o `Û·i´ã@sfddlmZmZmZmZddlmZddlmZddl m Z e Gdd„dƒƒZ e Gdd„de ƒƒZ d S) é)ÚAnyÚDictÚListÚOptional)Ú Checkpoint)ÚTrainRunContext)Ú DeveloperAPIc@seZdZdZdS)ÚRayTrainCallbackz"Base Ray Train callback interface.N)Ú__name__Ú __module__Ú __qualname__Ú__doc__©rrúO/home/ubuntu/vllm_env/lib/python3.10/site-packages/ray/train/v2/api/callback.pyr sr c@sPeZdZdZdedeeeefde e fdd„Z dedee e ffdd „Zd S) Ú UserCallbackzÄCallback interface for custom user-defined callbacks to handling events during training. This callback is called on the Ray Train controller process, not on the worker processes. Ú run_contextÚmetricsÚ checkpointcCódS)a*Called after all workers have reported a metric + checkpoint via `ray.train.report`. Args: run_context: The `TrainRunContext` for the current training run. metrics: A list of metric dictionaries reported by workers, where metrics[i] is the metrics dict reported by worker i. checkpoint: A Checkpoint object that has been persisted to storage. This is None if no workers reported a checkpoint (e.g. `ray.train.report(metrics, checkpoint=None)`). Nr)ÚselfrrrrrrÚ after_reportszUserCallback.after_reportÚworker_exceptionscCr)aCalled after one or more workers have raised an exception. Args: run_context: The `TrainRunContext` for the current training run. worker_exceptions: A dict from worker world rank to the exception raised by that worker. Nr)rrrrrrÚafter_exception+s zUserCallback.after_exceptionN)r r r r rrrÚstrrrrrÚintÚ Exceptionrrrrrrsþý üÿ ÿrN) ÚtypingrrrrÚ ray.trainrÚ(ray.train.v2._internal.execution.contextrÚray.util.annotationsrr rrrrrÚs