class_docstr: The tracker may be used to obtain the performance metrics from a set of
  evaluations.
code: def get_evaluations(self) -> Evaluations[ModelConfig]:
      return Evaluations(
          [info.config for info in self.infos],
          [info.performance for info in self.infos],
      )
  
imports: from __future__ import annotations
  import pickle
  from pathlib import Path
  from typing import Any, List, Optional
  from tsbench.config import Config, ModelConfig
  from tsbench.constants import DEFAULT_DATA_PATH
  from tsbench.evaluations import aws
  from tsbench.evaluations.metrics import Performance
  from tsbench.forecasts.quantile import QuantileForecasts
  from ._base import Tracker
  from ._evaluations import Evaluations
  from ._info import extract_job_infos, ValidationMetric, ValidationScores
  from .job import Job, load_jobs_from_analysis, load_jobs_from_directory
label_desc: Use image node_id 4 for calling the ModelTracker obj's underlying member method code with example usage: obj.get_evaluations() and returns: Evaluations