結果

問題 No.2959 Dolls' Tea Party
ユーザー vwxyz
提出日時 2024-11-09 02:05:15
言語 PyPy3
(7.3.15)
結果
AC  
実行時間 2,932 ms / 3,000 ms
コード長 24,711 bytes
コンパイル時間 384 ms
コンパイル使用メモリ 82,892 KB
実行使用メモリ 172,472 KB
最終ジャッジ日時 2024-11-09 02:06:43
合計ジャッジ時間 79,742 ms
ジャッジサーバーID
(参考情報)
judge3 / judge1
このコードへのチャレンジ
(要ログイン)
ファイルパターン 結果
sample AC * 4
other AC * 33
権限があれば一括ダウンロードができます

ソースコード

diff #
プレゼンテーションモードにする

import math
from functools import lru_cache
#mod = 998244353
imag = 911660635
iimag = 86583718
rate2 = (911660635, 509520358, 369330050, 332049552, 983190778, 123842337, 238493703, 975955924, 603855026, 856644456, 131300601,
842657263, 730768835, 942482514, 806263778, 151565301, 510815449, 503497456, 743006876, 741047443, 56250497, 867605899)
irate2 = (86583718, 372528824, 373294451, 645684063, 112220581, 692852209, 155456985, 797128860, 90816748, 860285882, 927414960,
354738543, 109331171, 293255632, 535113200, 308540755, 121186627, 608385704, 438932459, 359477183, 824071951, 103369235)
rate3 = (372528824, 337190230, 454590761, 816400692, 578227951, 180142363, 83780245, 6597683, 70046822, 623238099,
183021267, 402682409, 631680428, 344509872, 689220186, 365017329, 774342554, 729444058, 102986190, 128751033, 395565204)
irate3 = (509520358, 929031873, 170256584, 839780419, 282974284, 395914482, 444904435, 72135471, 638914820, 66769500,
771127074, 985925487, 262319669, 262341272, 625870173, 768022760, 859816005, 914661783, 430819711, 272774365, 530924681)
def butterfly(a):
n = len(a)
h = (n - 1).bit_length()
len_ = 0
while len_ < h:
if h - len_ == 1:
p = 1 << (h - len_ - 1)
rot = 1
for s in range(1 << len_):
offset = s << (h - len_)
for i in range(p):
l = a[i + offset]
r = a[i + offset + p] * rot % mod
a[i + offset] = (l + r) % mod
a[i + offset + p] = (l - r) % mod
if s + 1 != 1 << len_:
rot *= rate2[(~s & -~s).bit_length() - 1]
rot %= mod
len_ += 1
else:
p = 1 << (h - len_ - 2)
rot = 1
for s in range(1 << len_):
rot2 = rot * rot % mod
rot3 = rot2 * rot % mod
offset = s << (h - len_)
for i in range(p):
a0 = a[i + offset]
a1 = a[i + offset + p] * rot
a2 = a[i + offset + p * 2] * rot2
a3 = a[i + offset + p * 3] * rot3
a1na3imag = (a1 - a3) % mod * imag
a[i + offset] = (a0 + a2 + a1 + a3) % mod
a[i + offset + p] = (a0 + a2 - a1 - a3) % mod
a[i + offset + p * 2] = (a0 - a2 + a1na3imag) % mod
a[i + offset + p * 3] = (a0 - a2 - a1na3imag) % mod
if s + 1 != 1 << len_:
rot *= rate3[(~s & -~s).bit_length() - 1]
rot %= mod
len_ += 2
def butterfly_inv(a):
n = len(a)
h = (n - 1).bit_length()
len_ = h
while len_:
if len_ == 1:
p = 1 << (h - len_)
irot = 1
for s in range(1 << (len_ - 1)):
offset = s << (h - len_ + 1)
for i in range(p):
l = a[i + offset]
r = a[i + offset + p]
a[i + offset] = (l + r) % mod
a[i + offset + p] = (l - r) * irot % mod
if s + 1 != (1 << (len_ - 1)):
irot *= irate2[(~s & -~s).bit_length() - 1]
irot %= mod
