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[ray_client]: Insert decorators into the real ray module to allow for client mode (#13031)

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This commit is contained in:
Barak Michener
2020-12-22 22:51:45 -08:00
committed by GitHub
parent 646c4201ac
commit c4e273920f
28 changed files with 419 additions and 497 deletions
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.travis.yml
+1 -1
View File
@@ -46,7 +46,7 @@ matrix:
script:
# bazel python tests for medium size tests. Used for parallelization.
- if [ $RAY_CI_PYTHON_AFFECTED == "1" ]; then ./ci/keep_alive bazel test --config=ci $(./scripts/bazel_export_options) --test_tag_filters=-jenkins_only,medium_size_python_tests_a_to_j python/ray/tests/...; fi
- if [ $RAY_CI_PYTHON_AFFECTED == "1" ]; then ./ci/keep_alive bazel test --config=ci $(./scripts/bazel_export_options) --test_tag_filters=-jenkins_only,client_tests --test_env=RAY_TEST_CLIENT_MODE=1 python/ray/tests/...; fi
- if [ $RAY_CI_PYTHON_AFFECTED == "1" ]; then ./ci/keep_alive bazel test --config=ci $(./scripts/bazel_export_options) --test_tag_filters=-jenkins_only,client_tests --test_env=RAY_CLIENT_MODE=1 python/ray/tests/...; fi
- os: linux
env:
ci/travis/ci.sh
+7
View File
@@ -262,6 +262,11 @@ _bazel_build_before_install() {
bazel build "${target}"
}
_bazel_build_protobuf() {
bazel build "//:install_py_proto"
}
install_ray() {
# TODO(mehrdadn): This function should be unified with the one in python/build-wheel-windows.sh.
(
@@ -457,6 +462,8 @@ init() {
build() {
if [ "${LINT-}" != 1 ]; then
_bazel_build_before_install
else
_bazel_build_protobuf
fi
if ! need_wheels; then
python/ray/_private/client_mode_hook.py
+47
View File
@@ -0,0 +1,47 @@
import os
from contextlib import contextmanager
client_mode_enabled = os.environ.get("RAY_CLIENT_MODE", "0") == "1"
_client_hook_enabled = True
def _enable_client_hook(val: bool):
global _client_hook_enabled
_client_hook_enabled = val
def _disable_client_hook():
global _client_hook_enabled
out = _client_hook_enabled
_client_hook_enabled = False
return out
def _explicitly_enable_client_mode():
global client_mode_enabled
client_mode_enabled = True
@contextmanager
def disable_client_hook():
val = _disable_client_hook()
try:
yield None
finally:
_enable_client_hook(val)
def client_mode_hook(func):
"""
Decorator for ray module methods to delegate to ray client
"""
from ray.experimental.client import ray
def wrapper(*args, **kwargs):
global _client_hook_enabled
if client_mode_enabled and _client_hook_enabled:
return getattr(ray, func.__name__)(*args, **kwargs)
return func(*args, **kwargs)
return wrapper
python/ray/_raylet.pyx
+7
View File
@@ -107,6 +107,10 @@ from ray.exceptions import (
TaskCancelledError
)
from ray.utils import decode
from ray._private.client_mode_hook import (
_enable_client_hook,
_disable_client_hook,
)
import msgpack
cimport cpython
@@ -558,6 +562,7 @@ cdef CRayStatus task_execution_handler(
with gil:
try:
client_was_enabled = _disable_client_hook()
try:
# The call to execute_task should never raise an exception. If
# it does, that indicates that there was an internal error.
@@ -582,6 +587,8 @@ cdef CRayStatus task_execution_handler(
else:
logger.exception("SystemExit was raised from the worker")
return CRayStatus.UnexpectedSystemExit()
finally:
_enable_client_hook(client_was_enabled)
return CRayStatus.OK()
python/ray/experimental/client/__init__.py
+78 -122
View File
@@ -1,148 +1,104 @@
from ray.experimental.client.api import ClientAPI
from ray.experimental.client.api import APIImpl
from typing import Optional, List, Tuple
from contextlib import contextmanager
from typing import List, Tuple
import logging
import os
logger = logging.getLogger(__name__)
# About these global variables: Ray 1.0 uses exported module functions to
# provide its API, and we need to match that. However, we want different
# behaviors depending on where, exactly, in the client stack this is running.
#
# The reason for these differences depends on what's being pickled and passed
# to functions, or functions inside functions. So there are three cases to care
# about
#
# (Python Client)-->(Python ClientServer)-->(Internal Raylet Process)
#
# * _client_api should be set if we're inside the client
# * _server_api should be set if we're inside the clientserver
# * Both will be set if we're running both (as in a test)
# * Neither should be set if we're inside the raylet (but we still need to shim
# from the client API surface to the Ray API)
#
# The job of RayAPIStub (below) delegates to the appropriate one of these
# depending on what's set or not. Then, all users importing the ray object
# from this package get the stub which routes them to the appropriate APIImpl.
_client_api: Optional[APIImpl] = None
_server_api: Optional[APIImpl] = None
# The reason for _is_server is a hack around the above comment while running
# tests. If we have both a client and a server trying to control these static
# variables then we need a way to decide which to use. In this case, both
# _client_api and _server_api are set.
# This boolean flips between the two
_is_server: bool = False
@contextmanager
def stash_api_for_tests(in_test: bool):
global _is_server
is_server = _is_server
if in_test:
_is_server = True
try:
yield _server_api
finally:
if in_test:
_is_server = is_server
def _set_client_api(val: Optional[APIImpl]):
global _client_api
global _is_server
if _client_api is not None:
raise Exception("Trying to set more than one client API")
_client_api = val
_is_server = False
def _set_server_api(val: Optional[APIImpl]):
global _server_api
global _is_server
if _server_api is not None:
raise Exception("Trying to set more than one server API")
_server_api = val
_is_server = True
def reset_api():
global _client_api
global _server_api
global _is_server
_client_api = None
_server_api = None
_is_server = False
def _get_client_api() -> APIImpl:
global _client_api
return _client_api
def _get_server_instance():
"""Used inside tests to inspect the running server.
