/**
 * 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.
 */
/*!
 * \file test_aclnn_scatter_pa_cache.cpp
 * \brief
 */

#include <iostream>
#include <vector>
#include "acl/acl.h"
#include "aclnnop/aclnn_scatter_pa_cache.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
// 根据自己的实际device填写deviceId
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
std::vector<int64_t> keyShape = {2, 2, 3, 7};
std::vector<int64_t> keyCacheShape = {2, 2, 1, 7};
std::vector<int64_t> slotMappingShape = {2, 3};

std::vector<int64_t> compressLensShape = {2, 3};
std::vector<int64_t> compressSeqOffsetShape = {6};
std::vector<int64_t> seqLensShape = {2};
void* keyDeviceAddr = nullptr;
void* slotMappingDeviceAddr = nullptr;
void* keyCacheDeviceAddr = nullptr;
void* compressLensDeviceAddr = nullptr;
void* compressSeqOffsetDeviceAddr = nullptr;
void* seqLensDeviceAddr = nullptr;

aclTensor* key = nullptr;
aclTensor* slotMapping = nullptr;
aclTensor* keyCache = nullptr;
aclTensor* compressLens = nullptr;
aclTensor* compressSeqOffset = nullptr;
aclTensor* seqLens = nullptr;
char* cacheMode = const_cast<char*>("Norm");

std::vector<float> hostKey = {1};
std::vector<int32_t> hostSlotMapping = {0, 3, 6, 9, 12, 15};
std::vector<float> hostKeyCacheRef = {1};
std::vector<int32_t> hostCompressLens = {1, 0, 0, 0, 1, 0};
std::vector<int32_t> hostCompressSeqOffset = {0, 0, 1, 0, 1, 1};
std::vector<int32_t> hostSeqLens = {2, 1};

// 创建key aclTensor
ret = CreateAclTensor(hostKey, keyShape, &keyDeviceAddr, aclDataType::ACL_FLOAT, &key);
CHECK_RET(ret == ACL_SUCCESS, return ret);
// 创建slotMappitng aclTensor
ret = CreateAclTensor(hostSlotMapping, slotMappingShape, &slotMappingDeviceAddr, aclDataType::ACL_INT32, &slotMapping);
CHECK_RET(ret == ACL_SUCCESS, return ret);
// 创建keyCache aclTensor
ret = CreateAclTensor(hostKeyCacheRef, keyCacheShape, &keyCacheDeviceAddr, aclDataType::ACL_FLOAT, &keyCache);
CHECK_RET(ret == ACL_SUCCESS, return ret);
// 创建compressLens aclTensor
ret = CreateAclTensor(hostCompressLens, compressLensShape, &compressLensDeviceAddr, aclDataType::ACL_INT32, &compressLens);
CHECK_RET(ret == ACL_SUCCESS, return ret);
// 创建compressSeqOffset aclTensor
ret = CreateAclTensor(hostCompressSeqOffset, compressSeqOffsetShape, &compressSeqOffsetDeviceAddr, aclDataType::ACL_INT32, &compressSeqOffset);
CHECK_RET(ret == ACL_SUCCESS, return ret);
// 创建seqLens aclTensor
ret = CreateAclTensor(hostSeqLens, seqLensShape, &seqLensDeviceAddr, aclDataType::ACL_INT32, &seqLens);
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;
// 调用aclnnScatterPaCache第一段接口
ret = aclnnScatterPaCacheGetWorkspaceSize(key, keyCache, slotMapping, compressLens, compressSeqOffset, seqLens, cacheMode, &workspaceSize, &executor);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnScatterPaCacheGetWorkspaceSize 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aclnnScatterPaCache第二段接口
ret = aclnnScatterPaCache(workspaceAddr, workspaceSize, executor, stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnScatterPaCache 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(keyShape);
std::vector<float> resultData(size, 0);
ret = aclrtMemcpy(resultData.data(), resultData.size() * sizeof(resultData[0]), keyDeviceAddr,
                    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("result[%ld] is: %f\n", i, resultData[i]);
}

// 6. 释放aclTensor和aclScalar，需要根据具体API的接口定义修改
aclDestroyTensor(key);
aclDestroyTensor(slotMapping);
aclDestroyTensor(keyCache);
aclDestroyTensor(compressLens);
aclDestroyTensor(compressSeqOffset);
aclDestroyTensor(seqLens);
// 7. 释放device资源，需要根据具体API的接口定义参数
aclrtFree(keyDeviceAddr);
aclrtFree(slotMappingDeviceAddr);
aclrtFree(keyCacheDeviceAddr);
aclrtFree(compressLensDeviceAddr);
aclrtFree(compressSeqOffsetDeviceAddr);
aclrtFree(seqLensDeviceAddr);
if (workspaceSize > 0) {
    aclrtFree(workspaceAddr);
}
aclrtDestroyStream(stream);
aclrtResetDevice(deviceId);
aclFinalize();
return 0;
}