code: def match_snn(
      desc1: Tensor,
      desc2: Tensor,
      th: float = 0.8,
      dm: Optional[Tensor] = None,
  ) -> Tuple[Tensor, Tensor]:
      """Function, which finds nearest neighbors in desc2 for each vector in desc1.
  
      The method satisfies first to second nearest neighbor distance <= th.
  
      If the distance matrix dm is not provided, :py:func:`torch.cdist` is used.
  
      Args:
          desc1: Batch of descriptors of a shape :math:`(B1, D)`.
          desc2: Batch of descriptors of a shape :math:`(B2, D)`.
          th: distance ratio threshold.
          dm: Tensor containing the distances from each descriptor in desc1
            to each descriptor in desc2, shape of :math:`(B1, B2)`.
  
      Return:
          - Descriptor distance of matching descriptors, shape of :math:`(B3, 1)`.
          - Long tensor indexes of matching descriptors in desc1 and desc2. Shape: :math:`(B3, 2)`,
            where 0 <= B3 <= B1.
      """
      KORNIA_CHECK_SHAPE(desc1, ["B", "DIM"])
      KORNIA_CHECK_SHAPE(desc2, ["B", "DIM"])
  
      if (
          desc2.shape[0] < 2
      ):  # We cannot perform snn check, so output empty matches
          return _no_match(desc1)
      distance_matrix = _get_lazy_distance_matrix(desc1, desc2, dm)
      vals, idxs_in_2 = torch.topk(
          distance_matrix, 2, dim=1, largest=False
      )
      ratio = vals[:, 0] / vals[:, 1]
      mask = ratio <= th
      match_dists = ratio[mask]
      if len(match_dists) == 0:
          return _no_match(distance_matrix)
      idxs_in1 = torch.arange(
          0, idxs_in_2.size(0), device=distance_matrix.device
      )[mask]
      idxs_in_2 = idxs_in_2[:, 0][mask]
      matches_idxs = concatenate(
          [idxs_in1.view(-1, 1), idxs_in_2.view(-1, 1)], 1
      )
      return match_dists.view(-1, 1), matches_idxs.view(-1, 2)
  
imports: from typing import Any, ClassVar, Dict, List, Optional, Tuple
  import torch
  from kornia.core import Module, Tensor, concatenate
  from kornia.core.check import KORNIA_CHECK_DM_DESC, KORNIA_CHECK_SHAPE
  from kornia.feature.laf import get_laf_center
  from kornia.testing import is_mps_tensor_safe
  from .adalam import get_adalam_default_config, match_adalam
label_desc: Use image node_id 7 for calling a global function with example usage: match_snn(desc1, desc2, th, dm) and returns: match_dists,  matches_idxs, _no_match, _no_match