def _maybe_set_run_terminated(active_run, status):
"""
If the passed-in active run is defined and still running (i.e. hasn't already been terminated
within user code), mark it as terminated with the passed-in status.
"""
if active_run and not RunStatus.is_terminated(active_run.get_run().info.status):
active_run.set_terminated(status)
def _validate_autologging_run(autologging_integration, run_id):
"""
For testing purposes, verifies that an MLflow run produced by an `autologging_integration`
satisfies the following properties:
- The run has an autologging tag whose value is the name of the autologging integration
- The run has a terminal status (e.g., KILLED, FAILED, FINISHED)
"""
client = MlflowClient()
run = client.get_run(run_id)
autologging_tag_value = run.data.tags.get(MLFLOW_AUTOLOGGING)
assert autologging_tag_value == autologging_integration, (
"Autologging run with id {} failed to set autologging tag with expected value. Expected: "
"'{}', Actual: '{}'".format(run_id, autologging_integration, autologging_tag_value)
)
assert RunStatus.is_terminated(
RunStatus.from_string(run.info.status)
), "Autologging run with id {} has a non-terminal status '{}'".format(run_id, run.info.status)
