code: def __init__(
      self,
      in_size,
      out_size,
      hidden_size=128,
      num_steps=16,
      lam=1.0,
      alpha=0.5,
  ):
      super().__init__()
      self.num_steps = num_steps
      self.lam = lam
      self.alpha = alpha
      self.mlp = MLP(in_size, hidden_size)
      self.linear_out = nn.Linear(hidden_size, out_size)
  
imports: import argparse
  import dgl.sparse
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.data import CoraGraphDataset
  from torch.optim import Adam
label_desc: Use image node_id 1 to create a new TWIRLSWithAttention object from inherited base classes: nn with example: obj = TWIRLSWithAttention(in_size, out_size, hidden_size, num_steps, lam, alpha)