class_docstr: Write me
      
code: def compute_batch_q_values(self, state_batch):
      batch = self.process_state_batch(state_batch)
      q_values = self.model.predict_on_batch(batch)
      assert q_values.shape == (len(state_batch), self.nb_actions)
      return q_values
  
imports: from __future__ import division
  import warnings
  import keras.backend
  from keras.models import Model
  from keras.layers import Lambda, Input, Layer, Dense
  from rl.core import Agent
  from rl.policy import EpsGreedyQPolicy, GreedyQPolicy
  from rl.util import *
label_desc: Use image node_id 3 for calling the AbstractDQNAgent obj's underlying member method code with example usage: obj.compute_batch_q_values(state_batch) and returns: q_values