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"""This file defines the interface between the ray client worker
and the overall ray module API.
"""
import json
import logging
from concurrent.futures import Future
from typing import TYPE_CHECKING, Any, Callable, List, Optional, Union
from ray._private import ray_option_utils
from ray.util.client.runtime_context import _ClientWorkerPropertyAPI
if TYPE_CHECKING:
from ray.actor import ActorClass
from ray.core.generated.ray_client_pb2 import DataResponse
from ray.remote_function import RemoteFunction
from ray.util.client.common import ClientActorHandle, ClientObjectRef, ClientStub
logger = logging.getLogger(__name__)
def _as_bytes(value):
if isinstance(value, str):
return value.encode("utf-8")
return value
class _ClientAPI:
"""The Client-side methods corresponding to the ray API. Delegates
to the Client Worker that contains the connection to the ClientServer.
"""
def __init__(self, worker=None):
self.worker = worker
def get(self, vals, *, timeout=None):
"""get is the hook stub passed on to replace `ray.get`
Args:
vals: [Client]ObjectRef or list of these refs to retrieve.
timeout: Optional timeout in milliseconds
"""
return self.worker.get(vals, timeout=timeout)
def put(self, *args, **kwargs):
"""put is the hook stub passed on to replace `ray.put`
Args:
val: The value to `put`.
args: opaque arguments
kwargs: opaque keyword arguments
"""
return self.worker.put(*args, **kwargs)
def wait(self, *args, **kwargs):
"""wait is the hook stub passed on to replace `ray.wait`
Args:
args: opaque arguments
kwargs: opaque keyword arguments
"""
return self.worker.wait(*args, **kwargs)
def remote(self, *args, **kwargs):
"""remote is the hook stub passed on to replace `ray.remote`.
This sets up remote functions or actors, as the decorator,
but does not execute them.
Args:
args: opaque arguments
kwargs: opaque keyword arguments
"""
# Delayed import to avoid a cyclic import
from ray.util.client.common import remote_decorator
if len(args) == 1 and len(kwargs) == 0 and callable(args[0]):
# This is the case where the decorator is just @ray.remote.
return remote_decorator(options=None)(args[0])
assert (
len(args) == 0 and len(kwargs) > 0
), ray_option_utils.remote_args_error_string
return remote_decorator(options=kwargs)
# TODO(mwtian): consider adding _internal_ prefix to call_remote /
# call_release / call_retain.
def call_remote(self, instance: "ClientStub", *args, **kwargs) -> List[Future]:
"""call_remote is called by stub objects to execute them remotely.
This is used by stub objects in situations where they're called
with .remote, eg, `f.remote()` or `actor_cls.remote()`.
This allows the client stub objects to delegate execution to be
implemented in the most effective way whether it's in the client,
clientserver, or raylet worker.
Args:
instance: The Client-side stub reference to a remote object
args: opaque arguments
kwargs: opaque keyword arguments
"""
return self.worker.call_remote(instance, *args, **kwargs)
def call_release(self, id: bytes) -> None:
"""Attempts to release an object reference.
When client references are destructed, they release their reference,
which can opportunistically send a notification through the datachannel
to release the reference being held for that object on the server.
Args:
id: The id of the reference to release on the server side.
"""
return self.worker.call_release(id)
def call_retain(self, id: bytes) -> None:
"""Attempts to retain a client object reference.
Increments the reference count on the client side, to prevent
the client worker from attempting to release the server reference.
Args:
id: The id of the reference to retain on the client side.
"""
return self.worker.call_retain(id)
def close(self) -> None:
"""close cleans up an API connection by closing any channels or
shutting down any servers gracefully.
"""
return self.worker.close()
def get_actor(
self, name: str, namespace: Optional[str] = None
) -> "ClientActorHandle":
"""Returns a handle to an actor by name.
Args:
name: The name passed to this actor by
Actor.options(name="name").remote()
"""
return self.worker.get_actor(name, namespace)
def list_named_actors(self, all_namespaces: bool = False) -> List[str]:
"""List all named actors in the system.
Actors must have been created with Actor.options(name="name").remote().
This works for both detached & non-detached actors.
By default, only actors in the current namespace will be returned
and the returned entries will simply be their name.
