- Operator function: Computes whether the element value in
[object Object]([object Object]) is not equal to that of[object Object]. - 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.[object Object][object Object][object Object][object Object]
Parameters:
[object Object](aclTensor*, computation input):[object Object]in the formula, which is an aclTensor on the device. The data type must meet the data type deduction rules with[object Object](see ). The shape must meet the with[object Object]. The shape dimensions cannot exceed 8. are supported. The can be ND. UINT64.- [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]: The data type can be DOUBLE, FLOAT16, FLOAT, BFLOAT16, INT64, INT32, INT8, UINT8, BOOL, INT16, COMPLEX64, or COMPLEX128.
- [object Object]Atlas training products[object Object]: The data type can be DOUBLE, FLOAT16, FLOAT, INT64, INT32, INT8, UINT8, BOOL, INT16, COMPLEX64, or COMPLEX128.
[object Object](aclTensor*, computation input):[object Object]in the formula, which is an aclTensor on the device. The data type must meet the data type deduction rules with[object Object](see ). The shape must meet the with[object Object]. The shape dimensions cannot exceed 8. are supported. The can be ND.- [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]: The data type can be DOUBLE, FLOAT16, FLOAT, BFLOAT16, INT64, INT32, INT8, UINT8, BOOL, INT16, COMPLEX64, or COMPLEX128.
- [object Object]Atlas training products[object Object]: The data type can be DOUBLE, FLOAT16, FLOAT, INT64, INT32, INT8, UINT8, BOOL, INT16, COMPLEX64, or COMPLEX128.
[object Object](aclTensor*, computation output):[object Object]in the formula, which is an aclTensor on the device. The data type must be convertible to BOOL (see ). The shape must be the same as the shape after[object Object]and[object Object]are broadcast (see ). The shape dimension cannot exceed 8. are supported. The can be ND.- [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]: The data type can be DOUBLE, FLOAT16, FLOAT, BFLOAT16, INT64, INT32, INT8, UINT8, BOOL, INT16, COMPLEX64, or COMPLEX128.
- [object Object]Atlas training products[object Object]: The data type can be DOUBLE, FLOAT16, FLOAT, INT64, INT32, INT8, UINT8, BOOL, INT16, COMPLEX64, or COMPLEX128.
[object Object](uint64_t*, output): size of the workspace to be allocated on the device.[object Object](aclOpExecutor**, output): operator executor, covering the operator computation process.
Returns:
[object Object]: status code. For details, see .[object Object]
- Parameters:
[object Object](void*, input): address of the workspace to be allocated on the device.[object Object](uint64_t, input): size of the workspace to be allocated on the device, which is obtained by the first-phase API[object Object].[object Object](aclOpExecutor*, input): operator executor, containing the operator computation process.[object Object](aclrtStream, input): stream for executing the task.
- Returns:
[object Object]: status code. For details, see .
Parameters:
[object Object](aclTensor*, computation input/output):[object Object]in the formula. The data type must meet the type deduction rules (see ) with[object Object]. The shape must meet the with[object Object]. are supported. The can be ND.- [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]: The data type can be DOUBLE, FLOAT16, FLOAT, BFLOAT16, INT64, INT32, INT8, UINT8, BOOL, INT16, COMPLEX64, or COMPLEX128.
- [object Object]Atlas training products[object Object]: The data type can be DOUBLE, FLOAT16, FLOAT, INT64, INT32, INT8, UINT8, BOOL, INT16, COMPLEX64, or COMPLEX128.
[object Object](aclTensor*, computation input):[object Object]in the formula The data type must meet the type deduction rules (see ) with[object Object]. The shape must meet the with[object Object]. are supported. The can be ND.- [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]: The data type can be DOUBLE, FLOAT16, FLOAT, BFLOAT16, INT64, INT32, INT8, UINT8, BOOL, INT16, COMPLEX64, or COMPLEX128.
- [object Object]Atlas training products[object Object]: The data type can be DOUBLE, FLOAT16, FLOAT, INT64, INT32, INT8, UINT8, BOOL, INT16, COMPLEX64, or COMPLEX128.
[object Object](uint64_t*, output): size of the workspace to be allocated on the device.[object Object](aclOpExecutor**, output): operator executor, covering the operator computation process.
[object Object]
- Parameters:
[object Object](void*, input): address of the workspace to be allocated on the device.[object Object](uint64_t, input): size of the workspace to be allocated on the device, which is obtained by the first-phase API[object Object].[object Object](aclOpExecutor*, input): operator executor, containing the operator computation process.[object Object](aclrtStream, input): stream for executing the task.
- Returns:
[object Object]: status code. For details, see .
- Deterministic computing:
[object Object]defaults to a deterministic implementation.
The following example is for reference only. For details, see .
[object Object]