class_docstr: A policy that outputs a constant action, for testing purposes.
class_docstr_tok: ["A","policy","that","outputs","a","constant","action",",","for","testing","purposes","."]
code: def __init__(self, action_spec, time_step_spec, action):
      self._constant_action = action
      super(ConstantPolicy, self).__init__(
          time_step_spec=time_step_spec,
          action_spec=action_spec,
          info_spec={
              "a": tensor_spec.TensorSpec(shape=(), dtype=tf.int32),
              "b": tensor_spec.TensorSpec(shape=(4,), dtype=tf.float32),
          },
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import tensorflow
  import tensorflow_probability
  from tf_agents.bandits.policies import mixture_policy
  from tf_agents.policies import policy_saver
  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 1 to create a new ConstantPolicy object from inherited base classes: tf_policy with example: obj = ConstantPolicy(action_spec, time_step_spec, action)