remove ItemLikeVisitor impl for InherentOverlapChecker
Signed-off-by: Miguel Guarniz <mi9uel9@gmail.com>
This commit is contained in:
Miguel Guarniz
parent
63849b6ecf
commit
7c3c588988
@ -1,8 +1,8 @@
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use rustc_data_structures::fx::{FxHashMap, FxHashSet};
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use rustc_errors::struct_span_err;
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use rustc_hir as hir;
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use rustc_hir::def::DefKind;
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use rustc_hir::def_id::DefId;
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use rustc_hir::itemlikevisit::ItemLikeVisitor;
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use rustc_index::vec::IndexVec;
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use rustc_middle::traits::specialization_graph::OverlapMode;
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use rustc_middle::ty::{self, TyCtxt};
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@ -12,7 +12,10 @@
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use std::collections::hash_map::Entry;
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pub fn crate_inherent_impls_overlap_check(tcx: TyCtxt<'_>, (): ()) {
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tcx.hir().visit_all_item_likes(&mut InherentOverlapChecker { tcx });
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let mut inherent_overlap_checker = InherentOverlapChecker { tcx };
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for id in tcx.hir().items() {
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inherent_overlap_checker.check_item(id);
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}
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}
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struct InherentOverlapChecker<'tcx> {
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@ -121,200 +124,184 @@ fn check_for_overlapping_inherent_impls(
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|| true,
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);
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}
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}
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impl<'tcx> ItemLikeVisitor<'_> for InherentOverlapChecker<'tcx> {
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fn visit_item(&mut self, item: &hir::Item<'_>) {
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match item.kind {
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hir::ItemKind::Enum(..)
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| hir::ItemKind::Struct(..)
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| hir::ItemKind::Trait(..)
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| hir::ItemKind::Union(..) => {
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let impls = self.tcx.inherent_impls(item.def_id);
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fn check_item(&mut self, id: hir::ItemId) {
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let def_kind = self.tcx.hir().def_kind(id.def_id);
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if !matches!(def_kind, DefKind::Enum | DefKind::Struct | DefKind::Trait | DefKind::Union) {
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return;
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}
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// If there is only one inherent impl block,
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// there is nothing to overlap check it with
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if impls.len() <= 1 {
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return;
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let impls = self.tcx.inherent_impls(id.def_id);
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// If there is only one inherent impl block,
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// there is nothing to overlap check it with
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if impls.len() <= 1 {
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return;
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}
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let overlap_mode = OverlapMode::get(self.tcx, id.def_id.to_def_id());
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let impls_items = impls
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.iter()
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.map(|impl_def_id| (impl_def_id, self.tcx.associated_items(*impl_def_id)))
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.collect::<SmallVec<[_; 8]>>();
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// Perform a O(n^2) algorithm for small n,
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// otherwise switch to an allocating algorithm with
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// faster asymptotic runtime.
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const ALLOCATING_ALGO_THRESHOLD: usize = 500;
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if impls.len() < ALLOCATING_ALGO_THRESHOLD {
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for (i, &(&impl1_def_id, impl_items1)) in impls_items.iter().enumerate() {
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for &(&impl2_def_id, impl_items2) in &impls_items[(i + 1)..] {
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if self.impls_have_common_items(impl_items1, impl_items2) {
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self.check_for_overlapping_inherent_impls(
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overlap_mode,
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impl1_def_id,
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impl2_def_id,
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);
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}
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}
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}
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} else {
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// Build a set of connected regions of impl blocks.
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// Two impl blocks are regarded as connected if they share
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// an item with the same unhygienic identifier.
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// After we have assembled the connected regions,
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// run the O(n^2) algorithm on each connected region.
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// This is advantageous to running the algorithm over the
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// entire graph when there are many connected regions.
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let overlap_mode = OverlapMode::get(self.tcx, item.def_id.to_def_id());
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rustc_index::newtype_index! {
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pub struct RegionId {
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ENCODABLE = custom
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}
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}
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struct ConnectedRegion {
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idents: SmallVec<[Symbol; 8]>,
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impl_blocks: FxHashSet<usize>,
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}
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let mut connected_regions: IndexVec<RegionId, _> = Default::default();
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// Reverse map from the Symbol to the connected region id.
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let mut connected_region_ids = FxHashMap::default();
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let impls_items = impls
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.iter()
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.map(|impl_def_id| (impl_def_id, self.tcx.associated_items(*impl_def_id)))
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.collect::<SmallVec<[_; 8]>>();
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// Perform a O(n^2) algorithm for small n,
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// otherwise switch to an allocating algorithm with
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// faster asymptotic runtime.
