class_docstr: An RLModule that always knows the current EpisodeID and EnvID and
  returns these in its actions.
class_docstr_tok: ["An","RLModule","that","always","knows","the","current","EpisodeID","and","EnvID","and","returns","these","in","its","actions","."]
code: def _random_forward(self, batch, **kwargs):
      batch = super()._random_forward(batch, **kwargs)
      batch[SampleBatch.ACTIONS] = np.array(batch[SampleBatch.ACTIONS])
      batch[STATE_OUT] = np.array(
          [
              [self.state_space.sample()]
              for a in batch[SampleBatch.ACTIONS]
          ]
      )
      return batch
  
file_path: ray/rllib/examples/rl_module/episode_env_aware_rlm.py
imports: import numpy
  from gymnasium.spaces import Box
  from ray.rllib.utils.annotations import override
  from ray.rllib.core.rl_module import RLModule
  from ray.rllib.examples.rl_module.random_rl_module import RandomRLModule
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.core.models.base import STATE_OUT
label_desc: Use image node_id 4 for calling the StatefulRandomRLModule obj's underlying member method code with example usage: obj._random_forward(batch) and returns: batch