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-rw-r--r--src/armnn/backends/test/CreateWorkloadRef.cpp219
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()
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-30 22:33:54 +0000