Given a m x n binary matrix mat. In one step, you can choose one cell and flip it and all the four neighbours of it if they exist (Flip is changing 1 to 0 and 0 to 1). A pair of cells are called neighboors if they share one edge.
Return the minimum number of steps required to convert mat to a zero matrix or -1 if you cannot.
Binary matrix is a matrix with all cells equal to 0 or 1 only.
Zero matrix is a matrix with all cells equal to 0.
 
Example 1:

Input: mat = [[0,0],[0,1]]
Output: 3
Explanation: One possible solution is to flip (1, 0) then (0, 1) and finally (1, 1) as shown.

Example 2:
Input: mat = [[0]]
Output: 0
Explanation: Given matrix is a zero matrix. We don't need to change it.

Example 3:
Input: mat = [[1,1,1],[1,0,1],[0,0,0]]
Output: 6

Example 4:
Input: mat = [[1,0,0],[1,0,0]]
Output: -1
Explanation: Given matrix can't be a zero matrix

 
Constraints:

m == mat.length
n == mat[0].length
1 <= m <= 3
1 <= n <= 3
mat[i][j] is 0 or 1.

Difficulty: interview

Starter code:

class Solution:
    def minFlips(self, mat: List[List[int]]) -> int:
        

Solutions:
class Solution:
    def minFlips(self, mat: List[List[int]]) -> int:
        m = len(mat)
        n = len(mat[0])
        
        start = sum(val << (i*n + j) for i, row in enumerate(mat) for j, val in enumerate(row))
        
        queue = collections.deque([(start, 0)])
        seen = { start }
        
        dirs = [[0, 0], [0,1], [1, 0], [0, -1], [-1, 0]]
        while queue:
            # print(queue)
            current, d = queue.popleft()
            if current == 0:
                return d
            
            # for each index in matrix find neighbour
            for i in range(len(mat)):
                for j in range(len(mat[0])):
                    next_state = current
                    
                    # importants dirs has [0, 0] we need flip the current element and neigbour
                    for dir_ in dirs:
                        new_i = i + dir_[0]
                        new_j = j + dir_[1]
                        
                        if new_i >= 0 and new_i < len(mat) and new_j >= 0 and new_j < len(mat[0]):
                            next_state ^= (1 << (new_i * n + new_j )) # 0 xor 1 = 1, 1 xor 1 = 0
                    
                    if next_state not in seen:
                        seen.add(next_state)
                        queue.append((next_state, d + 1))
        
        return -1