code: def test_optimization_step(self):
      num_outputs = 4
      trn_data = self.generate_random_data(num_actions=num_outputs)
      clip_param = 0.1
      vf_coeff = 0.5
      entropy_coeff = 0.01
      batch_size = 256
      module = models.ActorCritic(num_outputs)
      initial_params = ppo_lib.get_initial_params(
          jax.random.key(0), module
      )
      config = ml_collections.ConfigDict(
          {
              "learning_rate": 2.5e-4,
              "decaying_lr_and_clip_param": True,
          }
      )
      state = ppo_lib.create_train_state(
          initial_params, module, config, 1000
      )
      state, _ = ppo_lib.train_step(
          state,
          trn_data,
          batch_size,
          clip_param=clip_param,
          vf_coeff=vf_coeff,
          entropy_coeff=entropy_coeff,
      )
      self.assertIsInstance(state, train_state.TrainState)
  
imports: from absl.testing import absltest
  from flax.training import train_state
  import jax
  import ml_collections
  import numpy
  import numpy.testing
  import agent
  import env_utils
  import models
  import ppo_lib
label_desc: Use image node_id 2 for calling the TestOptimizationStep obj's underlying member method code with example usage: obj.test_optimization_step() without return types