I am not sure what platform you are running, but on OSX this is even more
problematic. It creates orphaned processes that don't close and keep spinning
the cpus.
The problem, as I understand it, is that the multiprocessing module needs to be
able to fork, copy the memory, and start up the same interpreter again. But
Maya is using an embedded python interpreter and it thinks it needs to start up
Maya in the new processes, which crashes. On windows, the multiprocessing
module has the .set_executable() function:
http://docs.python.org/2/library/multiprocessing.html#multiprocessing.set_executable
But I don't have windows to test trying to set this to a valid python
interpreter, and it is not even platform independent as a solution.
What I have gotten to work just fine is the workflow of running your script in
a subprocess, and communicating the results back over the pipe. This allows
multiprocessing to run under whatever standard python interpreter you want, and
is independent of Maya.
There are two files here:
https://gist.github.com/justinfx/4741527
The first one is a modified version of your original code.
The second is the snippet to launch the subprocess from Maya and read the
results.
-- justin
On Feb 8, 2013, at 6:04 AM, Jan: wrote:
Hi,
i'm trying to use the python multiprocessing module to make my script
multi-threaded.
However every time it tries to start a new process it loads up the output
window with command line on how to load the maya batch process.
When I close the window the process closes as well and the function is never
called or it locks up.
Unfortunately I have no idea how I can pass command line info from the
multiprocessing function.
So my question is:
How can I load a multiprocessing process without having the output window pop
up and the process running properly.
Any help would be much appreciated.
(I was thinking of running my code inside of a different interpreter but I
have no idea on how to go at it)
Example function: (it works fine in any other standard python (2.6)
interpreter ).
from multiprocessing import Pool
from time import time
## Simple func to eat up cpu power.
def whileFunc(z):
while z 100:
z += 1
return z
## We have to work in __main__ else in some os versions the threads become
unsafe
if __name__ == __main__:
## Get current time
currtime = time()
## How often to run (just a test value)
N = 1000
## Just a list with 1s
myList = [1]*N
nrOfProcessors = 8 #16
## Set our pool of processors
po = Pool(nrOfProcessors)
## create the threads
res = po.map_async(whileFunc, myList)
print 'This value below should be a 1000:'
## The res.get() getting of the result actually starts the threads
(surprisingly enough.)
## This is also where maya will open up the Output Window and in some
cases lock up.
print len(res.get())
print 'time elapsed:', time() - currtime
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