/**
 * 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 <unistd.h>
#include "acl/acl.h"
#include "aclnnop/aclnn_group_norm_swish_grad.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 shape_size = 1;
  for (auto i : shape) {
    shape_size *= i;
  }
  return shape_size;
}

int Init(int32_t deviceId, aclrtStream* stream) {
  // 固定写法，AscendCL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对外接口列表
  // 根据自己的实际device填写deviceId
  int32_t deviceId = 0;
  aclrtStream stream;
  auto ret = Init(deviceId, &stream);
  // check根据自己的需要处理
  CHECK_RET(ret == 0, 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
  std::vector<int64_t> dyShape = {2, 3, 4};
  std::vector<int64_t> meanShape = {2, 1};
  std::vector<int64_t> rstdShape = {2, 1};
  std::vector<int64_t> xShape = {2, 3, 4};
  std::vector<int64_t> gammaShape = {3};
  std::vector<int64_t> betaShape = {3};
  std::vector<int64_t> dxOutShape = {2, 3, 4};
  std::vector<int64_t> dgammaOutShape = {3};
  std::vector<int64_t> dbetaOutShape = {3};
  void* dyDeviceAddr = nullptr;
  void* meanDeviceAddr = nullptr;
  void* rstdDeviceAddr = nullptr;
  void* xDeviceAddr = nullptr;
  void* gammaDeviceAddr = nullptr;
  void* betaDeviceAddr = nullptr;
  void* dxOutDeviceAddr = nullptr;
  void* dgammaOutDeviceAddr = nullptr;
  void* dbetaOutDeviceAddr = nullptr;
  aclTensor* dy = nullptr;
  aclTensor* mean = nullptr;
  aclTensor* rstd = nullptr;
  aclTensor* x = nullptr;
  aclTensor* gamma = nullptr;
  aclTensor* beta = nullptr;
  aclTensor* dxOut = nullptr;
  aclTensor* dgammaOut = nullptr;
  aclTensor* dbetaOut = nullptr;
  std::vector<float> dyHostData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0,
                                   13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0};
  std::vector<float> meanHostData = {2.0, 2};
  std::vector<float> rstdHostData = {2.0, 2};
  std::vector<float> xHostData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0,
                                  13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0};
  std::vector<float> gammaHostData = {2.0, 2, 2};
  std::vector<float> betaHostData = {2.0, 2, 2};
  std::vector<float> dxOutHostData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0,
                                   13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0};
  std::vector<float> dgammaOutHostData = {2.0, 2, 2};
  std::vector<float> dbetaOutHostData = {2.0, 2, 2};
  int64_t numGroups = 1;
  char* dataFormatOptional = nullptr;
  float swishScale = 1.0f;
  bool dgammaIsRequire = true;
  bool dbetaIsRequire = true;
  // 创建dy aclTensor
  ret = CreateAclTensor(dyHostData, dyShape, &dyDeviceAddr, aclDataType::ACL_FLOAT, &dy);
  CHECK_RET(ret == ACL_SUCCESS, return ret);
  // 创建mean aclTensor
  ret = CreateAclTensor(meanHostData, meanShape, &meanDeviceAddr, aclDataType::ACL_FLOAT, &mean);
  CHECK_RET(ret == ACL_SUCCESS, return ret);
  // 创建rstd aclTensor
  ret = CreateAclTensor(rstdHostData, rstdShape, &rstdDeviceAddr, aclDataType::ACL_FLOAT, &rstd);
  CHECK_RET(ret == ACL_SUCCESS, return ret);
  // 创建x aclTensor
  ret = CreateAclTensor(xHostData, xShape, &xDeviceAddr, aclDataType::ACL_FLOAT, &x);
  CHECK_RET(ret == ACL_SUCCESS, return ret);
  // 创建gamma aclTensor
  ret = CreateAclTensor(gammaHostData, gammaShape, &gammaDeviceAddr, aclDataType::ACL_FLOAT, &gamma);
  CHECK_RET(ret == ACL_SUCCESS, return ret);
  // 创建beta aclTensor
  ret = CreateAclTensor(betaHostData, betaShape, &betaDeviceAddr, aclDataType::ACL_FLOAT, &beta);
  CHECK_RET(ret == ACL_SUCCESS, return ret);
  // 创建dxOut aclTensor
  ret = CreateAclTensor(dxOutHostData, dxOutShape, &dxOutDeviceAddr, aclDataType::ACL_FLOAT, &dxOut);
  CHECK_RET(ret == ACL_SUCCESS, return ret);
  // 创建dgammaOut aclTensor
  ret = CreateAclTensor(dgammaOutHostData, dgammaOutShape, &dgammaOutDeviceAddr, aclDataType::ACL_FLOAT, &dgammaOut);
  CHECK_RET(ret == ACL_SUCCESS, return ret);
  // 创建dbetaOut aclTensor
  ret = CreateAclTensor(dbetaOutHostData, dbetaOutShape, &dbetaOutDeviceAddr, aclDataType::ACL_FLOAT, &dbetaOut);
  CHECK_RET(ret == ACL_SUCCESS, return ret);

