PairwiseDistance
class torch.nn.PairwiseDistance(p=2.0, eps=1e-06, keepdim=False)
Computes the pairwise distance between input vectors, or between
   columns of input matrices.
Distances are computed using "p"-norm, with constant "eps" added to
   avoid division by zero if "p" is negative, i.e.:
  \mathrm{dist}\left(x, y\right) = \left\Vert x-y + \epsilon e
  \right\Vert_p,

where e is the vector of ones and the "p"-norm is given by.
  \Vert x \Vert _p = \left( \sum_{i=1}^n  \vert x_i \vert ^ p
  \right) ^ {1/p}.

Parameters:
      * p (real, optional) -- the norm degree. Can be
        negative. Default: 2
  * **eps** (*float**, **optional*) -- Small value to avoid
    division by zero. Default: 1e-6

  * **keepdim** (*bool**, **optional*) -- Determines whether or
    not to keep the vector dimension. Default: False

Shape:
      * Input1: (N, D) or (D) where N = batch dimension and D =
        vector dimension