rustc_next_trait_solver/solve/eval_ctxt/
canonical.rs

1//! Canonicalization is used to separate some goal from its context,
2//! throwing away unnecessary information in the process.
3//!
4//! This is necessary to cache goals containing inference variables
5//! and placeholders without restricting them to the current `InferCtxt`.
6//!
7//! Canonicalization is fairly involved, for more details see the relevant
8//! section of the [rustc-dev-guide][c].
9//!
10//! [c]: https://rustc-dev-guide.rust-lang.org/solve/canonicalization.html
11
12use std::iter;
13
14use rustc_index::IndexVec;
15use rustc_type_ir::data_structures::HashSet;
16use rustc_type_ir::inherent::*;
17use rustc_type_ir::relate::solver_relating::RelateExt;
18use rustc_type_ir::{
19    self as ty, Canonical, CanonicalVarValues, InferCtxtLike, Interner, TypeFoldable,
20};
21use tracing::{debug, instrument, trace};
22
23use crate::canonicalizer::Canonicalizer;
24use crate::delegate::SolverDelegate;
25use crate::resolve::eager_resolve_vars;
26use crate::solve::eval_ctxt::CurrentGoalKind;
27use crate::solve::{
28    CanonicalInput, CanonicalResponse, Certainty, EvalCtxt, ExternalConstraintsData, Goal,
29    MaybeCause, NestedNormalizationGoals, NoSolution, PredefinedOpaquesData, QueryInput,
30    QueryResult, Response, inspect, response_no_constraints_raw,
31};
32
33trait ResponseT<I: Interner> {
34    fn var_values(&self) -> CanonicalVarValues<I>;
35}
36
37impl<I: Interner> ResponseT<I> for Response<I> {
38    fn var_values(&self) -> CanonicalVarValues<I> {
39        self.var_values
40    }
41}
42
43impl<I: Interner, T> ResponseT<I> for inspect::State<I, T> {
44    fn var_values(&self) -> CanonicalVarValues<I> {
45        self.var_values
46    }
47}
48
49impl<D, I> EvalCtxt<'_, D>
50where
51    D: SolverDelegate<Interner = I>,
52    I: Interner,
53{
54    /// Canonicalizes the goal remembering the original values
55    /// for each bound variable.
56    pub(super) fn canonicalize_goal(
57        &self,
58        goal: Goal<I, I::Predicate>,
59    ) -> (Vec<I::GenericArg>, CanonicalInput<I, I::Predicate>) {
60        // We only care about one entry per `OpaqueTypeKey` here,
61        // so we only canonicalize the lookup table and ignore
62        // duplicate entries.
63        let opaque_types = self.delegate.clone_opaque_types_lookup_table();
64        let (goal, opaque_types) = eager_resolve_vars(self.delegate, (goal, opaque_types));
65
66        let mut orig_values = Default::default();
67        let canonical = Canonicalizer::canonicalize_input(
68            self.delegate,
69            &mut orig_values,
70            QueryInput {
71                goal,
72                predefined_opaques_in_body: self
73                    .cx()
74                    .mk_predefined_opaques_in_body(PredefinedOpaquesData { opaque_types }),
75            },
76        );
77        let query_input = ty::CanonicalQueryInput { canonical, typing_mode: self.typing_mode() };
78        (orig_values, query_input)
79    }
80
81    /// To return the constraints of a canonical query to the caller, we canonicalize:
82    ///
83    /// - `var_values`: a map from bound variables in the canonical goal to
84    ///   the values inferred while solving the instantiated goal.
85    /// - `external_constraints`: additional constraints which aren't expressible
86    ///   using simple unification of inference variables.
87    ///
88    /// This takes the `shallow_certainty` which represents whether we're confident
89    /// that the final result of the current goal only depends on the nested goals.
90    ///
91    /// In case this is `Certainy::Maybe`, there may still be additional nested goals
92    /// or inference constraints required for this candidate to be hold. The candidate
93    /// always requires all already added constraints and nested goals.
