/*
 * Copyright (c) 2018-2019 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/core/NEON/kernels/NEFlattenLayerKernel.h"

#include "arm_compute/core/CPP/Validate.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"

#include "arm_compute/core/utils/misc/ShapeCalculator.h"

#include <arm_neon.h>

using namespace arm_compute;
using namespace misc::shape_calculator;

namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
{
    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
    ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
    // Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input) is not needed here as this kernel doesn't use NEON FP16 instructions.
    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);

    // Checks performed when output is configured
    if(output->total_size() != 0)
    {
        const TensorInfo tensor_info_output = input->clone()->set_tensor_shape(compute_flatten_shape(input));

        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &tensor_info_output);
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
    }

    return Status{};
}

std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
{
    // Output tensor auto initialization if not yet initialized
    auto_init_if_empty(*output, input->clone()->set_tensor_shape(compute_flatten_shape(input)));

    Window win = calculate_max_window(*input, Steps()); // Flatten does not need paddings

    output->set_valid_region(ValidRegion(Coordinates(), output->tensor_shape()));

    return std::make_pair(Status{}, win);
}
} // namespace

NEFlattenLayerKernel::NEFlattenLayerKernel()
    : _input(nullptr), _output(nullptr)
{
}

void NEFlattenLayerKernel::configure(const ITensor *input, ITensor *output)
{
    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));

    _input  = input;
    _output = output;

    // Configure kernel window
    auto win_config = validate_and_configure_window(input->info(), output->info());
    ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
    INEKernel::configure(win_config.second);
}

Status NEFlattenLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output)
{
    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get()).first);
    return Status{};
}

void NEFlattenLayerKernel::run(const Window &window, const ThreadInfo &info)
{
    ARM_COMPUTE_UNUSED(info);
    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);

    const size_t in_width   = _input->info()->dimension(0);
    const size_t in_height  = _input->info()->dimension(1);
    const size_t out_step_x = in_width * _input->info()->element_size();
    const size_t out_step_y = out_step_x * in_height;

    Window in_window(window);
    in_window.set(Window::DimX, Window::Dimension(0, 1, 1));

    Window out_window;
    out_window.use_tensor_dimensions(_output->info()->tensor_shape());
    out_window.set(Window::DimX, Window::Dimension(out_window.x().start(), out_window.x().end(), in_width));

    Window in_slice  = in_window.first_slice_window_3D();
    Window out_slice = out_window.first_slice_window_1D();

    do
    {
        Iterator in(_input, in_slice);
        Iterator out(_output, out_slice);

        uint8_t *out_ptr = out.ptr();

        execute_window_loop(in_slice, [&](const Coordinates & id)
        {
            memcpy(out_ptr + id.y() * out_step_x + id.z() * out_step_y, in.ptr(), out_step_x);
        },
        in);
    }
    while(in_window.slide_window_slice_3D(in_slice) && out_window.slide_window_slice_1D(out_slice));
}