Remove load_state and save_state

miplearn/tests/test_benchmark.py

@@ -18,8 +18,6 @@ def test_benchmark():
     # Training phase...
     training_solver = LearningSolver()
     training_solver.parallel_solve(train_instances, n_jobs=10)
-    training_solver.fit()
-    training_solver.save_state("data.bin")
 
     # Test phase...
     test_solvers = {
@@ -27,7 +25,7 @@ def test_benchmark():
         "Strategy B": LearningSolver(),
     }
     benchmark = BenchmarkRunner(test_solvers)
-    benchmark.load_state("data.bin")
+    benchmark.fit(train_instances)
     benchmark.parallel_solve(test_instances, n_jobs=2, n_trials=2)
     assert benchmark.raw_results().values.shape == (12,13)
     

miplearn/tests/test_solver.py

@@ -41,29 +41,6 @@ def test_solver():
             solver.fit()
             solver.solve(instance)
 
-
-# def test_solve_save_load_state():
-#     instance = _get_instance()
-#     components_before = {
-#         "warm-start": WarmStartComponent(),
-#     }
-#     solver = LearningSolver(components=components_before)
-#     solver.solve(instance)
-#     solver.fit()
-#     solver.save_state("/tmp/knapsack_train.bin")
-#     prev_x_train_len = len(solver.components["warm-start"].x_train)
-#     prev_y_train_len = len(solver.components["warm-start"].y_train)
-    
-#     components_after = {
-#         "warm-start": WarmStartComponent(),
-#     }
-#     solver = LearningSolver(components=components_after)
-#     solver.load_state("/tmp/knapsack_train.bin")
-#     assert len(solver.components.keys()) == 1
-#     assert len(solver.components["warm-start"].x_train) == prev_x_train_len
-#     assert len(solver.components["warm-start"].y_train) == prev_y_train_len
-
-
 def test_parallel_solve():
     instances = [_get_instance() for _ in range(10)]
     solver = LearningSolver()