[object Object]

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

• Description: Sets the elements of the input tensor self (last two dimensions) to 0 in the upper triangular part above the main diagonal. The diagonal parameter can be set to a positive or negative value. The default value is 0. A positive value indicates diagonals above the main diagonal. A negative value indicates diagonals below the main diagonal.

• Formula: In the following formula, i indicates the sequence number of the element in the second-to-last dimension (i is the row index), j indicates the sequence number of the element in the last dimension (j is the column index), and d indicates diagonal. In the two-dimensional coordinate diagram corresponding to (i, j), i+d==j indicates that the element is on the diagonal.

  $$Diagonal and lower triangular part, that is, i+d ≥ j. Retain the original value: out_{i, j} = self_{i, j}\\. Upper triangular part, that is, i+d < j. Elements are set to 0 (excluding the diagonal): out_{i, j} = 0.$$

• Example:

  $self = \begin{bmatrix} [9&6&3] \\ [1&2&3] \\ [3&4&1] \end{bmatrix}$, The result of triu(self, diagonal=0) is as follows: $\begin{bmatrix} [9&0&0] \\ [1&2&0] \\ [3&4&1] \end{bmatrix}$; Adjust the value of diagonal. The result of triu(self, diagonal=1) is as follows: $\begin{bmatrix} [9&6&0] \\ [1&2&3] \\ [3&4&1] \end{bmatrix}$; Adjust the value of diagonal to -1. The result of triu(self, diagonal=-1) is as follows: $\begin{bmatrix} [0&0&0] \\ [1&0&0] \\ [3&4&0] \end{bmatrix}$.

[object Object]

• aclnnTril and aclnnInplaceTril implement the same function in different ways. Select a proper operator based on your requirements.
  • aclnnTril: An output tensor object needs to be created to store the computation result.
  • aclnnInplaceTril: 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 calculate the required workspace size based on the computation process. Then, [object Object] or [object Object] is called to perform computation.

[object Object]

• Parameters

  [object Object]
  • Ascend 950PR/Ascend 950DT: Only COMPLEX32 and COMPLEX64 are supported.
  • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type cannot be BFLOAT16.

• Return Value

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

  The first-phase API implements input parameter validation. The following error codes may be returned.

  [object Object]

[object Object]

• Parameters

  [object Object]

• Return Value

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

[object Object]

• Parameters

  [object Object]
  • Ascend 950PR/Ascend 950DT: Only COMPLEX32 and COMPLEX64 are supported.
  • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type cannot be BFLOAT16.

• Return Value

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

  The first-phase API implements input parameter validation. The following error codes may be returned.

  [object Object]

[object Object]

• Parameters

  [object Object]

• Return Value

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

[object Object]

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

[object Object]

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