/**
 * Copyright (c) 2025 Huawei Technologies Co., Ltd.
 * This program is free software, you can redistribute it and/or modify it under the terms and conditions of
 * CANN Open Software License Agreement Version 2.0 (the "License").
 * Please refer to the License for details. You may not use this file except in compliance with the License.
 * THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
 * INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
 * See LICENSE in the root of the software repository for the full text of the License.
 */
#include <iostream>
#include <vector>
#include "acl/acl.h"
#include "aclnnop/aclnn_bidirection_lstmv2.h"

#define CHECK_RET(cond, return_expr) \
    do {                             \
        if (!(cond)) {               \
            return_expr;             \
        }                            \
    } while (0)

#define LOG_PRINT(message, ...)         \
    do {                                \
        printf(message, ##__VA_ARGS__); \
    } while (0)

int64_t GetShapeSize(const std::vector<int64_t>& shape)
{
    int64_t shapeSize = 1;
    for (auto i : shape) {
        shapeSize *= i;
    }
    return shapeSize;
}

void PrintOutResult(std::vector<int64_t>& shape, void** deviceAddr)
{
    auto size = GetShapeSize(shape);
    std::vector<float> resultData(size, 0);
    auto ret = aclrtMemcpy(resultData.data(), resultData.size() * sizeof(resultData[0]), *deviceAddr,
                           size * sizeof(resultData[0]), ACL_MEMCPY_DEVICE_TO_HOST);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("copy result from device to host failed. ERROR: %d\n", ret); return );
    for (int64_t i = 0; i < size; i++) {
        LOG_PRINT("mean result[%ld] is: %f\n", i, resultData[i]);
    }
}

int Init(int32_t deviceId, aclrtStream* stream)
{
    // 固定写法，资源初始化
    auto ret = aclInit(nullptr);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclInit failed. ERROR: %d\n", ret); return ret);
    ret = aclrtSetDevice(deviceId);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSetDevice failed. ERROR: %d\n", ret); return ret);
    ret = aclrtCreateStream(stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtCreateStream failed. ERROR: %d\n", ret); return ret);
    return 0;
}

template <typename T>
int CreateAclTensor(const std::vector<T>& hostData, const std::vector<int64_t>& shape, void** deviceAddr,
                    aclDataType dataType, aclTensor** tensor)
{
    auto size = GetShapeSize(shape) * sizeof(T);
    // 调用aclrtMalloc申请device侧内存
    auto ret = aclrtMalloc(deviceAddr, size, ACL_MEM_MALLOC_HUGE_FIRST);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtMalloc failed. ERROR: %d\n", ret); return ret);
    // 调用aclrtMemcpy将host侧数据复制到device侧内存上
    ret = aclrtMemcpy(*deviceAddr, size, hostData.data(), size, ACL_MEMCPY_HOST_TO_DEVICE);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtMemcpy failed. ERROR: %d\n", ret); return ret);

    // 计算连续tensor的strides
    std::vector<int64_t> strides(shape.size(), 1);
    for (int64_t i = shape.size() - 2; i >= 0; i--) {
        strides[i] = shape[i + 1] * strides[i + 1];
    }

    // 调用aclCreateTensor接口创建aclTensor
    *tensor = aclCreateTensor(shape.data(), shape.size(), dataType, strides.data(), 0, aclFormat::ACL_FORMAT_ND,
                              shape.data(), shape.size(), *deviceAddr);
    return 0;
}

int main()
{
    // 1. （固定写法）device/stream初始化，参考acl API手册
    // 根据自己的实际device填写deviceId
    int32_t deviceId = 0;
    aclrtStream stream;
    auto ret = Init(deviceId, &stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("Init acl failed. ERROR: %d\n", ret); return ret);

