min

The tool min returns the minimum value along a given axis.

import numpy

my_array = numpy.array([[2, 5],
[3, 7],
[1, 3],
[4, 0]])

print numpy.min(my_array, axis = 0) #Output : [1 0]
print numpy.min(my_array, axis = 1) #Output : [2 3 1 0]
print numpy.min(my_array, axis = None) #Output : 0
print numpy.min(my_array) #Output : 0

By default, the axis value is None. Therefore, it finds the minimum over all the dimensions of the input array.

max

The tool max returns the maximum value along a given axis.

import numpy

my_array = numpy.array([[2, 5],
[3, 7],
[1, 3],
[4, 0]])

print numpy.max(my_array, axis = 0) #Output : [4 7]
print numpy.max(my_array, axis = 1) #Output : [5 7 3 4]
print numpy.max(my_array, axis = None) #Output : 7
print numpy.max(my_array) #Output : 7

By default, the axis value is None. Therefore, it finds the maximum over all the dimensions of the input array.

Task

You are given a 2-D array with dimensions $N$X$\mbox{M}$.

Your task is to perform the min function over axis $\mbox{I}$ and then find the max of that.

Input Format

The first line of input contains the space separated values of $N$ and $\mbox{M}$.

The next $N$ lines contains $\mbox{M}$ space separated integers.

Output Format

Compute the min along axis $\mbox{I}$ and then print the max of that result.

Sample Input
4 2
2 5
3 7
1 3
4 0

Sample Output
3

Explanation

The min along axis $\mbox{I}$ = $[2,3,1,0]$

The max of $[2,3,1,0]$ = $3$

见题面

见题面