code: def forward(self, x):
      for lin, batch_norm in zip(self.lins[:-1], self.batch_norms):
          x = lin(x)
          if self.relu_last:
              x = batch_norm(x).relu_()
          else:
              x = batch_norm(x.relu_())
          x = F.dropout(x, p=self.dropout, training=self.training)
      x = self.lins[-1](x)
      return x
  
file_path: ogb/examples/lsc/mag240m/mlp.py
imports: import time
  import argparse
  import torch
  import torch.nn.functional
  from torch.utils.data import DataLoader
  from torch.nn import ModuleList, Linear, BatchNorm1d, Identity
  from ogb.lsc import MAG240MDataset, MAG240MEvaluator
  from root import ROOT
label_desc: Use image node_id 3 for calling the MLP obj's underlying member method code with example usage: obj.forward(x) and returns: x