diff options
Diffstat (limited to 'src/armnn/backends/test/CreateWorkloadRef.cpp')
-rw-r--r-- | src/armnn/backends/test/CreateWorkloadRef.cpp | 219 |
1 files changed, 124 insertions, 95 deletions
diff --git a/src/armnn/backends/test/CreateWorkloadRef.cpp b/src/armnn/backends/test/CreateWorkloadRef.cpp index abc46e4361..109156468a 100644 --- a/src/armnn/backends/test/CreateWorkloadRef.cpp +++ b/src/armnn/backends/test/CreateWorkloadRef.cpp @@ -39,71 +39,95 @@ void CheckInputsOutput(std::unique_ptr<Workload> workload, BOOST_AUTO_TEST_SUITE(CreateWorkloadRef) -template <typename ActivationWorkloadType> +template <typename ActivationWorkloadType, armnn::DataType DataType> static void RefCreateActivationWorkloadTest() { Graph graph; RefWorkloadFactory factory; - auto workload = CreateActivationWorkloadTest<ActivationWorkloadType>(factory, graph); + auto workload = CreateActivationWorkloadTest<ActivationWorkloadType, DataType>(factory, graph); - // check that outputs are as we expect them (see definition of CreateActivationWorkloadTest) + // Checks that outputs are as we expect them (see definition of CreateActivationWorkloadTest). CheckInputOutput(std::move(workload), - TensorInfo({ 1, 1 }, ActivationWorkloadType::ms_DataType), - TensorInfo({ 1, 1 }, ActivationWorkloadType::ms_DataType)); + TensorInfo({ 1, 1 }, DataType), + TensorInfo({ 1, 1 }, DataType)); } BOOST_AUTO_TEST_CASE(CreateActivationFloat32Workload) { - RefCreateActivationWorkloadTest<RefActivationFloat32Workload>(); + RefCreateActivationWorkloadTest<RefActivationFloat32Workload, armnn::DataType::Float32>(); } BOOST_AUTO_TEST_CASE(CreateActivationUint8Workload) { - RefCreateActivationWorkloadTest<RefActivationUint8Workload>(); + RefCreateActivationWorkloadTest<RefActivationUint8Workload, armnn::DataType::QuantisedAsymm8>(); } -template <typename AdditionWorkloadType> +template <typename AdditionWorkloadType, armnn::DataType DataType> static void RefCreateAdditionWorkloadTest() { Graph graph; RefWorkloadFactory factory; - auto workload = CreateAdditionWorkloadTest<AdditionWorkloadType>(factory, graph); + auto workload = CreateAdditionWorkloadTest<AdditionWorkloadType, DataType>(factory, graph); - // check that outputs are as we expect them (see definition of CreateAdditionWorkloadTest) + // Checks that outputs are as we expect them (see definition of CreateAdditionWorkloadTest). CheckInputsOutput(std::move(workload), - TensorInfo({ 2, 3 }, AdditionWorkloadType::ms_DataType), - TensorInfo({ 2, 3 }, AdditionWorkloadType::ms_DataType), - TensorInfo({ 2, 3 }, AdditionWorkloadType::ms_DataType)); + TensorInfo({ 2, 3 }, DataType), + TensorInfo({ 2, 3 }, DataType), + TensorInfo({ 2, 3 }, DataType)); } BOOST_AUTO_TEST_CASE(CreateAdditionFloatWorkload) { - RefCreateAdditionWorkloadTest<RefAdditionFloat32Workload>(); + RefCreateAdditionWorkloadTest<RefAdditionFloat32Workload, armnn::DataType::Float32>(); } BOOST_AUTO_TEST_CASE(CreateAdditionUint8Workload) { - RefCreateAdditionWorkloadTest<RefAdditionUint8Workload>(); + RefCreateAdditionWorkloadTest<RefAdditionUint8Workload, armnn::DataType::QuantisedAsymm8>(); } BOOST_AUTO_TEST_CASE(CreateBatchNormalizationWorkload) { Graph graph; RefWorkloadFactory factory; - auto workload = CreateBatchNormalizationWorkloadTest<RefBatchNormalizationFloat32Workload>(factory, graph); + auto workload = CreateBatchNormalizationWorkloadTest<RefBatchNormalizationFloat32Workload, armnn::DataType::Float32> + (factory, graph); - // check that outputs and inputs are as we expect them (see definition of