"""
global _server_api
if _server_api is not None:
return _server_api.server
class RayAPIStub:
"""This class stands in as the replacement API for the `import ray` module.
Much like the ray module, this mostly delegates the work to the
_client_worker. As parts of the ray API are covered, they are piped through
here or on the client worker API.
"""
def __init__(self):
from ray.experimental.client.api import ClientAPI
self.api = ClientAPI()
self.client_worker = None
self._server = None
self._connected_with_init = False
self._inside_client_test = False
def connect(self,
conn_str: str,
secure: bool = False,
metadata: List[Tuple[str, str]] = None,
stub=None) -> None:
metadata: List[Tuple[str, str]] = None) -> None:
"""Connect the Ray Client to a server.
Args:
conn_str: Connection string, in the form "[host]:port"
secure: Whether to use a TLS secured gRPC channel
metadata: gRPC metadata to send on connect
"""
# Delay imports until connect to avoid circular imports.
from ray.experimental.client.worker import Worker
_client_worker = Worker(conn_str, secure=secure, metadata=metadata)
_set_client_api(ClientAPI(_client_worker))
import ray._private.client_mode_hook
if self.client_worker is not None:
if self._connected_with_init:
return
raise Exception(
"ray.connect() called, but ray client is already connected")
if not self._inside_client_test:
# If we're calling a client connect specifically and we're not
# currently in client mode, ensure we are.
ray._private.client_mode_hook._explicitly_enable_client_mode()
self.client_worker = Worker(conn_str, secure=secure, metadata=metadata)
self.api.worker = self.client_worker
def disconnect(self):
global _client_api
if _client_api is not None:
_client_api.close()
_client_api = None
"""Disconnect the Ray Client.
"""
if self.client_worker is not None:
self.client_worker.close()
self.client_worker = None
# remote can be called outside of a connection, which is why it
# exists on the same API layer as connect() itself.
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
"""
return self.api.remote(*args, **kwargs)
def __getattr__(self, key: str):
global _get_client_api
api = _get_client_api()
return getattr(api, key)
if not self.is_connected():
raise Exception("Ray Client is not connected. "
"Please connect by calling `ray.connect`.")
return getattr(self.api, key)
def is_connected(self) -> bool:
global _client_api
return _client_api is not None
return self.api is not None
def init(self, *args, **kwargs):
if _is_client_test_env():
global _test_server
import ray.experimental.client.server.server as ray_client_server
_test_server, address_info = ray_client_server.init_and_serve(
"localhost:50051", test_mode=True, *args, **kwargs)
self.connect("localhost:50051")
return address_info
else:
raise NotImplementedError(
"Please call ray.connect() in client mode")
if self._server is not None:
raise Exception("Trying to start two instances of ray via client")
import ray.experimental.client.server.server as ray_client_server
self._server, address_info = ray_client_server.init_and_serve(
"localhost:50051", *args, **kwargs)
self.connect("localhost:50051")
self._connected_with_init = True
return address_info
def shutdown(self, _exiting_interpreter=False):
self.disconnect()
import ray.experimental.client.server.server as ray_client_server
if self._server is None:
return
ray_client_server.shutdown_with_server(self._server,
_exiting_interpreter)
self._server = None
ray = RayAPIStub()
_test_server = None
def _stop_test_server(*args):
global _test_server
_test_server.stop(*args)
def _is_client_test_env() -> bool:
return os.environ.get("RAY_TEST_CLIENT_MODE") == "1"
# Someday we might add methods in this module so that someone who
# tries to `import ray_client as ray` -- as a module, instead of
# `from ray_client import ray` -- as the API stub
python/ray/experimental/client/api.py
+82 -130
View File
@@ -1,74 +1,51 @@
# This file defines an interface and client-side API stub
# for referring either to the core Ray API or the same interface
# from the Ray client.
#
# In tandem with __init__.py, we want to expose an API that's
# close to `python/ray/__init__.py` but with more than one implementation.
# The stubs in __init__ should call into a well-defined interface.
# Only the core Ray API implementation should actually `import ray`
# (and thus import all the raylet worker C bindings and such).
# But to make sure that we're matching these calls, we define this API.
from abc import ABC
from abc import abstractmethod
from typing import TYPE_CHECKING, Any, Union, Optional
import ray.core.generated.ray_client_pb2 as ray_client_pb2
"""This file defines the interface between the ray client worker
and the overall ray module API.
"""
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from ray.experimental.client.common import ClientActorHandle
from ray.experimental.client.common import ClientStub
from ray.experimental.client.common import ClientActorHandle
from ray.experimental.client.common import ClientObjectRef
from ray._raylet import ObjectRef
# Use the imports for type checking. This is a python 3.6 limitation.
# See https://www.python.org/dev/peps/pep-0563/
PutType = Union[ClientObjectRef, ObjectRef]
class APIImpl(ABC):
"""
APIImpl is the interface to implement for whichever version of the core
Ray API that needs abstracting when run in client mode.
class ClientAPI:
"""The Client-side methods corresponding to the ray API. Delegates
to the Client Worker that contains the connection to the ClientServer.
"""
@abstractmethod
def get(self, vals, *, timeout: Optional[float] = None) -> Any:
"""
get is the hook stub passed on to replace `ray.get`
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
"""
pass
return self.worker.get(vals, timeout=timeout)
@abstractmethod
def put(self, vals: Any, *args,
**kwargs) -> Union["ClientObjectRef", "ObjectRef"]:
"""
put is the hook stub passed on to replace `ray.put`
def put(self, *args, **kwargs):
"""put is the hook stub passed on to replace `ray.put`
Args:
vals: The value or list of values to `put`.
args: opaque arguments
kwargs: opaque keyword arguments
"""
pass
return self.worker.put(*args, **kwargs)
@abstractmethod
def wait(self, *args, **kwargs):
"""
wait is the hook stub passed on to replace `ray.wait`
"""wait is the hook stub passed on to replace `ray.wait`
Args:
args: opaque arguments
kwargs: opaque keyword arguments
"""
pass
return self.worker.wait(*args, **kwargs)
@abstractmethod
def remote(self, *args, **kwargs):
"""
remote is the hook stub passed on to replace `ray.remote`.
"""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.
