Problem: You are given a binary array A=(A_1,A_2,\cdots,A_N) of length N.

Process Q queries of the following types. The i-th query is represented by three integers T_i,L_i,R_i.

* T_i=1: Replace the value of A_j with 1-A_j for each L_i \leq j \leq R_i.
* T_i=2: Calculate the inversion(*) of the array A_{L_i},A_{L_i+1},\cdots,A_{R_i}．



Note：The inversion of the array x_1,x_2,\cdots,x_k is the number of the pair of integers i,j with 1 \leq i < j \leq k, x_i > x_j.

Constraints

* 1 \leq N \leq 2 \times 10^5
* 0 \leq A_i \leq 1
* 1 \leq Q \leq 2 \times 10^5
* 1 \leq T_i \leq 2
* 1 \leq L_i \leq R_i \leq N
* All values in Input are integer.

Input

Input is given from Standard Input in the following format:


N Q
A_1 A_2 \cdots A_N
T_1 L_1 R_1
T_2 L_2 R_2
\vdots
T_Q L_Q R_Q


Output

For each query with T_i=2, print the answer.

Example

Input

5 5
0 1 0 0 1
2 1 5
1 3 4
2 2 5
1 1 3
2 1 2


Output

2
0
1

Solution (in PYTHON3):

Solution:
#!usr/bin/env python3
from collections import defaultdict, deque, Counter, OrderedDict
from bisect import bisect_left, bisect_right
from functools import reduce, lru_cache
from heapq import heappush, heappop, heapify

import itertools
import math, fractions
import sys, copy

def L(): return sys.stdin.readline().split()
def I(): return int(sys.stdin.readline().rstrip())
def SL(): return list(sys.stdin.readline().rstrip())
def LI(): return [int(x) for x in sys.stdin.readline().split()]
def LI1(): return [int(x) - 1 for x in sys.stdin.readline().split()]
def LS(): return [list(x) for x in sys.stdin.readline().split()]
def R(n): return [sys.stdin.readline().strip() for _ in range(n)]
def LR(n): return [L() for _ in range(n)]
def IR(n): return [I() for _ in range(n)]
def LIR(n): return [LI() for _ in range(n)]
def LIR1(n): return [LI1() for _ in range(n)]
def SR(n): return [SL() for _ in range(n)]
def LSR(n): return [LS() for _ in range(n)]

def perm(n, r): return math.factorial(n) // math.factorial(r)
def comb(n, r): return math.factorial(n) // (math.factorial(r) * math.factorial(n-r))

def make_list(n, *args, default=0): return [make_list(*args, default=default) for _ in range(n)] if len(args) > 0 else [default for _ in range(n)]

dire = [[1, 0], [0, 1], [-1, 0], [0, -1]]
dire8 = [[1, 0], [1, 1], [0, 1], [-1, 1], [-1, 0], [-1, -1], [0, -1], [1, -1]]
alphabets = "abcdefghijklmnopqrstuvwxyz"
ALPHABETS = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
MOD = 1000000007
INF = float("inf")

sys.setrecursionlimit(1000000)


# モノイドに対して適用可能、Nが2冪でなくても良い
class LazySegmentTree():
    '''
    Affine変換(x <- bx + c)の際の各関数の例

    monoid_identity = 0
    operator_identity = (1,0)

    def monoid_func(x,y):
        return (x+y) % MOD
    def composition(f,g): #g(f(x))の順に作用する
        b0,c0 = f
        b1,c1 = g
        return ((b0*b1) % MOD,(b1*c0+c1) % MOD)
    def effect(x,f,r): #xは格納されているデータ(モノイド)
        b,c = f
        return (b*x+c*r) % MOD
    '''

