code: def __init__(self, args, emb_layer, nclasses=2):
      super(Model, self).__init__()
      self.args = args
      self.drop = nn.Dropout(args.dropout)
      self.emb_layer = emb_layer
      if args.cnn:
          self.encoder = modules.CNN_Text(
              emb_layer.n_d, widths=[3, 4, 5]
          )
          d_out = 300
      elif args.lstm:
          self.encoder = nn.LSTM(
              emb_layer.n_d,
              args.d,
              args.depth,
              dropout=args.dropout,
          )
          d_out = args.d
      else:
          self.encoder = SRU(
              emb_layer.n_d,
              args.d,
              args.depth,
              dropout=args.dropout,
          )
          d_out = args.d
      self.out = nn.Linear(d_out, nclasses)
  
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 1 to create a new Model object from inherited base classes: nn with example: obj = Model(args, emb_layer, nclasses)