code: def _test_mask_recurrent_state_at(self, gpu):
      in_size = 2
      out_size = 4
      rseq = StatelessRecurrentSequential(
          L.Linear(in_size, 3),
          F.elu,
          L.NStepGRU(1, 3, out_size, 0),
          F.softmax,
      )
      if gpu >= 0:
          chainer.cuda.get_device_from_id(gpu).use()
          rseq.to_gpu()
      xp = rseq.xp
      seqs_x = [
          xp.random.uniform(-1, 1, size=(2, in_size)).astype(
              np.float32
          ),
          xp.random.uniform(-1, 1, size=(2, in_size)).astype(
              np.float32
          ),
      ]
      transposed_x = F.transpose_sequence(seqs_x)
      print("transposed_x[0]", transposed_x[0])
  
      def no_mask_n_step_forward():
          nomask_nstep_out, nstep_rs = rseq.n_step_forward(
              seqs_x, None, output_mode="concat"
          )
          return F.reshape(nomask_nstep_out, (2, 2, out_size)), nstep_rs
  
      nstep_out, nstep_rs = no_mask_n_step_forward()
  
      # Check if n_step_forward and forward twice results are same
      def no_mask_forward_twice():
          _, rs = rseq(transposed_x[0], None)
          return rseq(transposed_x[1], rs)
  
      nomask_out, nomask_rs = no_mask_forward_twice()
      xp.testing.assert_allclose(
          nstep_out.array[:, 1],
          nomask_out.array,
      )
      xp.testing.assert_allclose(nstep_rs[0].array, nomask_rs[0].array)
  
      # 1st-only mask forward twice: only 2nd should be the same
      def mask0_forward_twice():
          _, rs = rseq(transposed_x[0], None)
          rs = rseq.mask_recurrent_state_at(rs, 0)
          return rseq(transposed_x[1], rs)
  
      mask0_out, mask0_rs = mask0_forward_twice()
      with self.assertRaises(AssertionError):
          xp.testing.assert_allclose(
              nstep_out.array[0, 1],
              mask0_out.array[0],
          )
      xp.testing.assert_allclose(
          nstep_out.array[1, 1],
          mask0_out.array[1],
      )
  
      # 2nd-only mask forward twice: only 1st should be the same
      def mask1_forward_twice():
          _, rs = rseq(transposed_x[0], None)
          rs = rseq.mask_recurrent_state_at(rs, 1)
          return rseq(transposed_x[1], rs)
  
      mask1_out, mask1_rs = mask1_forward_twice()
      xp.testing.assert_allclose(
          nstep_out.array[0, 1],
          mask1_out.array[0],
      )
      with self.assertRaises(AssertionError):
          xp.testing.assert_allclose(
              nstep_out.array[1, 1],
              mask1_out.array[1],
          )
  
      # both 1st and 2nd mask forward twice: both should be different
      def mask01_forward_twice():
          _, rs = rseq(transposed_x[0], None)
          rs = rseq.mask_recurrent_state_at(rs, [0, 1])
          return rseq(transposed_x[1], rs)
  
      mask01_out, mask01_rs = mask01_forward_twice()
      with self.assertRaises(AssertionError):
          xp.testing.assert_allclose(
              nstep_out.array[0, 1],
              mask01_out.array[0],
          )
      with self.assertRaises(AssertionError):
          xp.testing.assert_allclose(
              nstep_out.array[1, 1],
              mask01_out.array[1],
          )
  
      # get and concat recurrent states and resume forward
      def get_and_concat_rs_forward():
          _, rs = rseq(transposed_x[0], None)
          rs0 = rseq.get_recurrent_state_at(rs, 0, unwrap_variable=True)
          rs1 = rseq.get_recurrent_state_at(rs, 1, unwrap_variable=True)
          concat_rs = rseq.concatenate_recurrent_states([rs0, rs1])
          return rseq(transposed_x[1], concat_rs)
  
      getcon_out, getcon_rs = get_and_concat_rs_forward()
      xp.testing.assert_allclose(getcon_rs[0].array, nomask_rs[0].array)
      xp.testing.assert_allclose(
          nstep_out.array[0, 1], getcon_out.array[0]
      )
      xp.testing.assert_allclose(
          nstep_out.array[1, 1], getcon_out.array[1]
      )
  
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 10 for calling the TestStatelessRecurrentSequential obj's underlying member method code with example usage: obj._test_mask_recurrent_state_at(gpu) and returns: F,  nstep_rs, rseq, rseq, rseq, rseq, rseq