/*
 * Copyright (c) 2016-2019 ARM Limited.
 *
 * SPDX-License-Identifier: MIT
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to
 * deal in the Software without restriction, including without limitation the
 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
 * sell copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all
 * copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 */
#include "arm_compute/runtime/NEON/functions/NEGaussianPyramid.h"

#include "arm_compute/core/Error.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/NEON/kernels/NEGaussianPyramidKernel.h"
#include "arm_compute/core/NEON/kernels/NEScaleKernel.h"
#include "arm_compute/core/PixelValue.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/runtime/NEON/NEScheduler.h"
#include "arm_compute/runtime/NEON/functions/NEGaussian5x5.h"
#include "arm_compute/runtime/Pyramid.h"
#include "arm_compute/runtime/Tensor.h"
#include "arm_compute/runtime/TensorAllocator.h"
#include "support/ToolchainSupport.h"

#include <cstddef>

using namespace arm_compute;

NEGaussianPyramid::NEGaussianPyramid()
    : _input(nullptr), _pyramid(nullptr), _tmp()
{
}

NEGaussianPyramidHalf::NEGaussianPyramidHalf() // NOLINT
    : _horizontal_border_handler(),
      _vertical_border_handler(),
      _horizontal_reduction(),
      _vertical_reduction()
{
}

void NEGaussianPyramidHalf::configure(const ITensor *input, IPyramid *pyramid, BorderMode border_mode, uint8_t constant_border_value)
{
    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
    ARM_COMPUTE_ERROR_ON(nullptr == pyramid);
    ARM_COMPUTE_ERROR_ON(input->info()->num_dimensions() != pyramid->get_pyramid_level(0)->info()->num_dimensions());
    ARM_COMPUTE_ERROR_ON(input->info()->dimension(0) != pyramid->info()->width());
    ARM_COMPUTE_ERROR_ON(input->info()->dimension(1) != pyramid->info()->height());
    ARM_COMPUTE_ERROR_ON(SCALE_PYRAMID_HALF != pyramid->info()->scale());

    // Constant value to use for vertical fill border when the border mode is CONSTANT
    const uint16_t pixel_value_u16 = static_cast<uint16_t>(constant_border_value) * 2 + static_cast<uint16_t>(constant_border_value) * 8 + static_cast<uint16_t>(constant_border_value) * 6;

    /* Get number of pyramid levels */
    const size_t num_levels = pyramid->info()->num_levels();

    _input   = input;
    _pyramid = pyramid;

    if(num_levels > 1)
    {
        // Apply half scale to the X dimension of the tensor shape
        TensorShape tensor_shape = pyramid->info()->tensor_shape();
        tensor_shape.set(0, (pyramid->info()->width() + 1) * SCALE_PYRAMID_HALF);

        PyramidInfo pyramid_info(num_levels - 1, SCALE_PYRAMID_HALF, tensor_shape, Format::S16);
        _tmp.init(pyramid_info);

        _horizontal_reduction.reserve(num_levels);
        _vertical_reduction.reserve(num_levels);
        _horizontal_border_handler.reserve(num_levels);
        _vertical_border_handler.reserve(num_levels);

        for(unsigned int i = 0; i < num_levels - 1; ++i)
        {
            /* Configure horizontal kernel */
            auto horizontal_kernel = support::cpp14::make_unique<NEGaussianPyramidHorKernel>();
            horizontal_kernel->configure(_pyramid->get_pyramid_level(i), _tmp.get_pyramid_level(i));

            /* Configure vertical kernel */
            auto vertical_kernel = support::cpp14::make_unique<NEGaussianPyramidVertKernel>();
            vertical_kernel->configure(_tmp.get_pyramid_level(i), _pyramid->get_pyramid_level(i + 1));

            /* Configure border */
            auto horizontal_border_kernel = support::cpp14::make_unique<NEFillBorderKernel>();
            horizontal_border_kernel->configure(_pyramid->get_pyramid_level(i), horizontal_kernel->border_size(), border_mode, PixelValue(constant_border_value));

