我正在 Windows 机器上尝试 python 的线程和多重处理。但是 python 给出以下消息。
RuntimeError:
Attempt to start a new process before the current process
has finished its bootstrapping phase.
This probably means that you are on Windows and you have
forgotten to use the proper idiom in the main module:
if __name__ == '__main__':
freeze_support()
...
The "freeze_support()" line can be omitted if the program
is not going to be frozen to produce a Windows executable.
在 Windows 中,如果 name == 'main':因此必须完成,我的实现如下,但是在解决如何发生此类错误之后,或者这是我所做的情况不知道。 请帮助我。
import random
import numpy
import matplotlib.pyplot
import time
import multiprocessing
from deap import algorithms
from deap import base
from deap import creator
from deap import tools
# from docutils.utils.punctuation_chars import delimiters
IND_INIT_SIZE = 3000
# MIN_ENERGY = 237178.013392/3600
MIN_ENERGY =7255
MIN_POWER = 303.4465137486
NBR_ITEMS = 3000
# Create the item dictionary: item name is an integer, and value is
# a (weight, value) 2-uple.
items = {}
# Create random items and store them in the items' dictionary.
for i in range(NBR_ITEMS):
items[i] = random.choice([[10,5],[10,10]])
creator.create("Fitness", base.Fitness, weights=(-1.0, -1.0))
creator.create("Individual", set, fitness=creator.Fitness)
toolbox = base.Toolbox()
# Attribute generator
toolbox.register("attr_item", random.randrange, NBR_ITEMS)
# Structure initializers
toolbox.register("individual", tools.initRepeat, creator.Individual, toolbox.attr_item, IND_INIT_SIZE)
toolbox.register("population", tools.initRepeat, list, toolbox.individual)
def evalKnapsack(individual):
energy = 0.0
power = 0.0
for item in individual:
energy += items[item][1]
power += items[item][0]
if power < MIN_POWER or energy < MIN_ENERGY:
return 100000000000,1000000000000
return energy, power
def cxSet(ind1, ind2):
"""Apply a crossover operation on input sets. The first child is the
intersection of the two sets, the second child is the difference of the
two sets.
"""
temp = set(ind1) # Used in order to keep type
ind1 &= ind2 # Intersection (inplace)
ind2 ^= temp # Symmetric Difference (inplace)
return ind1, ind2
def mutSet(individual):
"""Mutation that pops or add an element."""
for var in range(0,3000):
if random.random() < 0.5:
if len(individual) > 0: # We cannot pop from an empty set
individual.remove(random.choice(sorted(tuple(individual))))
else:
individual.add(random.randrange(NBR_ITEMS))
return individual,
toolbox.register("evaluate", evalKnapsack)
toolbox.register("mate", cxSet)
toolbox.register("mutate", mutSet)
toolbox.register("select", tools.selSPEA2)
pool = multiprocessing.Pool(4)
toolbox.register("map", pool.map)
def main():
# random.seed(64)
NGEN = 5
MU = 75
LAMBDA = 75
CXPB = 0.6
MUTPB = 0.3
pop = toolbox.population(n=MU)
hof = tools.ParetoFront()
stats = tools.Statistics(lambda ind: ind.fitness.values)
stats.register("avg", numpy.mean, axis=0)
stats.register("std", numpy.std, axis=0)
stats.register("min", numpy.min, axis=0)
stats.register("max", numpy.max, axis=0)
algorithms.eaMuPlusLambda(pop, toolbox, MU, LAMBDA, CXPB, MUTPB, NGEN, stats,
halloffame=hof)
return pop, stats, hof
if __name__ == '__main__':
for var in range(0,5):
start = time.time()
pop, stats, hof= main()
lischp=[]
lisclp=[]
libatthp=[]
libattlp=[]
ligoukei=[]
for ind in hof:
itemslist=[]
print ind, ind.fitness
for k in ind:
itemslist.append(items[k])
schpkazu=itemslist.count([10,5])
lischp.append(schpkazu)
battlpkazu=itemslist.count([10,10])
libattlp.append(battlpkazu)
print libatthp
print lischp
print libattlp
print lisclp
ligoukei.append(ind.fitness)
print ligoukei
#保存
with open('battlpcazu.csv',mode='a')as fb:
numpy.savetxt(fb,libattlp,fmt="%.0f",delimiter=",")
with open('schpcazu.csv',mode='a')as fc:
numpy.savetxt(fc,lischp,fmt="%.0f",delimiter=",")
elapsed_time = time.time() - start
print ("elapsed_time:{0}".format(elapsed_time)) + "[sec]"
最佳答案
Windows 上没有 os.fork() 调用,因此 python 从头开始运行您的脚本 对于每个新进程,除了用 包装的代码
if __name__ == '__main__':
...
在您的情况下,您只需要在主线程中创建进程池,因此将池初始化移到此部分(或从此部分调用的函数):
if __name__ == '__main__':
pool = multiprocessing.Pool(4)
for var in range(0,5):
...
关于python - python在Windows上进行多处理时出现运行时错误,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/34853707/