<｜begin▁of▁sentence｜>### Instruction:
Given a karate club graph, which is known for community structures often used as a benchmark in social network analysis, how can you compute the non-randomness of the graph and the relative measure that indicates to what extent the graph is different from random graphs in terms of probability?
### Response:
import networkx as nx

# Create a karate club graph
G = nx.karate_club_graph()

# Compute non-randomness
nr, nr_rd = nx.non_randomness(G, 2)

print('Non-randomness:', nr)
print('Relative non-randomness:', nr_rd)
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