94    #[instrument(level = "trace", skip(self), ret)]
95    pub(in crate::solve) fn evaluate_added_goals_and_make_canonical_response(
96        &mut self,
97        shallow_certainty: Certainty,
98    ) -> QueryResult<I> {
99        self.inspect.make_canonical_response(shallow_certainty);
100
101        let goals_certainty = self.try_evaluate_added_goals()?;
102        assert_eq!(
103            self.tainted,
104            Ok(()),
105            "EvalCtxt is tainted -- nested goals may have been dropped in a \
106            previous call to `try_evaluate_added_goals!`"
107        );
108
109        // We only check for leaks from universes which were entered inside
110        // of the query.
111        self.delegate.leak_check(self.max_input_universe).map_err(|NoSolution| {
112            trace!("failed the leak check");
113            NoSolution
114        })?;
115
116        let (certainty, normalization_nested_goals) =
117            match (self.current_goal_kind, shallow_certainty) {
118                // When normalizing, we've replaced the expected term with an unconstrained
119                // inference variable. This means that we dropped information which could
120                // have been important. We handle this by instead returning the nested goals
121                // to the caller, where they are then handled. We only do so if we do not
122                // need to recompute the `NormalizesTo` goal afterwards to avoid repeatedly
123                // uplifting its nested goals. This is the case if the `shallow_certainty` is
124                // `Certainty::Yes`.
125                (CurrentGoalKind::NormalizesTo, Certainty::Yes) => {
126                    let goals = std::mem::take(&mut self.nested_goals);
127                    // As we return all ambiguous nested goals, we can ignore the certainty
128                    // returned by `self.try_evaluate_added_goals()`.
129                    if goals.is_empty() {
130                        assert!(matches!(goals_certainty, Certainty::Yes));
131                    }
132                    (
133                        Certainty::Yes,
134                        NestedNormalizationGoals(
135                            goals.into_iter().map(|(s, g, _)| (s, g)).collect(),
136                        ),
137                    )
138                }
139                _ => {
140                    let certainty = shallow_certainty.and(goals_certainty);
141                    (certainty, NestedNormalizationGoals::empty())
142                }
143            };
144
145        if let Certainty::Maybe(cause @ MaybeCause::Overflow { keep_constraints: false, .. }) =
146            certainty
147        {
148            // If we have overflow, it's probable that we're substituting a type
149            // into itself infinitely and any partial substitutions in the query
150            // response are probably not useful anyways, so just return an empty
151            // query response.
152            //
153            // This may prevent us from potentially useful inference, e.g.
154            // 2 candidates, one ambiguous and one overflow, which both
155            // have the same inference constraints.
156            //
157            // Changing this to retain some constraints in the future
158            // won't be a breaking change, so this is good enough for now.
159            return Ok(self.make_ambiguous_response_no_constraints(cause));
160        }
161
162        let external_constraints =
163            self.compute_external_query_constraints(certainty, normalization_nested_goals);
164        let (var_values, mut external_constraints) =
165            eager_resolve_vars(self.delegate, (self.var_values, external_constraints));
166
167        // Remove any trivial or duplicated region constraints once we've resolved regions
168        let mut unique = HashSet::default();
169        external_constraints.region_constraints.retain(|outlives| {
170            outlives.0.as_region().is_none_or(|re| re != outlives.1) && unique.insert(*outlives)
171        });
172
173        let canonical = Canonicalizer::canonicalize_response(
174            self.delegate,
175            self.max_input_universe,
176            &mut Default::default(),
177            Response {
178                var_values,
179                certainty,
180                external_constraints: self.cx().mk_external_constraints(external_constraints),
181            },
182        );
183
184        // HACK: We bail with overflow if the response would have too many non-region
185        // inference variables. This tends to only happen if we encounter a lot of
186        // ambiguous alias types which get replaced with fresh inference variables
187        // during generalization. This prevents hangs caused by an exponential blowup,
188        // see tests/ui/traits/next-solver/coherence-alias-hang.rs.
189        match self.current_goal_kind {
190            // We don't do so for `NormalizesTo` goals as we erased the expected term and
191            // bailing with overflow here would prevent us from detecting a type-mismatch,
192            // causing a coherence error in diesel, see #131969. We still bail with overflow
193            // when later returning from the parent AliasRelate goal.
