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//
// Copyright © 2017 Arm Ltd. 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 <backendsCommon/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)
{
ARMNN_ASSERT(biases.has_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) :
BaseWorkload<TransposeConvolution2dQueueDescriptor>(descriptor, info),
m_Layer(memoryManager)
{
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);
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("ClTransposeConvolution2dWorkload_Execute");
RunClFunction(m_Layer, CHECK_LOCATION());
}
void ClTransposeConvolution2dWorkload::FreeUnusedTensors()
{
FreeTensorIfUnused(m_WeightsTensor);
FreeTensorIfUnused(m_BiasesTensor);
}
} // namespace armnn
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