hermetically seal everything, bring it up to date

python/client.py

@@ -0,0 +1,17 @@
+from ray import ray
+
+ray.connect("localhost:50050")
+
+@ray.remote
+def plus2(x):
+    return x + 2
+
+print(ray.get(plus2.remote(4)))
+
+@ray.remote
+def fact(x):
+    if x <= 0:
+        return 1
+    return x * ray.get(fact.remote(x - 1))
+
+print(ray.get(fact.remote(20)))

python/ray/__init__.py

@@ -0,0 +1,107 @@
+from ray.api import ClientAPI
+from ray.api import APIImpl
+from typing import Optional, List, Tuple
+from contextlib import contextmanager
+
+import logging
+
+logger = logging.getLogger(__name__)
+
+# _client_api has to be external to the API stub, below.
+# Otherwise, ray.remote() that contains ray.remote()
+# contains a reference to the RayAPIStub, therefore a
+# reference to the _client_api, and then tries to pickle
+# the thing.
+_client_api: Optional[APIImpl] = None
+
+_server_api: Optional[APIImpl] = None
+
+_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
+    yield _server_api
+    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
+    global _server_api
+    global _is_server
+    api = None
+    if _is_server:
+        api = _server_api
+    else:
+        api = _client_api
+    if api is None:
+        # We're inside a raylet worker
+        raise Exception("CoreRayAPI not supported")
+    return api
+
+
+class RayAPIStub:
+    def connect(self,
+                conn_str: str,
+                secure: bool = False,
+                metadata: List[Tuple[str, str]] = None,
+                stub=None):
+        from ray.worker import Worker
+        _client_worker = Worker(
+            conn_str, secure=secure, metadata=metadata, stub=stub)
+        _set_client_api(ClientAPI(_client_worker))
+
+    def disconnect(self):
+        global _client_api
+        if _client_api is not None:
+            _client_api.close()
+        _client_api = None
+
+    def __getattr__(self, key: str):
+        global _get_client_api
+        api = _get_client_api()
+        return getattr(api, key)
+
+
+ray = RayAPIStub()
+
+# 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
+# still gets expected functionality. This is the way the ray package
+# worked in the past.
+#
+# This really calls for PEP 562: https://www.python.org/dev/peps/pep-0562/
+# But until Python 3.6 is EOL, here we are.

python/ray/api.py

@@ -0,0 +1,77 @@
+# 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
+
+
+class APIImpl(ABC):
+    @abstractmethod
+    def get(self, *args, **kwargs):
+        pass
+
+    @abstractmethod
+    def put(self, *args, **kwargs):
+        pass
+
+    @abstractmethod
+    def wait(self, *args, **kwargs):
+        pass
+
+    @abstractmethod
+    def remote(self, *args, **kwargs):
+        pass
+
+    @abstractmethod
+    def call_remote(self, instance, kind: int, *args, **kwargs):
+        pass
+
+    @abstractmethod
+    def get_actor_from_object(self, id):
+        pass
+
+    @abstractmethod
+    def close(self, *args, **kwargs):
+        pass
+
+
+class ClientAPI(APIImpl):
+    def __init__(self, worker):
+        self.worker = worker
+
+    def get(self, *args, **kwargs):
+        return self.worker.get(*args, **kwargs)
+
+    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, f, kind, *args, **kwargs):
+        return self.worker.call_remote(f, kind, *args, **kwargs)
+
+    def get_actor_from_object(self, id):
+        raise Exception("Calling get_actor_from_object on the client side")
+
+    def close(self, *args, **kwargs):
+        return self.worker.close()
+
+    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)

