code: def compute_actions(
      self, obs_batch=None, add_noise=False, update=True, **kwargs
  ):
      if "observation" in kwargs:
          assert obs_batch is None, (
              "You can not use both arguments, "
              "`observation` and `obs_batch`. `observation` "
              "is deprecated."
          )
          deprecation_warning(
              old="ARSTFPolicy.compute_actions(observation=...)`",
              new="ARSTFPolicy.compute_actions(obs_batch=...)",
          )
          obs_batch = kwargs["observation"]
      else:
          assert obs_batch is not None
      # Squeeze batch dimension (we always calculate actions for only a
      # single obs).
      observation = obs_batch[0]
      observation = self.preprocessor.transform(observation)
      observation = self.observation_filter(
          observation[None], update=update
      )
  
      # `actions` is a list of (component) batches.
      # Eager mode.
      if not self.sess:
          dist_inputs, _ = self.model(
              {SampleBatch.CUR_OBS: observation}
          )
          dist = self.dist_class(dist_inputs, self.model)
          actions = dist.sample()
          actions = tree.map_structure(lambda a: a.numpy(), actions)
      # Graph mode.
      else:
          actions = self.sess.run(
              self.sampler, feed_dict={self.inputs: observation}
          )
  
      actions = unbatch(actions)
      if add_noise and isinstance(self.action_space, gym.spaces.Box):
          actions += (
              np.random.randn(*actions.shape) * self.action_noise_std
          )
      return actions, [], {}
  
imports: import gymnasium
  import numpy
  import tree
  import ray
  import ray.experimental.tf_utils
  from ray.rllib.algorithms.es.es_tf_policy import make_session
  from ray.rllib.models import ModelCatalog
  from ray.rllib.policy.policy import Policy
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils import deprecation_warning
  from ray.rllib.utils.filter import get_filter
  from ray.rllib.utils.framework import try_import_tf
  from ray.rllib.utils.spaces.space_utils import unbatch
label_desc: Use image node_id 2 for calling the ARSTFPolicy obj's underlying member method code with example usage: obj.compute_actions(obs_batch, add_noise, update) and returns: actions,  list,  dict