class_docstr: Simple Vanilla Policy Gradient.
  
  Args:
      env_spec (EnvSpec): Environment specification.
      policy (garage.tf.policies.StochasticPolicy): Policy.
      sampler (garage.sampler.Sampler): Sampler.
class_docstr_tok: ["Simple","Vanilla","Policy","Gradient",".","Args",":","env_spec","(","EnvSpec",")",":","Environment","specification",".","policy","(","garage.tf.policies.StochasticPolicy",")",":","Policy",".","sampler","(","garage.sampler.Sampler",")",":","Sampler","."]
docstr: Parameters to restore from snapshot.
  
  Args:
      state (dict): Parameters to restore from.
docstr_tok: ["Parameters","to","restore","from","snapshot",".","Args",":","state","(","dict",")",":","Parameters","to","restore","from","."]
code: def __setstate__(self, state):
      """Parameters to restore from snapshot.
  
      Args:
          state (dict): Parameters to restore from.
  
      """
      self.__dict__ = state
      self.init_opt()
  
file_path: garage/src/garage/examples/tf/tutorial_vpg.py
imports: import numpy
  import tensorflow
  from garage import EpisodeBatch, log_performance, wrap_experiment
  from garage.envs import PointEnv
  from garage.experiment.deterministic import set_seed
  from garage.np import discount_cumsum
  from garage.sampler import LocalSampler
  from garage.tf.policies import GaussianMLPPolicy
  from garage.trainer import TFTrainer
label_desc: Use image node_id 6 for calling the SimpleVPG obj's underlying member method code with example usage: obj.__setstate__(state) without return types