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const ALLOCATING_ALGO_THRESHOLD: usize = 500;
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if impls.len() < ALLOCATING_ALGO_THRESHOLD {
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for (i, &(&impl1_def_id, impl_items1)) in impls_items.iter().enumerate() {
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for &(&impl2_def_id, impl_items2) in &impls_items[(i + 1)..] {
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if self.impls_have_common_items(impl_items1, impl_items2) {
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self.check_for_overlapping_inherent_impls(
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overlap_mode,
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impl1_def_id,
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impl2_def_id,
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);
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}
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for (i, &(&_impl_def_id, impl_items)) in impls_items.iter().enumerate() {
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if impl_items.len() == 0 {
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continue;
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}
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// First obtain a list of existing connected region ids
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let mut idents_to_add = SmallVec::<[Symbol; 8]>::new();
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let mut ids = impl_items
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.in_definition_order()
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.filter_map(|item| {
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let entry = connected_region_ids.entry(item.name);
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if let Entry::Occupied(e) = &entry {
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Some(*e.get())
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} else {
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idents_to_add.push(item.name);
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None
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}
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})
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.collect::<SmallVec<[RegionId; 8]>>();
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// Sort the id list so that the algorithm is deterministic
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ids.sort_unstable();
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ids.dedup();
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let ids = ids;
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match &ids[..] {
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// Create a new connected region
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[] => {
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let id_to_set = connected_regions.next_index();
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// Update the connected region ids
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for ident in &idents_to_add {
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connected_region_ids.insert(*ident, id_to_set);
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}
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connected_regions.insert(
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id_to_set,
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ConnectedRegion {
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idents: idents_to_add,
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impl_blocks: std::iter::once(i).collect(),
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},
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);
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}
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// Take the only id inside the list
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&[id_to_set] => {
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let region = connected_regions[id_to_set].as_mut().unwrap();
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region.impl_blocks.insert(i);
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region.idents.extend_from_slice(&idents_to_add);
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// Update the connected region ids
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for ident in &idents_to_add {
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connected_region_ids.insert(*ident, id_to_set);
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}
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}
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} else {
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// Build a set of connected regions of impl blocks.
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// Two impl blocks are regarded as connected if they share
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// an item with the same unhygienic identifier.
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// After we have assembled the connected regions,
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// run the O(n^2) algorithm on each connected region.
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// This is advantageous to running the algorithm over the
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// entire graph when there are many connected regions.
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rustc_index::newtype_index! {
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pub struct RegionId {
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ENCODABLE = custom
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// We have multiple connected regions to merge.
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// In the worst case this might add impl blocks
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// one by one and can thus be O(n^2) in the size
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// of the resulting final connected region, but
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// this is no issue as the final step to check
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// for overlaps runs in O(n^2) as well.
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&[id_to_set, ..] => {
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let mut region = connected_regions.remove(id_to_set).unwrap();
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region.impl_blocks.insert(i);
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region.idents.extend_from_slice(&idents_to_add);
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// Update the connected region ids
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for ident in &idents_to_add {
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connected_region_ids.insert(*ident, id_to_set);
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}
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}
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struct ConnectedRegion {
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idents: SmallVec<[Symbol; 8]>,
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impl_blocks: FxHashSet<usize>,
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}
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let mut connected_regions: IndexVec<RegionId, _> = Default::default();
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// Reverse map from the Symbol to the connected region id.
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let mut connected_region_ids = FxHashMap::default();
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for (i, &(&_impl_def_id, impl_items)) in impls_items.iter().enumerate() {
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if impl_items.len() == 0 {
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continue;
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// Remove other regions from ids.
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for &id in ids.iter() {
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if id == id_to_set {
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continue;
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}
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let r = connected_regions.remove(id).unwrap();
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for ident in r.idents.iter() {
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connected_region_ids.insert(*ident, id_to_set);
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}
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region.idents.extend_from_slice(&r.idents);
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region.impl_blocks.extend(r.impl_blocks);
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}
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// First obtain a list of existing connected region ids
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let mut idents_to_add = SmallVec::<[Symbol; 8]>::new();
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let mut ids = impl_items
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.in_definition_order()
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.filter_map(|item| {
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let entry = connected_region_ids.entry(item.name);
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if let Entry::Occupied(e) = &entry {
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Some(*e.get())
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} else {
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idents_to_add.push(item.name);
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None
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}
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})
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.collect::<SmallVec<[RegionId; 8]>>();
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// Sort the id list so that the algorithm is deterministic
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ids.sort_unstable();
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ids.dedup();
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let ids = ids;
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match &ids[..] {
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// Create a new connected region
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[] => {
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let id_to_set = connected_regions.next_index();
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// Update the connected region ids
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for ident in &idents_to_add {
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connected_region_ids.insert(*ident, id_to_set);
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}
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connected_regions.insert(
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id_to_set,
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ConnectedRegion {
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idents: idents_to_add,
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impl_blocks: std::iter::once(i).collect(),
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},
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);
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}
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// Take the only id inside the list
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&[id_to_set] => {
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let region = connected_regions[id_to_set].as_mut().unwrap();
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region.impl_blocks.insert(i);
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region.idents.extend_from_slice(&idents_to_add);
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// Update the connected region ids
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for ident in &idents_to_add {
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connected_region_ids.insert(*ident, id_to_set);
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}
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}
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// We have multiple connected regions to merge.
