0f, 20.0f, + // Batch 1, Channel 0 + 19.0f, 20.0f, - // Batch 1, Channel 1 - 21.0f, 22.0f, + // Batch 1, Channel 1 + 21.0f, 22.0f, - // Batch 1, Channel 2 - 23.0f, 24.0f - })); + // Batch 1, Channel 2 + 23.0f, 24.0f + }, + qScale, qOffset)); - auto input1 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 7.0f, 8.0f, + auto input1 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 7.0f, 8.0f, - // Batch 0, Channel 1 - 9.0f, 10.0f, + // Batch 0, Channel 1 + 9.0f, 10.0f, - // Batch 0, Channel 2 - 11.0f, 12.0f, + // Batch 0, Channel 2 + 11.0f, 12.0f, - // Batch 1, Channel 0 - 25.0f, 26.0f, + // Batch 1, Channel 0 + 25.0f, 26.0f, - // Batch 1, Channel 1 - 27.0f, 28.0f, + // Batch 1, Channel 1 + 27.0f, 28.0f, - // Batch 1, Channel 2 - 29.0f, 30.0f - })); + // Batch 1, Channel 2 + 29.0f, 30.0f + }, + qScale, qOffset)); - auto input2 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 13.0f, 14.0f, + auto input2 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 13.0f, 14.0f, - // Batch 0, Channel 1 - 15.0f, 16.0f, + // Batch 0, Channel 1 + 15.0f, 16.0f, - // Batch 0, Channel 2 - 17.0f, 18.0f, + // Batch 0, Channel 2 + 17.0f, 18.0f, - // Batch 1, Channel 0 - 31.0f, 32.0f, + // Batch 1, Channel 0 + 31.0f, 32.0f, - // Batch 1, Channel 1 - 33.0f, 34.0f, + // Batch 1, Channel 1 + 33.0f, 34.0f, - // Batch 1, Channel 2 - 35.0f, 36.0f - })); + // Batch 1, Channel 2 + 35.0f, 36.0f + }, + qScale, qOffset)); LayerTestResult<T, 3> result(outputTensorInfo); @@ -765,193 +803,200 @@ LayerTestResult<T, 3> Concat3dTestImpl( return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 3> Concat3dDim0TestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - armnn::TensorInfo outputTensorInfo({ 6, 3, 2 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 6, 3, 2 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 3> result = Concat3dTestImpl<ArmnnType>( workloadFactory, memoryManager, outputTensorInfo, 0, true, qScale, qOffset); - result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 1.0f, 2.0f, + result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 1.0f, 2.0f, - // Batch 0, Channel 1 - 3.0f, 4.0f, + // Batch 0, Channel 1 + 3.0f, 4.0f, - // Batch 0, Channel 2 - 5.0f, 6.0f, + // Batch 0, Channel 2 + 5.0f, 6.0f, - // Batch 1, Channel 0 - 19.0f, 20.0f, + // Batch 1, Channel 0 + 19.0f, 20.0f, - // Batch 1, Channel 1 - 21.0f, 22.0f, + // Batch 1, Channel 1 + 21.0f, 22.0f, - // Batch 1, Channel 2 - 23.0f, 24.0f, + // Batch 1, Channel 2 + 23.0f, 24.0f, - // Batch 2, Channel 0 - 7.0f, 8.0f, + // Batch 2, Channel 0 + 7.0f, 8.0f, - // Batch 2, Channel 1 - 9.0f, 10.0f, + // Batch 2, Channel 1 + 9.0f, 10.0f, - // Batch 2, Channel 2 - 11.0f, 12.0f, + // Batch 2, Channel 2 + 11.0f, 12.0f, - // Batch 3, Channel 0 - 25.0f, 26.0f, + // Batch 3, Channel 0 + 25.0f, 26.0f, - // Batch 3, Channel 1 - 27.0f, 28.0f, + // Batch 3, Channel 1 + 27.0f, 28.0f, - // Batch 3, Channel 2 - 29.0f, 30.0f, + // Batch 3, Channel 2 + 29.0f, 30.0f, - // Batch 4, Channel 0 - 13.0f, 14.0f, + // Batch 4, Channel 0 + 13.0f, 14.0f, - // Batch 4, Channel 1 - 15.0f, 16.0f, + // Batch 4, Channel 1 + 15.0f, 16.0f, - // Batch 4, Channel 2 - 17.0f, 18.0f, + // Batch 4, Channel 2 + 17.0f, 18.0f, - // Batch 5, Channel 0 - 31.0f, 32.0f, + // Batch 5, Channel 0 + 31.0f, 32.0f, - // Batch 5, Channel 1 - 33.0f, 34.0f, + // Batch 5, Channel 1 + 33.0f, 34.0f, - // Batch 5, Channel 2 - 35.0f, 36.0f - })); + // Batch 5, Channel 2 + 35.0f, 36.0f + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 3> Concat3dDim1TestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - armnn::TensorInfo outputTensorInfo({ 2, 9, 2 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 2, 9, 2 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 3> result = Concat3dTestImpl<ArmnnType>( workloadFactory, memoryManager, outputTensorInfo, 1, true, qScale, qOffset); - result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 1.0f, 2.0f, + result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 1.0f, 2.0f, - // Batch 0, Channel 1 - 3.0f, 4.0f, + // Batch 0, Channel 1 + 3.0f, 4.0f, - // Batch 0, Channel 2 - 5.0f, 6.0f, + // Batch 0, Channel 2 + 5.0f, 6.0f, - // Batch 0, Channel 3 - 7.0f, 8.0f, + // Batch 0, Channel 3 + 7.0f, 8.0f, - // Batch 0, Channel 4 - 9.0f, 10.0f, + // Batch 0, Channel 4 + 9.0f, 10.0f, - // Batch 0, Channel 5 - 11.0f, 12.0f, + // Batch 0, Channel 5 + 11.0f, 12.0f, - // Batch 0, Channel 6 - 13.0f, 14.0f, + // Batch 0, Channel 6 + 13.0f, 14.0f, - // Batch 0, Channel 7 - 15.0f, 16.0f, + // Batch 0, Channel 7 + 15.0f, 16.0f, - // Batch 0, Channel 8 - 17.0f, 18.0f, + // Batch 0, Channel 8 + 17.0f, 18.0f, - // Batch 1, Channel 0 - 19.0f, 20.0f, + // Batch 1, Channel 0 + 19.0f, 20.0f, - // Batch 1, Channel 1 - 21.0f, 22.0f, + // Batch 1, Channel 1 + 21.0f, 22.0f, - // Batch 1, Channel 2 - 23.0f, 24.0f, + // Batch 1, Channel 2 + 23.0f, 24.0f, - // Batch 1, Channel 3 - 25.0f, 26.0f, + // Batch 1, Channel 3 + 25.0f, 26.0f, - // Batch 1, Channel 4 - 27.0f, 28.0f, + // Batch 1, Channel 4 + 27.0f, 28.0f, - // Batch 1, Channel 5 - 29.0f, 30.0f, + // Batch 1, Channel 5 + 29.0f, 30.0f, - // Batch 1, Channel 6 - 31.0f, 32.0f, + // Batch 1, Channel 6 + 31.0f, 32.0f, - // Batch 1, Channel 7 - 33.0f, 34.0f, + // Batch 1, Channel 7 + 33.0f, 34.0f, - // Batch 1, Channel 8 - 35.0f, 36.0f - })); + // Batch 1, Channel 8 + 35.0f, 36.0f + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 3> Concat3dDim2TestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor, float qScale, int32_t qOffset) { - armnn::TensorInfo outputTensorInfo({ 2, 3, 6 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 2, 3, 6 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 3> result = Concat3dTestImpl<ArmnnType>( workloadFactory, memoryManager, outputTensorInfo, 2, useSubtensor, qScale, qOffset); - result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 1.0f, 2.0f, 7.0f, 8.0f, 13.0f, 14.0f, + result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 1.0f, 2.0f, 7.0f, 8.0f, 13.0f, 14.0f, - // Batch 0, Channel 1 - 3.0f, 4.0f, 9.0f, 10.0f, 15.0f, 16.0f, + // Batch 0, Channel 1 + 3.0f, 4.0f, 9.0f, 10.0f, 15.0f, 16.0f, - // Batch 0, Channel 2 - 5.0f, 6.0f, 11.0f, 12.0f, 17.0f, 18.0f, + // Batch 0, Channel 2 + 5.0f, 6.0f, 11.0f, 12.0f, 17.0f, 18.0f, - // Batch 1, Channel 0 - 19.0f, 20.0f, 25.0f, 26.0f, 31.0f, 32.0f, + // Batch 1, Channel 0 + 19.0f, 20.0f, 25.0f, 26.0f, 31.0f, 32.0f, - // Batch 1, Channel 1 - 21.0f, 22.0f, 27.0f, 28.0f, 33.0f, 34.0f, + // Batch 1, Channel 1 + 21.0f, 22.0f, 27.0f, 28.0f, 33.0f, 34.0f, - // Batch 1, Channel 2 - 23.0f, 24.0f, 29.0f, 30.0f, 35.0f, 36.0f, - })); + // Batch 1, Channel 2 + 23.0f, 24.0f, 29.0f, 30.0f, 35.0f, 36.0f, + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 3> Concat3dDim0DiffInputDimsTestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - armnn::TensorInfo input0TensorInfo({ 2, 3, 2 }, ArmnnType); - auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { + TensorInfo input0TensorInfo({ 2, 3, 2 }, ArmnnType); + auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>( + { // Batch 0, Channel 0 1.0f, 2.0f, @@ -969,10 +1014,12 @@ LayerTestResult<T, 3> Concat3dDim0DiffInputDimsTestImpl( // Batch 1, Channel 2 23.0f, 24.0f - })); + }, + qScale, qOffset)); - armnn::TensorInfo input1TensorInfo({ 1, 3, 2 }, ArmnnType); - auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { + TensorInfo input1TensorInfo({ 1, 3, 2 }, ArmnnType); + auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>( + { // Batch 0, Channel 0 7.0f, 8.0f, @@ -981,10 +1028,12 @@ LayerTestResult<T, 3> Concat3dDim0DiffInputDimsTestImpl( // Batch 0, Channel 2 11.0f, 12.0f, - })); + }, + qScale, qOffset)); - armnn::TensorInfo input2TensorInfo({ 3, 3, 2 }, ArmnnType); - auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { + TensorInfo input2TensorInfo({ 3, 3, 2 }, ArmnnType); + auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>( + { // Batch 0, Channel 0 25.0f, 26.0f, @@ -1011,9 +1060,10 @@ LayerTestResult<T, 3> Concat3dDim0DiffInputDimsTestImpl( // Batch 2, Channel 2 35.0f, 36.0f - })); + }, + qScale, qOffset)); - armnn::TensorInfo outputTensorInfo({ 6, 3, 2 }, ArmnnType); + TensorInfo outputTensorInfo({ 6, 3, 2 }, ArmnnType); LayerTestResult<T, 3> result(outputTensorInfo); std::vector<T> output; @@ -1027,130 +1077,138 @@ LayerTestResult<T, 3> Concat3dDim0DiffInputDimsTestImpl( true); result.output = MakeTensor<T, 3>(outputTensorInfo, output); - result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 1.0f, 2.0f, + result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 1.0f, 2.0f, - // Batch 0, Channel 1 - 3.0f, 4.0f, + // Batch 0, Channel 1 + 3.0f, 4.0f, - // Batch 0, Channel 2 - 5.0f, 6.0f, + // Batch 0, Channel 2 + 5.0f, 6.0f, - // Batch 1, Channel 0 - 19.0f, 20.0f, + // Batch 1, Channel 0 + 19.0f, 20.0f, - // Batch 1, Channel 1 - 21.0f, 22.0f, + // Batch 1, Channel 1 + 21.0f, 22.0f, - // Batch 1, Channel 2 - 23.0f, 24.0f, + // Batch 1, Channel 2 + 23.0f, 24.0f, - // Batch 2, Channel 0 - 7.0f, 8.0f, + // Batch 2, Channel 0 + 7.0f, 8.0f, - // Batch 2, Channel 1 - 9.0f, 10.0f, + // Batch 2, Channel 1 + 9.0f, 10.0f, - // Batch 2, Channel 2 - 11.0f, 12.0f, + // Batch 2, Channel 2 + 11.0f, 12.0f, - // Batch 3, Channel 0 - 25.0f, 26.0f, + // Batch 3, Channel 0 + 25.0f, 26.0f, - // Batch 3, Channel 1 - 27.0f, 28.0f, + // Batch 3, Channel 1 + 27.0f, 28.0f, - // Batch 3, Channel 2 - 29.0f, 30.0f, + // Batch 3, Channel 2 + 29.0f, 30.0f, - // Batch 4, Channel 0 - 13.0f, 14.0f, + // Batch 4, Channel 0 + 13.0f, 14.0f, - // Batch 4, Channel 1 - 15.0f, 16.0f, + // Batch 4, Channel 1 + 15.0f, 16.0f, - // Batch 4, Channel 2 - 17.0f, 18.0f, + // Batch 4, Channel 2 + 17.0f, 18.0f, - // Batch 5, Channel 0 - 31.0f, 32.0f, + // Batch 5, Channel 0 + 31.0f, 32.0f, - // Batch 5, Channel 1 - 33.0f, 34.0f, + // Batch 5, Channel 1 + 33.0f, 34.0f, - // Batch 5, Channel 2 - 35.0f, 36.0f - })); + // Batch 5, Channel 2 + 35.0f, 36.0f + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 3> Concat3dDim1DiffInputDimsTestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - armnn::TensorInfo input0TensorInfo({ 2, 3, 2 }, ArmnnType, qScale, qOffset); - auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 1.0f, 2.0f, + TensorInfo input0TensorInfo({ 2, 3, 2 }, ArmnnType, qScale, qOffset); + auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 1.0f, 2.0f, - // Batch 0, Channel 1 - 3.0f, 4.0f, + // Batch 0, Channel 1 + 3.0f, 4.0f, - // Batch 0, Channel 2 - 5.0f, 6.0f, + // Batch 0, Channel 2 + 5.0f, 6.0f, - // Batch 1, Channel 0 - 19.0f, 20.0f, + // Batch 1, Channel 0 + 19.0f, 20.0f, - // Batch 1, Channel 1 - 21.0f, 22.0f, + // Batch 1, Channel 1 + 21.0f, 22.0f, - // Batch 1, Channel 2 - 23.0f, 24.0f - })); + // Batch 1, Channel 2 + 23.0f, 24.0f + }, + qScale, qOffset)); - armnn::TensorInfo input1TensorInfo({ 2, 4, 2 }, ArmnnType, qScale, qOffset); - auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 7.0f, 8.0f, + TensorInfo input1TensorInfo({ 2, 4, 2 }, ArmnnType, qScale, qOffset); + auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 7.0f, 8.0f, - // Batch 0, Channel 1 - 9.0f, 10.0f, + // Batch 0, Channel 1 + 9.0f, 10.0f, - // Batch 0, Channel 2 - 11.0f, 12.0f, + // Batch 0, Channel 2 + 11.0f, 12.0f, - // Batch 0, Channel 3 - 25.0f, 26.0f, + // Batch 0, Channel 3 + 25.0f, 26.0f, - // Batch 1, Channel 0 - 27.0f, 28.0f, + // Batch 1, Channel 0 + 27.0f, 28.0f, - // Batch 1, Channel 1 - 29.0f, 30.0f, + // Batch 1, Channel 1 + 29.0f, 30.0f, - // Batch 1, Channel 2 - 13.0f, 14.0f, + // Batch 1, Channel 2 + 13.0f, 14.0f, - // Batch 1, Channel 3 - 15.0f, 16.0f, - })); + // Batch 1, Channel 3 + 15.0f, 16.0f, + }, + qScale, qOffset)); - armnn::TensorInfo input2TensorInfo({ 2, 1, 2 }, ArmnnType, qScale, qOffset); - auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 17.0f, 18.0f, + TensorInfo input2TensorInfo({ 2, 1, 2 }, ArmnnType, qScale, qOffset); + auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 17.0f, 18.0f, - // Batch 1, Channel 0 - 31.0f, 32.0f, - })); + // Batch 1, Channel 0 + 31.0f, 32.0f, + }, + qScale, qOffset)); - armnn::TensorInfo outputTensorInfo({ 2, 8, 2 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 2, 8, 2 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 3> result(outputTensorInfo); std::vector<T> output; @@ -1164,131 +1222,139 @@ LayerTestResult<T, 3> Concat3dDim1DiffInputDimsTestImpl( true); result.output = MakeTensor<T, 3>(outputTensorInfo, output); - result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 1.0f, 2.0f, + result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 1.0f, 2.0f, - // Batch 0, Channel 1 - 3.0f, 4.0f, + // Batch 0, Channel 1 + 3.0f, 4.0f, - // Batch 0, Channel 2 - 5.0f, 6.0f, + // Batch 0, Channel 2 + 5.0f, 6.0f, - // Batch 0, Channel 3 - 7.0f, 8.0f, + // Batch 0, Channel 3 + 7.0f, 8.0f, - // Batch 0, Channel 4 - 9.0f, 10.0f, + // Batch 0, Channel 4 + 9.0f, 10.0f, - // Batch 0, Channel 5 - 11.0f, 12.0f, + // Batch 0, Channel 5 + 11.0f, 12.0f, - // Batch 0, Channel 6 - 25.0f, 26.0f, + // Batch 0, Channel 6 + 25.0f, 26.0f, - // Batch 0, Channel 7 - 17.0f, 18.0f, + // Batch 0, Channel 7 + 17.0f, 18.0f, - // Batch 1, Channel 0 - 19.0f, 20.0f, + // Batch 1, Channel 0 + 19.0f, 20.0f, - // Batch 1, Channel 1 - 21.0f, 22.0f, + // Batch 1, Channel 1 + 21.0f, 22.0f, - // Batch 1, Channel 2 - 23.0f, 24.0f, + // Batch 1, Channel 2 + 23.0f, 24.0f, - // Batch 1, Channel 3 - 27.0f, 28.0f, + // Batch 1, Channel 3 + 27.0f, 28.0f, - // Batch 1, Channel 4 - 29.0f, 30.0f, + // Batch 1, Channel 4 + 29.0f, 30.0f, - // Batch 1, Channel 5 - 13.0f, 14.0f, + // Batch 1, Channel 5 + 13.0f, 14.0f, - // Batch 1, Channel 6 - 15.0f, 16.0f, + // Batch 1, Channel 6 + 15.0f, 16.0f, - // Batch 1, Channel 7 - 31.0f, 32.0f, - })); + // Batch 1, Channel 7 + 31.0f, 32.0f, + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 3> Concat3dDim2DiffInputDimsTestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor, float qScale, int32_t qOffset) { - armnn::TensorInfo input0TensorInfo({ 2, 3, 2 }, ArmnnType, qScale, qOffset); - auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 1.0f, 2.0f, + TensorInfo input0TensorInfo({ 2, 3, 2 }, ArmnnType, qScale, qOffset); + auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 1.0f, 2.0f, - // Batch 0, Channel 1 - 3.0f, 4.0f, + // Batch 0, Channel 1 + 3.0f, 4.0f, - // Batch 0, Channel 2 - 5.0f, 6.0f, + // Batch 0, Channel 2 + 5.0f, 6.0f, - // Batch 1, Channel 0 - 19.0f, 20.0f, + // Batch 1, Channel 0 + 19.0f, 20.0f, - // Batch 1, Channel 1 - 21.0f, 22.0f, + // Batch 1, Channel 1 + 21.0f, 22.0f, - // Batch 1, Channel 2 - 23.0f, 24.0f - })); + // Batch 1, Channel 2 + 23.0f, 24.0f + }, + qScale, qOffset)); - armnn::TensorInfo input1TensorInfo({ 2, 3, 1 }, ArmnnType, qScale, qOffset); - auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 7.0f, + TensorInfo input1TensorInfo({ 2, 3, 1 }, ArmnnType, qScale, qOffset); + auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 7.0f, - // Batch 0, Channel 1 - 9.0f, + // Batch 0, Channel 1 + 9.0f, - // Batch 0, Channel 2 - 11.0f, + // Batch 0, Channel 2 + 11.0f, - // Batch 1, Channel 0 - 25.0f, + // Batch 1, Channel 0 + 25.0f, - // Batch 1, Channel 1 - 27.0f, + // Batch 1, Channel 1 + 27.0f, - // Batch 1, Channel 2 - 29.0f - })); + // Batch 1, Channel 2 + 29.0f + }, + qScale, qOffset)); - armnn::TensorInfo input2TensorInfo({ 2, 3, 3 }, ArmnnType, qScale, qOffset); - auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 13.0f, 14.0f, 50.0f, + TensorInfo input2TensorInfo({ 2, 3, 3 }, ArmnnType, qScale, qOffset); + auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 13.0f, 14.0f, 50.0f, - // Batch 0, Channel 1 - 15.0f, 16.0f, 51.0f, + // Batch 0, Channel 1 + 15.0f, 16.0f, 51.0f, - // Batch 0, Channel 2 - 17.0f, 18.0f, 52.0f, + // Batch 0, Channel 2 + 17.0f, 18.0f, 52.0f, - // Batch 1, Channel 0 - 31.0f, 32.0f, 53.0f, + // Batch 1, Channel 0 + 31.0f, 32.0f, 53.0f, - // Batch 1, Channel 1 - 33.0f, 34.0f, 54.0f, + // Batch 1, Channel 1 + 33.0f, 34.0f, 54.0f, - // Batch 1, Channel 2 - 35.0f, 36.0f, 55.0f, - })); + // Batch 1, Channel 2 + 35.0f, 36.0f, 55.0f, + }, + qScale, qOffset)); - armnn::TensorInfo outputTensorInfo({ 2, 3, 6 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 2, 3, 6 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 3> result(outputTensorInfo); std::vector<T> output; @@ -1302,67 +1368,75 @@ LayerTestResult<T, 3> Concat3dDim2DiffInputDimsTestImpl( useSubtensor); result.output = MakeTensor<T, 3>(outputTensorInfo, output); - result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - // Batch 0, Channel 0 - 1.0f, 2.0f, 7.0f, 13.0f, 14.0f, 50.0f, + result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>( + { + // Batch 0, Channel 0 + 1.0f, 2.0f, 7.0f, 13.0f, 14.0f, 50.0f, - // Batch 0, Channel 1 - 3.0f, 4.0f, 9.0f, 15.0f, 16.0f, 51.0f, + // Batch 0, Channel 1 + 3.0f, 4.0f, 9.0f, 15.0f, 16.0f, 51.0f, - // Batch 0, Channel 2 - 5.0f, 6.0f, 11.0f, 17.0f, 18.0f, 52.0f, + // Batch 0, Channel 2 + 5.0f, 6.0f, 11.0f, 17.0f, 18.0f, 52.0f, - // Batch 1, Channel 0 - 19.0f, 20.0f, 25.0f, 31.0f, 32.0f, 53.0f, + // Batch 1, Channel 0 + 19.0f, 20.0f, 25.0f, 31.0f, 32.0f, 53.0f, - // Batch 1, Channel 1 - 21.0f, 22.0f, 27.0f, 33.0f, 34.0f, 54.0f, + // Batch 1, Channel 1 + 21.0f, 22.0f, 27.0f, 33.0f, 34.0f, 54.0f, - // Batch 1, Channel 2 - 23.0f, 24.0f, 29.0f, 35.0f, 36.0f, 55.0f, - })); + // Batch 1, Channel 2 + 23.0f, 24.0f, 29.0f, 35.0f, 36.0f, 55.0f, + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 4> Concat4dTestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::TensorInfo& outputTensorInfo, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const TensorInfo& outputTensorInfo, unsigned int dimension, bool useSubtensor, float qScale, int32_t qOffset) { - armnn::TensorInfo inputTensorInfo({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset); + TensorInfo inputTensorInfo({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset); - auto input0 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, - 3.0f, 4.0f, - 5.0f, 6.0f, - 7.0f, 8.0f, - 9.0f, 10.0f, - 11.0f, 12.0f - })); - - auto input1 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - 11.0f, 12.0f, - 13.0f, 14.0f, - 15.0f, 16.0f, - 17.0f, 18.0f, - 19.0f, 20.0f, - 21.0f, 22.0f - })); + auto input0 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>( + { + 1.0f, 2.0f, + 3.0f, 4.0f, + 5.0f, 6.0f, + 7.0f, 8.0f, + 9.0f, 10.0f, + 11.0f, 12.0f + }, + qScale, qOffset)); + + auto input1 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>( + { + 11.0f, 12.0f, + 13.0f, 14.0f, + 15.0f, 16.0f, + 17.0f, 18.0f, + 19.0f, 20.0f, + 21.0f, 22.0f + }, + qScale, qOffset)); - auto input2 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - 21.0f, 22.0f, - 23.0f, 24.0f, - 25.0f, 26.0f, - 27.0f, 28.0f, - 29.0f, 30.0f, - 31.0f, 32.0f - })); + auto input2 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>( + { + 21.0f, 22.0f, + 23.0f, 24.0f, + 25.0f, 26.0f, + 27.0f, 28.0f, + 29.0f, 30.0f, + 31.0f, 32.0f + }, + qScale, qOffset)); LayerTestResult<T, 4> result(outputTensorInfo); @@ -1382,197 +1456,209 @@ LayerTestResult<T, 4> Concat4dTestImpl( return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 4> Concat4dDim0TestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - armnn::TensorInfo outputTensorInfo({ 3, 3, 2, 2 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 3, 3, 2, 2 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 4> result = Concat4dTestImpl<ArmnnType>( workloadFactory, memoryManager, outputTensorInfo, 0, true, qScale, qOffset); - result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, - 3.0f, 4.0f, - 5.0f, 6.0f, - 7.0f, 8.0f, - 9.0f, 10.0f, - 11.0f, 12.0f, - - 11.0f, 12.0f, - 13.0f, 14.0f, - 15.0f, 16.0f, - 17.0f, 18.0f, - 19.0f, 20.0f, - 21.0f, 22.0f, - - 21.0f, 22.0f, - 23.0f, 24.0f, - 25.0f, 26.0f, - 27.0f, 28.0f, - 29.0f, 30.0f, - 31.0f, 32.0f - })); + result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>( + { + 1.0f, 2.0f, + 3.0f, 4.0f, + 5.0f, 6.0f, + 7.0f, 8.0f, + 9.0f, 10.0f, + 11.0f, 12.0f, + + 11.0f, 12.0f, + 13.0f, 14.0f, + 15.0f, 16.0f, + 17.0f, 18.0f, + 19.0f, 20.0f, + 21.0f, 22.0f, + + 21.0f, 22.0f, + 23.0f, 24.0f, + 25.0f, 26.0f, + 27.0f, 28.0f, + 29.0f, 30.0f, + 31.0f, 32.0f + }, + qScale, qOffset)); + return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 4> Concat4dDim1TestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - armnn::TensorInfo outputTensorInfo({ 1, 9, 2, 2 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 1, 9, 2, 2 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 4> result = Concat4dTestImpl<ArmnnType>( workloadFactory, memoryManager, outputTensorInfo, 1, true, qScale, qOffset); - result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, - 3.0f, 4.0f, - 5.0f, 6.0f, - 7.0f, 8.0f, - 9.0f, 10.0f, - 11.0f, 12.0f, - - 11.0f, 12.0f, - 13.0f, 14.0f, - 15.0f, 16.0f, - 17.0f, 18.0f, - 19.0f, 20.0f, - 21.0f, 22.0f, - - 21.0f, 22.0f, - 23.0f, 24.0f, - 25.0f, 26.0f, - 27.0f, 28.0f, - 29.0f, 30.0f, - 31.0f, 32.0f - })); + result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>( + { + 1.0f, 2.0f, + 3.0f, 4.0f, + 5.0f, 6.0f, + 7.0f, 8.0f, + 9.0f, 10.0f, + 11.0f, 12.0f, + + 11.0f, 12.0f, + 13.0f, 14.0f, + 15.0f, 16.0f, + 17.0f, 18.0f, + 19.0f, 20.0f, + 21.0f, 22.0f, + + 21.0f, 22.0f, + 23.0f, 24.0f, + 25.0f, 26.0f, + 27.0f, 28.0f, + 29.0f, 30.0f, + 31.0f, 32.0f + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 4> Concat4dDim2TestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - armnn::TensorInfo outputTensorInfo({ 1, 3, 6, 2 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 1, 3, 6, 2 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 4> result = Concat4dTestImpl<ArmnnType>( workloadFactory, memoryManager, outputTensorInfo, 