class_docstr: A RL2 policy after adaptation.
  
  Args:
      policy (garage.tf.policies.Policy): Policy itself.
class_docstr_tok: ["A","RL2","policy","after","adaptation",".","Args",":","policy","(","garage.tf.policies.Policy",")",":","Policy","itself","."]
docstr: Set param values.
  
  Args:
      params (Tuple[np.ndarray, np.ndarray]): Two numpy array of
          parameter values, one of the network parameters, one
          for the initial hidden state.
docstr_tok: ["Set","param","values",".","Args",":","params","(","Tuple","[","np.ndarray",",","np.ndarray","]",")",":","Two","numpy","array","of","parameter","values",",","one","of","the","network","parameters",",","one","for","the","initial","hidden","state","."]
code: def set_param_values(self, params):
      """Set param values.
  
      Args:
          params (Tuple[np.ndarray, np.ndarray]): Two numpy array of
              parameter values, one of the network parameters, one
              for the initial hidden state.
  
      """
      inner_params, hiddens = params
      self._policy.set_param_values(inner_params)
      self._initial_hiddens = hiddens
  
imports: import abc
  import collections
  import akro
  from dowel import logger
  import numpy
  from garage import EnvSpec, EnvStep, EpisodeBatch, log_multitask_performance, StepType, Wrapper
  from garage.np.algos import MetaRLAlgorithm
  from garage.sampler import DefaultWorker
  from garage.tf.algos._rl2npo import RL2NPO
label_desc: Use image node_id 5 for calling the RL2AdaptedPolicy obj's underlying member method code with example usage: obj.set_param_values(params) without return types