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