@@ -77,12 +54,24 @@ class APIImpl(ABC):
args: opaque arguments
kwargs: opaque keyword arguments
"""
pass
# Delayed import to avoid a cyclic import
from ray.experimental.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])
error_string = ("The @ray.remote decorator must be applied either "
"with no arguments and no parentheses, for example "
"'@ray.remote', or it must be applied using some of "
"the arguments 'num_returns', 'num_cpus', 'num_gpus', "
"'memory', 'object_store_memory', 'resources', "
"'max_calls', or 'max_restarts', like "
"'@ray.remote(num_returns=2, "
"resources={\"CustomResource\": 1})'.")
assert len(args) == 0 and len(kwargs) > 0, error_string
return remote_decorator(options=kwargs)
@abstractmethod
def call_remote(self, instance: "ClientStub", *args, **kwargs):
"""
call_remote is called by stub objects to execute them remotely.
"""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()`.
@@ -95,31 +84,57 @@ class APIImpl(ABC):
args: opaque arguments
kwargs: opaque keyword arguments
"""
pass
return self.worker.call_remote(instance, *args, **kwargs)
@abstractmethod
def close(self) -> None:
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.
"""
close cleans up an API connection by closing any channels or
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.
"""
pass
return self.worker.close()
@abstractmethod
def kill(self, actor, *, no_restart=True):
def get_actor(self, name: str) -> "ClientActorHandle":
"""Returns a handle to an actor by name.
Args:
name: The name passed to this actor by
Actor.options(name="name").remote()
"""
kill forcibly stops an actor running in the cluster
return self.worker.get_actor(name)
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.
"""
pass
return self.worker.terminate_actor(actor, no_restart)
@abstractmethod
def cancel(self, obj, *, force=False, recursive=True):
"""
Cancels a task on the cluster.
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``
@@ -136,80 +151,11 @@ class APIImpl(ABC):
recursive (boolean): Whether to try to cancel tasks submitted by
the task specified.
"""
pass
@abstractmethod
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.
"""
@abstractmethod
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.
"""
class ClientAPI(APIImpl):
"""
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):
self.worker = worker
def get(self, vals, *, timeout=None):
return self.worker.get(vals, timeout=timeout)
def put(self, *args, **kwargs):
return self.worker.put(*args, **kwargs)
def wait(self, *args, **kwargs):
return self.worker.wait(*args, **kwargs)
def remote(self, *args, **kwargs):
return self.worker.remote(*args, **kwargs)
def call_remote(self, instance: "ClientStub", *args, **kwargs):
return self.worker.call_remote(instance, *args, **kwargs)
def call_release(self, id: bytes) -> None:
return self.worker.call_release(id)
def call_retain(self, id: bytes) -> None:
return self.worker.call_retain(id)
def close(self) -> None:
return self.worker.close()
def get_actor(self, name: str) -> "ClientActorHandle":
return self.worker.get_actor(name)
def kill(self, actor: "ClientActorHandle", *, no_restart=True):
return self.worker.terminate_actor(actor, no_restart)
def cancel(self, obj: "ClientObjectRef", *, force=False, recursive=True):
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.
"""True if our client is connected, and if the server is initialized.
Returns:
A boolean determining if the client is connected and
server initialized.
@@ -222,6 +168,8 @@ class ClientAPI(APIImpl):
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)
@@ -235,6 +183,8 @@ class ClientAPI(APIImpl):
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)
@@ -250,6 +200,8 @@ class ClientAPI(APIImpl):
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)
python/ray/experimental/client/client_pickler.py
+7 -6
View File
@@ -1,5 +1,4 @@
"""
Implements the client side of the client/server pickling protocol.
"""Implements the client side of the client/server pickling protocol.
All ray client client/server data transfer happens through this pickling
protocol. The model is as follows:
@@ -41,6 +40,7 @@ from ray.experimental.client.common import ClientRemoteMethod
from ray.experimental.client.common import OptionWrapper
from ray.experimental.client.common import SelfReferenceSentinel
import ray.core.generated.ray_client_pb2 as ray_client_pb2
from ray._private.client_mode_hook import disable_client_hook
if sys.version_info < (3, 8):
try:
@@ -155,10 +155,11 @@ class ServerUnpickler(pickle.Unpickler):
def dumps_from_client(obj: Any, client_id: str, protocol=None) -> bytes:
with io.BytesIO() as file:
cp = ClientPickler(client_id, file, protocol=protocol)
cp.dump(obj)
return file.getvalue()
with disable_client_hook():
with io.BytesIO() as file:
cp = ClientPickler(client_id, file, protocol=protocol)
cp.dump(obj)
return file.getvalue()
def loads_from_server(data: bytes,
python/ray/experimental/client/common.py
+18 -3
View File
@@ -2,6 +2,8 @@ import ray.core.generated.ray_client_pb2 as ray_client_pb2
from ray.experimental.client import ray
from ray.experimental.client.options import validate_options
import inspect
from ray.util.inspect import is_cython
import json
import threading
from typing import Any
@@ -52,8 +54,7 @@ class ClientStub:
class ClientRemoteFunc(ClientStub):
"""
A stub created on the Ray Client to represent a remote
"""A stub created on the Ray Client to represent a remote
function that can be exectued on the cluster.
This class is allowed to be passed around between remote functions.
@@ -112,7 +113,7 @@ class ClientRemoteFunc(ClientStub):
class ClientActorClass(ClientStub):
""" A stub created on the Ray Client to represent an actor class.
"""A stub created on the Ray Client to represent an actor class.
It is wrapped by ray.remote and can be executed on the cluster.
@@ -294,3 +295,17 @@ class DataEncodingSentinel:
class SelfReferenceSentinel(DataEncodingSentinel):
pass
def remote_decorator(options: Optional[Dict[str, Any]]):
def decorator(function_or_class) -> ClientStub:
if (inspect.isfunction(function_or_class)
or is_cython(function_or_class)):
return ClientRemoteFunc(function_or_class, options=options)
elif inspect.isclass(function_or_class):
return ClientActorClass(function_or_class, options=options)
else:
raise TypeError("The @ray.remote decorator must be applied to "
"either a function or to a class.")
return decorator
python/ray/experimental/client/dataclient.py
+1 -2
View File
@@ -1,5 +1,4 @@
"""
This file implements a threaded stream controller to abstract a data stream
"""This file implements a threaded stream controller to abstract a data stream
back to the ray clientserver.
