- Function: Checks whether the value of an element in selfRef is not equal to the value of other.
- Formula:
[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 stored in the memory of the input tensor.
- Each operator has calls. First,
[object Object]or[object Object]is called to obtain input parameters and compute the required workspace size based on the computation process. Then,[object Object]or[object Object]is called to perform computation.
Parameter description:
[object Object][object Object]Atlas A2 training products/Atlas A2 inference products[object Object] and [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]:
- self and other do not support UINT64.
- out does not support UINT64, UINT32, or UINT16.
[object Object]Atlas training products[object Object]:
- self and other do not support BFLOAT16 or UINT64.
- out does not support BFLOAT16, UINT64, UINT32, or UINT16.
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 A2 training products/Atlas A2 inference products[object Object] and [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: UINT64 is not supported.
[object Object]Atlas training products[object Object]: BFLOAT16 and UINT64 are not supported.
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 computing:
[object Object]defaults to a deterministic implementation.
The following example is for reference only. For details, see .
The following is an example of calling the aclnnNeScalar&aclnnInplaceNeScalar API: