docstr: Sets model weights for provided layer parameters.
  
  :param weights: list of model weights in the same order as received in get_weights
  :param rate: controls the mixture of given weight values versus old weight values.
      i.e. new_weight = rate * given_weight + (1 - rate) * old_weight
  :return: None
docstr_tok: ["Sets","model","weights","for","provided","layer","parameters",".",":","param","weights",":","list","of","model","weights","in","the","same","order","as","received","in","get_weights",":","param","rate",":","controls","the","mixture","of","given","weight","values","versus","old","weight","values",".","i.e",".","new_weight","=","rate","*","given_weight","+","(","1","-","rate",")","*","old_weight",":","return",":","None"]
code: def set_weights(
      self, weights: List[np.ndarray], rate: float = 1.0
  ) -> None:
      """
      Sets model weights for provided layer parameters.
  
      :param weights: list of model weights in the same order as received in get_weights
      :param rate: controls the mixture of given weight values versus old weight values.
          i.e. new_weight = rate * given_weight + (1 - rate) * old_weight
      :return: None
      """
      raise NotImplementedError
  
imports: from typing import Any, Dict, List, Tuple
  import numpy
  from rl_coach.base_parameters import AgentParameters
  from rl_coach.saver import SaverCollection
  from rl_coach.spaces import SpacesDefinition
label_desc: Use image node_id 7 for calling the Architecture obj's underlying member method code with example usage: obj.set_weights(weights, rate) without return types