python/ray/client_app.py

@@ -0,0 +1,90 @@
+from ray import ray
+from typing import Tuple
+
+ray.connect("localhost:50051")
+
+
+@ray.remote
+class HelloActor:
+    def __init__(self):
+        self.count = 0
+
+    def say_hello(self, whom: str) -> Tuple[str, int]:
+        self.count += 1
+        return ("Hello " + whom, self.count)
+
+
+actor = HelloActor.remote()
+s, count = ray.get(actor.say_hello.remote("you"))
+print(s, count)
+assert s == "Hello you"
+assert count == 1
+s, count = ray.get(actor.say_hello.remote("world"))
+print(s, count)
+assert s == "Hello world"
+assert count == 2
+
+
+@ray.remote
+def plus2(x):
+    return x + 2
+
+
+@ray.remote
+def fact(x):
+    print(x, type(fact))
+    if x <= 0:
+        return 1
+    # This hits the "nested tasks" issue
+    # https://github.com/ray-project/ray/issues/3644
+    # So we're on the right track!
+    return ray.get(fact.remote(x - 1)) * x
+
+
+@ray.remote
+def get_nodes():
+    return ray.nodes()  # Can access the full Ray API in remote methods.
+
+
+print("Cluster nodes", ray.get(get_nodes.remote()))
+print(ray.nodes())
+
+objectref = ray.put("hello world")
+
+# `ClientObjectRef(...)`
+print(objectref)
+
+# `hello world`
+print(ray.get(objectref))
+
+ref2 = plus2.remote(234)
+# `ClientObjectRef(...)`
+print(ref2)
+# `236`
+print(ray.get(ref2))
+
+ref3 = fact.remote(20)
+# `ClientObjectRef(...)`
+print(ref3)
+# `2432902008176640000`
+print(ray.get(ref3))
+
+# Reuse the cached ClientRemoteFunc object
+ref4 = fact.remote(5)
+# `120`
+print(ray.get(ref4))
+
+ref5 = fact.remote(10)
+
+print([ref2, ref3, ref4, ref5])
+# should return ref2, ref3, ref4
+res = ray.wait([ref5, ref2, ref3, ref4], num_returns=3)
+print(res)
+assert [ref2, ref3, ref4] == res[0]
+assert [ref5] == res[1]
+
+# should return ref2, ref3, ref4, ref5
+res = ray.wait([ref2, ref3, ref4, ref5], num_returns=4)
+print(res)
+assert [ref2, ref3, ref4, ref5] == res[0]
+assert [] == res[1]