"""
import logging
python/ray/experimental/client/examples/run_tune.py
+7
View File
@@ -0,0 +1,7 @@
from ray.experimental.client import ray
from ray.tune import tune
ray.connect("localhost:50051")
tune.run("PG", config={"env": "CartPole-v0"})
python/ray/experimental/client/logsclient.py
+8 -6
View File
@@ -1,5 +1,4 @@
"""
This file implements a threaded stream controller to return logs back from
"""This file implements a threaded stream controller to return logs back from
the ray clientserver.
"""
import sys
@@ -12,6 +11,10 @@ import ray.core.generated.ray_client_pb2 as ray_client_pb2
import ray.core.generated.ray_client_pb2_grpc as ray_client_pb2_grpc
logger = logging.getLogger(__name__)
# TODO(barakmich): Running a logger in a logger causes loopback.
# The client logger need its own root -- possibly this one.
# For the moment, let's just not propogate beyond this point.
logger.propagate = False
class LogstreamClient:
@@ -45,8 +48,7 @@ class LogstreamClient:
raise e
def log(self, level: int, msg: str):
"""
Log the message from the log stream.
"""Log the message from the log stream.
By default, calls logger.log but this can be overridden.
Args:
@@ -56,8 +58,7 @@ class LogstreamClient:
logger.log(level=level, msg=msg)
def stdstream(self, level: int, msg: str):
"""
Log the stdout/stderr entry from the log stream.
"""Log the stdout/stderr entry from the log stream.
By default, calls print but this can be overridden.
Args:
@@ -68,6 +69,7 @@ class LogstreamClient:
print(msg, file=print_file)
def set_logstream_level(self, level: int):
logger.setLevel(level)
req = ray_client_pb2.LogSettingsRequest()
req.enabled = True
req.loglevel = level
python/ray/experimental/client/ray_client_helpers.py
+4 -3
View File
@@ -1,16 +1,17 @@
from contextlib import contextmanager
import ray.experimental.client.server.server as ray_client_server
from ray.experimental.client import ray, reset_api
from ray.experimental.client import ray
@contextmanager
def ray_start_client_server():
server = ray_client_server.serve("localhost:50051", test_mode=True)
ray._inside_client_test = True
server = ray_client_server.serve("localhost:50051")
ray.connect("localhost:50051")
try:
yield ray
finally:
ray._inside_client_test = False
ray.disconnect()
server.stop(0)
reset_api()
python/ray/experimental/client/server/core_ray_api.py
-81
View File
@@ -1,81 +0,0 @@
# Along with `api.py` this is the stub that interfaces with
# the real (C-binding, raylet) ray core.
#
# Ideally, the first import line is the only time we actually
# import ray in this library (excluding the main function for the server)
#
# While the stub is trivial, it allows us to check that the calls we're
# making into the core-ray module are contained and well-defined.
from typing import Any
from typing import Optional
from typing import Union
import logging
import ray
from ray.experimental.client.api import APIImpl
from ray.experimental.client.common import ClientObjectRef
from ray.experimental.client.common import ClientStub
logger = logging.getLogger(__name__)
class CoreRayAPI(APIImpl):
"""
Implements the equivalent client-side Ray API by simply passing along to
the Core Ray API. Primarily used inside of Ray Workers as a trampoline back
to core ray when passed client stubs.
"""
def get(self, vals, *, timeout: Optional[float] = None) -> Any:
return ray.get(vals, timeout=timeout)
def put(self, vals: Any, *args,
**kwargs) -> Union[ClientObjectRef, ray._raylet.ObjectRef]:
return ray.put(vals, *args, **kwargs)
def wait(self, *args, **kwargs):
return ray.wait(*args, **kwargs)
def remote(self, *args, **kwargs):
return ray.remote(*args, **kwargs)
def call_remote(self, instance: ClientStub, *args, **kwargs):
raise NotImplementedError(
"Should not attempt execution of a client stub inside the raylet")
def close(self) -> None:
return None
def kill(self, actor, *, no_restart=True):
return ray.kill(actor, no_restart=no_restart)
def cancel(self, obj, *, force=False, recursive=True):
return ray.cancel(obj, force=force, recursive=recursive)
def is_initialized(self) -> bool:
return ray.is_initialized()
def call_release(self, id: bytes) -> None:
return None
def call_retain(self, id: bytes) -> None:
return None
# Allow for generic fallback to ray.* in remote methods. This allows calls
# like ray.nodes() to be run in remote functions even though the client
# doesn't currently support them.
def __getattr__(self, key: str):
return getattr(ray, key)
class RayServerAPI(CoreRayAPI):
"""
Ray Client server-side API shim. By default, simply calls the default Core
Ray API calls, but also accepts scheduling calls from functions running
inside of other remote functions that need to create more work.
"""
def __init__(self, server_instance):
self.server = server_instance
python/ray/experimental/client/server/logservicer.py
+4 -2
View File
@@ -1,5 +1,4 @@
"""
This file responds to log stream requests and forwards logs
"""This file responds to log stream requests and forwards logs
with its handler.
