| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include <test/CreateWorkload.hpp> |
| |
| #include <armnn/utility/PolymorphicDowncast.hpp> |
| #include <reference/RefTensorHandle.hpp> |
| #include <reference/RefWorkloadFactory.hpp> |
| #include <reference/workloads/RefWorkloads.hpp> |
| |
| #include <doctest/doctest.h> |
| |
| namespace |
| { |
| |
| template<typename Workload> |
| void CheckInputOutput(std::unique_ptr<Workload> workload, const TensorInfo& inputInfo, const TensorInfo& outputInfo) |
| { |
| auto queueDescriptor = workload->GetData(); |
| auto inputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]); |
| auto outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); |
| CHECK((inputHandle->GetTensorInfo() == inputInfo)); |
| CHECK((outputHandle->GetTensorInfo() == outputInfo)); |
| } |
| |
| template <typename Workload> |
| void CheckInputsOutput(std::unique_ptr<Workload> workload, |
| const TensorInfo& inputInfo0, |
| const TensorInfo& inputInfo1, |
| const TensorInfo& outputInfo) |
| { |
| auto queueDescriptor = workload->GetData(); |
| auto inputHandle0 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]); |
| auto inputHandle1 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[1]); |
| auto outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); |
| CHECK((inputHandle0->GetTensorInfo() == inputInfo0)); |
| CHECK((inputHandle1->GetTensorInfo() == inputInfo1)); |
| CHECK((outputHandle->GetTensorInfo() == outputInfo)); |
| } |
| |
| armnn::RefWorkloadFactory GetFactory() |
| { |
| std::shared_ptr<RefMemoryManager> memoryManager = std::make_shared<RefMemoryManager>(); |
| return RefWorkloadFactory(memoryManager); |
| } |
| |
| |
| } |
| |
| TEST_SUITE("CreateWorkloadRef") |
| { |
| template <typename ActivationWorkloadType, armnn::DataType DataType> |
| static void RefCreateActivationWorkloadTest() |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateActivationWorkloadTest<ActivationWorkloadType, DataType>(factory, graph); |
| |
| // Checks that outputs are as we expect them (see definition of CreateActivationWorkloadTest). |
| CheckInputOutput(std::move(workload), |
| TensorInfo({ 1, 1 }, DataType), |
| TensorInfo({ 1, 1 }, DataType)); |
| } |
| |
| TEST_CASE("CreateActivationFloat32Workload") |
| { |
| RefCreateActivationWorkloadTest<RefActivationWorkload, armnn::DataType::Float32>(); |
| } |
| |
| TEST_CASE("CreateActivationUint8Workload") |
| { |
| RefCreateActivationWorkloadTest<RefActivationWorkload, armnn::DataType::QAsymmU8>(); |
| } |
| |
| template <typename WorkloadType, |
| typename DescriptorType, |
| typename LayerType, |
| armnn::DataType DataType> |
| static void RefCreateElementwiseWorkloadTest() |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateElementwiseWorkloadTest<WorkloadType, DescriptorType, LayerType, DataType>( |
| factory, graph); |
| |
| CheckInputsOutput(std::move(workload), |
| TensorInfo({ 2, 3 }, DataType), |
| TensorInfo({ 2, 3 }, DataType), |
| TensorInfo({ 2, 3 }, DataType)); |
| } |
| |
| TEST_CASE("CreateSubtractionWorkloadWithBlobTest") |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| armnn::DataType DataType = armnn::DataType::Float32; |
| |
| auto workload = CreateSubtractionWithBlobWorkloadTest<RefSubtractionWorkload<>, |
| SubtractionQueueDescriptor, |
| armnn::DataType::Float32> |
| (factory, graph); |
| |
| CheckInputsOutput(std::move(workload), |
| TensorInfo({ 2, 3 }, DataType), |
| TensorInfo({ 2, 3 }, DataType), |
| TensorInfo({ 2, 3 }, DataType)); |
| } |
| |
| TEST_CASE("CreateAdditionWorkloadWithBlobTest") |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| armnn::DataType DataType = armnn::DataType::Float32; |
| |
| auto workload = CreateAdditionWithBlobWorkloadTest<RefAdditionWorkload<>, |
| AdditionQueueDescriptor, |
| armnn::DataType::Float32>(factory, graph); |
| |
| CheckInputsOutput(std::move(workload), |
| TensorInfo({ 2, 3 }, DataType), |
| TensorInfo({ 2, 3 }, DataType), |
| TensorInfo({ 2, 3 }, DataType)); |
| } |
| |
| TEST_CASE("CreateMultiplicationWorkloadWithBlobTest") |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| armnn::DataType DataType = armnn::DataType::Float32; |
| |
| auto workload = CreateMultiplicationWithBlobWorkloadTest<RefMultiplicationWorkload<>, |
| MultiplicationQueueDescriptor, |
| armnn::DataType::Float32>(factory, graph); |
| |
| CheckInputsOutput(std::move(workload), |
| TensorInfo({2, 3}, DataType), |
| TensorInfo({2, 3}, DataType), |
| TensorInfo({2, 3}, DataType)); |
| } |
| |
| TEST_CASE("CreateAdditionFloatWorkload") |
| { |
| RefCreateElementwiseWorkloadTest<RefAdditionWorkload<>, |
| AdditionQueueDescriptor, |
| AdditionLayer, |
| armnn::DataType::Float32>(); |
| } |
| |
| TEST_CASE("CreateAdditionUint8Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefAdditionWorkload<>, |
| AdditionQueueDescriptor, |
| AdditionLayer, |
| armnn::DataType::QAsymmU8>(); |
| } |
| |
| TEST_CASE("CreateAdditionInt16Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefAdditionWorkload<>, |
| AdditionQueueDescriptor, |
| AdditionLayer, |
| armnn::DataType::QSymmS16>(); |
| } |
| |
| TEST_CASE("CreateAdditionInt32Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefAdditionWorkload<int32_t>, |
| AdditionQueueDescriptor, |
| AdditionLayer, |
| armnn::DataType::Signed32>(); |
| } |
| |
| TEST_CASE("CreateSubtractionFloat32Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefSubtractionWorkload<>, |
