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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// See LICENSE file in the project root for full license information.
//
#pragma once
#include <armnn/TypesUtils.hpp>
#include "backends/ClLayerSupport.hpp"
#include "backends/ArmComputeTensorUtils.hpp"
#include "backends/ClTensorHandle.hpp"
namespace armnn
{
template <typename WorkloadType>
void InitClDepthwiseConvolutionWorkload(WorkloadType& workload)
{
using T = typename WorkloadType::KernelDataType;
using B = typename WorkloadType::BiasDataType;
auto& m_Data = workload.GetData();
auto& m_KernelTensor = workload.m_KernelTensor;
auto& m_BiasTensor = workload.m_BiasTensor;
auto& m_pDepthwiseConvolutionLayer = workload.m_pDepthwiseConvolutionLayer;
auto& weightInfo = m_Data.m_Weight->GetTensorInfo();
std::string reasonIfUnsupported;
if (!IsClDepthwiseConvolution2dDescParamsSupported(&reasonIfUnsupported, m_Data.m_Parameters, weightInfo))
{
throw UnimplementedException(reasonIfUnsupported);
}
armcomputetensorutils::BuildArmComputeTensor(m_KernelTensor, weightInfo);
arm_compute::CLTensor* optionalBias = nullptr;
if (m_Data.m_Parameters.m_BiasEnabled)
{
armcomputetensorutils::BuildArmComputeTensor(m_BiasTensor, m_Data.m_Bias->GetTensorInfo());
optionalBias = &m_BiasTensor;
}
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);
std::string name = std::string("ClDepthwiseConvolution") + GetDataTypeName(GetDataType<T>()) + "Workload";
m_Data.ValidateInputsOutputs(name, 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();
//Check for optimisation opportunities.
bool use3x3Optimisation = (weightInfo.GetShape()[3] == 3) && (weightInfo.GetShape()[2] == 3);
if (use3x3Optimisation)
{
m_pDepthwiseConvolutionLayer = std::make_unique<arm_compute::CLDepthwiseConvolutionLayer3x3>();
static_cast<arm_compute::CLDepthwiseConvolutionLayer3x3*>(m_pDepthwiseConvolutionLayer.get())->configure(
&input,
&m_KernelTensor,
optionalBias,
&output,
padStrideInfo);
}
else
{
m_pDepthwiseConvolutionLayer = std::make_unique<arm_compute::CLDepthwiseConvolutionLayer>();
static_cast<arm_compute::CLDepthwiseConvolutionLayer*>(m_pDepthwiseConvolutionLayer.get())->configure(
&input,
&m_KernelTensor,
optionalBias,
&output,
padStrideInfo);
}
BOOST_ASSERT(m_pDepthwiseConvolutionLayer);
InitialiseArmComputeClTensorData(m_KernelTensor, m_Data.m_Weight->template GetConstTensor<T>());
if (optionalBias)
{
InitialiseArmComputeClTensorData(*optionalBias, m_Data.m_Bias->template GetConstTensor<B>());
}
}
} //namespace armnn
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