class_docstr: Update the node feature hv with MLP, BN and ReLU.
class_docstr_tok: ["Update","the","node","feature","hv","with","MLP",",","BN","and","ReLU","."]
code: def __init__(self, mlp):
      super(ApplyNodeFunc, self).__init__()
      self.mlp = mlp
      self.bn = nn.BatchNorm1d(self.mlp.output_dim)
  
imports: import pickle
  from dgl.dataloading import GraphDataLoader
  import numpy
  from tqdm import tqdm
  import random
  import torch
  import torch.nn
  import torch.optim
  from dgl.data import GINDataset
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.nn.pytorch.conv import GINConv
  from dgl.nn.pytorch.glob import SumPooling, AvgPooling, MaxPooling
label_desc: Use image node_id 1 to create a new ApplyNodeFunc object from inherited base classes: nn with example: obj = ApplyNodeFunc(mlp)