| SubtractionQueueDescriptor, |
| SubtractionLayer, |
| armnn::DataType::Float32>(); |
| } |
| |
| TEST_CASE("CreateSubtractionFloat16Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefSubtractionWorkload<>, |
| SubtractionQueueDescriptor, |
| SubtractionLayer, |
| armnn::DataType::Float16>(); |
| } |
| |
| TEST_CASE("CreateSubtractionUint8Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefSubtractionWorkload<>, |
| SubtractionQueueDescriptor, |
| SubtractionLayer, |
| armnn::DataType::QAsymmU8>(); |
| } |
| |
| TEST_CASE("CreateSubtractionInt16Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefSubtractionWorkload<>, |
| SubtractionQueueDescriptor, |
| SubtractionLayer, |
| armnn::DataType::QSymmS16>(); |
| } |
| |
| TEST_CASE("CreateSubtractionInt32Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefSubtractionWorkload<int32_t>, |
| SubtractionQueueDescriptor, |
| SubtractionLayer, |
| armnn::DataType::Signed32>(); |
| } |
| |
| TEST_CASE("CreateMultiplicationFloatWorkload") |
| { |
| RefCreateElementwiseWorkloadTest<RefMultiplicationWorkload<>, |
| MultiplicationQueueDescriptor, |
| MultiplicationLayer, |
| armnn::DataType::Float32>(); |
| } |
| |
| TEST_CASE("CreateMultiplicationUint8Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefMultiplicationWorkload<>, |
| MultiplicationQueueDescriptor, |
| MultiplicationLayer, |
| armnn::DataType::QAsymmU8>(); |
| } |
| |
| TEST_CASE("CreateMultiplicationInt16Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefMultiplicationWorkload<>, |
| MultiplicationQueueDescriptor, |
| MultiplicationLayer, |
| armnn::DataType::QSymmS16>(); |
| } |
| |
| TEST_CASE("CreateMultiplicationInt32Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefMultiplicationWorkload<int32_t>, |
| MultiplicationQueueDescriptor, |
| MultiplicationLayer, |
| armnn::DataType::Signed32>(); |
| } |
| |
| TEST_CASE("CreateDivisionFloat32Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefDivisionWorkload<>, |
| DivisionQueueDescriptor, |
| DivisionLayer, |
| armnn::DataType::Float32>(); |
| } |
| |
| TEST_CASE("CreateDivisionFloat16Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefDivisionWorkload<>, |
| DivisionQueueDescriptor, |
| DivisionLayer, |
| armnn::DataType::Float16>(); |
| } |
| |
| TEST_CASE("CreateDivisionUint8Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefDivisionWorkload<>, |
| DivisionQueueDescriptor, |
| DivisionLayer, |
| armnn::DataType::QAsymmU8>(); |
| } |
| |
| TEST_CASE("CreateDivisionInt16Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefDivisionWorkload<>, |
| DivisionQueueDescriptor, |
| DivisionLayer, |
| armnn::DataType::QSymmS16>(); |
| } |
| |
| TEST_CASE("CreateDivisionInt32Workload") |
| { |
| RefCreateElementwiseWorkloadTest<RefDivisionWorkload<int32_t>, |
| DivisionQueueDescriptor, |
| DivisionLayer, |
| armnn::DataType::Signed32>(); |
| } |
| |
| template <typename BatchNormalizationWorkloadType, armnn::DataType DataType> |
| static void RefCreateBatchNormalizationWorkloadTest(DataLayout dataLayout) |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateBatchNormalizationWorkloadTest<BatchNormalizationWorkloadType, DataType>(factory, |
| graph, |
| dataLayout); |
| |
| TensorShape inputShape; |
| TensorShape outputShape; |
| |
| switch (dataLayout) |
| { |
| case DataLayout::NHWC: |
| inputShape = { 2, 4, 4, 3 }; |
| outputShape = { 2, 4, 4, 3 }; |
| break; |
| case DataLayout::NCHW: |
| default: |
| inputShape = { 2, 3, 4, 4 }; |
| outputShape = { 2, 3, 4, 4 }; |
| break; |
| } |
| |
| // Checks that outputs and inputs are as we expect them (see definition of CreateBatchNormalizationWorkloadTest). |
| CheckInputOutput(std::move(workload), TensorInfo(inputShape, DataType), TensorInfo(outputShape, DataType)); |
| } |
| |
| TEST_CASE("CreateBatchNormalizationWithBlobFloat32Workload") |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto dataType = armnn::DataType::Float32; |
| auto workload = CreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload, |
| armnn::DataType::Float32>(factory, graph, DataLayout::NHWC); |
| |
| TensorShape inputShape; |
| TensorShape outputShape; |
| |
| inputShape = { 2, 4, 4, 3 }; |
| outputShape = { 2, 4, 4, 3 }; |
| |
| // Checks that outputs and inputs are as we expect them (see definition of CreateBatchNormalizationWorkloadTest). |
| CheckInputOutput(std::move(workload), TensorInfo(inputShape, dataType), TensorInfo(outputShape, dataType)); |
| } |
| |
| TEST_CASE("CreateBatchNormalizationFloat32Workload") |
| { |
| RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload,armnn::DataType::Float32> |
| (DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateBatchNormalizationFloat32WorkloadNhwc") |
| { |
| RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload, armnn::DataType::Float32> |
| (DataLayout::NHWC); |
| } |
| |
| TEST_CASE("CreateBatchNormalizationFloat16Workload") |
| { |
| RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload,armnn::DataType::Float16> |
| (DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateBatchNormalizationFloat16WorkloadNhwc") |
| { |
| RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload, armnn::DataType::Float16> |
| (DataLayout::NHWC); |
| } |
| |
| TEST_CASE("CreateBatchNormalizationUint8Workload") |
| { |
| RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload, armnn::DataType::QAsymmU8> |
| (DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateBatchNormalizationUint8WorkloadNhwc") |
| { |
| RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload, armnn::DataType::QAsymmU8> |
| (DataLayout::NHWC); |
| } |
| |
| TEST_CASE("CreateBatchNormalizationInt16Workload") |
| { |
| RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload, armnn::DataType::QSymmS16> |
| (DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateBatchNormalizationInt16WorkloadNhwc") |
| { |
| RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload, armnn::DataType::QSymmS16> |
| (DataLayout::NHWC); |
| } |
| |
| TEST_CASE("CreateConvertFp16ToFp32Float32Workload") |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateConvertFp16ToFp32WorkloadTest<RefConvertFp16ToFp32Workload>(factory, graph); |
| |
| // Checks that outputs and inputs are as we expect them |
| CheckInputOutput( |
| std::move(workload), TensorInfo({1, 3, 2, 3}, DataType::Float16), TensorInfo({1, 3, 2, 3}, DataType::Float32)); |
| } |
| |
| TEST_CASE("CreateConvertFp32ToFp16Float16Workload") |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateConvertFp32ToFp16WorkloadTest<RefConvertFp32ToFp16Workload>(factory, graph); |
| |
| // Checks that outputs and inputs are as we expect them |
| CheckInputOutput( |
| std::move(workload), TensorInfo({1, 3, 2, 3}, DataType::Float32), TensorInfo({1, 3, 2, 3}, DataType::Float16)); |
| } |
| |
| static void RefCreateConvolution2dWorkloadTest(DataLayout dataLayout = DataLayout::NCHW) |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateConvolution2dWorkloadTest<RefConvolution2dWorkload, DataType::Float32> |
| (factory, graph, dataLayout); |
| |
| TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({2, 3, 8, 16}) |
| : std::initializer_list<unsigned int>({2, 8, 16, 3}); |
| TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({2, 2, 2, 10}) |
| : std::initializer_list<unsigned int>({2, 2, 10, 2}); |
| |
| // Checks that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest). |
| CheckInputOutput(std::move(workload), |
| TensorInfo(inputShape, DataType::Float32), |
| TensorInfo(outputShape, DataType::Float32)); |
| } |
| |
| TEST_CASE("CreateConvolution2dFloatNchwWorkload") |
| { |
| RefCreateConvolution2dWorkloadTest(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateConvolution2dFloatNhwcWorkload") |
| { |
| RefCreateConvolution2dWorkloadTest(DataLayout::NHWC); |
| } |
| |
| TEST_CASE("CreateConvolution2dWithBlobWorkload") |
| { |
| DataLayout dataLayout = DataLayout::NHWC; |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateConvolution2dFusedActivationWithBlobWorkloadTest<RefConvolution2dWorkload, DataType::Float32> |
| (factory, graph, dataLayout); |
| |
| TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({2, 3, 8, 16}) |
| : std::initializer_list<unsigned int>({2, 8, 16, 3}); |
| TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({2, 2, 2, 10}) |
| : std::initializer_list<unsigned int>({2, 2, 10, 2}); |
| |
| // Checks that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest). |
| CheckInputOutput(std::move(workload), |
| TensorInfo(inputShape, DataType::Float32), |
| TensorInfo(outputShape, DataType::Float32)); |
| } |
| |
| static void RefCreateDepthwiseConvolutionWorkloadTest(DataLayout dataLayout) |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateDepthwiseConvolution2dWorkloadTest<RefDepthwiseConvolution2dWorkload, DataType::Float32> |
| (factory, graph, dataLayout); |
| |
| TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({ 2, 2, 5, 5 }) |
| : std::initializer_list<unsigned int>({ 2, 5, 5, 2 }); |
| TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({ 2, 2, 5, 5 }) |
| : std::initializer_list<unsigned int>({ 2, 5, 5, 2 }); |
| |
| // Checks that inputs/outputs are as we expect them (see definition of CreateDepthwiseConvolution2dWorkloadTest). |
| CheckInputOutput(std::move(workload), |
| TensorInfo(inputShape, DataType::Float32), |
| TensorInfo(outputShape, DataType::Float32)); |
| } |
| |
| TEST_CASE("CreateDepthwiseConvolutionFloat32NhwcWorkload") |
| { |
| RefCreateDepthwiseConvolutionWorkloadTest(DataLayout::NHWC); |
| } |
| |
| TEST_CASE("RefCreateFullyConnectedWithBlobWorkloadTest") |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateFullyConnectedWithBlobWorkloadTest<RefFullyConnectedWorkload, |
| armnn::DataType::Float32>(factory, graph); |
| |
| // Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest). |
| float inputsQScale = 0.0f; |
| float outputQScale = 0.0f; |
| CheckInputOutput(std::move(workload), |
| TensorInfo({ 3, 1, 4, 5 }, armnn::DataType::Float32, inputsQScale), |
| TensorInfo({ 3, 7 }, armnn::DataType::Float32, outputQScale)); |
| } |
| |
| TEST_CASE("CreateFullyConnectedWorkloadWeightsBiasesAsInputsFloat32") |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| |
| auto workload = |
| CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest<RefFullyConnectedWorkload, |
| armnn::DataType::Float32>(factory, graph); |
| |
| // Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest). |
| float inputsQScale = 0.0f; |
| float outputQScale = 0.0f; |
| CheckInputsOutput(std::move(workload), |
| TensorInfo({ 3, 1, 4, 5 }, armnn::DataType::Float32, inputsQScale), |
| TensorInfo({ 7, 20 }, armnn::DataType::Float32, inputsQScale), |
| TensorInfo({ 3, 7 }, armnn::DataType::Float32, outputQScale)); |
| } |
| |
| template <typename FullyConnectedWorkloadType, armnn::DataType DataType> |
| static void RefCreateFullyConnectedWorkloadTest() |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateFullyConnectedWorkloadTest<FullyConnectedWorkloadType, DataType>(factory, graph); |
| |
| // Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest). |
| float inputsQScale = DataType == armnn::DataType::QAsymmU8 ? 1.0f : 0.0; |
| float outputQScale = DataType == armnn::DataType::QAsymmU8 ? 2.0f : 0.0; |
| CheckInputOutput(std::move(workload), |
| TensorInfo({ 3, 1, 4, 5 }, DataType, inputsQScale), |
| TensorInfo({ 3, 7 }, DataType, outputQScale)); |
| } |
| |
| TEST_CASE("CreateFullyConnectedWorkloadFloat32") |
| { |
| RefCreateFullyConnectedWorkloadTest<RefFullyConnectedWorkload, armnn::DataType::Float32>(); |
| } |
| |
| TEST_CASE("CreateFullyConnectedWorkloadQuantisedAsymm8") |
| { |
| RefCreateFullyConnectedWorkloadTest<RefFullyConnectedWorkload, armnn::DataType::QAsymmU8>(); |
| } |
| |
| TEST_CASE("CreateFullyConnectedWorkloadQuantisedSymm16") |
| { |
| RefCreateFullyConnectedWorkloadTest<RefFullyConnectedWorkload, armnn::DataType::QSymmS16>(); |
| } |
| |
| template <typename NormalizationWorkloadType, armnn::DataType DataType> |
| static void RefCreateNormalizationWorkloadTest(DataLayout dataLayout) |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateNormalizationWorkloadTest<NormalizationWorkloadType, DataType>(factory, graph, dataLayout); |
| |
| TensorShape inputShape; |
| TensorShape outputShape; |
| |
| switch (dataLayout) |
| { |
| case DataLayout::NHWC: |
| inputShape = { 3, 1, 5, 5 }; |
| outputShape = { 3, 1, 5, 5 }; |
| break; |
| case DataLayout::NCHW: |
| default: |
| inputShape = { 3, 5, 5, 1 }; |
| outputShape = { 3, 5, 5, 1 }; |
| break; |
| } |
| |
| // Checks that outputs and inputs are as we expect them (see definition of CreateNormalizationWorkloadTest). |
| CheckInputOutput(std::move(workload), TensorInfo(inputShape, DataType), TensorInfo(outputShape, DataType)); |
| } |
| |
| TEST_CASE("CreateRefNormalizationFloat32NchwWorkload") |
| { |
| RefCreateNormalizationWorkloadTest<RefNormalizationWorkload, armnn::DataType::Float32>(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateRefNormalizationFloat32NhwcWorkload") |
| { |
| RefCreateNormalizationWorkloadTest<RefNormalizationWorkload, armnn::DataType::Float32>(DataLayout::NHWC); |
| } |
| |
| TEST_CASE("CreateRefNormalizationUint8NchwWorkload") |
| { |
| RefCreateNormalizationWorkloadTest<RefNormalizationWorkload, armnn::DataType::QAsymmU8>(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateRefNormalizationUint8NhwcWorkload") |
| { |
| RefCreateNormalizationWorkloadTest<RefNormalizationWorkload, armnn::DataType::QAsymmU8>(DataLayout::NHWC); |
| } |
| |
| TEST_CASE("CreateRefNormalizationInt16NchwWorkload") |
| { |
| RefCreateNormalizationWorkloadTest<RefNormalizationWorkload, armnn::DataType::QSymmS16>(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateRefNormalizationInt16NhwcWorkload") |
| { |
| RefCreateNormalizationWorkloadTest<RefNormalizationWorkload, armnn::DataType::QSymmS16>(DataLayout::NHWC); |
| } |
| |
| template <typename Pooling2dWorkloadType, armnn::DataType DataType> |
| static void RefCreatePooling2dWorkloadTest(DataLayout dataLayout) |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreatePooling2dWorkloadTest<Pooling2dWorkloadType, DataType>(factory, graph, dataLayout); |
| |
| TensorShape inputShape; |
| TensorShape outputShape; |
| |
| switch (dataLayout) |
| { |
| case DataLayout::NHWC: |
| inputShape = { 3, 5, 5, 2 }; |
| outputShape = { 3, 2, 4, 2 }; |
| break; |
| case DataLayout::NCHW: |
| default: |
| inputShape = { 3, 2, 5, 5 }; |
| outputShape = { 3, 2, 2, 4 }; |
| } |
| |
| // Checks that outputs and inputs are as we expect them (see definition of CreatePooling2dWorkloadTest). |
| CheckInputOutput(std::move(workload), |
| TensorInfo(inputShape, DataType), |
| TensorInfo(outputShape, DataType)); |
| } |
| |
| TEST_CASE("CreatePooling2dFloat32Workload") |
| { |
| RefCreatePooling2dWorkloadTest<RefPooling2dWorkload, armnn::DataType::Float32>(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreatePooling2dFloat32NhwcWorkload") |
| { |
| RefCreatePooling2dWorkloadTest<RefPooling2dWorkload, armnn::DataType::Float32>(DataLayout::NHWC); |
| } |
| |
| TEST_CASE("CreatePooling2dUint8Workload") |
| { |
| RefCreatePooling2dWorkloadTest<RefPooling2dWorkload, armnn::DataType::QAsymmU8>(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreatePooling2dUint8NhwcWorkload") |
| { |
| RefCreatePooling2dWorkloadTest<RefPooling2dWorkload, armnn::DataType::QAsymmU8>(DataLayout::NHWC); |
| } |
| |
| TEST_CASE("CreatePooling2dInt16Workload") |
| { |
| RefCreatePooling2dWorkloadTest<RefPooling2dWorkload, armnn::DataType::QSymmS16>(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreatePooling2dInt16NhwcWorkload") |
| { |
| RefCreatePooling2dWorkloadTest<RefPooling2dWorkload, armnn::DataType::QSymmS16>(DataLayout::NHWC); |
| } |
| |
| template <typename SoftmaxWorkloadType, armnn::DataType DataType> |
| static void RefCreateSoftmaxWorkloadTest() |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateSoftmaxWorkloadTest<SoftmaxWorkloadType, DataType>(factory, graph); |
| |
| // Checks that outputs and inputs are as we expect them (see definition of CreateSoftmaxWorkloadTest). |
