16 using namespace armcomputetensorutils;
22 const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input);
23 const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output);
29 return arm_compute::NEReduceMean::validate(&aclInputInfo, coords, descriptor.
m_KeepDims, &aclOutputInfo);
std::array< unsigned int, MaxNumOfTensorDimensions > Coordinates
arm::pipe::ProfilingGuid GetGuid() const final
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
Copyright (c) 2021 ARM Limited and Contributors.
LayerDescriptor m_Parameters
std::vector< unsigned int > m_Axis
Values for the dimensions to reduce.
arm_compute::Status NeonMeanWorkloadValidate(const TensorInfo &input, const TensorInfo &output, const MeanDescriptor &descriptor)
std::vector< TensorInfo > m_InputTensorInfos
bool m_KeepDims
Enable/disable keep dimensions. If true, then the reduced dimensions that are of length 1 are kept...
MeanQueueDescriptor m_Data
std::vector< ITensorHandle * > m_Outputs
A MeanDescriptor for the MeanLayer.
#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)
Contains information about TensorInfos of a layer.
std::vector< ITensorHandle * > m_Inputs
NeonMeanWorkload(const MeanQueueDescriptor &descriptor, const WorkloadInfo &info)
#define ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID(name, guid)
unsigned int GetNumDimensions() const
void Execute() const override