Problem: You have been blessed as a child of Omkar. To express your gratitude, please solve this problem for Omkar!

An array a of length n is called complete if all elements are positive and don't exceed 1000, and for all indices x,y,z (1 ≤ x,y,z ≤ n), a_{x}+a_{y} ≠ a_{z} (not necessarily distinct).

You are given one integer n. Please find any complete array of length n. It is guaranteed that under given constraints such array exists.

Input

Each test contains multiple test cases. The first line contains t (1 ≤ t ≤ 1000) — the number of test cases. Description of the test cases follows.

The only line of each test case contains one integer n (1 ≤ n ≤ 1000).

It is guaranteed that the sum of n over all test cases does not exceed 1000.

Output

For each test case, print a complete array on a single line. All elements have to be integers between 1 and 1000 and for all indices x,y,z (1 ≤ x,y,z ≤ n) (not necessarily distinct), a_{x}+a_{y} ≠ a_{z} must hold.

If multiple solutions exist, you may print any.

Example

Input


2
5
4


Output


1 5 3 77 12
384 384 44 44

Note

It can be shown that the outputs above are valid for each test case. For example, 44+44 ≠ 384.

Below are some examples of arrays that are NOT complete for the 1st test case:

[1,2,3,4,5] 

Notice that a_{1}+a_{2} = a_{3}.

[1,3000,1,300,1] 

Notice that a_{2} = 3000 > 1000.

Solution (in PYTHON3):

Solution:
## necessary imports
import sys
input = sys.stdin.readline
# from math import ceil, floor, factorial;

def ceil(x):
    if x != int(x):
        x = int(x) + 1;
    return x;
    
# swap_array function
def swaparr(arr, a,b):
    temp = arr[a];
    arr[a] = arr[b];
    arr[b] = temp

## gcd function
def gcd(a,b):
    if b == 0:
        return a
    return gcd(b, a % b);

## nCr function efficient using Binomial Cofficient
def nCr(n, k): 
    if(k > n - k): 
        k = n - k 
    res = 1
    for i in range(k): 
        res = res * (n - i) 
        res = res / (i + 1) 
    return int(res) 

## upper bound function code -- such that e in a[:i] e < x;
def upper_bound(a, x, lo=0, hi = None):
    if hi == None:
        hi = len(a);
    while lo < hi:
        mid = (lo+hi)//2
        if a[mid] < x:
            lo = mid+1
        else:
            hi = mid
    return lo

## prime factorization
def primefs(n):
    ## if n == 1    ## calculating primes
    primes = {}
    while(n%2 == 0 and n > 0):
        primes[2] = primes.get(2, 0) + 1
        n = n//2
    for i in range(3, int(n**0.5)+2, 2):
        while(n%i == 0 and n > 0):
            primes[i] = primes.get(i, 0) + 1
            n = n//i
    if n > 2:
        primes[n] = primes.get(n, 0) + 1
    ## prime factoriazation of n is stored in dictionary
    ## primes and can be accesed. O(sqrt n)
    return primes

## MODULAR EXPONENTIATION FUNCTION
def power(x, y, p): 
    res = 1
    x = x % p  
    if (x == 0) : 
        return 0
    while (y > 0) : 
        if ((y & 1) == 1) : 
            res = (res * x) % p 
        y = y >> 1      
        x = (x * x) % p 
    return res 

## DISJOINT SET UNINON FUNCTIONS
def swap(a,b):
    temp = a
    a = b
    b = temp
    return a,b

# find function with path compression included (recursive)
# def find(x, link):
#     if link[x] == x:
#         return x
#     link[x] = find(link[x], link);
#     return link[x];

# find function with path compression (ITERATIVE)
def find(x, link):
    p = x;
    while( p != link[p]):
        p = link[p];
    
    while( x != p):
        nex = link[x];
        link[x] = p;
        x = nex;
    return p;


# the union function which makes union(x,y)
# of two nodes x and y
def union(x, y, link, size):
    x = find(x, link)
    y = find(y, link)
    if size[x] < size[y]:
        x,y = swap(x,y)
    if x != y:
        size[x] += size[y]
        link[y] = x

## returns an array of boolean if primes or not USING SIEVE OF ERATOSTHANES
def sieve(n): 
    prime = [True for i in range(n+1)] 
    p = 2
    while (p * p <= n): 
        if (prime[p] == True): 
            for i in range(p * p, n+1, p):
                prime[i] = False
        p += 1
    return prime

#### PRIME FACTORIZATION IN O(log n) using Sieve ####
MAXN = int(1e5 + 5)
def spf_sieve():
    spf[1] = 1;
    for i in range(2, MAXN):
        spf[i] = i;
    for i in range(4, MAXN, 2):
        spf[i] = 2;
    for i in range(3, ceil(MAXN ** 0.5), 2):
        if spf[i] == i:
            for j in range(i*i, MAXN, i):
                if spf[j] == j:
                    spf[j] = i;
    ## function for storing smallest prime factors (spf) in the array

################## un-comment below 2 lines when using factorization #################
# spf = [0 for i in range(MAXN)]
# spf_sieve();
def factoriazation(x):
    ret = {};
    while x != 1:
        ret[spf[x]] = ret.get(spf[x], 0) + 1;
        x = x//spf[x]
    return ret
    ## this function is useful for multiple queries only, o/w use
    ## primefs function above. complexity O(log n)

## taking integer array input
def int_array():
    return list(map(int, input().strip().split()))
## taking string array input
def str_array():
    return input().strip().split();

#defining a couple constants
MOD = int(1e9)+7;
CMOD = 998244353;
INF = float('inf'); NINF = -float('inf');

################### ---------------- TEMPLATE ENDS HERE ---------------- ###################

for _ in range(int(input())):
    n = int(input());
    ans = [1] * n;
    print(*ans);