ClTransposeConvolution2dWorkload.cpp

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//
// Copyright © 2019-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
 
#include "ClTransposeConvolution2dWorkload.hpp"
 
#include "ClWorkloadUtils.hpp"
 
#include <cl/ClLayerSupport.hpp>
#include <cl/ClTensorHandle.hpp>
#include <cl/ClLayerSupport.hpp>
 
#include <aclCommon/ArmComputeUtils.hpp>
#include <aclCommon/ArmComputeTensorUtils.hpp>
 
#include <armnn/backends/TensorHandle.hpp>
 
#include <arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h>
 
namespace armnn
{
 
using namespace armcomputetensorutils;
 
arm_compute::Status ClTransposeConvolution2dWorkloadValidate(const TensorInfo& input,
                                                             const TensorInfo& output,
                                                             const TransposeConvolution2dDescriptor& descriptor,
                                                             const TensorInfo& weights,
                                                             const Optional<TensorInfo>& biases)
{
    arm_compute::TensorInfo aclInputInfo   = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
    arm_compute::TensorInfo aclOutputInfo  = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout);
    arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout);
 
    arm_compute::TensorInfo aclBiasesInfo;
    arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr;
 
    if (descriptor.m_BiasEnabled)
    {
        if (!biases.has_value())
        {
            return arm_compute::Status{arm_compute::ErrorCode::RUNTIME_ERROR,
                                        "ArmNN ClTransposeConv2dWorkload has empty bias value."};
        }
        aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout);
        optionalAclBiasesInfo = &aclBiasesInfo;
    }
 
    arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(descriptor);
 
    return arm_compute::CLDeconvolutionLayer::validate(&aclInputInfo,
                                                       &aclWeightsInfo,
                                                       optionalAclBiasesInfo,
                                                       &aclOutputInfo,
                                                       padStrideInfo);
}
 
ClTransposeConvolution2dWorkload::ClTransposeConvolution2dWorkload(
    const TransposeConvolution2dQueueDescriptor& descriptor,
    const WorkloadInfo& info,
    std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager,
    const arm_compute::CLCompileContext& clCompileContext)
    : ClBaseWorkload<TransposeConvolution2dQueueDescriptor>(descriptor, info)
    , m_Layer(memoryManager)
{
    // Add details for profiling output
    WorkloadInfo detailsInfo;
 
    detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos;
    detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos;
    detailsInfo.m_WeightsTensorInfo = armnn::Optional<armnn::TensorInfo>(descriptor.m_Weight->GetTensorInfo());
    if (descriptor.m_Parameters.m_BiasEnabled)
    {
        detailsInfo.m_BiasTensorInfo = armnn::Optional<armnn::TensorInfo>(descriptor.m_Bias->GetTensorInfo());
    }
 
    // Report Profiling Details
    ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClTransposeConvolution2dWorkload_Construct",
                                         descriptor.m_Parameters,
                                         detailsInfo,
                                         this->GetGuid());
 
    const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo();
 
    m_WeightsTensor = std::make_unique<arm_compute::CLTensor>();
    BuildArmComputeTensor(*m_WeightsTensor, weightInfo, m_Data.m_Parameters.m_DataLayout);
 
    if (m_Data.m_Parameters.m_BiasEnabled)
    {
        m_BiasesTensor = std::make_unique<arm_compute::CLTensor>();
        BuildArmComputeTensor(*m_BiasesTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout);
    }
 
    m_Data.ValidateInputsOutputs("ClTransposeConvolution2dWorkload", 1, 1);
 
    arm_compute::ICLTensor& input  = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
    arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(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);
 
    arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(m_Data.m_Parameters);
    {
        ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID("ClTransposeConvolution2dWorkload_configure");
        m_Layer.configure(clCompileContext, &input, m_WeightsTensor.get(), m_BiasesTensor.get(), &output,
                          padStrideInfo);
    }
 
    InitializeArmComputeClTensorData(*m_WeightsTensor, m_Data.m_Weight);
    if (m_BiasesTensor)
    {
        InitializeArmComputeClTensorData(*m_BiasesTensor, m_Data.m_Bias);
    }
 
    m_Layer.prepare();
 
    FreeUnusedTensors();
}
 
void ClTransposeConvolution2dWorkload::Execute() const
{
    ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID("ClTransposeConvolution2dWorkload_Execute");
    RunClFunction(m_Layer, CHECK_LOCATION());
}
 
void ClTransposeConvolution2dWorkload::FreeUnusedTensors()
{
    FreeTensorIfUnused(m_WeightsTensor);
    FreeTensorIfUnused(m_BiasesTensor);
}
 
} // namespace armnn