blob: 5f613f455411026af7f79c9c97f0ebc1fce139f8 [file] [log] [blame]
//
// Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "NeonConcatWorkload.hpp"
#include "NeonWorkloadUtils.hpp"
#include <aclCommon/ArmComputeTensorUtils.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
#include <armnn/backends/TensorHandle.hpp>
#include <neon/NeonTensorHandle.hpp>
namespace armnn
{
using namespace armcomputetensorutils;
namespace
{
size_t CalcAxis(const armnn::OriginsDescriptor& descriptor)
{
return (descriptor.GetNumDimensions() - descriptor.GetConcatAxis()) - 1;
}
} //namespace
arm_compute::Status NeonConcatWorkloadValidate(const std::vector<const TensorInfo*>& inputs,
const TensorInfo& output,
const OriginsDescriptor& descriptor)
{
std::vector<arm_compute::TensorInfo> aclInputs;
for (const TensorInfo* input : inputs)
{
arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(*input, armnn::DataLayout::NCHW);
aclInputs.emplace_back(aclInputInfo);
}
const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output);
std::vector<const arm_compute::ITensorInfo*> aclInputPtrs;
for (arm_compute::ITensorInfo& input : aclInputs)
{
aclInputPtrs.emplace_back(&input);
}
size_t aclAxis = CalcAxis(descriptor);
return arm_compute::NEConcatenateLayer::validate(aclInputPtrs, &aclOutputInfo, aclAxis);
}
NeonConcatWorkload::NeonConcatWorkload(
const ConcatQueueDescriptor& descriptor, const WorkloadInfo& info)
: NeonBaseWorkload<ConcatQueueDescriptor>(descriptor, info)
{
// Report Profiling Details
ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonConcatWorkload_Construct",
descriptor.m_Parameters,
info,
this->GetGuid());
bool allInputsAreSubtensors = true;
// Check that all inputs are sub-tensors
for (auto input : descriptor.m_Inputs)
{
if (!input->GetParent())
{
// Non sub-tensor input found so we need to execute the concat function
allInputsAreSubtensors = false;
break;
}
}
if (allInputsAreSubtensors)
{
// Can skip configuring the concat function since it's not executed
return;
}
std::vector<const arm_compute::ITensor *> aclInputs;
for (auto input : m_Data.m_Inputs)
{
arm_compute::ITensor& aclInput = armnn::PolymorphicPointerDowncast<IAclTensorHandle>(input)->GetTensor();
aclInputs.emplace_back(&aclInput);
}
arm_compute::ITensor& output = armnn::PolymorphicPointerDowncast<IAclTensorHandle>(
m_Data.m_Outputs[0])->GetTensor();
// Create the layer function
m_Layer.reset(new arm_compute::NEConcatenateLayer());
// Configure input and output tensors
size_t aclAxis = CalcAxis(descriptor.m_Parameters);
m_Layer->configure(aclInputs, &output, aclAxis);
// Prepare
m_Layer->prepare();
}
void NeonConcatWorkload::Execute() const
{
if (m_Layer)
{
ARMNN_SCOPED_PROFILING_EVENT_NEON_NAME_GUID("NeonConcatWorkload_Execute");
m_Layer->run();
}
}
} //namespace armnn