aclnnInplaceOne
产品支持情况
| 产品 | 是否支持 |
|---|---|
| Atlas A2 训练系列产品/Atlas A2 推理系列产品 | √ |
功能说明
- 算子功能: 创建一个与给定张量形状相同且所有元素都为 1 的新张量。
函数原型
每个算子分为两段式接口,必须先调用“aclnnInplaceOneGetWorkspaceSize”接口获取计算所需workspace大小以及包含了算子计算流程的执行器,再调用“aclnnInplaceOne”接口执行计算。
aclnnStatus aclnnInplaceOneGetWorkspaceSize(
const aclTensor *self,
uint64_t *workspaceSize,
aclOpExecutor **executor)
aclnnStatus aclnnInplaceOne(
void *workspace,
uint64_t workspaceSize,
aclOpExecutor *executor,
const aclrtStream stream)
aclnnInplaceOneGetWorkspaceSize
-
参数说明:
参数名 输入/输出 描述 使用说明 数据类型 数据格式 维度(shape) 非连续Tensor self 输入/输出 输入/输出张量,数据类型和数据格式在支持的范围之内。 无 FLOAT16、FLOAT32、INT32、INT8、UINT8、BF16、BOOL ND 0-8 √ workspaceSize 输出 返回需要在Device侧申请的workspace大小。 - - - - - executor 输出 返回op执行器,包含了算子计算流程。 - - - - - -
返回值:
aclnnStatus:返回状态码,具体参见aclnn返回码。
第一段接口会完成入参校验,出现以下场景时报错:
返回码 错误码 描述 ACLNN_ERR_PARAM_NULLPTR 161001 传入的tensor是空指针。 ACLNN_ERR_PARAM_INVALID 161002 self的数据类型和数据格式不在支持的范围之内。 self的数据维度超过了8维。 self的数据形状不一致。
aclnnInplaceOne
-
参数说明:
参数名 输入/输出 描述 workspace 输入 在Device侧申请的workspace内存地址。 workspaceSize 输入 在Device侧申请的workspace大小,由第一段接口aclnnInplaceOneGetWorkspaceSize获取。 executor 输入 op执行器,包含了算子计算流程。 stream 输入 指定执行任务的Stream。 -
返回值:
aclnnStatus:返回状态码,具体参见aclnn返回码。
调用说明
| 调用方式 | 样例代码 | 说明 |
|---|---|---|
| aclnn接口 | test_ones_like | 通过[aclnnInplaceOne]接口方式调用ones_like算子。 |
约束说明
无
调用示例
示例代码如下,仅供参考,具体编译和执行过程请参考编译与运行样例。
/**
* This program is free software, you can redistribute it and/or modify it.
* 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 "acl/acl.h"
#include "aclnn_ones.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;
}
void PrintOutResult(std::vector<int64_t>& shape, void** deviceAddr)
{
auto size = GetShapeSize(shape);
std::vector<float> resultData(size, 0);
auto ret = aclrtMemcpy(
resultData.data(), resultData.size() * sizeof(resultData[0]), *deviceAddr, 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);
for (int64_t i = 0; i < size; i++) {
if(resultData[i] != 1.f) {
LOG_PRINT("error result[%ld] is: %f\n", i, resultData[i]);
break;
}
}
}
int Init(int32_t deviceId, aclrtStream* stream)
{
// 固定写法,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);
// 2. 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);
// 3. 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. 调用acl进行device/stream初始化
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
aclTensor* out = nullptr;
void* outDeviceAddr = nullptr;
std::vector<int64_t> outShape = {32, 4, 4, 4};
std::vector<float> outHostData(2048, 1);
ret = CreateAclTensor(outHostData, outShape, &outDeviceAddr, aclDataType::ACL_FLOAT, &out);
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;
// 4. 调用aclnnOnesLike第一段接口
ret = aclnnInplaceOneGetWorkspaceSize(out, &workspaceSize, &executor);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnInplaceOneGetWorkspaceSize 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 > static_cast<uint64_t>(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);
}
// 5. 调用aclnnOnesLike第二段接口
ret = aclnnInplaceOne(workspaceAddr, workspaceSize, executor, stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnInplaceOne failed. ERROR: %d\n", ret); return ret);
// 6. (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
PrintOutResult(outShape, &outDeviceAddr);
// 7. 释放aclTensor,需要根据具体API的接口定义修改
aclDestroyTensor(out);
// 8. 释放device资源
aclrtFree(outDeviceAddr);
if (workspaceSize > static_cast<uint64_t>(0)) {
aclrtFree(workspaceAddr);
}
aclrtDestroyStream(stream);
aclrtResetDevice(deviceId);
// 9. acl去初始化
aclFinalize();
return 0;
}