forked from rust-lang/rust
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathsearch_graph.rs
121 lines (107 loc) · 4.21 KB
/
search_graph.rs
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
use std::convert::Infallible;
use std::marker::PhantomData;
use rustc_type_ir::search_graph::{self, PathKind};
use rustc_type_ir::solve::{CanonicalInput, Certainty, NoSolution, QueryResult};
use rustc_type_ir::{Interner, TypingMode};
use super::inspect::ProofTreeBuilder;
use super::{FIXPOINT_STEP_LIMIT, has_no_inference_or_external_constraints};
use crate::delegate::SolverDelegate;
/// This type is never constructed. We only use it to implement `search_graph::Delegate`
/// for all types which impl `SolverDelegate` and doing it directly fails in coherence.
pub(super) struct SearchGraphDelegate<D: SolverDelegate> {
_marker: PhantomData<D>,
}
pub(super) type SearchGraph<D> = search_graph::SearchGraph<SearchGraphDelegate<D>>;
impl<D, I> search_graph::Delegate for SearchGraphDelegate<D>
where
D: SolverDelegate<Interner = I>,
I: Interner,
{
type Cx = D::Interner;
const ENABLE_PROVISIONAL_CACHE: bool = true;
type ValidationScope = Infallible;
fn enter_validation_scope(
_cx: Self::Cx,
_input: CanonicalInput<I>,
) -> Option<Self::ValidationScope> {
None
}
const FIXPOINT_STEP_LIMIT: usize = FIXPOINT_STEP_LIMIT;
type ProofTreeBuilder = ProofTreeBuilder<D>;
fn inspect_is_noop(inspect: &mut Self::ProofTreeBuilder) -> bool {
inspect.is_noop()
}
const DIVIDE_AVAILABLE_DEPTH_ON_OVERFLOW: usize = 4;
fn initial_provisional_result(
cx: I,
kind: PathKind,
input: CanonicalInput<I>,
) -> QueryResult<I> {
match kind {
PathKind::Coinductive => response_no_constraints(cx, input, Certainty::Yes),
PathKind::Unknown => response_no_constraints(cx, input, Certainty::overflow(false)),
// Even though we know these cycles to be unproductive, we still return
// overflow during coherence. This is both as we are not 100% confident in
// the implementation yet and any incorrect errors would be unsound there.
// The affected cases are also fairly artificial and not necessarily desirable
// so keeping this as ambiguity is fine for now.
//
// See `tests/ui/traits/next-solver/cycles/unproductive-in-coherence.rs` for an
// example where this would matter. We likely should change these cycles to `NoSolution`
// even in coherence once this is a bit more settled.
PathKind::Inductive => match input.typing_mode {
TypingMode::Coherence => {
response_no_constraints(cx, input, Certainty::overflow(false))
}
TypingMode::Analysis { .. }
| TypingMode::PostBorrowckAnalysis { .. }
| TypingMode::PostAnalysis => Err(NoSolution),
},
}
}
fn is_initial_provisional_result(
cx: Self::Cx,
kind: PathKind,
input: CanonicalInput<I>,
result: QueryResult<I>,
) -> bool {
Self::initial_provisional_result(cx, kind, input) == result
}
fn on_stack_overflow(
cx: I,
inspect: &mut ProofTreeBuilder<D>,
input: CanonicalInput<I>,
) -> QueryResult<I> {
inspect.canonical_goal_evaluation_overflow();
response_no_constraints(cx, input, Certainty::overflow(true))
}
fn on_fixpoint_overflow(cx: I, input: CanonicalInput<I>) -> QueryResult<I> {
response_no_constraints(cx, input, Certainty::overflow(false))
}
fn is_ambiguous_result(result: QueryResult<I>) -> bool {
result.is_ok_and(|response| {
has_no_inference_or_external_constraints(response)
&& matches!(response.value.certainty, Certainty::Maybe(_))
})
}
fn propagate_ambiguity(
cx: I,
for_input: CanonicalInput<I>,
from_result: QueryResult<I>,
) -> QueryResult<I> {
let certainty = from_result.unwrap().value.certainty;
response_no_constraints(cx, for_input, certainty)
}
}
fn response_no_constraints<I: Interner>(
cx: I,
input: CanonicalInput<I>,
certainty: Certainty,
) -> QueryResult<I> {
Ok(super::response_no_constraints_raw(
cx,
input.canonical.max_universe,
input.canonical.variables,
certainty,
))
}