"""
import io
@@ -70,6 +69,9 @@ def log_status_change_thread(log_queue, request_iterator):
std_handler.register_global()
root_logger.addHandler(current_handler)
root_logger.setLevel(req.loglevel)
except grpc.RpcError as e:
logger.debug(f"closing log thread "
f"grpc error reading request_iterator: {e}")
finally:
if current_handler is not None:
root_logger.setLevel(default_level)
python/ray/experimental/client/server/server.py
+79 -53
View File
@@ -17,27 +17,25 @@ import ray.core.generated.ray_client_pb2_grpc as ray_client_pb2_grpc
import time
import inspect
import json
from ray.experimental.client import stash_api_for_tests, _set_server_api
from ray.experimental.client.server.server_pickler import convert_from_arg
from ray.experimental.client.server.server_pickler import dumps_from_server
from ray.experimental.client.server.server_pickler import loads_from_client
from ray.experimental.client.server.core_ray_api import RayServerAPI
from ray.experimental.client.server.dataservicer import DataServicer
from ray.experimental.client.server.logservicer import LogstreamServicer
from ray.experimental.client.server.server_stubs import current_remote
from ray._private.client_mode_hook import disable_client_hook
logger = logging.getLogger(__name__)
class RayletServicer(ray_client_pb2_grpc.RayletDriverServicer):
def __init__(self, test_mode=False):
def __init__(self):
self.object_refs: Dict[str, Dict[bytes, ray.ObjectRef]] = defaultdict(
dict)
self.function_refs = {}
self.actor_refs: Dict[bytes, ray.ActorHandle] = {}
self.actor_owners: Dict[str, Set[bytes]] = defaultdict(set)
self.registered_actor_classes = {}
self._test_mode = test_mode
self._current_function_stub = None
def ClusterInfo(self, request,
@@ -45,7 +43,8 @@ class RayletServicer(ray_client_pb2_grpc.RayletDriverServicer):
resp = ray_client_pb2.ClusterInfoResponse()
resp.type = request.type
if request.type == ray_client_pb2.ClusterInfoType.CLUSTER_RESOURCES:
resources = ray.cluster_resources()
with disable_client_hook():
resources = ray.cluster_resources()
# Normalize resources into floats
# (the function may return values that are ints)
float_resources = {k: float(v) for k, v in resources.items()}
@@ -54,7 +53,8 @@ class RayletServicer(ray_client_pb2_grpc.RayletDriverServicer):
table=float_resources))
elif request.type == \
ray_client_pb2.ClusterInfoType.AVAILABLE_RESOURCES:
resources = ray.available_resources()
with disable_client_hook():
resources = ray.available_resources()
# Normalize resources into floats
# (the function may return values that are ints)
float_resources = {k: float(v) for k, v in resources.items()}
@@ -62,7 +62,8 @@ class RayletServicer(ray_client_pb2_grpc.RayletDriverServicer):
ray_client_pb2.ClusterInfoResponse.ResourceTable(
table=float_resources))
else:
resp.json = self._return_debug_cluster_info(request, context)
with disable_client_hook():
resp.json = self._return_debug_cluster_info(request, context)
return resp
def _return_debug_cluster_info(self, request, context=None) -> str:
@@ -118,16 +119,18 @@ class RayletServicer(ray_client_pb2_grpc.RayletDriverServicer):
try:
object_ref = \
self.object_refs[req.client_id][req.task_object.id]
ray.cancel(
object_ref,
force=req.task_object.force,
recursive=req.task_object.recursive)
with disable_client_hook():
ray.cancel(
object_ref,
force=req.task_object.force,
recursive=req.task_object.recursive)
except Exception as e:
return_exception_in_context(e, context)
elif req.WhichOneof("terminate_type") == "actor":
try:
actor_ref = self.actor_refs[req.actor.id]
ray.kill(actor_ref, no_restart=req.actor.no_restart)
with disable_client_hook():
ray.kill(actor_ref, no_restart=req.actor.no_restart)
except Exception as e:
return_exception_in_context(e, context)
else:
@@ -145,7 +148,8 @@ class RayletServicer(ray_client_pb2_grpc.RayletDriverServicer):
objectref = self.object_refs[client_id][request.id]
logger.debug("get: %s" % objectref)
try:
item = ray.get(objectref, timeout=request.timeout)
with disable_client_hook():
item = ray.get(objectref, timeout=request.timeout)
except Exception as e:
return ray_client_pb2.GetResponse(
valid=False, error=cloudpickle.dumps(e))
@@ -171,7 +175,8 @@ class RayletServicer(ray_client_pb2_grpc.RayletDriverServicer):
context: gRPC context.
"""
obj = loads_from_client(request.data, self)
objectref = ray.put(obj)
with disable_client_hook():
objectref = ray.put(obj)
self.object_refs[client_id][objectref.binary()] = objectref
logger.debug("put: %s" % objectref)
return ray_client_pb2.PutResponse(id=objectref.binary())
@@ -187,11 +192,12 @@ class RayletServicer(ray_client_pb2_grpc.RayletDriverServicer):
num_returns = request.num_returns
timeout = request.timeout
try:
ready_object_refs, remaining_object_refs = ray.wait(
object_refs,
num_returns=num_returns,
timeout=timeout if timeout != -1 else None,
)
with disable_client_hook():
ready_object_refs, remaining_object_refs = ray.wait(
object_refs,
num_returns=num_returns,
timeout=timeout if timeout != -1 else None,
)
except Exception as e:
# TODO(ameer): improve exception messages.
logger.error(f"Exception {e}")
@@ -215,8 +221,8 @@ class RayletServicer(ray_client_pb2_grpc.RayletDriverServicer):
"schedule: %s %s" % (task.name,
ray_client_pb2.ClientTask.RemoteExecType.Name(
task.type)))
with stash_api_for_tests(self._test_mode):
try:
try:
with disable_client_hook():
if task.type == ray_client_pb2.ClientTask.FUNCTION:
result = self._schedule_function(task, context)
elif task.type == ray_client_pb2.ClientTask.ACTOR:
@@ -232,11 +238,11 @@ class RayletServicer(ray_client_pb2_grpc.RayletDriverServicer):
task.type))
result.valid = True
return result
except Exception as e:
logger.error(f"Caught schedule exception {e}")
raise e
return ray_client_pb2.ClientTaskTicket(
valid=False, error=cloudpickle.dumps(e))
except Exception as e:
logger.error(f"Caught schedule exception {e}")
raise e
return ray_client_pb2.ClientTaskTicket(
valid=False, error=cloudpickle.dumps(e))
def _schedule_method(self, task: ray_client_pb2.ClientTask,
context=None) -> ray_client_pb2.ClientTaskTicket:
@@ -307,31 +313,33 @@ class RayletServicer(ray_client_pb2_grpc.RayletDriverServicer):
def lookup_or_register_func(
self, id: bytes, client_id: str,
options: Optional[Dict]) -> ray.remote_function.RemoteFunction:
if id not in self.function_refs:
funcref = self.object_refs[client_id][id]
func = ray.get(funcref)
if not inspect.isfunction(func):
raise Exception("Attempting to register function that "
"isn't a function.")
if options is None or len(options) == 0:
self.function_refs[id] = ray.remote(func)
else:
self.function_refs[id] = ray.remote(**options)(func)
with disable_client_hook():
if id not in self.function_refs:
funcref = self.object_refs[client_id][id]
func = ray.get(funcref)
if not inspect.isfunction(func):
raise Exception("Attempting to register function that "
"isn't a function.")
if options is None or len(options) == 0:
self.function_refs[id] = ray.remote(func)
else:
self.function_refs[id] = ray.remote(**options)(func)
return self.function_refs[id]
def lookup_or_register_actor(self, id: bytes, client_id: str,
options: Optional[Dict]):
if id not in self.registered_actor_classes:
actor_class_ref = self.object_refs[client_id][id]
actor_class = ray.get(actor_class_ref)
if not inspect.isclass(actor_class):
raise Exception("Attempting to schedule actor that "
"isn't a class.")
if options is None or len(options) == 0:
reg_class = ray.remote(actor_class)
else:
reg_class = ray.remote(**options)(actor_class)
self.registered_actor_classes[id] = reg_class
with disable_client_hook():
if id not in self.registered_actor_classes:
actor_class_ref = self.object_refs[client_id][id]
actor_class = ray.get(actor_class_ref)
if not inspect.isclass(actor_class):
raise Exception("Attempting to schedule actor that "
"isn't a class.")
if options is None or len(options) == 0:
reg_class = ray.remote(actor_class)
else:
reg_class = ray.remote(**options)(actor_class)
self.registered_actor_classes[id] = reg_class
return self.registered_actor_classes[id]
@@ -369,12 +377,22 @@ def decode_options(
return opts
def serve(connection_str, test_mode=False):
_current_servicer: Optional[RayletServicer] = None
# Used by tests to peek inside the servicer
def _get_current_servicer():
global _current_servicer
return _current_servicer
def serve(connection_str):
server = grpc.server(futures.ThreadPoolExecutor(max_workers=10))
task_servicer = RayletServicer(test_mode=test_mode)
task_servicer = RayletServicer()
data_servicer = DataServicer(task_servicer)
logs_servicer = LogstreamServicer()
_set_server_api(RayServerAPI(task_servicer))
global _current_servicer
_current_servicer = task_servicer
ray_client_pb2_grpc.add_RayletDriverServicer_to_server(
task_servicer, server)
ray_client_pb2_grpc.add_RayletDataStreamerServicer_to_server(
@@ -386,12 +404,20 @@ def serve(connection_str, test_mode=False):
return server
def init_and_serve(connection_str, test_mode=False, *args, **kwargs):
info = ray.init(*args, **kwargs)
server = serve(connection_str, test_mode)
def init_and_serve(connection_str, *args, **kwargs):
with disable_client_hook():
# Disable client mode inside the worker's environment
info = ray.init(*args, **kwargs)
server = serve(connection_str)
return (server, info)
def shutdown_with_server(server, _exiting_interpreter=False):
server.stop(1)
with disable_client_hook():
ray.shutdown(_exiting_interpreter)
if __name__ == "__main__":
logging.basicConfig(level="INFO")
# TODO(barakmich): Perhaps wrap ray init
python/ray/experimental/client/server/server_pickler.py
+9 -8
View File
@@ -1,5 +1,4 @@
"""
Implements the client side of the client/server pickling protocol.
"""Implements the client side of the client/server pickling protocol.
These picklers are aware of the server internals and can find the
references held for the client within the server.
@@ -20,6 +19,7 @@ import ray
from typing import Any
from typing import TYPE_CHECKING
from ray._private.client_mode_hook import disable_client_hook
from ray.experimental.client.client_pickler import PickleStub
from ray.experimental.client.server.server_stubs import (
ServerSelfReferenceSentinel)
@@ -121,12 +121,13 @@ def loads_from_client(data: bytes,
fix_imports=True,
encoding="ASCII",
errors="strict") -> Any:
if isinstance(data, str):
raise TypeError("Can't load pickle from unicode string")
file = io.BytesIO(data)
return ClientUnpickler(
server_instance, file, fix_imports=fix_imports,
encoding=encoding).load()
with disable_client_hook():
if isinstance(data, str):
raise TypeError("Can't load pickle from unicode string")
file = io.BytesIO(data)
return ClientUnpickler(
server_instance, file, fix_imports=fix_imports,
encoding=encoding).load()
def convert_from_arg(pb: "ray_client_pb2.Arg",
python/ray/experimental/client/worker.py
+7 -35
View File
@@ -3,7 +3,6 @@ It implements the Ray API functions that are forwarded through grpc calls
to the server.
"""
import base64
import inspect
import json
import logging
import uuid
@@ -14,7 +13,6 @@ from typing import List
from typing import Tuple
from typing import Optional
from ray.util.inspect import is_cython
import grpc
import ray.cloudpickle as cloudpickle
@@ -23,12 +21,9 @@ import ray.core.generated.ray_client_pb2_grpc as ray_client_pb2_grpc
from ray.experimental.client.client_pickler import convert_to_arg
from ray.experimental.client.client_pickler import dumps_from_client
from ray.experimental.client.client_pickler import loads_from_server
from ray.experimental.client.common import ClientActorClass
from ray.experimental.client.common import ClientActorHandle
from ray.experimental.client.common import ClientActorRef
from ray.experimental.client.common import ClientObjectRef
from ray.experimental.client.common import ClientRemoteFunc
from ray.experimental.client.common import ClientStub
from ray.experimental.client.dataclient import DataClient
from ray.experimental.client.logsclient import LogstreamClient
@@ -61,6 +56,7 @@ class Worker:
self.log_client = LogstreamClient(self.channel)
self.log_client.set_logstream_level(logging.INFO)
self.closed = False
def get(self, vals, *, timeout: Optional[float] = None) -> Any:
to_get = []
@@ -153,21 +149,6 @@ class Worker:
return (client_ready_object_ids, client_remaining_object_ids)
def remote(self, *args, **kwargs):
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])
error_string = ("The @ray.remote decorator must be applied either "
"with no arguments and no parentheses, for example "
"'@ray.remote', or it must be applied using some of "
"the arguments 'num_returns', 'num_cpus', 'num_gpus', "
"'memory', 'object_store_memory', 'resources', "
"'max_calls', or 'max_restarts', like "
"'@ray.remote(num_returns=2, "
"resources={\"CustomResource\": 1})'.")
