human
PYTHON3 solution for "You are given n segments on a number line, numbered from 1 to n. The i-th segments covers all integer points from l_i to r_i and has a value w_i.

You are asked to select a subset of these segments (possibly, all of them). Once the subset is selected, it's possible to travel between two integer points if there exists a selected segment that covers both of them. A subset is good if it's possible to reach point m starting from point 1 in arbitrary number of moves.

The cost of the subset is the difference between the maximum and the minimum values of segments in it. Find the minimum cost of a good subset.

In every test there exists at least one good subset.

Input

The first line contains two integers n and m (1 ≤ n ≤ 3 ⋅ 10^5.
2 ≤ m ≤ 10^6) — the number of segments and the number of integer points.

Each of the next n lines contains three integers l_i, r_i and w_i (1 ≤ l_i < r_i ≤ m.
1 ≤ w_i ≤ 10^6) — the description of the i-th segment.

In every test there exists at least one good subset.

Output

Print a single integer — the minimum cost of a good subset.

Examples

Input

5 12
1 5 5
3 4 10
4 10 6
11 12 5
10 12 3

Output

3

Input

1 10
1 10 23

Output

0":


 ... Give me a Python program to find the minimum cost of a good subset?
assistant
#Here is Python program to find the minimum cost of a good subset.
 from sys import stdin, stdout

class LazySegmentTree:
    def __init__(self, data, default=0, func=min):
        """initialize the lazy segment tree with data"""
        self._default = default
        self._func = func

        self._len = len(data)
        self._size = _size = 1 << (self._len - 1).bit_length()
        self._lazy = [0] * (2 * _size)

        self.data = [default] * (2 * _size)
        self.data[_size:_size + self._len] = data
        for i in reversed(range(_size)):
            self.data[i] = func(self.data[i + i], self.data[i + i + 1])

    def __len__(self):
        return self._len

    def _push(self, idx):
        """push query on idx to its children"""
        # Let the children know of the queries
        q, self._lazy[idx] = self._lazy[idx], 0

        self._lazy[2 * idx] += q
        self._lazy[2 * idx + 1] += q
        self.data[2 * idx] += q
        self.data[2 * idx + 1] += q

    def _update(self, idx):
        """updates the node idx to know of all queries applied to it via its ancestors"""
        for i in reversed(range(1, idx.bit_length())):
            self._push(idx >> i)

    def _build(self, idx):
        """make the changes to idx be known to its ancestors"""
        idx >>= 1
        while idx:
            self.data[idx] = self._func(self.data[2 * idx], self.data[2 * idx + 1]) + self._lazy[idx]
            idx >>= 1

    def add(self, start, stop, value):
        """lazily add value to [start, stop)"""
        start = start_copy = start + self._size
        stop = stop_copy = stop + self._size
        while start < stop:
            if start & 1:
                self._lazy[start] += value
                self.data[start] += value
                start += 1
            if stop & 1:
                stop -= 1
                self._lazy[stop] += value
                self.data[stop] += value
            start >>= 1
            stop >>= 1

        # Tell all nodes above of the updated area of the updates
        self._build(start_copy)
        self._build(stop_copy - 1)

  ...