code: def test_n_samples(self):
      with self.test_session():
          x = Normal(loc=0.0, scale=1.0)
          x_data = tf.constant(0.0)
          ed.evaluate("mean_squared_error", {x: x_data}, n_samples=1)
          ed.evaluate("mean_squared_error", {x: x_data}, n_samples=5)
          self.assertRaises(
              TypeError,
              ed.evaluate,
              "mean_squared_error",
              {x: x_data},
              n_samples="1",
          )
  
file_path: edward/tests/criticisms/evaluate_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, Categorical, Multinomial, Normal
label_desc: Use image node_id 5 for calling the test_evaluate_class obj's underlying member method code with example usage: obj.test_n_samples() without return types