code: def testGreedy(self):
      # Given some action values with one largest value:
      action_values = [0.5, 0.99, 0.9, 1.0, 0.1, -0.1, -100.0]
  
      # And zero epsilon:
      epsilon = 0.0
  
      # We expect a deterministic greedy policy that chooses one action.
      expected = [0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]
  
      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 2 for calling the EpsilonGreedyTest obj's underlying member method code with example usage: obj.testGreedy() without return types