在 joblib `Parallel` 上下文中 pickling `matlab` 对象时出错
Error pickling a `matlab` object in joblib `Parallel` context
我正在 运行 从 Python 上下文中并行处理一些 Matlab 代码（我知道，但这就是正在发生的事情），我遇到了涉及 matlab.double。相同的代码在 multiprocessing.Pool 中运行良好，所以我无法弄清楚问题出在哪里。这是一个最小的重现测试用例。
import matlab
from multiprocessing import Pool
from joblib import Parallel, delayed
# A global object that I would like to be available in the parallel subroutine
x = matlab.double([[0.0]])
def f(i):
print(i, x)
with Pool(4) as p:
p.map(f, range(10))
# This prints 1, [[0.0]]\n2, [[0.0]]\n... as expected
for _ in Parallel(4, backend='multiprocessing')(delayed(f)(i) for i in range(10)):
pass
# This also prints 1, [[0.0]]\n2, [[0.0]]\n... as expected
# Now run with default `backend='loky'`
for _ in Parallel(4)(delayed(f)(i) for i in range(10)):
pass
# ^ this crashes.
因此，唯一有问题的是使用 'loky' 后端的那个。
完整的追溯是：
exception calling callback for <Future at 0x7f63b5a57358 state=finished raised BrokenProcessPool>
joblib.externals.loky.process_executor._RemoteTraceback:
'''
Traceback (most recent call last):
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/process_executor.py", line 391, in _process_worker
call_item = call_queue.get(block=True, timeout=timeout)
File "~/miniconda3/envs/myenv/lib/python3.6/multiprocessing/queues.py", line 113, in get
return _ForkingPickler.loads(res)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/mlarray.py", line 31, in <module>
from _internal.mlarray_sequence import _MLArrayMetaClass
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/_internal/mlarray_sequence.py", line 3, in <module>
from _internal.mlarray_utils import _get_strides, _get_size, \
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/_internal/mlarray_utils.py", line 4, in <module>
import matlab
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/__init__.py", line 24, in <module>
from mlarray import double, single, uint8, int8, uint16, \
ImportError: cannot import name 'double'
'''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/_base.py", line 625, in _invoke_callbacks
callback(self)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 309, in __call__
self.parallel.dispatch_next()
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 731, in dispatch_next
if not self.dispatch_one_batch(self._original_iterator):
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 759, in dispatch_one_batch
self._dispatch(tasks)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 716, in _dispatch
job = self._backend.apply_async(batch, callback=cb)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/_parallel_backends.py", line 510, in apply_async
future = self._workers.submit(SafeFunction(func))
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/reusable_executor.py", line 151, in submit
fn, *args, **kwargs)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/process_executor.py", line 1022, in submit
raise self._flags.broken
joblib.externals.loky.process_executor.BrokenProcessPool: A task has failed to un-serialize. Please ensure that the arguments of the function are all picklable.
joblib.externals.loky.process_executor._RemoteTraceback:
'''
Traceback (most recent call last):
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/process_executor.py", line 391, in _process_worker
call_item = call_queue.get(block=True, timeout=timeout)
File "~/miniconda3/envs/myenv/lib/python3.6/multiprocessing/queues.py", line 113, in get
return _ForkingPickler.loads(res)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/mlarray.py", line 31, in <module>
from _internal.mlarray_sequence import _MLArrayMetaClass
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/_internal/mlarray_sequence.py", line 3, in <module>
from _internal.mlarray_utils import _get_strides, _get_size, \
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/_internal/mlarray_utils.py", line 4, in <module>
import matlab
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/__init__.py", line 24, in <module>
from mlarray import double, single, uint8, int8, uint16, \
ImportError: cannot import name 'double'
'''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "test.py", line 20, in <module>
for _ in Parallel(4)(delayed(f)(i) for i in range(10)):
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 934, in __call__
self.retrieve()
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 833, in retrieve
self._output.extend(job.get(timeout=self.timeout))
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/_parallel_backends.py", line 521, in wrap_future_result
return future.result(timeout=timeout)
File "~/miniconda3/envs/myenv/lib/python3.6/concurrent/futures/_base.py", line 432, in result
return self.__get_result()
File "~/miniconda3/envs/myenv/lib/python3.6/concurrent/futures/_base.py", line 384, in __get_result
raise self._exception
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/_base.py", line 625, in _invoke_callbacks
callback(self)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 309, in __call__
self.parallel.dispatch_next()
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 731, in dispatch_next
if not self.dispatch_one_batch(self._original_iterator):
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 759, in dispatch_one_batch
self._dispatch(tasks)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 716, in _dispatch
job = self._backend.apply_async(batch, callback=cb)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/_parallel_backends.py", line 510, in apply_async
future = self._workers.submit(SafeFunction(func))
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/reusable_executor.py", line 151, in submit
fn, *args, **kwargs)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/process_executor.py", line 1022, in submit
raise self._flags.broken
joblib.externals.loky.process_executor.BrokenProcessPool: A task has failed to un-serialize. Please ensure that the arguments of the function are all picklable.
