class_docstr: Implements adaptive parameter noise
  
  :param initial_stddev: (float) the initial value for the standard deviation of the noise
  :param desired_action_stddev: (float) the desired value for the standard deviation of the noise
  :param adoption_coefficient: (float) the update coefficient for the standard deviation of the noise
class_docstr_tok: ["Implements","adaptive","parameter","noise",":","param","initial_stddev",":","(","float",")","the","initial","value","for","the","standard","deviation","of","the","noise",":","param","desired_action_stddev",":","(","float",")","the","desired","value","for","the","standard","deviation","of","the","noise",":","param","adoption_coefficient",":","(","float",")","the","update","coefficient","for","the","standard","deviation","of","the","noise"]
code: def __repr__(self):
      fmt = "AdaptiveParamNoiseSpec(initial_stddev={}, desired_action_stddev={}, adoption_coefficient={})"
      return fmt.format(
          self.initial_stddev,
          self.desired_action_stddev,
          self.adoption_coefficient,
      )
  
imports: from abc import ABC, abstractmethod
  import numpy
label_desc: Use image node_id 4 for calling the AdaptiveParamNoiseSpec obj's underlying member method code with example usage: obj.__repr__() and returns: fmt