code: def required_model_output_shape(action_space, model_config=None):
      custom_model_config = model_config["custom_model_config"] or {}
      if custom_model_config is not None and custom_model_config.get(
          "output_dim"
      ):
          return custom_model_config.get("output_dim")
      return action_space.shape
  
imports: from functools import partial
  from gymnasium.spaces import Box, Dict, Discrete, Tuple
  import numpy
  import unittest
  import ray
  from ray.rllib.models import ActionDistribution, ModelCatalog, MODEL_DEFAULTS
  from ray.rllib.models.preprocessors import Preprocessor, TupleFlatteningPreprocessor
  from ray.rllib.models.tf.tf_action_dist import MultiActionDistribution, TFActionDistribution
  from ray.rllib.models.tf.tf_modelv2 import TFModelV2
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.framework import try_import_tf, try_import_torch
  from ray.rllib.utils.spaces.space_utils import get_dummy_batch_for_space
  from ray.rllib.utils.torch_utils import convert_to_torch_tensor
label_desc: Use image node_id 2 for calling the CustomActionDistribution obj's underlying member method code with example usage: obj.required_model_output_shape(action_space, model_config) and returns: action_space, custom_model_config