code: def euclidean_distance(
      x: Tensor, y: Tensor, keepdim: bool = False, eps: float = 1e-6
  ) -> Tensor:
      """Compute the Euclidean distance between two set of n-dimensional points.
  
      More: https://en.wikipedia.org/wiki/Euclidean_distance
  
      Args:
          x: first set of points of shape :math:`(*, N)`.
          y: second set of points of shape :math:`(*, N)`.
          keepdim: whether to keep the dimension after reduction.
          eps: small value to have numerical stability.
      """
      KORNIA_CHECK_SHAPE(x, ["*", "N"])
      KORNIA_CHECK_SHAPE(y, ["*", "N"])
      KORNIA_CHECK(x.shape == y.shape)
  
      return (x - y + eps).pow(2).sum(-1, keepdim).sqrt()
  
file_path: kornia/kornia/geometry/linalg.py
imports: from __future__ import annotations
  import torch
  from kornia.core import Tensor, zeros_like
  from kornia.core.check import KORNIA_CHECK, KORNIA_CHECK_IS_TENSOR, KORNIA_CHECK_SHAPE
  from kornia.geometry.conversions import convert_points_from_homogeneous, convert_points_to_homogeneous
label_desc: Use image node_id 8 for calling a global function with example usage: euclidean_distance(x, y, keepdim, eps) and returns: unknown