code: def construct_model_templates(self, hyperparameters, **kwargs):
      path = kwargs.pop("path", self.path)
      problem_type = kwargs.pop("problem_type", self.problem_type)
      eval_metric = kwargs.pop("eval_metric", self.eval_metric)
      quantile_levels = kwargs.pop(
          "quantile_levels", self.quantile_levels
      )
      invalid_model_names = kwargs.pop(
          "invalid_model_names", self._get_banned_model_names()
      )
      silent = kwargs.pop("silent", self.verbosity < 3)
      ag_args_fit = kwargs.pop("ag_args_fit", None)
      if quantile_levels is not None:
          if ag_args_fit is None:
              ag_args_fit = dict()
          ag_args_fit = ag_args_fit.copy()
          ag_args_fit["quantile_levels"] = quantile_levels
  
      return get_preset_models(
          path=path,
          problem_type=problem_type,
          eval_metric=eval_metric,
          hyperparameters=hyperparameters,
          ag_args_fit=ag_args_fit,
          invalid_model_names=invalid_model_names,
          silent=silent,
          **kwargs,
      )
  
file_path: autogluon/tabular/src/autogluon/tabular/trainer/auto_trainer.py
imports: import logging
  from typing import Dict, List
  from autogluon.core.models import AbstractModel
  from autogluon.core.trainer.abstract_trainer import AbstractTrainer
  from autogluon.core.utils import generate_train_test_split
  from ..models.lgb.lgb_model import LGBModel
  from .model_presets.presets import MODEL_TYPES, get_preset_models
  from .model_presets.presets_distill import get_preset_models_distillation
label_desc: Use image node_id 1 for calling the AutoTrainer obj's underlying member method code with example usage: obj.construct_model_templates(hyperparameters) and returns: get_preset_models