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opt_solver: clarify model member names (#10042)
Small readability refactor in `opt_solver`, no behavioral change.
## Rename
- `m_models` → `m_objective_models`
- `m_last_model` → `m_model`
## Rationale
`m_models` is the per-objective vector of witnessing models, indexed by
the objective index `i` exactly like `m_objective_vars`,
`m_objective_values`, and `m_objective_terms`. It was the only member of
that parallel family not following the `m_objective_*` naming, so
`m_objective_models` makes the intent self-documenting.
`m_last_model` is the single, transient model most recently obtained
from the context and handed back to callers via `get_model_core`.
Renaming it to `m_model` reads more naturally, and the two now-distinct
names (`m_model` vs `m_objective_models`) avoid the previous one-letter
`m_model`/`m_models` clash hazard.
Both are private members of `opt_solver`, so the change is fully
self-contained within `opt_solver.{h,cpp}`. A stale TRACE label ("last
model") was updated to "current model" to match.
## Testing
- Builds clean (CMake/Ninja, Release).
- `test-z3 /a`: 92 passed, 0 failed.
- Spot-checked optimization behavior (single-objective minimize with
large `distinct`, box mode) — unchanged.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
This commit is contained in:
Lev Nachmanson
GitHub
parent
fdc32d0e60
commit
557a0cadab
2 changed files with 34 additions and 34 deletions
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@ -81,7 +81,7 @@ namespace opt {
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}
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void opt_solver::assert_expr_core(expr * t) {
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m_last_model = nullptr;
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m_model = nullptr;
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if (has_quantifiers(t)) {
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m_params.m_relevancy_lvl = 2;
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}
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@ -178,7 +178,7 @@ namespace opt {
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verbose_stream().flush(););
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}
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lbool r;
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m_last_model = nullptr;
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m_model = nullptr;
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if (m_first && num_assumptions == 0 && m_context.get_scope_level() == 0) {
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r = m_context.setup_and_check();
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}
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@ -187,9 +187,9 @@ namespace opt {
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}
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r = adjust_result(r);
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if (r == l_true) {
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m_context.get_model(m_last_model);
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if (m_models.size() == 1)
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m_models.set(0, m_last_model.get());
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m_context.get_model(m_model);
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if (m_objective_models.size() == 1)
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m_objective_models.set(0, m_model.get());
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}
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m_first = false;
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if (dump_benchmarks()) {
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@ -232,15 +232,15 @@ namespace opt {
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// Save results before popping
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inf_eps val = m_objective_values[i];
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model_ref mdl;
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if (m_models[i])
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mdl = m_models[i];
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if (m_objective_models[i])
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mdl = m_objective_models[i];
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m_context.pop(1);
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// Restore the computed values after pop
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m_objective_values[i] = val;
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if (mdl)
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m_models.set(i, mdl.get());
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m_objective_models.set(i, mdl.get());
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// The baseline model may witness a greater value than the LP
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// optimizer returned, e.g. for non-linear objectives like mod
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@ -260,8 +260,8 @@ namespace opt {
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expr_ref obj_val = (*baseline_model)(m_objective_terms.get(i));
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if (a.is_numeral(obj_val, r) && inf_eps(r) > m_objective_values[i]) {
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m_objective_values[i] = inf_eps(r);
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if (!m_models[i])
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m_models.set(i, baseline_model.get());
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if (!m_objective_models[i])
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m_objective_models.set(i, baseline_model.get());
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expr* obj = m_objective_terms.get(i);
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if (a.is_int(obj))
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blocker = a.mk_ge(obj, a.mk_numeral(r + 1, true));
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@ -301,7 +301,7 @@ namespace opt {
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bool opt_solver::maximize_objective(unsigned i, expr_ref& blocker) {
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smt::theory_var v = m_objective_vars[i];
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bool has_shared = false;
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m_last_model = nullptr;
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m_model = nullptr;
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blocker = nullptr;
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//
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// compute an optimization hint.
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@ -310,13 +310,13 @@ namespace opt {
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// relative to other theories.
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//
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inf_eps val = get_optimizer().maximize(v, blocker, has_shared);
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m_context.get_model(m_last_model);
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m_context.get_model(m_model);
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inf_eps val2;
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has_shared = true;
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TRACE(opt, tout << (has_shared?"has shared":"non-shared") << " " << val << " " << blocker << "\n";
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if (m_last_model) tout << *m_last_model << "\n";);
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if (!m_models[i])
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m_models.set(i, m_last_model.get());
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if (m_model) tout << *m_model << "\n";);
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if (!m_objective_models[i])
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m_objective_models.set(i, m_model.get());
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TRACE(opt, tout << "maximize " << i << " " << val << " " << m_objective_values[i] << " " << blocker << "\n";);
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//
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@ -334,7 +334,7 @@ namespace opt {
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// an actual model in update_objective().
