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modernize hyperparameter search example #960

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f3b113e
update
OrestisLomis Apr 27, 2026
d288c9a
increase nb queens
OrestisLomis Apr 27, 2026
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28 changes: 14 additions & 14 deletions examples/advanced/hyperparameter_search.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,13 +3,12 @@

Generally applicable, and demonstrated on n-queens with ortools
"""
import sys
from cpmpy import *
from cpmpy.solvers import CPM_ortools, param_combinations
import cpmpy as cp
from cpmpy.solvers import param_combinations
from cpmpy.transformations.flatten_model import flatten_model

def main():

@IgnaceBleukx IgnaceBleukx May 7, 2026

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give model as arg?
Also function name could be more informative. Like "tune_parameters" or something.

model = nqueens(n=25)
model = nqueens(n=50)
# flatten once upfront, reduces overhead of multiple solves
model = flatten_model(model)

@IgnaceBleukx IgnaceBleukx May 7, 2026

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This is from when flatten was the only transformation for ortools...
I would actually just remove this. The overhead should be negligable, and we don't count it in the runtime anyway (only solve time there)


Expand All @@ -22,7 +21,7 @@ def main():
configs = [] # (runtime, param)
for params in param_combinations(all_params):
print("Running with", params)
s = CPM_ortools(model)
s = cp.SolverLookup.get("ortools", model)
s.solve(**params)
print(s.status())

Expand All @@ -36,24 +35,25 @@ def main():
print("Fastest in", round(best[0],2), "seconds, config:", best[1])
print("Comparing best -- worst:", round(configs[0][0],2), "--", round(configs[-1][0],2))

s = CPM_ortools(model); s.solve()
s = cp.SolverLookup.get("ortools", model)
s.solve()
print("With default parameters:", round(s.status().runtime,2))

# Outputs:
# Fastest in 0.02 seconds, config: {'cp_model_probing_level': 0, 'linearization_level': 0, 'symmetry_level': 1}
# Comparing best -- worst: 0.02 -- 0.2
# With default parameters: 0.13
# Fastest in 0.01 seconds, config: {'cp_model_probing_level': 0, 'linearization_level': 2, 'symmetry_level': 0}
# Comparing best -- worst: 0.05 -- 0.24
# With default parameters: 0.16



def nqueens(n=8):
""" N-queens problem
"""
queens = intvar(1,n, shape=n)
return Model(
AllDifferent(queens),
AllDifferent([queens[i] + i for i in range(n)]),
AllDifferent([queens[i] - i for i in range(n)]),
queens = cp.intvar(1,n, shape=n)
return cp.Model(
cp.AllDifferent(queens),
cp.AllDifferent([queens[i] + i for i in range(n)]),
cp.AllDifferent([queens[i] - i for i in range(n)]),
)


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