查看回溯，似乎根本原因是在子进程中导入 matlab 包时出现问题。
可能值得注意的是，如果我定义了 x = np.array([[0.0]])（在导入 numpy as np 之后），那么所有 运行 都很好。当然，主进程对任何 matlab 导入都没有问题，所以我不确定为什么子进程会这样。
我不确定这个错误是否与 matlab 包有什么特别的关系，或者它是否与全局变量和 cloudpickle 或 loky 有关。在我的应用程序中，坚持使用 loky 会有所帮助，所以我将不胜感激！
我还应该注意，我正在为 Python 使用官方 Matlab 引擎：https://www.mathworks.com/help/matlab/matlab-engine-for-python.html。我想这可能会让其他人很难尝试测试用例，所以我希望我可以用 matlab.double 以外的类型重现这个错误，但我还没有找到另一个。
深入挖掘后，我注意到导入 matlab 包的过程比我预期的更循环，我推测这可能是问题的一部分？问题是，当 import matlab 被 loky 的 _ForkingPickler 变为 运行 时，首先导入一些文件 matlab/mlarray.py，然后导入其他一些文件，其中一个包含 import matlab，这会导致 matlab/__init__.py 变为 运行，它内部有 from mlarray import double, single, uint8, ...，这是导致崩溃的行。
这种循环可能是问题所在吗？如果是这样，为什么我可以在主进程中导入这个模块而不是在 loky 后端？
错误是由于子进程中全局对象加载顺序不正确引起的。在回溯中可以清楚地看到
_ForkingPickler.loads(res) -> ... -> import matlab -> from mlarray import ...
当 cloudpickle.
加载全局变量 x 时，matlab 尚未导入
joblib 和 loky 似乎将模块视为普通全局对象并将它们动态发送到子进程。 joblib 不记录那些 objects/modules 的定义顺序。因此它们在子进程中以随机顺序加载（初始化）。
一个简单的解决方法是在您的函数中导入 matlab 后手动 pickle matlab 对象并加载它。
import matlab
import pickle
px = pickle.dumps(matlab.double([[0.0]]))
def f(i):
import matlab
x=pickle.loads(px)
print(i, x)
当然你也可以使用joblib.dumps和loads来序列化对象。
使用初始化器
感谢@Aaron 的建议，您也可以在加载x.
之前使用initializer（for loky）导入Matlab
Currently there's no simple API to specify initializer。所以我写了一个简单的函数：
def with_initializer(self, f_init):
# Overwrite initializer hook in the Loky ProcessPoolExecutor
# https://github.com/tomMoral/loky/blob/f4739e123acb711781e46581d5ed31ed8201c7a9/loky/process_executor.py#L850
hasattr(self._backend, '_workers') or self.__enter__()
origin_init = self._backend._workers._initializer
def new_init():
origin_init()
f_init()
self._backend._workers._initializer = new_init if callable(origin_init) else f_init
return self
它有点老套，但适用于当前版本的 joblib 和 loky。
然后你可以像这样使用它：
import matlab
from joblib import Parallel, delayed
x = matlab.double([[0.0]])
def f(i):
print(i, x)
def _init_matlab():
import matlab
with Parallel(4) as p:
for _ in with_initializer(p, _init_matlab)(delayed(f)(i) for i in range(10)):
pass
希望joblib的开发者以后在Parallel的构造函数中加入initializer参数
我正在 运行 从 Python 上下文中并行处理一些 Matlab 代码（我知道，但这就是正在发生的事情），我遇到了涉及 matlab.double。相同的代码在 multiprocessing.Pool 中运行良好，所以我无法弄清楚问题出在哪里。这是一个最小的重现测试用例。
import matlab
from multiprocessing import Pool
from joblib import Parallel, delayed
# A global object that I would like to be available in the parallel subroutine
x = matlab.double([[0.0]])
def f(i):
print(i, x)
with Pool(4) as p:
p.map(f, range(10))
# This prints 1, [[0.0]]\n2, [[0.0]]\n... as expected
for _ in Parallel(4, backend='multiprocessing')(delayed(f)(i) for i in range(10)):
pass
# This also prints 1, [[0.0]]\n2, [[0.0]]\n... as expected
# Now run with default `backend='loky'`
for _ in Parallel(4)(delayed(f)(i) for i in range(10)):