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//
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if (!m_last_model) {
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if (!m_model) {
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// Without a model there is nothing to validate 'val' against; keep
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// the previous behavior of adopting the (possibly infinite) hint.
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if (val > m_objective_values[i])
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@ -348,7 +348,7 @@ namespace opt {
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//
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auto update_objective = [&]() {
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rational r;
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expr_ref value = (*m_last_model)(m_objective_terms.get(i));
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expr_ref value = (*m_model)(m_objective_terms.get(i));
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if (arith_util(m).is_numeral(value, r) && r > m_objective_values[i])
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m_objective_values[i] = inf_eps(r);
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};
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@ -369,12 +369,12 @@ namespace opt {
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}
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else if (m_context.get_context().update_model(has_shared)) {
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TRACE(opt, tout << "updated\n";);
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m_last_model = nullptr;
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m_context.get_model(m_last_model);
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if (!m_last_model)
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m_model = nullptr;
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m_context.get_model(m_model);
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if (!m_model)
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return false;
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else if (!has_shared || val == current_objective_value(i))
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m_models.set(i, m_last_model.get());
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m_objective_models.set(i, m_model.get());
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else if (!check_bound())
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return false;
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}
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@ -385,8 +385,8 @@ namespace opt {
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tout << "objective: " << mk_pp(m_objective_terms.get(i), m) << "\n";
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tout << "maximal value: " << val << "\n";
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tout << "new condition: " << blocker << "\n";
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if (m_models[i]) model_smt2_pp(tout << "update model:\n", m, *m_models[i], 0);
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if (m_last_model) model_smt2_pp(tout << "last model:\n", m, *m_last_model, 0);
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if (m_objective_models[i]) model_smt2_pp(tout << "update model:\n", m, *m_objective_models[i], 0);
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if (m_model) model_smt2_pp(tout << "current model:\n", m, *m_model, 0);
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});
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return true;
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}
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@ -398,8 +398,8 @@ namespace opt {
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lbool is_sat = m_context.check(0, nullptr);
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is_sat = adjust_result(is_sat);
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if (is_sat == l_true) {
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m_context.get_model(m_last_model);
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m_models.set(i, m_last_model.get());
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m_context.get_model(m_model);
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m_objective_models.set(i, m_model.get());
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}
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pop_core(1);
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return is_sat == l_true;
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@ -422,13 +422,13 @@ namespace opt {
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}
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void opt_solver::get_model_core(model_ref & m) {
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if (m_last_model.get()) {
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m = m_last_model.get();
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if (m_model.get()) {
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m = m_model.get();
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return;
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}
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for (unsigned i = m_models.size(); i-- > 0; ) {
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auto* mdl = m_models[i];
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for (unsigned i = m_objective_models.size(); i-- > 0; ) {
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auto* mdl = m_objective_models[i];
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if (mdl) {
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TRACE(opt, tout << "get " << i << "\n" << *mdl << "\n";);
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m = mdl;
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@ -436,7 +436,7 @@ namespace opt {
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}
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}
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TRACE(opt, tout << "get last\n";);
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m = m_last_model.get();
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m = m_model.get();
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}
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proof * opt_solver::get_proof_core() {
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@ -478,7 +478,7 @@ namespace opt {
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m_objective_vars.push_back(v);
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m_objective_values.push_back(inf_eps(rational::minus_one(), inf_rational()));
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m_objective_terms.push_back(term);
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m_models.push_back(nullptr);
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m_objective_models.push_back(nullptr);
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return v;
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}
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@ -73,10 +73,10 @@ namespace opt {
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generic_model_converter& m_fm;
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progress_callback * m_callback;
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symbol m_logic;
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model_ref m_last_model;
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model_ref m_model;
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svector<smt::theory_var> m_objective_vars;
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vector<inf_eps> m_objective_values;
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sref_vector<model> m_models;
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sref_vector<model> m_objective_models;
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expr_ref_vector m_objective_terms;
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bool m_dump_benchmarks;
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static unsigned m_dump_count;
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@ -171,7 +171,7 @@ namespace opt {
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void update_from_baseline_model(unsigned i, model_ref& baseline_model, expr_ref& blocker);
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inf_eps const & saved_objective_value(unsigned obj_index);
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inf_eps current_objective_value(unsigned obj_index);
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model* get_model_idx(unsigned obj_index) { return m_models[obj_index]; }
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model* get_model_idx(unsigned obj_index) { return m_objective_models[obj_index]; }
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bool was_unknown() const { return m_was_unknown; }
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