NeonSplitterWorkload.cpp

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//
// Copyright © 2019-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
 
#include "NeonSplitterWorkload.hpp"
 
#include <arm_compute/runtime/NEON/functions/NESplit.h>
 
#include <aclCommon/ArmComputeTensorUtils.hpp>
#include <aclCommon/ArmComputeUtils.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
#include <armnn/backends/TensorHandle.hpp>
#include <neon/NeonTensorHandle.hpp>
#include <backendsCommon/WorkloadUtils.hpp>
 
#include "NeonWorkloadUtils.hpp"
 
namespace armnn
{
 
using namespace armcomputetensorutils;
 
namespace
{
unsigned int CalcAclAxis(unsigned int numDimensions, unsigned int splitAxis)
{
    return (numDimensions - splitAxis) - 1;
}
 
} //namespace
 
arm_compute::Status NeonSplitterWorkloadValidate(const TensorInfo& input,
                                                 const std::vector<std::reference_wrapper<TensorInfo>>& outputs,
                                                 unsigned int splitAxis)
{
    const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input);
 
    size_t numOutputs = outputs.size();
 
    std::vector<arm_compute::TensorInfo> aclOutputs;
    aclOutputs.reserve(numOutputs);
 
    std::vector<arm_compute::ITensorInfo*> aclOutputPtr;
    aclOutputPtr.reserve(numOutputs);
 
    for (size_t i = 0u; i < outputs.size(); ++i)
    {
        aclOutputs.emplace_back(BuildArmComputeTensorInfo(outputs[i]));
        aclOutputPtr.emplace_back(&aclOutputs.back());
    }
 
    unsigned int aclAxis = CalcAclAxis(input.GetNumDimensions(), splitAxis);
    return arm_compute::NESplit::validate(&aclInputInfo, aclOutputPtr, aclAxis);
}
 
NeonSplitterWorkload::NeonSplitterWorkload(const SplitterQueueDescriptor& descriptor, const WorkloadInfo& info)
    : NeonBaseWorkload<SplitterQueueDescriptor>(descriptor, info)
{
    // Report Profiling Details
    ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonSplitterWorkload_Construct",
                                         descriptor.m_Parameters,
                                         info,
                                         this->GetGuid());
 
    bool allOutputsAreSubtensors = true;
 
    // Check that all outputs are sub-tensors
    for (auto output : m_Data.m_Outputs)
    {
        if (output && !output->GetParent())
        {
            // Non sub-tensor input found so we need to execute the split function
            allOutputsAreSubtensors = false;
            break;
        }
    }
 
    if (allOutputsAreSubtensors)
    {
        // Can skip configuring the split function since it's not executed
        return;
    }
 
    arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
 
    std::vector<arm_compute::ITensor *> aclOutputs;
    for (auto output : m_Data.m_Outputs)
    {
        arm_compute::ITensor& aclOutput  = PolymorphicPointerDowncast<IAclTensorHandle>(output)->GetTensor();
        aclOutputs.emplace_back(&aclOutput);
    }
 
    // Create the layer function
    std::unique_ptr<arm_compute::NESplit> layer(new arm_compute::NESplit());
 
    // Configure input and output tensors
    std::set<unsigned int> splitAxis = ComputeSplitAxis(descriptor.m_Parameters, m_Data.m_Inputs[0]->GetShape());
    if (splitAxis.size() != 1)
    {
        throw InvalidArgumentException("Cannot derive split axis from SplitterDescriptor");
    }
 
    unsigned int aclAxis = CalcAclAxis(descriptor.m_Parameters.GetNumDimensions(), *splitAxis.begin());
    layer->configure(&input, aclOutputs, aclAxis);
 
    // Prepare
    layer->prepare();
    m_Layer.reset(layer.release());
}
 
void NeonSplitterWorkload::Execute() const
{
    if (m_Layer)
    {
        ARMNN_SCOPED_PROFILING_EVENT_NEON_NAME_GUID("NeonSplitterWorkload_Execute");
        m_Layer->run();
    }
}
 
} //namespace armnn