code: def _step_rnn_tanh(rnn, x, state):
      assert isinstance(rnn, L.NStepRNNTanh)
      assert len(rnn.ws) == 1
      assert len(rnn.bs) == 1
      assert len(rnn.ws[0]) == 2
      assert len(rnn.bs[0]) == 2
      if state is None:
          xp = rnn.xp
          h = xp.zeros((len(x), rnn.out_size), dtype=np.float32)
      else:
          h = state
      w0, w1 = rnn.ws[0]
      b0, b1 = rnn.bs[0]
      h = F.tanh(F.linear(x, w0, b0) + F.linear(h, w1, b1))
      return h, h
  
imports: import unittest
  import chainer
  from chainer import functions
  from chainer import links
  from chainer import testing
  import numpy
  from chainerrl.links import StatelessRecurrentSequential
label_desc: Use image node_id 2 for calling a global function with example usage: _step_rnn_tanh(rnn, x, state) and returns: h,  h