len_ -= 1
else:
p = 1 << (h - len_)
irot = 1
for s in range(1 << (len_ - 2)):
irot2 = irot * irot % mod
irot3 = irot2 * irot % mod
offset = s << (h - len_ + 2)
for i in range(p):
a0 = a[i + offset]
a1 = a[i + offset + p]
a2 = a[i + offset + p * 2]
a3 = a[i + offset + p * 3]
a2na3iimag = (a2 - a3) * iimag % mod
a[i + offset] = (a0 + a1 + a2 + a3) % mod
a[i + offset + p] = (a0 - a1 + a2na3iimag) * irot % mod
a[i + offset + p * 2] = (a0 + a1 - a2 - a3) * irot2 % mod
a[i + offset + p * 3] = (a0 - a1 - a2na3iimag) * irot3 % mod
if s + 1 != (1 << (len_ - 2)):
irot *= irate3[(~s & -~s).bit_length() - 1]
irot %= mod
len_ -= 2
def convolution_naive(a, b):
n = len(a)
m = len(b)
ans = [0] * (n + m - 1)
if n < m:
for j in range(m):
for i in range(n):
ans[i + j] = (ans[i + j] + a[i] * b[j]) % mod
else:
for i in range(n):
for j in range(m):
ans[i + j] = (ans[i + j] + a[i] * b[j]) % mod
return ans
def convolution_ntt(a, b):
a = a.copy()
b = b.copy()
n = len(a)
m = len(b)
z = 1 << (n + m - 2).bit_length()
a += [0] * (z - n)
butterfly(a)
b += [0] * (z - m)
butterfly(b)
for i in range(z):
a[i] = a[i] * b[i] % mod
butterfly_inv(a)
a = a[:n + m - 1]
iz = pow(z, mod - 2, mod)
for i in range(n + m - 1):
a[i] = a[i] * iz % mod
return a
def convolution_square(a):
a = a.copy()
n = len(a)
z = 1 << (2 * n - 2).bit_length()
a += [0] * (z - n)
butterfly(a)
for i in range(z):
a[i] = a[i] * a[i] % mod
butterfly_inv(a)
a = a[:2 * n - 1]
iz = pow(z, mod - 2, mod)
for i in range(2 * n - 1):
a[i] = a[i] * iz % mod
return a
def convolution(a, b):
"""It calculates (+, x) convolution in mod 998244353.
Given two arrays a[0], a[1], ..., a[n - 1] and b[0], b[1], ..., b[m - 1],
it calculates the array c of length n + m - 1, defined by
> c[i] = sum(a[j] * b[i - j] for j in range(i + 1)) % 998244353.
It returns an empty list if at least one of a and b are empty.
Complexity
----------
> O(n log n), where n = len(a) + len(b).
"""
n = len(a)
m = len(b)
if n == 0 or m == 0:
return []
if min(n, m) <= 60:
return convolution_naive(a, b)
if a is b:
return convolution_square(a)
return convolution_ntt(a, b)
def integrate(a):
a=a.copy()
n = len(a)
assert n > 0
a.pop()
a.insert(0, 0)
inv = [1, 1]
for i in range(2, n):
inv.append(-inv[mod%i] * (mod//i) % mod)
a[i] = a[i] * inv[i] % mod
return a
def differentiate(a):
n = len(a)
assert n > 0
for i in range(2, n):
a[i] = a[i] * i % mod
a.pop(0)
a.append(0)
return a
def inverse(a):
n = len(a)
assert n > 0 and a[0] != 0
res = [pow(a[0], mod - 2, mod)]
m = 1
while m < n:
f = a[:min(n,2*m)] + [0]*(2*m-min(n,2*m))
g = res + [0]*m
butterfly(f)
butterfly(g)
for i in range(2*m):
f[i] = f[i] * g[i] % mod
butterfly_inv(f)
f = f[m:] + [0]*m
butterfly(f)
for i in range(2*m):
f[i] = f[i] * g[i] % mod
butterfly_inv(f)
iz = pow(2*m, mod-2, mod)
iz = (-iz*iz) % mod
for i in range(m):
f[i] = f[i] * iz % mod
res += f[:m]
m <<= 1
return res[:n]
def log(a):
a = a.copy()
n = len(a)
assert n > 0 and a[0] == 1
a_inv = inverse(a)
a=differentiate(a)
a = convolution(a, a_inv)[:n]
a=integrate(a)
return a
def exp(a):
a = a.copy()
n = len(a)
assert n > 0 and a[0] == 0
g = [1]
a[0] = 1
h_drv = a.copy()
h_drv=differentiate(h_drv)
m = 1
while m < n:
f_fft = a[:m] + [0] * m
butterfly(f_fft)
if m > 1:
_f = [f_fft[i] * g_fft[i] % mod for i in range(m)]
butterfly_inv(_f)
_f = _f[m // 2:] + [0] * (m // 2)
butterfly(_f)
for i in range(m):
_f[i] = _f[i] * g_fft[i] % mod
butterfly_inv(_f)
_f = _f[:m//2]
iz = pow(m, mod - 2, mod)
iz *= -iz
iz %= mod
for i in range(m//2):
_f[i] = _f[i] * iz % mod
g.extend(_f)
t = a[:m]
t=differentiate(t)
r = h_drv[:m - 1]
r.append(0)
butterfly(r)
for i in range(m):
r[i] = r[i] * f_fft[i] % mod
butterfly_inv(r)
im = pow(-m, mod - 2, mod)
for i in range(m):
r[i] = r[i] * im % mod
for i in range(m):
t[i] = (t[i] + r[i]) % mod
t = [t[-1]] + t[:-1]
t += [0] * m
butterfly(t)
g_fft = g + [0] * (2 * m - len(g))
butterfly(g_fft)
for i in range(2 * m):
t[i] = t[i] * g_fft[i] % mod
butterfly_inv(t)
t = t[:m]
i2m = pow(2 * m, mod - 2, mod)
for i in range(m):
t[i] = t[i] * i2m % mod
v = a[m:min(n, 2 * m)]
v += [0] * (m - len(v))
t = [0] * (m - 1) + t + [0]
t=integrate(t)
for i in range(m):
v[i] = (v[i] - t[m + i]) % mod
v += [0] * m
butterfly(v)
for i in range(2 * m):
v[i] = v[i] * f_fft[i] % mod
butterfly_inv(v)
v = v[:m]
i2m = pow(2 * m, mod - 2, mod)
for i in range(m):
v[i] = v[i] * i2m % mod
for i in range(min(n - m, m)):
a[m + i] = v[i]
m *= 2
return a
def power(a,k):
n = len(a)
assert n>0
if k==0:
return [1]+[0]*(n-1)
l = 0
while l < len(a) and not a[l]:
l += 1
if l * k >= n:
return [0] * n
ic = pow(a[l], mod - 2, mod)
pc = pow(a[l], k, mod)
a = log([a[i] * ic % mod for i in range(l, len(a))])
for i in range(len(a)):
a[i] = a[i] * k % mod
a = exp(a)
for i in range(len(a)):
a[i] = a[i] * pc % mod
a = [0] * (l * k) + a[:n - l * k]
return a
def sqrt(a):
if len(a) == 0:
return []
if a[0] == 0:
for d in range(1, len(a)):
if a[d]:
if d & 1:
return None
if len(a) - 1 < d // 2:
break
res=sqrt(a[d:]+[0]*(d//2))
if res == None:
return None
res = [0]*(d//2)+res
return res
return [0]*len(a)
sqr = Tonelli_Shanks(a[0],mod)
if sqr == None:
return None
T = [0] * (len(a))
T[0] = sqr
res = T.copy()
T[0] = pow(sqr,mod-2,mod) #T:res^{-1}
m = 1
two_inv = (mod + 1) // 2
F = [sqr]
while m <= len(a) - 1:
for i in range(m):
F[i] *= F[i]
F[i] %= mod
butterfly_inv(F)
iz = pow(m, mod-2, mod)
for i in range(m):
F[i] = F[i] * iz % mod
delta = [0] * (2 * m)
for i in range(m):
delta[i + m] = F[i] - a[i] - (a[i + m] if i+m<len(a) else 0)
butterfly(delta)
G = [0] * (2 * m)
for i in range(m):
G[i] = T[i]
butterfly(G)
for i in range(2 * m):
delta[i] *= G[i]
delta[i] %= mod
butterfly_inv(delta)
iz = pow(2*m, mod-2, mod)
for i in range(2*m):
