17 using namespace armcomputetensorutils;
25 const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input);
26 const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output);
32 return arm_compute::NEReductionOperation::validate(&aclInputInfo,
34 static_cast<unsigned int>(coords[0]),
65 m_Layer.configure(&input,
67 static_cast<unsigned int>(coords[0]),
#define IS_MULTI_AXES_REDUCE_SUPPORTED(func, input, desc, status)
Macro function check if layer with multiple axes is supported on each backend.
NeonReduceWorkload(const ReduceQueueDescriptor &descriptor, const WorkloadInfo &info)
bool m_KeepDims
if true then output shape has no change.
std::array< unsigned int, MaxNumOfTensorDimensions > Coordinates
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
Copyright (c) 2021 ARM Limited and Contributors.
LayerDescriptor m_Parameters
arm_compute::Status NeonReduceWorkloadValidate(const TensorInfo &input, const TensorInfo &output, const ReduceDescriptor &descriptor)
void Execute() const override
arm_compute::ReductionOperation ConvertReductionOperationToAcl(const ReduceDescriptor &descriptor)
std::vector< TensorInfo > m_InputTensorInfos
ReduceQueueDescriptor m_Data
A ReduceDescriptor for the REDUCE operators.
profiling::ProfilingGuid GetGuid() const final
std::vector< uint32_t > m_vAxis
The indices of the dimensions to reduce.
std::vector< ITensorHandle * > m_Outputs
#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)
Contains information about TensorInfos of a layer.
std::vector< ITensorHandle * > m_Inputs
#define ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID(name, guid)
unsigned int GetNumDimensions() const