- Description: Performs subtraction.
- Formula:
Each operator has calls. First, [object Object] is called to obtain the workspace size required for computation and the executor that contains the operator computation process. Then, [object Object] is called to perform computation.
[object Object][object Object]
Parameters:
[object Object](aclTensor *, compute input): input[object Object]in the formula. The data type must meet the with other. The shape must meet the with[object Object]. The number of dimensions cannot exceed 8. are supported. The can be ND.- [object Object]Atlas A2 training products/Atlas A2 inference products[object Object], [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be INT8, UINT8, INT16, INT32, INT64, FLOAT16, FLOAT, DOUBLE, COMPLEX64, COMPLEX128, or BFLOAT16.
- [object Object]Atlas training products[object Object]: The data type can be INT8, UINT8, INT16, INT32, INT64, FLOAT16, FLOAT, DOUBLE, COMPLEX64, or COMPLEX128.
[object Object](aclTensor *, compute input): 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]. The number of dimensions cannot exceed 8. are supported. The can be ND.- [object Object]Atlas A2 training products/Atlas A2 inference products[object Object], [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be INT8, UINT8, INT16, INT32, INT64, FLOAT16, FLOAT, DOUBLE, COMPLEX64, COMPLEX128, or BFLOAT16.
- [object Object]Atlas training products[object Object]: The data type can be INT8, UINT8, INT16, INT32, INT64, FLOAT16, FLOAT, DOUBLE, COMPLEX64, or COMPLEX128.
[object Object](aclScalar*, compute input):[object Object]in the formula. The data type must be convertible to that after deduction between[object Object]and[object Object].- [object Object]Atlas A2 training products/Atlas A2 inference products[object Object], [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be INT8, UINT8, INT16, INT32, INT64, FLOAT16, FLOAT, DOUBLE, COMPLEX64, COMPLEX128, or BFLOAT16.
- [object Object]Atlas training products[object Object]: The data type can be INT8, UINT8, INT16, INT32, INT64, FLOAT16, FLOAT, DOUBLE, COMPLEX64, or COMPLEX128.
[object Object](aclTensor*, compute output):[object Object]in the formula. The data type must be convertible from that after deduction between[object Object]and[object Object](see ). The shape must be the shape after[object Object]and[object Object]are broadcast, and the number of dimensions cannot exceed 8. are supported. The can be ND.- [object Object]Atlas A2 training products/Atlas A2 inference products[object Object], [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be INT8, UINT8, INT16, INT32, INT64, FLOAT16, FLOAT, DOUBLE, COMPLEX64, COMPLEX128, or BFLOAT16.
- [object Object]Atlas training products[object Object]: The data type can be INT8, UINT8, INT16, INT32, INT64, FLOAT16, FLOAT, DOUBLE, COMPLEX64, or COMPLEX128.
[object Object](uint64_t*, output): size of the workspace to be allocated on the device.[object Object](aclOpExecutor**, output): operator executor, containing the operator computation process.
Returns:
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 calling[object Object].[object Object](aclOpExecutor*, input): operator executor, containing the operator computation process.[object Object](aclrtStream, input): stream for executing the task.
Returns:
- Deterministic compute:
[object Object]defaults to a deterministic implementation.
The following example is for reference only. For details, see .