2, true, qScale, qOffset); - result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, - 3.0f, 4.0f, - 11.0f, 12.0f, - 13.0f, 14.0f, - 21.0f, 22.0f, - 23.0f, 24.0f, - - 5.0f, 6.0f, - 7.0f, 8.0f, - 15.0f, 16.0f, - 17.0f, 18.0f, - 25.0f, 26.0f, - 27.0f, 28.0f, - - 9.0f, 10.0f, - 11.0f, 12.0f, - 19.0f, 20.0f, - 21.0f, 22.0f, - 29.0f, 30.0f, - 31.0f, 32.0f - })); + result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>( + { + 1.0f, 2.0f, + 3.0f, 4.0f, + 11.0f, 12.0f, + 13.0f, 14.0f, + 21.0f, 22.0f, + 23.0f, 24.0f, + + 5.0f, 6.0f, + 7.0f, 8.0f, + 15.0f, 16.0f, + 17.0f, 18.0f, + 25.0f, 26.0f, + 27.0f, 28.0f, + + 9.0f, 10.0f, + 11.0f, 12.0f, + 19.0f, 20.0f, + 21.0f, 22.0f, + 29.0f, 30.0f, + 31.0f, 32.0f + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 4> Concat4dDim3TestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset, bool useSubtensor) { - armnn::TensorInfo outputTensorInfo({ 1, 3, 2, 6 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 1, 3, 2, 6 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 4> result = Concat4dTestImpl<ArmnnType>( workloadFactory, memoryManager, outputTensorInfo, 3, useSubtensor, qScale, qOffset); - result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, - 11.0f, 12.0f, - 21.0f, 22.0f, - 3.0f, 4.0f, - 13.0f, 14.0f, - 23.0f, 24.0f, - - 5.0f, 6.0f, - 15.0f, 16.0f, - 25.0f, 26.0f, - 7.0f, 8.0f, - 17.0f, 18.0f, - 27.0f, 28.0f, - - 9.0f, 10.0f, - 19.0f, 20.0f, - 29.0f, 30.0f, - 11.0f, 12.0f, - 21.0f, 22.0f, - 31.0f, 32.0f - })); + result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>( + { + 1.0f, 2.0f, + 11.0f, 12.0f, + 21.0f, 22.0f, + 3.0f, 4.0f, + 13.0f, 14.0f, + 23.0f, 24.0f, + + 5.0f, 6.0f, + 15.0f, 16.0f, + 25.0f, 26.0f, + 7.0f, 8.0f, + 17.0f, 18.0f, + 27.0f, 28.0f, + + 9.0f, 10.0f, + 19.0f, 20.0f, + 29.0f, 30.0f, + 11.0f, 12.0f, + 21.0f, 22.0f, + 31.0f, 32.0f + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 4> Concat4dDiffShapeDim0TestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - unsigned int dimension = 0; - armnn::TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset); + constexpr unsigned int dimension = 0u; - auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, - 3.0f, 4.0f, - 5.0f, 6.0f, - 7.0f, 8.0f, - 9.0f, 10.0f, - 11.0f, 12.0f - })); - - armnn::TensorInfo inputTensorInfo1({ 2, 3, 2, 2 }, ArmnnType, qScale, qOffset); - - auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, { - 11.0f, 12.0f, - 13.0f, 14.0f, - 15.0f, 16.0f, - 17.0f, 18.0f, - 19.0f, 20.0f, - 21.0f, 22.0f, - - 21.0f, 22.0f, - 23.0f, 24.0f, - 25.0f, 26.0f, - 27.0f, 28.0f, - 29.0f, 30.0f, - 31.0f, 32.0f + TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset); + auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>( + { + 1.0f, 2.0f, + 3.0f, 4.0f, + 5.0f, 6.0f, + 7.0f, 8.0f, + 9.0f, 10.0f, + 11.0f, 12.0f + }, + qScale, qOffset)); + + TensorInfo inputTensorInfo1({ 2, 3, 2, 2 }, ArmnnType, qScale, qOffset); + + auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>( + { + 11.0f, 12.0f, + 13.0f, 14.0f, + 15.0f, 16.0f, + 17.0f, 18.0f, + 19.0f, 20.0f, + 21.0f, 22.0f, - })); + 21.0f, 22.0f, + 23.0f, 24.0f, + 25.0f, 26.0f, + 27.0f, 28.0f, + 29.0f, 30.0f, + 31.0f, 32.0f + }, + qScale, qOffset)); - armnn::TensorInfo outputTensorInfo({ 3, 3, 2, 2 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 3, 3, 2, 2 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 4> result(outputTensorInfo); @@ -1588,62 +1674,67 @@ LayerTestResult<T, 4> Concat4dDiffShapeDim0TestImpl( true); result.output = MakeTensor<T, 4>(outputTensorInfo, output); - result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, - 3.0f, 4.0f, - 5.0f, 6.0f, - 7.0f, 8.0f, - 9.0f, 10.0f, - 11.0f, 12.0f, - - 11.0f, 12.0f, - 13.0f, 14.0f, - 15.0f, 16.0f, - 17.0f, 18.0f, - 19.0f, 20.0f, - 21.0f, 22.0f, - - 21.0f, 22.0f, - 23.0f, 24.0f, - 25.0f, 26.0f, - 27.0f, 28.0f, - 29.0f, 30.0f, - 31.0f, 32.0f - })); + result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>( + { + 1.0f, 2.0f, + 3.0f, 4.0f, + 5.0f, 6.0f, + 7.0f, 8.0f, + 9.0f, 10.0f, + 11.0f, 12.0f, + + 11.0f, 12.0f, + 13.0f, 14.0f, + 15.0f, 16.0f, + 17.0f, 18.0f, + 19.0f, 20.0f, + 21.0f, 22.0f, + + 21.0f, 22.0f, + 23.0f, 24.0f, + 25.0f, 26.0f, + 27.0f, 28.0f, + 29.0f, 30.0f, + 31.0f, 32.0f + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 4> Concat4dDiffShapeDim1TestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - unsigned int dimension = 1; - armnn::TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset); - - auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, - 3.0f, 4.0f, - 5.0f, 6.0f, - 7.0f, 8.0f, - 9.0f, 10.0f, - 11.0f, 12.0f - })); - - armnn::TensorInfo inputTensorInfo1({ 1, 2, 2, 2 }, ArmnnType, qScale, qOffset); + constexpr unsigned int dimension = 1u; - auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, { - 11.0f, 12.0f, - 13.0f, 14.0f, - 15.0f, 16.0f, - 17.0f, 18.0f, - - })); + TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset); + auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>( + { + 1.0f, 2.0f, + 3.0f, 4.0f, + 5.0f, 6.0f, + 7.0f, 8.0f, + 9.0f, 10.0f, + 11.0f, 12.0f + }, + qScale, qOffset)); + + TensorInfo inputTensorInfo1({ 1, 2, 2, 2 }, ArmnnType, qScale, qOffset); + + auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>( + { + 11.0f, 12.0f, + 13.0f, 14.0f, + 15.0f, 16.0f, + 17.0f, 18.0f, + }, + qScale, qOffset)); - armnn::TensorInfo outputTensorInfo({ 1, 5, 2, 2 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 1, 5, 2, 2 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 4> result(outputTensorInfo); @@ -1659,57 +1750,61 @@ LayerTestResult<T, 4> Concat4dDiffShapeDim1TestImpl( true); result.output = MakeTensor<T, 4>(outputTensorInfo, output); - result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, - 3.0f, 4.0f, - 5.0f, 6.0f, - 7.0f, 8.0f, - 9.0f, 10.0f, - 11.0f, 12.0f, - 11.0f, 12.0f, - 13.0f, 14.0f, - 15.0f, 16.0f, - 17.0f, 18.0f - })); + result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>( + { + 1.0f, 2.0f, + 3.0f, 4.0f, + 5.0f, 6.0f, + 7.0f, 8.0f, + 9.0f, 10.0f, + 11.0f, 12.0f, + 11.0f, 12.0f, + 13.0f, 14.0f, + 15.0f, 16.0f, + 17.0f, 18.0f + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 4> Concat4dDiffShapeDim2TestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset) { - unsigned int dimension = 2; - armnn::TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset); + constexpr unsigned int dimension = 2u; - auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, - 3.0f, 4.0f, - 5.0f, 6.0f, - 7.0f, 8.0f, - 9.0f, 10.0f, - 11.0f, 12.0f - })); - - armnn::TensorInfo inputTensorInfo1({ 1, 3, 3, 2 }, ArmnnType, qScale, qOffset); - - auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, { - 11.0f, 12.0f, - 13.0f, 14.0f, - 15.0f, 16.0f, - 17.0f, 18.0f, - 19.0f, 20.0f, - 21.0f, 22.0f, - 23.0f, 24.0f, - 25.0f, 26.0f, - 27.0f, 28.0f - })); + TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset); + auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>( + { + 1.0f, 2.0f, + 3.0f, 4.0f, + 5.0f, 6.0f, + 7.0f, 8.0f, + 9.0f, 10.0f, + 11.0f, 12.0f + }, + qScale, qOffset)); - armnn::TensorInfo outputTensorInfo({ 1, 3, 5, 2 }, ArmnnType, qScale, qOffset); + TensorInfo inputTensorInfo1({ 1, 3, 3, 2 }, ArmnnType, qScale, qOffset); + auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>( + { + 11.0f, 12.0f, + 13.0f, 14.0f, + 15.0f, 16.0f, + 17.0f, 18.0f, + 19.0f, 20.0f, + 21.0f, 22.0f, + 23.0f, 24.0f, + 25.0f, 26.0f, + 27.0f, 28.0f + }, + qScale, qOffset)); + TensorInfo outputTensorInfo({ 1, 3, 5, 2 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 4> result(outputTensorInfo); std::vector<T> output; @@ -1723,64 +1818,69 @@ LayerTestResult<T, 4> Concat4dDiffShapeDim2TestImpl( dimension, true); - result.output = MakeTensor<T, 4>(outputTensorInfo, output); - result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, - 3.0f, 4.0f, - 11.0f, 12.0f, - 13.0f, 14.0f, - 15.0f, 16.0f, - - 5.0f, 6.0f, - 7.0f, 8.0f, - 17.0f, 18.0f, - 19.0f, 20.0f, - 21.0f, 22.0f, - - 9.0f, 10.0f, - 11.0f, 12.0f, - 23.0f, 24.0f, - 25.0f, 26.0f, - 27.0f, 28.0f - })); + result.output = MakeTensor<T, 4>(outputTensorInfo, output); + result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>( + { + 1.0f, 2.0f, + 3.0f, 4.0f, + 11.0f, 12.0f, + 13.0f, 14.0f, + 15.0f, 16.0f, + + 5.0f, 6.0f, + 7.0f, 8.0f, + 17.0f, 18.0f, + 19.0f, 20.0f, + 21.0f, 22.0f, + + 9.0f, 10.0f, + 11.0f, 12.0f, + 23.0f, 24.0f, + 25.0f, 26.0f, + 27.0f, 28.0f + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> LayerTestResult<T, 4> Concat4dDiffShapeDim3TestImpl( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, float qScale, int32_t qOffset, bool useSubtensor) { - unsigned int dimension = 3; - armnn::TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset); - - auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, - 3.0f, 4.0f, - 5.0f, 6.0f, - 7.0f, 8.0f, - 9.0f, 10.0f, - 11.0f, 12.0f - })); + constexpr unsigned int dimension = 3u; - armnn::TensorInfo inputTensorInfo1({ 1, 3, 2, 3 }, ArmnnType, qScale, qOffset); - - auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, { - 11.0f, 12.0f, 13.0f, - 14.0f, 15.0f, 16.0f, + TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset); + auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>( + { + 1.0f, 2.0f, + 3.0f, 4.0f, + 5.0f, 6.0f, + 7.0f, 8.0f, + 9.0f, 10.0f, + 11.0f, 12.0f + }, + qScale, qOffset)); + + TensorInfo inputTensorInfo1({ 1, 3, 2, 3 }, ArmnnType, qScale, qOffset); + auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>( + { + 11.0f, 12.0f, 13.0f, + 14.0f, 15.0f, 16.0f, - 17.0f, 18.0f, 19.0f, - 20.0f, 21.0f, 22.0f, + 17.0f, 18.0f, 19.0f, + 20.0f, 21.0f, 22.0f, - 23.0f, 24.0f, 25.0f, - 26.0f, 27.0f, 28.0f - })); + 23.0f, 24.0f, 25.0f, + 26.0f, 27.0f, 28.0f + }, + qScale, qOffset)); - armnn::TensorInfo outputTensorInfo({ 1, 3, 2, 5 }, ArmnnType, qScale, qOffset); + TensorInfo outputTensorInfo({ 1, 3, 2, 5 }, ArmnnType, qScale, qOffset); LayerTestResult<T, 4> result(outputTensorInfo); @@ -1796,30 +1896,32 @@ LayerTestResult<T, 4> Concat4dDiffShapeDim3TestImpl( useSubtensor); result.output = MakeTensor<T, 4>(outputTensorInfo, output); - result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { - 1.0f, 2.0f, 11.0f, 12.0f, 13.0f, - 3.0f, 4.0f, 14.0f, 15.0f, 16.0f, - 5.0f, 6.0f, 17.0f, 18.0f, 19.0f, - 7.0f, 8.0f, 20.0f, 21.0f, 22.0f, - 9.0f, 10.0f, 23.0f, 24.0f, 25.0f, - 11.0f, 12.0f, 26.0f, 27.0f, 28.0f - })); + result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>( + { + 1.0f, 2.0f, 11.0f, 12.0f, 13.0f, + 3.0f, 4.0f, 14.0f, 15.0f, 16.0f, + 5.0f, 6.0f, 17.0f, 18.0f, 19.0f, + 7.0f, 8.0f, 20.0f, 21.0f, 22.0f, + 9.0f, 10.0f, 23.0f, 24.0f, 25.0f, + 11.0f, 12.0f, 26.0f, 27.0f, 28.0f + }, + qScale, qOffset)); return result; } -template<armnn::DataType ArmnnType, typename T> +template<DataType ArmnnType, typename T> LayerTestResult<T, 3> ConcatDifferentInputOutputQParamTest( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor) { // Defines the tensor descriptors. - armnn::TensorInfo outputTensorInfo({ 3, 6, 3 }, ArmnnType); - armnn::TensorInfo inputTensorInfo1({ 3, 6, 2 }, ArmnnType); - armnn::TensorInfo inputTensorInfo2({ 3, 6, 1 }, ArmnnType); + TensorInfo outputTensorInfo({ 3, 6, 3 }, ArmnnType); + TensorInfo inputTensorInfo1({ 3, 6, 2 }, ArmnnType); + TensorInfo inputTensorInfo2({ 3, 6, 1 }, ArmnnType); - std::vector<armnn::TensorShape> inputTensorShapes({inputTensorInfo1.GetShape(), inputTensorInfo2.GetShape()}); + std::vector<TensorShape> inputTensorShapes({inputTensorInfo1.GetShape(), inputTensorInfo2.GetShape()}); // Quantized input1 tensor. const float inputScale1 = 0.5f; @@ -1894,31 +1996,31 @@ LayerTestResult<T, 3> ConcatDifferentInputOutputQParamTest( inputTensorInfo2.SetQuantizationOffset(inputOffset2); std::vector<unsigned int> wOrigin1 = { 0, 0, 0 }; //Extent of the window is defined by size of input[0]. - armnn::ConcatQueueDescriptor::ViewOrigin window1(wOrigin1); + ConcatQueueDescriptor::ViewOrigin window1(wOrigin1); std::vector<unsigned int> wOrigin2 = { 0, 0, 2 }; //Extent of the window is defined by size of input[1]. - armnn::ConcatQueueDescriptor::ViewOrigin window2(wOrigin2); + ConcatQueueDescriptor::ViewOrigin window2(wOrigin2); - std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + std::unique_ptr<ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); bool subTensorsSupported = useSubtensor && workloadFactory.SupportsSubTensors(); - std::unique_ptr<armnn::ITensorHandle> inputHandle1 = + std::unique_ptr<ITensorHandle> inputHandle1 = subTensorsSupported ? workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo1.GetShape(), wOrigin1.data()) : workloadFactory.CreateTensorHandle(inputTensorInfo1); - std::unique_ptr<armnn::ITensorHandle> inputHandle2 = + std::unique_ptr<ITensorHandle> inputHandle2 = subTensorsSupported ? workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo2.GetShape(), wOrigin2.data()) : workloadFactory.CreateTensorHandle(inputTensorInfo2); - armnn::ConcatQueueDescriptor data; - armnn::OriginsDescriptor desc = armnn::CreateDescriptorForConcatenation( + ConcatQueueDescriptor data; + OriginsDescriptor desc = CreateDescriptorForConcatenation( inputTensorShapes.begin(),inputTensorShapes.end(), 2); data.m_Parameters = desc; - armnn::WorkloadInfo info; + WorkloadInfo info; AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); @@ -1926,7 +2028,7 @@ LayerTestResult<T, 3> ConcatDifferentInputOutputQParamTest( data.m_ViewOrigins.push_back(window1); data.m_ViewOrigins.push_back(window2); - std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConcat(data, info); + std::unique_ptr<IWorkload> workload = workloadFactory.CreateConcat(data, info); inputHandle1->Allocate(); inputHandle2->Allocate(); @@ -1947,16 +2049,16 @@ LayerTestResult<T, 3> ConcatDifferentInputOutputQParamTest( // Explicit template specializations // -template LayerTestResult<armnn::ResolveType<armnn::DataType::QuantisedAsymm8>, 3> -ConcatDifferentInputOutputQParamTest<armnn::DataType::QuantisedAsymm8>( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, +template LayerTestResult<ResolveType<DataType::QuantisedAsymm8>, 3> +ConcatDifferentInputOutputQParamTest<DataType::QuantisedAsymm8>( + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor); -template LayerTestResult<armnn::ResolveType<armnn::DataType::QuantisedSymm16>, 3> -ConcatDifferentInputOutputQParamTest<armnn::DataType::QuantisedSymm16>( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, +template LayerTestResult<ResolveType<DataType::QuantisedSymm16>, 