code: def get_quantile_hyper_params(framework):
      """Parameters that currently can be searched during HPO"""
      hyper_params = get_hyper_params(framework)
      new_hyper_params = {
          "gamma": 5.0,  # margin loss weight which helps ensure noncrossing quantile estimates
          # Options: range(0.1, 10.0)
          "alpha": 0.01,  # used for smoothing huber pinball loss
      }
      hyper_params.update(new_hyper_params)
      return hyper_params
  
file_path: autogluon/tabular/src/autogluon/tabular/models/tabular_nn/hyperparameters/parameters.py
imports: from autogluon.core.constants import BINARY, MULTICLASS, QUANTILE, REGRESSION
label_desc: Use image node_id 3 for calling a global function with example usage: get_quantile_hyper_params(framework) and returns: hyper_params