class_docstr: Abstract class for Backend Storage.
  This class defines the API interface for front ends to connect with various types of backends.
docstr: Fetch the run from backend store. The resulting :py:class:`Run <mlflow.entities.Run>`
  contains a collection of run metadata - :py:class:`RunInfo <mlflow.entities.RunInfo>`,
  as well as a collection of run parameters, tags, and metrics -
  :py:class:`RunData <mlflow.entities.RunData>`. In the case where multiple metrics with the
  same key are logged for the run, the :py:class:`RunData <mlflow.entities.RunData>` contains
  the value at the latest timestamp for each metric. If there are multiple values with the
  latest timestamp for a given metric, the maximum of these values is returned.
  
  :param run_id: Unique identifier for the run.
  
  :return: A single :py:class:`mlflow.entities.Run` object, if the run exists. Otherwise,
           raises an exception.
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code: def get_run(self, run_id):
      """
      Fetch the run from backend store. The resulting :py:class:`Run <mlflow.entities.Run>`
      contains a collection of run metadata - :py:class:`RunInfo <mlflow.entities.RunInfo>`,
      as well as a collection of run parameters, tags, and metrics -
      :py:class:`RunData <mlflow.entities.RunData>`. In the case where multiple metrics with the
      same key are logged for the run, the :py:class:`RunData <mlflow.entities.RunData>` contains
      the value at the latest timestamp for each metric. If there are multiple values with the
      latest timestamp for a given metric, the maximum of these values is returned.
  
      :param run_id: Unique identifier for the run.
  
      :return: A single :py:class:`mlflow.entities.Run` object, if the run exists. Otherwise,
               raises an exception.
      """
      pass
  
imports: from abc import ABCMeta, abstractmethod
  from typing import List, Optional
  from mlflow.entities import DatasetInput, ViewType
  from mlflow.store.entities.paged_list import PagedList
  from mlflow.store.tracking import SEARCH_MAX_RESULTS_DEFAULT
  from mlflow.utils.annotations import developer_stable, experimental
  from mlflow.utils.async_logging.async_logging_queue import AsyncLoggingQueue
  from mlflow.utils.async_logging.run_operations import RunOperations
label_desc: Use image node_id 9 for calling the AbstractStore obj's underlying member method code with example usage: obj.get_run(run_id) without return types