class_docstr: Base class flexible RNNs.
  
  Forward function can handle sequences of length 0.
docstr: Initialise a hidden_state.
  
  Args:
      x (torch.Tensor): network input
  
  Returns:
      HiddenState: default (zero-like) hidden state
docstr_tok: ["Initialise","a","hidden_state",".","Args",":","x","(","torch.Tensor",")",":","network","input","Returns",":","HiddenState",":","default","(","zero-like",")","hidden","state"]
code: def init_hidden_state(self, x: torch.Tensor) -> HiddenState:
      """
      Initialise a hidden_state.
  
      Args:
          x (torch.Tensor): network input
  
      Returns:
          HiddenState: default (zero-like) hidden state
      """
      pass
  
imports: from abc import ABC, abstractmethod
  from typing import Tuple, Type, Union
  import torch
  from torch import nn
  from torch.nn.utils import rnn
label_desc: Use image node_id 2 for calling the RNN obj's underlying member method code with example usage: obj.init_hidden_state(x) without return types