class_docstr: Informations of each trial from one model inference
class_docstr_tok: ["Informations","of","each","trial","from","one","model","inference"]
code: def __init__(
      self,
      obs,
      actions,
      values,
      neglogpacs,
      dones,
      last_value,
      inf_batch_size,
  ):
      self.iter = 0
      self.obs = obs
      self.actions = actions
      self.values = values
      self.neglogpacs = neglogpacs
      self.dones = dones
      self.last_value = last_value
  
      self.rewards = None
      self.returns = None
  
      self.inf_batch_size = inf_batch_size
  
imports: import copy
  import logging
  import numpy
  from gym import spaces
  from schema import Schema, Optional
  import nni
  from nni import ClassArgsValidator
  from nni.tuner import Tuner
  from nni.utils import OptimizeMode, extract_scalar_reward
  from .model import Model
  from .util import set_global_seeds
  from .policy import build_lstm_policy
label_desc: Use image node_id 1 to create a new TrialsInfo object  with example: obj = TrialsInfo(obs, actions, values, neglogpacs, dones, last_value, inf_batch_size)