Shortcuts

# Euclidean Distance¶

## Functional Interface¶

torchmetrics.functional.pairwise_euclidean_distance(x, y=None, reduction=None, zero_diagonal=None)[source]

Calculates pairwise euclidean distances:

If both and are passed in, the calculation will be performed pairwise between the rows of and . If only is passed in, the calculation will be performed between the rows of .

Parameters
Return type

Tensor

Returns

A [N,N] matrix of distances if only x is given, else a [N,M] matrix

Example

>>> import torch
>>> from torchmetrics.functional import pairwise_euclidean_distance
>>> x = torch.tensor([[2, 3], [3, 5], [5, 8]], dtype=torch.float32)
>>> y = torch.tensor([[1, 0], [2, 1]], dtype=torch.float32)
>>> pairwise_euclidean_distance(x, y)
tensor([[3.1623, 2.0000],
[5.3852, 4.1231],
[8.9443, 7.6158]])
>>> pairwise_euclidean_distance(x)
tensor([[0.0000, 2.2361, 5.8310],
[2.2361, 0.0000, 3.6056],
[5.8310, 3.6056, 0.0000]])


© Copyright Copyright (c) 2020-2023, Lightning-AI et al... Revision 54a06013.

Built with Sphinx using a theme provided by Read the Docs.
Versions
latest
stable
v0.11.4
v0.11.3
v0.11.2
v0.11.1
v0.11.0
v0.10.3
v0.10.2
v0.10.1
v0.10.0
v0.9.3
v0.9.2
v0.9.1
v0.9.0
v0.8.2
v0.8.1
v0.8.0
v0.7.3
v0.7.2
v0.7.1
v0.7.0
v0.6.2
v0.6.1
v0.6.0
v0.5.1
v0.5.0
v0.4.1
v0.4.0
v0.3.2
v0.3.1
v0.3.0
v0.2.0
v0.1.0