code: def testPyEnvCompatible(self):
      if not common.has_eager_been_enabled():
          self.skipTest("Only supported in eager.")
  
      actor_net = actor_network.ActorNetwork(
          self._observation_tensor_spec,
          self._action_tensor_spec,
          fc_layer_params=(10,),
      )
  
      tf_policy = actor_policy.ActorPolicy(
          self._time_step_tensor_spec,
          self._action_tensor_spec,
          actor_network=actor_net,
      )
  
      py_policy = py_tf_eager_policy.PyTFEagerPolicy(tf_policy)
      time_step = self._env.reset()
  
      for _ in range(100):
          action_step = py_policy.action(time_step)
          time_step = self._env.step(action_step.action)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.agents.ddpg import actor_network
  from tf_agents.environments import batched_py_environment
  from tf_agents.environments import random_py_environment
  from tf_agents.policies import actor_policy
  from tf_agents.policies import policy_saver
  from tf_agents.policies import py_tf_eager_policy
  from tf_agents.policies import random_tf_policy
  from tf_agents.specs import array_spec
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.utils import common
  from tf_agents.utils import nest_utils
  from tf_agents.utils import test_utils
label_desc: Use image node_id 2 for calling the PyTFEagerPolicyTest obj's underlying member method code with example usage: obj.testPyEnvCompatible() without return types