code: def skip_hpo(model, X, y, X_val, y_val, time_limit=None, **kwargs):
      """Skips HPO and simply trains the model once with the provided HPO time budget. Returns model artifacts as if from HPO."""
      fit_model_args = dict(X=X, y=y, **kwargs)
      predict_proba_args = dict(X=X_val)
      fit_and_save_model(
          model=model,
          fit_args=fit_model_args,
          predict_proba_args=predict_proba_args,
          y_val=y_val,
          time_start=time.time(),
          time_limit=time_limit,
      )
      hpo_results = {"total_time": model.fit_time}
      hpo_model_performances = {model.name: model.val_score}
      hpo_results["hpo_model_performances"] = hpo_model_performances
      hpo_models = {model.name: {"path": model.path}}
      return hpo_models, hpo_results
  
file_path: autogluon/core/src/autogluon/core/models/abstract/model_trial.py
imports: import logging
  import os
  import time
  from ...hpo.constants import CUSTOM_BACKEND, RAY_BACKEND, VALID_BACKEND
  from ...utils.exceptions import TimeLimitExceeded
  from ...utils.loaders import load_pkl
label_desc: Use image node_id 4 for calling a global function with example usage: skip_hpo(model, X, y, X_val, y_val, time_limit) and returns: hpo_models,  hpo_results