194            CurrentGoalKind::NormalizesTo => {}
195            CurrentGoalKind::Misc | CurrentGoalKind::CoinductiveTrait => {
196                let num_non_region_vars = canonical
197                    .variables
198                    .iter()
199                    .filter(|c| !c.is_region() && c.is_existential())
200                    .count();
201                if num_non_region_vars > self.cx().recursion_limit() {
202                    debug!(?num_non_region_vars, "too many inference variables -> overflow");
203                    return Ok(self.make_ambiguous_response_no_constraints(MaybeCause::Overflow {
204                        suggest_increasing_limit: true,
205                        keep_constraints: false,
206                    }));
207                }
208            }
209        }
210
211        Ok(canonical)
212    }
213
214    /// Constructs a totally unconstrained, ambiguous response to a goal.
215    ///
216    /// Take care when using this, since often it's useful to respond with
217    /// ambiguity but return constrained variables to guide inference.
218    pub(in crate::solve) fn make_ambiguous_response_no_constraints(
219        &self,
220        maybe_cause: MaybeCause,
221    ) -> CanonicalResponse<I> {
222        response_no_constraints_raw(
223            self.cx(),
224            self.max_input_universe,
225            self.variables,
226            Certainty::Maybe(maybe_cause),
227        )
228    }
229
230    /// Computes the region constraints and *new* opaque types registered when
231    /// proving a goal.
232    ///
233    /// If an opaque was already constrained before proving this goal, then the
234    /// external constraints do not need to record that opaque, since if it is
235    /// further constrained by inference, that will be passed back in the var
236    /// values.
237    #[instrument(level = "trace", skip(self), ret)]
238    fn compute_external_query_constraints(
239        &self,
240        certainty: Certainty,
241        normalization_nested_goals: NestedNormalizationGoals<I>,
242    ) -> ExternalConstraintsData<I> {
243        // We only return region constraints once the certainty is `Yes`. This
244        // is necessary as we may drop nested goals on ambiguity, which may result
245        // in unconstrained inference variables in the region constraints. It also
246        // prevents us from emitting duplicate region constraints, avoiding some
247        // unnecessary work. This slightly weakens the leak check in case it uses
248        // region constraints from an ambiguous nested goal. This is tested in both
249        // `tests/ui/higher-ranked/leak-check/leak-check-in-selection-5-ambig.rs` and
250        // `tests/ui/higher-ranked/leak-check/leak-check-in-selection-6-ambig-unify.rs`.
251        let region_constraints = if certainty == Certainty::Yes {
252            self.delegate.make_deduplicated_outlives_constraints()
253        } else {
254            Default::default()
255        };
256
257        // We only return *newly defined* opaque types from canonical queries.
258        //
259        // Constraints for any existing opaque types are already tracked by changes
260        // to the `var_values`.
261        let opaque_types = self
262            .delegate
263            .clone_opaque_types_added_since(self.initial_opaque_types_storage_num_entries);
264
265        ExternalConstraintsData { region_constraints, opaque_types, normalization_nested_goals }
266    }
267
268    /// After calling a canonical query, we apply the constraints returned
269    /// by the query using this function.
270    ///
271    /// This happens in three steps:
272    /// - we instantiate the bound variables of the query response
273    /// - we unify the `var_values` of the response with the `original_values`
274    /// - we apply the `external_constraints` returned by the query, returning
275    ///   the `normalization_nested_goals`
276    pub(super) fn instantiate_and_apply_query_response(
277        &mut self,
278        param_env: I::ParamEnv,
279        original_values: &[I::GenericArg],
280        response: CanonicalResponse<I>,
281    ) -> (NestedNormalizationGoals<I>, Certainty) {
282        let instantiation = Self::compute_query_response_instantiation_values(
283            self.delegate,
284            &original_values,
285            &response,
286            self.origin_span,
287        );
288
289        let Response { var_values, external_constraints, certainty } =
290            self.delegate.instantiate_canonical(response, instantiation);
291
292        Self::unify_query_var_values(
293            self.delegate,
294            param_env,
295            &original_values,
296            var_values,
297            self.origin_span,
298        );
299
300        let ExternalConstraintsData {
301            region_constraints,
302            opaque_types,
303            normalization_nested_goals,
304        } = &*external_constraints;
305
306        self.register_region_constraints(region_constraints);
307        self.register_new_opaque_types(opaque_types);
308
309        (normalization_nested_goals.clone(), certainty)
310    }
311
312    /// This returns the canonical variable values to instantiate the bound variables of
313    /// the canonical response. This depends on the `original_values` for the
314    /// bound variables.
