Function col2im

tests/validation/reference/Col2Im.cpp:38–87

{
template <typename T>
SimpleTensor<T> col2im(const SimpleTensor<T> &src, const TensorShape &dst_shape, unsigned int num_groups)
{
    SimpleTensor<T> dst{dst_shape, src.data_type(), 1};

    // Compute reference
    const size_t batches    = dst_shape.total_size() / (dst_shape.x() * dst_shape.y() * dst_shape.z());
    const size_t src_width  = src.shape().x();
    const size_t src_height = src.shape().y();

    if (num_groups == 1)
    {
        // Batches are on the 3rd dimension of the input tensor
#if defined(_OPENMP)
#pragma omp parallel for collapse(3)
#endif /* _OPENMP */
        for (size_t b = 0; b < batches; ++b)
        {
            for (size_t x = 0; x < src_width; ++x)
            {
                for (size_t y = 0; y < src_height; ++y)
                {
                    const int dst_idx = y + x * src_height + b * src_height * src_width;
                    dst[dst_idx]      = src[coord2index(src.shape(), Coordinates(x, y, b))];
                }
            }
        }
    }
    else
    {
#if defined(_OPENMP)
#pragma omp parallel for collapse(4)
#endif /* _OPENMP */
        for (size_t b = 0; b < batches; ++b)
        {
            for (size_t g = 0; g < num_groups; ++g)
            {
                for (size_t x = 0; x < src_width; ++x)
                {
                    for (size_t y = 0; y < src_height; ++y)
                    {
                        const int dst_idx =
                            y + x * src_height + g * src_height * src_width + b * src_height * src_width * num_groups;
                        dst[dst_idx] = src[coord2index(src.shape(), Coordinates(x, y, g, b))];
                    }
                }
            }
        }
    }
    return dst;
}

template SimpleTensor<float>
col2im(const SimpleTensor<float> &src, const TensorShape &dst_shape, unsigned int num_groups);