code: def test_data_tensor(self):
      with self.test_session() as sess:
          x_data = tf.zeros(50)
  
          mu = Normal(0.0, 1.0)
          x = Normal(mu, 1.0, sample_shape=50)
  
          qmu = Empirical(tf.Variable(tf.ones(1000)))
  
          # analytic solution: N(mu=0.0, sigma=\sqrt{1/51}=0.140)
          inference = ed.Gibbs({mu: qmu}, data={x: x_data})
          inference.run()
  
          self.assertAllClose(
              qmu.mean().eval(), 0, rtol=1e-2, atol=1e-2
          )
          self.assertAllClose(
              qmu.stddev().eval(), np.sqrt(1 / 51), rtol=1e-2, atol=1e-2
          )
  
file_path: edward/tests/inferences/gibbs_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import edward
  import numpy
  import tensorflow
  from edward.models import Bernoulli, Beta, Empirical, Normal
label_desc: Use image node_id 4 for calling the test_gibbs_class obj's underlying member method code with example usage: obj.test_data_tensor() without return types