/**
 * 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.
 */

 /* Generated By CANNBot */

#include <cmath>
#include <iostream>
#include <vector>
#include "acl/acl.h"
#include "aclnnop/aclnn_cosh.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 ExecuteCosh(aclTensor* self, aclTensor* out, aclrtStream stream) {
    uint64_t workspaceSize = 0;
    aclOpExecutor* executor;
    int ret = aclnnCoshGetWorkspaceSize(self, out, &workspaceSize, &executor);
    if (ret != ACL_SUCCESS) return ret;

    void* workspaceAddr = nullptr;
    if (workspaceSize > 0) {
        ret = aclrtMalloc(&workspaceAddr, workspaceSize, ACL_MEM_MALLOC_HUGE_FIRST);
        if (ret != ACL_SUCCESS) return ret;
    }

    ret = aclnnCosh(workspaceAddr, workspaceSize, executor, stream);
    if (workspaceSize > 0) aclrtFree(workspaceAddr);
    return ret;
}

int PrintAndCheckResults(void* outDeviceAddr, const std::vector<int64_t>& outShape,
                         const std::vector<float>& selfHostData) {
    auto size = GetShapeSize(outShape);
    std::vector<float> resultData(size, 0);
    int ret = aclrtMemcpy(resultData.data(), resultData.size() * sizeof(resultData[0]), outDeviceAddr,
                          size * sizeof(resultData[0]), ACL_MEMCPY_DEVICE_TO_HOST);
    if (ret != ACL_SUCCESS) return ret;

    // FP32 社区标准容差（spec.yaml numerical_tolerance.per_dtype）
    constexpr double kAtolFp32 = 1.22e-4;
    constexpr double kRtolFp32 = 1.22e-3;
    bool ok = true;
    for (int64_t i = 0; i < size; i++) {
        double golden = std::cosh(static_cast<double>(selfHostData[i]));
        double npu = resultData[i];
        double absErr = std::abs(npu - golden);
        double relErr = absErr / (std::abs(golden) + 1e-7);
        bool casePass = (absErr <= kAtolFp32) || (relErr <= kRtolFp32);
        if (!casePass) ok = false;
        LOG_PRINT("result[%ld] x=%.6f golden=%.6f npu=%.6f abs=%.3e rel=%.3e %s\n",
                  i, selfHostData[i], golden, npu, absErr, relErr,
                  casePass ? "PASS" : "FAIL");
    }
    LOG_PRINT("aclnnCosh sample: %s\n", ok ? "PASS" : "FAIL");
    return ok ? ACL_SUCCESS : -1;
}

int CreateInputOutputTensors(aclTensor** self, aclTensor** out,
                             void** selfDeviceAddr, void** outDeviceAddr,
                             std::vector<float>& selfHostData) {
    std::vector<int64_t> selfShape = {4, 2};
    std::vector<int64_t> outShape = {4, 2};
    // 覆盖 0、±1、±2、小值/中等值：cosh 偶函数 + 典型范围
    selfHostData = {0.0f, 1.0f, -1.0f, 0.5f, -0.5f, 2.0f, -2.0f, 0.25f};
    std::vector<float> outHostData(8, 0.0f);

    // 创建self aclTensor
    int ret = CreateAclTensor(selfHostData, selfShape, selfDeviceAddr, aclDataType::ACL_FLOAT, self);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    // 创建out aclTensor
    ret = CreateAclTensor(outHostData, outShape, outDeviceAddr, aclDataType::ACL_FLOAT, out);
    CHECK_RET(ret == ACL_SUCCESS, return ret);

    return ACL_SUCCESS;
}

void CleanupResources(aclTensor* self, aclTensor* out,
                      void* selfDeviceAddr, void* outDeviceAddr,
                      aclrtStream stream, int32_t deviceId) {
    // 释放aclTensor和aclScalar，需要根据具体API的接口定义修改
    aclDestroyTensor(self);
    aclDestroyTensor(out);

    // 释放device资源，需要根据具体API的接口定义修改
    aclrtFree(selfDeviceAddr);
    aclrtFree(outDeviceAddr);
    aclrtDestroyStream(stream);
    aclrtResetDevice(deviceId);
    aclFinalize();
}

int main() {
    // 1. Device/stream initialization
    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. Construct input and output tensors
    void* selfDeviceAddr = nullptr;
    void* outDeviceAddr = nullptr;
    aclTensor* self = nullptr;
    aclTensor* out = nullptr;
    std::vector<float> selfHostData;

    ret = CreateInputOutputTensors(&self, &out, &selfDeviceAddr, &outDeviceAddr, selfHostData);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("Create tensors failed. ERROR: %d\n", ret);
              CleanupResources(self, out, selfDeviceAddr, outDeviceAddr, stream, deviceId); return ret);

    // 3. Execute cosh operation
    ret = ExecuteCosh(self, out, stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("ExecuteCosh failed. ERROR: %d\n", ret);
              CleanupResources(self, out, selfDeviceAddr, outDeviceAddr, stream, deviceId); return ret);

    // 4. Synchronize stream
    ret = aclrtSynchronizeStream(stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSynchronizeStream failed. ERROR: %d\n", ret);
              CleanupResources(self, out, selfDeviceAddr, outDeviceAddr, stream, deviceId); return ret);

    // 5. Print results and check against CPU std::cosh golden
    std::vector<int64_t> outShape = {4, 2};
    int checkRet = PrintAndCheckResults(outDeviceAddr, outShape, selfHostData);

    // 6. Cleanup resources
    CleanupResources(self, out, selfDeviceAddr, outDeviceAddr, stream, deviceId);

    return checkRet == ACL_SUCCESS ? 0 : 1;
}