Complete the count_operation function to count the number of operations incurred by calling tab on each value in the given list. 

To count the number of arithmetic operations being performed by calls to tab(2) and to tab(3). The table below shows the number of operations incurred by each sub-computation for tab(2)

Expression	Reason	Ops encountered	Running Total
tab(2)	top level call		0
foo(2, 0)	i=0 in while loop of tab	None (yet)	0
range(1, n+1)	In foo: bound of for i loop.	+	1
count = count + bar(0, 0)	In foo, i=1, j=0, in for j loop.	+	2
range(2 * 0)	In bar: bound of for j loop	*	3
ub = 2 * ub	for j completed	*	4
count = count + bar(0, 0)	In foo, i=2, j=0 in for j loop.	+	5
range(2 * 1)	In bar, val=1, bound of for j loop	*	30
v % 2 == 1	In bar, v=1, j=0, if predicate in for j loop	%	31
count+1	In bar, v=1, consequent of if	+	32
v // 2	In bar, after if in for j loop, j=0	//	33
v % 2 == 1	In bar, v=0, j=1, if predicate in for j loop	%	34
ncount+1	In bar, v=0, alternative of if	+	35
v // 2	In bar, after if in for j loop, j=1	//	36
ub = 2 * ub	for j completed, i=2	*	37
i = i + 1	Back in tab inside while loop	+	38

Sample Input

2 2 3 

Sample Output

38 183

def tab(n): tbl = [] i = 0 while i < n: tbl.append(foo(n, i)) i = i + 1 return tbl def foo(n, r): ub = 1 count = 0 for i in range(1, n+1): for j in range(ub): count = count + bar(j, r) ub = 2 * ub return count def bar(val, r): count = 0 ncount = 0 v = val for j in range(2 * r): if v % 2 == 1: count = count + 1 else: ncount = ncount + 1 v = v // 2 if count == r: return 1 else: return 0

def count_operations(ns):