torch_pdist: Pdist

In torch: Tensors and Neural Networks with 'GPU' Acceleration

Pdist

Description

Pdist

Usage

torch_pdist(self, p = 2L)

Arguments

self	NA input tensor of shape N \times M.
p	NA p value for the p-norm distance to calculate between each vector pair \in [0, \infty].

pdist(input, p=2) -> Tensor

Computes the p-norm distance between every pair of row vectors in the input. This is identical to the upper triangular portion, excluding the diagonal, of ⁠torch_norm(input[:, NULL] - input, dim=2, p=p)⁠. This function will be faster if the rows are contiguous.

If input has shape N \times M then the output will have shape \frac{1}{2} N (N - 1).

This function is equivalent to scipy.spatial.distance.pdist(input, 'minkowski', p=p) if p \in (0, \infty). When p = 0 it is equivalent to scipy.spatial.distance.pdist(input, 'hamming') * M. When p = \infty, the closest scipy function is ⁠scipy.spatial.distance.pdist(xn, lambda x, y: np.abs(x - y).max())⁠.

torch documentation built on May 29, 2024, 9:54 a.m.