---
title: Asum
description: "安全声明："
url: https://www.hiascend.com/document/detail/zh/canncommercial/latest/API/SiP/SIP_API_0037.html
sourcePath: /source/zh/canncommercial/900/API/SiP/SIP_API_0037.html
indexId: e55f774efa42844b3858f46e3b13185c89a13f2879fcca22a16b4c91d0c8952455
---
# Asum

安全声明：

该样例旨在提供快速上手、开发和调试算子的最小化实现，其核心目标是使用最精简的代码展示算子的核心功能，而非提供生产级的安全保障。

不推荐用户直接将示例代码作为业务代码，若用户将示例代码应用在自身的真实业务场景中且发生了安全问题，则需用户自行承担。

#### asdBlasSasum

asdBlasSasum算子调用示例：

```
#include <iostream>
#include <vector>
#include "asdsip.h"
#include "acl/acl.h"
#include "utils/mem_base.h"
#include "acl_meta.h"
#include <string>
using namespace AsdSip;
#define ASD_STATUS_CHECK(err)                                                \
do {                                                                     \
AsdSip::AspbStatus err_ = (err);                                     \
if (err_ != AsdSip::ErrorType::ACL_SUCCESS) {                                      \
std::cout << "Execute failed." << std::endl;                     \
exit(-1);                                                        \
}                                                                    \
} while (0)
#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，acl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侧数据复制到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(int argc, char **argv)
{
int deviceId = 0;
// aclrtContext context;
aclrtStream stream;
auto ret = Init(deviceId, &stream);
CHECK_RET(ret == ::ACL_SUCCESS, LOG_PRINT("Init acl failed. ERROR: %d\n", ret); return ret);
int64_t n = 8;
int64_t incx = 1;
int64_t xSize = 8;
int64_t ySize = 1;
std::vector<float> tensorInXData;
tensorInXData.reserve(xSize);
for (int i = 0; i < xSize; i++) {
tensorInXData.push_back(1.0 + i);
}
std::cout << "------- input X -------" << std::endl;
for (int64_t i = 0; i < xSize; i++) {
std::cout << tensorInXData[i] << " ";
}
std::cout << std::endl;
std::vector<float> tensorInYData;
tensorInYData.reserve(ySize);
for (int i = 0; i < ySize; i++) {
tensorInYData.push_back(0.0);
}
std::vector<int64_t> xShape = {xSize};
std::vector<int64_t> yShape = {ySize};
aclTensor *inputX = nullptr;
aclTensor *inputY = nullptr;
void *inputXDeviceAddr = nullptr;
void *inputYDeviceAddr = nullptr;
ret = CreateAclTensor<float>(tensorInXData, xShape, &inputXDeviceAddr, aclDataType::ACL_FLOAT, &inputX);
CHECK_RET(ret == ::ACL_SUCCESS, return ret);
ret = CreateAclTensor<float>(tensorInYData, yShape, &inputYDeviceAddr, aclDataType::ACL_FLOAT, &inputY);
CHECK_RET(ret == ::ACL_SUCCESS, return ret);
asdBlasHandle handle;
asdBlasCreate(handle);
size_t lwork = 0;
void *buffer = nullptr;
asdBlasMakeAsumPlan(handle);
asdBlasGetWorkspaceSize(handle, lwork);
std::cout << "lwork = " << lwork << std::endl;
if (lwork > 0) {
ret = aclrtMalloc(&buffer, static_cast<int64_t>(lwork), ACL_MEM_MALLOC_HUGE_FIRST);
CHECK_RET(ret == ::ACL_SUCCESS, LOG_PRINT("allocate workspace failed. ERROR: %d\n", ret); return ret);
}
asdBlasSetWorkspace(handle, buffer);
asdBlasSetStream(handle, stream);
ASD_STATUS_CHECK(asdBlasSasum(handle, n, inputX, incx, inputY));
asdBlasSynchronize(handle);
asdBlasDestroy(handle);
ret = aclrtMemcpy(tensorInYData.data(),
ySize * sizeof(float),
inputYDeviceAddr,
ySize * 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);
std::cout << "------- result -------" << std::endl;
std::cout << tensorInYData[0] << std::endl;
std::cout << "Execute successfully." << std::endl;
aclDestroyTensor(inputX);
aclDestroyTensor(inputY);
aclrtFree(inputXDeviceAddr);
aclrtFree(inputYDeviceAddr);
aclrtDestroyStream(stream);
aclrtResetDevice(deviceId);
aclFinalize();
return 0;
}
```