delta[i] = delta[i] * iz % mod
for i in range(m, min(2 * m, len(a))):
res[i] = -delta[i] * two_inv%mod
res[i]%=mod
if 2 * m > len(a) - 1:
break
F = res[:2 * m]
butterfly(F)
eps = [F[i] * G[i] % mod for i in range(2 * m)]
butterfly_inv(eps)
for i in range(m):
eps[i] = 0
iz = pow(2*m, mod-2, mod)
for i in range(m,2*m):
eps[i] = eps[i] * iz % mod
butterfly(eps)
for i in range(2 * m):
eps[i] *= G[i]
eps[i] %= mod
butterfly_inv(eps)
for i in range(m, 2 * m):
T[i] = -eps[i]*iz
T[i]%=mod
iz = iz*iz % mod
m <<= 1
return res
def division_modulus(f,g):
n=len(f)
m=len(g)
while m and g[m-1]==0:
m-=1
assert m
if n>=m:
fR=f[::-1][:n-m+1]
gR=g[:m][::-1][:n-m+1]+[0]*max(0,n-m+1-m)
qR=convolution(fR,inverse(gR))[:n-m+1]
q=qR[::-1]
r=[(f[i]-x)%mod for i,x in enumerate(convolution(g,q)[:m-1])]
while r and r[-1]==0:
r.pop()
else:
q,r=[],f.copy()
return q,r
def taylor_shift(a,c):
a=a.copy()
n=len(a)
#MD=MOD(mod)
#MD.Build_Fact(n-1)
for i in range(n):
a[i]*=MD.Fact(i)
a[i]%=mod
C=[1]
for i in range(1,n):
C.append(C[-1]*c%mod)
for i in range(n):
C[i]*=MD.Fact_Inve(i)
C[i]%=mod
a=convolution(a,C[::-1])[n-1:]
for i in range(n):
a[i]*=MD.Fact_Inve(i)
a[i]%=mod
return a
def multipoint_evaluation(f, x):
n = len(x)
sz = 1 << (n - 1).bit_length()
g = [[1] for _ in range(2 * sz)]
for i in range(n):
g[i + sz] = [-x[i], 1]
for i in range(1, sz)[::-1]:
g[i] = convolution(g[2 * i],g[2 * i + 1])
g[1] =division_modulus(f,g[1])[1]
for i in range(2, 2 * sz):
g[i]=division_modulus(g[i>>1],g[i])[1]
res = [g[i + sz][0] if g[i+sz] else 0 for i in range(n)]
return res
def Chirp_Z_transform(f,q,M):
if q==0:
if f:
return f[0]%mod
else:
return 0
if M==0:
return []
N=len(f)
pow_q=[1]+[q]*(N+M-2)
inve_q=pow(q,mod-2,mod)
pow_inve_q=[1]+[inve_q]*(N+M-2)
for _ in range(2):
for i in range(1,N+M-1):
pow_q[i]*=pow_q[i-1]
pow_q[i]%=mod
pow_inve_q[i]*=pow_inve_q[i-1]
pow_inve_q[i]%=mod
a=[f[i]*pow_inve_q[i]%mod for i in range(N-1,-1,-1)]
b=pow_q
ab=convolution(a,b)
return [ab[j+N-1]*pow_inve_q[j]%mod for j in range(M)]
def relaxed_convolution(N,f):
retu=[0]*N
A,B=[],[]
C=None
for i in range(N):
a,b=f(i,C)
A.append(a)
B.append(b)
pow2=1
while (i+2)%pow2==0:
if pow2==i+2:
break
elif pow2*2==i+2:
tpl=((i+1-pow2,i+1,i+1-pow2,i+1),)
else:
tpl=((pow2-1,2*pow2-1,i+1-pow2,i+1),(i+1-pow2,i+1,pow2-1,2*pow2-1),)
for la,ra,lb,rb in tpl:
for j,c in enumerate(convolution(A[la:ra],B[lb:rb]),la+lb):
if j<N:
retu[j]+=c
retu[j]%=mod
pow2*=2
C=retu[i]
return retu
def Berlekamp_Massey(A,mod):
n = len(A)
B, C = [1], [1]
l, m, p = 0, 1, 1
for i in range(n):
d = A[i]
for j in range(1, l + 1):
d += C[j] * A[i - j]
d %= mod
if d == 0:
m += 1
continue
T = C.copy()
q = pow(p, mod - 2, mod) * d % mod
if len(C) < len(B) + m:
C += [0] * (len(B) + m - len(C))
for j, b in enumerate(B):
C[j + m] -= q * b
C[j + m] %= mod
if 2 * l <= i:
B = T
l, m, p = i + 1 - l, 1, d
else:
m += 1
