25 template<armnn::DataType ArmnnType,
typename T = armnn::ResolveType<ArmnnType>>
31 const std::vector<float>& inputValues,
32 const std::vector<float>& expectedOutputValues,
38 auto inputTensor = MakeTensor<T, 4>(inputTensorInfo,
39 armnnUtils::QuantizedVector<T>(inputValues, qScale, qOffset));
42 result.outputExpected = MakeTensor<T, 4>(outputTensorInfo,
43 armnnUtils::QuantizedVector<T>(expectedOutputValues, qScale, qOffset));
46 std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
47 std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
53 AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
54 AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
56 std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateInstanceNormalization(descriptor, info);
58 inputHandle->Allocate();
59 outputHandle->Allocate();
70 template<armnn::DataType ArmnnType,
typename T = armnn::ResolveType<ArmnnType>>
86 std::vector<float> inputValues
109 std::vector<float> expectedOutputValues
121 0.99995005f, -0.7337929f,
123 -0.99995005f, 0.52413774f,
126 -0.99995005f, -1.1531031f,
128 0.99995005f, 1.3627582f
143 return InstanceNormTestImpl<ArmnnType>(
149 expectedOutputValues,
153 template<armnn::DataType ArmnnType,
typename T = armnn::ResolveType<ArmnnType>>
169 std::vector<float> inputValues
192 std::vector<float> expectedOutputValues
227 return InstanceNormTestImpl<ArmnnType>(
233 expectedOutputValues,
244 return InstanceNormTest<armnn::DataType::Float32>(workloadFactory, memoryManager, dataLayout);
252 return InstanceNormTest<armnn::DataType::Float16>(workloadFactory, memoryManager, dataLayout);
260 return InstanceNormTest2<armnn::DataType::Float32>(workloadFactory, memoryManager, dataLayout);
268 return InstanceNormTest2<armnn::DataType::Float16>(workloadFactory, memoryManager, dataLayout);
#define ARMNN_NO_DEPRECATE_WARN_BEGIN
float m_Gamma
Gamma, the scale scalar value applied for the normalized tensor. Defaults to 1.0. ...
LayerTestResult< float, 4 > InstanceNormFloat32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::DataLayout dataLayout)
LayerTestResult< armnn::Half, 4 > InstanceNormFloat16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::DataLayout dataLayout)
void IgnoreUnused(Ts &&...)
LayerDescriptor m_Parameters
#define ARMNN_NO_DEPRECATE_WARN_END
float m_Eps
Epsilon, small scalar value added to variance to avoid dividing by zero. Defaults to 1e-12f...
std::shared_ptr< IMemoryManager > IMemoryManagerSharedPtr
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. ...
Contains information about inputs and outputs to a layer.
LayerTestResult< armnn::Half, 4 > InstanceNormFloat16Test2(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::DataLayout dataLayout)
LayerTestResult< float, 4 > InstanceNormFloat32Test2(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::DataLayout dataLayout)
void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)
void PermuteTensorNhwcToNchw(armnn::TensorInfo &tensorInfo, std::vector< T > &tensorData)