code: def test_tuple_input(self):
      # Input: a tuple of two 4+1+3=8-length arrays
      # Expected output: a list of 3 tuples, each has two 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
          ),
      ]
      batched_seqs_x0 = np.concatenate(seqs_x0, axis=0)
      batched_seqs_x1 = np.concatenate(seqs_x1, axis=0)
      sections = [4, 5]
      split = stateless_recurrent.split_batched_sequences(
          (batched_seqs_x0, batched_seqs_x1), sections
      )
      self.assertEqual(len(split), 3)
      self.assertIsInstance(split[0], tuple)
      self.assertEqual(len(split[0]), 2)
      np.testing.assert_allclose(split[0][0].array, seqs_x0[0])
      np.testing.assert_allclose(split[0][1].array, seqs_x1[0])
      np.testing.assert_allclose(split[1][0].array, seqs_x0[1])
      np.testing.assert_allclose(split[1][1].array, seqs_x1[1])
      np.testing.assert_allclose(split[2][0].array, seqs_x0[2])
      np.testing.assert_allclose(split[2][1].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 TestSplitBatchedSequences obj's underlying member method code with example usage: obj.test_tuple_input() without return types