/**

 * 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.

 */

 	 

/**

 *

 * NOTE: Portions of this code were AI-generated and have been

 * technically reviewed for functional accuracy and security

 */



#include <iostream>

#include <vector>

#include <cmath>

#include "acl/acl.h"

#include "../op_api/aclnn_asinh_v2.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;

}



int main() 

{

    // 1. （固定写法）device/stream初始化，参考acl API手册

    int32_t deviceId = 0;

    aclrtStream stream;

    auto ret = Init(deviceId, &stream);

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



    // 2. 构造输入与输出

    std::vector<int64_t> selfShape = {8, 8};

    std::vector<int64_t> outShape = {8, 8};

    void* selfDeviceAddr = nullptr;

    void* outDeviceAddr = nullptr;

    aclTensor* self = nullptr;

    aclTensor* out = nullptr;



    /* 构造输入数据，基于等价类 */

    std::vector<float> selfHostData = {

        -INFINITY,  -12,        -1.000001, -1.00001,    -1.0001,    -1.001,     -1.01,  -1.0,

        -0.99999,   -0.9999,    -0.999,    -0.99,       -0.9,       -0.8,       -0.71,  -0.705,  

        -0.7,       -0.65,      -0.6,      -0.5,        -0.4,       -0.3,       -0.2,   -0.1,

        -0.01,      -0.001,     -0.0001,   -0.00001,    -0.000001,  -0.0000001,

        0,          NAN,        0.0000001, 0.000001,    0.00001,    0.0001,     0.01,   0.1,

        0.2,        0.3,        0.4,       0.5,         0.5,        0.6,        0.65,   0.7,

        0.705,      0.71,       0.8,       0.9,         0.99,       0.999,      0.9999, 0.99999,

        1,          1.01,       1.001,     1.0001,      1.00001,    1.000001,   12,     INFINITY};

    /* 输出数据，初始化成0，后续会被 */

    std::vector<float> outHostData(selfHostData.size(), 0.0);



    // 创建张量

    ret = CreateAclTensor(selfHostData, selfShape, &selfDeviceAddr, aclDataType::ACL_FLOAT, &self);

    CHECK_RET(ret == ACL_SUCCESS, return ret);

    ret = CreateAclTensor(outHostData, outShape, &outDeviceAddr, aclDataType::ACL_FLOAT, &out);

    CHECK_RET(ret == ACL_SUCCESS, return ret);



    // 3. 获取workspaceSize大小并分配空间

    uint64_t workspaceSize = 0;

    aclOpExecutor* executor = nullptr;

    ret = aclnnAsinhV2GetWorkspaceSize(self, out, &workspaceSize, &executor);

    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnAsinhV2GetWorkspaceSize failed. ERROR: %d\n", ret); return ret);



    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);

    }



    // 4、调用asinh算子

    ret = aclnnAsinhV2(workspaceAddr, workspaceSize, executor, stream);

    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnAsinhV2 failed. ERROR: %d\n", ret); return ret);



    // 5、同步等待算子执行结束

    ret = aclrtSynchronizeStream(stream);

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



    // 6. 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

    auto size = GetShapeSize(outShape);

    std::vector<float> resultData(size, 0.0);

    ret = aclrtMemcpy(

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



    // 6、数据校验

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

        float outputExpected = std::asinh(selfHostData[i]);

        int32_t right = (std::fabs(resultData[i] - outputExpected) > 1e-6) ? 0 : 1;

        LOG_PRINT("%ld: asinh(%lf) = %lf, %lf, right=%d\n", i, selfHostData[i], resultData[i], outputExpected, right);

    }



    // 7. 资源释放

    aclDestroyTensor(self);

    aclDestroyTensor(out);

    aclrtFree(selfDeviceAddr);

    aclrtFree(outDeviceAddr);

    if (workspaceSize > 0) {

        aclrtFree(workspaceAddr);

    }

    aclrtDestroyStream(stream);

    aclrtResetDevice(deviceId);

    aclFinalize();

    return 0;

}