<｜begin▁of▁sentence｜>### Instruction:
Given a list of NetworkX graphs, including a complete graph with 5 nodes and a cycle graph with 5 nodes, can the FeatherGraph model from the CIKM ‘20 paper 'Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models' be used to generate embeddings for these graphs? Use the fit method to process the graphs and then acquire the graph embeddings with the get_embedding method.
### Response:
import networkx as nx
from karateclub import FeatherGraph
import numpy as np

# Creating a list of NetworkX graphs
g1 = nx.complete_graph(5)
g2 = nx.cycle_graph(5)
graphs = [g1, g2]

# Instantiate the FeatherGraph model
model = FeatherGraph(order=5, eval_points=25, theta_max=2.5, seed=42, pooling='mean')

# Fit the model
model.fit(graphs)

# Get the embedding
embedding = model.get_embedding()

print(embedding)
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