pass
# ^ this crashes.
因此，唯一有问题的是使用 'loky' 后端的那个。
完整的追溯是：
exception calling callback for <Future at 0x7f63b5a57358 state=finished raised BrokenProcessPool>
joblib.externals.loky.process_executor._RemoteTraceback:
'''
Traceback (most recent call last):
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/process_executor.py", line 391, in _process_worker
call_item = call_queue.get(block=True, timeout=timeout)
File "~/miniconda3/envs/myenv/lib/python3.6/multiprocessing/queues.py", line 113, in get
return _ForkingPickler.loads(res)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/mlarray.py", line 31, in <module>
from _internal.mlarray_sequence import _MLArrayMetaClass
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/_internal/mlarray_sequence.py", line 3, in <module>
from _internal.mlarray_utils import _get_strides, _get_size, \
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/_internal/mlarray_utils.py", line 4, in <module>
import matlab
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/__init__.py", line 24, in <module>
from mlarray import double, single, uint8, int8, uint16, \
ImportError: cannot import name 'double'
'''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/_base.py", line 625, in _invoke_callbacks
callback(self)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 309, in __call__
self.parallel.dispatch_next()
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 731, in dispatch_next
if not self.dispatch_one_batch(self._original_iterator):
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 759, in dispatch_one_batch
self._dispatch(tasks)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 716, in _dispatch
job = self._backend.apply_async(batch, callback=cb)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/_parallel_backends.py", line 510, in apply_async
future = self._workers.submit(SafeFunction(func))
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/reusable_executor.py", line 151, in submit
fn, *args, **kwargs)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/process_executor.py", line 1022, in submit
raise self._flags.broken
joblib.externals.loky.process_executor.BrokenProcessPool: A task has failed to un-serialize. Please ensure that the arguments of the function are all picklable.
joblib.externals.loky.process_executor._RemoteTraceback:
'''
Traceback (most recent call last):
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/process_executor.py", line 391, in _process_worker
call_item = call_queue.get(block=True, timeout=timeout)
File "~/miniconda3/envs/myenv/lib/python3.6/multiprocessing/queues.py", line 113, in get
return _ForkingPickler.loads(res)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/mlarray.py", line 31, in <module>
from _internal.mlarray_sequence import _MLArrayMetaClass
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/_internal/mlarray_sequence.py", line 3, in <module>
from _internal.mlarray_utils import _get_strides, _get_size, \
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/_internal/mlarray_utils.py", line 4, in <module>
import matlab
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/matlab/__init__.py", line 24, in <module>
from mlarray import double, single, uint8, int8, uint16, \
ImportError: cannot import name 'double'
'''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "test.py", line 20, in <module>
for _ in Parallel(4)(delayed(f)(i) for i in range(10)):
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 934, in __call__
self.retrieve()
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 833, in retrieve
self._output.extend(job.get(timeout=self.timeout))
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/_parallel_backends.py", line 521, in wrap_future_result
return future.result(timeout=timeout)
File "~/miniconda3/envs/myenv/lib/python3.6/concurrent/futures/_base.py", line 432, in result
return self.__get_result()
File "~/miniconda3/envs/myenv/lib/python3.6/concurrent/futures/_base.py", line 384, in __get_result
raise self._exception
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/_base.py", line 625, in _invoke_callbacks
callback(self)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 309, in __call__
self.parallel.dispatch_next()
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 731, in dispatch_next
if not self.dispatch_one_batch(self._original_iterator):
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 759, in dispatch_one_batch
self._dispatch(tasks)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/parallel.py", line 716, in _dispatch
job = self._backend.apply_async(batch, callback=cb)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/_parallel_backends.py", line 510, in apply_async
future = self._workers.submit(SafeFunction(func))
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/reusable_executor.py", line 151, in submit
fn, *args, **kwargs)
File "~/miniconda3/envs/myenv/lib/python3.6/site-packages/joblib/externals/loky/process_executor.py", line 1022, in submit
raise self._flags.broken
joblib.externals.loky.process_executor.BrokenProcessPool: A task has failed to un-serialize. Please ensure that the arguments of the function are all picklable.
