code: def __init__(self, num_states, num_actions, hidden_size):
      super(ActorCritic, self).__init__()
  
      self.num_actions = num_actions
      self.fc = nn.Linear(num_states, hidden_size)
      self.critic_linear2 = nn.Linear(hidden_size, 1)
      self.actor_linear2 = nn.Linear(hidden_size, num_actions)
  
imports: import math
  import random
  import logging
  import copy
  import torch
  from torch import optim
  from torch import nn
  import torch.nn.functional
  import numpy
  import nni
  from nni.tuner import Tuner
label_desc: Use image node_id 1 to create a new ActorCritic object from inherited base classes: nn with example: obj = ActorCritic(num_states, num_actions, hidden_size)