If `all_namespaces` is set to True, all actors in the cluster will be
returned regardless of namespace, and the retunred entries will be of
the form '<namespace>/<name>'.
"""
return self.worker.list_named_actors(all_namespaces)
def kill(self, actor: "ClientActorHandle", *, no_restart=True):
"""kill forcibly stops an actor running in the cluster
Args:
no_restart: Whether this actor should be restarted if it's a
restartable actor.
"""
return self.worker.terminate_actor(actor, no_restart)
def cancel(self, obj: "ClientObjectRef", *, force=False, recursive=True):
"""Cancels a task on the cluster.
If the specified task is pending execution, it will not be executed. If
the task is currently executing, the behavior depends on the ``force``
flag, as per `ray.cancel()`
Only non-actor tasks can be canceled. Canceled tasks will not be
retried (max_retries will not be respected).
Args:
object_ref: ObjectRef returned by the task
that should be canceled.
force: Whether to force-kill a running task by killing
the worker that is running the task.
recursive: Whether to try to cancel tasks submitted by
the task specified.
"""
return self.worker.terminate_task(obj, force, recursive)
# Various metadata methods for the client that are defined in the protocol.
def is_initialized(self) -> bool:
"""True if our client is connected, and if the server is initialized.
Returns:
A boolean determining if the client is connected and
server initialized.
"""
return self.worker.is_initialized()
def nodes(self):
"""Get a list of the nodes in the cluster (for debugging only).
Returns:
Information about the Ray clients in the cluster.
"""
# This should be imported here, otherwise, it will error doc build.
import ray.core.generated.ray_client_pb2 as ray_client_pb2
return self.worker.get_cluster_info(ray_client_pb2.ClusterInfoType.NODES)
def method(self, *args, **kwargs):
"""Annotate an actor method
Args:
num_returns: The number of object refs that should be returned by
invocations of this actor method.
"""
# NOTE: So this follows the same logic as in ray/actor.py::method()
# The reason to duplicate it here is to simplify the client mode
# redirection logic. As the annotated method gets pickled and sent to
# the server from the client it carries this private variable, it
# activates the same logic on the server side; so there's no need to
# pass anything else. It's inside the class definition that becomes an
# actor. Similar annotations would follow the same way.
valid_kwargs = ["num_returns", "concurrency_group"]
error_string = (
"The @ray.method decorator must be applied using at least one of "
f"the arguments in the list {valid_kwargs}, for example "
"'@ray.method(num_returns=2)'."
)
assert len(args) == 0 and len(kwargs) > 0, error_string
for key in kwargs:
key_error_string = (
f'Unexpected keyword argument to @ray.method: "{key}". The '
f"supported keyword arguments are {valid_kwargs}"
)
assert key in valid_kwargs, key_error_string
def annotate_method(method):
if "num_returns" in kwargs:
method.__ray_num_returns__ = kwargs["num_returns"]
if "concurrency_group" in kwargs:
method.__ray_concurrency_group__ = kwargs["concurrency_group"]
return method
return annotate_method
def cluster_resources(self):
"""Get the current total cluster resources.
Note that this information can grow stale as nodes are added to or
removed from the cluster.
Returns:
A dictionary mapping resource name to the total quantity of that
resource in the cluster.
"""
# This should be imported here, otherwise, it will error doc build.
import ray.core.generated.ray_client_pb2 as ray_client_pb2
return self.worker.get_cluster_info(
ray_client_pb2.ClusterInfoType.CLUSTER_RESOURCES
)
def available_resources(self):
"""Get the current available cluster resources.
This is different from `cluster_resources` in that this will return
idle (available) resources rather than total resources.
Note that this information can grow stale as tasks start and finish.
Returns:
A dictionary mapping resource name to the total quantity of that
resource in the cluster.
"""
# This should be imported here, otherwise, it will error doc build.
import ray.core.generated.ray_client_pb2 as ray_client_pb2
return self.worker.get_cluster_info(
ray_client_pb2.ClusterInfoType.AVAILABLE_RESOURCES
)
def get_runtime_context(self):
"""Return a Ray RuntimeContext describing the state on the server
Returns:
A RuntimeContext wrapping a client making get_cluster_info calls.
