我想并行化一个在共享的numpy 2D数组上运行的方法。
我的原始应用程序是研究的一部分,非常复杂,但是,我创建了一个基本上复制问题的玩具示例。
有一家服装店出售不同大小和颜色的衣服。我将此商店的库存表示为2D矩阵,其中self.supply_arr[i][j]
表示size i
和color j
的衣服的总可用性。我有多个客户试图从商店购买。商店不应该出售超过库存的衣服。下面,我展示了一个非平行的例子。
import numpy as np
class ClothStore(object):
def __init__(self, num_customers):
self.supply_arr = np.random.randint(5, size=(2,2))
self.sold_arr = np.zeros((2,2), dtype=int)
self.num_customers = num_customers
def make_purchase(self, size, color):
left = self.supply_arr[size][color] - self.sold_arr[size][color]
if left > 0:
self.sold_arr[size][color] += 1
return True
else:
return False
def run(self):
for customer in xrange(self.num_customers):
size = np.random.randint(2)
color = np.random.randint(2)
purchase = self.make_purchase(size, color)
if purchase:
print "Customer: {} made successful purchase".format(customer)
if __name__ == "__main__":
store = ClothStore(100)
store.run()
print "Supply Arr: {}".format(store.supply_arr)
print "Sold Arr: {}".format(store.sold_arr)
我试图使用run(self)
并将pathos
表示为self.supply_arr
来并行化np.empty((2,2), dtype=object)
方法,其中每个元素我初始化为multiprocessing.Value
。但是,我无法让它发挥作用。任何帮助,将不胜感激。谢谢。
我设法用迂回的方式解决了我自己的问题。它不是最优雅的方式,但它有效。我真的很感激帮助使它更优雅。
import numpy as np
from pathos.multiprocessing import ProcessingPool as Pool
from multiprocess import Manager
class ClothStoreNew(object):
def __init__(self, num_customers):
self.supply_arr = np.random.randint(5, size=(2, 2))
self.num_customers = num_customers
def make_purchase(self, arg):
sold_dict = arg[0]
i = arg[1]
size = self.demand[i][1]
color = self.demand[i][2]
sold = sold_dict.get((size, color), 0)
if self.supply_arr[size][color] > sold:
sold_dict[(size, color)] = sold + 1
def run(self):
m = Manager()
sold_dict = m.dict()
pool = Pool(processes=100)
self.demand = []
for customer in xrange(self.num_customers):
size = np.random.randint(1)
color = np.random.randint(1)
self.demand.append([customer, size, color])
pool.map(self.make_purchase, ([sold_dict, i] for i in xrange(self.num_customers)))
pool.close()
pool.join()
return dict(sold_dict)
if __name__ == "__main__":
store = ClothStoreNew(20)
sold_dict = store.run()
print "Supply Arr: {}".format(store.supply_arr)
print "Sold Dict: {}".format(sold_dict)
如您所见,我使用manager.dict()
进行同步。我想使用manager.list()
,但似乎没有用。此外,使用Manager
锁定每个更新的整个字典,理想的解决方案是一次锁定字典(或2D矩阵的每个单独的单元格)的每个单独的键,以便在其他单元格上操作的进程不会不得不等