assert len(args) == 0 and len(kwargs) > 0, error_string
return remote_decorator(options=kwargs)
def call_remote(self, instance, *args, **kwargs) -> List[bytes]:
task = instance._prepare_client_task()
for arg in args:
@@ -190,6 +171,8 @@ class Worker:
return ticket.return_ids
def call_release(self, id: bytes) -> None:
if self.closed:
return
self.reference_count[id] -= 1
if self.reference_count[id] == 0:
self._release_server(id)
@@ -212,6 +195,7 @@ class Worker:
self.channel.close()
self.channel = None
self.server = None
self.closed = True
def get_actor(self, name: str) -> ClientActorHandle:
task = ray_client_pb2.ClientTask()
@@ -258,7 +242,9 @@ class Worker:
req.type = type
resp = self.server.ClusterInfo(req)
if resp.WhichOneof("response_type") == "resource_table":
return resp.resource_table.table
# translate from a proto map to a python dict
output_dict = {k: v for k, v in resp.resource_table.table.items()}
return output_dict
return json.loads(resp.json)
def is_initialized(self) -> bool:
@@ -268,20 +254,6 @@ class Worker:
return False
def remote_decorator(options: Optional[Dict[str, Any]]):
def decorator(function_or_class) -> ClientStub:
if (inspect.isfunction(function_or_class)
or is_cython(function_or_class)):
return ClientRemoteFunc(function_or_class, options=options)
elif inspect.isclass(function_or_class):
return ClientActorClass(function_or_class, options=options)
else:
raise TypeError("The @ray.remote decorator must be applied to "
"either a function or to a class.")
return decorator
def make_client_id() -> str:
id = uuid.uuid4()
return id.hex
python/ray/state.py
+4
View File
@@ -9,6 +9,7 @@ import ray
from ray import gcs_utils
from google.protobuf.json_format import MessageToDict
from ray._private import services
from ray._private.client_mode_hook import client_mode_hook
from ray.utils import (decode, binary_to_hex, hex_to_binary)
from ray._raylet import GlobalStateAccessor
@@ -851,6 +852,7 @@ def jobs():
return state.job_table()
@client_mode_hook
def nodes():
"""Get a list of the nodes in the cluster (for debugging only).
@@ -964,6 +966,7 @@ def object_transfer_timeline(filename=None):
return state.chrome_tracing_object_transfer_dump(filename=filename)
@client_mode_hook
def cluster_resources():
"""Get the current total cluster resources.
@@ -977,6 +980,7 @@ def cluster_resources():
return state.cluster_resources()
@client_mode_hook
def available_resources():
"""Get the current available cluster resources.
python/ray/test_utils.py
+1 -1
View File
@@ -446,4 +446,4 @@ def new_scheduler_enabled():
def client_test_enabled() -> bool:
return os.environ.get("RAY_TEST_CLIENT_MODE") == "1"
return os.environ.get("RAY_CLIENT_MODE") == "1"
python/ray/tests/BUILD
+1 -1
View File
@@ -167,7 +167,7 @@ py_test_module_list(
name_suffix = "_client_mode",
# TODO(barakmich): py_test will support env in Bazel 4.0.0...
# Until then, we can use tags.
#env = {"RAY_TEST_CLIENT_MODE": "true"},
#env = {"RAY_CLIENT_MODE": "1"},
tags = ["exclusive", "client_tests"],
deps = ["//:ray_lib"],
)
python/ray/tests/conftest.py
+2 -22
View File
@@ -9,18 +9,12 @@ import subprocess
import ray
from ray.cluster_utils import Cluster
from ray.test_utils import init_error_pubsub
from ray.test_utils import client_test_enabled
import ray.experimental.client as ray_client
@pytest.fixture
def shutdown_only():
yield None
# The code after the yield will run as teardown code.
if client_test_enabled():
ray_client.ray.disconnect()
ray_client._stop_test_server(1)
ray_client.reset_api()
ray.shutdown()
@@ -49,17 +43,10 @@ def _ray_start(**kwargs):
init_kwargs = get_default_fixture_ray_kwargs()
init_kwargs.update(kwargs)
# Start the Ray processes.
if client_test_enabled():
address_info = ray_client.ray.init(**init_kwargs)
else:
address_info = ray.init(**init_kwargs)
address_info = ray.init(**init_kwargs)
yield address_info
# The code after the yield will run as teardown code.
if client_test_enabled():
ray_client.ray.disconnect()
ray_client._stop_test_server(1)
ray_client.reset_api()
ray.shutdown()
@@ -144,16 +131,9 @@ def _ray_start_cluster(**kwargs):
# We assume driver will connect to the head (first node),
# so ray init will be invoked if do_init is true
if len(remote_nodes) == 1 and do_init:
if client_test_enabled():
ray_client.ray.init(address=cluster.address)
else:
ray.init(address=cluster.address)
ray.init(address=cluster.address)
yield cluster
# The code after the yield will run as teardown code.
if client_test_enabled():
ray_client.ray.disconnect()
ray_client._stop_test_server(1)
ray_client.reset_api()
ray.shutdown()
cluster.shutdown()
python/ray/tests/test_actor.py
+1 -8
View File
@@ -16,18 +16,12 @@ from ray.test_utils import wait_for_condition
from ray.test_utils import wait_for_pid_to_exit
from ray.tests.client_test_utils import create_remote_signal_actor
if client_test_enabled():
from ray.experimental.client import ray
else:
import ray
import ray
# NOTE: We have to import setproctitle after ray because we bundle setproctitle
# with ray.
import setproctitle # noqa
@pytest.mark.skipif(
client_test_enabled(),
reason="defining early, no ray package injection yet")
def test_caching_actors(shutdown_only):
