Operator function: Returns a random number tensor, which is obtained from an independent normal distribution of the given mean (float) and standard deviation (tensor).
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](float, computation input): mean of the random number distribution. The data type can be FLOAT.[object Object](aclTensor*, computation input): standard deviation of the random number distribution, which is an aclTensor on the device. The data type can be FLOAT16, FLOAT, or DOUBLE.[object Object]cannot be an empty tensor, and the shape cannot exceed eight dimensions. The can be ND.[object Object](int64_t*, computation input): seed for sampling the pseudo-random number generator. The data type is INT64.[object Object](int64_t*, computation input): offset for sampling the pseudo-random number generator. The data type is INT64.[object Object](aclTensor*, output): output tensor, which is an aclTensor on the device. The data type can be FLOAT, FLOAT16, or DOUBLE. The shape must be the same as that of[object Object], and cannot exceed 8 dimensions. The can be ND.[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 the first-phase API aclnnNormalFloatTensorGetWorkspaceSize.[object Object](aclOpExecutor*, input): operator executor, containing the operator computation process.[object Object](aclrtStream, input): stream for executing the task.
Returns:
- Deterministic computing:
[object Object]defaults to a deterministic implementation.
The following example is for reference only. For details, see .