[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 self is [N, M], and $self_{in}$ indicates the element whose subscript is n in row i of self. The formula for calculating the norm distance between row i and row j is 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, [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]

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

[object Object]

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