Description: Returns a 2D tensor with 1s on the diagonal and 0s elsewhere.
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](int64_t, compute input): the first dimension, which is an integer on the host. The value must be greater than or equal to 0.[object Object](int64_t, compute input): the second dimension, which is an integer on the host. The value must be greater than or equal to 0.[object Object](aclTensor*, compute output): output tensor, which is an aclTensor on the device. are supported. The can be ND. Only two dimensions are supported. The shape must be (n, m).- [object Object]Atlas training products[object Object] and [object Object]Atlas inference products[object Object]: The data type can be FLOAT16, FLOAT32, INT32, INT16, INT8, UINT8, INT64, or BOOL.
- [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 FLOAT16, FLOAT32, INT32, INT16, INT8, UINT8, INT64, BOOL, or BFLOAT16.
[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:
[object Object]
Parameters:
[object Object](void*, input): memory 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 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:
- Deterministic computation:
[object Object]defaults to a deterministic implementation.
The following example is for reference only. For details, see .
[object Object]