code: def test_temperature_normal(self, temperature):
      with tf.Graph().as_default():
          rng = np.random.RandomState(0)
          # in numpy, so that multiple calls don't trigger different random numbers.
          loc_t = tf.convert_to_tensor(rng.randn(5, 5))
          scale_t = tf.convert_to_tensor(rng.rand(5, 5))
          tempered_normal = glow_ops.TemperedNormal(
              loc=loc_t, scale=scale_t, temperature=temperature
          )
          # smoke test for a single sample.
          smoke_sample = tempered_normal.sample()
          samples = tempered_normal.sample((10000,), seed=0)
  
          with tf.Session() as sess:
              ops = [samples, loc_t, scale_t, smoke_sample]
              samples_np, loc_exp, scale_exp, _ = sess.run(ops)
              scale_exp *= temperature
              loc_act = np.mean(samples_np, axis=0)
              scale_act = np.std(samples_np, axis=0)
              self.assertTrue(np.allclose(loc_exp, loc_act, atol=1e-2))
              self.assertTrue(
                  np.allclose(scale_exp, scale_act, atol=1e-2)
              )
  
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 21 for calling the GlowOpsTest obj's underlying member method code with example usage: obj.test_temperature_normal(temperature) without return types