blob: be36f40633f7b067b4d3a0d6b0e1579b65cbda9b [file] [log] [blame]
//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "RefStackWorkload.hpp"
#include "RefWorkloadUtils.hpp"
#include "Stack.hpp"
#include <Profiling.hpp>
namespace armnn
{
RefStackWorkload::RefStackWorkload(const StackQueueDescriptor& descriptor,
const WorkloadInfo& info)
: BaseWorkload(descriptor, info)
{}
void RefStackWorkload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefStackWorkload_Execute");
// Can perform a simple concatenation when axis == 0
if (!m_Data.m_Parameters.m_Axis)
{
float* output = GetOutputTensorData<float>(0, m_Data);
BOOST_ASSERT(output != nullptr);
unsigned int numInputs = m_Data.m_Parameters.m_NumInputs;
unsigned int inputLength = GetTensorInfo(m_Data.m_Inputs[0]).GetNumElements();
for (unsigned int inputIdx=0; inputIdx<numInputs; ++inputIdx)
{
const float* input = GetInputTensorData<float>(inputIdx, m_Data);
for (unsigned int elmt=0; elmt<inputLength; ++elmt)
{
output[(inputIdx * inputLength) + elmt] = input[elmt];
}
}
return;
}
std::vector<std::unique_ptr<Decoder<float>>> inputDecoders;
for (unsigned int i=0; i<m_Data.m_Inputs.size(); ++i)
{
inputDecoders.push_back(MakeDecoder<float>(GetTensorInfo(m_Data.m_Inputs[i]),
m_Data.m_Inputs[i]->Map()));
}
std::unique_ptr<Encoder<float>> outputEncoder = MakeEncoder<float>(GetTensorInfo(m_Data.m_Outputs[0]),
m_Data.m_Outputs[0]->Map());
Stack(m_Data, inputDecoders, *outputEncoder);
}
} // namespace armnn