code: def forward(self, input):
      if self.args.cnn:
          input = input.t()
      emb = self.emb_layer(input)
      emb = self.drop(emb)
  
      if self.args.cnn:
          output = self.encoder(emb)
      else:
          output, hidden = self.encoder(emb)
          output = output[-1]
  
      output = self.drop(output)
      return self.out(output)
  
imports: import os
  import sys
  import argparse
  import time
  import random
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from torch.autograd import Variable
  from sru import *
  import dataloader
  import modules
label_desc: Use image node_id 2 for calling the Model obj's underlying member method code with example usage: obj.forward(input) and returns: self