3> +ConcatDifferentInputOutputQParamTest<DataType::QuantisedSymm16>( + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor); // @@ -1964,8 +2066,8 @@ ConcatDifferentInputOutputQParamTest<armnn::DataType::QuantisedSymm16>( // LayerTestResult<float,3> ConcatTest( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { unsigned int outputWidth = 3; unsigned int outputHeight = 6; @@ -1980,9 +2082,9 @@ LayerTestResult<float,3> ConcatTest( unsigned int inputChannels2 = 1; // Define the tensor descriptors. - armnn::TensorInfo outputTensorInfo({ outputChannels, outputHeight, outputWidth }, armnn::DataType::Float32); - armnn::TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, armnn::DataType::Float32); - armnn::TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, armnn::DataType::Float32); + TensorInfo outputTensorInfo({ outputChannels, outputHeight, outputWidth }, DataType::Float32); + TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, DataType::Float32); + TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, DataType::Float32); LayerTestResult<float,3> ret(outputTensorInfo); @@ -2041,27 +2143,27 @@ LayerTestResult<float,3> ConcatTest( ); std::vector<unsigned int> wOrigin1 = {0, 0, 0}; //Extent of the window is defined by size of input[0]. - armnn::ConcatQueueDescriptor::ViewOrigin window1(wOrigin1); + ConcatQueueDescriptor::ViewOrigin window1(wOrigin1); std::vector<unsigned int> wOrigin2 = {2, 0, 0}; //Extent of the window is defined by size of input[1]. - armnn::ConcatQueueDescriptor::ViewOrigin window2(wOrigin2); + ConcatQueueDescriptor::ViewOrigin window2(wOrigin2); - std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + std::unique_ptr<ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); bool subTensorsSupported = workloadFactory.SupportsSubTensors(); - std::unique_ptr<armnn::ITensorHandle> inputHandle1 = + std::unique_ptr<ITensorHandle> inputHandle1 = subTensorsSupported ? workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo1.GetShape(), wOrigin1.data()) : workloadFactory.CreateTensorHandle(inputTensorInfo1); - std::unique_ptr<armnn::ITensorHandle> inputHandle2 = + std::unique_ptr<ITensorHandle> inputHandle2 = subTensorsSupported ? workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo2.GetShape(), wOrigin2.data()) : workloadFactory.CreateTensorHandle(inputTensorInfo2); - armnn::ConcatQueueDescriptor data; - armnn::WorkloadInfo info; + ConcatQueueDescriptor data; + WorkloadInfo info; AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); @@ -2069,7 +2171,7 @@ LayerTestResult<float,3> ConcatTest( data.m_ViewOrigins.push_back(window1); data.m_ViewOrigins.push_back(window2); - std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConcat(data, info); + std::unique_ptr<IWorkload> workload = workloadFactory.CreateConcat(data, info); inputHandle1->Allocate(); inputHandle2->Allocate(); @@ -2087,156 +2189,156 @@ LayerTestResult<float,3> ConcatTest( } LayerTestResult<float, 1> Concat1dTest( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat1dTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); + return Concat1dTestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 2> Concat2dDim0Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat2dDim0TestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); + return Concat2dDim0TestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 2> Concat2dDim1Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat2dDim1TestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); + return Concat2dDim1TestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 2> Concat2dDim0DiffInputDimsTest( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat2dDim0DiffInputDimsTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); + return Concat2dDim0DiffInputDimsTestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 2> Concat2dDim1DiffInputDimsTest( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat2dDim1DiffInputDimsTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); + return Concat2dDim1DiffInputDimsTestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 3> Concat3dDim0Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat3dDim0TestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); + return Concat3dDim0TestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 3> Concat3dDim1Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat3dDim1TestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); + return Concat3dDim1TestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 3> Concat3dDim2Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor) { - return Concat3dDim2TestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, useSubtensor, 0.0f, 0); + return Concat3dDim2TestImpl<DataType::Float32>(workloadFactory, memoryManager, useSubtensor, 0.0f, 0); } LayerTestResult<float, 3> Concat3dDim0DiffInputDimsTest( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat3dDim0DiffInputDimsTestImpl<armnn::DataType::Float32>( + return Concat3dDim0DiffInputDimsTestImpl<DataType::Float32>( workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 3> Concat3dDim1DiffInputDimsTest( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat3dDim1DiffInputDimsTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); + return Concat3dDim1DiffInputDimsTestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 3> Concat3dDim2DiffInputDimsTest( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor) { - return Concat3dDim2DiffInputDimsTestImpl<armnn::DataType::Float32>( + return Concat3dDim2DiffInputDimsTestImpl<DataType::Float32>( workloadFactory, memoryManager, useSubtensor, 0.0f, 0); } LayerTestResult<float, 4> Concat4dDim0Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat4dDim0TestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); + return Concat4dDim0TestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 4> Concat4dDim1Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat4dDim1TestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); + return Concat4dDim1TestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 4> Concat4dDim2Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat4dDim2TestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); + return Concat4dDim2TestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 4> Concat4dDim3Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor) { - return Concat4dDim3TestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0, useSubtensor); + return Concat4dDim3TestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0, useSubtensor); } LayerTestResult<float, 4> Concat4dDiffShapeDim0Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat4dDiffShapeDim0TestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); + return Concat4dDiffShapeDim0TestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 4> Concat4dDiffShapeDim1Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat4dDiffShapeDim1TestImpl<armnn::DataType::Float32>( + return Concat4dDiffShapeDim1TestImpl<DataType::Float32>( workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 4> Concat4dDiffShapeDim2Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat4dDiffShapeDim2TestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); + return