class_docstr: The Catalog class used to build all the models needed for DreamerV3 training.
docstr: Initializes a DreamerV3Catalog instance.
  
  Args:
      observation_space: The observation space of the environment.
      action_space: The action space of the environment.
      model_config_dict: The model config to use.
docstr_tok: ["Initializes","a","DreamerV3Catalog","instance",".","Args",":","observation_space",":","The","observation","space","of","the","environment",".","action_space",":","The","action","space","of","the","environment",".","model_config_dict",":","The","model","config","to","use","."]
code: def __init__(
      self,
      observation_space: gym.Space,
      action_space: gym.Space,
      model_config_dict: dict,
  ):
      """Initializes a DreamerV3Catalog instance.
  
      Args:
          observation_space: The observation space of the environment.
          action_space: The action space of the environment.
          model_config_dict: The model config to use.
      """
      super().__init__(
          observation_space=observation_space,
          action_space=action_space,
          model_config_dict=model_config_dict,
      )
  
      self.model_size = self._model_config_dict["model_size"]
      self.is_img_space = len(self.observation_space.shape) in [2, 3]
      self.is_gray_scale = (
          self.is_img_space and len(self.observation_space.shape) == 2
      )
  
file_path: ray/python/ray/rllib/algorithms/dreamerv3/dreamerv3_catalog.py
imports: import gymnasium
  from ray.rllib.core.models.catalog import Catalog
  from ray.rllib.core.models.base import Encoder, Model
  from ray.rllib.utils import override
label_desc: Use image node_id 1 to create a new DreamerV3Catalog object from inherited base classes: Catalog with example: obj = DreamerV3Catalog(observation_space, action_space, model_config_dict)