315    fn compute_query_response_instantiation_values<T: ResponseT<I>>(
316        delegate: &D,
317        original_values: &[I::GenericArg],
318        response: &Canonical<I, T>,
319        span: I::Span,
320    ) -> CanonicalVarValues<I> {
321        // FIXME: Longterm canonical queries should deal with all placeholders
322        // created inside of the query directly instead of returning them to the
323        // caller.
324        let prev_universe = delegate.universe();
325        let universes_created_in_query = response.max_universe.index();
326        for _ in 0..universes_created_in_query {
327            delegate.create_next_universe();
328        }
329
330        let var_values = response.value.var_values();
331        assert_eq!(original_values.len(), var_values.len());
332
333        // If the query did not make progress with constraining inference variables,
334        // we would normally create a new inference variables for bound existential variables
335        // only then unify this new inference variable with the inference variable from
336        // the input.
337        //
338        // We therefore instantiate the existential variable in the canonical response with the
339        // inference variable of the input right away, which is more performant.
340        let mut opt_values = IndexVec::from_elem_n(None, response.variables.len());
341        for (original_value, result_value) in
342            iter::zip(original_values, var_values.var_values.iter())
343        {
344            match result_value.kind() {
345                ty::GenericArgKind::Type(t) => {
346                    if let ty::Bound(debruijn, b) = t.kind() {
347                        assert_eq!(debruijn, ty::INNERMOST);
348                        opt_values[b.var()] = Some(*original_value);
349                    }
350                }
351                ty::GenericArgKind::Lifetime(r) => {
352                    if let ty::ReBound(debruijn, br) = r.kind() {
353                        assert_eq!(debruijn, ty::INNERMOST);
354                        opt_values[br.var()] = Some(*original_value);
355                    }
356                }
357                ty::GenericArgKind::Const(c) => {
358                    if let ty::ConstKind::Bound(debruijn, bv) = c.kind() {
359                        assert_eq!(debruijn, ty::INNERMOST);
360                        opt_values[bv.var()] = Some(*original_value);
361                    }
362                }
363            }
364        }
365
366        let var_values = delegate.cx().mk_args_from_iter(
367            response.variables.iter().enumerate().map(|(index, var_kind)| {
368                if var_kind.universe() != ty::UniverseIndex::ROOT {
369                    // A variable from inside a binder of the query. While ideally these shouldn't
370                    // exist at all (see the FIXME at the start of this method), we have to deal with
371                    // them for now.
372                    delegate.instantiate_canonical_var_with_infer(var_kind, span, |idx| {
373                        prev_universe + idx.index()
374                    })
375                } else if var_kind.is_existential() {
376                    // As an optimization we sometimes avoid creating a new inference variable here.
377                    //
378                    // All new inference variables we create start out in the current universe of the caller.
379                    // This is conceptually wrong as these inference variables would be able to name
380                    // more placeholders then they should be able to. However the inference variables have
381                    // to "come from somewhere", so by equating them with the original values of the caller
382                    // later on, we pull them down into their correct universe again.
383                    if let Some(v) = opt_values[ty::BoundVar::from_usize(index)] {
384                        v
385                    } else {
386                        delegate
387                            .instantiate_canonical_var_with_infer(var_kind, span, |_| prev_universe)
388                    }
389                } else {
390                    // For placeholders which were already part of the input, we simply map this
391                    // universal bound variable back the placeholder of the input.
392                    original_values[var_kind.expect_placeholder_index()]
393                }
394            }),
395        );
396
397        CanonicalVarValues { var_values }
398    }
399
400    /// Unify the `original_values` with the `var_values` returned by the canonical query..
401    ///
402    /// This assumes that this unification will always succeed. This is the case when
403    /// applying a query response right away. However, calling a canonical query, doing any
404    /// other kind of trait solving, and only then instantiating the result of the query
405    /// can cause the instantiation to fail. This is not supported and we ICE in this case.
406    ///
407    /// We always structurally instantiate aliases. Relating aliases needs to be different
408    /// depending on whether the alias is *rigid* or not. We're only really able to tell
409    /// whether an alias is rigid by using the trait solver. When instantiating a response
410    /// from the solver we assume that the solver correctly handled aliases and therefore
411    /// always relate them structurally here.
