<｜begin▁of▁sentence｜>### Instruction:
Given the Astrophysics collaborations graph, can you read it from a GML file named 'astro-ph.gml', and use the Louvain and Leiden community detection algorithms from cdlib to find clusterings of the network? Then, can you calculate and print the Normalized Mutual Information (NMI) score to assess the similarity between the two resulting partitions?
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Reading the graph from the Astrophysics collaborations file
G = nx.read_gml('astro-ph.gml')

# Detecting communities using the Louvain algorithm
louvain_communities = algorithms.louvain(G)

# Detecting communities using the Leiden algorithm
leiden_communities = algorithms.leiden(G)

# Calculating the Normalized Mutual Information between the two partitions
nmi = evaluation.normalized_mutual_information(louvain_communities, leiden_communities)

# Printing the result
print(nmi.score)
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