code: def _step_lstm(lstm, x, state):
      assert isinstance(lstm, nn.LSTM)
      lstm_cell = nn.LSTMCell(
          input_size=lstm.input_size, hidden_size=lstm.hidden_size
      )
      assert lstm.num_layers == 1
      lstm_cell.weight_ih = lstm.weight_ih_l0
      lstm_cell.weight_hh = lstm.weight_hh_l0
      lstm_cell.bias_ih = lstm.bias_ih_l0
      lstm_cell.bias_hh = lstm.bias_hh_l0
      h, c = lstm_cell(x, state)
      return h, (h, c)
  
file_path: pfrl/tests/nn_tests/test_recurrent_sequential.py
imports: import unittest
  import pytest
  import torch
  import torch.nn.functional
  from torch import nn
  from pfrl.nn import Lambda, RecurrentSequential
  from pfrl.testing import torch_assert_allclose
label_desc: Use image node_id 1 for calling a global function with example usage: _step_lstm(lstm, x, state) and returns: h,  h,  c