Edit distance（编辑距离）python

import numpy
import torch

def levenshteinDistance(s1, s2):
    if len(s1) > len(s2):
        s1, s2 = s2, s1

    distances = range(len(s1) + 1)
    for i2, c2 in enumerate(s2):
        distances_ = [i2+1]
        for i1, c1 in enumerate(s1):
            if c1 == c2:
                distances_.append(distances[i1])
            else:
                distances_.append(1 + min((distances[i1], distances[i1 + 1], distances_[-1])))
        distances = distances_
    return distances[-1]


# a = numpy.random.randint(0,100, (3,4))
# a = numpy.array(([[18, 98, 46, 59],
#                  [92, 78, 83, 47],
#                  [31, 77, 22, 92]]))
a = torch.tensor(([[18, 98, 46, 59],
                 [92, 78, 83, 47],
                 [31, 77, 22, 92]]))

# b = numpy.random.randint(0,100, (3,4))
# b = numpy.array([[18, 98, 46, 59, 60],
#                  [66,  4, 87,  4, 60],
#                  [27, 89,54,  2, 60]])
b = torch.tensor([[98, 18, 47, 59, 60],
                 [66,  4, 87,  4, 60],
                 [27, 89,54,  2, 60]])

print(a)
print(b)

for ai,bi in zip(a,b):
    print(levenshteinDistance(ai, bi))

# print(levenshteinDistance(['hors','hors','horsa'], ['horse','ros']))