code: def testNormalActions(self, loc, scale):
      action_spec = tensor_spec.BoundedTensorSpec(
          [1], tf.float32, tf.float32.min, tf.float32.max
      )
      wrapped_policy = DistributionPolicy(
          tfp.distributions.Normal([loc], [scale]),
          self._time_step_spec,
          action_spec,
      )
      policy = greedy_policy.GreedyPolicy(wrapped_policy)
  
      self.assertEqual(policy.time_step_spec, self._time_step_spec)
      self.assertEqual(policy.action_spec, action_spec)
  
      observations = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
      time_step = ts.restart(observations, batch_size=2)
      action_step = policy.action(time_step)
      tf.nest.assert_same_structure(action_spec, action_step.action)
  
      action_ = self.evaluate(action_step.action)
      self.assertAlmostEqual(action_[0], loc)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.policies import greedy_policy
  from tf_agents.policies import tf_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.utils import test_utils
label_desc: Use image node_id 3 for calling the GreedyPolicyTest obj's underlying member method code with example usage: obj.testNormalActions(loc, scale) without return types