- Description: Computes the result of self * log(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.[object Object][object Object][object Object][object Object]
Parameters
[object Object](aclTensor*, compute input): input[object Object]in the formula,[object Object]on the device. The data type must meet the with[object Object]. The shape must meet the with[object Object]. are supported. The can be ND.- [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be FLOAT, FLOAT16, INT32, INT64, INT16, INT8, UINT8, BOOL, or BFLOAT16.
[object Object](aclTensor*, compute input): input[object Object]in the formula,[object Object]on the device. The data type must meet the with[object Object]. The shape must meet the with[object Object]. are supported. The can be ND.- [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be FLOAT, FLOAT16, INT32, INT64, INT16, INT8, UINT8, BOOL, or BFLOAT16.
[object Object](aclTensor *, compute output):[object Object]in the formula,[object Object]on the device. The shape must be that after broadcasting between[object Object]and[object Object]. are supported. The can be ND.- [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be FLOAT, FLOAT16, INT32, INT64, INT16, INT8, UINT8, 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]: status code. For details, see .The first-phase API implements input parameter verification. The following errors may be thrown:
[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 calling[object Object].[object Object](aclOpExecutor *, input): operator executor, containing the operator computation process.[object Object](aclrtStream, input): stream for executing the task.
Returns:
Parameters
[object Object](aclTensor *, compute input/output): input[object Object]in the formula,[object Object]on the device. The data type must be convertible from that after deduction between[object Object]and[object Object], and must meet the with[object Object]. The shape must meet the with[object Object]. are supported. The can be ND.- [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be FLOAT, FLOAT16, INT32, INT64, INT16, INT8, UINT8, BOOL, or BFLOAT16.
[object Object](aclTensor*, compute input):[object Object]input in the formula,[object Object]on the device. The data type must meet the with[object Object]. The shape must meet the with[object Object]. are supported. The can be ND.- [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be FLOAT, FLOAT16, INT32, INT64, INT16, INT8, UINT8, 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]: 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]and[object Object]default to a deterministic implementation.
The following example is for reference only. For details, see .