class_docstr: Write me
      
code: def choose_weights(self):
      mean = self.theta[: self.num_weights]
      std = self.theta[self.num_weights :]
      weights_flat = std * np.random.randn(self.num_weights) + mean
  
      sampled_weights = self.get_weights_list(weights_flat)
      self.model.set_weights(sampled_weights)
  
imports: from __future__ import division
  from collections import deque
  from copy import deepcopy
  import numpy
  import keras.backend
  from keras.models import Model
  from rl.core import Agent
  from rl.util import *
label_desc: Use image node_id 10 for calling the CEMAgent obj's underlying member method code with example usage: obj.choose_weights() without return types