code: def __init__(self, h_feats):
      super().__init__()
      self.W1 = nn.Linear(h_feats * 2, h_feats)
      self.W2 = nn.Linear(h_feats, 1)
  
imports: import itertools
  import os
  import dgl
  import dgl.data
  import numpy
  import scipy.sparse
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.nn import SAGEConv
  import dgl.function
  from sklearn.metrics import roc_auc_score
label_desc: Use image node_id 1 to create a new MLPPredictor object from inherited base classes: nn with example: obj = MLPPredictor(h_feats)