[object Object]

[object Object][object Object]undefined[object Object]

• Description: Performs the sign function on each element of the input tensor and outputs the result tensor.

• Formula:

  $$resultput_i = \left\{ \begin{aligned} 1,\quad input_i > 0\\ 0,\quad input_i = 0\\ -1,\quad input_i < 0 \end{aligned} \right.$$

• Calculation formula (BOOL type):

  $$resultput_i = \left\{ \begin{aligned} \text{True},\quad input_i = \text{True}\\ \text{False},\quad input_i = \text{False}\\ \end{aligned} \right.$$

• Calculation formula (complex number, with the real part and imaginary part):

  $$resultput_i = \alpha \cdot cos(\theta_i) + \beta \cdot sin(\theta_i) \\ \alpha = \left\{ \begin{aligned} 1,\quad real(input_i) > 0 \\ 0,\quad real(input_i) = 0 \\ -1,\quad real(input_i) < 0 \\ \end{aligned} \right. \\ \beta = \left\{ \begin{aligned} 1,\quad image(input_i) > 0 \\ 0,\quad image(input_i) = 0 \\ -1,\quad image(input_i) < 0 \\ \end{aligned} \right. \\ \theta_i = arctan(\frac{image(input_i)}{real(input_i)})$$

[object Object]

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]

[object Object]

• Parameters:

  • [object Object] (const aclTensor, compute input): tensor on the device. It supports 1 to 8 dimensions. Non-contiguous tensors are supported. The supports ND.
    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be DOUBLE, FLOAT, FLOAT16, INT32, INT64, COMPLEX64, COMPLEX128, 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 DOUBLE, FLOAT, FLOAT16, INT32, INT64, COMPLEX64, COMPLEX128, BOOL, or BFLOAT16.
  • [object Object] (aclTensor, compute output): tensor on the device. It supports 1 to 8 dimensions. Non-contiguous tensors are supported. The supports ND. The data type and shape must be the same as those of [object Object], and the dtype must be the same as that of [object Object].
    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be DOUBLE, FLOAT, FLOAT16, INT32, INT64, COMPLEX64, COMPLEX128, 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 DOUBLE, FLOAT, FLOAT16, INT32, INT64, COMPLEX64, COMPLEX128, 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 .

[object Object]

• Parameters:

  • [object Object] (void *, input): address of the workspace memory 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:

  [object Object]: status code. For details, see .

[object Object]

• Deterministic compute:
  • [object Object] defaults to a deterministic implementation.

[object Object]

The following example is for reference only. For details, see .