15 using namespace armcomputetensorutils;
21 const arm_compute::TensorInfo aclInput = BuildArmComputeTensorInfo(input, descriptor.
m_DataLayout);
22 const arm_compute::TensorInfo aclOutput = BuildArmComputeTensorInfo(output, descriptor.
m_DataLayout);
26 return arm_compute::CLL2NormalizeLayer::validate(&aclInput, &aclOutput, axis, descriptor.
m_Eps);
39 input.info()->set_data_layout(aclDataLayout);
40 output.info()->set_data_layout(aclDataLayout);
44 m_Layer.configure(&input, &output, axis,
m_Data.m_Parameters.m_Eps);
float m_Eps
Used to avoid dividing by zero.
arm_compute::Status ClL2NormalizationWorkloadValidate(const TensorInfo &input, const TensorInfo &output, const L2NormalizationDescriptor &descriptor)
#define ARMNN_SCOPED_PROFILING_EVENT_CL(name)
void RunClFunction(arm_compute::IFunction &function, const CheckLocation &location)
const QueueDescriptor m_Data
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
Copyright (c) 2020 ARM Limited.
void Execute() const override
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
A L2NormalizationDescriptor for the L2NormalizationLayer.
std::vector< ITensorHandle * > m_Outputs
Contains information about inputs and outputs to a layer.
std::vector< ITensorHandle * > m_Inputs
ClL2NormalizationFloatWorkload(const L2NormalizationQueueDescriptor &descriptor, const WorkloadInfo &info)