    def __init__(self, initial_values, monoid_func, composition, effect, monoid_identity, operator_identity):
        self.N = len(initial_values)
        self.monoid_func = monoid_func
        self.composition = composition # composition(f, g) => g(f(x))の順であることに注意
        self.effect = effect #右作用 effect(a, f) => f(a), 雑に可換な処理を書こうとするとバグるので注意
        self.monoid_identity = monoid_identity
        self.operator_identity = operator_identity
        self.data = [self.monoid_identity]*(2*self.N)
        self.lazy = [self.operator_identity]*(2*self.N)
        self.size = [0]*(2*self.N)

        for i, ai in enumerate(initial_values):
            self.data[self.N+i] = ai
            self.size[self.N+i] = 1
        for i in range(self.N-1,0,-1):
            self.data[i] = self.monoid_func(self.data[i << 1], self.data[i << 1 | 1])
            self.size[i] = self.size[i << 1] + self.size[i << 1 | 1]

    def update(self,i,x):  # i番目(0-index)の値をxに変更
        i += self.N
        self.data[i] = x
        while i>1:
            i >>= 1
            self.data[i] = self.monoid_func(self.data[i << 1], self.data[i << 1 | 1])

    def eval_at(self,i):  # i番目で作用を施した値を返す
        return self.effect(self.data[i],self.lazy[i],self.size[i])

    def eval_above(self,i):  # i番目より上の値を再計算する
        while i > 1:
            i >>= 1
            self.data[i] = self.monoid_func(self.eval_at(i << 1),self.eval_at(i << 1 | 1))

    def propagate_at(self,i):  # i番目で作用を施し、1つ下に作用の情報を伝える
        self.data[i] = self.effect(self.data[i],self.lazy[i],self.size[i])
        self.lazy[i << 1] = self.composition(self.lazy[i << 1],self.lazy[i])
        self.lazy[i << 1 | 1] = self.composition(self.lazy[i << 1 | 1], self.lazy[i])
        self.lazy[i] = self.operator_identity

    def propagate_above(self,i):  # i番目より上で作用を施す
        H = i.bit_length()
        for h in range(H,0,-1):
            self.propagate_at(i >> h)

    def fold(self, L, R):  # [L,R)の区間取得
        L += self.N
        R += self.N
        L0 = L // (L & -L)
        R0 = R // (R & -R) - 1
        self.propagate_above(L0)
        self.propagate_above(R0)
        vL = self.monoid_identity
        vR = self.monoid_identity
        while L < R:
            if L & 1:
                vL = self.monoid_func(vL,self.eval_at(L))
                L += 1
            if R & 1:
                R -= 1
                vR = self.monoid_func(self.eval_at(R),vR)
            L >>= 1
            R >>= 1
        return self.monoid_func(vL,vR)

    def apply_range(self,L,R,x):# 区間 [L,R) にxを作用
        L += self.N
        R += self.N
        L0 = L // (L & -L)
        R0 = R // (R & -R) - 1
        self.propagate_above(L0)
        self.propagate_above(R0)
        while L < R:
            if L & 1:
                self.lazy[L] = self.composition(self.lazy[L], x)
                L += 1
            if R & 1:
                R -= 1
                self.lazy[R] = self.composition(self.lazy[R], x)
            L >>= 1
            R >>= 1
        self.eval_above(L0)
        self.eval_above(R0)

def main():
    N, Q = LI()
    A = LI()
    X = [(1-a, a, 0) for a in A]
    query = LIR(Q)

    monoid_identity = (0, 0, 0)
    operator_identity = 0

    def monoid_func(x,y):
        return (x[0] + y[0], x[1] + y[1], x[2] + y[2] + x[1] * y[0])

    def composition(f, g):
        return f ^ g

    def effect(x, f, r):
        c0, c1, cnt = x
        return (c1, c0, c0 * c1 - cnt) if f else x

    seg = LazySegmentTree(X, monoid_func, composition, effect, monoid_identity, operator_identity)

    for t, l, r in query:
        if t == 1:
            seg.apply_range(l-1, r, 1)
        else:
            print(seg.fold(l-1, r)[-1])


if __name__ == '__main__':
    main()