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1from itertools import permutations
2import numpy as np
3
4# slot 0 slot 1 slot 2
5cost = np.array([[0.8, 0.1, 0.5], # cat
6 [0.2, 0.9, 0.4]]) # chair
7
8assignments = permutations(range(cost.shape[1]), cost.shape[0])
9best = min(
10 assignments,
11 key=lambda slots: sum(cost[i, j] for i, j in enumerate(slots)),
12)
13
14assert best == (1, 0)
15print(best) # cat -> slot 1, chair -> slot 0
16# Slot 2 is supervised as no-object.