code: def use_swap_map(
      matrix,
      swap_map,
      swap_ids,
      threshold,
      used_escape_attempts,
      escape_attempts,
      permutation,
      verbosity,
  ):
      used_stripes = []
      swaps = 0
      improvement = 0.0
  
      # set the traversal order and threshold
      ix = np.flip(
          np.argsort(swap_map)
      )  # small to large -> large to small
      threshold = min(max(swap_map[ix[0]] * threshold, 0.0001), 1.0)
  
      # iterate through the potential swaps in benefit order
      for swap in range(len(ix)):
          swap_id = ix[swap]
          src = swap_ids[swap_id][0]
          dst = swap_ids[swap_id][1]
  
          # early-out of swaps that are below the threshold (don't be so greedy)
          if swap_map[ix[swap]] < threshold:
              # see if an arbitrary swap helps things if we've converged
              if (
                  len(used_stripes) == 0
                  and used_escape_attempts < escape_attempts
              ):
                  swap_id = np.random.randint(len(swap_ids))
                  if verbosity > 15:
                      print(
                          f"converged, attempt #{used_escape_attempts+1} to jiggle out, using index {swap_id} into the sorted list={ix[swap_id]}"
                      )
                  swap_id = ix[swap_id]
                  src = swap_ids[swap_id][0]
                  dst = swap_ids[swap_id][1]
                  used_escape_attempts += 1
              else:
                  break
  
          # skip swaps that include a stripe we've already modified
          if (
              int(src / 4) in used_stripes
              or int(dst / 4) in used_stripes
          ):
              continue
  
          # we'll need to update these stripes later
          used_stripes.append(int(src / 4))
          used_stripes.append(int(dst / 4))
  
          # make the swap
          if verbosity > 20:
              print(f"\t{swap}\t{src},{dst}  {swap_map[swap_id]:.4f}")
          matrix[..., [src, dst]] = matrix[..., [dst, src]]
          permutation[src], permutation[dst] = (
              permutation[dst],
              permutation[src],
          )
          improvement += swap_map[swap_id]
          swaps += 1
  
      return (
          matrix,
          swaps,
          swap_map,
          swap_ids,
          used_stripes,
          improvement,
          used_escape_attempts,
          permutation,
      )
  
file_path: apex/apex/contrib/sparsity/permutation_search_kernels/channel_swap.py
imports: from .permutation_utilities import *
label_desc: Use image node_id 7 for calling a global function with example usage: use_swap_map(matrix, swap_map, swap_ids, threshold, used_escape_attempts, escape_attempts, permutation, verbosity) and returns: matrix,  swaps,  swap_map,  swap_ids,  used_stripes,  improvement,  used_escape_attempts,  permutation