python/ray/common.py

@@ -0,0 +1,205 @@
+import rpc.ray_client_pb2 as ray_client_pb2
+from ray import ray
+from typing import Any
+from typing import Dict
+import cloudpickle
+
+
+class ClientBaseRef:
+    def __init__(self, id):
+        self.id = id
+
+    def __repr__(self):
+        return "%s(%s)" % (
+            type(self).__name__,
+            self.id.hex(),
+        )
+
+    def __eq__(self, other):
+        return self.id == other.id
+
+    def binary(self):
+        return self.id
+
+
+class ClientObjectRef(ClientBaseRef):
+    pass
+
+
+class ClientActorNameRef(ClientBaseRef):
+    pass
+
+
+class ClientRemoteFunc:
+    def __init__(self, f):
+        self._func = f
+        self._name = f.__name__
+        self.id = None
+        self._ref = None
+        self._raylet_remote = None
+
+    def __call__(self, *args, **kwargs):
+        raise TypeError(f"Remote function cannot be called directly. "
+                        "Use {self._name}.remote method instead")
+
+    def remote(self, *args, **kwargs):
+        return ray.call_remote(self, ray_client_pb2.ClientTask.FUNCTION, *args,
+                               **kwargs)
+
+    def _get_ray_remote_impl(self):
+        if self._raylet_remote is None:
+            self._raylet_remote = ray.remote(self._func)
+        return self._raylet_remote
+
+    def __repr__(self):
+        return "ClientRemoteFunc(%s, %s)" % (self._name, self.id)
+
+    def _prepare_client_task(self) -> ray_client_pb2.ClientTask:
+        if self._ref is None:
+            self._ref = ray.put(self._func)
+        task = ray_client_pb2.ClientTask()
+        task.type = ray_client_pb2.ClientTask.FUNCTION
+        task.name = self._name
+        task.payload_id = self._ref.id
+        return task
+
+
+class ClientActorClass:
+    def __init__(self, actor_cls):
+        self.actor_cls = actor_cls
+        self._name = actor_cls.__name__
+        self._ref = None
+        self._raylet_remote = None
+
+    def __call__(self, *args, **kwargs):
+        raise TypeError(f"Remote actor cannot be instantiated directly. "
+                        "Use {self._name}.remote() instead")
+
+    def __getstate__(self) -> Dict:
+        state = {
+            "actor_cls": self.actor_cls,
+            "_name": self._name,
+            "_ref": self._ref,
+        }
+        return state
+
+    def __setstate__(self, state: Dict) -> None:
+        self.actor_cls = state["actor_cls"]
+        self._name = state["_name"]
+        self._ref = state["_ref"]
+
+    def remote(self, *args, **kwargs):
+        # Actually instantiate the actor
+        ref = ray.call_remote(self, ray_client_pb2.ClientTask.ACTOR, *args,
+                              **kwargs)
+        return ClientActorHandle(ClientActorNameRef(ref.id), self)
+
+    def __repr__(self):
+        return "ClientRemoteActor(%s, %s)" % (self._name, self._ref)
+
+    def __getattr__(self, key):
+        raise NotImplementedError("static methods")
+
+    def _prepare_client_task(self) -> ray_client_pb2.ClientTask:
+        if self._ref is None:
+            self._ref = ray.put(self.actor_cls)
+        task = ray_client_pb2.ClientTask()
+        task.type = ray_client_pb2.ClientTask.ACTOR
+        task.name = self._name
+        task.payload_id = self._ref.id
+        return task
+
+
+class ClientActorHandle:
+    def __init__(self, actor_id: ClientActorNameRef,
+                 actor_class: ClientActorClass):
+        self.actor_id = actor_id
+        self.actor_class = actor_class
+        self._real_actor_handle = None
+
+    def _get_ray_remote_impl(self):
+        if self._real_actor_handle is None:
+            self._real_actor_handle = ray.get_actor_from_object(self.actor_id)
+        return self._real_actor_handle
+
+    def __getstate__(self) -> Dict:
+        state = {
+            "actor_id": self.actor_id,
+            "actor_class": self.actor_class,
+            "_real_actor_handle": self._real_actor_handle,
+        }
+        return state
+
+    def __setstate__(self, state: Dict) -> None:
+        self.actor_id = state["actor_id"]
+        self.actor_class = state["actor_class"]
+        self._real_actor_handle = state["_real_actor_handle"]
+
+    def __getattr__(self, key):
+        return ClientRemoteMethod(self, key)
+
+    def __repr__(self):
+        return "ClientActorHandle(%s, %s, %s)" % (
+            self.actor_id, self.actor_class, self._real_actor_handle)
+
+
+class ClientRemoteMethod:
+    def __init__(self, actor_handle: ClientActorHandle, method_name: str):
+        self.actor_handle = actor_handle
+        self.method_name = method_name
+
+    def __call__(self, *args, **kwargs):
+        raise TypeError(f"Remote method cannot be called directly. "
+                        "Use {self._name}.remote() instead")
+
+    def _get_ray_remote_impl(self):
+        return getattr(self.actor_handle._get_ray_remote_impl(),
+                       self.method_name)
+
+    def __getstate__(self) -> Dict:
+        state = {
+            "actor_handle": self.actor_handle,
+            "method_name": self.method_name,
+        }
+        return state
+
+    def __setstate__(self, state: Dict) -> None:
+        self.actor_handle = state["actor_handle"]
+        self.method_name = state["method_name"]
+
+    def remote(self, *args, **kwargs):
+        return ray.call_remote(self, ray_client_pb2.ClientTask.METHOD, *args,
+                               **kwargs)
+
+    def __repr__(self):
+        name = "%s.%s" % (self.actor_handle.actor_class._name,
+                          self.method_name)
+        return "ClientRemoteMethod(%s, %s)" % (name,
+                                               self.actor_handle.actor_id)
+
+    def _prepare_client_task(self) -> ray_client_pb2.ClientTask:
+        task = ray_client_pb2.ClientTask()
+        task.type = ray_client_pb2.ClientTask.METHOD
+        task.name = self.method_name
+        task.payload_id = self.actor_handle.actor_id.id
+        return task
+
+
+def convert_from_arg(pb) -> Any:
+    if pb.local == ray_client_pb2.Arg.Locality.REFERENCE:
+        return ClientObjectRef(pb.reference_id)
+    elif pb.local == ray_client_pb2.Arg.Locality.INTERNED:
+        return cloudpickle.loads(pb.data)
+
+    raise Exception("convert_from_arg: Uncovered locality enum")
+
+
+def convert_to_arg(val):
+    out = ray_client_pb2.Arg()
+    if isinstance(val, ClientObjectRef):
+        out.local = ray_client_pb2.Arg.Locality.REFERENCE
+        out.reference_id = val.id
+    else:
+        out.local = ray_client_pb2.Arg.Locality.INTERNED
+        out.data = cloudpickle.dumps(val)
+    return out