res = [-c % mod for c in C[1:]]
return res
def BMBM(A,N,mod):
deno=[1]+[-c for c in Berlekamp_Massey(A,mod)]
nume=[0]*(len(deno)-1)
for i in range(len(A)):
for j in range(len(deno)):
if i+j<len(nume):
nume[i+j]+=A[i]*deno[j]
nume[i+j]%=mod
return Bostan_Mori(nume,deno,N,mod=mod)
import math
from collections import defaultdict
# pow/log/exp of FPS
# thanks for https://judge.yosupo.jp/submission/126665
# FFT
# code from: https://atcoder.jp/contests/practice2/submissions/24974537
# but changed a little
_fft_mod = 998244353
_fft_imag = 911660635
_fft_iimag = 86583718
_fft_rate2 = (911660635, 509520358, 369330050, 332049552, 983190778, 123842337, 238493703, 975955924, 603855026, 856644456, 131300601, 842657263,
    730768835, 942482514, 806263778, 151565301, 510815449, 503497456, 743006876, 741047443, 56250497, 867605899)
_fft_irate2 = (86583718, 372528824, 373294451, 645684063, 112220581, 692852209, 155456985, 797128860, 90816748, 860285882, 927414960, 354738543,
    109331171, 293255632, 535113200, 308540755, 121186627, 608385704, 438932459, 359477183, 824071951, 103369235)
_fft_rate3 = (372528824, 337190230, 454590761, 816400692, 578227951, 180142363, 83780245, 6597683, 70046822, 623238099, 183021267, 402682409,
    631680428, 344509872, 689220186, 365017329, 774342554, 729444058, 102986190, 128751033, 395565204)
_fft_irate3 = (509520358, 929031873, 170256584, 839780419, 282974284, 395914482, 444904435, 72135471, 638914820, 66769500, 771127074, 985925487,
    262319669, 262341272, 625870173, 768022760, 859816005, 914661783, 430819711, 272774365, 530924681)
def _butterfly(a):
n = len(a)
h = (n - 1).bit_length()
len_ = 0
while len_ < h:
if h - len_ == 1:
p = 1 << (h - len_ - 1)
rot = 1
for s in range(1 << len_):
offset = s << (h - len_)
for i in range(p):
l = a[i + offset]
r = a[i + offset + p] * rot % _fft_mod
a[i + offset] = (l + r) % _fft_mod
a[i + offset + p] = (l - r) % _fft_mod
if s + 1 != (1 << len_):
rot *= _fft_rate2[(~s & -~s).bit_length() - 1]
rot %= _fft_mod
len_ += 1
else:
p = 1 << (h - len_ - 2)
rot = 1
for s in range(1 << len_):
rot2 = rot * rot % _fft_mod
rot3 = rot2 * rot % _fft_mod
offset = s << (h - len_)
for i in range(p):
a0 = a[i + offset]
a1 = a[i + offset + p] * rot
a2 = a[i + offset + p * 2] * rot2
a3 = a[i + offset + p * 3] * rot3
a1na3imag = (a1 - a3) % _fft_mod * _fft_imag
a[i + offset] = (a0 + a2 + a1 + a3) % _fft_mod
a[i + offset + p] = (a0 + a2 - a1 - a3) % _fft_mod
a[i + offset + p * 2] = (a0 - a2 + a1na3imag) % _fft_mod
a[i + offset + p * 3] = (a0 - a2 - a1na3imag) % _fft_mod
if s + 1 != (1 << len_):
rot *= _fft_rate3[(~s & -~s).bit_length() - 1]
rot %= _fft_mod
len_ += 2
def _butterfly_inv(a):
n = len(a)
h = (n - 1).bit_length()
len_ = h
while len_:
if len_ == 1:
p = 1 << (h - len_)
irot = 1
for s in range(1 << (len_ - 1)):
offset = s << (h - len_ + 1)
for i in range(p):
