def execute(tensor, para):
# loop over each density and each round
if para['parallelMode']: # run on multiple processes
pool = multiprocessing.Pool()
for den in para['density']:
for roundId in xrange(para['rounds']):
pool.apply_async(executeOneSetting, (tensor, den, roundId, para))
pool.close()
pool.join()
else: # run on single processes
for den in para['density']:
for roundId in xrange(para['rounds']):
executeOneSetting(tensor, den, roundId, para)
# summarize the dumped results
evallib.summarizeResult(para, tensor.shape[2])
def execute(tensor, para):
# loop over each density and each round
if para['parallelMode']: # run on multiple processes
pool = multiprocessing.Pool()
for den in para['density']:
for roundId in xrange(para['rounds']):
pool.apply_async(executeOneSetting,
(tensor, den, roundId, para))
pool.close()
pool.join()
else: # run on single processes
for den in para['density']:
for roundId in xrange(para['rounds']):
executeOneSetting(tensor, den, roundId, para)
# summarize the dumped results
evallib.summarizeResult(para, tensor.shape[2])