code: def setup(self):
      # Gather model-relevant settings.
      B = 1
      T = self.config.model_config_dict["batch_length_T"]
      horizon_H = self.config.model_config_dict["horizon_H"]
      gamma = self.config.model_config_dict["gamma"]
      symlog_obs = do_symlog_obs(
          self.config.observation_space,
          self.config.model_config_dict.get("symlog_obs", "auto"),
      )
      model_size = self.config.model_config_dict["model_size"]
  
      if self.config.model_config_dict["use_float16"]:
          tf.compat.v1.keras.layers.enable_v2_dtype_behavior()
          tf.keras.mixed_precision.set_global_policy("mixed_float16")
  
      # Build encoder and decoder from catalog.
      catalog = self.config.get_catalog()
      self.encoder = catalog.build_encoder(framework=self.framework)
      self.decoder = catalog.build_decoder(framework=self.framework)
  
      # Build the world model (containing encoder and decoder).
      self.world_model = WorldModel(
          model_size=model_size,
          observation_space=self.config.observation_space,
          action_space=self.config.action_space,
          batch_length_T=T,
          encoder=self.encoder,
          decoder=self.decoder,
          symlog_obs=symlog_obs,
      )
      self.actor = ActorNetwork(
          action_space=self.config.action_space,
          model_size=model_size,
      )
      self.critic = CriticNetwork(
          model_size=model_size,
      )
      # Build the final dreamer model (containing the world model).
      self.dreamer_model = DreamerModel(
          model_size=self.config.model_config_dict["model_size"],
          action_space=self.config.action_space,
          world_model=self.world_model,
          actor=self.actor,
          critic=self.critic,
          horizon=horizon_H,
          gamma=gamma,
      )
      self.action_dist_cls = catalog.get_action_dist_cls(
          framework=self.framework
      )
  
      # Perform a test `call()` to force building the dreamer model's variables.
      test_obs = np.tile(
          np.expand_dims(
              self.config.observation_space.sample(), (0, 1)
          ),
          reps=(B, T) + (1,) * len(self.config.observation_space.shape),
      )
      if isinstance(self.config.action_space, gym.spaces.Discrete):
          test_actions = np.tile(
              np.expand_dims(
                  one_hot(
                      self.config.action_space.sample(),
                      depth=self.config.action_space.n,
                  ),
                  (0, 1),
              ),
              reps=(B, T, 1),
          )
      else:
          test_actions = np.tile(
              np.expand_dims(self.config.action_space.sample(), (0, 1)),
              reps=(B, T, 1),
          )
  
      self.dreamer_model(
          None,
          _convert_to_tf(test_obs, dtype=tf.float32),
          _convert_to_tf(test_actions, dtype=tf.float32),
          _convert_to_tf(np.ones((B, T)), dtype=tf.bool),
          _convert_to_tf(np.zeros((B * T,)), dtype=tf.bool),
      )
  
      # Initialize the critic EMA net:
      self.critic.init_ema()
  
imports: import abc
  import gymnasium
  import numpy
  from ray.rllib.algorithms.dreamerv3.utils import do_symlog_obs
  from ray.rllib.algorithms.dreamerv3.tf.models.actor_network import ActorNetwork
  from ray.rllib.algorithms.dreamerv3.tf.models.critic_network import CriticNetwork
  from ray.rllib.algorithms.dreamerv3.tf.models.dreamer_model import DreamerModel
  from ray.rllib.algorithms.dreamerv3.tf.models.world_model import WorldModel
  from ray.rllib.core.models.base import STATE_IN, STATE_OUT
  from ray.rllib.core.models.specs.specs_dict import SpecDict
  from ray.rllib.core.rl_module.rl_module import RLModule
  from ray.rllib.policy.eager_tf_policy import _convert_to_tf
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.annotations import ExperimentalAPI, override
  from ray.rllib.utils.framework import try_import_tf
  from ray.rllib.utils.nested_dict import NestedDict
  from ray.rllib.utils.numpy import one_hot
label_desc: Use image node_id 1 for calling the DreamerV3RLModule obj's underlying member method code with example usage: obj.setup() without return types