412    #[instrument(level = "trace", skip(delegate))]
413    fn unify_query_var_values(
414        delegate: &D,
415        param_env: I::ParamEnv,
416        original_values: &[I::GenericArg],
417        var_values: CanonicalVarValues<I>,
418        span: I::Span,
419    ) {
420        assert_eq!(original_values.len(), var_values.len());
421
422        for (&orig, response) in iter::zip(original_values, var_values.var_values.iter()) {
423            let goals =
424                delegate.eq_structurally_relating_aliases(param_env, orig, response, span).unwrap();
425            assert!(goals.is_empty());
426        }
427    }
428
429    fn register_region_constraints(
430        &mut self,
431        outlives: &[ty::OutlivesPredicate<I, I::GenericArg>],
432    ) {
433        for &ty::OutlivesPredicate(lhs, rhs) in outlives {
434            match lhs.kind() {
435                ty::GenericArgKind::Lifetime(lhs) => self.register_region_outlives(lhs, rhs),
436                ty::GenericArgKind::Type(lhs) => self.register_ty_outlives(lhs, rhs),
437                ty::GenericArgKind::Const(_) => panic!("const outlives: {lhs:?}: {rhs:?}"),
438            }
439        }
440    }
441
442    fn register_new_opaque_types(&mut self, opaque_types: &[(ty::OpaqueTypeKey<I>, I::Ty)]) {
443        for &(key, ty) in opaque_types {
444            let prev = self.delegate.register_hidden_type_in_storage(key, ty, self.origin_span);
445            // We eagerly resolve inference variables when computing the query response.
446            // This can cause previously distinct opaque type keys to now be structurally equal.
447            //
448            // To handle this, we store any duplicate entries in a separate list to check them
449            // at the end of typeck/borrowck. We could alternatively eagerly equate the hidden
450            // types here. However, doing so is difficult as it may result in nested goals and
451            // any errors may make it harder to track the control flow for diagnostics.
452            if let Some(prev) = prev {
453                self.delegate.add_duplicate_opaque_type(key, prev, self.origin_span);
454            }
455        }
456    }
457}
458
459/// Used by proof trees to be able to recompute intermediate actions while
460/// evaluating a goal. The `var_values` not only include the bound variables
461/// of the query input, but also contain all unconstrained inference vars
462/// created while evaluating this goal.
463pub(in crate::solve) fn make_canonical_state<D, T, I>(
464    delegate: &D,
465    var_values: &[I::GenericArg],
466    max_input_universe: ty::UniverseIndex,
467    data: T,
468) -> inspect::CanonicalState<I, T>
469where
470    D: SolverDelegate<Interner = I>,
471    I: Interner,
472    T: TypeFoldable<I>,
473{
474    let var_values = CanonicalVarValues { var_values: delegate.cx().mk_args(var_values) };
475    let state = inspect::State { var_values, data };
476    let state = eager_resolve_vars(delegate, state);
477    Canonicalizer::canonicalize_response(delegate, max_input_universe, &mut vec![], state)
478}
479
480// FIXME: needs to be pub to be accessed by downstream
481// `rustc_trait_selection::solve::inspect::analyse`.
482pub fn instantiate_canonical_state<D, I, T: TypeFoldable<I>>(
483    delegate: &D,
484    span: I::Span,
485    param_env: I::ParamEnv,
486    orig_values: &mut Vec<I::GenericArg>,
487    state: inspect::CanonicalState<I, T>,
488) -> T
489where
490    D: SolverDelegate<Interner = I>,
491    I: Interner,
492{
493    // In case any fresh inference variables have been created between `state`
494    // and the previous instantiation, extend `orig_values` for it.
495    orig_values.extend(
496        state.value.var_values.var_values.as_slice()[orig_values.len()..]
497            .iter()
498            .map(|&arg| delegate.fresh_var_for_kind_with_span(arg, span)),
499    );
500
501    let instantiation =
502        EvalCtxt::compute_query_response_instantiation_values(delegate, orig_values, &state, span);
503
504    let inspect::State { var_values, data } = delegate.instantiate_canonical(state, instantiation);
505
506    EvalCtxt::unify_query_var_values(delegate, param_env, orig_values, var_values, span);
507    data
508}