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14 using namespace armnn::armcomputetensorutils;
23 const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.
m_DataLayout);
24 const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.
m_DataLayout);
26 return arm_compute::NEInstanceNormalizationLayer::validate(&aclInputInfo,
50 input.info()->set_data_layout(aclDataLayout);
51 output.info()->set_data_layout(aclDataLayout);
53 m_Layer.configure(&input,
float m_Beta
Beta, the offset scalar value applied for the normalized tensor. Defaults to 1.0.
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
An InstanceNormalizationDescriptor for InstanceNormalizationLayer.
arm_compute::Status NeonInstanceNormalizationWorkloadValidate(const TensorInfo &input, const TensorInfo &output, const InstanceNormalizationDescriptor &descriptor)
LayerDescriptor m_Parameters
Contains information about TensorInfos of a layer.
float m_Gamma
Gamma, the scale scalar value applied for the normalized tensor. Defaults to 1.0.
void Execute() const override
std::vector< ITensorHandle * > m_Outputs
#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
InstanceNormalizationQueueDescriptor m_Data
Copyright (c) 2021 ARM Limited and Contributors.
NeonInstanceNormalizationWorkload(const InstanceNormalizationQueueDescriptor &descriptor, const WorkloadInfo &info)
#define ARMNN_SCOPED_PROFILING_EVENT_NEON_NAME_GUID(label)
Creates a profiling event that uses GetGuid() and GetName() from the calling class.
float m_Eps
Epsilon, small scalar value added to variance to avoid dividing by zero. Defaults to 1e-12f.
std::vector< ITensorHandle * > m_Inputs