oserror:[errno 12]使用python多处理池时无法分配内存

我正在尝试使用python将一个函数并行应用于5个交叉验证集 multiprocessing 对不同的参数值重复这个过程,比如:

import pandas as pd
import numpy as np
import multiprocessing as mp
from sklearn.model_selection import StratifiedKFold

#simulated datasets
X = pd.DataFrame(np.random.randint(2, size=(3348,868), dtype='int8'))
y = pd.Series(np.random.randint(2, size=3348, dtype='int64'))

#dummy function to apply
def _work(args):
    del(args)

for C in np.arange(0.0,2.0e-3,1.0e-6):
    splitter = StratifiedKFold(n_splits=5)
    with mp.Pool(processes=5) as pool:
        pool_results = \
            pool.map(
                func=_work,
                iterable=((C,X.iloc[train_index],X.iloc[test_index]) for train_index, test_index in splitter.split(X, y))
            )

然而,在执行过程的中途,我得到了以下错误:

Traceback (most recent call last):
  File "mre.py", line 19, in <module>
    with mp.Pool(processes=5) as pool:
  File "/usr/lib/python3.5/multiprocessing/context.py", line 118, in Pool
    context=self.get_context())
  File "/usr/lib/python3.5/multiprocessing/pool.py", line 168, in __init__
    self._repopulate_pool()
  File "/usr/lib/python3.5/multiprocessing/pool.py", line 233, in _repopulate_pool
    w.start()
  File "/usr/lib/python3.5/multiprocessing/process.py", line 105, in start
    self._popen = self._Popen(self)
  File "/usr/lib/python3.5/multiprocessing/context.py", line 267, in _Popen
    return Popen(process_obj)
  File "/usr/lib/python3.5/multiprocessing/popen_fork.py", line 20, in __init__
    self._launch(process_obj)
  File "/usr/lib/python3.5/multiprocessing/popen_fork.py", line 67, in _launch
    self.pid = os.fork()
OSError: [Errno 12] Cannot allocate memory

我在Ubuntu 16.04上运行这个,内存为32GB,正在检查 htop 在执行过程中,它不会超过18.5GB,所以我不认为内存不足。
这显然是由于我的数据帧与 splitter.split(X,y) 从我将数据帧直接传递给 Pool 对象没有引发错误。

我看见了 this answer 这说明这可能是由于创建了太多的文件依赖关系,但我不知道如何解决这个问题,上下文管理器不应该帮助避免这种问题吗?