Concat4dDiffShapeDim2TestImpl<DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<float, 4> Concat4dDiffShapeDim3Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor) { - return Concat4dDiffShapeDim3TestImpl<armnn::DataType::Float32>( + return Concat4dDiffShapeDim3TestImpl<DataType::Float32>( workloadFactory, memoryManager, 0.0f, 0, useSubtensor); } -LayerTestResult<armnn::Half, 3> ConcatFloat16Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) +LayerTestResult<Half, 3> ConcatFloat16Test( + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat3dDim1TestImpl<armnn::DataType::Float16>(workloadFactory, memoryManager, 0.0f, 0); + return Concat3dDim1TestImpl<DataType::Float16>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<uint8_t, 3> ConcatUint8DifferentQParamsTest( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { unsigned int outputWidth = 3; unsigned int outputHeight = 6; @@ -2251,9 +2353,9 @@ LayerTestResult<uint8_t, 3> ConcatUint8DifferentQParamsTest( unsigned int inputChannels2 = 1; // Defines the tensor descriptors. - armnn::TensorInfo outputTensorInfo({ outputChannels, outputHeight, outputWidth }, armnn::DataType::QuantisedAsymm8); - armnn::TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, armnn::DataType::QuantisedAsymm8); - armnn::TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, armnn::DataType::QuantisedAsymm8); + TensorInfo outputTensorInfo({ outputChannels, outputHeight, outputWidth }, DataType::QuantisedAsymm8); + TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, DataType::QuantisedAsymm8); + TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, DataType::QuantisedAsymm8); // Quantized input1 tensor. Range [-3, 1] const float inputScale1 = 0.015686f; @@ -2332,27 +2434,27 @@ LayerTestResult<uint8_t, 3> ConcatUint8DifferentQParamsTest( inputTensorInfo2.SetQuantizationOffset(inputOffset2); std::vector<unsigned int> wOrigin1 = { 0, 0, 0 }; //Extent of the window is defined by size of input[0]. - armnn::ConcatQueueDescriptor::ViewOrigin window1(wOrigin1); + ConcatQueueDescriptor::ViewOrigin window1(wOrigin1); std::vector<unsigned int> wOrigin2 = { 2, 0, 0 }; //Extent of the window is defined by size of input[1]. - armnn::ConcatQueueDescriptor::ViewOrigin window2(wOrigin2); + ConcatQueueDescriptor::ViewOrigin window2(wOrigin2); - std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + std::unique_ptr<ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); bool subTensorsSupported = workloadFactory.SupportsSubTensors(); - std::unique_ptr<armnn::ITensorHandle> inputHandle1 = + std::unique_ptr<ITensorHandle> inputHandle1 = subTensorsSupported ? workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo1.GetShape(), wOrigin1.data()) : workloadFactory.CreateTensorHandle(inputTensorInfo1); - std::unique_ptr<armnn::ITensorHandle> inputHandle2 = + std::unique_ptr<ITensorHandle> inputHandle2 = subTensorsSupported ? workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo2.GetShape(), wOrigin2.data()) : workloadFactory.CreateTensorHandle(inputTensorInfo2); - armnn::ConcatQueueDescriptor data; - armnn::WorkloadInfo info; + ConcatQueueDescriptor data; + WorkloadInfo info; AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); @@ -2360,7 +2462,7 @@ LayerTestResult<uint8_t, 3> ConcatUint8DifferentQParamsTest( data.m_ViewOrigins.push_back(window1); data.m_ViewOrigins.push_back(window2); - std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConcat(data, info); + std::unique_ptr<IWorkload> workload = workloadFactory.CreateConcat(data, info); inputHandle1->Allocate(); inputHandle2->Allocate(); @@ -2378,8 +2480,8 @@ LayerTestResult<uint8_t, 3> ConcatUint8DifferentQParamsTest( } LayerTestResult<uint8_t, 3> ConcatUint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { unsigned int outputWidth = 3; unsigned int outputHeight = 6; @@ -2394,9 +2496,9 @@ LayerTestResult<uint8_t, 3> ConcatUint8Test( unsigned int inputChannels2 = 1; // Defines the tensor descriptors. - armnn::TensorInfo outputTensorInfo({ outputChannels, outputHeight, outputWidth }, armnn::DataType::QuantisedAsymm8); - armnn::TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, armnn::DataType::QuantisedAsymm8); - armnn::TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, armnn::DataType::QuantisedAsymm8); + TensorInfo outputTensorInfo({ outputChannels, outputHeight, outputWidth }, DataType::QuantisedAsymm8); + TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, DataType::QuantisedAsymm8); + TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, DataType::QuantisedAsymm8); // Arbitrary scale and offsets. They don't really matter as the Concat operator doesn't dequantize/quantize them. const float scale = 0.13497836f; @@ -2466,29 +2568,29 @@ LayerTestResult<uint8_t, 3> ConcatUint8Test( ); std::vector<unsigned int> wOrigin1 = { 0, 0, 0 }; //Extent of the window is defined by size of input[0]. - armnn::ConcatQueueDescriptor::ViewOrigin window1(wOrigin1); + ConcatQueueDescriptor::ViewOrigin window1(wOrigin1); std::vector<unsigned int> wOrigin2 = { 2, 0, 0 }; //Extent of the window is defined by size of input[1]. - armnn::ConcatQueueDescriptor::ViewOrigin window2(wOrigin2); + ConcatQueueDescriptor::ViewOrigin window2(wOrigin2); - std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + std::unique_ptr<ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); bool subTensorsSupported = workloadFactory.SupportsSubTensors(); - std::unique_ptr<armnn::ITensorHandle> inputHandle1 = + std::unique_ptr<ITensorHandle> inputHandle1 = subTensorsSupported ? workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo1.GetShape(), wOrigin1.data()) : workloadFactory.CreateTensorHandle(inputTensorInfo1); - std::unique_ptr<armnn::ITensorHandle> inputHandle2 = + std::unique_ptr<ITensorHandle> inputHandle2 = subTensorsSupported ? workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo2.GetShape(), wOrigin2.data()) : workloadFactory.CreateTensorHandle(inputTensorInfo2); - armnn::ConcatQueueDescriptor data; - armnn::WorkloadInfo info; + ConcatQueueDescriptor data; + WorkloadInfo info; AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); @@ -2496,7 +2598,7 @@ LayerTestResult<uint8_t, 3> ConcatUint8Test( data.m_ViewOrigins.push_back(window1); data.m_ViewOrigins.push_back(window2); - std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConcat(data, info); + std::unique_ptr<IWorkload> workload = workloadFactory.CreateConcat(data, info); inputHandle1->Allocate(); inputHandle2->Allocate(); @@ -2514,8 +2616,8 @@ LayerTestResult<uint8_t, 3> ConcatUint8Test( } LayerTestResult<uint16_t, 3> ConcatUint16Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { unsigned int outputWidth = 3; unsigned int outputHeight = 6; @@ -2530,9 +2632,9 @@ LayerTestResult<uint16_t, 3> ConcatUint16Test( unsigned int inputChannels2 = 1; // Defines the tensor descriptors. - armnn::TensorInfo outputTensorInfo({ outputChannels, outputHeight, outputWidth }, armnn::DataType::QuantisedSymm16); - armnn::TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, armnn::DataType::QuantisedSymm16); - armnn::TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, armnn::DataType::QuantisedSymm16); + TensorInfo outputTensorInfo({ outputChannels, outputHeight, outputWidth }, DataType::QuantisedSymm16); + TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, DataType::QuantisedSymm16); + TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, DataType::QuantisedSymm16); // Arbitrary scale and offsets. They don't really matter as the Concat operator doesn't dequantize/quantize them. const float scale = 0.13497836f; @@ -2599,29 +2701,29 @@ LayerTestResult<uint16_t, 3> ConcatUint16Test( })); std::vector<unsigned int> wOrigin1 = { 0, 0, 0 }; //Extent of the window is defined by size of input[0]. - armnn::ConcatQueueDescriptor::ViewOrigin window1(wOrigin1); + ConcatQueueDescriptor::ViewOrigin window1(wOrigin1); std::vector<unsigned int> wOrigin2 = { 2, 0, 0 }; //Extent of the window is defined by size of input[1]. - armnn::ConcatQueueDescriptor::ViewOrigin window2(wOrigin2); + ConcatQueueDescriptor::ViewOrigin window2(wOrigin2); - std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + std::unique_ptr<ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); bool subTensorsSupported = workloadFactory.SupportsSubTensors(); - std::unique_ptr<armnn::ITensorHandle> inputHandle1 = + std::unique_ptr<ITensorHandle> inputHandle1 = subTensorsSupported ? workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo1.GetShape(), wOrigin1.data()) : workloadFactory.CreateTensorHandle(inputTensorInfo1); - std::unique_ptr<armnn::ITensorHandle> inputHandle2 = + std::unique_ptr<ITensorHandle> inputHandle2 = subTensorsSupported ? workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo2.GetShape(), wOrigin2.data()) : workloadFactory.CreateTensorHandle(inputTensorInfo2); - armnn::ConcatQueueDescriptor data; - armnn::WorkloadInfo info; + ConcatQueueDescriptor data; + WorkloadInfo info; AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); @@ -2629,7 +2731,7 @@ LayerTestResult<uint16_t, 3> ConcatUint16Test( data.m_ViewOrigins.push_back(window1); data.m_ViewOrigins.push_back(window2); - std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConcat(data, info); + std::unique_ptr<IWorkload> workload = workloadFactory.CreateConcat(data, info); inputHandle1->Allocate(); inputHandle2->Allocate(); @@ -2647,147 +2749,147 @@ LayerTestResult<uint16_t, 3> ConcatUint16Test( } LayerTestResult<uint8_t, 1> Concat1dUint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat1dTestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); + return Concat1dTestImpl<DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 2> Concat2dDim0Uint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat2dDim0TestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); + return Concat2dDim0TestImpl<DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 2> Concat2dDim1Uint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat2dDim1TestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); + return Concat2dDim1TestImpl<DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 2> Concat2dDim0DiffInputDimsUint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat2dDim0DiffInputDimsTestImpl<armnn::DataType::QuantisedAsymm8>( + return Concat2dDim0DiffInputDimsTestImpl<DataType::QuantisedAsymm8>( workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 2> Concat2dDim1DiffInputDimsUint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat2dDim1DiffInputDimsTestImpl<armnn::DataType::QuantisedAsymm8>( + return Concat2dDim1DiffInputDimsTestImpl<DataType::QuantisedAsymm8>( workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 3> Concat3dDim0Uint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat3dDim0TestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); + return Concat3dDim0TestImpl<DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 3> Concat3dDim1Uint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat3dDim1TestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); + return Concat3dDim1TestImpl<DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 3> Concat3dDim2Uint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor) { - return Concat3dDim2TestImpl<armnn::DataType::QuantisedAsymm8>( + return Concat3dDim2TestImpl<DataType::QuantisedAsymm8>( workloadFactory, memoryManager, useSubtensor, 0.5f, -1); } LayerTestResult<uint8_t, 3> Concat3dDim0DiffInputDimsUint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat3dDim0TestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); + return Concat3dDim0TestImpl<DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 3> Concat3dDim1DiffInputDimsUint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat3dDim1DiffInputDimsTestImpl<armnn::DataType::QuantisedAsymm8>( + return Concat3dDim1DiffInputDimsTestImpl<DataType::QuantisedAsymm8>( workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 3> Concat3dDim2DiffInputDimsUint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor) { - return Concat3dDim2DiffInputDimsTestImpl<armnn::DataType::QuantisedAsymm8>( + return Concat3dDim2DiffInputDimsTestImpl<DataType::QuantisedAsymm8>( workloadFactory, memoryManager, useSubtensor, 0.5f, -1); } LayerTestResult<uint8_t, 4> Concat4dDim0Uint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat4dDim0TestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); + return Concat4dDim0TestImpl<DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 4> Concat4dDim1Uint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat4dDim1TestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); + return Concat4dDim1TestImpl<DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 4> Concat4dDim2Uint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat4dDim2TestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); + return Concat4dDim2TestImpl<DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 4> Concat4dDim3Uint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor) { - return Concat4dDim3TestImpl<armnn::DataType::QuantisedAsymm8>( + return Concat4dDim3TestImpl<DataType::QuantisedAsymm8>( workloadFactory, memoryManager, 0.5f, -1, useSubtensor); } LayerTestResult<uint8_t, 4> Concat4dDiffShapeDim0Uint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat4dDiffShapeDim0TestImpl<armnn::DataType::QuantisedAsymm8>( + return Concat4dDiffShapeDim0TestImpl<DataType::QuantisedAsymm8>( workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 4> Concat4dDiffShapeDim1Uint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat4dDiffShapeDim1TestImpl<armnn::DataType::QuantisedAsymm8>( + return Concat4dDiffShapeDim1TestImpl<DataType::QuantisedAsymm8>( workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 4> Concat4dDiffShapeDim2Uint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return Concat4dDiffShapeDim2TestImpl<armnn::DataType::QuantisedAsymm8>( + return Concat4dDiffShapeDim2TestImpl<DataType::QuantisedAsymm8>( workloadFactory, memoryManager, 0.5f, -1); } LayerTestResult<uint8_t, 4> Concat4dDiffShapeDim3Uint8Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + IWorkloadFactory& workloadFactory, + const IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor) { - return Concat4dDiffShapeDim3TestImpl<armnn::DataType::QuantisedAsymm8>( + return Concat4dDiffShapeDim3TestImpl<DataType::QuantisedAsymm8>( workloadFactory, memoryManager, 0.5f, -1, useSubtensor); } |