            /* Configure border */
            auto vertical_border_kernel = support::cpp14::make_unique<NEFillBorderKernel>();
            vertical_border_kernel->configure(_tmp.get_pyramid_level(i), vertical_kernel->border_size(), border_mode, PixelValue(pixel_value_u16));

            _vertical_border_handler.emplace_back(std::move(vertical_border_kernel));
            _horizontal_border_handler.emplace_back(std::move(horizontal_border_kernel));
            _vertical_reduction.emplace_back(std::move(vertical_kernel));
            _horizontal_reduction.emplace_back(std::move(horizontal_kernel));
        }

        _tmp.allocate();
    }
}

void NEGaussianPyramidHalf::run()
{
    ARM_COMPUTE_ERROR_ON_MSG(_pyramid == nullptr, "Unconfigured function");

    /* Get number of pyramid levels */
    const size_t num_levels = _pyramid->info()->num_levels();

    /* The first level of the pyramid has the input image */
    _pyramid->get_pyramid_level(0)->copy_from(*_input);

    for(unsigned int i = 0; i < num_levels - 1; ++i)
    {
        NEScheduler::get().schedule(_horizontal_border_handler[i].get(), Window::DimZ);
        NEScheduler::get().schedule(_horizontal_reduction[i].get(), Window::DimY);
        NEScheduler::get().schedule(_vertical_border_handler[i].get(), Window::DimZ);
        NEScheduler::get().schedule(_vertical_reduction[i].get(), Window::DimY);
    }
}

NEGaussianPyramidOrb::NEGaussianPyramidOrb() // NOLINT
    : _gaus5x5(),
      _scale_nearest()
{
}

void NEGaussianPyramidOrb::configure(const ITensor *input, IPyramid *pyramid, BorderMode border_mode, uint8_t constant_border_value)
{
    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
    ARM_COMPUTE_ERROR_ON(nullptr == pyramid);
    ARM_COMPUTE_ERROR_ON(input->info()->num_dimensions() != pyramid->get_pyramid_level(0)->info()->num_dimensions());
    ARM_COMPUTE_ERROR_ON(input->info()->dimension(0) != pyramid->info()->width());
    ARM_COMPUTE_ERROR_ON(input->info()->dimension(1) != pyramid->info()->height());
    ARM_COMPUTE_ERROR_ON(SCALE_PYRAMID_ORB != pyramid->info()->scale());

    /* Get number of pyramid levels */
    const size_t num_levels = pyramid->info()->num_levels();

    _input   = input;
    _pyramid = pyramid;

    if(num_levels > 1)
    {
        PyramidInfo pyramid_info(num_levels - 1, SCALE_PYRAMID_ORB, pyramid->info()->tensor_shape(), Format::U8);
        _tmp.init(pyramid_info);

        for(unsigned int i = 0; i < num_levels - 1; ++i)
        {
            /* Configure gaussian 5x5 */
            auto gaus5x5_kernel = support::cpp14::make_unique<NEGaussian5x5>();
            gaus5x5_kernel->configure(_pyramid->get_pyramid_level(i), _tmp.get_pyramid_level(i), border_mode, constant_border_value);
            _gaus5x5.emplace_back(std::move(gaus5x5_kernel));

            /* Configure scale */
            auto scale_kernel = support::cpp14::make_unique<NEScale>();
            scale_kernel->configure(_tmp.get_pyramid_level(i), _pyramid->get_pyramid_level(i + 1), InterpolationPolicy::NEAREST_NEIGHBOR, BorderMode::UNDEFINED);
            _scale_nearest.emplace_back(std::move(scale_kernel));
        }

        _tmp.allocate();
    }
}

void NEGaussianPyramidOrb::run()
{
    ARM_COMPUTE_ERROR_ON_MSG(_pyramid == nullptr, "Unconfigured function");

    /* Get number of pyramid levels */
    const size_t num_levels = _pyramid->info()->num_levels();

    /* The first level of the pyramid has the input image */
    _pyramid->get_pyramid_level(0)->copy_from(*_input);

    for(unsigned int i = 0; i < num_levels - 1; ++i)
    {
        _gaus5x5[i].get()->run();
        _scale_nearest[i].get()->run();
    }
}