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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "Stack.hpp"
#include "RefWorkloadUtils.hpp"
namespace armnn
{
void Stack(const StackQueueDescriptor& data,
std::vector<std::unique_ptr<Decoder<float>>>& inputs,
Encoder<float>& output)
{
const TensorInfo& outputInfo = GetTensorInfo(data.m_Outputs[0]);
const TensorInfo& inputInfo = GetTensorInfo(data.m_Inputs[0]);
unsigned int outputNumDims = outputInfo.GetNumDimensions();
unsigned int inputNumDims = inputInfo.GetNumDimensions();
const armnn::TensorShape& outputDims = outputInfo.GetShape();
const armnn::TensorShape& inputDims = inputInfo.GetShape();
unsigned int axis = data.m_Parameters.m_Axis;
// Can perform a simple concatenation when axis == 0
if (!axis)
{
unsigned int numInputs = data.m_Parameters.m_NumInputs;
unsigned int inputLength = inputInfo.GetNumElements();
for (unsigned int inputIdx=0; inputIdx<numInputs; ++inputIdx)
{
for (unsigned int elmt=0; elmt<inputLength; ++elmt)
{
(*inputs[inputIdx])[elmt];
output[(inputIdx * inputLength) + elmt];
output.Set(inputs[inputIdx]->Get());
}
}
return;
}
// Initialise output data
unsigned int numOutputElements = 1;
for (unsigned int i=0; i<outputNumDims; ++i)
{
numOutputElements *= outputDims[i];
}
const unsigned int iNumTensors = static_cast<unsigned int>(data.m_Inputs.size());
const unsigned int iBatchSize = inputDims[0];
const unsigned int iChannels = (inputNumDims > 1) ? inputDims[1] : 1;
const unsigned int iHeight = (inputNumDims > 2) ? inputDims[2] : 1;
const unsigned int iWidth = (inputNumDims > 3) ? inputDims[3] : 1;
const unsigned int oBatchSize = outputDims[1];
const unsigned int oChannels = (outputNumDims > 2) ? outputDims[2] : 1;
const unsigned int oHeight = (outputNumDims > 3) ? outputDims[3] : 1;
const unsigned int oWidth = (outputNumDims > 4) ? outputDims[4] : 1;
// Array to store the input coordinates
// iCoordinates[0] = i, iCoordinates[1] = bi, iCoordinates[2] = ci
// iCoordinates[3] = hi, iCoordinates[4] = wi, iCoordinates[5] = 0
// iCoordinates[5] will be always zero and used for not incrementing
// the output when the input has less than 4 dimensions
std::array<unsigned int, 6> iCoordinates{ 0 };
// Array of pointers used to map the output coordinates to the input ones, in accordance with the axis
// This array is initialized with &iCoordinates[5] since this will be always zero
std::array<unsigned int *, 5> oCoordinates = { &iCoordinates[5],
&iCoordinates[5],
&iCoordinates[5],
&iCoordinates[5],
&iCoordinates[5] };
// Set the axis coordinate
oCoordinates[axis] = &iCoordinates[0];
// Map the output coordinates, accounting for the axis
unsigned int dim_shift = 0;
for(unsigned int dim = 0; dim < inputNumDims; ++dim)
{
if(dim == axis)
{
dim_shift++;
}
oCoordinates[dim + dim_shift] = &iCoordinates[dim + 1];
}
// Alias for the input coordinates
unsigned int &i = iCoordinates[0];
unsigned int &bi = iCoordinates[1];
unsigned int &ci = iCoordinates[2];
unsigned int &hi = iCoordinates[3];
unsigned int &wi = iCoordinates[4];
// Alias for the output coordinates
unsigned int &o = *(oCoordinates[0]);
unsigned int &bo = *(oCoordinates[1]);
unsigned int &co = *(oCoordinates[2]);
unsigned int &ho = *(oCoordinates[3]);
unsigned int &wo = *(oCoordinates[4]);
// Stack tensors
for(; i < iNumTensors; ++(i))
{
for(bi = 0; bi < iBatchSize; ++(bi))
{
for(ci = 0; ci < iChannels; ++(ci))
{
for(hi = 0; hi < iHeight; ++(hi))
{
for(wi = 0; wi < iWidth; ++(wi))
{
output[o * oWidth * oHeight * oChannels * oBatchSize +
bo * oWidth * oHeight * oChannels +
co * oWidth * oHeight +
ho * oWidth +
wo];
output.Set(inputs[i]->Get());
++(*(inputs[i]));
}
}
}
}
}
}
} // namespace armnn
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