class_docstr: In-memory container for the trials that the algorithm suggests/observes/etc.
  
  This behaves a bit like a managed dictionary, but the "keys" are trials ids, which
  (at the time of writing) can vary depending on how we chose to compute them.
class_docstr_tok: ["In-memory","container","for","the","trials","that","the","algorithm","suggests\/observes\/etc",".","This","behaves","a","bit","like","a","managed","dictionary",",","but","the","``","keys","''","are","trials","ids",",","which","(","at","the","time","of","writing",")","can","vary","depending","on","how","we","chose","to","compute","them","."]
docstr: Get the equivalent trial from the registry.
  
  If `trial` isn't in the registry, raises a RuntimeError.
docstr_tok: ["Get","the","equivalent","trial","from","the","registry",".","If","`","trial","`","is","n't","in","the","registry",",","raises","a","RuntimeError","."]
code: def get_existing(self, trial: Trial) -> Trial:
      """Get the equivalent trial from the registry.
  
      If `trial` isn't in the registry, raises a RuntimeError.
      """
      trial_id = _get_id(trial)
      if trial_id not in self:
          raise RuntimeError(
              f"Trial `{trial}` isn't in the registry (id={trial_id})"
          )
      return self[trial_id]
  
imports: from __future__ import annotations
  import copy
  from collections import defaultdict
  from logging import getLogger
  from typing import Any, Container, Iterable, Iterator, Mapping
  from orion.core.worker.trial import Trial, TrialCM
label_desc: Use image node_id 12 for calling the Registry obj's underlying member method code with example usage: obj.get_existing(trial) and returns: self