  // 3. 调用CANN算子库API，需要修改为具体的API
  uint64_t workspaceSize = 0;
  aclOpExecutor* executor;
  // 调用aclnnGroupNormSwishGrad第一段接口
  ret = aclnnGroupNormSwishGradGetWorkspaceSize(dy, mean, rstd, x, gamma, beta, numGroups, dataFormatOptional, swishScale, dgammaIsRequire, dbetaIsRequire, dxOut, dgammaOut, dbetaOut, &workspaceSize, &executor);
  CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnGroupNormSwishGradGetWorkspaceSize 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aclnnGroupNormSwishGrad第二段接口
  ret = aclnnGroupNormSwishGrad(workspaceAddr, workspaceSize, executor, stream);
  CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnGroupNormSwishGrad 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侧内存上的结果拷贝至host侧，需要根据具体API的接口定义修改
  auto size = GetShapeSize(dxOutShape);
  ret = aclrtMemcpy(dxOutHostData.data(), dxOutHostData.size() * sizeof(dxOutHostData[0]), dxOutDeviceAddr, size * sizeof(float),
                    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("dxOutHostData[%ld] is: %f\n", i, dxOutHostData[i]);
  }

  size = GetShapeSize(dgammaOutShape);
  ret = aclrtMemcpy(dgammaOutHostData.data(), dgammaOutHostData.size() * sizeof(dgammaOutHostData[0]), dgammaOutDeviceAddr, size * sizeof(float),
                    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("dgammaOutHostData[%ld] is: %f\n", i, dgammaOutHostData[i]);
  }

  size = GetShapeSize(dbetaOutShape);
  ret = aclrtMemcpy(dbetaOutHostData.data(), dbetaOutHostData.size() * sizeof(dbetaOutHostData[0]), dbetaOutDeviceAddr, size * sizeof(float),
                    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("dbetaOutHostData[%ld] is: %f\n", i, dbetaOutHostData[i]);
  }

  // 6. 释放aclTensor和aclScalar，需要根据具体API的接口定义修改
  aclDestroyTensor(dy);
  aclDestroyTensor(mean);
  aclDestroyTensor(rstd);
  aclDestroyTensor(x);
  aclDestroyTensor(gamma);
  aclDestroyTensor(beta);
  aclDestroyTensor(dxOut);
  aclDestroyTensor(dgammaOut);
  aclDestroyTensor(dbetaOut);

  // 7. 释放device资源，需要根据具体API的接口定义修改
  aclrtFree(dyDeviceAddr);
  aclrtFree(meanDeviceAddr);
  aclrtFree(rstdDeviceAddr);
  aclrtFree(xDeviceAddr);
  aclrtFree(gammaDeviceAddr);
  aclrtFree(betaDeviceAddr);
  aclrtFree(dxOutDeviceAddr);
  aclrtFree(dgammaOutDeviceAddr);
  aclrtFree(dbetaOutDeviceAddr);

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