code: def test_split(self):
      x, x_mask, _ = self.get_data()
  
      x_inv, z, log_p = glow.split("split", x, x_mask, inverse=False)
      x_inv_inv, _, log_p_inv = glow.split(
          "split", x_inv, x_mask, z=z, inverse=True
      )
      self.evaluate(tf.global_variables_initializer())
      x, x_inv, x_inv_inv, z, log_p, log_p_inv = self.evaluate(
          [x, x_inv, x_inv_inv, z, log_p, log_p_inv]
      )
      diff = x - x_inv_inv
      log_p_diff = log_p - log_p_inv
      self.assertEqual(
          x_inv.shape, (BATCH_SIZE, TARGET_LENGTH, N_CHANNELS // 2)
      )
      self.assertEqual(
          z.shape, (BATCH_SIZE, TARGET_LENGTH, N_CHANNELS // 2)
      )
      self.assertTrue(np.allclose(diff, 0.0, atol=1e-5))
      self.assertTrue(np.allclose(log_p_diff, 0.0, atol=1e-5))
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import tempfile
  from absl.testing import parameterized
  import numpy
  from tensor2tensor.layers import common_attention
  from tensor2tensor.layers import transformer_glow_layers
  from tensor2tensor.layers import transformer_glow_layers_ops
  from tensor2tensor.models import transformer
  import tensorflow.compat.v1
label_desc: Use image node_id 8 for calling the TransformerGlowLayersTest obj's underlying member method code with example usage: obj.test_split() without return types