docstr: Our policies can be loaded from pkl, but after unpickling you cannot continue training.
          
docstr_tok: ["Our","policies","can","be","loaded","from","pkl",",","but","after","unpickling","you","can","not","continue","training","."]
code: def __getstate__(self):
      """Our policies can be loaded from pkl, but after unpickling you cannot continue training."""
      excluded_subnames = [
          "_tf",
          "_op",
          "_vars",
          "_adam",
          "buffer",
          "sess",
          "_stats",
          "main",
          "target",
          "lock",
          "env",
          "sample_transitions",
          "stage_shapes",
          "create_actor_critic",
      ]
  
      state = {
          k: v
          for k, v in self.__dict__.items()
          if all([not subname in k for subname in excluded_subnames])
      }
      state["buffer_size"] = self.buffer_size
      state["tf"] = self.sess.run(
          [x for x in self._global_vars("") if "buffer" not in x.name]
      )
      return state
  
imports: from collections import OrderedDict
  import numpy
  import tensorflow
  from tensorflow.contrib.staging import StagingArea
  from baselines import logger
  from baselines.her.util import import_function, store_args, flatten_grads, transitions_in_episode_batch, convert_episode_to_batch_major
  from baselines.her.normalizer import Normalizer
  from baselines.her.replay_buffer import ReplayBuffer
  from baselines.common.mpi_adam import MpiAdam
  from baselines.common import tf_util
label_desc: Use image node_id 22 for calling the DDPG obj's underlying member method code with example usage: obj.__getstate__() and returns: state