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// In the worst case this might add impl blocks
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// one by one and can thus be O(n^2) in the size
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// of the resulting final connected region, but
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// this is no issue as the final step to check
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// for overlaps runs in O(n^2) as well.
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&[id_to_set, ..] => {
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let mut region = connected_regions.remove(id_to_set).unwrap();
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region.impl_blocks.insert(i);
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region.idents.extend_from_slice(&idents_to_add);
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// Update the connected region ids
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for ident in &idents_to_add {
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connected_region_ids.insert(*ident, id_to_set);
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}
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// Remove other regions from ids.
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for &id in ids.iter() {
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if id == id_to_set {
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continue;
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}
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let r = connected_regions.remove(id).unwrap();
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for ident in r.idents.iter() {
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connected_region_ids.insert(*ident, id_to_set);
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}
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region.idents.extend_from_slice(&r.idents);
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region.impl_blocks.extend(r.impl_blocks);
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}
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connected_regions.insert(id_to_set, region);
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}
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}
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connected_regions.insert(id_to_set, region);
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}
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}
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}
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debug!(
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"churning through {} components (sum={}, avg={}, var={}, max={})",
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connected_regions.len(),
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impls.len(),
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impls.len() / connected_regions.len(),
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{
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let avg = impls.len() / connected_regions.len();
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let s = connected_regions
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.iter()
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.flatten()
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.map(|r| r.impl_blocks.len() as isize - avg as isize)
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.map(|v| v.abs() as usize)
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.sum::<usize>();
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s / connected_regions.len()
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},
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connected_regions
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.iter()
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.flatten()
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.map(|r| r.impl_blocks.len())
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.max()
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.unwrap()
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);
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// List of connected regions is built. Now, run the overlap check
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// for each pair of impl blocks in the same connected region.
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for region in connected_regions.into_iter().flatten() {
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let mut impl_blocks =
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region.impl_blocks.into_iter().collect::<SmallVec<[usize; 8]>>();
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impl_blocks.sort_unstable();
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for (i, &impl1_items_idx) in impl_blocks.iter().enumerate() {
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let &(&impl1_def_id, impl_items1) = &impls_items[impl1_items_idx];
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for &impl2_items_idx in impl_blocks[(i + 1)..].iter() {
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let &(&impl2_def_id, impl_items2) = &impls_items[impl2_items_idx];
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if self.impls_have_common_items(impl_items1, impl_items2) {
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self.check_for_overlapping_inherent_impls(
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overlap_mode,
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impl1_def_id,
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impl2_def_id,
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);
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}
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}
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debug!(
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"churning through {} components (sum={}, avg={}, var={}, max={})",
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connected_regions.len(),
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impls.len(),
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impls.len() / connected_regions.len(),
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{
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let avg = impls.len() / connected_regions.len();
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let s = connected_regions
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.iter()
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.flatten()
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.map(|r| r.impl_blocks.len() as isize - avg as isize)
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.map(|v| v.abs() as usize)
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.sum::<usize>();
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s / connected_regions.len()
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},
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connected_regions.iter().flatten().map(|r| r.impl_blocks.len()).max().unwrap()
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);
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// List of connected regions is built. Now, run the overlap check
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// for each pair of impl blocks in the same connected region.
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for region in connected_regions.into_iter().flatten() {
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let mut impl_blocks =
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region.impl_blocks.into_iter().collect::<SmallVec<[usize; 8]>>();
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impl_blocks.sort_unstable();
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for (i, &impl1_items_idx) in impl_blocks.iter().enumerate() {
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let &(&impl1_def_id, impl_items1) = &impls_items[impl1_items_idx];
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for &impl2_items_idx in impl_blocks[(i + 1)..].iter() {
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let &(&impl2_def_id, impl_items2) = &impls_items[impl2_items_idx];
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if self.impls_have_common_items(impl_items1, impl_items2) {
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self.check_for_overlapping_inherent_impls(
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overlap_mode,
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impl1_def_id,
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impl2_def_id,
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);
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}
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}
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}
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}
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_ => {}
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}
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}
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fn visit_trait_item(&mut self, _trait_item: &hir::TraitItem<'_>) {}
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fn visit_impl_item(&mut self, _impl_item: &hir::ImplItem<'_>) {}
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fn visit_foreign_item(&mut self, _foreign_item: &hir::ForeignItem<'_>) {}
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}
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