/**

 * Copyright (c) 2026 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_lt_tensor.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;

}



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侧数据拷贝到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;

}



struct LtTensorData {

    std::vector<int64_t> selfShape = {4, 2};

    std::vector<int64_t> otherShape = {4, 2};

    std::vector<int64_t> outShape = {4, 2};

    void* selfDeviceAddr = nullptr;

    void* otherDeviceAddr = nullptr;

    void* outDeviceAddr = nullptr;

    aclTensor* self = nullptr;

    aclTensor* other = nullptr;

    aclTensor* out = nullptr;

    std::vector<double> selfHostData = {0, 1, 2, 3, 4, 5, 6, 7};

    std::vector<double> otherHostData = {5, 5, 5, 5, 5, 5, 5, 5};

    std::vector<double> outHostData = {0, 0, 0, 0, 0, 0, 0, 0};

    void* workspaceAddr = nullptr;

    uint64_t workspaceSize = 0;

};



int CreateInputAndOutputTensors(LtTensorData& data)

{

    auto ret = 0;



    // 创建self aclTensor

    ret = CreateAclTensor(data.selfHostData, data.selfShape, &data.selfDeviceAddr, aclDataType::ACL_DOUBLE, &data.self);

    CHECK_RET(ret == ACL_SUCCESS, return ret);

    // 创建other aclTensor

    ret = CreateAclTensor(

        data.otherHostData, data.otherShape, &data.otherDeviceAddr, aclDataType::ACL_DOUBLE, &data.other);

    CHECK_RET(ret == ACL_SUCCESS, return ret);

    // 创建out aclTensor

    ret = CreateAclTensor(data.outHostData, data.outShape, &data.outDeviceAddr, aclDataType::ACL_DOUBLE, &data.out);

    CHECK_RET(ret == ACL_SUCCESS, return ret);



    return ret;

}



int ExecuteLtTensorComputation(aclrtStream stream, LtTensorData& data)

{

    auto ret = 0;

    aclOpExecutor* executor;



    // 调用aclnnLtTensor第一段接口

    ret = aclnnLtTensorGetWorkspaceSize(data.self, data.other, data.out, &data.workspaceSize, &executor);

    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnLtTensorGetWorkspaceSize failed. ERROR: %d\n", ret); return ret);



    // 根据第一段接口计算出的workspaceSize申请device内存

    data.workspaceAddr = nullptr;

    if (data.workspaceSize > 0) {

        ret = aclrtMalloc(&data.workspaceAddr, data.workspaceSize, ACL_MEM_MALLOC_HUGE_FIRST);

        CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("allocate workspace failed. ERROR: %d\n", ret); return ret);

    }



    // 调用aclnnLtTensor第二段接口

    ret = aclnnLtTensor(data.workspaceAddr, data.workspaceSize, executor, stream);

    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnLtTensor failed. ERROR: %d\n", ret); return ret);



    // 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);



    return ret;

}



int ProcessAndPrintResults(const LtTensorData& data)

{

    auto ret = 0;

    auto size = GetShapeSize(data.outShape);

    std::vector<double> resultData(size, 0);

    ret = aclrtMemcpy(

        resultData.data(), resultData.size() * sizeof(resultData[0]), data.outDeviceAddr, 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 ret);

    for (int64_t i = 0; i < size; i++) {

        LOG_PRINT("less tensor result[%ld] is: %lf\n", i, resultData[i]);

    }

    return ret;

}



void ReleaseResources(LtTensorData& data)

{

    // 释放aclTensor和aclScalar

    aclDestroyTensor(data.self);

    aclDestroyTensor(data.other);

    aclDestroyTensor(data.out);



    // 释放device资源

    aclrtFree(data.selfDeviceAddr);

    aclrtFree(data.otherDeviceAddr);

    aclrtFree(data.outDeviceAddr);

    if (data.workspaceSize > 0) {

        aclrtFree(data.workspaceAddr);

    }

}



int ExecuteLtTensorOperator(aclrtStream stream)

{

    LtTensorData data;



    // 创建输入和输出张量

    auto ret = CreateInputAndOutputTensors(data);

    CHECK_RET(ret == ACL_SUCCESS, return ret);



    // 执行LtTensor算子操作

    ret = ExecuteLtTensorComputation(stream, data);

    CHECK_RET(ret == ACL_SUCCESS, return ret);



    // 处理并打印结果

    ret = ProcessAndPrintResults(data);

    CHECK_RET(ret == ACL_SUCCESS, return ret);



    // 释放资源

    ReleaseResources(data);



    return 0;

}



int main()

{

    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);



    // 执行InplaceLtScalar操作

    ret = ExecuteLtTensorOperator(stream);

    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("ExecuteInplaceLtScalarOperator failed. ERROR: %d\n", ret); return ret);



    // 重置设备和终结ACL

    aclrtDestroyStream(stream);

    aclrtResetDevice(deviceId);

    aclFinalize();

    return 0;

}