class_docstr: Mock PyEnvironment with rewards that are nested dicts.
class_docstr_tok: ["Mock","PyEnvironment","with","rewards","that","are","nested","dicts","."]
code: def reward_spec(self):
      return {
          "reward": specs.ArraySpec([], np.float32, name="reward"),
          "constraint": specs.ArraySpec(
              [], np.float32, name="constraint"
          ),
      }
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import threading
  from typing import Text
  from absl.testing import parameterized
  from absl.testing.absltest import mock
  import numpy
  import tensorflow
  from tf_agents import specs
  from tf_agents.environments import batched_py_environment
  from tf_agents.environments import py_environment
  from tf_agents.environments import suite_gym
  from tf_agents.environments import tf_py_environment
  from tf_agents.trajectories import time_step
  from tf_agents.utils import common
label_desc: Use image node_id 4 for calling the PYEnvironmentMockNestedRewards obj's underlying member method code with example usage: obj.reward_spec() and returns: dict