code: def op_mean(x, nbs):
      res = np.zeros_like(x)
      for u in range(len(nbs)):
          nb = nbs[u]
          if len(nb != 0):
              res[u] = np.mean(x[nb], axis=0)
      return res
  
imports: import time
  import numpy
  import torch
  import typing
  from sklearn import preprocessing
  from sklearn.metrics.pairwise import cosine_similarity
  import tqdm
  import tabulate
  import autogl.data.graph
  from ._feature_engineer import FeatureEngineer
  from .._data_preprocessor_registry import DataPreprocessorUniversalRegistry
  from ._selectors import GBDTFeatureSelector
  from ....utils import get_logger
label_desc: Use image node_id 2 for calling a global function with example usage: op_mean(x, nbs) and returns: res