class_docstr: Convert all metric names to canonical name as specified on a
  multi_type_experiment.
  
  For example, a multi-type experiment may have an offline simulator which attempts to
  approximate observations from some online system. We want to map the offline
  metric names to the corresponding online ones so the model can associate them.
  
  This is done by replacing metric names in the data with the corresponding
  online metric names.
  
  In the inverse transform, data will be mapped back onto the original metric names.
  By default, this transform is turned off. It can be enabled by passing the
  "perform_untransform" flag to the config.
code: def untransform_observations(
      self,
      observations: List[Observation],
  ) -> List[Observation]:
      if not self.perform_untransform:
          return observations
      for obs in observations:
          trial_index = int(not_none(obs.features.trial_index))
          trial_type = self.trial_index_to_type[trial_index]
          reverse_map = self.reverse_metric_name_map.get(trial_type)
  
          if not reverse_map:
              continue
  
          for j in range(len(obs.data.metric_names)):
              if obs.data.metric_names[j] in reverse_map:
                  obs.data.metric_names[j] = reverse_map[
                      obs.data.metric_names[j]
                  ]
      return observations
  
file_path: Ax/ax/modelbridge/transforms/convert_metric_names.py
imports: from typing import Dict, List, Optional, TYPE_CHECKING
  from ax.core.multi_type_experiment import MultiTypeExperiment
  from ax.core.observation import Observation, ObservationData
  from ax.core.search_space import SearchSpace
  from ax.modelbridge.transforms.base import Transform
  from ax.models.types import TConfig
  from ax.utils.common.docutils import copy_doc
  from ax.utils.common.typeutils import not_none
label_desc: Use image node_id 3 for calling the ConvertMetricNames obj's underlying member method code with example usage: obj.untransform_observations(observations) and returns: observations, observations