python/ray/serve/deployment_state.py
def _recover_from_checkpoint(self, all_current_actor_names: List[str]) -> None:
        """
        Recover from checkpoint upon controller failure with all actor names
        found in current cluster.

        Each deployment resumes target state from checkpoint if available.

        For current state it will prioritize reconstructing from current
        actor names found that matches deployment tag if applicable.
        """
        deployment_to_current_replicas = self._map_actor_names_to_deployment(
            all_current_actor_names
        )
        checkpoint = self._kv_store.get(CHECKPOINT_KEY)
        if checkpoint is not None:
            (
                deployment_state_info,
                self._deleted_deployment_metadata,
            ) = cloudpickle.loads(checkpoint)

            for deployment_tag, checkpoint_data in deployment_state_info.items():
                deployment_state = self._create_deployment_state(deployment_tag)

                target_state_checkpoint = checkpoint_data
                deployment_state.recover_target_state_from_checkpoint(
                    target_state_checkpoint
                )
                if len(deployment_to_current_replicas[deployment_tag]) > 0:
                    deployment_state.recover_current_state_from_replica_actor_names(  # noqa: E501
                        deployment_to_current_replicas[deployment_tag]
                    )
                self._deployment_states[deployment_tag] = deployment_state

        Recover from checkpoint upon controller failure with all actor names
        found in current cluster.

        Each deployment resumes target state from checkpoint if available.

        For current state it will prioritize reconstructing from current
        actor names found that matches deployment tag if applicable.
        
Recover from checkpoint upon controller failure with all actor names
found in current cluster.

Each deployment resumes target state from checkpoint if available.

For current state it will prioritize reconstructing from current
actor names found that matches deployment tag if applicable.
Recover from checkpoint upon controller failure with all actor names found in current cluster . Each deployment resumes target state from checkpoint if available . For current state it will prioritize reconstructing from current actor names found that matches deployment tag if applicable .
def _recover_from_checkpoint(self, all_current_actor_names: List[str]) -> None:
        deployment_to_current_replicas = self._map_actor_names_to_deployment(
            all_current_actor_names
        )
        checkpoint = self._kv_store.get(CHECKPOINT_KEY)
        if checkpoint is not None:
            (
                deployment_state_info,
                self._deleted_deployment_metadata,
            ) = cloudpickle.loads(checkpoint)
            for deployment_tag, checkpoint_data in deployment_state_info.items():
                deployment_state = self._create_deployment_state(deployment_tag)
                target_state_checkpoint = checkpoint_data
                deployment_state.recover_target_state_from_checkpoint(
                    target_state_checkpoint
                )
                if len(deployment_to_current_replicas[deployment_tag]) > 0:
                    deployment_state.recover_current_state_from_replica_actor_names(  
                        deployment_to_current_replicas[deployment_tag]
                    )
                self._deployment_states[deployment_tag] = deployment_state
def _recover_from_checkpoint ( self , all_current_actor_names : List [ str ] ) -> None : deployment_to_current_replicas = self . _map_actor_names_to_deployment ( all_current_actor_names ) checkpoint = self . _kv_store . get ( CHECKPOINT_KEY ) if checkpoint is not None : ( deployment_state_info , self . _deleted_deployment_metadata , ) = cloudpickle . loads ( checkpoint ) for deployment_tag , checkpoint_data in deployment_state_info . items ( ) : deployment_state = self . _create_deployment_state ( deployment_tag ) target_state_checkpoint = checkpoint_data deployment_state . recover_target_state_from_checkpoint ( target_state_checkpoint ) if len ( deployment_to_current_replicas [ deployment_tag ] ) > 0 : deployment_state . recover_current_state_from_replica_actor_names ( deployment_to_current_replicas [ deployment_tag ] ) self . _deployment_states [ deployment_tag ] = deployment_state
Recover from checkpoint upon controller failure with all actor names
found in current cluster.
Recover from checkpoint upon controller failure with all actor names found in current cluster .
"""
        Recover from checkpoint upon controller failure with all actor names
        found in current cluster.

        Each deployment resumes target state from checkpoint if available.

        For current state it will prioritize reconstructing from current
        actor names found that matches deployment tag if applicable.
        """ # noqa: E501
self
all_current_actor_names
List[str]