code: def forward(self, x):
      # x: [N, F*T]
      x = x.reshape(len(x), self.d_feat, -1)  # [N, F, T]
      x = x.permute(0, 2, 1)  # [N, T, F]
      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
  import random
  from ...utils import get_or_create_path
  from ...log import get_module_logger
  import torch
  import torch.nn
  import torch.optim
  from ...model.base import Model
  from ...data.dataset import DatasetH
  from ...data.dataset.handler import DataHandlerLP
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