python/ray/worker.py

@@ -0,0 +1,142 @@
+"""This file includes the Worker class which sits on the client side.
+It implements the Ray API functions that are forwarded through grpc calls
+to the server.
+"""
+import inspect
+import logging
+from typing import List
+from typing import Tuple
+
+import cloudpickle
+import grpc
+
+import rpc.ray_client_pb2 as ray_client_pb2
+import rpc.ray_client_pb2_grpc as ray_client_pb2_grpc
+from ray.common import convert_to_arg
+from ray.common import ClientObjectRef
+from ray.common import ClientActorClass
+from ray.common import ClientRemoteFunc
+
+logger = logging.getLogger(__name__)
+
+
+class Worker:
+    def __init__(self,
+                 conn_str: str = "",
+                 secure: bool = False,
+                 metadata: List[Tuple[str, str]] = None,
+                 stub=None):
+        """Initializes the worker side grpc client.
+
+        Args:
+            stub: custom grpc stub.
+            secure: whether to use SSL secure channel or not.
+            metadata: additional metadata passed in the grpc request headers.
+        """
+        self.metadata = metadata
+        if stub is None:
+            if secure:
+                credentials = grpc.ssl_channel_credentials()
+                self.channel = grpc.secure_channel(conn_str, credentials)
+            else:
+                self.channel = grpc.insecure_channel(conn_str)
+            self.server = ray_client_pb2_grpc.RayletDriverStub(self.channel)
+        else:
+            self.server = stub
+
+    def get(self, ids):
+        to_get = []
+        single = False
+        if isinstance(ids, list):
+            to_get = [x.id for x in ids]
+        elif isinstance(ids, ClientObjectRef):
+            to_get = [ids.id]
+            single = True
+        else:
+            raise Exception("Can't get something that's not a "
+                            "list of IDs or just an ID: %s" % type(ids))
+        out = [self._get(x) for x in to_get]
+        if single:
+            out = out[0]
+        return out
+
+    def _get(self, id: bytes):
+        req = ray_client_pb2.GetRequest(id=id)
+        data = self.server.GetObject(req, metadata=self.metadata)
+        if not data.valid:
+            raise Exception(
+                "Client GetObject returned invalid data: id invalid?")
+        return cloudpickle.loads(data.data)
+
+    def put(self, vals):
+        to_put = []
+        single = False
+        if isinstance(vals, list):
+            to_put = vals
+        else:
+            single = True
+            to_put.append(vals)
+
+        out = [self._put(x) for x in to_put]
+        if single:
+            out = out[0]
+        return out
+
+    def _put(self, val):
+        data = cloudpickle.dumps(val)
+        req = ray_client_pb2.PutRequest(data=data)
+        resp = self.server.PutObject(req, metadata=self.metadata)
+        return ClientObjectRef(resp.id)
+
+    def wait(self,
+             object_refs: List[ClientObjectRef],
+             *,
+             num_returns: int = 1,
+             timeout: float = None
+             ) -> Tuple[List[ClientObjectRef], List[ClientObjectRef]]:
+        assert isinstance(object_refs, list)
+        for ref in object_refs:
+            assert isinstance(ref, ClientObjectRef)
+        data = {
+            "object_refs": [
+                cloudpickle.dumps(object_ref) for object_ref in object_refs
+            ],
+            "num_returns": num_returns,
+            "timeout": timeout if timeout else -1
+        }
+        req = ray_client_pb2.WaitRequest(**data)
+        resp = self.server.WaitObject(req, metadata=self.metadata)
+        if not resp.valid:
+            # TODO(ameer): improve error/exceptions messages.
+            raise Exception("Client Wait request failed. Reference invalid?")
+        client_ready_object_ids = [
+            ClientObjectRef(id) for id in resp.ready_object_ids
+        ]
+        client_remaining_object_ids = [
+            ClientObjectRef(id) for id in resp.remaining_object_ids
+        ]
+
+        return (client_ready_object_ids, client_remaining_object_ids)
+
+    def remote(self, function_or_class, *args, **kwargs):
+        # TODO(barakmich): Arguments to ray.remote
+        # get captured here.
+        if inspect.isfunction(function_or_class):
+            return ClientRemoteFunc(function_or_class)
+        elif inspect.isclass(function_or_class):
+            return ClientActorClass(function_or_class)
+        else:
+            raise TypeError("The @ray.remote decorator must be applied to "
+                            "either a function or to a class.")
+
+    def call_remote(self, instance, kind, *args, **kwargs):
+        task = instance._prepare_client_task()
+        for arg in args:
+            pb_arg = convert_to_arg(arg)
+            task.args.append(pb_arg)
+        logging.debug("Scheduling %s" % task)
+        ticket = self.server.Schedule(task, metadata=self.metadata)
+        return ClientObjectRef(ticket.return_id)
+
+    def close(self):
+        self.channel.close()

