code: def hidden_step(self, X, H, training=False):
      for i in range(self.start, len(self.layers)):
          X = self.G[i](X, Variable(H[i]))
          if training:
              X = self.D[i](X)
          H[i] = X
      return X
  
imports: from collections import Counter
  import numpy
  import torch
  from torch import nn
  from torch.autograd import Variable
  from torch.optim import Optimizer
  from cornac.utils.common import get_rng
label_desc: Use image node_id 14 for calling the GRU4RecModel obj's underlying member method code with example usage: obj.hidden_step(X, H, training) and returns: X