class_docstr: The Catalog class used to build all the models needed for DreamerV3 training.
docstr: Builds the World-Model's decoder network depending on the obs space.
docstr_tok: ["Builds","the","World-Model","'s","decoder","network","depending","on","the","obs","space","."]
code: def build_decoder(self, framework: str) -> Model:
      """Builds the World-Model's decoder network depending on the obs space."""
      if framework != "tf2":
          raise NotImplementedError
  
      if self.is_img_space:
          from ray.rllib.algorithms.dreamerv3.tf.models.components import (
              conv_transpose_atari,
          )
  
          return conv_transpose_atari.ConvTransposeAtari(
              model_size=self.model_size,
              gray_scaled=self.is_gray_scale,
          )
      else:
          from ray.rllib.algorithms.dreamerv3.tf.models.components import (
              vector_decoder,
          )
  
          return vector_decoder.VectorDecoder(
              model_size=self.model_size,
              observation_space=self.observation_space,
          )
  
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 3 for calling the DreamerV3Catalog obj's underlying member method code with example usage: obj.build_decoder(framework) and returns: conv_transpose_atari, vector_decoder