code: def forward(self, x):
      out, _ = self.rnn(x)
      return self.fc_out(out[:, -1, :]).squeeze()
  
imports: from __future__ import division
  from __future__ import print_function
  import numpy
  import pandas
  import copy
  from ...utils import get_or_create_path
  from ...log import get_module_logger
  import torch
  import torch.nn
  import torch.optim
  from torch.utils.data import DataLoader
  from .pytorch_utils import count_parameters
  from ...model.base import Model
  from ...data.dataset.handler import DataHandlerLP
  from ...model.utils import ConcatDataset
  from ...data.dataset.weight import Reweighter
label_desc: Use image node_id 2 for calling the GRUModel obj's underlying member method code with example usage: obj.forward(x) and returns: self