| |
| armnn::TensorInfo tensorInfo({4, 1}, DataType); |
| if (DataType == armnn::DataType::QAsymmU8) |
| { |
| tensorInfo.SetQuantizationOffset(0); |
| tensorInfo.SetQuantizationScale(1.f / 256); |
| } |
| else if (DataType == armnn::DataType::QAsymmS8) |
| { |
| tensorInfo.SetQuantizationOffset(-128); |
| tensorInfo.SetQuantizationScale(1.f / 256); |
| } |
| CheckInputOutput( |
| std::move(workload), |
| tensorInfo, |
| tensorInfo); |
| } |
| |
| TEST_CASE("CreateSoftmaxFloat32Workload") |
| { |
| RefCreateSoftmaxWorkloadTest<RefSoftmaxWorkload, armnn::DataType::Float32>(); |
| } |
| |
| TEST_CASE("CreateSoftmaxFloat16Workload") |
| { |
| RefCreateSoftmaxWorkloadTest<RefSoftmaxWorkload, armnn::DataType::Float16>(); |
| } |
| |
| TEST_CASE("CreateSoftmaxQuantisedAsymm8Workload") |
| { |
| RefCreateSoftmaxWorkloadTest<RefSoftmaxWorkload, armnn::DataType::QAsymmU8>(); |
| } |
| |
| TEST_CASE("CreateSoftmaxQuantisedSymm16Workload") |
| { |
| RefCreateSoftmaxWorkloadTest<RefSoftmaxWorkload, armnn::DataType::QSymmS16>(); |
| } |
| |
| template <typename SplitterWorkloadType, armnn::DataType DataType> |
| static void RefCreateSplitterWorkloadTest() |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateSplitterWorkloadTest<SplitterWorkloadType, DataType>(factory, graph); |
| |
| // Checks that outputs are as we expect them (see definition of CreateSplitterWorkloadTest). |
| SplitterQueueDescriptor queueDescriptor = workload->GetData(); |
| auto inputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]); |
| CHECK((inputHandle->GetTensorInfo() == TensorInfo({ 5, 7, 7 }, DataType))); |
| |
| auto outputHandle0 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); |
| CHECK((outputHandle0->GetTensorInfo() == TensorInfo({ 1, 7, 7 }, DataType))); |
| |
| auto outputHandle1 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[1]); |
| CHECK((outputHandle1->GetTensorInfo() == TensorInfo({ 2, 7, 7 }, DataType))); |
| |
| auto outputHandle2 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[2]); |
| CHECK((outputHandle2->GetTensorInfo() == TensorInfo({ 2, 7, 7 }, DataType))); |
| } |
| |
| TEST_CASE("CreateSplitterFloat32Workload") |
| { |
| RefCreateSplitterWorkloadTest<RefSplitterWorkload, armnn::DataType::Float32>(); |
| } |
| |
| TEST_CASE("CreateSplitterFloat16Workload") |
| { |
| RefCreateSplitterWorkloadTest<RefSplitterWorkload, armnn::DataType::Float16>(); |
| } |
| |
| TEST_CASE("CreateSplitterUint8Workload") |
| { |
| RefCreateSplitterWorkloadTest<RefSplitterWorkload, armnn::DataType::QAsymmU8>(); |
| } |
| |
| template <typename SplitterWorkloadType, typename ConcatWorkloadType, armnn::DataType DataType> |
| static void RefCreateSplitterConcatWorkloadTest() |
| { |
| // Tests that it is possible to decide which output of the splitter layer |
| // should be lined to which input of the concat layer. |
| // We tested that is is possible to specify 0th output |
| // of the splitter to be the 1st input to the concat and the 1st output of the splitter to be 0th input |
| // of the concat. |
| |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workloads = CreateSplitterConcatWorkloadTest<SplitterWorkloadType, ConcatWorkloadType, DataType> |
| (factory, graph); |
| |
| auto wlSplitter = std::move(workloads.first); |
| auto wlConcat = std::move(workloads.second); |
| |
| //Checks that the index of inputs/outputs matches what we declared on InputDescriptor construction. |
| armnn::RefTensorHandle* sOut0 = dynamic_cast<armnn::RefTensorHandle*>(wlSplitter->GetData().m_Outputs[0]); |
| armnn::RefTensorHandle* sOut1 = dynamic_cast<armnn::RefTensorHandle*>(wlSplitter->GetData().m_Outputs[1]); |
| armnn::RefTensorHandle* mIn0 = dynamic_cast<armnn::RefTensorHandle*>(wlConcat->GetData().m_Inputs[0]); |
| armnn::RefTensorHandle* mIn1 = dynamic_cast<armnn::RefTensorHandle*>(wlConcat->GetData().m_Inputs[1]); |
| |
| CHECK(sOut0); |
| CHECK(sOut1); |
| CHECK(mIn0); |
| CHECK(mIn1); |
| |
| bool validDataPointers = (sOut0 == mIn1) && (sOut1 == mIn0); |
| |
| CHECK(validDataPointers); |
| } |
| |
| TEST_CASE("CreateSplitterConcatFloat32") |
| { |
| RefCreateSplitterConcatWorkloadTest<RefSplitterWorkload, RefConcatWorkload, DataType::Float32>(); |
| } |
| |
| TEST_CASE("CreateSplitterConcatFloat16") |
| { |
| RefCreateSplitterConcatWorkloadTest<RefSplitterWorkload, RefConcatWorkload, DataType::Float16>(); |
| } |
| |
| TEST_CASE("CreateSplitterConcatUint8") |
| { |
| RefCreateSplitterConcatWorkloadTest<RefSplitterWorkload, RefConcatWorkload, DataType::QAsymmU8>(); |
| } |
| |
| template <typename SplitterWorkloadType, typename ActivationWorkloadType, armnn::DataType DataType> |
| static void RefCreateSingleOutputMultipleInputsTest() |
| { |
| // Tests that it is possible to assign multiple (two) different layers to each of the outputs of a splitter layer. |
| // We created a splitter with two outputs. That each of those outputs is used by two different activation layers. |
| |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| std::unique_ptr<SplitterWorkloadType> wlSplitter; |
| std::unique_ptr<ActivationWorkloadType> wlActiv0_0; |
| std::unique_ptr<ActivationWorkloadType> wlActiv0_1; |
| std::unique_ptr<ActivationWorkloadType> wlActiv1_0; |
| std::unique_ptr<ActivationWorkloadType> wlActiv1_1; |
| |
| CreateSplitterMultipleInputsOneOutputWorkloadTest<SplitterWorkloadType, |
