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"])

    return (x - y + eps).pow(2).sum(-1, keepdim).sqrt()
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/geometry/linalg.py