class_docstr: A job provides data available for a single training job.
  
  It is first obtained from a training job run on AWS Sagemaker. By storing
  it locally, it can be loaded from the file system at a later point and no
  Sagemaker connection is required. The initializer of this class should not
  be used directly.
class_docstr_tok: ["A","job","provides","data","available","for","a","single","training","job",".","It","is","first","obtained","from","a","training","job","run","on","AWS","Sagemaker",".","By","storing","it","locally",",","it","can","be","loaded","from","the","file","system","at","a","later","point","and","no","Sagemaker","connection","is","required",".","The","initializer","of","this","class","should","not","be","used","directly","."]
docstr: Returns the hyperparameters associated with the job.
docstr_tok: ["Returns","the","hyperparameters","associated","with","the","job","."]
code: def hyperparameters(self) -> dict[str, Any]:
      """
      Returns the hyperparameters associated with the job.
      """
      return self.config["hyperparameters"]
  
imports: from __future__ import annotations
  import json
  import math
  import os
  import shutil
  from pathlib import Path
  from typing import Any, cast, Dict, List, Optional, Union
  import numpy
  from tsbench.config import MODEL_REGISTRY
  from tsbench.evaluations.aws import Analysis, TrainingJob
  from tsbench.evaluations.metrics import Metric, Performance
  from tsbench.forecasts import QuantileForecasts
label_desc: Use image node_id 4 for calling the Job obj's underlying member method code with example usage: obj.hyperparameters() and returns: self