l = a[i + offset]
r = a[i + offset + p]
a[i + offset] = (l + r) % _fft_mod
a[i + offset + p] = (l - r) * irot % _fft_mod
if s + 1 != (1 << (len_ - 1)):
irot *= _fft_irate2[(~s & -~s).bit_length() - 1]
irot %= _fft_mod
len_ -= 1
else:
p = 1 << (h - len_)
irot = 1
for s in range(1 << (len_ - 2)):
irot2 = irot * irot % _fft_mod
irot3 = irot2 * irot % _fft_mod
offset = s << (h - len_ + 2)
for i in range(p):
a0 = a[i + offset]
a1 = a[i + offset + p]
a2 = a[i + offset + p * 2]
a3 = a[i + offset + p * 3]
a2na3iimag = (a2 - a3) * _fft_iimag % _fft_mod
a[i + offset] = (a0 + a1 + a2 + a3) % _fft_mod
a[i + offset + p] = (a0 - a1 +
a2na3iimag) * irot % _fft_mod
a[i + offset + p * 2] = (a0 + a1 -
a2 - a3) * irot2 % _fft_mod
a[i + offset + p * 3] = (a0 - a1 -
a2na3iimag) * irot3 % _fft_mod
if s + 1 != (1 << (len_ - 1)):
irot *= _fft_irate3[(~s & -~s).bit_length() - 1]
irot %= _fft_mod
len_ -= 2
def _convolution_naive(a, b):
n = len(a)
m = len(b)
ans = [0] * (n + m - 1)
if n < m:
for j in range(m):
for i in range(n):
ans[i + j] = (ans[i + j] + a[i] * b[j]) % _fft_mod
else:
for i in range(n):
for j in range(m):
ans[i + j] = (ans[i + j] + a[i] * b[j]) % _fft_mod
return ans
def _convolution_fft(a, b):
a = a.copy()
b = b.copy()
n = len(a)
m = len(b)
z = 1 << (n + m - 2).bit_length()
a += [0] * (z - n)
_butterfly(a)
b += [0] * (z - m)
_butterfly(b)
for i in range(z):
a[i] = a[i] * b[i] % _fft_mod
_butterfly_inv(a)
a = a[:n + m - 1]
iz = pow(z, _fft_mod - 2, _fft_mod)
for i in range(n + m - 1):
a[i] = a[i] * iz % _fft_mod
return a
def _convolution_square(a):
a = a.copy()
n = len(a)
z = 1 << (2 * n - 2).bit_length()
a += [0] * (z - n)
_butterfly(a)
for i in range(z):
a[i] = a[i] * a[i] % _fft_mod
_butterfly_inv(a)
a = a[:2 * n - 1]
iz = pow(z, _fft_mod - 2, _fft_mod)
for i in range(2 * n - 1):
a[i] = a[i] * iz % _fft_mod
return a
def convolution(a, b):
n = len(a)
m = len(b)
if n == 0 or m == 0:
return []
if min(n, m) <= 0:
return _convolution_naive(a, b)
if a is b:
return _convolution_square(a)
return _convolution_fft(a, b)
# ----
# 1/F
# : a[0] != 0
# : FFT
def poly_inv(a, length = None):
if length == None: M = len(a)
else: M = length
if M <= 0: return []
n = len(a)
r = pow(a[0], _fft_mod-2, _fft_mod)
m = 1
res = [r]
while m < M:
f = a[:min(n,2*m)] + [0]*(2*m-min(n,2*m))
g = res + [0]*m
_butterfly(f)
_butterfly(g)
for i in range(2*m):
f[i] = f[i] * g[i] % _fft_mod
_butterfly_inv(f)
f = f[m:] + [0]*m
_butterfly(f)
for i in range(2*m):
f[i] = f[i] * g[i] % _fft_mod
_butterfly_inv(f)
iz = pow(2*m, _fft_mod-2, _fft_mod)
iz = (-iz*iz) % _fft_mod
for i in range(m):
f[i] = f[i] * iz % _fft_mod
res += f[:m]
m <<= 1
return res[:M]
#
# x
def multi_eval(x, a):
n = len(x)
siz = 1 << (n-1).bit_length()
g = [[1] for i in range(2 * siz)]
for i in range(n):
g[i + siz] = [-x[i], 1]
for i in range(siz-1, 0, -1):
g[i] = convolution(g[2 * i], g[2 * i + 1])
