Cupy get error in multithread.pool if GPU already used - python-3.x

Question

I tried to use cupy in two parts of my program, one of them being parallelized with a pool.
I managed to reproduce it with a simple example:
import cupy
import numpy as np
from multiprocessing import pool
def f(x):
return cupy.asnumpy(2*cupy.array(x))
input = np.array([1,2,3,4])
print(cupy.asnumpy(cupy.array(input)))
print(np.array(list(map(f, input))))
p = pool.Pool(4)
output = p.map(f, input)
p.close()
p.join()
print(output)
The output is the following:
[1 2 3 4]
[2 4 6 8]
Exception in thread Thread-3:
Traceback (most recent call last):
File "/usr/lib/python3.6/threading.py", line 916, in _bootstrap_inner
self.run()
File "/usr/lib/python3.6/threading.py", line 864, in run
self._target(*self._args, **self._kwargs)
File "/usr/lib/python3.6/multiprocessing/pool.py", line 489, in _handle_results
task = get()
File "/usr/lib/python3.6/multiprocessing/connection.py", line 251, in recv
return _ForkingPickler.loads(buf.getbuffer())
File "cupy/cuda/runtime.pyx", line 126, in cupy.cuda.runtime.CUDARuntimeError.__init__
TypeError: an integer is required
also, the code freezes and doesn't exit but I think it's not related to cupy.
And my config is this one:
CuPy Version : 5.2.0
CUDA Root : /usr/local/cuda-10.0
CUDA Build Version : 10000
CUDA Driver Version : 10000
CUDA Runtime Version : 10000
cuDNN Build Version : 7301
cuDNN Version : 7301
NCCL Build Version : 2307

Answer 1

This issue is not specific to CuPy. Due to the limitation of CUDA, processes cannot be forked after CUDA initialization.
You need to use multiprocessing.set_start_method('spawn') (or forkserver), or avoid initializing CUDA (i.e., do not use CuPy API except import cupy) until you fork child processes.

Answer 2

When I tried multiprocessing with cupy before, I needed to use spawn context.
ctx = multiprocessing.get_context('spawn')
pool = ctx.Pool(4)
I don't know this resolves your problem but can you try it?