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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ClConvolution2dUint8Workload.hpp"
#include <backends/cl/ClTensorHandle.hpp>
#include <backends/CpuTensorHandle.hpp>
#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
#include <backends/cl/ClLayerSupport.hpp>
#include "ClWorkloadUtils.hpp"
namespace armnn
{
using namespace armcomputetensorutils;
ClConvolution2dUint8Workload::ClConvolution2dUint8Workload(const Convolution2dQueueDescriptor& descriptor,
const WorkloadInfo& info, std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
: Uint8Workload<Convolution2dQueueDescriptor>(descriptor, info)
, m_ConvolutionLayer(memoryManager)
{
// todo: check tensor shapes match
const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo();
m_KernelTensor = std::make_unique<arm_compute::CLTensor>();
BuildArmComputeTensor(*m_KernelTensor, weightInfo, descriptor.m_DataLayout);
arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX,
m_Data.m_Parameters.m_StrideY,
m_Data.m_Parameters.m_PadLeft,
m_Data.m_Parameters.m_PadRight,
m_Data.m_Parameters.m_PadTop,
m_Data.m_Parameters.m_PadBottom,
arm_compute::DimensionRoundingType::FLOOR);
if (m_Data.m_Parameters.m_BiasEnabled)
{
m_BiasTensor = std::make_unique<arm_compute::CLTensor>();
BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), descriptor.m_DataLayout);
}
m_Data.ValidateInputsOutputs("ClConvolution2dUint8Workload", 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();
m_ConvolutionLayer.configure(&input,
m_KernelTensor.get(),
m_BiasTensor.get(),
&output,
padStrideInfo);
InitializeArmComputeClTensorData(*m_KernelTensor, m_Data.m_Weight);
if (m_BiasTensor)
{
InitializeArmComputeClTensorData(*m_BiasTensor, m_Data.m_Bias);
}
// Force Compute Library to perform the necessary copying and reshaping, after which
// delete all the input tensors that will no longer be needed
m_ConvolutionLayer.prepare();
FreeUnusedTensors();
}
void ClConvolution2dUint8Workload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_CL("ClConvolution2dUint8Workload_Execute");
m_ConvolutionLayer.run();
}
void ClConvolution2dUint8Workload::FreeUnusedTensors()
{
FreeTensorIfUnused(m_KernelTensor);
FreeTensorIfUnused(m_BiasTensor);
}
} //namespace armnn
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