<｜begin▁of▁sentence｜>### Instruction:
Given a graph G with 100 nodes where each node is connected with a probability of 0.1, and a feature matrix for each node with random values. Can you use the BANE model to create and extract embeddings for all nodes in this graph?
### Response:
import networkx as nx
from karateclub import BANE
import numpy as np

# Create a random graph
G = nx.fast_gnp_random_graph(100, 0.1)

# Create random node features
features = np.random.rand(100, 5)

# Initialize BANE model
bane_model = BANE(dimensions=32, svd_iterations=20, seed=42, alpha=0.3, iterations=100, binarization_iterations=20)

# Fit the model using the graph and the features
bane_model.fit(G, features)

# Get the embeddings
embeddings = bane_model.get_embedding()
print(embeddings)
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