code: def forward(self, net: Tensor) -> Tensor:
      for rnn in self.rnn_list:
          net, final_state = rnn(net, None)
      return self.head(net[:, -1])
  
file_path: carefree-learn/cflearn/models/ml/rnn.py
imports: import torch.nn
  import torch.nn.init
  from torch import no_grad
  from torch import Tensor
  from typing import Dict
  from typing import List
  from typing import Optional
  from .fcnn import FCNN
  from typing import Dict
  from typing import Optional
  from .base import MLModel
  from ...schema import MLEncoderSettings
  from ...schema import MLGlobalEncoderSettings
label_desc: Use image node_id 3 for calling the RNN obj's underlying member method code with example usage: obj.forward(net) and returns: self