<｜begin▁of▁sentence｜>### Instruction:
Given a bipartite graph with edges [('A', 1), ('B', 1), ('C', 2), ('D', 3), ('E', 4), ('A', 2)] and nodes ['A', 'B', 'C', 'D', 'E'] in one set and [1, 2, 3, 4] in the other, compute the minimum vertex cover.
### Response:
import networkx as nx
from networkx.algorithms.bipartite.matching import maximum_matching
from networkx.algorithms.bipartite.covering import to_vertex_cover

# Create a bipartite graph
B = nx.Graph()
B.add_nodes_from(['A', 'B', 'C', 'D', 'E'], bipartite=0)
B.add_nodes_from([1, 2, 3, 4], bipartite=1)
B.add_edges_from([('A', 1), ('B', 1), ('C', 2), ('D', 3), ('E', 4), ('A', 2)])

# Compute maximum matching for the bipartite graph
matching = maximum_matching(B)

# Determine one bipartite node set if not already labeled
top_nodes = {n for n, d in B.nodes(data=True) if d['bipartite']==0}

# Compute the minimum vertex cover
vertex_cover = to_vertex_cover(B, matching, top_nodes)

print("Minimum vertex cover:", vertex_cover)
<|EOT|>