    // 2. 构造输入与输出，需要根据API的接口自定义构造
    int time_step = 2;
    int batch_size = 32;
    int input_size = 32;
    int hidden_size = 32;

    int64_t numLayers = 1;
    bool isbias = true;
    bool batchFirst = false;
    bool bidirection = true;
    bool packed = false;

    std::vector<int64_t> selfShape = {time_step, batch_size, input_size};
    std::vector<int64_t> weightHIShape = {4 * hidden_size, input_size};
    std::vector<int64_t> weightHHShape = {4 * hidden_size, hidden_size};
    std::vector<int64_t> initHShape = {2, batch_size, hidden_size};
    std::vector<int64_t> initCShape = {2, batch_size, hidden_size};
    std::vector<int64_t> biasHIShape = {4 * hidden_size};
    std::vector<int64_t> biasHHShape = {4 * hidden_size};
    std::vector<int64_t> outShape = {time_step, batch_size, 2 * hidden_size};
    std::vector<int64_t> outHShape = {2, batch_size, hidden_size};
    std::vector<int64_t> outCShape = {2, batch_size, hidden_size};

    void* selfDeviceAddr = nullptr;
    void* weightHIDeviceAddr = nullptr;
    void* weightHHDeviceAddr = nullptr;
    void* weightHIReverseDeviceAddr = nullptr;
    void* weightHHReverseDeviceAddr = nullptr;
    void* initHDeviceAddr = nullptr;
    void* initCDeviceAddr = nullptr;
    void* biasHIDeviceAddr = nullptr;
    void* biasHHDeviceAddr = nullptr;
    void* biasHIReverseDeviceAddr = nullptr;
    void* biasHHReverseDeviceAddr = nullptr;
    void* outDeviceAddr = nullptr;
    void* outHDeviceAddr = nullptr;
    void* outCDeviceAddr = nullptr;

    aclTensor* self = nullptr;
    aclTensor* weightHI = nullptr;
    aclTensor* weightHH = nullptr;
    aclTensor* weightHIReverse = nullptr;
    aclTensor* weightHHReverse = nullptr;
    aclTensor* biasHI = nullptr;
    aclTensor* biasHH = nullptr;
    aclTensor* biasHIReverse = nullptr;
    aclTensor* biasHHReverse = nullptr;
    aclTensor* batchSize = nullptr;
    aclTensor* initH = nullptr;
    aclTensor* initC = nullptr;
    aclTensor* out = nullptr;
    aclTensor* outH = nullptr;
    aclTensor* outC = nullptr;

    std::vector<uint16_t> selfHostData(GetShapeSize(selfShape));
    std::vector<uint16_t> weightHIHostData(GetShapeSize(weightHIShape));
    std::vector<uint16_t> weightHHHostData(GetShapeSize(weightHHShape));
    std::vector<uint16_t> biasHIHostData(GetShapeSize(biasHIShape));
    std::vector<uint16_t> biasHHHostData(GetShapeSize(biasHHShape));
    std::vector<uint16_t> initHHostData(GetShapeSize(initHShape));
    std::vector<uint16_t> initCHostData(GetShapeSize(initCShape));
    std::vector<uint16_t> outHostData(GetShapeSize(outShape));
    std::vector<uint16_t> outHHostData(GetShapeSize(outHShape));
    std::vector<uint16_t> outCHostData(GetShapeSize(outCShape));

    ret = CreateAclTensor(selfHostData, selfShape, &selfDeviceAddr, aclDataType::ACL_FLOAT16, &self);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    ret = CreateAclTensor(weightHIHostData, weightHIShape, &weightHIDeviceAddr, aclDataType::ACL_FLOAT16, &weightHI);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    ret = CreateAclTensor(weightHHHostData, weightHHShape, &weightHHDeviceAddr, aclDataType::ACL_FLOAT16, &weightHH);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    ret = CreateAclTensor(initHHostData, initHShape, &initHDeviceAddr, aclDataType::ACL_FLOAT16, &initH);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    ret = CreateAclTensor(initCHostData, initCShape, &initCDeviceAddr, aclDataType::ACL_FLOAT16, &initC);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    ret = CreateAclTensor(biasHIHostData, biasHIShape, &biasHIDeviceAddr, aclDataType::ACL_FLOAT16, &biasHI);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    ret = CreateAclTensor(biasHHHostData, biasHHShape, &biasHHDeviceAddr, aclDataType::ACL_FLOAT16, &biasHH);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    ret = CreateAclTensor(weightHIHostData, weightHIShape, &weightHIReverseDeviceAddr, aclDataType::ACL_FLOAT16,
                          &weightHIReverse);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    ret = CreateAclTensor(weightHHHostData, weightHHShape, &weightHHReverseDeviceAddr, aclDataType::ACL_FLOAT16,
                          &weightHHReverse);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    ret = CreateAclTensor(biasHIHostData, biasHIShape, &biasHIReverseDeviceAddr, aclDataType::ACL_FLOAT16,
                          &biasHIReverse);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    ret = CreateAclTensor(biasHHHostData, biasHHShape, &biasHHReverseDeviceAddr, aclDataType::ACL_FLOAT16,
                          &biasHHReverse);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    ret = CreateAclTensor(outHostData, outShape, &outDeviceAddr, aclDataType::ACL_FLOAT16, &out);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    ret = CreateAclTensor(outHHostData, outHShape, &outHDeviceAddr, aclDataType::ACL_FLOAT16, &outH);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    ret = CreateAclTensor(outCHostData, outCShape, &outCDeviceAddr, aclDataType::ACL_FLOAT16, &outC);
    CHECK_RET(ret == ACL_SUCCESS, return ret);

