In this Kata, you will be given a multi-dimensional array containing `2 or more` sub-arrays of integers. Your task is to find the maximum product that can be formed by taking any one element from each sub-array.

```
Examples:
solve( [[1, 2],[3, 4]] ) = 8. The max product is given by 2 * 4
solve( [[10,-15],[-1,-3]] ) = 45, given by (-15) * (-3)
solve( [[1,-1],[2,3],[10,-100]] ) = 300, given by (-1) * 3 * (-100)
```

More examples in test cases. Good luck!

Difficulty: EASY
Starter code: def solve(arr):
	

Solutions:
def solve(arr):
	(p, q) = (1, 1)
	for k in arr:
		(x, y) = (max(k), min(k))
		a = p * x
		b = q * x
		c = p * y
		d = q * y
		p = max(a, b, c, d)
		q = min(a, b, c, d)
	return max(p, q)


def solve(arr):
	result = arr[0]
	for number_array in range(1, len(arr)):
		result = [x * y for x in result for y in arr[number_array]]
	return max(result)


def solve(arr, cur=[1]):
	return solve(arr[1:], [x * y for x in cur for y in arr[0]]) if arr else max(cur)


from itertools import product
from functools import reduce

def solve(arr):
	return max((reduce(int.__mul__, p, 1) for p in product(*arr)))


from itertools import product
from functools import reduce
from operator import mul

def solve(A):
	return max(map(lambda g: reduce(mul, g, 1), product(*A)))


from functools import reduce

def solve(arr):
	f = lambda x, y: [i * j for i in x for j in y]
	return max(reduce(f, arr))


from itertools import product
from functools import reduce

def solve(arr):
	return max((reduce(lambda m, n: m * n, prod) for prod in product(*arr)))


from functools import reduce
from itertools import product
from operator import mul

def solve(arr):
	xss = [[min(a), max(a)] for a in arr]
	return max((reduce(mul, xs) for xs in product(*xss)))


def solve(a):
	r_min = r_max = 1
	for x in a:
		cur = [n * m for n in [min(x), max(x)] for m in [r_min, r_max]]
		r_min = min(cur)
		r_max = max(cur)
	return r_max