class_docstr: Attributes determining groups of Instances we want to be aggregating over.
code: def from_metric_name(cls, metric_name: MetricName):
      return cls(
          split=metric_name.split,
          sub_split=metric_name.sub_split,
          perturbation=metric_name.perturbation,
      )
  
file_path: H2O/h2o_hf/helm/src/helm/benchmark/metrics/metric_name.py
imports: from dataclasses import dataclass
  from typing import Optional
  from helm.benchmark.augmentations.perturbation_description import PerturbationDescription
  from helm.benchmark.scenarios.scenario import Instance
label_desc: Use image node_id 2 for calling the MetricContext obj's underlying member method code with example usage: obj.from_metric_name(cls, metric_name) and returns: cls