索引错误:尝试在多处理中传递二维数组时，元组索引超出范围.池

Question

我正在尝试制作一些程序来探索使用库多处理的处理优势。但是，我收到一个 IndexError：元组索引超出范围，当传入 multiprocessing.poolmap(， <2Darray>(。我的代码如下

我试图展平数组，但没有奏效

import numpy as np 
import time 
import concurrent.futures 
import multiprocessing
def mean_py(array):
    start_time = time.time() 
    x = array.shape[1] 
    y = array.shape[2] 
    values = np.empty((x,y), type(array[0][0][0]))
    for i in range(x):
        for j in range(y): 
            values[i][j] = ((np.mean(array[:,i,j]))) 
    end_time = time.time() 
    hours, rem = divmod(end_time-start_time, 3600)
    minutes, seconds = divmod(rem,60) 
    print("{:0>2}:{:0>2}:{:05.2f}".format(int(hours), int(minutes), int(seconds)))
    print(f"{'.'*80}")
    return values 
def generate_array():
    a = np.random.randn(1_000_000).reshape(1000,1000)
    b = np.random.randn(1_000_000).reshape(1000,1000)
    c = np.random.randn(1_000_000).reshape(1000,1000)
    d = np.random.randn(1_000_000).reshape(1000,1000)
    e = np.random.randn(1_000_000).reshape(1000,1000)
    f = np.random.randn(1_000_000).reshape(1000,1000)
    g = np.random.randn(1_000_000).reshape(1000,1000)
    h = np.random.randn(1_000_000).reshape(1000,1000)
    i = np.random.randn(1_000_000).reshape(1000,1000)
    arrays = [a, b, c, d, e, f, g, h, i]
    final_array = []
    for array in arrays:
        final_array.append(array)
        print(f"{array} added.")
    final_array = np.asarray(final_array)
    return final_array

start = time.time() 
final_array = generate_array()

pool = multiprocessing.Pool(processes = 2)
result = pool.map(mean_py, final_array)
#result = mean_py(final_array)
end = time.time() 
print(f'nTime complete: {end-start:.2f}sn')```

```Traceback (most recent call last):
  File "implementation_v02.py", line 51, in <module>
    result = pool.map(mean_py, final_array)
  File "/home/roger/anaconda3/lib/python3.7/multiprocessing/pool.py", line 290, in map
    return self._map_async(func, iterable, mapstar, chunksize).get()
  File "/home/roger/anaconda3/lib/python3.7/multiprocessing/pool.py", line 683, in get
    raise self._value
IndexError: tuple index out of range```

Answer 1

这将起作用：

result = pool.map(mean_py, [final_array, final_array])

您需要传递列表或 1D 数组。它尝试映射列表或 1d 数组中的每个元素，并将其"分发"到您的 pool.map 函数参数 (mean_py(。它不知道如何处理您传递给它的 3 维数组......它应该采用 9*1000*1000 元素中的每一个吗？切片并仅传递一个维度？哪一个？