nn_pairwise_distance: Pairwise distance

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

Pairwise distance

Description

Computes the batchwise pairwise distance between vectors v_1, v_2 using the p-norm:

Usage

nn_pairwise_distance(p = 2, eps = 1e-06, keepdim = FALSE)

Arguments

p	(real): the norm degree. 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

Details

\Vert x \Vert _p = \left( \sum_{i=1}^n \vert x_i \vert ^ p \right) ^ {1/p}.

Shape

• Input1: (N, D) where ⁠D = vector dimension⁠

• Input2: (N, D), same shape as the Input1

• Output: (N). If keepdim is TRUE, then (N, 1).

Examples

if (torch_is_installed()) {
pdist <- nn_pairwise_distance(p = 2)
input1 <- torch_randn(100, 128)
input2 <- torch_randn(100, 128)
output <- pdist(input1, input2)
}

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