code: def pad_adj(adj, max_len):
      pad_len = max_len - adj.shape[0]
      for i in range(pad_len):
          adj = np.insert(adj, adj.shape[-1], 0, axis=1)
      for i in range(len):
          adj = np.insert(adj, adj.shape[0], 0, axis=0)
  
file_path: DeepKE/src/deepke/attribution_extraction/standard/module/GCN.py
imports: import logging
  import torch
  import numpy
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling a global function with example usage: pad_adj(adj, max_len) without return types