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 $\in [0,\mathrm{\infty }]$.

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