code: def __init__(self, config: RLModuleConfig):
      if not isinstance(config.observation_space, gym.spaces.Dict):
          raise ValueError(
              "This model requires the environment to provide a "
              "gym.spaces.Dict observation space."
          )
      # We need to adjust the observation space for this RL Module so that, when
      # building the default models, the RLModule does not "see" the action mask but
      # only the original observation space without the action mask. This tricks it
      # into building models that are compatible with the original observation space.
      config.observation_space = config.observation_space[
          "observations"
      ]
  
      # The PPORLModule, in its constructor, will build models for the modified
      # observation space.
      super().__init__(config)
  
imports: import gymnasium
  from ray.rllib.algorithms.ppo.tf.ppo_tf_rl_module import PPOTfRLModule
  from ray.rllib.algorithms.ppo.torch.ppo_torch_rl_module import PPOTorchRLModule
  from ray.rllib.core.rl_module.rl_module import RLModule, RLModuleConfig
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.framework import try_import_torch, try_import_tf
  from ray.rllib.utils.torch_utils import FLOAT_MIN
label_desc: Use image node_id 1 to create a new ActionMaskRLMBase object from inherited base classes: RLModule with example: obj = ActionMaskRLMBase(config)