    // 3. 调用CANN算子库API，需要修改为具体的Api名称
    uint64_t workspaceSize = 0;
    aclOpExecutor* executor;

    // 调用aclnnBidirectionLSTMV2第一段接口
    ret = aclnnBidirectionLSTMV2GetWorkspaceSize(self, initH, initC, weightHI, weightHH, biasHI, biasHH,
                                                 weightHIReverse, weightHHReverse, biasHIReverse, biasHHReverse,
                                                 batchSize, numLayers, isbias, batchFirst, bidirection, packed, out,
                                                 outH, outC, &workspaceSize, &executor);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnBidirectionLSTMV2GetWorkspaceSize failed. ERROR: %d\n", ret);
              return ret);

    // 根据第一段接口计算出的workspaceSize申请device内存
    void* workspaceAddr = nullptr;
    if (workspaceSize > 0) {
        ret = aclrtMalloc(&workspaceAddr, workspaceSize, ACL_MEM_MALLOC_HUGE_FIRST);
        CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("allocate workspace failed. ERROR: %d\n", ret); return ret);
    }

    // 调用aclnnBidirectionLSTMV2第二段接口
    ret = aclnnBidirectionLSTMV2(workspaceAddr, workspaceSize, executor, stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnBidirectionLSTMV2 failed. ERROR: %d\n", ret); return ret);

    // 4. （固定写法）同步等待任务执行结束
    ret = aclrtSynchronizeStream(stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSynchronizeStream failed. ERROR: %d\n", ret); return ret);

    // 5. 获取输出的值，将device侧内存上的结果复制至host侧，需要根据具体API的接口定义修改
    PrintOutResult(outShape, &outDeviceAddr);
    PrintOutResult(outHShape, &outHDeviceAddr);
    PrintOutResult(outCShape, &outCDeviceAddr);

    // 6. 释放aclTensor和aclScalar，需要根据具体API的接口定义修改
    aclDestroyTensor(self);
    aclDestroyTensor(weightHI);
    aclDestroyTensor(weightHH);
    aclDestroyTensor(initH);
    aclDestroyTensor(initC);
    aclDestroyTensor(biasHI);
    aclDestroyTensor(biasHH);
    aclDestroyTensor(weightHIReverse);
    aclDestroyTensor(weightHHReverse);
    aclDestroyTensor(biasHIReverse);
    aclDestroyTensor(biasHHReverse);
    aclDestroyTensor(out);
    aclDestroyTensor(outH);
    aclDestroyTensor(outC);

    // 7. 释放device资源
    aclrtFree(selfDeviceAddr);
    aclrtFree(weightHIDeviceAddr);
    aclrtFree(weightHHDeviceAddr);
    aclrtFree(initHDeviceAddr);
    aclrtFree(initCDeviceAddr);
    aclrtFree(biasHIDeviceAddr);
    aclrtFree(biasHHDeviceAddr);
    aclrtFree(weightHIReverseDeviceAddr);
    aclrtFree(weightHHReverseDeviceAddr);
    aclrtFree(biasHIReverseDeviceAddr);
    aclrtFree(biasHHReverseDeviceAddr);
    aclrtFree(outDeviceAddr);
    aclrtFree(outHDeviceAddr);
    aclrtFree(outCDeviceAddr);

    if (workspaceSize > 0) {
        aclrtFree(workspaceAddr);
    }
    aclrtDestroyStream(stream);
    aclrtResetDevice(deviceId);
    aclFinalize();

    return 0;
}