code: def test_actnorm_3d(self):
      with tf.Graph().as_default():
          x_t = tf.random_normal(
              (16, 5, 32, 32, 3), mean=50.0, stddev=2.0
          )
          ops = [glow_ops.actnorm, glow_ops.get_variable_ddi]
          with arg_scope(ops, init=True):
              x_act, _ = glow_ops.actnorm_3d("actnorm", x_t)
          with tf.Session() as session:
              x_act_np = session.run(x_act)
              # Mean and standard deviation per time-step equals zero and one.
              for time_step in range(5):
                  x_act_curr = x_act_np[:, time_step, :, :, :]
                  channel_mean = np.mean(x_act_curr, axis=(0, 1, 2))
                  channel_var = np.var(x_act_curr, axis=(0, 1, 2))
                  self.assertTrue(
                      np.allclose(channel_mean, 0.0, atol=1e-3)
                  )
                  self.assertTrue(
                      np.allclose(channel_var, 1.0, atol=1e-3)
                  )
  
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 19 for calling the GlowOpsTest obj's underlying member method code with example usage: obj.test_actnorm_3d() without return types