python/ray_worker/__init__.py

@@ -0,0 +1,74 @@
+import rpc.ray_client_pb2 as ray_client_pb2
+import rpc.ray_client_pb2_grpc as ray_client_pb2_grpc
+
+import queue
+import grpc
+import cloudpickle
+import threading
+import concurrent.futures
+from ray import ray
+from ray.common import ClientObjectRef
+
+
+class Worker:
+    def __init__(self, conn_str):
+        self.channel = grpc.insecure_channel(conn_str)
+        self.worker_stub = ray_client_pb2_grpc.RayletWorkerConnectionStub(self.channel)
+        self.send_queue = None
+        self.pool = concurrent.futures.ThreadPoolExecutor(max_workers=3)
+        self.server = ray_client_pb2_grpc.RayletDriverStub(self.channel)
+
+    def begin(self):
+        self.send_queue = queue.Queue()
+        work_stream = self.worker_stub.Workstream(iter(self.send_queue.get, None))
+        start = ray_client_pb2.WorkStatus(
+            status = ray_client_pb2.WorkStatus.StatusCode.READY,
+            error_msg = "python_worker",
+        )
+        self.send_queue.put(start)
+        for work in work_stream:
+            print("Got work")
+            task = work.task
+            if task.type != ray_client_pb2.ClientTask.RemoteExecType.FUNCTION:
+                send_queue.put(ray_client_pb2.WorkStatus(
+                    status = ray_client_pb2.WorkStatus.StatusCode.ERROR,
+                    error_msg = "unimplemented",
+                ))
+                continue
+            args = self.decode_args(task)
+            func = self.get(task.payload_id)
+            #self.pool.submit(self.run_and_return, func, args, work.ticket)
+            t = threading.Thread(target=self.run_and_return, args=(func, args, work.ticket))
+            t.start()
+
+
+    def run_and_return(self, func, args, ticket):
+        res = func(*args)
+        out_data = cloudpickle.dumps(res)
+        self.send_queue.put(ray_client_pb2.WorkStatus(
+            status = ray_client_pb2.WorkStatus.StatusCode.COMPLETE,
+            complete_data = out_data,
+            finished_ticket = ticket,
+        ))
+
+    # def get(self, id_bytes):
+        # data = self.server.GetObject(ray_client_pb2.GetRequest(
+            # id = id_bytes,
+        # ))
+        # return cloudpickle.loads(data.data)
+    def get(self, id_bytes):
+        return ray.get(ClientObjectRef(id_bytes))
+
+    def decode_args(self, task):
+        out = []
+        for arg in task.args:
+            t = self.convert_from_arg(arg)
+            out.append(t)
+        return out
+
+    def convert_from_arg(self, pb):
+        if pb.local == ray_client_pb2.Arg.Locality.REFERENCE:
+            return self.get(pb.reference_id)
+        elif pb.local == ray_client_pb2.Arg.Locality.INTERNED:
+            return cloudpickle.loads(pb.data)
+        raise Exception("convert_from_arg: Uncovered locality enum")

python/rpc/mk_proto.sh

@@ -1 +1,7 @@
+#!/bin/sh
 python -m grpc_tools.protoc -I../../ray_rpc --python_out=. --grpc_python_out=. ../../ray_rpc/ray_client.proto
+SEDCMD="sed"
+if [ -n "`which gsed`" ]; then
+  SEDCMD="gsed"
+fi
+$SEDCMD -i 's/^import ray_client_pb2/import rpc.ray_client_pb2/g' *.py

