交叉匹配两个2D数组并返回匹配的索引

def find_matching_indices(arr1, arr2):
    matches = []
    for i in range(len(arr1)):
        for j in range(len(arr1[i])):
            for x in range(len(arr2)):
                for y in range(len(arr2[x])):
                    if arr1[i][j] == arr2[x][y]:
                        matches.append((i, j, x, y))
    return matches

# 示例数组
array1 = [
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
]

array2 = [
    [9, 8, 7],
    [6, 5, 4],
    [3, 2, 1]
]

# 找到匹配的索引
matching_indices = find_matching_indices(array1, array2)
print("匹配的索引:", matching_indices)

import multiprocessing as mp

def match_chunk(chunk1, chunk2):
    return [(i, j, x, y) for i, row1 in enumerate(chunk1) for j, val1 in enumerate(row1)
            for x, row2 in enumerate(chunk2) for y, val2 in enumerate(row2) if val1 == val2]

def parallel_find_matching_indices(arr1, arr2, num_processes=mp.cpu_count()):
    pool = mp.Pool(processes=num_processes)
    chunks1 = [arr1[i::num_processes] for i in range(num_processes)]
    chunks2 = [arr2[i::num_processes] for i in range(num_processes)]
    results = pool.starmap(match_chunk, zip(chunks1, chunks2))
    pool.close()
    pool.join()
    return [item for sublist in results for item in sublist]

# 使用并行处理找到匹配的索引
matching_indices_parallel = parallel_find_matching_indices(array1, array2)
print("并行匹配的索引:", matching_indices_parallel)