class_docstr: Model space that is specialized for benchmarking.
  
  We recommend using this model space for benchmarking, for its validation and efficiency.
  
  Parameters
  ----------
  model_space
      If not provided, it will be set to the default model space of the evaluator.
  evaluator
      Evaluator that will be used to benchmark the space.
  
  Examples
  --------
  Can be either::
  
      BenchmarkModelSpace(evaluator)
  
  or::
  
      BenchmarkModelSpace(pytorch_model_space, evaluator)
  
  In the case where the model space is provided, it will be validated by the evaluator and must be a match.
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code: def __init__(self, model_space: BaseModelSpace):
      ...
  
file_path: nni/nni/nas/benchmark/space.py
imports: from __future__ import annotations
  import logging
  from typing import TYPE_CHECKING, overload
  from nni.mutable import MutableDict
  from nni.nas.space import RawFormatModelSpace, BaseModelSpace
label_desc: Use image node_id 2 to create a new BenchmarkModelSpace object from inherited base classes: RawFormatModelSpace with example: obj = BenchmarkModelSpace(model_space)