code: def precise_dist(feat, nbrs, num_process=4, sort=True, verbose=False):
      import torch
  
      feat_share = torch.from_numpy(feat).share_memory_()
      nbrs_share = torch.from_numpy(nbrs).share_memory_()
      dist_share = torch.zeros_like(nbrs_share).float().share_memory_()
  
      precise_dist_share_mem(
          feat_share,
          nbrs_share,
          dist_share,
          num_process=num_process,
          sort=sort,
          verbose=verbose,
      )
  
      del feat_share
      gc.collect()
      return dist_share.numpy(), nbrs_share.numpy()
  
imports: import gc
  from tqdm import tqdm
  from .faiss_gpu import faiss_search_approx_knn
label_desc: Use image node_id 1 for calling a global function with example usage: precise_dist(feat, nbrs, num_process, sort, verbose) and returns: dist_share,  nbrs_share