ComplexMatDot
asdBlasComplexMatDot算子调用示例:
#include <iostream>
#include <vector>
#include "asdsip.h"
#include <complex>
#include "acl/acl.h"
#include "acl_meta.h"
using namespace AsdSip;
#define ASD_STATUS_CHECK(err) \
do { \
AsdSip::AspbStatus err_ = (err); \
if (err_ != AsdSip::NO_ERROR) { \
std::cout << "Execute failed." << std::endl; \
exit(-1); \
} else { \
std::cout << "Execute successfully." << std::endl; \
} \
} 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<float> *tensorData, int64_t rows, int64_t cols)
{
for (int64_t i = 0; i < rows; i++) {
for (int64_t j = 0; j < cols; j++) {
std::cout << tensorData[i * cols + j] << " ";
}
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 m = 3;
int64_t n = 2;
int64_t matSize = m * n;
std::vector<std::complex<float>> tensorInMatXData;
tensorInMatXData.reserve(matSize);
for (int64_t i = 0; i < m; i++) {
for (int64_t j = 0; j < n; j++) {
tensorInMatXData[n * i + j] = {(float)(1.0 + i), (float)(1.0 + i)};
}
}
std::vector<std::complex<float>> tensorInMatYData;
tensorInMatYData.reserve(matSize);
for (int64_t i = 0; i < m; i++) {
for (int64_t j = 0; j < n; j++) {
tensorInMatYData[n * i + j] = {(float)(2.0 + i), 3.0};
}
}
std::cout << "------- input matX -------" << std::endl;
printTensor(tensorInMatXData.data(), m, n);
std::cout << "------- input matY -------" << std::endl;
printTensor(tensorInMatYData.data(), m, n);
std::vector<int64_t> xShape = {matSize};
std::vector<int64_t> yShape = {matSize};
aclTensor *inputX = nullptr;
aclTensor *inputY = nullptr;
void *inputXDeviceAddr = nullptr;
void *inputYDeviceAddr = nullptr;
ret = CreateAclTensor(tensorInMatXData, xShape, &inputXDeviceAddr, aclDataType::ACL_COMPLEX64, &inputX);
CHECK_RET(ret == ACL_SUCCESS, return ret);
ret = CreateAclTensor(tensorInMatYData, yShape, &inputYDeviceAddr, aclDataType::ACL_COMPLEX64, &inputY);
CHECK_RET(ret == ACL_SUCCESS, return ret);
asdBlasHandle handle;
asdBlasCreate(handle);
size_t lwork = 0;
void *buffer = nullptr;
asdBlasMakeComplexMatDotPlan(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(asdBlasComplexMatDot(handle, m, n, inputX, inputY, inputX));
asdBlasSynchronize(handle);
asdBlasDestroy(handle);
ret = aclrtMemcpy(tensorInMatXData.data(),
matSize * sizeof(std::complex<float>),
inputXDeviceAddr,
matSize * sizeof(std::complex<float>),
ACL_MEMCPY_DEVICE_TO_HOST);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("copy tensor x from device to host failed. ERROR: %d\n", ret); return ret);
std::cout << "------- matX -------" << std::endl;
printTensor(tensorInMatXData.data(), m, n);
aclDestroyTensor(inputX);
aclDestroyTensor(inputY);
aclrtFree(inputXDeviceAddr);
aclrtFree(inputYDeviceAddr);
aclrtDestroyStream(stream);
aclrtResetDevice(deviceId);
aclFinalize();
return 0;
}父主题: BLAS