import networkx as nx

import matplotlib.pyplot as plt

​

# Create an empty graph

G = nx.Graph()

​

# Define the number of nodes in each layer

input_nodes = 3

hidden_nodes = 4

​

# Add nodes to the graph

for i in range(input_nodes):

    G.add_node("Input {}".format(i+1))

​

for i in range(hidden_nodes):

    G.add_node("Hidden {}".format(i+1))

​

# Add edges between nodes

for i in range(input_nodes):

    for j in range(hidden_nodes):

        G.add_edge("Input {}".format(i+1), "Hidden {}".format(j+1))

​

# Position nodes in the graph

pos = nx.spring_layout(G)

​

# Draw the graph

nx.draw(G, pos, with_labels=True, node_size=800, node_color='lightblue', font_size=10, font_weight='bold', edge_color='gray')

​

# Display the graph

plt.title("Neural Network Graph")

plt.axis('off')

plt.show()