class_docstr: Extension of standard TFModel to provide DDPG action- and q-outputs.
  
  Data flow:
      obs -> forward() -> model_out
      model_out -> get_policy_output() -> deterministic actions
      model_out, actions -> get_q_values() -> Q(s, a)
      model_out, actions -> get_twin_q_values() -> Q_twin(s, a)
  
  Note that this class by itself is not a valid model unless you
  implement forward() in a subclass.
docstr: Return the list of variables for the policy net.
docstr_tok: ["Return","the","list","of","variables","for","the","policy","net","."]
code: def policy_variables(self) -> List[TensorType]:
      """Return the list of variables for the policy net."""
      return list(self.policy_model.variables)
  
file_path: ray/rllib_contrib/ddpg/src/rllib_ddpg/ddpg/ddpg_tf_model.py
imports: from typing import List, Optional
  import gymnasium
  import numpy
  from ray.rllib.models.tf.tf_modelv2 import TFModelV2
  from ray.rllib.utils.framework import try_import_tf
  from ray.rllib.utils.typing import ModelConfigDict, TensorType
label_desc: Use image node_id 5 for calling the DDPGTFModel obj's underlying member method code with example usage: obj.policy_variables() and returns: list