code: def forward(
      self, input: Tensor, states: List[Tuple[Tensor, Tensor]]
  ) -> Tuple[Tensor, List[Tuple[Tensor, Tensor]]]:
      # List[LSTMState]: [forward LSTMState, backward LSTMState]
      outputs = jit.annotate(List[Tensor], [])
      output_states = jit.annotate(List[Tuple[Tensor, Tensor]], [])
      # XXX: enumerate https://github.com/pytorch/pytorch/issues/14471
      i = 0
      for direction in self.directions:
          state = states[i]
          out, out_state = direction(input, state)
          outputs += [out]
          output_states += [out_state]
          i += 1
      return torch.cat(outputs, -1), output_states
  
imports: import numbers
  import warnings
  from collections import namedtuple
  from typing import List, Tuple
  import torch
  import torch.jit
  import torch.nn
  from torch import Tensor
  from torch.nn import Parameter
label_desc: Use image node_id 2 for calling the BidirLSTMLayer obj's underlying member method code with example usage: obj.forward(input, states) and returns: torch,  output_states