// // Copyright © 2017 Arm Ltd. All rights reserved. // SPDX-License-Identifier: MIT // #include "ClPooling2dWorkload.hpp" #include #include #include #include #include "ClWorkloadUtils.hpp" namespace armnn { using namespace armcomputetensorutils; arm_compute::Status ClPooling2dWorkloadValidate(const TensorInfo& input, const TensorInfo& output, const Pooling2dDescriptor& descriptor) { const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout.GetDataLayout()); const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout.GetDataLayout()); arm_compute::PoolingLayerInfo layerInfo = BuildArmComputePoolingLayerInfo(descriptor); return arm_compute::CLPoolingLayer::validate(&aclInputInfo, &aclOutputInfo, layerInfo); } ClPooling2dWorkload::ClPooling2dWorkload( const Pooling2dQueueDescriptor& descriptor, const WorkloadInfo& info) : BaseWorkload(descriptor, info) { m_Data.ValidateInputsOutputs("ClPooling2dWorkload", 1, 1); arm_compute::ICLTensor& input = static_cast(m_Data.m_Inputs[0])->GetTensor(); arm_compute::ICLTensor& output = static_cast(m_Data.m_Outputs[0])->GetTensor(); arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout.GetDataLayout()); input.info()->set_data_layout(aclDataLayout); output.info()->set_data_layout(aclDataLayout); arm_compute::PoolingLayerInfo layerInfo = BuildArmComputePoolingLayerInfo(m_Data.m_Parameters); // Run the layer. m_PoolingLayer.configure(&input, &output, layerInfo); } void ClPooling2dWorkload::Execute() const { ARMNN_SCOPED_PROFILING_EVENT_CL("ClPooling2dWorkload_Execute"); m_PoolingLayer.run(); } }