| ActivationWorkloadType, DataType>(factory, graph, wlSplitter, wlActiv0_0, wlActiv0_1, wlActiv1_0, wlActiv1_1); |
| |
| armnn::RefTensorHandle* sOut0 = dynamic_cast<armnn::RefTensorHandle*>(wlSplitter->GetData().m_Outputs[0]); |
| armnn::RefTensorHandle* sOut1 = dynamic_cast<armnn::RefTensorHandle*>(wlSplitter->GetData().m_Outputs[1]); |
| armnn::RefTensorHandle* activ0_0Im = dynamic_cast<armnn::RefTensorHandle*>(wlActiv0_0->GetData().m_Inputs[0]); |
| armnn::RefTensorHandle* activ0_1Im = dynamic_cast<armnn::RefTensorHandle*>(wlActiv0_1->GetData().m_Inputs[0]); |
| armnn::RefTensorHandle* activ1_0Im = dynamic_cast<armnn::RefTensorHandle*>(wlActiv1_0->GetData().m_Inputs[0]); |
| armnn::RefTensorHandle* activ1_1Im = dynamic_cast<armnn::RefTensorHandle*>(wlActiv1_1->GetData().m_Inputs[0]); |
| |
| |
| CHECK(sOut0); |
| CHECK(sOut1); |
| CHECK(activ0_0Im); |
| CHECK(activ0_1Im); |
| CHECK(activ1_0Im); |
| CHECK(activ1_1Im); |
| |
| bool validDataPointers = (sOut0 == activ0_0Im) && (sOut0 == activ0_1Im) && |
| (sOut1 == activ1_0Im) && (sOut1 == activ1_1Im); |
| |
| CHECK(validDataPointers); |
| } |
| |
| TEST_CASE("CreateSingleOutputMultipleInputsFloat32") |
| { |
| RefCreateSingleOutputMultipleInputsTest<RefSplitterWorkload, RefActivationWorkload, |
| armnn::DataType::Float32>(); |
| } |
| |
| TEST_CASE("CreateSingleOutputMultipleInputsUint8") |
| { |
| RefCreateSingleOutputMultipleInputsTest<RefSplitterWorkload, RefActivationWorkload, |
| armnn::DataType::QAsymmU8>(); |
| } |
| |
| template <typename ResizeBilinearWorkloadType, armnn::DataType DataType> |
| static void RefCreateResizeBilinearTest(DataLayout dataLayout) |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateResizeBilinearWorkloadTest<ResizeBilinearWorkloadType, DataType>(factory, graph, dataLayout); |
| |
| TensorShape inputShape; |
| TensorShape outputShape; |
| |
| switch (dataLayout) |
| { |
| case DataLayout::NHWC: |
| inputShape = { 2, 4, 4, 3 }; |
| outputShape = { 2, 2, 2, 3 }; |
| break; |
| case DataLayout::NCHW: |
| default: |
| inputShape = { 2, 3, 4, 4 }; |
| outputShape = { 2, 3, 2, 2 }; |
| } |
| |
| // Checks that outputs and inputs are as we expect them (see definition of CreateResizeBilinearWorkloadTest). |
| CheckInputOutput(std::move(workload), |
| TensorInfo(inputShape, DataType), |
| TensorInfo(outputShape, DataType)); |
| } |
| |
| TEST_CASE("CreateResizeBilinearFloat32") |
| { |
| RefCreateResizeBilinearTest<RefResizeWorkload, armnn::DataType::Float32>(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateResizeBilinearFloat16") |
| { |
| RefCreateResizeBilinearTest<RefResizeWorkload, armnn::DataType::Float16>(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateResizeBilinearUint8") |
| { |
| RefCreateResizeBilinearTest<RefResizeWorkload, armnn::DataType::QAsymmU8>(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateResizeBilinearQuantisedAsymm16") |
| { |
| RefCreateResizeBilinearTest<RefResizeWorkload, armnn::DataType::QSymmS16>(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateResizeBilinearFloat32Nhwc") |
| { |
| RefCreateResizeBilinearTest<RefResizeWorkload, armnn::DataType::Float32>(DataLayout::NHWC); |
| } |
| |
| template <typename BatchToSpaceNdWorkloadType, armnn::DataType DataType> |
| static void RefCreateBatchToSpaceNdTest() |
| { |
| Graph graph; |
| RefWorkloadFactory factory; |
| |
| auto workload = CreateBatchToSpaceNdWorkloadTest<BatchToSpaceNdWorkloadType, DataType>(factory, graph); |
| |
| CheckInputOutput(std::move(workload), |
| TensorInfo({ 1, 1, 1, 1 }, DataType), |
| TensorInfo({ 1, 1, 1, 1 }, DataType)); |
| } |
| |
| TEST_CASE("CreateBatchToSpaceNdFloat32") |
| { |
| RefCreateBatchToSpaceNdTest<RefBatchToSpaceNdWorkload, armnn::DataType::Float32>(); |
| } |
| |
| TEST_CASE("CreateBatchToSpaceNdFloat16") |
| { |
| RefCreateBatchToSpaceNdTest<RefBatchToSpaceNdWorkload, armnn::DataType::Float16>(); |
| } |
| |
| TEST_CASE("CreateBatchToSpaceNdUint8") |
| { |
| RefCreateBatchToSpaceNdTest<RefBatchToSpaceNdWorkload, armnn::DataType::QAsymmU8>(); |
| } |
| |
| TEST_CASE("CreateBatchToSpaceNdQSymm16") |
| { |
| RefCreateBatchToSpaceNdTest<RefBatchToSpaceNdWorkload, armnn::DataType::QSymmS16>(); |
| } |
| |
| template <typename L2NormalizationWorkloadType, armnn::DataType DataType> |
| static void RefCreateL2NormalizationTest(DataLayout dataLayout) |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = |
| CreateL2NormalizationWorkloadTest<L2NormalizationWorkloadType, DataType>(factory, graph, dataLayout); |
| |
| TensorShape inputShape; |
| TensorShape outputShape; |
| |
| switch (dataLayout) |
| { |
| case DataLayout::NHWC: |
| inputShape = { 5, 50, 67, 20 }; |
| outputShape = { 5, 50, 67, 20 }; |
| break; |
| case DataLayout::NCHW: |
| default: |
| inputShape = { 5, 20, 50, 67 }; |
| outputShape = { 5, 20, 50, 67 }; |
| break; |
| } |
| |
| // Checks that outputs and inputs are as we expect them (see definition of CreateL2NormalizationWorkloadTest). |
| CheckInputOutput(std::move(workload), TensorInfo(inputShape, DataType), TensorInfo(outputShape, DataType)); |
| } |
| |
| TEST_CASE("CreateL2NormalizationFloat32") |
| { |
| RefCreateL2NormalizationTest<RefL2NormalizationWorkload, armnn::DataType::Float32>(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateL2NormalizationFloat32Nhwc") |
| { |
| RefCreateL2NormalizationTest<RefL2NormalizationWorkload, armnn::DataType::Float32>(DataLayout::NHWC); |
