code: def get_automm_presets(problem_type: str, presets: str):
      """
      Get the default hyperparameters and hyperparameter_tune_kwargs given problem type and presets.
  
      Parameters
      ----------
      problem_type
          Problem type.
      presets
          Name of a preset.
  
      Returns
      -------
      hyperparameters
          The hyperparameter overrides of this preset.
      hyperparameter_tune_kwargs
          Hyperparameter tuning strategy and kwargs (for example, how many HPO trials to run).
      """
      if not presets:
          presets = DEFAULT
      if presets == "hpo":
          presets = f"{DEFAULT}_{presets}"
      presets = presets.lower()
      if problem_type in [
          BINARY,
          MULTICLASS,
          REGRESSION,
          None,
      ]:
          problem_type = DEFAULT
  
      if problem_type in automm_presets.list_keys():
          (
              hyperparameters,
              hyperparameter_tune_kwargs,
          ) = automm_presets.create(problem_type, presets)
      else:
          raise ValueError(
              f"Problem type '{problem_type}' doesn't have any presets yet. "
              f"Consider one of these: {automm_presets.list_keys()}"
          )
  
      return hyperparameters, hyperparameter_tune_kwargs
  
imports: from typing import List, Optional
  from autogluon.common.utils.try_import import try_import_ray
  from .constants import BEST_QUALITY, BINARY, DATA, DEFAULT, ENVIRONMENT, HIGH_QUALITY, MEDIUM_QUALITY, MODEL, MULTICLASS, OPTIMIZATION, REGRESSION
  from .registry import Registry
label_desc: Use image node_id 18 for calling a global function with example usage: get_automm_presets(problem_type, presets) and returns: hyperparameters,  hyperparameter_tune_kwargs