class_docstr: Client of an MLflow Tracking Server that creates and manages experiments and runs.
class_docstr_tok: ["Client","of","an","MLflow","Tracking","Server","that","creates","and","manages","experiments","and","runs","."]
docstr: Set a run's status to terminated.
  
  :param status: A string value of :py:class:`mlflow.entities.RunStatus`.
                 Defaults to "FINISHED".
  :param end_time: If not provided, defaults to the current time.
docstr_tok: ["Set","a","run","'s","status","to","terminated",".",":","param","status",":","A","string","value","of",":","py",":","class",":","`","mlflow.entities.RunStatus","`",".","Defaults","to","``","FINISHED","''",".",":","param","end_time",":","If","not","provided",",","defaults","to","the","current","time","."]
code: def set_terminated(self, run_id, status=None, end_time=None):
      """Set a run's status to terminated.
  
      :param status: A string value of :py:class:`mlflow.entities.RunStatus`.
                     Defaults to "FINISHED".
      :param end_time: If not provided, defaults to the current time."""
      end_time = end_time if end_time else get_current_time_millis()
      status = (
          status if status else RunStatus.to_string(RunStatus.FINISHED)
      )
      self.store.update_run_info(
          run_id,
          run_status=RunStatus.from_string(status),
          end_time=end_time,
          run_name=None,
      )
  
imports: import os
  from collections import OrderedDict
  from itertools import zip_longest
  from typing import List, Optional
  from mlflow.entities import ExperimentTag, Metric, Param, RunStatus, RunTag, ViewType
  from mlflow.entities.dataset_input import DatasetInput
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE, ErrorCode
  from mlflow.store.artifact.artifact_repository_registry import get_artifact_repository
  from mlflow.store.tracking import GET_METRIC_HISTORY_MAX_RESULTS, SEARCH_MAX_RESULTS_DEFAULT
  from mlflow.tracking._tracking_service import utils
  from mlflow.tracking.metric_value_conversion_utils import convert_metric_value_to_float_if_possible
  from mlflow.utils import chunk_list
  from mlflow.utils.async_logging.run_operations import RunOperations, get_combined_run_operations
  from mlflow.utils.mlflow_tags import MLFLOW_USER
  from mlflow.utils.string_utils import is_string_type
  from mlflow.utils.time import get_current_time_millis
  from mlflow.utils.uri import add_databricks_profile_info_to_artifact_uri
  from mlflow.utils.validation import MAX_ENTITIES_PER_BATCH, MAX_METRICS_PER_BATCH, MAX_PARAMS_TAGS_PER_BATCH, PARAM_VALIDATION_MSG, _validate_experiment_artifact_location, _validate_run_id
label_desc: Use image node_id 27 for calling the TrackingServiceClient obj's underlying member method code with example usage: obj.set_terminated(run_id, status, end_time) without return types