8 #include <DataTypeUtils.hpp> 19 template<armnn::DataType ArmnnType,
typename T = armnn::ResolveType<ArmnnType>>
26 const std::vector<float>& inputData,
27 const std::vector<float>& outputData,
28 const std::vector<int32_t> vAxis,
30 bool keepDims =
false)
33 auto inputTensor = ConvertToDataType<ArmnnType>(inputData, inputTensorInfo);
35 std::vector<float> actualOutput(outputTensorInfo.
GetNumElements());
37 std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.
CreateTensorHandle(inputTensorInfo);
38 std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.
CreateTensorHandle(outputTensorInfo);
41 std::vector<uint32_t> updated_idx;
42 uint32_t resolvedAxis = 0;
43 for (uint32_t i = 0; i < vAxis.size(); ++i)
47 resolvedAxis = inputTensorInfo.
GetNumDimensions() +
static_cast<uint32_t
>(vAxis[i]);
50 resolvedAxis =
static_cast<uint32_t
>(vAxis[i]);
53 updated_idx.push_back(resolvedAxis);
61 AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
62 AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
68 inputHandle->Allocate();
69 outputHandle->Allocate();
79 outputHandle->GetShape(),
85 template<armnn::DataType ArmnnType,
typename T>
96 if (armnn::IsQuantizedType<T>())
104 std::vector<float> inputValues
106 1001.0f, 11.0f, 1003.0f,
107 10.0f, 1002.0f, 12.0f
109 std::vector<float> outputValues
111 1001.0f, 1002.0f, 1003.0f
114 return ReductionTestCommon<ArmnnType>(workloadFactory,
125 template<armnn::DataType ArmnnType,
typename T>
136 if (armnn::IsQuantizedType<T>())
144 std::vector<float> inputValues
146 1001.0f, 11.0f, 1003.0f,
147 10.0f, 1002.0f, 12.0f
149 std::vector<float> outputValues
154 return ReductionTestCommon<ArmnnType>(workloadFactory,
166 template<armnn::DataType ArmnnType,
typename T>
177 if (armnn::IsQuantizedType<T>())
185 std::vector<float> inputValues
191 std::vector<float> outputValues
196 return ReductionTestCommon<ArmnnType>(workloadFactory,
208 template<armnn::DataType ArmnnType,
typename T>
219 if (armnn::IsQuantizedType<T>())
227 std::vector<float> inputValues
229 1001.0f, 11.0f, 1003.0f,
230 10.0f, 1002.0f, 12.0f
232 std::vector<float> outputValues
237 return ReductionTestCommon<ArmnnType>(workloadFactory,
248 template<armnn::DataType ArmnnType,
typename T>
259 if (armnn::IsQuantizedType<T>())
267 std::vector<float> inputValues
269 1001.0f, 11.0f, 1003.0f,
270 10.0f, 1002.0f, 12.0f
272 std::vector<float> outputValues
277 return ReductionTestCommon<ArmnnType>(workloadFactory,
291 ReduceMaxSimpleTest<armnn::DataType::Float32>(
297 ReduceMaxNegativeAxisTest<armnn::DataType::Float32>(
303 ReduceMaxSimpleTest2<armnn::DataType::Float32>(
309 ReduceMinSimpleTest<armnn::DataType::Float32>(
315 ReduceMinNegativeAxisTest<armnn::DataType::Float32>(
const TensorShape & GetShape() const
bool m_KeepDims
if true then output shape has no change.
LayerTestResult< float, 4 > ReduceMaxSimpleTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
ReduceOperation m_ReduceOperation
Specifies the reduction operation to execute.
void IgnoreUnused(Ts &&...)
LayerDescriptor m_Parameters
LayerTestResult< float, 4 > ReduceMinNegativeAxisTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
std::shared_ptr< IMemoryManager > IMemoryManagerSharedPtr
void CopyDataFromITensorHandle(void *mem, const armnn::ITensorHandle *tensorHandle)
LayerTestResult< float, 4 > ReduceMinSimpleTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
void SetQuantizationScale(float scale)
LayerTestResult< float, 4 > ReduceMaxNegativeAxisTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
std::vector< uint32_t > m_vAxis
The indices of the dimensions to reduce.
LayerTestResult< float, 4 > ReduceMaxSimpleTest2(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)
Contains information about TensorInfos of a layer.
void SetQuantizationOffset(int32_t offset)
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const
unsigned int GetNumDimensions() const
virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0
unsigned int GetNumElements() const