code: def setUp(self):
      super(FixedPolicyTest, self).setUp()
      # Creates an MDP with:
      # - dim(observation) = 2
      # - number of actions = 4
      self._obs_spec = tensor_spec.TensorSpec([2], tf.float32)
      self._time_step_spec = ts.time_step_spec(self._obs_spec)
      self._num_actions = 4
      self._action_spec = tensor_spec.BoundedTensorSpec(
          shape=(1,),
          dtype=tf.int32,
          minimum=0,
          maximum=self._num_actions - 1,
      )
  
      # The policy always outputs the same action.
      self._fixed_action = 1
      self._policy = fixed_policy.FixedPolicy(
          np.asarray([self._fixed_action], dtype=np.int32),
          self._time_step_spec,
          self._action_spec,
      )
  
file_path: agents/tf_agents/policies/fixed_policy_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  from tf_agents.policies import fixed_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.utils import test_utils
label_desc: Use image node_id 1 for calling the FixedPolicyTest obj's underlying member method code with example usage: obj.setUp() without return types