CreateBatchNormalizationWorkloadTest) + // Checks that outputs and inputs are as we expect them (see definition of CreateBatchNormalizationWorkloadTest). CheckInputOutput( std::move(workload), TensorInfo({2, 3, 1, 1}, DataType::Float32), TensorInfo({2, 3, 1, 1}, DataType::Float32)); } +BOOST_AUTO_TEST_CASE(CreateConvertFp16ToFp32Float32Workload) +{ + Graph graph; + RefWorkloadFactory factory; + 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)); +} + +BOOST_AUTO_TEST_CASE(CreateConvertFp32ToFp16Float16Workload) +{ + Graph graph; + RefWorkloadFactory factory; + 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)); +} + BOOST_AUTO_TEST_CASE(CreateConvolution2dWorkload) { Graph graph; RefWorkloadFactory factory; - auto workload = CreateConvolution2dWorkloadTest<RefConvolution2dFloat32Workload>(factory, graph); + auto workload = CreateConvolution2dWorkloadTest<RefConvolution2dFloat32Workload, + DataType::Float32>(factory, graph); - // check that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest) + // Checks that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest). CheckInputOutput(std::move(workload), TensorInfo({2, 3, 8, 16}, DataType::Float32), TensorInfo({2, 2, 2, 10}, DataType::Float32)); @@ -116,170 +140,172 @@ BOOST_AUTO_TEST_CASE(CreateDepthwiseConvolution2dWorkload) auto workload = CreateDepthwiseConvolution2dWorkloadTest<RefDepthwiseConvolution2dFloat32Workload>(factory, graph); - // check that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest) + // Checks that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest). CheckInputOutput(std::move(workload), TensorInfo({2, 3, 8, 16}, DataType::Float32), TensorInfo({2, 9, 2, 10}, DataType::Float32)); } -template <typename FullyConnectedWorkloadType> +template <typename FullyConnectedWorkloadType, armnn::DataType DataType> static void RefCreateFullyConnectedWorkloadTest() { Graph graph; RefWorkloadFactory factory; - auto workload = CreateFullyConnectedWorkloadTest<FullyConnectedWorkloadType>(factory, graph); + auto workload = CreateFullyConnectedWorkloadTest<FullyConnectedWorkloadType, DataType>(factory, graph); - // check that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest) - float inputsQScale = FullyConnectedWorkloadType::ms_DataType == DataType::QuantisedAsymm8 ? 1.0f : 0.0; - float outputQScale = FullyConnectedWorkloadType::ms_DataType == DataType::QuantisedAsymm8 ? 2.0f : 0.0; + // Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest). + float inputsQScale = DataType == armnn::DataType::QuantisedAsymm8 ? 1.0f : 0.0; + float outputQScale = DataType == armnn::DataType::QuantisedAsymm8 ? 2.0f : 0.0; CheckInputOutput(std::move(workload), - TensorInfo({ 3, 1, 4, 5 }, FullyConnectedWorkloadType::ms_DataType, inputsQScale), - TensorInfo({ 3, 7 }, FullyConnectedWorkloadType::ms_DataType, outputQScale)); + TensorInfo({ 3, 1, 4, 5 }, DataType, inputsQScale), + TensorInfo({ 3, 7 }, DataType, outputQScale)); } BOOST_AUTO_TEST_CASE(CreateFullyConnectedFloat32Workload) { - RefCreateFullyConnectedWorkloadTest<RefFullyConnectedFloat32Workload>(); + RefCreateFullyConnectedWorkloadTest<RefFullyConnectedFloat32Workload, armnn::DataType::Float32>(); } BOOST_AUTO_TEST_CASE(CreateFullyConnectedUint8Workload) { - RefCreateFullyConnectedWorkloadTest<RefFullyConnectedUint8Workload>(); + RefCreateFullyConnectedWorkloadTest<RefFullyConnectedUint8Workload, armnn::DataType::QuantisedAsymm8>(); } -template <typename MultiplicationWorkloadType> +template <typename MultiplicationWorkloadType, armnn::DataType DataType> static void