docstr: Test that actnorm provides activations with zero channel-mean.
docstr_tok: ["Test","that","actnorm","provides","activations","with","zero","channel-mean","."]
code: def test_actnorm(self):
      """Test that actnorm provides activations with zero channel-mean."""
      with tf.Graph().as_default():
          x_t = tf.random_normal((16, 32, 32, 3), mean=50.0, stddev=2.0)
          x_act = glow_ops.actnorm("actnorm", x_t, init=True)
          with tf.Session() as session:
              x_act_np, _ = session.run(x_act)
              channel_mean = np.mean(x_act_np, axis=(0, 1, 2))
              channel_var = np.var(x_act_np, 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 3 for calling the GlowOpsTest obj's underlying member method code with example usage: obj.test_actnorm() without return types