class_docstr: An exploration that adds white noise to continuous actions.
  
  If explore=True, returns actions plus scale (annealed over time) x
  Gaussian noise. Also, some completely random period is possible at the
  beginning.
  
  If explore=False, returns the deterministic action.
class_docstr_tok: ["An","exploration","that","adds","white","noise","to","continuous","actions",".","If","explore=True",",","returns","actions","plus","scale","(","annealed","over","time",")","x","Gaussian","noise",".","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(self._tf_state_op)
      scale = self.scale_schedule(self.last_timestep)
      return {
          "cur_scale": convert_to_numpy(scale)
          if self.framework != "tf"
          else scale,
          "last_timestep": convert_to_numpy(self.last_timestep)
          if self.framework != "tf"
          else self.last_timestep,
      }
  
imports: from gymnasium.spaces import Space
  import numpy
  from typing import Union, Optional
  from ray.rllib.models.action_dist import ActionDistribution
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.utils.annotations import override, PublicAPI
  from ray.rllib.utils.exploration.exploration import Exploration
  from ray.rllib.utils.exploration.random import Random
  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.schedules.piecewise_schedule import PiecewiseSchedule
  from ray.rllib.utils.tf_utils import zero_logps_from_actions
label_desc: Use image node_id 5 for calling the GaussianNoise obj's underlying member method code with example usage: obj.get_state(sess) and returns: dict, sess