RefCreateMultiplicationWorkloadTest() { Graph graph; RefWorkloadFactory factory; - auto workload = CreateMultiplicationWorkloadTest<MultiplicationWorkloadType>(factory, graph); + auto workload = CreateMultiplicationWorkloadTest<MultiplicationWorkloadType, DataType>(factory, graph); - // check that outputs are as we expect them (see definition of CreateMultiplicationWorkloadTest) + // Checks that outputs are as we expect them (see definition of CreateMultiplicationWorkloadTest). CheckInputsOutput(std::move(workload), - TensorInfo({ 2, 3 }, MultiplicationWorkloadType::ms_DataType), - TensorInfo({ 2, 3 }, MultiplicationWorkloadType::ms_DataType), - TensorInfo({ 2, 3 }, MultiplicationWorkloadType::ms_DataType)); + TensorInfo({ 2, 3 }, DataType), + TensorInfo({ 2, 3 }, DataType), + TensorInfo({ 2, 3 }, DataType)); } BOOST_AUTO_TEST_CASE(CreateMultiplicationFloatWorkload) { - RefCreateMultiplicationWorkloadTest<RefMultiplicationFloat32Workload>(); + RefCreateMultiplicationWorkloadTest<RefMultiplicationFloat32Workload, armnn::DataType::Float32>(); } BOOST_AUTO_TEST_CASE(CreateMultiplicationUint8Workload) { - RefCreateMultiplicationWorkloadTest<RefMultiplicationUint8Workload>(); + RefCreateMultiplicationWorkloadTest<RefMultiplicationUint8Workload, armnn::DataType::QuantisedAsymm8>(); } BOOST_AUTO_TEST_CASE(CreateNormalizationWorkload) { Graph graph; RefWorkloadFactory factory; - auto workload = CreateNormalizationWorkloadTest<RefNormalizationFloat32Workload>(factory, graph); + auto workload = CreateNormalizationWorkloadTest<RefNormalizationFloat32Workload, + armnn::DataType::Float32>(factory, graph); - // check that outputs and inputs are as we expect them (see definition of CreateNormalizationWorkloadTest) + // Checks that outputs and inputs are as we expect them (see definition of CreateNormalizationWorkloadTest). CheckInputOutput(std::move(workload), TensorInfo({3, 5, 5, 1}, DataType::Float32), TensorInfo({3, 5, 5, 1}, DataType::Float32)); } -template <typename Pooling2dWorkloadType> +template <typename Pooling2dWorkloadType, armnn::DataType DataType> static void RefCreatePooling2dWorkloadTest() { Graph graph; RefWorkloadFactory factory; - auto workload = CreatePooling2dWorkloadTest<Pooling2dWorkloadType>(factory, graph); + auto workload = CreatePooling2dWorkloadTest<Pooling2dWorkloadType, DataType>(factory, graph); - // check that outputs and inputs are as we expect them (see definition of CreatePooling2dWorkloadTest) + // Checks that outputs and inputs are as we expect them (see definition of CreatePooling2dWorkloadTest). CheckInputOutput( std::move(workload), - TensorInfo({3, 2, 5, 5}, Pooling2dWorkloadType::ms_DataType), - TensorInfo({3, 2, 2, 4}, Pooling2dWorkloadType::ms_DataType)); + TensorInfo({3, 2, 5, 5}, DataType), + TensorInfo({3, 2, 2, 4}, DataType)); } BOOST_AUTO_TEST_CASE(CreatePooling2dFloat32Workload) { - RefCreatePooling2dWorkloadTest<RefPooling2dFloat32Workload>(); + RefCreatePooling2dWorkloadTest<RefPooling2dFloat32Workload, armnn::DataType::Float32>(); } BOOST_AUTO_TEST_CASE(CreatePooling2dUint8Workload) { - RefCreatePooling2dWorkloadTest<RefPooling2dUint8Workload>(); + RefCreatePooling2dWorkloadTest<RefPooling2dUint8Workload, armnn::DataType::QuantisedAsymm8>(); } -template <typename SoftmaxWorkloadType> +template <typename SoftmaxWorkloadType, armnn::DataType DataType> static void RefCreateSoftmaxWorkloadTest() { Graph graph; RefWorkloadFactory factory; - auto workload = CreateSoftmaxWorkloadTest<SoftmaxWorkloadType>(factory, graph); + auto workload = CreateSoftmaxWorkloadTest<SoftmaxWorkloadType, DataType>(factory, graph); - // check that outputs and inputs are as we expect them (see definition of CreateSoftmaxWorkloadTest) + // Checks that outputs and inputs are as we expect them (see definition of CreateSoftmaxWorkloadTest). CheckInputOutput( std::move(workload), - TensorInfo({4, 1}, SoftmaxWorkloadType::ms_DataType), - TensorInfo({4, 1}, SoftmaxWorkloadType::ms_DataType)); + TensorInfo({4, 1}, DataType), + TensorInfo({4, 1}, DataType)); } BOOST_AUTO_TEST_CASE(CreateSoftmaxFloat32Workload) { - RefCreateSoftmaxWorkloadTest<RefSoftmaxFloat32Workload>(); + RefCreateSoftmaxWorkloadTest<RefSoftmaxFloat32Workload, armnn::DataType::Float32>(); } BOOST_AUTO_TEST_CASE(CreateSoftmaxUint8Workload) { - RefCreateSoftmaxWorkloadTest<RefSoftmaxUint8Workload>(); + RefCreateSoftmaxWorkloadTest<RefSoftmaxUint8Workload, armnn::DataType::QuantisedAsymm8>(); } -template <typename SplitterWorkloadType> +template <typename SplitterWorkloadType, armnn::DataType DataType> static void RefCreateSplitterWorkloadTest() { Graph graph; RefWorkloadFactory factory; - auto workload = CreateSplitterWorkloadTest<SplitterWorkloadType>(factory, graph); + auto workload = CreateSplitterWorkloadTest<SplitterWorkloadType, DataType>(factory, graph); - // check that outputs are as we expect them (see definition of CreateSplitterWorkloadTest) + // Checks that outputs are as we expect them (see definition of CreateSplitterWorkloadTest). SplitterQueueDescriptor queueDescriptor = workload->GetData(); auto inputHandle = boost::polymorphic_downcast<ConstCpuTensorHandle*>(queueDescriptor.m_Inputs[0]); - BOOST_TEST((inputHandle->GetTensorInfo() == TensorInfo({ 5, 7, 7 }, SplitterWorkloadType::ms_DataType))); + BOOST_TEST((inputHandle->GetTensorInfo() == TensorInfo({ 5, 7, 7 }, DataType))); auto outputHandle0 = boost::polymorphic_downcast<CpuTensorHandle*>(queueDescriptor.m_Outputs[0]); - BOOST_TEST((outputHandle0->GetTensorInfo() == TensorInfo({ 1, 7, 7 }, SplitterWorkloadType::ms_DataType))); + BOOST_TEST((outputHandle0->GetTensorInfo() == TensorInfo({ 1, 7, 7 }, DataType))); auto outputHandle1 = boost::polymorphic_downcast<CpuTensorHandle*>(queueDescriptor.m_Outputs[1]); - BOOST_TEST((outputHandle1->GetTensorInfo() == TensorInfo({ 2, 7, 7 }, SplitterWorkloadType::ms_DataType))); + BOOST_TEST((outputHandle1->GetTensorInfo() == TensorInfo({ 2, 7, 7 }, DataType))); auto outputHandle2 = boost::polymorphic_downcast<CpuTensorHandle*>(queueDescriptor.m_Outputs[2]); - BOOST_TEST((outputHandle2->GetTensorInfo() == TensorInfo({ 2, 7, 7 }, SplitterWorkloadType::ms_DataType))); + BOOST_TEST((outputHandle2->GetTensorInfo() == TensorInfo({ 2, 7, 7 }, DataType))); } BOOST_AUTO_TEST_CASE(CreateSplitterFloat32Workload) { - RefCreateSplitterWorkloadTest<RefSplitterFloat32Workload>(); + RefCreateSplitterWorkloadTest<RefSplitterFloat32Workload, armnn::DataType::Float32>(); } BOOST_AUTO_TEST_CASE(CreateSplitterUint8Workload) { - RefCreateSplitterWorkloadTest<RefSplitterUint8Workload>(); + RefCreateSplitterWorkloadTest<RefSplitterUint8Workload, armnn::DataType::QuantisedAsymm8>(); } -template <typename SplitterWorkloadType, typename MergerWorkloadType> +template <typename SplitterWorkloadType, typename MergerWorkloadType, armnn::DataType DataType> static void RefCreateSplitterMergerWorkloadTest() { - // Test that it is possible to decide which output of the splitter layer - // should be lined to which input of the merger layer - // We test that is is possible to specify 0th output - // of the splitter to be the 1st input to the merger and