Input: board = [[-3,1,1,1],[-3,1,-3,1],[-3,2,1,1]]
\n\nOutput: 4
\n\nExplanation:
\n\n![\"\"](\"https://assets.leetcode.com/uploads/2024/08/08/rooks2.png\")
We can place the rooks in the cells (0, 2), (1, 3), and (2, 1) for a sum of 1 + 1 + 2 = 4.
You are given a m x n 2D array board representing a chessboard, where board[i][j] represents the value of the cell (i, j).
Rooks in the same row or column attack each other. You need to place three rooks on the chessboard such that the rooks do not attack each other.
\n\nReturn the maximum sum of the cell values on which the rooks are placed.
\n\n\n
Example 1:
\n\nInput: board = [[-3,1,1,1],[-3,1,-3,1],[-3,2,1,1]]
\n\nOutput: 4
\n\nExplanation:
\n\n
We can place the rooks in the cells (0, 2), (1, 3), and (2, 1) for a sum of 1 + 1 + 2 = 4.
Example 2:
\n\nInput: board = [[1,2,3],[4,5,6],[7,8,9]]
\n\nOutput: 15
\n\nExplanation:
\n\nWe can place the rooks in the cells (0, 0), (1, 1), and (2, 2) for a sum of 1 + 5 + 9 = 15.
Example 3:
\n\nInput: board = [[1,1,1],[1,1,1],[1,1,1]]
\n\nOutput: 3
\n\nExplanation:
\n\nWe can place the rooks in the cells (0, 2), (1, 1), and (2, 0) for a sum of 1 + 1 + 1 = 3.
\n
Constraints:
\n\n3 <= m == board.length <= 1003 <= n == board[i].length <= 100-109 <= board[i][j] <= 109给你一个 m x n 的二维整数数组 board ，它表示一个国际象棋棋盘，其中 board[i][j] 表示格子 (i, j) 的 价值 。
处于 同一行 或者 同一列 车会互相 攻击 。你需要在棋盘上放三个车，确保它们两两之间都 无法互相攻击 。
\n\n请你返回满足上述条件下，三个车所在格子 值 之和 最大 为多少。
\n\n\n\n
示例 1：
\n\n输入：board = [[-3,1,1,1],[-3,1,-3,1],[-3,2,1,1]]
\n\n输出：4
\n\n解释：
\n\n
我们可以将车分别放在格子 (0, 2) ，(1, 3) 和 (2, 1) 处，价值之和为 1 + 1 + 2 = 4 。
示例 2：
\n\n输入：board = [[1,2,3],[4,5,6],[7,8,9]]
\n\n输出：15
\n\n解释：
\n\n我们可以将车分别放在格子 (0, 0) ，(1, 1) 和 (2, 2) 处，价值之和为 1 + 5 + 9 = 15 。
示例 3：
\n\n输入：board = [[1,1,1],[1,1,1],[1,1,1]]
\n\n输出：3
\n\n解释：
\n\n我们可以将车分别放在格子 (0, 2) ，(1, 1) 和 (2, 0) 处，价值之和为 1 + 1 + 1 = 3 。
\n\n
提示：
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collections<\\/a>\\u3002\\u5982\\u679c\\u60a8\\u9700\\u8981\\u4f7f\\u7528\\u5176\\u4ed6\\u5e93\\u51fd\\u6570\\uff0c\\u8bf7\\u81ea\\u884c\\u5bfc\\u5165\\u3002<\\/p>\\r\\n\\r\\n \\u6ce8\\u610f Python 2.7 \\u5c06\\u57282020\\u5e74\\u540e\\u4e0d\\u518d\\u7ef4\\u62a4<\\/a>\\u3002 \\u5982\\u60f3\\u4f7f\\u7528\\u6700\\u65b0\\u7248\\u7684Python\\uff0c\\u8bf7\\u9009\\u62e9Python 3\\u3002<\\/p>\"],\"c\":[\"C\",\" \\u7248\\u672c\\uff1a \\u7f16\\u8bd1\\u65f6\\uff0c\\u5c06\\u4f1a\\u91c7\\u7528 \\u4e3a\\u4e86\\u4f7f\\u7528\\u65b9\\u4fbf\\uff0c\\u5927\\u90e8\\u5206\\u6807\\u51c6\\u5e93\\u7684\\u5934\\u6587\\u4ef6\\u5df2\\u7ecf\\u88ab\\u81ea\\u52a8\\u5bfc\\u5165\\u3002<\\/p>\\r\\n\\r\\n \\u5982\\u60f3\\u4f7f\\u7528\\u54c8\\u5e0c\\u8868\\u8fd0\\u7b97, \\u60a8\\u53ef\\u4ee5\\u4f7f\\u7528 uthash<\\/a>\\u3002 \\\"uthash.h\\\"\\u5df2\\u7ecf\\u9ed8\\u8ba4\\u88ab\\u5bfc\\u5165\\u3002\\u8bf7\\u770b\\u5982\\u4e0b\\u793a\\u4f8b:<\\/p>\\r\\n\\r\\n 1. 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