Question

我正在为Windows机器上的python尝试线程和多处理。但是python给出了以下消息。

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，如果名字==＆＃39;主要＆＃39;：因此必须完成并且我实现如下，但是，在，解决之后如何发生这样的错误或它是我不知道的情况。请帮帮我。

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]"

Answer 1

在windows上没有os.fork（）调用，所以python从头开始运行你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，您需要仅在主线程中创建进程池，因此将池初始化移动到此部分（或从此部分调用的函数）：

if __name__ == '__main__':  
    pool = multiprocessing.Pool(4)
    for var in range(0,5):
        ...

Windows上的python occers的runtimeError到多处理

1 个答案: