- Function: Performs the addition calculation.
- Formulas:
aclnnAddV3 and aclnnInplaceAddV3 provide the same functionality. The differences are as follows. Select the appropriate operator based on your actual scenario.
- aclnnAddV3: You need to create an output tensor object to store the computation result.
- aclnnInplaceAddV3: You do not need to create an output tensor object. Instead, the computation result is directly stored in the memory of the input tensor.
Each operator is divided into [(../common/) You must call aclnnAddV3GetWorkspaceSize or aclnnInplaceAddV3GetWorkspaceSize to obtain the workspace size required for computation and the executor that contains the operator computation process, and then call aclnnAddV3 or aclnnInplaceAddV3 to perform computation.
[object Object][object Object][object Object][object Object]
Parameter description:
[object Object]- [object Object]Atlas training products[object Object] and [object Object]Atlas inference products[object Object]: The data type cannot be BFLOAT16.
Returns
[object Object]: status code. For details, see .The first-phase API implements input parameter validation. The following error codes may be returned.
[object Object]
Parameter description:
[object Object]- [object Object]Atlas training products[object Object] and [object Object]Atlas inference products[object Object]: The data type cannot be BFLOAT16.
Returns
[object Object]: status code. For details, see .The first-phase API implements input parameter validation. The following error codes may be returned.
[object Object]
- Deterministic computation:
- The default deterministic implementation is used in aclnnAddV3&aclnnInplaceAddV3.
The following example is for reference only. For details, see .