python/worker.py

@@ -1,81 +1,8 @@
 # from rpc import ray_client_pb2
 # from rpc import ray_client_pb2_grpc
-import ray.core.generated.ray_client_pb2 as ray_client_pb2
-import ray.core.generated.ray_client_pb2_grpc as ray_client_pb2_grpc
-
-import queue
+from ray_worker import Worker
 import sys
-import grpc
-import cloudpickle
-import threading
-import concurrent.futures
-from ray.experimental.client import ray
-from ray.experimental.client.common import ClientObjectRef
-
-
-
-class Worker:
-    def __init__(self, conn_str):
-        self.channel = grpc.insecure_channel(conn_str)
-        self.worker_stub = ray_client_pb2_grpc.RayletWorkerConnectionStub(self.channel)
-        self.send_queue = None
-        self.pool = concurrent.futures.ThreadPoolExecutor(max_workers=3)
-        self.server = ray_client_pb2_grpc.RayletDriverStub(self.channel)
-
-    def begin(self):
-        self.send_queue = queue.Queue()
-        work_stream = self.worker_stub.Workstream(iter(self.send_queue.get, None))
-        start = ray_client_pb2.WorkStatus(
-            status = ray_client_pb2.WorkStatus.StatusCode.READY,
-            error_msg = "python_worker",
-        )
-        self.send_queue.put(start)
-        for work in work_stream:
-            print("Got work")
-            task = work.task
-            if task.type != ray_client_pb2.ClientTask.RemoteExecType.FUNCTION:
-                send_queue.put(ray_client_pb2.WorkStatus(
-                    status = ray_client_pb2.WorkStatus.StatusCode.ERROR,
-                    error_msg = "unimplemented",
-                ))
-                continue
-            args = self.decode_args(task)
-            func = self.get(task.payload_id)
-            #self.pool.submit(self.run_and_return, func, args, work.ticket)
-            t = threading.Thread(target=self.run_and_return, args=(func, args, work.ticket))
-            t.start()
-
-
-    def run_and_return(self, func, args, ticket):
-        res = func(*args)
-        out_data = cloudpickle.dumps(res)
-        self.send_queue.put(ray_client_pb2.WorkStatus(
-            status = ray_client_pb2.WorkStatus.StatusCode.COMPLETE,
-            complete_data = out_data,
-            finished_ticket = ticket,
-        ))
-
-    # def get(self, id_bytes):
-        # data = self.server.GetObject(ray_client_pb2.GetRequest(
-            # id = id_bytes,
-        # ))
-        # return cloudpickle.loads(data.data)
-    def get(self, id_bytes):
-        return ray.get(ClientObjectRef(id_bytes))
-
-    def decode_args(self, task):
-        out = []
-        for arg in task.args:
-            t = self.convert_from_arg(arg)
-            out.append(t)
-        return out
-
-    def convert_from_arg(self, pb):
-        if pb.local == ray_client_pb2.Arg.Locality.REFERENCE:
-            return self.get(pb.reference_id)
-        elif pb.local == ray_client_pb2.Arg.Locality.INTERNED:
-            return cloudpickle.loads(pb.data)
-        raise Exception("convert_from_arg: Uncovered locality enum")
+from ray import ray
 
 
 def main():

raylet_grpc.go

@@ -58,7 +58,7 @@ func (r *Raylet) Workstream(conn WorkstreamConnection) error {
 	worker := &SimpleWorker{
 		workChan:   make(chan *ray_rpc.Work),
 		clientConn: conn,
-		pool:       wp,
+		pool:       r.Workers,
 	}
 	r.Workers.Register(worker)
 	err := worker.Run()

worker.go

@@ -27,7 +27,7 @@ func (s *SimpleWorker) AssignWork(work *ray_rpc.Work) error {
 }
 
 func (s *SimpleWorker) Close() error {
-	close(w.workChan)
+	close(s.workChan)
 	return nil
 }
 

worker_pool.go

@@ -34,6 +34,7 @@ func (wp *SimpleRRWorkerPool) Register(worker Worker) error {
 	wp.Lock()
 	defer wp.Unlock()
 	wp.workers = append(wp.workers, worker)
+	return nil
 }
 
 func (wp *SimpleRRWorkerPool) Schedule(work *ray_rpc.Work) error {