Vasya has an array of integers of length *n*.

Vasya performs the following operations on the array: on each step he finds the longest segment of consecutive equal integers (the leftmost, if there are several such segments) and removes it. For example, if Vasya's array is [13, 13, 7, 7, 7, 2, 2, 2], then after one operation it becomes [13, 13, 2, 2, 2].

Compute the number of operations Vasya should make until the array becomes empty, i.e. Vasya removes all elements from it.
The first line contains a single integer *n* (1 ≤ *n* ≤ 200 000) — the length of the array.

The second line contains a sequence *a*<sub class="lower-index">1</sub>, *a*<sub class="lower-index">2</sub>, ..., *a*<sub class="lower-index">*n*</sub> (1 ≤ *a*<sub class="lower-index">*i*</sub> ≤ 10<sup class="upper-index">9</sup>) — Vasya's array.
In the first example, at first Vasya removes two fives at the second and third positions. The array becomes [2, 2]. In the second operation Vasya removes two twos at the first and second positions. After that the array becomes empty.

In the second example Vasya has to perform five operations to make the array empty. In each of them he removes the first element from the array.

In the third example Vasya needs three operations. In the first operation he removes all integers 4, in the second — all integers 100, in the third — all integers 2.

In the fourth example in the first operation Vasya removes the first two integers 10. After that the array becomes [50, 10, 50, 50]. Then in the second operation Vasya removes the two rightmost integers 50, so that the array becomes [50, 10]. In the third operation he removes the remaining 50, and the array becomes [10] after that. In the last, fourth operation he removes the only remaining 10. The array is empty after that.
4
2 5 5 2
2
5
6 3 4 1 5
5
8
4 4 4 2 2 100 100 100
3
6
10 10 50 10 50 50
4
1
1
1
100
45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45
1
1
100
1
2
1 100
2
2
1 1
1
2
100 100
1
3
1 1 1
1
3
1 1 3
2
3
1 100 1
3
3
1 5 6
3
3
10 4 10
3
3
10 10 4
2
4
100 4 56 33
4
4
1 2 2 1
2
4
1 1 1 3
2
4
5 1 1 1
2
1
4
1
2
21 21
1
3
48 48 14
2
10
69 69 69 69 69 13 69 7 69 7
6
20
15 15 71 100 71 71 15 93 15 100 100 71 100 100 100 15 100 100 71 15
14
31
17 17 17 17 29 17 17 29 91 17 29 17 91 17 29 17 17 17 29 17 17 17 17 17 17 17 17 29 29 17 17
12
43
40 69 69 77 9 10 58 69 23 9 58 51 10 69 10 89 77 77 9 9 10 9 69 58 40 10 23 10 58 9 9 77 58 9 77 10 58 58 40 77 9 89 40
38
54
34 75 90 23 47 13 68 37 14 39 48 41 42 100 19 43 68 47 13 47 48 65 45 89 56 86 67 52 87 81 86 63 44 9 89 21 86 89 20 43 43 37 24 43 77 14 43 42 99 92 49 99 27 40
53
66
79 79 49 49 79 81 79 79 79 79 81 49 49 79 49 49 79 49 49 81 81 49 49 49 81 49 49 49 81 81 79 81 49 81 49 79 81 49 79 79 81 49 79 79 81 49 49 79 79 79 81 79 49 47 49 49 47 81 79 49 79 79 79 49 49 49
34
80
80 86 39 5 58 20 66 61 32 75 93 20 57 20 20 61 45 17 86 43 31 75 37 80 92 10 6 18 21 8 93 92 11 75 86 39 53 27 45 77 20 20 1 80 66 13 11 51 58 11 31 51 73 93 15 88 6 32 99 6 39 87 6 39 6 80 8 45 46 45 23 53 23 58 24 53 28 46 87 68
78
100
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7
3
9
1 2 2 2 1 2 2 2 1
3
12
1 1 1 49 63 63 63 19 38 38 65 27
7
7
31 31 21 21 13 96 96
4
3
1000000000 1 1000000000
3
'''input
4
2 5 5 2
'''
from sys import stdin
import collections
# from random import randint


# heapdict source code
def doc(s):
    if hasattr(s, '__call__'):
        s = s.__doc__
    def f(g):
        g.__doc__ = s
        return g
    return f

class heapdict(collections.MutableMapping):
    __marker = object()

    @staticmethod
    def _parent(i):
        return ((i - 1) >> 1)

    @staticmethod
    def _left(i):
        return ((i << 1) + 1)

