449 lines
14 KiB
Python
449 lines
14 KiB
Python
#!/usr/bin/env python3
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# Copyright 2010-2025 Google LLC
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Unit tests for ortools.sat.python.cmh."""
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import sys
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from absl.testing import absltest
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from ortools.sat.python import cp_model_helper as cmh
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from ortools.util.python import sorted_interval_list
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class Callback(cmh.SolutionCallback):
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def __init__(self):
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cmh.SolutionCallback.__init__(self)
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self.__solution_count = 0
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def OnSolutionCallback(self):
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print("New Solution")
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self.__solution_count += 1
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def solution_count(self):
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return self.__solution_count
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class BestBoundCallback:
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def __init__(self):
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self.best_bound: float = 0.0
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def new_best_bound(self, bb: float):
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self.best_bound = bb
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class CpModelHelperTest(absltest.TestCase):
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def tearDown(self) -> None:
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super().tearDown()
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sys.stdout.flush()
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def test_variable_domain(self):
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model_string = """
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variables { domain: [ -10, 10 ] }
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variables { domain: [ -5, -5, 3, 6 ] }
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"""
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model = cmh.CpModelProto()
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self.assertTrue(model.parse_text_format(model_string))
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d0 = cmh.CpSatHelper.variable_domain(model.variables[0])
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d1 = cmh.CpSatHelper.variable_domain(model.variables[1])
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self.assertEqual(d0.flattened_intervals(), [-10, 10])
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self.assertEqual(d1.flattened_intervals(), [-5, -5, 3, 6])
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def test_simple_solve(self):
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model_string = """
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variables { domain: -10 domain: 10 }
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variables { domain: -10 domain: 10 }
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variables { domain: -461168601842738790 domain: 461168601842738790 }
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constraints {
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linear {
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vars: 0
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vars: 1
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coeffs: 1
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coeffs: 1
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domain: -9223372036854775808
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domain: 9223372036854775807
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}
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}
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constraints {
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linear {
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vars: 0
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vars: 1
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vars: 2
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coeffs: 1
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coeffs: 2
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coeffs: -1
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domain: 0
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domain: 9223372036854775807
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}
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}
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objective {
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vars: 2
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coeffs: -1
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scaling_factor: -1
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}"""
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model = cmh.CpModelProto()
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self.assertTrue(model.parse_text_format(model_string))
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solve_wrapper = cmh.SolveWrapper()
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response_wrapper = solve_wrapper.solve_and_return_response_wrapper(model)
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self.assertEqual(cmh.OPTIMAL, response_wrapper.status())
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self.assertEqual(30.0, response_wrapper.objective_value())
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def test_simple_solve_with_core(self):
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model_string = """
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variables { domain: -10 domain: 10 }
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variables { domain: -10 domain: 10 }
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variables { domain: -461168601842738790 domain: 461168601842738790 }
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constraints {
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linear {
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vars: 0
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vars: 1
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coeffs: 1
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coeffs: 1
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domain: -9223372036854775808
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domain: 9223372036854775807
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}
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}
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constraints {
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linear {
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vars: 0
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vars: 1
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vars: 2
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coeffs: 1
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coeffs: 2
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coeffs: -1
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domain: 0
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domain: 9223372036854775807
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}
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}
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objective {
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vars: 2
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coeffs: -1
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scaling_factor: -1
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}"""
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model = cmh.CpModelProto()
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self.assertTrue(model.parse_text_format(model_string))
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parameters = cmh.SatParameters()
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parameters.optimize_with_core = True
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solve_wrapper = cmh.SolveWrapper()
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solve_wrapper.set_parameters(parameters)
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response_wrapper = solve_wrapper.solve_and_return_response_wrapper(model)
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self.assertEqual(cmh.OPTIMAL, response_wrapper.status())
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self.assertEqual(30.0, response_wrapper.objective_value())
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def test_simple_solve_with_proto_api(self):
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model = cmh.CpModelProto()
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x = model.variables.add()
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x.domain.extend([-10, 10])
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y = model.variables.add()
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y.domain.extend([-10, 10])
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obj_var = model.variables.add()
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obj_var.domain.extend([-461168601842738790, 461168601842738790])
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ct = model.constraints.add()
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ct.linear.vars.extend([0, 1, 2])
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ct.linear.coeffs.extend([1, 2, -1])
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ct.linear.domain.extend([0, 0])
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model.objective.vars.append(2)
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model.objective.coeffs.append(-1)
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model.objective.scaling_factor = -1
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solve_wrapper = cmh.SolveWrapper()
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response_wrapper = solve_wrapper.solve_and_return_response_wrapper(model)
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self.assertEqual(cmh.OPTIMAL, response_wrapper.status())
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self.assertEqual(30.0, response_wrapper.objective_value())
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self.assertEqual(30.0, response_wrapper.best_objective_bound())
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self.assertRaises(TypeError, response_wrapper.value, None)
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self.assertRaises(TypeError, response_wrapper.float_value, None)
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self.assertRaises(TypeError, response_wrapper.boolean_value, None)
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def test_solution_callback(self):
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model_string = """
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variables { domain: 0 domain: 5 }
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variables { domain: 0 domain: 5 }
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constraints {
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linear { vars: 0 vars: 1 coeffs: 1 coeffs: 1 domain: 6 domain: 6 } }
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"""
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model = cmh.CpModelProto()
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self.assertTrue(model.parse_text_format(model_string))
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solve_wrapper = cmh.SolveWrapper()
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callback = Callback()
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solve_wrapper.add_solution_callback(callback)
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params = cmh.SatParameters()
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params.enumerate_all_solutions = True
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solve_wrapper.set_parameters(params)
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response_wrapper = solve_wrapper.solve_and_return_response_wrapper(model)
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self.assertEqual(5, callback.solution_count())
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self.assertEqual(cmh.OPTIMAL, response_wrapper.status())
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def test_best_bound_callback(self):
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model_string = """
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variables { domain: 0 domain: 1 }
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variables { domain: 0 domain: 1 }
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variables { domain: 0 domain: 1 }
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variables { domain: 0 domain: 1 }
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constraints { bool_or { literals: [0, 1, 2, 3] } }
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objective {
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vars: [0, 1, 2, 3]
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coeffs: [3, 2, 4, 5]
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offset: 0.6
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}
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"""
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model = cmh.CpModelProto()
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self.assertTrue(model.parse_text_format(model_string))
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solve_wrapper = cmh.SolveWrapper()
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best_bound_callback = BestBoundCallback()
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solve_wrapper.add_best_bound_callback(best_bound_callback.new_best_bound)
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params = cmh.SatParameters()
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params.num_workers = 1
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params.linearization_level = 2
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params.log_search_progress = True
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solve_wrapper.set_parameters(params)
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response_wrapper = solve_wrapper.solve_and_return_response_wrapper(model)
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self.assertEqual(2.6, best_bound_callback.best_bound)
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self.assertEqual(cmh.OPTIMAL, response_wrapper.status())
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def test_model_stats(self):
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model_string = """
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variables { domain: -10 domain: 10 }
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variables { domain: -10 domain: 10 }
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variables { domain: -1000 domain: 1000 }
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constraints {
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linear {
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vars: 0
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vars: 1
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coeffs: 1
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coeffs: 1
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domain: -1000
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domain: 1000
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}
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}
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constraints {
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linear {
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vars: 0
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vars: 1
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vars: 2
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coeffs: 1
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coeffs: 2
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coeffs: -1
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domain: 0
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domain: 1000
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}
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}
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objective {
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vars: 2
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coeffs: -1
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scaling_factor: -1
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}
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name: 'testModelStats'
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"""
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model = cmh.CpModelProto()
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self.assertTrue(model.parse_text_format(model_string))
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stats = cmh.CpSatHelper.model_stats(model)
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self.assertTrue(stats)
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def test_int_lin_expr(self):
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model = cmh.CpModelProto()
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x = cmh.IntVar(model).with_name("x")
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self.assertTrue(x.is_integer())
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self.assertIsInstance(x, cmh.IntVar)
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self.assertIsInstance(x, cmh.LinearExpr)
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e1 = x + 2
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self.assertTrue(e1.is_integer())
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self.assertEqual(str(e1), "(x + 2)")
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e2 = 3 + x
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self.assertTrue(e2.is_integer())
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self.assertEqual(str(e2), "(x + 3)")
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y = cmh.IntVar(model).with_name("y")
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e3 = y * 5
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self.assertTrue(e3.is_integer())
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self.assertEqual(str(e3), "(5 * y)")
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e4 = -2 * y
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self.assertTrue(e4.is_integer())
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self.assertEqual(str(e4), "(-2 * y)")
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e5 = x - 1
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self.assertTrue(e5.is_integer())
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self.assertEqual(str(e5), "(x - 1)")
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e6 = x - 2 * y
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self.assertTrue(e6.is_integer())
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self.assertEqual(str(e6), "(x + (-2 * y))")
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z = cmh.IntVar(model).with_name("z")
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z.domain = sorted_interval_list.Domain.from_values([0, 1])
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e7 = -z
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self.assertTrue(e7.is_integer())
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self.assertEqual(str(e7), "(-z)")
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not_z = ~z
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self.assertTrue(not_z.is_integer())
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self.assertEqual(str(not_z), "not(z)")
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self.assertEqual(not_z.index, -3)
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e8 = cmh.LinearExpr.sum([x, y, z])
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self.assertEqual(str(e8), "(x + y + z)")
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e9 = cmh.LinearExpr.sum([x, y, z, 11])
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self.assertEqual(str(e9), "(x + y + z + 11)")
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e10 = cmh.LinearExpr.weighted_sum([x, y, z], [1, 2, 3])
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self.assertEqual(str(e10), "(x + 2 * y + 3 * z)")
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e11 = cmh.LinearExpr.weighted_sum([x, y, z, 5], [1, 2, 3, -1])
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self.assertEqual(str(e11), "(x + 2 * y + 3 * z - 5)")
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e12 = x - y - 2 * z
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self.assertEqual(str(e12), "(x + (-y) + (-2 * z))")
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def test_float_lin_expr(self):
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model = cmh.CpModelProto()
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x = cmh.IntVar(model).with_name("x")
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self.assertTrue(x.is_integer())
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self.assertIsInstance(x, cmh.IntVar)
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self.assertIsInstance(x, cmh.LinearExpr)
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e1 = x + 2.5
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self.assertFalse(e1.is_integer())
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self.assertEqual(str(e1), "(x + 2.5)")
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e2 = 3.1 + x
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self.assertFalse(e2.is_integer())
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self.assertEqual(str(e2), "(x + 3.1)")
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y = cmh.IntVar(model).with_name("y")
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e3 = y * 5.2
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self.assertFalse(e3.is_integer())
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self.assertEqual(str(e3), "(5.2 * y)")
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e4 = -2.25 * y
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self.assertFalse(e4.is_integer())
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self.assertEqual(str(e4), "(-2.25 * y)")
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e5 = x - 1.1
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self.assertFalse(e5.is_integer())
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self.assertEqual(str(e5), "(x - 1.1)")
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e6 = x + 2.4 * y
