code: def test_log_prob_calcuation(model_class):
      model = model_class("MlpPolicy", IdentityEnvBox())
      # Fixed mean/std
      model.proba_step = Helper.proba_vals
      # Check that the log probability is the one expected for the given mean/std
      logprob = model.action_probability(
          observation=np.array([[0.5], [0.5]]), actions=0.2, logp=True
      )
      assert np.allclose(
          logprob, np.array([-16.616353440210627])
      ), "Calculation failed for {}".format(model_class)
  
imports: import pytest
  import numpy
  from stable_baselines import A2C, ACKTR, PPO1, PPO2, TRPO
  from stable_baselines.common.identity_env import IdentityEnvBox
label_desc: Use image node_id 1 for calling a global function with example usage: test_log_prob_calcuation(model_class) without return types