"""
return _ClientWorkerPropertyAPI(self.worker).build_runtime_context()
# Client process isn't assigned any GPUs.
def get_gpu_ids(self) -> list:
return []
def timeline(self, filename: Optional[str] = None) -> Optional[List[Any]]:
logger.warning(
"Timeline will include events from other clients using this server."
)
# This should be imported here, otherwise, it will error doc build.
import ray.core.generated.ray_client_pb2 as ray_client_pb2
all_events = self.worker.get_cluster_info(
ray_client_pb2.ClusterInfoType.TIMELINE
)
if filename is not None:
with open(filename, "w") as outfile:
json.dump(all_events, outfile)
else:
return all_events
def _internal_kv_initialized(self) -> bool:
"""Hook for internal_kv._internal_kv_initialized."""
# NOTE(edoakes): the kv is always initialized because we initialize it
# manually in the proxier with a GCS client if Ray hasn't been
# initialized yet.
return True
def _internal_kv_exists(
self, key: Union[str, bytes], *, namespace: Optional[Union[str, bytes]] = None
) -> bool:
"""Hook for internal_kv._internal_kv_exists."""
return self.worker.internal_kv_exists(
_as_bytes(key), namespace=_as_bytes(namespace)
)
def _internal_kv_get(
self, key: Union[str, bytes], *, namespace: Optional[Union[str, bytes]] = None
) -> bytes:
"""Hook for internal_kv._internal_kv_get."""
return self.worker.internal_kv_get(
_as_bytes(key), namespace=_as_bytes(namespace)
)
def _internal_kv_put(
self,
key: Union[str, bytes],
value: Union[str, bytes],
overwrite: bool = True,
*,
namespace: Optional[Union[str, bytes]] = None,
) -> bool:
"""Hook for internal_kv._internal_kv_put."""
return self.worker.internal_kv_put(
_as_bytes(key), _as_bytes(value), overwrite, namespace=_as_bytes(namespace)
)
def _internal_kv_del(
self,
key: Union[str, bytes],
*,
del_by_prefix: bool = False,
namespace: Optional[Union[str, bytes]] = None,
) -> int:
"""Hook for internal_kv._internal_kv_del."""
return self.worker.internal_kv_del(
_as_bytes(key), del_by_prefix=del_by_prefix, namespace=_as_bytes(namespace)
)
def _internal_kv_list(
self,
prefix: Union[str, bytes],
*,
namespace: Optional[Union[str, bytes]] = None,
) -> List[bytes]:
"""Hook for internal_kv._internal_kv_list."""
return self.worker.internal_kv_list(
_as_bytes(prefix), namespace=_as_bytes(namespace)
)
def _pin_runtime_env_uri(self, uri: str, expiration_s: int) -> None:
"""Hook for internal_kv._pin_runtime_env_uri."""
return self.worker.pin_runtime_env_uri(uri, expiration_s)
def _convert_actor(self, actor: "ActorClass") -> str:
"""Register a ClientActorClass for the ActorClass and return a UUID"""
return self.worker._convert_actor(actor)
def _convert_function(self, func: "RemoteFunction") -> str:
"""Register a ClientRemoteFunc for the ActorClass and return a UUID"""
return self.worker._convert_function(func)
def _get_converted(self, key: str) -> "ClientStub":
"""Given a UUID, return the converted object"""
return self.worker._get_converted(key)
def _converted_key_exists(self, key: str) -> bool:
"""Check if a key UUID is present in the store of converted objects."""
return self.worker._converted_key_exists(key)
def __getattr__(self, key: str):
if not key.startswith("_"):
raise NotImplementedError(
"Not available in Ray client: `ray.{}`. This method is only "
"available within Ray remote functions and is not yet "
"implemented in the client API.".format(key)
)
return self.__getattribute__(key)
def _register_callback(
self, ref: "ClientObjectRef", callback: Callable[["DataResponse"], None]
) -> None:
self.worker.register_callback(ref, callback)
def _get_dashboard_url(self) -> str:
import ray.core.generated.ray_client_pb2 as ray_client_pb2
return self.worker.get_cluster_info(
ray_client_pb2.ClusterInfoType.DASHBOARD_URL
).get("dashboard_url", "")