// // Copyright © 2017 Arm Ltd. All rights reserved. // SPDX-License-Identifier: MIT // #include "NeonL2NormalizationFloatWorkload.hpp" #include namespace armnn { using namespace armcomputetensorutils; arm_compute::Status NeonL2NormalizationWorkloadValidate(const TensorInfo& input, const TensorInfo& output, const L2NormalizationDescriptor& descriptor) { const arm_compute::TensorInfo aclInput = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); const arm_compute::TensorInfo aclOutput = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); arm_compute::NormalizationLayerInfo normalizationInfo = CreateAclNormalizationLayerInfoForL2Normalization(input, descriptor.m_DataLayout); return arm_compute::NENormalizationLayer::validate(&aclInput, &aclOutput, normalizationInfo); } NeonL2NormalizationFloatWorkload::NeonL2NormalizationFloatWorkload(const L2NormalizationQueueDescriptor& descriptor, const WorkloadInfo& info, std::shared_ptr& memoryManager) : FloatWorkload(descriptor, info) , m_Layer(memoryManager) { m_Data.ValidateInputsOutputs("NeonL2NormalizationFloatWorkload", 1, 1); arm_compute::ITensor& input = boost::polymorphic_downcast(m_Data.m_Inputs[0])->GetTensor(); arm_compute::ITensor& output = boost::polymorphic_downcast(m_Data.m_Outputs[0])->GetTensor(); arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); input.info()->set_data_layout(aclDataLayout); output.info()->set_data_layout(aclDataLayout); m_Layer.configure(&input, &output, CreateAclNormalizationLayerInfoForL2Normalization( info.m_InputTensorInfos[0], m_Data.m_Parameters.m_DataLayout)); } void NeonL2NormalizationFloatWorkload::Execute() const { ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonL2NormalizationFloatWorkload_Execute"); m_Layer.run(); } } //namespace armnn