aclnnAdd&aclnnInplaceAdd
Applicable Products
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Function
Description: Performs addition computation.
Formula:
Function Prototype
aclnnAdd and aclnnInplaceAdd implement the same function. The differences in usage are as follows. Select the appropriate operator based on your actual scenario.
aclnnAdd: Create a new output tensor object to store the computation result.
aclnnInplaceAdd: No need to create a new output tensor object. The computation result is stored directly in the memory of the input tensor.
Each operator uses the two-phase API. You must first call the "aclnnAddGetWorkspaceSize" or "aclnnInplaceAddGetWorkspaceSize" API to obtain the workspace size required for computation and the executor that encapsulates the operator computation process, and then call the "aclnnAdd" or "aclnnInplaceAdd" API to perform the computation.
aclnnStatus aclnnAddGetWorkspaceSize( const aclTensor* self, const aclTensor* other, const aclScalar* alpha, aclTensor* out, uint64_t* workspaceSize, aclOpExecutor** executor)aclnnStatus aclnnAdd( void* workspace, uint64_t workspaceSize, aclOpExecutor* executor, aclrtStream stream)aclnnStatus aclnnInplaceAddGetWorkspaceSize( const aclTensor* selfRef, const aclTensor* other, const aclScalar* alpha, uint64_t* workspaceSize, aclOpExecutor** executor)aclnnStatus aclnnInplaceAdd( void* workspace, uint64_t workspaceSize, aclOpExecutor* executor, aclrtStream stream)
aclnnAddGetWorkspaceSize
Parameters:
Parameter Input/Output Description Instruction Data Type Data Format Dimensions (shape) Non-contiguous Tensor self Input Input self in the formula. FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, COMPLEX64, BFLOAT16 ND No more than eight dimensions. √ other Input. Input "other" in the formula. FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, COMPLEX64, BFLOAT16 ND No more than 8 dimensions. √ alpha Input The alpha in the formula. The data type must be convertible to the data type derived from self and other. FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, COMPLEX64, BFLOAT16 - - - out Output The out in the formula. FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, COMPLEX64, BFLOAT16 ND No more than 8 dimensions. √ workspaceSize Output Returns the workspace size to be requested on the Device side. - - - - - executor Output Returns the operator executor, which contains the operator computation flow. - - - - - Atlas training products : BFLOAT16 data type is not supported.
Return value
aclnnStatus: return code. For details, see aclnn Return Codes.
The first-phase API performs input parameter validation and returns an error in the following scenarios:
Return Value Error Code Description ACLNN_ERR_PARAM_NULLPTR 161001 The input self, other, alpha, or out is a null pointer. ACLNN_ERR_PARAM_INVALID 161002 The data types of self and other are not within the supported range. Data type deduction cannot be performed between self and other. The deduced data type cannot be converted to the specified output type of out. Broadcast cannot be performed on the shapes of self and other. Alpha cannot be converted to the data type derived from self and other. The shape of out is not the shape after broadcasting self and other. The dimension of self, other, or out is greater than 8.
aclnnAdd
Parameters:
Parameter Input/Output Description workspace Input Specifies the memory address of the workspace applied on the device side. workspaceSize Input Specifies the size of the workspace applied on the device side, obtained from the first-phase API aclnnAddGetWorkspaceSize. executor Input Operator executor that contains the operator computation process. stream Input Specifies the stream for task execution. Return value
aclnnStatus: return code. For details, see aclnn Return Codes.
aclnnInplaceAddGetWorkspaceSize
Parameters:
Atlas training products : The BFLOAT16 data type is not supported.
Return value
aclnnStatus: return code. For details, see aclnn Return Codes.
The first-phase API performs input parameter validation and returns an error in the following scenarios:
Return Value Error Code Description ACLNN_ERR_PARAM_NULLPTR 161001 The passed selfRef, other, or alpha is a null pointer. ACLNN_ERR_PARAM_INVALID 161002 The data types of selfRef and other are not within the supported range. Data type deduction cannot be performed between selfRef and other. The deduced data type cannot be converted to the data type of selfRef. The shapes of selfRef and other cannot be broadcast. The broadcast shape is not equal to the shape of selfRef. alpha cannot be converted to the data type deduced from selfRef and other. The dimension of selfRef or other is greater than 8.
aclnnInplaceAdd
Parameters:
Parameter Input/Output Description workspace Input Address of the workspace applied for on the Device side. workspaceSize Input Size of the workspace applied for on the Device side, obtained by the first-phase API aclnnInplaceAddGetWorkspaceSize. executor Input Operator executor that contains the operator computation flow. stream Input Specifies the stream for task execution. Return value
aclnnStatus: return code. For details, see aclnn Return Codes.
Constraints
Deterministic computation:
- aclnnAdd&aclnnInplaceAdd defaults to a deterministic implementation.
Example
The following provides example code for reference only. For details about compilation and running, see Compile and Run Samples.
#include <iostream>
#include <vector>
#include "acl/acl.h"
#include "aclnnop/aclnn_add.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) {
// Boilerplate for resource initialization.
