[object Object]

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

• This API is used to calculate the p-norm distance between each pair of row vectors in the input self.

• Formula:

  Assume that the shape of the input [object Object] is [N, M], and $self_{in}$ indicates the element whose index is [object Object] in row [object Object] of [object Object]. The norm distance between row [object Object] and row [object Object] is calculated as follows:

  $$out_{ij} = \sum_{k=0}^{M-1}||self_{in}-self_{jn}||_p = (\sum_{k=0}^{M-1}|self_{in}-self_{jn}|^p)^\frac{1}{p}$$

  The shape of out is [$\frac{1}{2}N(N-1)$], where the elements are arranged in the following order: $out_{01}$, ..., $out_{0,N-1}$,$out_{1,2}$, ... $out_{1,N-1}$, ..., $out_{N-2,N-1}$

[object Object]

Each operator has calls. First, aclnnPdistForwardGetWorkspaceSize is called to obtain the workspace size required for computation and the executor that contains the operator computation process. Then, aclnnPdistForward is called to perform computation.

[object Object]

• Parameters:

  [object Object]

• Returns:

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

  The first-phase API implements input parameter verification. The following errors may be thrown.

  [object Object]

[object Object]

• Parameters:

  [object Object]

• Returns:

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

[object Object]

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

[object Object]

The following examples are for reference only. For details, see .