code: def test_scale_1d(self):
      with self.test_session():
          N = 10
          M = 5
          mu = Normal(loc=0.0, scale=1.0)
          x = Normal(loc=tf.ones(M) * mu, scale=tf.ones(M))
  
          qmu = Normal(loc=tf.Variable(0.0), scale=tf.constant(1.0))
  
          x_ph = tf.placeholder(tf.float32, [M])
          inference = ed.KLqp({mu: qmu}, data={x: x_ph})
          inference.initialize(scale={x: tf.range(M, dtype=tf.float32)})
          self.assertAllEqual(inference.scale[x].eval(), np.arange(M))
  
file_path: edward/tests/inferences/inference_scale_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 Normal
label_desc: Use image node_id 2 for calling the test_inference_scale_class obj's underlying member method code with example usage: obj.test_scale_1d() without return types