code: def forward(self, obs, **kwargs):
      obs = to_torch(obs, device=self.linear.weight.device)
      steps_onehot = nn.functional.one_hot(
          obs["cur_step"].long(), self.input_dim
      ).float()
      return self.linear(steps_onehot)
  
imports: from __future__ import annotations
  import pytest
  import nni
  from nni.mutable import *
  from nni.nas.evaluator import FunctionalEvaluator
  from nni.nas.execution import SequentialExecutionEngine
  from nni.nas.space import *
  from nni.nas.strategy import GridSearch, Random, RegularizedEvolution, PolicyBasedRL
  import torch
  from torch import nn
  from tianshou.policy import A2CPolicy
  from tianshou.data import to_torch
label_desc: Use image node_id 2 for calling the CriticNetwork obj's underlying member method code with example usage: obj.forward(obs) and returns: self