# torch_cdist: Cdist In torch: Tensors and Neural Networks with 'GPU' Acceleration

Cdist

## Usage

 1 torch_cdist(x1, x2, p = 2L, compute_mode = NULL) 

## Arguments

 x1 (Tensor) input tensor of shape B \times P \times M. x2 (Tensor) input tensor of shape B \times R \times M. p NA p value for the p-norm distance to calculate between each vector pair \in [0, ∞]. compute_mode NA 'use_mm_for_euclid_dist_if_necessary' - will use matrix multiplication approach to calculate euclidean distance (p = 2) if P > 25 or R > 25 'use_mm_for_euclid_dist' - will always use matrix multiplication approach to calculate euclidean distance (p = 2) 'donot_use_mm_for_euclid_dist' - will never use matrix multiplication approach to calculate euclidean distance (p = 2) Default: use_mm_for_euclid_dist_if_necessary.

## TEST

Computes batched the p-norm distance between each pair of the two collections of row vectors.

torch documentation built on Oct. 7, 2021, 9:22 a.m.