| } |
| |
| TEST_CASE("CreateL2NormalizationInt16") |
| { |
| RefCreateL2NormalizationTest<RefL2NormalizationWorkload, armnn::DataType::QSymmS16>(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateL2NormalizationInt16Nhwc") |
| { |
| RefCreateL2NormalizationTest<RefL2NormalizationWorkload, armnn::DataType::QSymmS16>(DataLayout::NHWC); |
| } |
| |
| TEST_CASE("CreateL2NormalizationUint8") |
| { |
| RefCreateL2NormalizationTest<RefL2NormalizationWorkload, armnn::DataType::QAsymmU8>(DataLayout::NCHW); |
| } |
| |
| TEST_CASE("CreateL2NormalizationUint8Nhwc") |
| { |
| RefCreateL2NormalizationTest<RefL2NormalizationWorkload, armnn::DataType::QAsymmU8>(DataLayout::NHWC); |
| } |
| |
| template <typename ReshapeWorkloadType, armnn::DataType DataType> |
| static void RefCreateReshapeWorkloadTest() |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateReshapeWorkloadTest<ReshapeWorkloadType, DataType>(factory, graph); |
| |
| // Checks that outputs and inputs are as we expect them (see definition of CreateReshapeWorkloadTest). |
| CheckInputOutput( |
| std::move(workload), |
| TensorInfo({ 4, 1 }, DataType), |
| TensorInfo({ 1, 4 }, DataType)); |
| } |
| |
| TEST_CASE("CreateReshapeWorkloadFloat32") |
| { |
| RefCreateReshapeWorkloadTest<RefReshapeWorkload, armnn::DataType::Float32>(); |
| } |
| |
| TEST_CASE("CreateReshapeWorkloadQuantisedAsymm8") |
| { |
| RefCreateReshapeWorkloadTest<RefReshapeWorkload, armnn::DataType::QAsymmU8>(); |
| } |
| |
| TEST_CASE("CreateReshapeWorkloadQuantisedSymm16") |
| { |
| RefCreateReshapeWorkloadTest<RefReshapeWorkload, armnn::DataType::QSymmS16>(); |
| } |
| |
| template <typename ConcatWorkloadType, armnn::DataType DataType> |
| static void RefCreateConcatWorkloadTest(const armnn::TensorShape& outputShape, |
| unsigned int concatAxis) |
| { |
| Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateConcatWorkloadTest<ConcatWorkloadType, DataType>(factory, graph, outputShape, concatAxis); |
| |
| CheckInputsOutput(std::move(workload), |
| TensorInfo({ 2, 3, 2, 5 }, DataType), |
| TensorInfo({ 2, 3, 2, 5 }, DataType), |
| TensorInfo(outputShape, DataType)); |
| } |
| |
| TEST_CASE("CreateConcatDim0Float32Workload") |
| { |
| RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::Float32>({ 4, 3, 2, 5 }, 0); |
| } |
| |
| TEST_CASE("CreateConcatDim0Float16Workload") |
| { |
| RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::Float16>({ 4, 3, 2, 5 }, 0); |
| } |
| |
| TEST_CASE("CreateConcatDim0Uint8Workload") |
| { |
| RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::QAsymmU8>({ 4, 3, 2, 5 }, 0); |
| } |
| |
| TEST_CASE("CreateConcatDim0Uint16Workload") |
| { |
| RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::QSymmS16>({ 4, 3, 2, 5 }, 0); |
| } |
| |
| TEST_CASE("CreateConcatDim1Float32Workload") |
| { |
| RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::Float32>({ 2, 6, 2, 5 }, 1); |
| } |
| |
| TEST_CASE("CreateConcatDim1Uint8Workload") |
| { |
| RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::QAsymmU8>({ 2, 6, 2, 5 }, 1); |
| } |
| |
| TEST_CASE("CreateConcatDim2Float32Workload") |
| { |
| RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::Float32>({ 2, 3, 4, 5 }, 2); |
| } |
| |
| TEST_CASE("CreateConcatDim2Uint8Workload") |
| { |
| RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::QAsymmU8>({ 2, 3, 4, 5 }, 2); |
| } |
| |
| TEST_CASE("CreateConcatDim3Float32Workload") |
| { |
| RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::Float32>({ 2, 3, 2, 10 }, 3); |
| } |
| |
| TEST_CASE("CreateConcatDim3Uint8Workload") |
| { |
| RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::QAsymmU8>({ 2, 3, 2, 10 }, 3); |
| } |
| |
| template <typename ConstantWorkloadType, armnn::DataType DataType> |
| static void RefCreateConstantWorkloadTest(const armnn::TensorShape& outputShape) |
| { |
| armnn::Graph graph; |
| RefWorkloadFactory factory = GetFactory(); |
| auto workload = CreateConstantWorkloadTest<ConstantWorkloadType, DataType>(factory, graph, outputShape); |
| |
| // Check output is as expected |
| auto queueDescriptor = workload->GetData(); |
| auto outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); |
| CHECK((outputHandle->GetTensorInfo() == TensorInfo(outputShape, DataType))); |
| } |
| |
| TEST_CASE("CreateConstantUint8Workload") |
| { |
| RefCreateConstantWorkloadTest<RefConstantWorkload, armnn::DataType::QAsymmU8>({ 2, 3, 2, 10 }); |
| } |
| |
| TEST_CASE("CreateConstantInt16Workload") |
| { |
| RefCreateConstantWorkloadTest<RefConstantWorkload, armnn::DataType::QSymmS16>({ 2, 3, 2, 10 }); |
| } |
| |
| TEST_CASE("CreateConstantFloat32Workload") |
| { |
| RefCreateConstantWorkloadTest<RefConstantWorkload, armnn::DataType::Float32>({ 2, 3, 2, 10 }); |
| } |
| |
| TEST_CASE("CreateConstantSigned32Workload") |
| { |
| RefCreateConstantWorkloadTest<RefConstantWorkload, armnn::DataType::Signed32>({ 2, 3, 2, 10 }); |
| } |
| |
| static void RefCreatePreluWorkloadTest(const armnn::TensorShape& inputShape, |
| const armnn::TensorShape& alphaShape, |
| const armnn::TensorShape& outputShape, |
| armnn::DataType dataType) |
| { |
| armnn::Graph graph; |
| RefWorkloadFactory factory; |
| auto workload = CreatePreluWorkloadTest<RefPreluWorkload>(factory, |
| graph, |
| inputShape, |
| alphaShape, |
| outputShape, |
| dataType); |
| |
| // Check output is as expected |
