[GitHub] nkhdiscovery edited a comment on issue #4659: gpu memory allocate will be error when using multiprocessing.Process

[GitBox <gi...@apache.org>]

nkhdiscovery edited a comment on issue #4659: gpu memory allocate will be error when using multiprocessing.Process
URL: https://github.com/apache/incubator-mxnet/issues/4659#issuecomment-466630959
 
 
   @leezu 
   Here is something even more complex which works, I thought anybody else may come here and needs the solution - which does not work if you do not force  `mp.set_start_method('forkserver', force=True)`
   ```
   import random
   import numpy as np
   import mxnet as mx
   import multiprocessing as mp
   
   def test():
       mx.random.seed(random.randint(10,200))
       a = mx.nd.random_normal(shape=(2,2), ctx=mx.gpu(0))
       print('child no. ', mp.current_process().name, ':' , a)
   
   if __name__ == '__main__':
       mp.set_start_method('forkserver', force=True)
       ab = mx.nd.random_normal(shape=(2,2), ctx=mx.gpu(0))
       print('main proc.: ', ab)
       runs = [mp.Process(target=test) for i in range(3)]
       for p in runs:
         p.start()
       for p in runs:
         p.join()
   
       print('done')
   ```
   
   Hope it helps.

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