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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ClSplitterWorkload.hpp"
#include "ClWorkloadUtils.hpp"
#include <aclCommon/ArmComputeTensorUtils.hpp>
#include <aclCommon/ArmComputeUtils.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
#include <armnn/backends/TensorHandle.hpp>
#include <cl/ClTensorHandle.hpp>
namespace armnn
{
using namespace armcomputetensorutils;
namespace
{
unsigned int CalcAclAxis(unsigned int numDimensions, unsigned int splitAxis)
{
return (numDimensions - splitAxis) - 1;
}
} //namespace
arm_compute::Status ClSplitterWorkloadValidate(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::CLSplit::validate(&aclInputInfo, aclOutputPtr, aclAxis);
}
ClSplitterWorkload::ClSplitterWorkload(const SplitterQueueDescriptor& descriptor,
const WorkloadInfo& info,
const arm_compute::CLCompileContext&)
: BaseWorkload<SplitterQueueDescriptor>(descriptor, info)
{
// Report Profiling Details
ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClSplitterWorkload_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::ICLTensor& input = armnn::PolymorphicPointerDowncast<IClTensorHandle>(
m_Data.m_Inputs[0])->GetTensor();
std::vector<arm_compute::ICLTensor *> aclOutputs;
for (auto output : m_Data.m_Outputs)
{
arm_compute::ICLTensor& aclOutput = armnn::PolymorphicPointerDowncast<IClTensorHandle>(output)->GetTensor();
aclOutputs.emplace_back(&aclOutput);
}
// Create the layer function
// 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());
auto layer = std::make_unique<arm_compute::CLSplit>();
{
ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "ClSplitterWorkload_configure");
layer->configure(&input, aclOutputs, aclAxis);
}
// Prepare
layer->prepare();
m_Layer = std::move(layer);
}
void ClSplitterWorkload::Execute() const
{
if (m_Layer)
{
ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClSplitterWorkload_Execute", this->GetGuid());
m_Layer->run();
}
}
} //namespace armnn
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