//
//  CastBufExecution.cpp
//  MNN
//
//  Created by MNN on 2023/08/11.
//  Copyright © 2018, Alibaba Group Holding Limited
//

#ifndef MNN_OPENCL_BUFFER_CLOSED
#include "backend/opencl/execution/buffer/CastBufExecution.hpp"

namespace MNN {
namespace OpenCL {

CastBufExecution::CastBufExecution(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs, const std::string& compute, const MNN::Op* op, Backend* backend) : CommonExecution(backend, op) {
    mBuildOptions.emplace(compute);
}
ErrorCode CastBufExecution::onEncode(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs) {
    mUnits.resize(1);
    auto &unit = mUnits[0];
    Tensor* input      = inputs[0];
    Tensor* output     = outputs[0];
    auto openCLBackend = static_cast<OpenCLBackend*>(backend());
    auto runtime       = openCLBackend->getOpenCLRuntime();

    std::vector<int> outputShape = tensorShapeFormat(output);
    int totalSize = 0;
    if(MNN::MNN_DATA_FORMAT_NC4HW4 == TensorUtils::getDescribe(output)->dimensionFormat){
        totalSize = outputShape[0] * outputShape[1] * outputShape[2] * ROUND_UP(outputShape[3], 4);
    }else{
        totalSize = outputShape[0] * outputShape[1] * outputShape[2] * outputShape[3];
    }
    std::set<std::string> buildOptions = mBuildOptions;
    if(totalSize % 4 != 0) {
        buildOptions.emplace("-DPACK_LEAVE");
    }
    unit.kernel = runtime->buildKernel("cast_buf", "cast_buf", mBuildOptions, openCLBackend->getPrecision(), inputs[0], outputs[0]);
    mMaxWorkGroupSize = static_cast<uint32_t>(runtime->getMaxWorkGroupSize(unit.kernel));
    
    mGlobalWorkSize = {
        static_cast<uint32_t>(UP_DIV(totalSize, 4)),
        static_cast<uint32_t>(1)
    };

    uint32_t idx = 0;
    cl_int ret = CL_SUCCESS;
    ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[0]);
    ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]);
    ret |= unit.kernel->get().setArg(idx++, openCLBuffer(input));
    ret |= unit.kernel->get().setArg(idx++, openCLBuffer(output));
    ret |= unit.kernel->get().setArg(idx++, totalSize);
    MNN_CHECK_CL_SUCCESS(ret, "setArg CastBufExecution");

    std::string kernelName = "cast_buf";
    mLocalSize = localWS2DDefault(mGlobalWorkSize, mMaxWorkGroupSize, openCLBackend->getOpenCLRuntime(), kernelName, unit.kernel, openCLBackend->getCLTuneLevel(), "cast_buf").first;
    openCLBackend->recordKernel2d(unit.kernel, mGlobalWorkSize, mLocalSize);
    unit.globalWorkSize = {mGlobalWorkSize[0], mGlobalWorkSize[1]};
    unit.localWorkSize = {mLocalSize[0], mLocalSize[1]};
    return NO_ERROR;
}

static DataType _mapDataType(DataType src) {
    if (DataType_DT_BOOL == src) {
        return DataType_DT_INT32;
    }
    if (DataType_DT_INT64 == src) {
        return DataType_DT_INT32;
    }
    if (DataType_DT_DOUBLE == src) {
        return DataType_DT_FLOAT;
    }
    return src;
}

class CastBufCreator : public OpenCLBackend::Creator {
public:
    virtual Execution* onCreate(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs,
                                const MNN::Op* op, Backend* backend) const override {
        for (int i = 0; i < inputs.size(); ++i) {
            TensorUtils::setTensorSupportPack(inputs[i], false);
        }
        for (int i = 0; i < outputs.size(); ++i) {
            TensorUtils::setTensorSupportPack(outputs[i], false);
        }
        auto cast = op->main_as_CastParam();
        // cast param srcT is invalid
        // auto srcT = _mapDataType(cast->srcT());
        auto dstT = _mapDataType(cast->dstT());

        const auto &inputDataType = inputs[0]->getType();
        if (inputDataType.bytes() == 4 && cast->dstT() == MNN::DataType_DT_BOOL) OPENCL_CREATOR_CHECK(new CastBufExecution(inputs, outputs, "-DTO_BOOL", op, backend)); else OPENCL_CREATOR_CHECK(new CastBufExecution(inputs, outputs, "", op, backend));
        return nullptr;
    }
};

REGISTER_OPENCL_OP_CREATOR(CastBufCreator, OpType_Cast, BUFFER);

} // namespace OpenCL
} // namespace MNN
#endif /* MNN_OPENCL_BUFFER_CLOSED */