class_docstr: Write me
      
class_docstr_tok: ["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
  from collections import deque
  import os
  import warnings
  import numpy
  import keras.backend
  import keras.optimizers
  from rl.core import Agent
  from rl.random import OrnsteinUhlenbeckProcess
  from rl.util import *
label_desc: Use image node_id 8 for calling the DDPGAgent obj's underlying member method code with example usage: obj.process_state_batch(batch) and returns: self, batch