    @staticmethod
    def _right(i):
        return ((i+1) << 1)    
    
    def __init__(self, *args, **kw):
        self.heap = []
        self.d = {}
        self.update(*args, **kw)

    @doc(dict.clear)
    def clear(self):
        self.heap.clear()
        self.d.clear()

    @doc(dict.__setitem__)
    def __setitem__(self, key, value):
        if key in self.d:
            self.pop(key)
        wrapper = [value, key, len(self)]
        self.d[key] = wrapper
        self.heap.append(wrapper)
        self._decrease_key(len(self.heap)-1)

    def _min_heapify(self, i):
        l = self._left(i)
        r = self._right(i)
        n = len(self.heap)
        if l < n and self.heap[l][0] < self.heap[i][0]:
            low = l
        else:
            low = i
        if r < n and self.heap[r][0] < self.heap[low][0]:
            low = r

        if low != i:
            self._swap(i, low)
            self._min_heapify(low)

    def _decrease_key(self, i):
        while i:
            parent = self._parent(i)
            if self.heap[parent][0] < self.heap[i][0]: break
            self._swap(i, parent)
            i = parent

    def _swap(self, i, j):
        self.heap[i], self.heap[j] = self.heap[j], self.heap[i]
        self.heap[i][2] = i
        self.heap[j][2] = j

    @doc(dict.__delitem__)
    def __delitem__(self, key):
        wrapper = self.d[key]
        while wrapper[2]:
            parentpos = self._parent(wrapper[2])
            parent = self.heap[parentpos]
            self._swap(wrapper[2], parent[2])
        self.popitem()

    @doc(dict.__getitem__)
    def __getitem__(self, key):
        return self.d[key][0]

    @doc(dict.__iter__)
    def __iter__(self):
        return iter(self.d)

    def popitem(self):
        """D.popitem() -> (k, v), remove and return the (key, value) pair with lowest\nvalue; but raise KeyError if D is empty."""
        wrapper = self.heap[0]
        if len(self.heap) == 1:
            self.heap.pop()
        else:
            self.heap[0] = self.heap.pop(-1)
            self.heap[0][2] = 0
            self._min_heapify(0)
        del self.d[wrapper[1]]
        return wrapper[1], wrapper[0]    

    @doc(dict.__len__)
    def __len__(self):
        return len(self.d)

    def peekitem(self):
        """D.peekitem() -> (k, v), return the (key, value) pair with lowest value;\n but raise KeyError if D is empty."""
        return (self.heap[0][1], self.heap[0][0])

del doc
__all__ = ['heapdict']


def create_necessities(arr, n):
	size_heap = heapdict()
	link = dict()

	# for unique indentification
	# for last element processing and saving code
	arr.append(-1)
	count = 1
	for i in range(n + 1):
		if i == 0:
			leader = arr[i]
			size = 1
		else:
			if arr[i] == arr[i - 1]:
				size += 1
			else:
				size_heap[count] = -size
				link[count] = leader

				count += 1
				leader = arr[i]
				size = 1

	# creating neighbours
	next_node = dict()
	prev_node = dict()
	for i in link:
		if i == 1:
			prev_node[i] = None

			if i + 1 < count:
				next_node[i] = i + 1
			else:
				next_node[i] = None
		elif i == count:
			break

		else:
			prev_node[i] = i - 1 
			if i + 1 < count:
				next_node[i] = i + 1
			else:
				next_node[i] = None

	# print(prev_node, next_node)
	return link, size_heap, prev_node, next_node
	

# main start
n = int(stdin.readline().strip())
arr = list(map(int, stdin.readline().split()))

# arr = []
# for i in range(200000):
# 	arr.append(randint(1, 1))
link, size_heap, prev_node, next_node = create_necessities(arr, len(arr))

op = 0
while len(size_heap) > 0:
	node, size = size_heap.popitem()

	prev_node[next_node[node]] = prev_node[node]
	next_node[prev_node[node]] = next_node[node]

	if prev_node[node] != None and next_node[node] != None and link[prev_node[node]] == link[next_node[node]]:
		if prev_node[node] in size_heap and next_node[node] in size_heap:

			# adjusting the size_heap
			temp1 = size_heap[prev_node[node]]
			temp2 = size_heap[next_node[node]]
			size_heap[prev_node[node]] = -float('inf')
			size_heap.popitem()
			size_heap[next_node[node]] = -float('inf')
			size_heap.popitem()
			size_heap[prev_node[node]] = temp1 + temp2

			# adjusting neighbours
			next_node[prev_node[node]] = next_node[node]
	op += 1
print(op)