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self.assertFalse(e6.is_integer())
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self.assertEqual(str(e6), "(x + (2.4 * y))")
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e7 = x - 2.4 * y
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self.assertFalse(e7.is_integer())
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self.assertEqual(str(e7), "(x + (-(2.4 * y)))")
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z = cmh.IntVar(model).with_name("z")
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e8 = cmh.LinearExpr.sum([x, y, z, -2])
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self.assertTrue(e8.is_integer())
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self.assertEqual(str(e8), "(x + y + z - 2)")
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e9 = cmh.LinearExpr.sum([x, y, z, 1.5])
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self.assertFalse(e9.is_integer())
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self.assertEqual(str(e9), "(x + y + z + 1.5)")
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e10 = cmh.LinearExpr.weighted_sum([x, y, z], [1.0, 2.25, 5.5])
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self.assertFalse(e10.is_integer())
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self.assertEqual(str(e10), "(x + 2.25 * y + 5.5 * z)")
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e11 = cmh.LinearExpr.weighted_sum([x, y, z, 1.5], [1.0, 2.25, 5.5, -1])
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self.assertFalse(e11.is_integer())
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self.assertEqual(str(e11), "(x + 2.25 * y + 5.5 * z - 1.5)")
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e12 = (x + 2) * 3.1
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self.assertFalse(e12.is_integer())
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self.assertEqual(str(e12), "(3.1 * (x + 2))")
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class CpModelBuilderTest(absltest.TestCase):
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def test_basic(self):
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model_proto = cmh.CpModelProto()
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# Singular message.
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objective = model_proto.objective
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# Singular int.
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self.assertEqual(objective.offset, 0)
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objective.offset = 123
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self.assertEqual(objective.offset, 123)
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# Set a message.
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new_obj = cmh.CpObjectiveProto()
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new_obj.offset = 456
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model_proto.objective = new_obj
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self.assertEqual(objective.offset, 456)
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# Large int.
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objective.offset = 500000000000
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self.assertEqual(objective.offset, 500000000000)
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# Repeated message.
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my_var = model_proto.variables.add()
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# Singular string.
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self.assertEqual(my_var.name, "")
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my_var.name = "my_var"
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self.assertEqual(my_var.name, "my_var")
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my_var.domain.extend([0, 1])
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domain = list(my_var.domain)
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self.assertLen(domain, 2)
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self.assertEqual(domain[0], 0)
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self.assertEqual(domain[1], 1)
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# Repeated int.
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objective.vars.append(0)
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self.assertLen(objective.vars, 1)
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self.assertEqual(objective.vars[0], 0)
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objective.vars[0] = 42
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self.assertEqual(objective.vars[0], 42)
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# Singular enum
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search_strategy = model_proto.search_strategy.add()
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self.assertEqual(
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search_strategy.variable_selection_strategy,
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cmh.DecisionStrategyProto.CHOOSE_FIRST,
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)
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search_strategy.variable_selection_strategy = (
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cmh.DecisionStrategyProto.CHOOSE_LOWEST_MIN
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)
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self.assertEqual(
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search_strategy.variable_selection_strategy,
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cmh.DecisionStrategyProto.CHOOSE_LOWEST_MIN,
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)
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class SatParametersBuilderTest(absltest.TestCase):
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def test_basic_api(self) -> None:
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params = cmh.SatParameters()
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# Test that we can set and get an integer parameter.
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params.num_workers = 10
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self.assertEqual(params.num_workers, 10)
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# Test that we can set and get an enum parameter.
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self.assertEqual(
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params.clause_cleanup_ordering,
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cmh.SatParameters.ClauseOrdering.CLAUSE_ACTIVITY,
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)
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params.clause_cleanup_ordering = cmh.SatParameters.ClauseOrdering.CLAUSE_LBD
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self.assertEqual(
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params.clause_cleanup_ordering,
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cmh.SatParameters.ClauseOrdering.CLAUSE_LBD,
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)
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# Test that we can set and get a repeated string parameter.
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params.subsolvers.append("no_lp")
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self.assertLen(params.subsolvers, 1)
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self.assertEqual(params.subsolvers[0], "no_lp")
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if __name__ == "__main__":
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absltest.main()
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