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Fix bug in which remote function redefinition doesn't happen. (#6175)

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This commit is contained in:
Robert Nishihara
2019-11-26 09:19:19 -08:00
committed by Edward Oakes
parent 7f8de61441
commit ffb9c0ecae
6 changed files with 256 additions and 47 deletions
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python/ray/remote_function.py
+23 -7
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@@ -6,6 +6,7 @@ import os
import logging
from functools import wraps
from ray import cloudpickle as pickle
from ray.function_manager import FunctionDescriptor
import ray.signature
@@ -24,7 +25,10 @@ class RemoteFunction(object):
Attributes:
_function: The original function.
_function_descriptor: The function descriptor.
_function_descriptor: The function descriptor. This is not defined
until the remote function is first invoked because that is when the
function is pickled, and the pickled function is used to compute
the function descriptor.
_function_name: The module and function name.
_num_cpus: The default number of CPUs to use for invocations of this
remote function.
@@ -57,9 +61,6 @@ class RemoteFunction(object):
def __init__(self, function, num_cpus, num_gpus, memory,
object_store_memory, resources, num_return_vals, max_calls):
self._function = function
self._function_descriptor = FunctionDescriptor.from_function(function)
self._function_descriptor_list = (
self._function_descriptor.get_function_descriptor_list())
self._function_name = (
self._function.__module__ + "." + self._function.__name__)
self._num_cpus = (DEFAULT_REMOTE_FUNCTION_CPUS
@@ -146,10 +147,25 @@ class RemoteFunction(object):
worker = ray.worker.get_global_worker()
worker.check_connected()
# If this function was not exported in this session and job, we need to
# export this function again, because the current GCS doesn't have it.
if self._last_export_session_and_job != worker.current_session_and_job:
# If this function was not exported in this session and job,
# we need to export this function again, because current GCS
# doesn't have it.
# There is an interesting question here. If the remote function is
# used by a subsequent driver (in the same script), should the
# second driver pickle the function again? If yes, then the remote
# function definition can differ in the second driver (e.g., if
# variables in its closure have changed). We probably want the
# behavior of the remote function in the second driver to be
# independent of whether or not the function was invoked by the
# first driver. This is an argument for repickling the function,
# which we do here.
self._pickled_function = pickle.dumps(self._function)
self._function_descriptor = FunctionDescriptor.from_function(
self._function, self._pickled_function)
self._function_descriptor_list = (
self._function_descriptor.get_function_descriptor_list())
self._last_export_session_and_job = worker.current_session_and_job
worker.function_actor_manager.export(self)