---
title: mul_complex32
description: "安全声明："
url: https://www.hiascend.com/document/detail/zh/canncommercial/latest/API/SiP/SIP_API_0078.html
sourcePath: /source/zh/canncommercial/900/API/SiP/SIP_API_0078.html
indexId: b1a6cfbbb32a683a5ca61c596bd459191d22eed1d01899d694a441ab4eaf63e155
---
# mul_complex32

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。

#### mul_complex32

mul_complex32算子的调用示例：
```
#include <iostream>
#include <vector>
#include <complex>
#include "asdsip.h"
#include "acl/acl.h"
#include "acl_meta.h"
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;
}
void printTensor(const std::complex<op::fp16_t> *tensorData, int64_t nums)
{
for (int64_t i = 0; i < nums; i++) {
std::cout << "(" << (float)tensorData[i].real() << "," << (float)tensorData[i].imag() << ")" << " ";
}
std::cout << std::endl;
}
int main(int argc, char **argv)
{
int 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);
int64_t n = 8;
int64_t vecSize = n;
std::vector<std::complex<op::fp16_t>> tensorInXData;
std::vector<std::complex<op::fp16_t>> tensorInYData;
tensorInXData.reserve(vecSize);
tensorInYData.reserve(vecSize);
for (int64_t i = 0; i < vecSize; i++) {
tensorInXData.push_back({(op::fp16_t)(9.0f + i), (op::fp16_t)(100.0f + i)});
}
for (int64_t i = 0; i < vecSize; i++) {
tensorInYData.push_back({(op::fp16_t)(22.0f + i), (op::fp16_t)(33.0f * (i + 1))});
}
std::vector<std::complex<op::fp16_t>> tensorOutZData(
vecSize, {(op::fp16_t)0.0f, (op::fp16_t)0.0f});
std::cout << "------- input X -------" << std::endl;
printTensor(tensorInXData.data(), vecSize);
std::cout << "------- input Y -------" << std::endl;
printTensor(tensorInYData.data(), vecSize);
std::vector<int64_t> xShape = {vecSize};
std::vector<int64_t> yShape = {vecSize};
std::vector<int64_t> zShape = {vecSize};
aclTensor *inputX = nullptr;
aclTensor *inputY = nullptr;
aclTensor *outputZ = nullptr;
void *inputXDeviceAddr = nullptr;
void *inputYDeviceAddr = nullptr;
void *outputZDeviceAddr = nullptr;
ret = CreateAclTensor(tensorInXData, xShape, &inputXDeviceAddr, aclDataType::ACL_COMPLEX32, &inputX);
CHECK_RET(ret == ::ACL_SUCCESS, return ret);
ret = CreateAclTensor(tensorInYData, yShape, &inputYDeviceAddr, aclDataType::ACL_COMPLEX32, &inputY);
CHECK_RET(ret == ::ACL_SUCCESS, return ret);
ret = CreateAclTensor(tensorOutZData, zShape, &outputZDeviceAddr, aclDataType::ACL_COMPLEX32, &outputZ);
CHECK_RET(ret == ::ACL_SUCCESS, return ret);
ASD_STATUS_CHECK(asdMul(n, inputX, inputY, outputZ, stream));
ret = aclrtSynchronizeStream(stream);
CHECK_RET(ret == ::ACL_SUCCESS, LOG_PRINT("aclrtSynchronizeStream failed. ERROR: %d\n", ret); return ret);
ret = aclrtMemcpy(tensorOutZData.data(),
vecSize * sizeof(std::complex<op::fp16_t>),
outputZDeviceAddr,
vecSize * sizeof(std::complex<op::fp16_t>),
ACL_MEMCPY_DEVICE_TO_HOST);
CHECK_RET(ret == ::ACL_SUCCESS, LOG_PRINT("copy z from device to host failed. ERROR: %d\n", ret); return ret);
std::cout << "------- output Z -------" << std::endl;
printTensor(tensorOutZData.data(), vecSize);
std::cout << "Execute successfully." << std::endl;
aclDestroyTensor(inputX);
aclDestroyTensor(inputY);
aclDestroyTensor(outputZ);
aclrtFree(inputXDeviceAddr);
aclrtFree(inputYDeviceAddr);
aclrtFree(outputZDeviceAddr);
aclrtDestroyStream(stream);
aclrtResetDevice(deviceId);
aclFinalize();
return 0;
}
```