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));
45 std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
46 std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
51 AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
52 AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
54 std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateInstanceNormalization(descriptor, info);
56 inputHandle->Allocate();
57 outputHandle->Allocate();
68 template<armnn::DataType ArmnnType,
typename T = armnn::ResolveType<ArmnnType>>
84 std::vector<float> inputValues
107 std::vector<float> expectedOutputValues
119 0.99995005f, -0.7337929f,
121 -0.99995005f, 0.52413774f,
124 -0.99995005f, -1.1531031f,
126 0.99995005f, 1.3627582f
141 return InstanceNormTestImpl<ArmnnType>(
147 expectedOutputValues,
151 template<armnn::DataType ArmnnType,
typename T = armnn::ResolveType<ArmnnType>>
167 std::vector<float> inputValues
190 std::vector<float> expectedOutputValues
225 return InstanceNormTestImpl<ArmnnType>(
231 expectedOutputValues,
242 return InstanceNormTest<armnn::DataType::Float32>(workloadFactory, memoryManager, dataLayout);
250 return InstanceNormTest<armnn::DataType::Float16>(workloadFactory, memoryManager, dataLayout);
258 return InstanceNormTest2<armnn::DataType::Float32>(workloadFactory, memoryManager, dataLayout);
266 return InstanceNormTest2<armnn::DataType::Float16>(workloadFactory, memoryManager, dataLayout);
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
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)