<｜begin▁of▁sentence｜>### Instruction:
As a fitness trainer, when designing and leading exercise programs, it is important to group individuals based on their specific fitness levels and goals. Just as in the context of a graph with 10 vertices arranged into 3 clusters, with the first 3 vertices representing one cluster, the next 3 vertices representing another, and the last 4 representing a third cluster, it is crucial to be able to determine the sizes of each cluster in order to tailor workouts effectively.

In this scenario, using the VertexClustering.sizes function in the igraph API would be analogous to understanding the composition of each fitness cluster in terms of the number of individuals it contains. This would enable the fitness trainer to allocate appropriate resources and attention to each group, ensuring that the exercise program benefits all participants.
### Response:
import igraph as ig

# Create a graph with 3 clusters
vertices = 10
g = ig.Graph.Full(3)
g += ig.Graph.Full(3)
g += ig.Graph.Full(4)
clustering = ig.VertexClustering(g, [0, 0, 0, 1, 1, 1, 2, 2, 2, 2])

# Get the sizes of the clusters
cluster_sizes = clustering.sizes()
print(cluster_sizes)
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