for i in range(1, 2 * siz):
if i == 1: f = a[::]
else: f = g[i >> 1]
m = len(f) - len(g[i]) + 1
v = convolution(f[::-1][:m], poly_inv(g[i][::-1], m))[m-1::-1]
w = convolution(v, g[i])
g[i] = f[::]
h = g[i]
for j in range(len(w)):
h[j] -= w[j]
h[j] %= _fft_mod
while len(h) > 1 and h[-1] == 0:
h.pop()
return [g[i+siz][0] for i in range(n)]
# DEF MOD FACT
mod = _fft_mod
N = 10**6 + 5
fact = [1]*(N+1)
factinv = [1]*(N+1)
for i in range(2, N+1):
fact[i] = fact[i-1] * i % mod
factinv[-1] = pow(fact[-1], mod-2, mod)
for i in range(N-1, 1, -1):
factinv[i] = factinv[i+1] * (i+1) % mod
def cmb(a, b):
if (a < b) or (b < 0): return 0
return fact[a] * factinv[b] % mod * factinv[a-b] % mod
# log(F)
# : a[0] = 1
# : FFT, inv
def poly_log(a, length = None):
if length == None: M = len(a)
else: M = length
if M <= 0: return []
n = len(a)
if n == 1: return [0] * M
b = [a[i+1] * (i+1) % _fft_mod for i in range(n-1)]
t = convolution(b, poly_inv(a, length = M))
return [0] + [t[i] * factinv[i+1] % _fft_mod * fact[i] % _fft_mod for i in range(M-1)]
# exp(F)
# : a[0] = 0
# : FFT, inv, log
def poly_exp(a, length = None):
if length == None: M = len(a)
else: M = length
if M <= 0: return []
n = len(a)
m = 1
res = [1]
while m < M:
f = a[:min(n,2*m)] + [0]*(2*m-min(n,2*m))
#print(res)
v = poly_log(res, length = 2*m)
w = [(f[i]-v[i])%_fft_mod for i in range(2*m)]
w[0] = (w[0]+1)%_fft_mod
g = convolution(res, w)
res += g[m:2*m]
m <<= 1
return res[:M]
def poly_pow_nonzero(a, m, l):
n = len(a)
bais = pow(a[0], m, _fft_mod)
invs = pow(a[0], _fft_mod-2, _fft_mod)
r = [a[i] * invs % _fft_mod for i in range(n)]
r = poly_log(r, length = l)
for i in range(l):
r[i] = r[i] * m % _fft_mod
r = poly_exp(r, length = l)
for i in range(l):
r[i] = r[i] * bais % _fft_mod
return r
def poly_pow(a, m, l):
n = len(a)
ind = 0
for i in range(n):
if a[i] != 0:
ind = i
break
if ind * m >= l:
return [0] * l
return [0] * (ind * m) + poly_pow_nonzero(a[ind:], m, l-ind*m)
# DEF MOD FACT 6
def main():
N,K=map(int,input().split())
A=list(map(int,input().split()))
mod=998244353
MOD=998244353
facts = [1] * (K + 1)
ifacts = [1] * (K + 1)
for i in range(K):
facts[i + 1] = facts[i] * (i + 1) % MOD
ifacts[i + 1] = pow(facts[i + 1], MOD - 2, MOD)
F = [[0 for i in range(K + 1)] for j in range(K + 1)]
F_log = [[0 for i in range(K + 1)] for j in range(K + 1)]
for i in range(K + 1):
for j in range(i + 1):
F[i][j] = ifacts[j]
F_log[i] = poly_log(F[i])
memo_log=F_log
ans=0
cntD=[0]*(K+1)
for d in range(K):
cntD[math.gcd(K,d)]+=1
for d in range(K+1):
if cntD[d]:
S=K//d
cnt=[0]*(d+2)
for i in range(N):
cnt[min(d,A[i]//S)]+=1
poly=exp([sum(memo_log[c][x]*cnt[c]%mod for c in range(1,d+1)) for x in range(d+1)])
ans+=cntD[d]*poly[d]%mod*fact[d]%mod
ans%=mod
ans*=pow(K,mod-2,mod)
ans%=mod
print(ans)
main()
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