StridedSlice.cpp

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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
 
#include "StridedSlice.hpp"
 
#include <ResolveType.hpp>
 
#include <armnn/utility/Assert.hpp>
#include <armnn/utility/NumericCast.hpp>
 
#include <cstring>
 
namespace armnn
{
 
namespace
{
 
void PadParams(StridedSliceDescriptor& p, unsigned int dimCount)
{
    ARMNN_ASSERT_MSG(dimCount <= 4, "Expected input with at most 4 dimensions");
 
    const unsigned int beginIndicesCount =
        armnn::numeric_cast<unsigned int>(p.m_Begin.size());
 
    ARMNN_ASSERT(dimCount >= beginIndicesCount);
    const unsigned int padCount = dimCount - beginIndicesCount;
 
    p.m_Begin.resize(dimCount);
    p.m_End.resize(dimCount);
    p.m_Stride.resize(dimCount);
 
    for (unsigned int i = beginIndicesCount; i > 0; --i)
    {
        p.m_Stride[i + padCount - 1] = p.m_Stride[i - 1];
        p.m_Begin[i + padCount - 1] = p.m_Begin[i - 1];
        p.m_End[i + padCount - 1] = p.m_End[i - 1];
    }
 
    for (unsigned int i = 0; i < padCount; ++i)
    {
        p.m_Stride[i] = 1;
        p.m_Begin[i] = 0;
        p.m_End[i] = 0;
    }
 
    p.m_ShrinkAxisMask <<= padCount;
    p.m_EllipsisMask <<= padCount;
    p.m_NewAxisMask <<= padCount;
    p.m_BeginMask <<= padCount;
    p.m_EndMask <<= padCount;
    p.m_BeginMask |= (1 << padCount) - 1;
    p.m_EndMask |= (1 << padCount) - 1;
}
 
bool LoopCondition(int index, int stop, int stride)
{
    return stride > 0 ? index >= stop : index <= stop;
}
 
TensorShape ExtendShape(const TensorShape& inputShape,
                        unsigned int newNumDimensions)
{
    if (inputShape.GetNumDimensions() >= newNumDimensions)
    {
        return inputShape;
    }
 
    std::vector<unsigned int> newSizes(newNumDimensions, 0);
 
    unsigned int diff = newNumDimensions - inputShape.GetNumDimensions();
 
    for (unsigned int i = 0; i < diff; i++)
    {
        newSizes[i] = 1;
    }
 
    for (unsigned int i = diff; i < newNumDimensions; i++)
    {
        newSizes[i] = inputShape[i - diff];
    }
 
    return TensorShape(newNumDimensions, newSizes.data());
}
 
} // Anonymous namespace
 
void StridedSlice(const TensorInfo& inputInfo,
                  const StridedSliceDescriptor& params,
                  const void* inputData,
                  void* outputData,
                  unsigned int dataTypeSize)
{
    if (inputData == nullptr)
    {
        throw armnn::InvalidArgumentException("Slice: Null inputData pointer");
    }
    if (outputData == nullptr)
    {
        throw armnn::InvalidArgumentException("Slice: Null outputData pointer");
    }
 
    const unsigned char* input = reinterpret_cast<const unsigned char*>(inputData);
    unsigned char* output = reinterpret_cast<unsigned char*>(outputData);
 
    const TensorShape inputShape = ExtendShape(inputInfo.GetShape(), 4);
 
    StridedSliceDescriptor paddedParams = params;
 
    // Pad parameters to 4 dimensions
    PadParams(paddedParams, 4);
 
    const int start0 = paddedParams.GetStartForAxis(inputShape, 0);
    const int stop0  = paddedParams.GetStopForAxis (inputShape, 0, start0);
 
    const int start1 = paddedParams.GetStartForAxis(inputShape, 1);
    const int stop1  = paddedParams.GetStopForAxis (inputShape, 1, start1);
 
    const int start2 = paddedParams.GetStartForAxis(inputShape, 2);
    const int stop2  = paddedParams.GetStopForAxis (inputShape, 2, start2);
 
    const int start3 = paddedParams.GetStartForAxis(inputShape, 3);
    const int stop3  = paddedParams.GetStopForAxis (inputShape, 3, start3);
 
    const int step = armnn::numeric_cast<int>(dataTypeSize);
 
    for (int in0 = start0;
         !LoopCondition(in0, stop0, paddedParams.m_Stride[0]);
         in0 += paddedParams.m_Stride[0])
    {
        for (int in1 = start1;
             !LoopCondition(in1, stop1, paddedParams.m_Stride[1]);
             in1 += paddedParams.m_Stride[1])
        {
            for (int in2 = start2;
                 !LoopCondition(in2, stop2, paddedParams.m_Stride[2]);
                 in2 += paddedParams.m_Stride[2])
            {
                for (int in3 = start3;
                     !LoopCondition(in3, stop3, paddedParams.m_Stride[3]);
                     in3 += paddedParams.m_Stride[3])
                {
                    int dim1 = armnn::numeric_cast<int>(inputShape[1]);
                    int dim2 = armnn::numeric_cast<int>(inputShape[2]);
                    int dim3 = armnn::numeric_cast<int>(inputShape[3]);
 
                    int inputOffset = (((in0 * dim1 + in1) * dim2 + in2) * dim3 + in3) * step;
                    ::memcpy(output, input + inputOffset, dataTypeSize);
                    output += step;
                }
            }
        }
    }
}
 
} // namespace armnn