Description: Performs the inverse hyperbolic cosine operation on each element of the input tensor and outputs the result.
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 written in place to the input tensor's memory.
- Each operator has calls. First,
[object Object]or[object Object]is called to obtain the workspace size required for computation and the executor covering the operator 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 aclTensor on the device. It supports . Its can be ND.- [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT16, FLOAT, DOUBLE, INT8, INT16, INT32, INT64, UINT8, BOOL, COMPLEX64, or COMPLEX128.
- [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, FLOAT, DOUBLE, INT8, INT16, INT32, INT64, UINT8, BOOL, COMPLEX64, COMPLEX128, or BFLOAT16.
[object Object](aclTensor*, computation output):[object Object]in the formula, which is aclTensor on the device. If the input is a complex number, the output must be a complex number. It supports . Its can be ND.- [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT16, FLOAT, DOUBLE, COMPLEX64, or COMPLEX128.
- [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, FLOAT, DOUBLE, COMPLEX64, COMPLEX128, or BFLOAT16.
[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]
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, covering the operator computation process.[object Object](aclrtStream, input): stream for executing the task.
Returns:
Parameters:
[object Object](aclTensor*, computation input/output):[object Object]/[object Object]in the formula, which is aclTensor on the device. It supports . Its can be ND.- [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT16, FLOAT, DOUBLE, COMPLEX64, or COMPLEX128.
- [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, FLOAT, DOUBLE, COMPLEX64, COMPLEX128, or BFLOAT16.
[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]
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, covering the operator computation process.[object Object](aclrtStream, input): stream for executing the task.
Returns:
- Deterministic computation:
[object Object]and[object Object]each default to a deterministic implementation.
The following example is for reference only. For details, see .
[object Object]