the 1st output of the splitter to be 0th input + // Tests that it is possible to decide which output of the splitter layer + // should be lined to which input of the merger layer. + // We tested that is is possible to specify 0th output + // of the splitter to be the 1st input to the merger and the 1st output of the splitter to be 0th input // of the merger. Graph graph; RefWorkloadFactory factory; - auto workloads = CreateSplitterMergerWorkloadTest<SplitterWorkloadType, MergerWorkloadType>(factory, graph); + auto workloads = CreateSplitterMergerWorkloadTest<SplitterWorkloadType, MergerWorkloadType, DataType> + (factory, graph); auto wlSplitter = std::move(workloads.first); auto wlMerger = std::move(workloads.second); - //check that the index of inputs/outputs matches what we declared on InputDescriptor construction. + //Checks that the index of inputs/outputs matches what we declared on InputDescriptor construction. armnn::CpuTensorHandle* sOut0 = dynamic_cast<armnn::CpuTensorHandle*>(wlSplitter->GetData().m_Outputs[0]); armnn::CpuTensorHandle* sOut1 = dynamic_cast<armnn::CpuTensorHandle*>(wlSplitter->GetData().m_Outputs[1]); armnn::CpuTensorHandle* mIn0 = dynamic_cast<armnn::CpuTensorHandle*>(wlMerger->GetData().m_Inputs[0]); @@ -297,19 +323,19 @@ static void RefCreateSplitterMergerWorkloadTest() BOOST_AUTO_TEST_CASE(CreateSplitterMergerFloat32) { - RefCreateSplitterMergerWorkloadTest<RefSplitterFloat32Workload, RefMergerFloat32Workload>(); + RefCreateSplitterMergerWorkloadTest<RefSplitterFloat32Workload, RefMergerFloat32Workload, DataType::Float32>(); } BOOST_AUTO_TEST_CASE(CreateSplitterMergerUint8) { - RefCreateSplitterMergerWorkloadTest<RefSplitterUint8Workload, RefMergerUint8Workload>(); + RefCreateSplitterMergerWorkloadTest<RefSplitterUint8Workload, RefMergerUint8Workload, DataType::QuantisedAsymm8>(); } -template <typename SplitterWorkloadType, typename ActivationWorkloadType> +template <typename SplitterWorkloadType, typename ActivationWorkloadType, armnn::DataType DataType> static void RefCreateSingleOutputMultipleInputsTest() { - // Test that it is possible to assign multiple (two) different layers to each of the outputs of a splitter layer. - // We create a splitter with two outputs. That each of those outputs is used by two different activation layers + // 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; @@ -320,7 +346,7 @@ static void RefCreateSingleOutputMultipleInputsTest() std::unique_ptr<ActivationWorkloadType> wlActiv1_1; CreateSplitterMultipleInputsOneOutputWorkloadTest<SplitterWorkloadType, - ActivationWorkloadType>(factory, graph, wlSplitter, wlActiv0_0, wlActiv0_1, wlActiv1_0, wlActiv1_1); + ActivationWorkloadType, DataType>(factory, graph, wlSplitter, wlActiv0_0, wlActiv0_1, wlActiv1_0, wlActiv1_1); armnn::CpuTensorHandle* sOut0 = dynamic_cast<armnn::CpuTensorHandle*>(wlSplitter->GetData().m_Outputs[0]); armnn::CpuTensorHandle* sOut1 = dynamic_cast<armnn::CpuTensorHandle*>(wlSplitter->GetData().m_Outputs[1]); @@ -345,73 +371,76 @@ static void RefCreateSingleOutputMultipleInputsTest() BOOST_AUTO_TEST_CASE(CreateSingleOutputMultipleInputsFloat32) { - RefCreateSingleOutputMultipleInputsTest<RefSplitterFloat32Workload, RefActivationFloat32Workload>(); + RefCreateSingleOutputMultipleInputsTest<RefSplitterFloat32Workload, RefActivationFloat32Workload, + armnn::DataType::Float32>(); } BOOST_AUTO_TEST_CASE(CreateSingleOutputMultipleInputsUint8) { - RefCreateSingleOutputMultipleInputsTest<RefSplitterUint8Workload, RefActivationUint8Workload>(); + RefCreateSingleOutputMultipleInputsTest<RefSplitterUint8Workload, RefActivationUint8Workload, + armnn::DataType::QuantisedAsymm8>(); } -template <typename ResizeBilinearWorkloadType> +template <typename ResizeBilinearWorkloadType, armnn::DataType DataType> static void RefCreateResizeBilinearTest() { Graph graph; RefWorkloadFactory factory; - auto workload = CreateResizeBilinearWorkloadTest<ResizeBilinearWorkloadType>(factory, graph); + auto workload = CreateResizeBilinearWorkloadTest<ResizeBilinearWorkloadType, DataType>(factory, graph); - // check that outputs and inputs are as we expect them (see definition of CreateResizeBilinearWorkloadTest) + // Checks that outputs and inputs are as we expect them (see definition of CreateResizeBilinearWorkloadTest). CheckInputOutput( std::move(workload), - TensorInfo({ 2, 3, 4, 4 }, ResizeBilinearWorkloadType::ms_DataType), - TensorInfo({ 2, 3, 2, 2 }, ResizeBilinearWorkloadType::ms_DataType)); + TensorInfo({ 2, 3, 4, 4 }, DataType), + TensorInfo({ 2, 3, 2, 2 }, DataType)); } BOOST_AUTO_TEST_CASE(CreateResizeBilinearFloat32) { - RefCreateResizeBilinearTest<RefResizeBilinearFloat32Workload>(); + RefCreateResizeBilinearTest<RefResizeBilinearFloat32Workload, armnn::DataType::Float32>(); } BOOST_AUTO_TEST_CASE(CreateResizeBilinearUint8) { - RefCreateResizeBilinearTest<RefResizeBilinearUint8Workload>(); + RefCreateResizeBilinearTest<RefResizeBilinearUint8Workload, armnn::DataType::QuantisedAsymm8>(); } BOOST_AUTO_TEST_CASE(CreateL2NormalizationFloat32) { Graph graph; RefWorkloadFactory factory; - auto workload = CreateL2NormalizationWorkloadTest<RefL2NormalizationFloat32Workload>(factory, graph); + auto workload = CreateL2NormalizationWorkloadTest<RefL2NormalizationFloat32Workload, armnn::DataType::Float32> + (factory, graph); - // check that outputs and inputs are as we expect them (see definition of CreateL2NormalizationWorkloadTest) + // Checks that outputs and inputs are as we expect them (see definition of CreateL2NormalizationWorkloadTest). CheckInputOutput( std::move(workload), - TensorInfo({ 5, 20, 50, 67 }, RefL2NormalizationFloat32Workload::ms_DataType), - TensorInfo({ 5, 20, 50, 67 }, RefL2NormalizationFloat32Workload::ms_DataType)); + TensorInfo({ 5, 20, 50, 67 }, armnn::DataType::Float32), + TensorInfo({ 5, 20, 50, 67 }, armnn::DataType::Float32)); } -template <typename ReshapeWorkloadType> +template <typename ReshapeWorkloadType, armnn::DataType DataType> static void RefCreateReshapeWorkloadTest() { Graph graph; RefWorkloadFactory factory; - auto workload = CreateReshapeWorkloadTest<ReshapeWorkloadType>(factory, graph); + auto workload = CreateReshapeWorkloadTest<ReshapeWorkloadType, DataType>(factory, graph); - // check that outputs and inputs are as we expect them (see definition of CreateReshapeWorkloadTest) + // Checks that outputs and inputs are as we expect them (see definition of CreateReshapeWorkloadTest). CheckInputOutput( std::move(workload), - TensorInfo({ 4, 1 }, ReshapeWorkloadType::ms_DataType), - TensorInfo({ 1, 4 }, ReshapeWorkloadType::ms_DataType)); + TensorInfo({ 4, 1 }, DataType), + TensorInfo({ 1, 4 }, DataType)); } BOOST_AUTO_TEST_CASE(CreateReshapeFloat32Workload) { - RefCreateReshapeWorkloadTest<RefReshapeFloat32Workload>(); + RefCreateReshapeWorkloadTest<RefReshapeFloat32Workload, armnn::DataType::Float32>(); } BOOST_AUTO_TEST_CASE(CreateReshapeUint8Workload) { - RefCreateReshapeWorkloadTest<RefReshapeUint8Workload>(); + RefCreateReshapeWorkloadTest<RefReshapeUint8Workload, armnn::DataType::QuantisedAsymm8>(); } BOOST_AUTO_TEST_SUITE_END() |