class_docstr: Write me
      
code: def process_state_batch(self, batch):
      batch = np.array(batch)
      if self.processor is None:
          return batch
      return self.processor.process_state_batch(batch)
  
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 2 for calling the AbstractDQNAgent obj's underlying member method code with example usage: obj.process_state_batch(batch) and returns: self, batch