code: def test_tuple_input(self):
      # Input: a list of 3 tuples, each has two arrays
      # Expected output: a tuple of two 4+1+3=8-length arrays
      in_size0 = 2
      in_size1 = 3
      seqs_x0 = [
          np.random.uniform(-1, 1, size=(4, in_size0)).astype(
              np.float32
          ),
          np.random.uniform(-1, 1, size=(1, in_size0)).astype(
              np.float32
          ),
          np.random.uniform(-1, 1, size=(3, in_size0)).astype(
              np.float32
          ),
      ]
      seqs_x1 = [
          np.random.uniform(-1, 1, size=(4, in_size1)).astype(
              np.float32
          ),
          np.random.uniform(-1, 1, size=(1, in_size1)).astype(
              np.float32
          ),
          np.random.uniform(-1, 1, size=(3, in_size1)).astype(
              np.float32
          ),
      ]
      seqs_x = [
          (seqs_x0[0], seqs_x1[0]),
          (seqs_x0[1], seqs_x1[1]),
          (seqs_x0[2], seqs_x1[2]),
      ]
      concat_seqs = stateless_recurrent.concatenate_sequences(seqs_x)
      self.assertIsInstance(concat_seqs, tuple)
      self.assertEqual(len(concat_seqs), 2)
      self.assertEqual(concat_seqs[0].shape, (8, in_size0))
      self.assertEqual(concat_seqs[1].shape, (8, in_size1))
      np.testing.assert_allclose(concat_seqs[0][:4].array, seqs_x0[0])
      np.testing.assert_allclose(concat_seqs[0][4:5].array, seqs_x0[1])
      np.testing.assert_allclose(concat_seqs[0][5:].array, seqs_x0[2])
      np.testing.assert_allclose(concat_seqs[1][:4].array, seqs_x1[0])
      np.testing.assert_allclose(concat_seqs[1][4:5].array, seqs_x1[1])
      np.testing.assert_allclose(concat_seqs[1][5:].array, seqs_x1[2])
  
imports: import unittest
  from chainer import links
  from chainer import testing
  import numpy
  from chainerrl.links import stateless_recurrent
label_desc: Use image node_id 2 for calling the TestConcatenateSequences obj's underlying member method code with example usage: obj.test_tuple_input() without return types