Given a square grid of integers arr, a falling path with non-zero shifts is a choice of exactly one element from each row of arr, such that no two elements chosen in adjacent rows are in the same column.
Return the minimum sum of a falling path with non-zero shifts.
 
Example 1:
Input: arr = [[1,2,3],[4,5,6],[7,8,9]]
Output: 13
Explanation: 
The possible falling paths are:
[1,5,9], [1,5,7], [1,6,7], [1,6,8],
[2,4,8], [2,4,9], [2,6,7], [2,6,8],
[3,4,8], [3,4,9], [3,5,7], [3,5,9]
The falling path with the smallest sum is [1,5,7], so the answer is 13.

 
Constraints:

1 <= arr.length == arr[i].length <= 200
-99 <= arr[i][j] <= 99

```python

USER_FILENAME = "<user_code>"
import sys, json, builtins
import math, heapq, bisect, itertools, functools, collections, statistics, fractions, decimal, operator, array, random, re, string, os, pathlib
try:
    import resource as _res
except Exception:
    _res = None
from collections import Counter, defaultdict, deque, OrderedDict
from functools import lru_cache, reduce
from itertools import accumulate, permutations, combinations, product
from math import gcd, ceil, floor, sqrt
from decimal import Decimal
try:
    from typing import *
except Exception:
    pass
try:
    sys.setrecursionlimit(1_000_000)
except Exception:
    pass
try:
    import site as _site
    try:
        _sys_sites = _site.getsitepackages() if hasattr(_site, "getsitepackages") else []
        for _p in _sys_sites:
            if _p and _p not in sys.path:
                sys.path.append(_p)
    except Exception:
        pass
    try:
        _usp = _site.getusersitepackages()
        if isinstance(_usp, str):
            _usp = [_usp]
        for _p in _usp:
            if _p and _p not in sys.path:
                sys.path.append(_p)
    except Exception:
        pass
except Exception:
    pass

def _disabled_input(*args, **kwargs):
    raise RuntimeError("input() is disabled in callable mode")
builtins.input = _disabled_input

ns = {"__name__": "__judge__"}  # prevent if __name__ == "__main__" blocks
for _k, _v in list(globals().items()):
    if not _k.startswith("_"):
        ns[_k] = _v
_CODE = "class Solution:\n    def minFallingPathSum1(self, arr: List[List[int]]) -> int:\n        '''\n        Time: O(mn^2)  - due linear search for min in inner loop\n        Space: O(n + n) ~ O(n)\n        '''\n        m = len(arr)\n        n = len(arr[0])\n        \n        if m == 1: # 1 ele sq. matrix\n            return arr[0][0]\n        \n        def get_min_neighbors(j):\n            a, row_prev[j] = row_prev[j], float('inf')\n            min_val = min(row_prev)\n            row_prev[j] = a\n            return min_val\n        \n        row_prev = arr[0]\n        cur = [0]*n\n        global_min = float('inf')\n        \n        for row in range(1, m):\n            for col in range(n):\n                cur[col] = get_min_neighbors(col) + arr[row][col]\n                \n                if row == m-1 and cur[col] < global_min:\n                    global_min = cur[col]\n     \n            row_prev = cur[:]\n        \n        return global_min\n\n    def minFallingPathSum(self, arr: List[List[int]]) -> int:\n        '''\n        Time: O(mn) - if heapq.nsmallest is linear, here min search is in outer loop\n        Space: O(n + n) ~ O(n)\n        '''\n        m = len(arr)\n        n = len(arr[0])\n        \n        if m == 1: # 1 ele sq. matrix\n            return arr[0][0]\n        \n        def get_min_neighbors():\n            #min1, min2 = heapq.nsmallest(2, row_prev) #also works\n            min1 = float('inf')\n            min2 = float('inf')\n            \n            for val in dp:\n                if val < min1:\n                    min2 = min1\n                    min1 = val\n                elif val < min2:\n                    min2 = val\n                    \n            return min1, min2\n        \n        dp = arr[0]\n        cur = [0]*n\n        global_min = float('inf')\n        \n        for row in range(1, m):\n            min1, min2 = get_min_neighbors()\n            for col in range(n):\n                min_val = min1 if dp[col] != min1 else min2 #doesnt matter if duplicates\n                cur[col] = min_val + arr[row][col] \n                \n                if row == m-1 and cur[col] < global_min:\n                    global_min = cur[col]\n     \n            dp = cur[:]\n\n        return global_min"
_co = compile(_CODE, USER_FILENAME, "exec")
exec(_co, ns, ns)

_target = None
_fn_name = 'minFallingPathSum'
if _fn_name:
    if "Solution" in ns:
        try:
            _obj = ns["Solution"]()
            if hasattr(_obj, _fn_name):
                _target = getattr(_obj, _fn_name)
        except Exception:
            _target = None
    if _target is None and _fn_name in ns and callable(ns[_fn_name]):
        _target = ns[_fn_name]
# Fallback: if there's exactly one user-defined function, use it
if _target is None:
    _cands = [v for k, v in ns.items() if callable(v) and getattr(v, "__module__", "") in ("__judge__", "__main__")]
    _user_funcs = [c for c in _cands if getattr(c, "__name__", "").startswith("_") is False]
    if len(_user_funcs) == 1:
        _target = _user_funcs[0]
if _target is None:
    raise RuntimeError(f"Could not resolve callable '{_fn_name}'")

_raw = sys.stdin.read().strip()
if _raw:
    _parsed = json.loads(_raw)
    if isinstance(_parsed, dict):
        _kwargs = _parsed.get("kwargs", {})
        _args = _parsed.get("args", [])
    else:
        _args, _kwargs = _parsed, {}
else:
    _args, _kwargs = [], {}
if not isinstance(_args, (list, tuple)):
    _args = [_args]
_res = _target(*_args, **_kwargs)
try:
    sys.stdout.write(repr(_res) + "\n")
except Exception:
    pass

```

Measured memory_bytes: