class_docstr: A recommender uses a surrogate to recommend models and their configurations
  based on desired target metrics.
  
  This class implements the general interface.
docstr: The number of CPUs required for fitting the recommender.
docstr_tok: ["The","number","of","CPUs","required","for","fitting","the","recommender","."]
code: def required_cpus(self) -> int:
      """
      The number of CPUs required for fitting the recommender.
      """
      return 1
  
file_path: gluonts/src/gluonts/nursery/tsbench/src/tsbench/recommender/_base.py
imports: from abc import ABC
  from typing import cast, Generic, List, Optional, TypeVar
  from tsbench.config import Config, DatasetConfig, EnsembleConfig, ModelConfig
  from tsbench.evaluations.metrics import Performance
  from ._recommendation import Recommendation
  from .generator import CandidateGenerator, ReplayCandidateGenerator
  from .utils import argsort_nondominated
label_desc: Use image node_id 2 for calling the Recommender obj's underlying member method code with example usage: obj.required_cpus() and returns: int