#### asdBlasScasum

asdBlasScasum算子调用示例：

```
#include <iostream>
#include "asdsip.h"
#include "acl/acl.h"
#include "utils/mem_base.h"
#include "acl_meta.h"
#include <vector>
#include <string>
using namespace AsdSip;
#define ASD_STATUS_CHECK(err)                                                \
do {                                                                     \
AsdSip::AspbStatus err_ = (err);                                     \
if (err_ != AsdSip::ErrorType::ACL_SUCCESS) {                                      \
std::cout << "Execute failed." << std::endl; \
exit(-1);                                                        \
}                                                                    \
} while (0)
#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，acl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侧数据复制到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(int argc, char **argv)
{
int deviceId = 0;
// aclrtContext context;
aclrtStream stream;
auto ret = Init(deviceId, &stream);
CHECK_RET(ret == ::ACL_SUCCESS, LOG_PRINT("Init acl failed. ERROR: %d\n", ret); return ret);
int64_t n = 8;
int64_t incx = 1;
int64_t xSize = 8;
int64_t ySize = 1;
std::vector<std::complex<float>> tensorInXData;
tensorInXData.reserve(xSize);
for (int i = 0; i < xSize; i++) {
tensorInXData.push_back({(float)(1.0 + i), (float)(3.0 + i)});
}
std::cout << "------- input X -------" << std::endl;
for (int64_t i = 0; i < xSize; i++) {
std::cout << tensorInXData[i] << " ";
}
std::cout << std::endl;
std::vector<float> tensorInYData;
tensorInYData.reserve(ySize);
for (int i = 0; i < ySize; i++) {
tensorInYData.push_back(0.0);
}
std::vector<int64_t> xShape = {xSize};
std::vector<int64_t> yShape = {ySize};
aclTensor *inputX = nullptr;
aclTensor *inputY = nullptr;
void *inputXDeviceAddr = nullptr;
void *inputYDeviceAddr = nullptr;
ret = CreateAclTensor(tensorInXData, xShape, &inputXDeviceAddr, aclDataType::ACL_COMPLEX64, &inputX);
CHECK_RET(ret == ::ACL_SUCCESS, return ret);
ret = CreateAclTensor(tensorInYData, yShape, &inputYDeviceAddr, aclDataType::ACL_FLOAT, &inputY);
CHECK_RET(ret == ::ACL_SUCCESS, return ret);
asdBlasHandle handle;
asdBlasCreate(handle);
size_t lwork = 0;
void *buffer = nullptr;
asdBlasMakeAsumPlan(handle);
asdBlasGetWorkspaceSize(handle, lwork);
std::cout << "lwork = " << lwork << std::endl;
if (lwork > 0) {
ret = aclrtMalloc(&buffer, static_cast<int64_t>(lwork), ACL_MEM_MALLOC_HUGE_FIRST);
CHECK_RET(ret == ::ACL_SUCCESS, LOG_PRINT("allocate workspace failed. ERROR: %d\n", ret); return ret);
}
asdBlasSetWorkspace(handle, buffer);
asdBlasSetStream(handle, stream);
ASD_STATUS_CHECK(asdBlasScasum(handle, n, inputX, incx, inputY));
asdBlasSynchronize(handle);
asdBlasDestroy(handle);
ret = aclrtMemcpy(tensorInYData.data(),
ySize * sizeof(float),
inputYDeviceAddr,
ySize * 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);
std::cout << "------- result -------" << std::endl;
std::cout << tensorInYData[0] << std::endl;
std::cout << "Execute successfully." << std::endl;
aclDestroyTensor(inputX);
aclDestroyTensor(inputY);
aclrtFree(inputXDeviceAddr);
aclrtFree(inputYDeviceAddr);
aclrtDestroyStream(stream);
aclrtResetDevice(deviceId);
aclFinalize();
return 0;
}
```