code: def testDistribution(self):
      # Given some action values and non-zero epsilon:
      action_values = [0.9, 1.0, 0.9, 0.1, -0.6]
      epsilon = 0.1
  
      # We expect a distribution that concentrates the right probabilities.
      expected = [0.02, 0.92, 0.02, 0.02, 0.02]
  
      result = policy_ops.epsilon_greedy(action_values, epsilon).probs
      with self.test_session() as sess:
          self.assertAllClose(sess.run(result), expected)
  
file_path: trfl/trfl/policy_ops_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow.compat.v1
  from trfl import policy_ops
label_desc: Use image node_id 3 for calling the EpsilonGreedyTest obj's underlying member method code with example usage: obj.testDistribution() without return types