如何使用 Dask 並行化循環？

Question

我發現Dask 文檔很混亂。 假設我有一個 function：

import random
import dask

def my_function(arg1, arg2, arg3):
    val = random.uniform(arg1, arg2) 
    va2 = random.uniform(arg2, arg3)
    return val1 + val2

some_list = []
for i in range(100):
    some_num = dask.delayed(my_function)(arg1, arg2, arg3)
    some_list += [some_num]

computed_list = dask.compute(*some_list)

這件事會失敗，因為my_function()沒有得到所有 3 個 arguments。

如何在dask中並行化這段代碼？

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編輯：

如果您將@dask.delayed裝飾器放在 function def頂部並正常調用它，似乎可以工作，但現在.compute() -method 行拋出：

KilledWorker: ('my_function-ac3c88f1-53f8-4d36-a520-ff8c40c6ee61', <Worker 'tcp://127.0.0.1:35925', name: 1, memory: 0, processing: 10>)

Answer 1

我先構建一個圖，然后在其上調用計算：

import random
import dask

@dask.delayed
def my_function(arg1, arg2, arg3):
    val1 = random.uniform(arg1, arg2) 
    val2 = random.uniform(arg2, arg3)
    return val1 + val2

arg1 = 1
arg2 = 2
arg3 = 3

some_list = []
for i in range(10):
    some_num = my_function(arg1, arg2, arg3)
    some_list.append(some_num)

graph = dask.delayed()(some_list)
# graph.visualize()
computed_list = graph.compute()