查看回溯，似乎根本原因是在子进程中导入 matlab 包时出现问题。
可能值得注意的是，如果我定义了 x = np.array([[0.0]])（在导入 numpy as np 之后），那么所有 运行 都很好。当然，主进程对任何 matlab 导入都没有问题，所以我不确定为什么子进程会这样。
我不确定这个错误是否与 matlab 包有什么特别的关系，或者它是否与全局变量和 cloudpickle 或 loky 有关。在我的应用程序中，坚持使用 loky 会有所帮助，所以我将不胜感激！
我还应该注意，我正在为 Python 使用官方 Matlab 引擎：https://www.mathworks.com/help/matlab/matlab-engine-for-python.html。我想这可能会让其他人很难尝试测试用例，所以我希望我可以用 matlab.double 以外的类型重现这个错误，但我还没有找到另一个。
深入挖掘后，我注意到导入 matlab 包的过程比我预期的更循环，我推测这可能是问题的一部分？问题是，当 import matlab 被 loky 的 _ForkingPickler 变为 运行 时，首先导入一些文件 matlab/mlarray.py，然后导入其他一些文件，其中一个包含 import matlab，这会导致 matlab/__init__.py 变为 运行，它内部有 from mlarray import double, single, uint8, ...，这是导致崩溃的行。
这种循环可能是问题所在吗？如果是这样，为什么我可以在主进程中导入这个模块而不是在 loky 后端？
错误是由于子进程中全局对象加载顺序不正确引起的。在回溯中可以清楚地看到
_ForkingPickler.loads(res) -> ... -> import matlab -> from mlarray import ...
当 cloudpickle.
x 时，matlab 尚未导入
joblib 和 loky 似乎将模块视为普通全局对象并将它们动态发送到子进程。 joblib 不记录那些 objects/modules 的定义顺序。因此它们在子进程中以随机顺序加载（初始化）。
一个简单的解决方法是在您的函数中导入 matlab 后手动 pickle matlab 对象并加载它。
import matlab
import pickle
px = pickle.dumps(matlab.double([[0.0]]))
def f(i):
import matlab
x=pickle.loads(px)
print(i, x)
当然你也可以使用joblib.dumps和loads来序列化对象。
使用初始化器
感谢@Aaron 的建议，您也可以在加载x.
initializer（for loky）导入Matlab
Currently there's no simple API to specify initializer。所以我写了一个简单的函数：
def with_initializer(self, f_init):
# Overwrite initializer hook in the Loky ProcessPoolExecutor
# https://github.com/tomMoral/loky/blob/f4739e123acb711781e46581d5ed31ed8201c7a9/loky/process_executor.py#L850
hasattr(self._backend, '_workers') or self.__enter__()
origin_init = self._backend._workers._initializer
def new_init():
origin_init()
f_init()
self._backend._workers._initializer = new_init if callable(origin_init) else f_init
return self
它有点老套，但适用于当前版本的 joblib 和 loky。 然后你可以像这样使用它：
import matlab
from joblib import Parallel, delayed
x = matlab.double([[0.0]])
def f(i):
print(i, x)
def _init_matlab():
import matlab
with Parallel(4) as p:
for _ in with_initializer(p, _init_matlab)(delayed(f)(i) for i in range(10)):
pass
希望joblib的开发者以后在Parallel的构造函数中加入initializer参数