Problem: Misha walked through the snowy forest and he was so fascinated by the trees to decide to draw his own tree!

Misha would like to construct a rooted tree with n vertices, indexed from 1 to n, where the root has index 1. Every other vertex has a parent p_i, and i is called a child of vertex p_i. Vertex u belongs to the subtree of vertex v iff v is reachable from u while iterating over the parents (u, p_{u}, p_{p_{u}}, ...). Clearly, v belongs to its own subtree, and the number of vertices in the subtree is called the size of the subtree. Misha is only interested in trees where every vertex belongs to the subtree of vertex 1.

Below there is a tree with 6 vertices. The subtree of vertex 2 contains vertices 2, 3, 4, 5. Hence the size of its subtree is 4. 

<image>

The branching coefficient of the tree is defined as the maximum number of children in any vertex. For example, for the tree above the branching coefficient equals 2. Your task is to construct a tree with n vertices such that the sum of the subtree sizes for all vertices equals s, and the branching coefficient is minimum possible.

Input

The only input line contains two integers n and s — the number of vertices in the tree and the desired sum of the subtree sizes (2 ≤ n ≤ 10^5; 1 ≤ s ≤ 10^{10}).

Output

If the required tree does not exist, output «No». Otherwise output «Yes» on the first line, and in the next one output integers p_2, p_3, ..., p_n, where p_i denotes the parent of vertex i.

Examples

Input


3 5


Output


Yes
1 1 


Input


4 42


Output


No


Input


6 15


Output


Yes
1 2 3 1 5 

Note

Below one can find one of the possible solutions for the first sample case. The sum of subtree sizes equals 3 + 1 + 1 = 5, and the branching coefficient equals 2.

<image>

Below one can find one of the possible solutions for the third sample case. The sum of subtree sizes equals 6 + 3 + 2 + 1 + 2 + 1 = 15, and the branching coefficient equals 2.

<image>

Solution (in PYTHON3):

Solution:
def good(max_branch, s, n):
    nodes = 0
    can = 1
    lowest_s = 0
    depth = 1
    while(nodes < n):
        added = min(n - nodes, can)
        lowest_s += added * depth
        nodes += added
        can *= max_branch
        depth += 1
    return lowest_s <= s


n, s = map(int, input().split())

if s < 2 * n - 1 or s * 2 > n * (n + 1):
    print('No')
else:
    lo, hi = 1, n
    while lo < hi:
        mid = (lo + hi) >> 1
        if good(mid, s, n) == False:
            lo = mid + 1
        else:
            hi = mid

    max_branch = lo

    level_size = [1] * (n + 1)
    node_level = [i for i in range(n + 1)]
    cur_node = n
    cur_level = 1
    cur_sum = n * (n + 1) // 2
    can = 1
    while cur_sum > s:
        if level_size[cur_level] == can:
            cur_level += 1
            can *= max_branch
            
        if cur_sum - (cur_node - cur_level) < s:
            cur_level = cur_node - (cur_sum - s)
                
        node_level[cur_node] = cur_level
        level_size[cur_level] += 1
        cur_sum -= cur_node - cur_level
        cur_node -= 1

    #print(cur_sum)
    #print(node_level)
    
    node_list = [[] for _ in range(n + 1)]
    for i in range(1, n + 1):
        node_list[node_level[i]].append(i)

    pre = 0
    children = [0] * (n + 1)
    parent = [-1] * (n + 1)
    seen_nodes = 1
    for level in range(2, n + 1):
        idx = 0
        if not node_list[level - 1]:
            assert seen_nodes == n
            break
        cur_father = node_list[level - 1][0]
        for node in node_list[level]:
            if children[cur_father] == max_branch:
                idx += 1
                cur_father = node_list[level - 1][idx]
            children[cur_father] += 1
            parent[node] = cur_father
            seen_nodes += 1
            
    print('Yes')
    print(*parent[2:])