We can find longest decreasing path instead, the result will be the same. Use `dp`

to record previous results and choose the max `dp`

value of smaller neighbors.

```
def longestIncreasingPath(self, matrix):
def dfs(i, j):
if not dp[i][j]:
val = matrix[i][j]
dp[i][j] = 1 + max(
dfs(i - 1, j) if i and val > matrix[i - 1][j] else 0,
dfs(i + 1, j) if i < M - 1 and val > matrix[i + 1][j] else 0,
dfs(i, j - 1) if j and val > matrix[i][j - 1] else 0,
dfs(i, j + 1) if j < N - 1 and val > matrix[i][j + 1] else 0)
return dp[i][j]
if not matrix or not matrix[0]: return 0
M, N = len(matrix), len(matrix[0])
dp = [[0] * N for i in range(M)]
return max(dfs(x, y) for x in range(M) for y in range(N))
```