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Move collected data to instance.training_data

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Alinson S. Xavier
2021-01-21 08:21:40 -06:00
parent 23dd311d75
commit 06402516e6
11 changed files with 97 additions and 89 deletions
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34
miplearn/solvers/tests/test_learning_solver.py
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@@ -25,20 +25,19 @@ def test_learning_solver():
)
solver.solve(instance)
assert instance.solution["x"][0] == 1.0
assert instance.solution["x"][1] == 0.0
assert instance.solution["x"][2] == 1.0
assert instance.solution["x"][3] == 1.0
assert instance.lower_bound == 1183.0
assert instance.upper_bound == 1183.0
assert round(instance.lp_solution["x"][0], 3) == 1.000
assert round(instance.lp_solution["x"][1], 3) == 0.923
assert round(instance.lp_solution["x"][2], 3) == 1.000
assert round(instance.lp_solution["x"][3], 3) == 0.000
assert round(instance.lp_value, 3) == 1287.923
assert instance.found_violated_lazy_constraints == []
assert instance.found_violated_user_cuts == []
assert len(instance.solver_log) > 100
data = instance.training_data[0]
assert data["Solution"]["x"][0] == 1.0
assert data["Solution"]["x"][1] == 0.0
assert data["Solution"]["x"][2] == 1.0
assert data["Solution"]["x"][3] == 1.0
assert data["Lower bound"] == 1183.0
assert data["Upper bound"] == 1183.0
assert round(data["LP solution"]["x"][0], 3) == 1.000
assert round(data["LP solution"]["x"][1], 3) == 0.923
assert round(data["LP solution"]["x"][2], 3) == 1.000
assert round(data["LP solution"]["x"][3], 3) == 0.000
assert round(data["LP value"], 3) == 1287.923
assert len(data["MIP log"]) > 100
solver.fit([instance])
solver.solve(instance)
@@ -55,7 +54,8 @@ def test_parallel_solve():
results = solver.parallel_solve(instances, n_jobs=3)
assert len(results) == 10
for instance in instances:
assert len(instance.solution["x"].keys()) == 4
data = instance.training_data[0]
assert len(data["Solution"]["x"].keys()) == 4
def test_solve_fit_from_disk():
@@ -73,14 +73,14 @@ def test_solve_fit_from_disk():
solver.solve(filenames[0])
with open(filenames[0], "rb") as file:
instance = pickle.load(file)
assert hasattr(instance, "solution")
assert len(instance.training_data) > 0
# Test: parallel_solve
solver.parallel_solve(filenames)
for filename in filenames:
with open(filename, "rb") as file:
instance = pickle.load(file)
assert hasattr(instance, "solution")
assert len(instance.training_data) > 0
# Test: solve (with specified output)
output = [f + ".out" for f in filenames]