class_docstr: An exploration that adds Ornstein-Uhlenbeck noise to continuous actions.
  
  If explore=True, returns sampled actions plus a noise term X,
  which changes according to this formula:
  Xt+1 = -theta*Xt + sigma*N[0,stddev], where theta, sigma and stddev are
  constants. Also, some completely random period is possible at the
  beginning.
  If explore=False, returns the deterministic action.
class_docstr_tok: ["An","exploration","that","adds","Ornstein-Uhlenbeck","noise","to","continuous","actions",".","If","explore=True",",","returns","sampled","actions","plus","a","noise","term","X",",","which","changes","according","to","this","formula",":","Xt+1","=","-theta","*","Xt","+","sigma","*","N","[","0",",","stddev","]",",","where","theta",",","sigma","and","stddev","are","constants",".","Also",",","some","completely","random","period","is","possible","at","the","beginning",".","If","explore=False",",","returns","the","deterministic","action","."]
docstr: Returns the current scale value.
  
  Returns:
      Union[float,tf.Tensor[float]]: The current scale value.
docstr_tok: ["Returns","the","current","scale","value",".","Returns",":","Union","[","float",",","tf.Tensor","[","float","]","]",":","The","current","scale","value","."]
code: def get_state(self, sess: Optional["tf.Session"] = None):
      """Returns the current scale value.
  
      Returns:
          Union[float,tf.Tensor[float]]: The current scale value.
      """
      if sess:
          return sess.run(
              dict(
                  self._tf_state_op,
                  **{
                      "ou_state": self.ou_state,
                  },
              )
          )
  
      state = super().get_state()
      return dict(
          state,
          **{
              "ou_state": convert_to_numpy(self.ou_state)
              if self.framework != "tf"
              else self.ou_state,
          },
      )
  
file_path: ray/python/ray/rllib/utils/exploration/ornstein_uhlenbeck_noise.py
imports: import numpy
  from typing import Optional, Union
  from ray.rllib.models.action_dist import ActionDistribution
  from ray.rllib.utils.annotations import override, PublicAPI
  from ray.rllib.utils.exploration.gaussian_noise import GaussianNoise
  from ray.rllib.utils.framework import try_import_tf, try_import_torch, get_variable, TensorType
  from ray.rllib.utils.numpy import convert_to_numpy
  from ray.rllib.utils.schedules import Schedule
  from ray.rllib.utils.tf_utils import zero_logps_from_actions
label_desc: Use image node_id 4 for calling the OrnsteinUhlenbeckNoise obj's underlying member method code with example usage: obj.get_state(sess) and returns: dict, sess