class_docstr: Informations of each trial from one model inference
class_docstr_tok: ["Informations","of","each","trial","from","one","model","inference"]
docstr: Convert shape
docstr_tok: ["Convert","shape"]
code: def convert_shape(self):
      """
      Convert shape
      """
  
      def sf01(arr):
          """
          swap and then flatten axes 0 and 1
          """
          s = arr.shape
          return arr.swapaxes(0, 1).reshape(s[0] * s[1], *s[2:])
  
      self.obs = sf01(self.obs)
      self.returns = sf01(self.returns)
      self.dones = sf01(self.dones)
      self.actions = sf01(self.actions)
      self.values = sf01(self.values)
      self.neglogpacs = sf01(self.neglogpacs)
  
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 4 for calling the TrialsInfo obj's underlying member method code with example usage: obj.convert_shape() and returns: arr