25 template<armnn::DataType ArmnnType,
typename T = armnn::ResolveType<ArmnnType>>
32 const std::vector<float>& inputValues,
33 const std::vector<float>& expectedOutputValues,
39 std::vector<T> inputTensor = armnnUtils::QuantizedVector<T>(inputValues, qScale, qOffset);
40 std::vector<T> expectedOutput = armnnUtils::QuantizedVector<T>(expectedOutputValues, qScale, qOffset);
43 std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.
CreateTensorHandle(inputTensorInfo);
44 std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.
CreateTensorHandle(outputTensorInfo);
48 AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
49 AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
53 inputHandle->Allocate();
54 outputHandle->Allocate();
64 outputHandle->GetShape(),
68 template<armnn::DataType ArmnnType,
typename T = armnn::ResolveType<ArmnnType>>
85 std::vector<float> inputValues
108 std::vector<float> expectedOutputValues
120 0.99995005f, -0.7337929f,
122 -0.99995005f, 0.52413774f,
125 -0.99995005f, -1.1531031f,
127 0.99995005f, 1.3627582f
142 return InstanceNormTestImpl<ArmnnType>(
149 expectedOutputValues,
153 template<armnn::DataType ArmnnType,
typename T = armnn::ResolveType<ArmnnType>>
170 std::vector<float> inputValues
193 std::vector<float> expectedOutputValues
228 return InstanceNormTestImpl<ArmnnType>(
235 expectedOutputValues,
247 return InstanceNormTest<armnn::DataType::Float32>(workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
256 return InstanceNormTest<armnn::DataType::Float16>(workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
265 return InstanceNormTest2<armnn::DataType::Float32>(workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
274 return InstanceNormTest2<armnn::DataType::Float16>(workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
const TensorShape & GetShape() const
virtual std::unique_ptr< IWorkload > CreateInstanceNormalization(const InstanceNormalizationQueueDescriptor &descriptor, const WorkloadInfo &info) const
float m_Gamma
Gamma, the scale scalar value applied for the normalized tensor. Defaults to 1.0. ...
LayerTestResult< float, 4 > InstanceNormFloat32Test2(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, armnn::DataLayout dataLayout)
void IgnoreUnused(Ts &&...)
LayerTestResult< armnn::Half, 4 > InstanceNormFloat16Test2(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, armnn::DataLayout dataLayout)
LayerDescriptor m_Parameters
float m_Eps
Epsilon, small scalar value added to variance to avoid dividing by zero. Defaults to 1e-12f...
std::shared_ptr< IMemoryManager > IMemoryManagerSharedPtr
LayerTestResult< armnn::Half, 4 > InstanceNormFloat16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, armnn::DataLayout dataLayout)
void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
float m_Beta
Beta, the offset scalar value applied for the normalized tensor. Defaults to 1.0. ...
LayerTestResult< float, 4 > InstanceNormFloat32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, armnn::DataLayout dataLayout)
Contains information about TensorInfos of a layer.
virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0
unsigned int GetNumElements() const
void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)
void PermuteTensorNhwcToNchw(armnn::TensorInfo &tensorInfo, std::vector< T > &tensorData)