<｜begin▁of▁sentence｜>### Instruction:
As an infectious disease specialist, you are asked to use networkx to model a GNP random graph with 100 nodes and a probability for edge creation of 0.05. Then, you are required to utilize the SymmNMF model from the SDM’12 paper 'Symmetric Nonnegative Matrix Factorization for Graph Clustering' to obtain node embeddings and cluster memberships for the modeled graph.
### Response:
import networkx as nx
from karateclub import SymmNMF
import numpy as np

# Create a graph
G = nx.gnp_random_graph(100, 0.05)

# Initialize the SymmNMF model
model = SymmNMF(dimensions=32, iterations=200, rho=100.0, seed=42)

# Fit the model
model.fit(G)

# Get the embeddings
embeddings = model.get_embedding()

# Get the memberships
memberships = model.get_memberships()

# Example usage
print(embeddings)
print(memberships)
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