# Test defining actors before ray.init() has been called.
@@ -705,7 +699,6 @@ def test_options_num_returns(ray_start_regular_shared):
assert ray.get([obj1, obj2]) == [1, 2]
@pytest.mark.skipif(client_test_enabled(), reason="remote args")
def test_options_name(ray_start_regular_shared):
@ray.remote
class Foo:
python/ray/tests/test_advanced.py
+2
View File
@@ -354,6 +354,8 @@ def test_illegal_api_calls(ray_start_regular):
ray.get(3)
@pytest.mark.skipif(
client_test_enabled(), reason="grpc interaction with releasing resources")
def test_multithreading(ray_start_2_cpus):
# This test requires at least 2 CPUs to finish since the worker does not
# release resources when joining the threads.
python/ray/tests/test_basic.py
+1 -4
View File
@@ -15,10 +15,7 @@ from ray.test_utils import (
wait_for_pid_to_exit,
)
if client_test_enabled():
from ray.experimental.client import ray
else:
import ray
import ray
logger = logging.getLogger(__name__)
python/ray/tests/test_experimental_client.py
+26 -4
View File
@@ -160,8 +160,7 @@ def test_basic_actor(ray_start_regular_shared):
def test_pass_handles(ray_start_regular_shared):
"""
Test that passing client handles to actors and functions to remote actors
"""Test that passing client handles to actors and functions to remote actors
in functions (on the server or raylet side) works transparently to the
caller.
"""
@@ -264,9 +263,32 @@ def test_stdout_log_stream(ray_start_regular_shared):
assert all((msg.find("Hello world") for msg in log_msgs))
def test_basic_named_actor(ray_start_regular_shared):
def test_create_remote_before_start(ray_start_regular_shared):
"""Creates remote objects (as though in a library) before
starting the client.
"""
Test that ray.get_actor() can create and return a detached actor.
from ray.experimental.client import ray
@ray.remote
class Returner:
def doit(self):
return "foo"
@ray.remote
def f(x):
return x + 20
# Prints in verbose tests
print("Created remote functions")
with ray_start_client_server() as ray:
assert ray.get(f.remote(3)) == 23
a = Returner.remote()
assert ray.get(a.doit.remote()) == "foo"
def test_basic_named_actor(ray_start_regular_shared):
"""Test that ray.get_actor() can create and return a detached actor.
"""
with ray_start_client_server() as ray:
python/ray/tests/test_experimental_client_metadata.py
+1 -2
View File
@@ -2,8 +2,7 @@ from ray.experimental.client.ray_client_helpers import ray_start_client_server
def test_get_ray_metadata(ray_start_regular_shared):
"""
Test the ClusterInfo client data pathway and API surface
"""Test the ClusterInfo client data pathway and API surface
"""
with ray_start_client_server() as ray:
ip_address = ray_start_regular_shared["node_ip_address"]
python/ray/tests/test_experimental_client_references.py
+3 -3
View File
@@ -2,11 +2,11 @@ from ray.experimental.client.ray_client_helpers import ray_start_client_server
from ray.test_utils import wait_for_condition
import ray as real_ray
from ray.core.generated.gcs_pb2 import ActorTableData
from ray.experimental.client import _get_server_instance
from ray.experimental.client.server.server import _get_current_servicer
def server_object_ref_count(n):
server = _get_server_instance()
server = _get_current_servicer()
assert server is not None
def test_cond():
@@ -20,7 +20,7 @@ def server_object_ref_count(n):
def server_actor_ref_count(n):
server = _get_server_instance()
server = _get_current_servicer()
assert server is not None
def test_cond():
python/ray/worker.py
+11
View File
@@ -51,6 +51,7 @@ from ray.ray_logging import setup_logger
from ray.ray_logging import global_worker_stdstream_dispatcher
from ray.utils import _random_string, check_oversized_pickle
from ray.util.inspect import is_cython
from ray._private.client_mode_hook import client_mode_hook
SCRIPT_MODE = 0
WORKER_MODE = 1
@@ -469,6 +470,7 @@ _global_node = None
"""ray.node.Node: The global node object that is created by ray.init()."""
@client_mode_hook
def init(
address=None,
*,
@@ -781,6 +783,7 @@ def init(
_post_init_hooks = []
@client_mode_hook
def shutdown(_exiting_interpreter=False):
"""Disconnect the worker, and terminate processes started by ray.init().
@@ -1044,6 +1047,7 @@ def listen_error_messages_raylet(worker, task_error_queue, threads_stopped):
worker.error_message_pubsub_client.close()
@client_mode_hook
def is_initialized():
"""Check if ray.init has been called yet.
@@ -1322,6 +1326,7 @@ def show_in_dashboard(message, key="", dtype="text"):
blocking_get_inside_async_warned = False
@client_mode_hook
def get(object_refs, *, timeout=None):
"""Get a remote object or a list of remote objects from the object store.
@@ -1400,6 +1405,7 @@ def get(object_refs, *, timeout=None):
return values
@client_mode_hook
def put(value):
"""Store an object in the object store.
@@ -1428,6 +1434,7 @@ def put(value):
blocking_wait_inside_async_warned = False
@client_mode_hook
def wait(object_refs, *, num_returns=1, timeout=None, fetch_local=True):
"""Return a list of IDs that are ready and a list of IDs that are not.
@@ -1528,6 +1535,7 @@ def wait(object_refs, *, num_returns=1, timeout=None, fetch_local=True):
return ready_ids, remaining_ids
@client_mode_hook
def get_actor(name):
"""Get a handle to a detached actor.
@@ -1548,6 +1556,7 @@ def get_actor(name):
return handle
@client_mode_hook
def kill(actor, *, no_restart=True):
"""Kill an actor forcefully.
@@ -1575,6 +1584,7 @@ def kill(actor, *, no_restart=True):
worker.core_worker.kill_actor(actor._ray_actor_id, no_restart)
@client_mode_hook
def cancel(object_ref, *, force=False, recursive=True):
"""Cancels a task according to the following conditions.
@@ -1691,6 +1701,7 @@ def make_decorator(num_returns=None,
return decorator
@client_mode_hook
def remote(*args, **kwargs):
"""Defines a remote function or an actor class.