code: def check_split_latent_conditioning(self, merge_std):
      with tf.Graph().as_default():
          rng = np.random.RandomState(0)
          x_rand = rng.randn(12, 32, 32, 32).astype(np.float32)
          latent_rand = rng.randn(12, 32, 32, 16).astype(np.float32)
          x_t = tf.convert_to_tensor(x_rand)
          latent_t = tf.convert_to_tensor(latent_rand)
          hparams = glow.glow_hparams()
          hparams.level_scale = merge_std
          hparams.add_hparam("latent_dist_encoder", "pointwise")
  
          # Test initalization.
          # x2 ~ N(scale * latent, 1.0) where initial scale is 1.0
          exp_x2 = x_rand[:, :, :, 16:]
          exp_eps = x_rand[:, :, :, 16:] - latent_rand
          x_inv, _, eps, x2_t, _ = glow_ops.split(
              merge_std,
              x_t,
              cond_latents=latent_t,
              hparams=hparams,
              condition=True,
          )
          # Test reversibility.
          x_inv_inv, _, _ = glow_ops.split(
              merge_std,
              x_inv,
              cond_latents=latent_t,
              eps=eps,
              reverse=True,
              hparams=hparams,
              condition=True,
          )
          with tf.Session() as sess:
              sess.run(tf.global_variables_initializer())
              actual_eps, actual_x2, diff_np = sess.run(
                  [eps, x2_t, x_inv_inv - x_t]
              )
              self.assertTrue(np.allclose(diff_np, 0.0, atol=1e-5))
              self.assertTrue(np.allclose(actual_eps, exp_eps))
              self.assertTrue(np.allclose(exp_x2, actual_x2))
  
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 six.moves import range
  from six.moves import zip
  from tensor2tensor.models.research import glow
  from tensor2tensor.models.research import glow_ops
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import hparam
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 15 for calling the GlowOpsTest obj's underlying member method code with example usage: obj.check_split_latent_conditioning(merge_std) without return types