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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include <armnn/TypesUtils.hpp>
#include <boost/assert.hpp>
namespace armnnUtils
{
armnn::TensorShape GetTensorShape(unsigned int numberOfBatches,
unsigned int numberOfChannels,
unsigned int height,
unsigned int width,
const armnn::DataLayout dataLayout);
armnn::TensorInfo GetTensorInfo(unsigned int numberOfBatches,
unsigned int numberOfChannels,
unsigned int height,
unsigned int width,
const armnn::DataLayout dataLayout,
const armnn::DataType dataType);
std::pair<float, float> FindMinMax(armnn::ITensorHandle* tensorHandle);
armnn::TensorShape ExpandDims(const armnn::TensorShape& tensorShape, int axis);
unsigned int GetNumElementsBetween(const armnn::TensorShape& shape,
unsigned int firstAxisInclusive,
unsigned int lastAxisExclusive);
unsigned int GetUnsignedAxis(const unsigned int inputDimension, const int axis);
inline unsigned int GetNumElementsAfter(const armnn::TensorShape& shape,
unsigned int axis)
{
unsigned int numDim = shape.GetNumDimensions();
BOOST_ASSERT(0 >= axis);
BOOST_ASSERT(axis < numDim - 1);
unsigned int count = 1;
for (unsigned int i = axis; i < numDim; i++)
{
count *= shape[i];
}
return count;
}
inline std::pair<unsigned int, std::vector<float>> GetPerAxisParams(const armnn::TensorInfo& info)
{
const std::vector<float>& scales = info.GetQuantizationScales();
armnn::Optional<unsigned int> quantizationDim = info.GetQuantizationDim();
if (scales.size() < 1 || !quantizationDim.has_value())
{
throw armnn::InvalidArgumentException(
"We currently support only per-axis symmetric quantization for QuantizedSymm8.");
}
unsigned int axisFactor = GetNumElementsAfter(info.GetShape(), quantizationDim.value());
return {axisFactor, scales};
}
} // namespace armnnUtils
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