- Description: Performs element-wise multiplication of
[object Object]and[object Object], multiplies the result by the scalar[object Object], and then performs element-wise addition of this scaled result with the input[object Object]or[object Object]. - Formula:
When
[object Object]is used,[object Object]and[object Object]in the formula correspond to those in the first-phase API. When[object Object]is used, both[object Object]and[object Object]in the formula correspond to[object Object]in the first-phase API.
[object Object]and[object Object]implement the same function in different ways. Select a proper operator based on your requirements.[object Object]: An output tensor object needs to be created to store the computation result.[object Object]: No output tensor object needs to be created, and the computation result is written in place to the input tensor's memory.
Each operator has calls. First,
[object Object]or[object Object]is called to obtain the workspace size required for computation and the executor covering the operator computation process. Then,[object Object]or[object Object]is called to perform computation.[object Object][object Object][object Object][object Object]
Parameters:
[object Object]- [object Object]Atlas training products[object Object]: The data type cannot be BFLOAT16.
Returns:
[object Object]: status code. For details, see .The first-phase API implements input parameter verification. The following errors may be thrown.
[object Object]
Parameters:
[object Object]- [object Object]Atlas training products[object Object]: The data type cannot be BFLOAT16.
Returns:
[object Object]: status code. For details, see .The first-phase API implements input parameter verification. The following errors may be thrown.
[object Object]
- Deterministic computation:
[object Object]and[object Object]each default to a deterministic implementation.
The following example is for reference only. For details, see .
aclnnAddcmul
aclnnInplaceAddcmul