<｜begin▁of▁sentence｜>### Instruction:
Given a graph where each node connects to any other with a probability of 0.5, how would you use NetworkX's 'randomized_partitioning' function to create a random partition of its nodes, and how would you determine the cut size of the partition?
### Response:
import networkx as nx
from networkx.algorithms.community import randomized_partitioning

# Create a graph
G = nx.erdos_renyi_graph(10, 0.5)

# Perform randomized partitioning of the graph nodes
# p is the probability of adding a node to the set being formed
p = 0.5
# You can optionally define a seed for reproducibility
seed = 42

# Compute the random partitioning
partition, cut_size = randomized_partitioning(G, seed=seed, p=p)

# Print our partition and the cut size
print('Partition 1:', partition[0])
print('Partition 2:', partition[1])
print('Cut size:', cut_size)
<|EOT|>
