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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// See LICENSE file in the project root for full license information.
//
#include <armnn/Tensor.hpp>
#include <functional>
namespace armnn
{
struct BroadcastLoop
{
BroadcastLoop(const TensorShape& inShape0, const TensorShape& inShape1, const TensorShape& outShape);
unsigned int GetNumDimensions()
{
return static_cast<unsigned int>(m_DimData.size());
}
template <typename T0, typename T1, typename U, typename Func>
void Unroll(Func operationFunc,
unsigned int dimension,
const T0* inData0,
const T1* inData1,
U* outData)
{
if (dimension >= GetNumDimensions())
{
*outData = operationFunc(*inData0, *inData1);
return;
}
for (unsigned int i = 0; i < m_DimData[dimension].m_DimSize; i++)
{
Unroll(operationFunc, dimension + 1, inData0, inData1, outData);
inData0 += m_DimData[dimension].m_Stride1;
inData1 += m_DimData[dimension].m_Stride2;
outData += m_DimData[dimension].m_StrideOut;
}
}
private:
// Struct to hold the dimension data
struct BroadcastDimensionData
{
unsigned int m_DimSize;
unsigned int m_StrideOut;
unsigned int m_Stride1;
unsigned int m_Stride2;
};
std::vector<BroadcastDimensionData> m_DimData;
};
} //namespace armnn
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