code: def __init__(
      self,
      rnn_type: str,
      input_size: int,
      hidden_size: int,
      dropout: float = 0.0,
  ) -> None:
      super(SingleRNN, self).__init__()
  
      self.rnn_type = rnn_type
      self.input_size = input_size
      self.hidden_size = hidden_size
  
      self.rnn: nn.modules.Module = getattr(nn, rnn_type)(
          input_size,
          hidden_size,
          1,
          dropout=dropout,
          batch_first=True,
          bidirectional=True,
      )
  
      self.proj = nn.Linear(hidden_size * 2, input_size)
  
imports: import math
  from typing import List, Optional, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new SingleRNN object from inherited base classes: nn with example: obj = SingleRNN(rnn_type, input_size, hidden_size, dropout)