class_docstr: A model configuration describes the configuration of a GluonTS model and
  allows instantiating an estimator from it.
  
  Compared to an estimator, this configuration class can easily be hashed and
  different objects with the same configuration are considered equal under
  the `==` operator.
docstr: Returns whether predictions should be generated in parallel.
docstr_tok: ["Returns","whether","predictions","should","be","generated","in","parallel","."]
code: def prefers_parallel_predictions(self) -> bool:
      """
      Returns whether predictions should be generated in parallel.
      """
      return False
  
imports: from dataclasses import asdict, dataclass, MISSING
  from pathlib import Path
  from typing import Any, Dict, List, Optional, TypeVar
  from gluonts.model.estimator import Estimator
  from gluonts.model.predictor import Predictor
  from mxnet.gluon import nn
  from tsbench.config.dataset import DatasetConfig
  from tsbench.gluonts import TimedTrainer
  from tsbench.gluonts.callbacks import Callback
label_desc: Use image node_id 6 for calling the ModelConfig obj's underlying member method code with example usage: obj.prefers_parallel_predictions() and returns: False