Write function bmi that calculates body mass index (bmi = weight / height ^ 2).


if bmi <= 18.5 return "Underweight"

if bmi <= 25.0 return "Normal"

if bmi <= 30.0 return "Overweight"

if bmi > 30 return "Obese"

```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 = 'def bmi(weight, height):\n  bmi_val = weight / height**2\n  return get_weight_class(bmi_val)\n\n# bmi_ranges start open bound & end closed bound\ndef get_weight_class(bmi_val):\n  bmi_ranges = [(0, 18.5), (18.5, 25), (25, 30), (30, float("inf"))]\n  weight_classes = {\n    (0, 18.5): "Underweight",\n    (18.5, 25): "Normal",\n    (25, 30): "Overweight",\n    (30, float("inf")): "Obese",\n  }\n  # see what range bmi belongs to with binary search\n  start = 0\n  end = len(bmi_ranges) - 1\n\n  while not(start > end):\n    mid_i = start + abs(end - start)//2\n    range_start, range_end = bmi_ranges[mid_i]\n\n    if range_start < bmi_val <= range_end:\n      return weight_classes[(range_start, range_end)]\n    elif bmi_val <= range_start:\n      end = mid_i - 1\n    elif bmi_val > range_end:\n      start = mid_i + 1\n\n  raise ValueError("BMI value out of range.")\n'
_co = compile(_CODE, USER_FILENAME, "exec")
exec(_co, ns, ns)

_target = None
_fn_name = 'bmi'
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: 5968