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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,77 +1,52 @@ | ||
| # Copyright 2020 by B. Knueven, D. Mildebrath, C. Muir, J-P Watson, and D.L. Woodruff | ||
| # This software is distributed under the 3-clause BSD License. | ||
| import mpisppy.cylinders.spoke | ||
| from mpisppy.cylinders.lagrangian_bounder import _LagrangianMixin | ||
|
|
||
| class SubgradientOuterBound(mpisppy.cylinders.spoke.OuterBoundSpoke): | ||
| class SubgradientOuterBound(_LagrangianMixin, mpisppy.cylinders.spoke.OuterBoundSpoke): | ||
|
|
||
| converger_spoke_char = 'G' | ||
|
|
||
| def lagrangian_prep(self): | ||
| verbose = self.opt.options['verbose'] | ||
| # Split up PH_Prep? Prox option is important for APH. | ||
| # Seems like we shouldn't need the Lagrangian stuff, so attach_prox=False | ||
| # Scenarios are created here | ||
| self.opt.PH_Prep(attach_prox=False) | ||
| self.opt._reenable_W() | ||
| self.opt._create_solvers() | ||
|
|
||
| def lagrangian(self): | ||
| verbose = self.opt.options['verbose'] | ||
| # This is sort of a hack, but might help folks: | ||
| if "ipopt" in self.opt.options["solver_name"]: | ||
| print("\n WARNING: An ipopt solver will not give outer bounds\n") | ||
| teeme = False | ||
| if "tee-rank0-solves" in self.opt.options: | ||
| teeme = self.opt.options['tee-rank0-solves'] | ||
|
|
||
| self.opt.solve_loop( | ||
| solver_options=self.opt.current_solver_options, | ||
| dtiming=False, | ||
| gripe=True, | ||
| tee=teeme, | ||
| verbose=verbose | ||
| ) | ||
| ''' DTM (dlw edits): This is where PHBase Iter0 checks for scenario | ||
| probabilities that don't sum to one and infeasibility and | ||
| will send a kill signal if needed. For now we are relying | ||
| on the fact that the OPT thread is solving the same | ||
| models, and hence would detect both of those things on its | ||
| own--the Lagrangian spoke doesn't need to check again. ''' | ||
| return self.opt.Ebound(verbose) | ||
|
|
||
| def main(self): | ||
| # The rho_setter should be attached to the opt object | ||
| rho_setter = None | ||
| if hasattr(self.opt, 'rho_setter'): | ||
| rho_setter = self.opt.rho_setter | ||
| extensions = self.opt.extensions is not None | ||
| verbose = self.opt.options['verbose'] | ||
|
|
||
| self.lagrangian_prep() | ||
|
|
||
| if extensions: | ||
| self.opt.extobject.pre_iter0() | ||
| self.dk_iter = 1 | ||
| self.trivial_bound = self.lagrangian() | ||
| if extensions: | ||
| self.opt.extobject.post_iter0() | ||
|
|
||
| self.bound = self.trivial_bound | ||
| if extensions: | ||
| self.opt.extobject.post_iter0_after_sync() | ||
|
|
||
| self.opt.current_solver_options = self.opt.iterk_solver_options | ||
|
|
||
| # update rho / alpha | ||
| if self.opt.options.get('subgradient_rho_multiplier') is not None: | ||
| rf = self.opt.options['subgradient_rho_multiplier'] | ||
| for scenario in self.opt.local_scenarios.values(): | ||
| for ndn_i in scenario._mpisppy_model.rho: | ||
| scenario._mpisppy_model.rho[ndn_i] *= rf | ||
|
|
||
| self.trivial_bound = self.lagrangian() | ||
|
|
||
| self.opt.current_solver_options = self.opt.iterk_solver_options | ||
|
|
||
| self.bound = self.trivial_bound | ||
|
|
||
| while not self.got_kill_signal(): | ||
| # compute a subgradient step | ||
| self.opt.Compute_Xbar(verbose) | ||
| self.opt.Update_W(verbose) | ||
| if extensions: | ||
| self.opt.extobject.miditer() | ||
| bound = self.lagrangian() | ||
| if extensions: | ||
| self.opt.extobject.enditer() | ||
| if bound is not None: | ||
| self.bound = bound | ||
|
|
||
| def finalize(self): | ||
| self.final_bound = self.bound | ||
| if self.opt.extensions is not None and \ | ||
| hasattr(self.opt.extobject, 'post_everything'): | ||
| self.opt.extobject.post_everything() | ||
| return self.final_bound | ||
| if extensions: | ||
| self.opt.extobject.enditer_after_sync() |