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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "RefWorkloadUtils.hpp"
#include "TensorBufferArrayView.hpp"
#include "BaseIterator.hpp"
#include "Decoders.hpp"
#include "Encoders.hpp"
#include <armnn/Tensor.hpp>
#include <armnnUtils/DataLayoutIndexed.hpp>
#include <boost/assert.hpp>
#include <boost/numeric/conversion/cast.hpp>
#include <cmath>
#include <limits>
namespace armnn
{
/// Performs multiplication of an integer with a multiplier which is less than one,
/// using quantized integer arithmetic which is consistent with AndroidNN's CPU executor.
struct QuantizedMultiplierSmallerThanOne
{
public:
/// Constructs a QuantizedMultiplierSmallerThanOne which will multiply by the given multiplier.
/// This stores the appropriate integer quantities (derived from the given multiplier) for later use.
/// The implementation of this function is adapted from Android NN's QuantizeMultiplierSmallerThanOne().
QuantizedMultiplierSmallerThanOne(float multiplier);
/// The implementation of this function is adapted from Android NN's MultiplyByQuantizedMultiplierSmallerThanOne().
int32_t operator*(int32_t rhs) const;
private:
/// The implementation of this function is adapted from gemmlowp's SaturatingRoundingDoublingHighMul().
static int32_t SaturatingRoundingDoublingHighMul(int32_t a, int32_t b);
/// The implementation of this function is adapted from gemmlowp's RoundingDivideByPOT().
static int32_t RoundingDivideByPOT(int32_t x, int exponent);
int32_t m_Multiplier;
int32_t m_RightShift;
};
void Convolve(const TensorShape& rInputShape,
Decoder<float>& rInputDecoder,
const TensorShape& rOutputShape,
Encoder<float>& rOutputEncoder,
const TensorShape& rFilterShape,
Decoder<float>& rFilterDecoder,
bool biasEnabled,
Decoder<float>* pBiasDecoder,
DataLayout dataLayout,
unsigned int paddingTop,
unsigned int paddingLeft,
unsigned int xStride,
unsigned int yStride,
unsigned int xDilation,
unsigned int yDilation,
bool depthwise = false);
} //namespace armnn
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