<｜begin▁of▁sentence｜>### Instruction:
Using the one_exchange function from NetworkX, how can one compute a partitioning of the graph with the edge set [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 0), (0, 3)] that results in a locally maximal cut value? An initial cut set {0, 3} is provided as a starting point.
### Response:
import networkx as nx
from networkx.algorithms.community import one_exchange

# Create a graph
G = nx.Graph()
G.add_edges_from([(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 0), (0, 3)])

# Initial cut (optional)
initial_cut = {0, 3}

# Use the one_exchange algorithm to find a maximum cut
partition, cut_value = one_exchange(G, initial_cut=initial_cut)

print('Partition:', partition)
print('Cut value:', cut_value)
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