/*******************************************************
 * Copyright (c) 2014, ArrayFire
 * All rights reserved.
 *
 * This file is distributed under 3-clause BSD license.
 * The complete license agreement can be obtained at:
 * http://arrayfire.com/licenses/BSD-3-Clause
 ********************************************************/

#pragma once
#include <kernel_headers/unwrap.hpp>
#include <program.hpp>
#include <cache.hpp>
#include <traits.hpp>
#include <string>
#include <map>
#include <mutex>
#include <common/dispatch.hpp>
#include <Param.hpp>
#include <debug_opencl.hpp>
#include <type_util.hpp>
#include <math.hpp>
#include "config.hpp"

using cl::Buffer;
using cl::Program;
using cl::Kernel;
using cl::KernelFunctor;
using cl::EnqueueArgs;
using cl::NDRange;
using std::string;

namespace opencl
{
    namespace kernel
    {
        template<typename T>
        void unwrap(Param out, const Param in,
                    const dim_t wx, const dim_t wy,
                    const dim_t sx, const dim_t sy,
                    const dim_t px, const dim_t py,
                    const dim_t nx, const bool is_column)
        {
            std::string ref_name =
                std::string("unwrap_") +
                std::string(dtype_traits<T>::getName()) +
                std::string("_") +
                std::to_string(is_column);

            int device = getActiveDeviceId();

            kc_entry_t entry = kernelCache(device, ref_name);

            if (entry.prog==0 && entry.ker==0) {
                ToNumStr<T> toNumStr;
                std::ostringstream options;
                options << " -D is_column=" << is_column
                        << " -D ZERO=" << toNumStr(scalar<T>(0))
                        << " -D T="    << dtype_traits<T>::getName();

                if (std::is_same<T, double>::value ||
                    std::is_same<T, cdouble>::value) {
                    options << " -D USE_DOUBLE";
                }

                Program prog;
                buildProgram(prog, unwrap_cl, unwrap_cl_len, options.str());

                entry.prog = new Program(prog);
                entry.ker = new Kernel(*entry.prog, "unwrap_kernel");

                addKernelToCache(device, ref_name, entry);
            }

            dim_t TX = 1, TY = 1;
            dim_t BX = 1;
            const dim_t BY = out.info.dims[2] * out.info.dims[3];
            dim_t reps = 1;

            if (is_column) {
                TX = std::min(THREADS_PER_GROUP, nextpow2(out.info.dims[0]));
                TY = THREADS_PER_GROUP / TX;
                BX = divup(out.info.dims[1], TY);
                reps = divup((wx * wy), TX);
            } else {
                TX = THREADS_X;
                TY = THREADS_Y;
                BX = divup(out.info.dims[0], TX);
                reps = divup((wx * wy), TY);
            }

            NDRange local(TX, TY);
            NDRange global(local[0] * BX,
                            local[1] * BY);

            auto unwrapOp = KernelFunctor<Buffer, const KParam,
                                        const Buffer, const KParam,
                                        const int, const int,
                                        const int, const int,
                                        const int, const int,
                                        const int, const int> (*entry.ker);

            unwrapOp(EnqueueArgs(getQueue(), global, local),
                    *out.data, out.info, *in.data, in.info, wx, wy, sx, sy, px, py, nx, reps);

            CL_DEBUG_FINISH(getQueue());
        }
    }
}
