python joblib Parallel on Windows not working even “if __name__ == '__main__':” is added

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情话喂你
情话喂你 2021-02-09 00:11

I\'m running parallel processing in Python on Windows. Here\'s my code:

from joblib import Parallel, delayed

def f(x): 
    return sqrt(x)

if __name__ == \'__m         


        
2条回答
  •  抹茶落季
    2021-02-09 00:33

    According to this site the problem is Windows specific:

    Yes: under linux we are forking, thus their is no need to pickle the function, and it works fine. Under windows, the function needs to be pickleable, ie it needs to be imported from another file. This is actually good practice: making modules pushes for reuse.

    I've tried your code and it works flawlessly under Linux. Under Windows it runs OK if it is run from a script, like python script_with_your_code.py. But it fails when ran in an interactive python session. It worked for me when I saved the f function in separate module and imported it into my interactive session.

    NOT WORKING:
    Interactive session:

    >>> from math import sqrt
    >>> from joblib import Parallel, delayed
    
    >>> def f(x):
    ...     return sqrt(x)
    
    >>> if __name__ == '__main__':
    ...     a = Parallel(n_jobs=2)(delayed(f)(i) for i in range(10))
    ...
    Process PoolWorker-1:
    Traceback (most recent call last):
      File "C:\Python27\lib\multiprocessing\process.py", line 258, in _bootstrap
        self.run()
      File "C:\Python27\lib\multiprocessing\process.py", line 114, in run
        self._target(*self._args, **self._kwargs)
      File "C:\Python27\lib\multiprocessing\pool.py", line 102, in worker
        task = get()
      File "C:\Python27\lib\site-packages\joblib\pool.py", line 359, in get
        return recv()
    AttributeError: 'module' object has no attribute 'f'
    


    WORKING:
    fun.py

    from math import sqrt
    
    def f(x):
        return sqrt(x)
    

    Interactive session:

    >>> from joblib import Parallel, delayed
    >>> from fun import f
    
    >>> if __name__ == '__main__':
    ...     a = Parallel(n_jobs=2)(delayed(f)(i) for i in range(10))
    ...
    >>> a
    [0.0, 1.0, 1.4142135623730951, 1.7320508075688772, 2.0, 2.23606797749979, 2.449489742783178, 2.6457513110645907, 2.8284271247461903, 3.0]
    

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