| auto queueDescriptor = workload->GetData(); |
| auto outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); |
| CHECK((outputHandle->GetTensorInfo() == TensorInfo(outputShape, dataType))); |
| } |
| |
| TEST_CASE("CreatePreluFloat32Workload") |
| { |
| RefCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, armnn::DataType::Float32); |
| } |
| |
| TEST_CASE("CreatePreluFloat16Workload") |
| { |
| RefCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, armnn::DataType::Float16); |
| } |
| |
| TEST_CASE("CreatePreluUint8Workload") |
| { |
| RefCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, armnn::DataType::QAsymmU8); |
| } |
| |
| TEST_CASE("CreatePreluInt16Workload") |
| { |
| RefCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, armnn::DataType::QSymmS16); |
| } |
| |
| TEST_CASE("CreatePreluFloat32NoBroadcastWorkload") |
| { |
| CHECK_THROWS_AS(RefCreatePreluWorkloadTest({ 1, 4, 7, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, |
| armnn::DataType::Float32), |
| armnn::InvalidArgumentException); |
| } |
| |
| TEST_CASE("CreatePreluFloat16NoBroadcastWorkload") |
| { |
| CHECK_THROWS_AS(RefCreatePreluWorkloadTest({ 1, 4, 7, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, |
| armnn::DataType::Float16), |
| armnn::InvalidArgumentException); |
| } |
| |
| TEST_CASE("CreatePreluUint8NoBroadcastWorkload") |
| { |
| CHECK_THROWS_AS(RefCreatePreluWorkloadTest({ 1, 4, 7, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, |
| armnn::DataType::QAsymmU8), |
| armnn::InvalidArgumentException); |
| } |
| |
| TEST_CASE("CreatePreluInt16NoBroadcastWorkload") |
| { |
| CHECK_THROWS_AS(RefCreatePreluWorkloadTest({ 1, 4, 7, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, |
| armnn::DataType::QSymmS16), |
| armnn::InvalidArgumentException); |
| } |
| |
| template <typename SpaceToDepthWorkloadType, armnn::DataType DataType> |
| static void RefCreateSpaceToDepthWorkloadTest() |
| { |
| Graph graph; |
| RefWorkloadFactory factory; |
| |
| auto workload = CreateSpaceToDepthWorkloadTest<SpaceToDepthWorkloadType, DataType>(factory, graph); |
| |
| CheckInputOutput(std::move(workload), |
| TensorInfo({ 1, 2, 2, 1 }, DataType), |
| TensorInfo({ 1, 1, 1, 4 }, DataType)); |
| } |
| |
| TEST_CASE("CreateSpaceToDepthWorkloadFloat32") |
| { |
| RefCreateSpaceToDepthWorkloadTest<RefSpaceToDepthWorkload, armnn::DataType::Float32>(); |
| } |
| |
| TEST_CASE("CreateSpaceToDepthWorkloadFloat16") |
| { |
| RefCreateSpaceToDepthWorkloadTest<RefSpaceToDepthWorkload, armnn::DataType::Float16>(); |
| } |
| |
| TEST_CASE("CreateSpaceToDepthWorkloadQASymm8") |
| { |
| RefCreateSpaceToDepthWorkloadTest<RefSpaceToDepthWorkload, armnn::DataType::QAsymmU8>(); |
| } |
| |
| TEST_CASE("CreateSpaceToDepthWorkloadQSymm16") |
| { |
| RefCreateSpaceToDepthWorkloadTest<RefSpaceToDepthWorkload, armnn::DataType::QSymmS16>(); |
| } |
| |
| template <armnn::DataType DataType> |
| static void RefCreateStackWorkloadTest(const armnn::TensorShape& inputShape, |
| const armnn::TensorShape& outputShape, |
| unsigned int axis, |
| unsigned int numInputs) |
| { |
| armnn::Graph graph; |
| RefWorkloadFactory factory; |
| auto workload = CreateStackWorkloadTest<RefStackWorkload, DataType>(factory, |
| graph, |
| inputShape, |
| outputShape, |
| axis, |
| numInputs); |
| |
| // Check inputs and output are as expected |
| StackQueueDescriptor queueDescriptor = workload->GetData(); |
| for (unsigned int i = 0; i < numInputs; ++i) |
| { |
| auto inputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[i]); |
| CHECK((inputHandle->GetTensorInfo() == TensorInfo(inputShape, DataType))); |
| } |
| auto outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); |
| CHECK((outputHandle->GetTensorInfo() == TensorInfo(outputShape, DataType))); |
| } |
| |
| TEST_CASE("CreateStackFloat32Workload") |
| { |
| RefCreateStackWorkloadTest<armnn::DataType::Float32>({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2); |
| } |
| |
| TEST_CASE("CreateStackUint8Workload") |
| { |
| RefCreateStackWorkloadTest<armnn::DataType::QAsymmU8>({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2); |
| } |
| |
| TEST_CASE("CreateStackUint16Workload") |
| { |
| RefCreateStackWorkloadTest<armnn::DataType::QSymmS16>({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2); |
| } |
| |
| template <typename QLstmWorkloadType> |
| static void RefCreateQLstmWorkloadTest() |
| { |
| Graph graph; |
| RefWorkloadFactory factory; |
| |
| auto workload = CreateQLstmWorkloadTest<QLstmWorkloadType>(factory, graph); |
| |
| armnn::TensorInfo inputInfo({2 , 4}, armnn::DataType::QAsymmS8, 0.0078125f, 0); |
| |
| armnn::TensorInfo cellStateInfo({2 , 4}, armnn::DataType::QSymmS16, 3.05176e-05f, 0); |
| |
| armnn::TensorInfo outputInfo({2 , 4}, armnn::DataType::QAsymmS8, 0.007f, 0); |
| |
| QLstmQueueDescriptor queueDescriptor = workload->GetData(); |
| auto inputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]); |
| auto cellStateOutHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[1]); |
| auto outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[2]); |
| |
| CHECK((inputHandle->GetTensorInfo() == inputInfo)); |
| CHECK((cellStateOutHandle->GetTensorInfo() == cellStateInfo)); |
| CHECK((outputHandle->GetTensorInfo() == outputInfo)); |
| } |
| |
| TEST_CASE("CreateQLstmWorkload") |
| { |
| RefCreateQLstmWorkloadTest<RefQLstmWorkload>(); |
| } |
| |
| } |
