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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ParserHelper.hpp"
#include <armnn/Descriptors.hpp>
#include <armnnUtils/Permute.hpp>
#include <boost/format.hpp>
namespace armnnUtils
{
const armnn::PermutationVector NHWCToArmNN = { 0, 2, 3, 1 };
const armnn::PermutationVector ArmNNToNHWC = { 0, 3, 1, 2 };
void ProcessConcatInputTensorInfo(armnn::TensorInfo& inputTensorInfo,
armnn::OriginsDescriptor& concatDescriptor,
const unsigned int& concatAxis,
unsigned int inputIndex,
unsigned int& mergeDimOrigin)
{
const uint32_t inputRank = concatDescriptor.GetNumDimensions();
// double check dimensions of the tensors
if (inputTensorInfo.GetNumDimensions() != inputRank)
{
throw armnn::ParseException(
boost::str(
boost::format(
"The number of dimensions: %1% for input tensors of the "
"concatenation op should be %2% %3%")
% inputTensorInfo.GetNumDimensions()
% inputRank
% CHECK_LOCATION().AsString()));
}
for (unsigned int j = 0; j < concatAxis; ++j)
{
concatDescriptor.SetViewOriginCoord(inputIndex, j, 0);
}
concatDescriptor.SetViewOriginCoord(inputIndex, concatAxis, mergeDimOrigin);
mergeDimOrigin += inputTensorInfo.GetShape()[concatAxis];
for (unsigned int j = concatAxis + 1; j < inputRank; ++j)
{
concatDescriptor.SetViewOriginCoord(inputIndex, j, 0);
}
}
void CalculateReducedOutputTensoInfo(const armnn::TensorInfo& inputTensorInfo,
const std::set<unsigned int>& axisSet,
bool keepDims,
armnn::TensorInfo& outputTensorInfo)
{
std::vector<unsigned int> outputShapeVector;
bool dimensionFound = false;
unsigned int size = 1;
for (unsigned int i = 0; i < inputTensorInfo.GetNumDimensions(); ++i)
{
dimensionFound = false;
for (unsigned int axis: axisSet)
{
if (axis == i)
{
dimensionFound = true;
break;
}
}
if (!dimensionFound)
{
size *= inputTensorInfo.GetShape()[i];
if (keepDims)
{
outputShapeVector.push_back(inputTensorInfo.GetShape()[i]);
}
}
else
{
if (keepDims)
{
outputShapeVector.push_back(1);
}
}
}
if (keepDims)
{
armnn::TensorShape outputTensorShape(inputTensorInfo.GetNumDimensions(), &outputShapeVector[0]);
outputTensorInfo = armnn::TensorInfo(outputTensorShape, inputTensorInfo.GetDataType());
}
else
{
outputTensorInfo = armnn::TensorInfo({size}, inputTensorInfo.GetDataType());
}
}
void CalculateStridedSliceOutputTensorInfo(const armnn::TensorInfo& inputTensorInfo,
const armnn::StridedSliceDescriptor& desc,
armnn::TensorInfo& outputTensorInfo)
{
const armnn::TensorShape& inputShape = inputTensorInfo.GetShape();
std::vector<unsigned int> outputShapeVector;
for (unsigned int i = 0; i < inputTensorInfo.GetNumDimensions(); i++)
{
if (desc.m_ShrinkAxisMask & (1 << i))
{
continue;
}
int stride = desc.m_Stride[i];
int start = desc.GetStartForAxis(inputShape, i);
int stop = desc.GetStopForAxis(inputShape, i, start);
int newSize = stride > 0 ? ((stop - start) + stride - 1) / stride :
((start - stop) - stride - 1) / -stride;
newSize = std::max(0, newSize);
outputShapeVector.push_back(static_cast<unsigned int>(newSize));
}
armnn::TensorShape outputTensorShape(inputTensorInfo.GetNumDimensions(), &outputShapeVector[0]);
outputTensorInfo = armnn::TensorInfo(armnn::TensorShape(outputTensorShape), inputTensorInfo.GetDataType());
}
} // namespace armnnUtils
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