/**
 * This program is free software, you can redistribute it and/or modify.
 * Copyright (c) 2025 Huawei Technologies Co., Ltd.
 * This file is a part of the CANN Open Software.
 * Licensed under 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 "aclnn_range.h"
 #include<cmath>
 using namespace std;
 
 #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，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);
     // 2. 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);
     // 3. 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;
 }
 
 int main()
 {   LOG_PRINT("[TEST]hellorange");
      // 1. 调用acl进行device/stream初始化
    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
    float startValue = 2.0;
    float endValue = 29.0;
    float stepValue = 3.0;

    aclTensor* selfStart = nullptr;
    void* selfStartDeviceAddr = nullptr;
    std::vector<int64_t> selfStartShape = {1};
    std::vector<int64_t> selfStartHostData(1, startValue);
    ret = CreateAclTensor(selfStartHostData, selfStartShape, &selfStartDeviceAddr, aclDataType::ACL_FLOAT, &selfStart);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    const std::vector<float> startVec = {startValue};
    aclFloatArray* startArray = aclCreateFloatArray(startVec.data(), startVec.size());
    
    aclTensor* selfEnd = nullptr;
    void* selfEndDeviceAddr = nullptr;
    std::vector<int64_t> selfEndShape = {1};
    std::vector<int64_t> selfEndHostData(1, endValue);
    ret = CreateAclTensor(selfEndHostData, selfEndShape, &selfEndDeviceAddr, aclDataType::ACL_FLOAT, &selfEnd);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    const std::vector<float> endVec = {endValue};
    aclFloatArray* endArray = aclCreateFloatArray(endVec.data(), endVec.size());
    
    aclTensor* selfStep = nullptr;
    void* selfStepDeviceAddr = nullptr;
    std::vector<int64_t> selfStepShape = {1};
    std::vector<int64_t> selfStepHostData(1, stepValue);
    ret = CreateAclTensor(selfStepHostData, selfStepShape, &selfStepDeviceAddr, aclDataType::ACL_FLOAT, &selfStep);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    const std::vector<float> stepVec = {stepValue};
    aclFloatArray* stepArray = aclCreateFloatArray(stepVec.data(), stepVec.size());
  
    //计算输出长度
    int64_t outputLength=static_cast<int64_t>(abs(  ceil( (endValue-startValue)/stepValue ) )  );
    std::cout<<"输出数据长度为："<<outputLength<<endl;
    aclTensor* out = nullptr;
    void* outDeviceAddr = nullptr;
    std::vector<int64_t> outShape = {outputLength};
    std::vector<float> outHostData(outputLength, 1);
    ret = CreateAclTensor(outHostData, outShape, &outDeviceAddr, aclDataType::ACL_FLOAT, &out);
    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;

    // 4. 调用aclnn第一段接口
    ret = aclnnRangeGetWorkspaceSize(startArray,endArray,stepArray,out ,&workspaceSize, &executor);
    if (ret != ACL_SUCCESS) {
        const char* errMsg = aclGetRecentErrMsg();
        LOG_PRINT("[ERROR] aclnnRangeGetWorkspaceSize failed: %s", errMsg ? errMsg : "nullptr");
    }
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnRangeGetWorkspaceSize 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 > static_cast<uint64_t>(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);
    }

    // 5. 调用aclnn第二段接口

    ret = aclnnRange(workspaceAddr, workspaceSize, executor, stream);
 
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnRange failed. ERROR: %d\n", ret); return ret);

    // 6. （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);

    // 7. 获取输出的值，将device侧内存上的结果拷贝至host侧，需要根据具体API的接口定义修改
    PrintOutResult(outShape, &outDeviceAddr);

    // 8. 释放aclTensor，需要根据具体API的接口定义修改
    aclDestroyTensor(selfStart);
    aclDestroyTensor(selfEnd);
    aclDestroyTensor(selfStep);
    aclDestroyFloatArray(startArray);
    aclDestroyFloatArray(endArray);
    aclDestroyFloatArray(stepArray);
    aclDestroyTensor(out);
    
    // 9. 释放device资源
    aclrtFree(selfStartDeviceAddr);
    aclrtFree(selfEndDeviceAddr);
    aclrtFree(selfStepDeviceAddr);
    aclrtFree(outDeviceAddr);
    if (workspaceSize > static_cast<uint64_t>(0)) {
        aclrtFree(workspaceAddr);
    }
    aclrtDestroyStream(stream);
    aclrtResetDevice(deviceId);

    // 10. acl去初始化
    aclFinalize();

    return 0;
 }