code: def aug(graph, x, feat_drop_rate, edge_mask_rate):
      n_node = graph.num_nodes()
  
      edge_mask = mask_edge(graph, edge_mask_rate)
      feat = drop_feature(x, feat_drop_rate)
  
      src = graph.edges()[0]
      dst = graph.edges()[1]
  
      nsrc = src[edge_mask]
      ndst = dst[edge_mask]
  
      ng = dgl.graph((nsrc, ndst), num_nodes=n_node)
      ng = ng.add_self_loop()
  
      return ng, feat
  
imports: import dgl
  import numpy
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: aug(graph, x, feat_drop_rate, edge_mask_rate) and returns: ng,  feat