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#include "precomp.hpp"

using namespace cv;
using namespace cv::gpu;

namespace
{
    size_t alignUpStep(size_t what, size_t alignment)
    {
        size_t alignMask = alignment - 1;
        size_t inverseAlignMask = ~alignMask;
        size_t res = (what + alignMask) & inverseAlignMask;
        return res;
    }
}

void cv::gpu::CudaMem::create(int rows_, int cols_, int type_)
{
#ifndef HAVE_CUDA
    (void) rows_;
    (void) cols_;
    (void) type_;
    throw_no_cuda();
#else
    if (alloc_type == SHARED)
    {
        DeviceInfo devInfo;
        CV_Assert( devInfo.canMapHostMemory() );
    }

    type_ &= Mat::TYPE_MASK;

    if (rows == rows_ && cols == cols_ && type() == type_ && data)
        return;

    if (data)
        release();

    CV_DbgAssert( rows_ >= 0 && cols_ >= 0 );

    if (rows_ > 0 && cols_ > 0)
    {
        flags = Mat::MAGIC_VAL + Mat::CONTINUOUS_FLAG + type_;
        rows = rows_;
        cols = cols_;
        step = elemSize() * cols;

        if (alloc_type == SHARED)
        {
            DeviceInfo devInfo;
            step = alignUpStep(step, devInfo.textureAlignment());
        }

        int64 _nettosize = (int64)step*rows;
        size_t nettosize = (size_t)_nettosize;

        if (_nettosize != (int64)nettosize)
            CV_Error(cv::Error::StsNoMem, "Too big buffer is allocated");

        size_t datasize = alignSize(nettosize, (int)sizeof(*refcount));

        void* ptr = 0;

        switch (alloc_type)
        {
        case PAGE_LOCKED:    cudaSafeCall( cudaHostAlloc(&ptr, datasize, cudaHostAllocDefault) ); break;
        case SHARED:         cudaSafeCall( cudaHostAlloc(&ptr, datasize, cudaHostAllocMapped) );  break;
        case WRITE_COMBINED: cudaSafeCall( cudaHostAlloc(&ptr, datasize, cudaHostAllocWriteCombined) ); break;
        default:             CV_Error(cv::Error::StsBadFlag, "Invalid alloc type");
        }

        datastart = data =  (uchar*)ptr;
        dataend = data + nettosize;

        refcount = (int*)cv::fastMalloc(sizeof(*refcount));
        *refcount = 1;
    }
#endif
}

CudaMem cv::gpu::CudaMem::reshape(int new_cn, int new_rows) const
{
    CudaMem hdr = *this;

    int cn = channels();
    if (new_cn == 0)
        new_cn = cn;

    int total_width = cols * cn;

    if ((new_cn > total_width || total_width % new_cn != 0) && new_rows == 0)
        new_rows = rows * total_width / new_cn;

    if (new_rows != 0 && new_rows != rows)
    {
        int total_size = total_width * rows;

        if (!isContinuous())
            CV_Error(cv::Error::BadStep, "The matrix is not continuous, thus its number of rows can not be changed");

        if ((unsigned)new_rows > (unsigned)total_size)
            CV_Error(cv::Error::StsOutOfRange, "Bad new number of rows");

        total_width = total_size / new_rows;

        if (total_width * new_rows != total_size)
            CV_Error(cv::Error::StsBadArg, "The total number of matrix elements is not divisible by the new number of rows");

        hdr.rows = new_rows;
        hdr.step = total_width * elemSize1();
    }

    int new_width = total_width / new_cn;

    if (new_width * new_cn != total_width)
        CV_Error(cv::Error::BadNumChannels, "The total width is not divisible by the new number of channels");

    hdr.cols = new_width;
    hdr.flags = (hdr.flags & ~CV_MAT_CN_MASK) | ((new_cn - 1) << CV_CN_SHIFT);

    return hdr;
}

void cv::gpu::CudaMem::release()
{
#ifdef HAVE_CUDA
    if (refcount && CV_XADD(refcount, -1) == 1)
    {
        cudaFreeHost(datastart);
        fastFree(refcount);
    }

    data = datastart = dataend = 0;
    step = rows = cols = 0;
    refcount = 0;
#endif
}

GpuMat cv::gpu::CudaMem::createGpuMatHeader() const
{
#ifndef HAVE_CUDA
    throw_no_cuda();
    return GpuMat();
#else
    CV_Assert( alloc_type == SHARED );

    void *pdev;
    cudaSafeCall( cudaHostGetDevicePointer(&pdev, data, 0) );

    return GpuMat(rows, cols, type(), pdev, step);
#endif
}

void cv::gpu::registerPageLocked(Mat& m)
{
#ifndef HAVE_CUDA
    (void) m;
    throw_no_cuda();
#else
    CV_Assert( m.isContinuous() );
    cudaSafeCall( cudaHostRegister(m.data, m.step * m.rows, cudaHostRegisterPortable) );
#endif
}

void cv::gpu::unregisterPageLocked(Mat& m)
{
#ifndef HAVE_CUDA
    (void) m;
#else
    cudaSafeCall( cudaHostUnregister(m.data) );
#endif
}