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);
// Call aclrtMalloc to allocate device memory.
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);
// Call aclrtMemcpy to copy host data to device memory.
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);
// Compute the strides of a contiguous tensor.
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];
}
// Call the aclCreateTensor API to create an 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. (Boilerplate) Initialize the device/stream. See the ACL API manual.
// Enter the deviceId based on your actual device.
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. Construct the inputs and outputs. Custom construction is required based on the API.
std::vector<int64_t> selfShape = {4, 2};
std::vector<int64_t> otherShape = {4, 2};
std::vector<int64_t> outShape = {4, 2};
void* selfDeviceAddr = nullptr;
void* otherDeviceAddr = nullptr;
void* outDeviceAddr = nullptr;
aclTensor* self = nullptr;
aclTensor* other = nullptr;
aclScalar* alpha = nullptr;
aclTensor* out = nullptr;
std::vector<float> selfHostData = {0, 1, 2, 3, 4, 5, 6, 7};
std::vector<float> otherHostData = {1, 1, 1, 2, 2, 2, 3, 3};
std::vector<float> outHostData(8, 0);
float alphaValue = 1.2f;
// Create the self aclTensor.
ret = CreateAclTensor(selfHostData, selfShape, &selfDeviceAddr, aclDataType::ACL_FLOAT, &self);
CHECK_RET(ret == ACL_SUCCESS, return ret);
// Create the other aclTensor.
ret = CreateAclTensor(otherHostData, otherShape, &otherDeviceAddr, aclDataType::ACL_FLOAT, &other);
CHECK_RET(ret == ACL_SUCCESS, return ret);
// Create the alpha aclScalar.
alpha = aclCreateScalar(&alphaValue, aclDataType::ACL_FLOAT);
CHECK_RET(alpha != nullptr, return ret);
// Create the out aclTensor.
ret = CreateAclTensor(outHostData, outShape, &outDeviceAddr, aclDataType::ACL_FLOAT, &out);
CHECK_RET(ret == ACL_SUCCESS, return ret);
uint64_t workspaceSize = 0;
aclOpExecutor* executor;
// Example of calling the aclnnAdd API.
// 3. Call the CANN operator library API.
// Call the aclnnAdd first-phase API.
ret = aclnnAddGetWorkspaceSize(self, other, alpha, out, &workspaceSize, &executor);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnAddGetWorkspaceSize failed. ERROR: %d\n", ret); return ret);
// Apply for device memory based on the workspaceSize calculated by the first-phase API.
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);
}
// Call the aclnnAdd second-phase API.
ret = aclnnAdd(workspaceAddr, workspaceSize, executor, stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnAdd failed. ERROR: %d\n", ret); return ret);
// 4. (Boilerplate) Synchronously wait for task execution to complete.
ret = aclrtSynchronizeStream(stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSynchronizeStream failed. ERROR: %d\n", ret); return ret);
// 5. Obtain the output value and copy the result from the device memory to the host memory. Modify based on the specific API definition.
auto size = GetShapeSize(outShape);
std::vector<float> resultData(size, 0);
ret = aclrtMemcpy(resultData.data(), resultData.size() * sizeof(resultData[0]), outDeviceAddr,
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]);
}
// Example of calling the aclnnInplaceAdd API
// 3. Call the CANN operator library API.
LOG_PRINT("\ntest aclnnInplaceAdd\n");
// Call the first-phase API of aclnnInplaceAdd.
ret = aclnnInplaceAddGetWorkspaceSize(self, other, alpha, &workspaceSize, &executor);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnInplaceAddGetWorkspaceSize failed. ERROR: %d\n", ret); return ret);
// Apply for device memory based on the workspaceSize calculated by the first-phase API.
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);
}
// Call the second-phase API of aclnnInplaceAdd.
ret = aclnnInplaceAdd(workspaceAddr, workspaceSize, executor, stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnInplaceAdd failed. ERROR: %d\n", ret); return ret);
// 4. (Boilerplate) Synchronously wait for the task to complete.
ret = aclrtSynchronizeStream(stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSynchronizeStream failed. ERROR: %d\n", ret); return ret);
// 5. Obtain the output value and copy the result from the device memory to the host memory. Modify based on the specific API definition.
ret = aclrtMemcpy(resultData.data(), resultData.size() * sizeof(resultData[0]), selfDeviceAddr,
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. Release aclTensor and aclScalar. Modify based on the specific API definition.
aclDestroyTensor(self);
aclDestroyTensor(other);
aclDestroyScalar(alpha);
aclDestroyTensor(out);
// 7. Release device resources. Modify based on the specific API definition.
aclrtFree(selfDeviceAddr);
aclrtFree(otherDeviceAddr);
aclrtFree(outDeviceAddr);
if (workspaceSize > 0) {
aclrtFree(workspaceAddr);
}
aclrtDestroyStream(stream);
aclrtResetDevice(deviceId);
aclFinalize();
return 0;
}