blob: 867925faa25a85ac4efc6d845e4f5a8dc91b0844 [file] [log] [blame]
//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "RefWorkloadUtils.hpp"
#include "backends/WorkloadData.hpp"
#include <armnn/Tensor.hpp>
namespace armnn
{
template <typename DataType>
void Merger(const MergerQueueDescriptor& data)
{
const TensorInfo& outputInfo0 = GetTensorInfo(data.m_Outputs[0]);
for (unsigned int index = 0 ; index < outputInfo0.GetNumElements(); ++index)
{
unsigned int indices[MaxNumOfTensorDimensions] = { 0 };
unsigned int indexRemainder = index;
unsigned int dimensionStride = outputInfo0.GetNumElements();
for (unsigned int i=0; i<outputInfo0.GetNumDimensions(); i++)
{
dimensionStride /= outputInfo0.GetShape()[i];
indices[i] = indexRemainder / dimensionStride; // Use integer division to round down.
indexRemainder -= indices[i] * dimensionStride;
}
for (unsigned int viewIdx = 0; viewIdx < data.m_ViewOrigins.size(); ++viewIdx)
{
MergerQueueDescriptor::ViewOrigin const& view = data.m_ViewOrigins[viewIdx];
//Split view extents are defined by the size of (the corresponding) input tensor.
const TensorInfo& inputInfo = GetTensorInfo(data.m_Inputs[viewIdx]);
BOOST_ASSERT(inputInfo.GetNumDimensions() == outputInfo0.GetNumDimensions());
// Check all dimensions to see if this element is inside the given input view.
bool insideView = true;
for (unsigned int i=0; i<inputInfo.GetNumDimensions(); i++)
{
if (indices[i] < view.m_Origin[i])
{
insideView = false;
}
if (indices[i] >= view.m_Origin[i] + inputInfo.GetShape()[i])
{
insideView = false;
}
}
if (insideView)
{
unsigned int inIndex = 0;
unsigned int dimensionStride = 1;
for (unsigned int i = inputInfo.GetNumDimensions(); i-- > 0;)
{
inIndex += dimensionStride * (indices[i] - view.m_Origin[i]);
dimensionStride *= inputInfo.GetShape()[i];
}
//We are within the view, copy input data to the output corresponding to this view.
(GetOutputTensorData<DataType>(0, data))[index] =
(GetInputTensorData<DataType>(viewIdx, data))[inIndex];
//What should we do if input views overlap on the output tensor?
//We could error, take the average, or shm else...
//For now just stop after finding first view (input) that matches.
break;
}
}
}
}
} //namespace armnn