Only use warmstart=true if warm start is available

miplearn/solvers.py

@@ -78,10 +78,14 @@ class LearningSolver:
         for component in self.components.values():
             component.before_solve(self, instance, model)
         
+        is_warm_start_available = False
+        if "warm-start" in self.components.keys():
+            if self.components["warm-start"].is_warm_start_available:
+                is_warm_start_available = True
         if self.is_persistent:
-            solve_results = self.internal_solver.solve(tee=tee, warmstart=True)
+            solve_results = self.internal_solver.solve(tee=tee, warmstart=is_warm_start_available)
         else:
-            solve_results = self.internal_solver.solve(model, tee=tee, warmstart=True)
+            solve_results = self.internal_solver.solve(model, tee=tee, warmstart=is_warm_start_available)
         
         solve_results["Solver"][0]["Nodes"] = self.internal_solver._solver_model.getAttr("NodeCount")
         

miplearn/warmstart.py

@@ -130,6 +130,7 @@ class WarmStartComponent(Component):
         self.y_train = {}
         self.predictors = {}
         self.predictor_prototype = predictor_prototype
+        self.is_warm_start_available = False
     
     def before_solve(self, solver, instance, model):
         # Build x_test
@@ -163,8 +164,11 @@ class WarmStartComponent(Component):
                 else:
                     if ws[i,0] == 1:
                         var[index].value = 0
+                        self.is_warm_start_available = True
                     elif ws[i,1] == 1:
                         var[index].value = 1
+                        self.is_warm_start_available = True
+
 
     def after_solve(self, solver, instance, model):
         y_test = SolutionExtractor().extract([instance], [model])