feat(ir): actually get toposort working
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0a672e0aea
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1 changed files with 75 additions and 78 deletions
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@ -1,6 +1,5 @@
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use std::{collections::BTreeSet, iter, ops::RangeInclusive};
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use std::{num::NonZeroUsize, ops::RangeInclusive};
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use either::Either;
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use instruction::SocketCount;
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use serde::{Deserialize, Serialize};
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@ -9,7 +8,7 @@ pub mod instruction;
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pub mod semi_human;
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pub type Map<K, V> = std::collections::BTreeMap<K, V>;
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pub type Set<V> = std::collections::BTreeSet<V>;
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pub type Set<T> = std::collections::BTreeSet<T>;
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/// Gives you a super well typed graph IR for a given human-readable repr.
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///
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@ -41,8 +40,8 @@ pub fn from_ron(source: &str) -> ron::error::SpannedResult<GraphIr> {
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/// to come back to an already visited node.
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///
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/// Here, if an edge points from _A_ to _B_ (`A --> B`),
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/// then _A_ is called a **dependency** of _B_,
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/// and _B_ is called a **dependent** of _A_.
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/// then _A_ is called a **dependency** or an **input source** of _B_,
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/// and _B_ is called a **dependent** or an **output target** of _A_.
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///
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/// The DAG also enables another neat operation:
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/// [Topological sorting](https://en.wikipedia.org/wiki/Topological_sorting).
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@ -69,33 +68,8 @@ pub struct GraphIr {
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rev_edges: Map<id::Input, id::Output>,
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}
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// TODO: this impl block, but actually the whole module, screams for tests
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impl GraphIr {
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/// Look "forwards" in the graph to see what other instructions this instruction feeds into.
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///
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/// The output slots represent the top-level iterator,
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/// and each one's connections are emitted one level below.
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///
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/// Just [`Iterator::flatten`] if you are not interested in the slots.
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///
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/// The same caveats as for [`GraphIr::resolve`] apply.
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#[must_use]
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pub fn dependents(
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&self,
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subject: &id::Instruction,
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) -> Option<impl Iterator<Item = impl Iterator<Item = &id::Instruction>> + '_> {
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let (subject, kind) = self.instructions.get_key_value(subject)?;
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let SocketCount { inputs, .. } = kind.socket_count();
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Some((0..inputs).map(|idx| {
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let output = id::Output(socket(subject, idx));
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self.edges
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.get(&output)
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.map_or(Either::Right(iter::empty()), |targets| {
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Either::Left(targets.iter().map(|input| &input.socket().belongs_to))
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})
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}))
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}
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/// Look "backwards" in the graph,
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/// and find out what instructions need to be done before this one.
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/// The input slots are visited in order.
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@ -105,22 +79,41 @@ impl GraphIr {
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///
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/// The same caveats as for [`GraphIr::resolve`] apply.
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#[must_use]
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pub fn dependencies(
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pub fn input_sources(
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&self,
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subject: &id::Instruction,
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) -> Option<impl Iterator<Item = Option<&id::Instruction>> + '_> {
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) -> Option<impl Iterator<Item = Option<&id::Output>> + '_> {
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let (subject, kind) = self.instructions.get_key_value(subject)?;
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let SocketCount { inputs, .. } = kind.socket_count();
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Some((0..inputs).map(|idx| {
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let input = id::Input(socket(subject, idx));
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self.rev_edges
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.get(&input)
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.map(|output| &output.socket().belongs_to)
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self.rev_edges.get(&input)
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}))
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}
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/// Look "forwards" in the graph to see what other instructions this instruction feeds into.
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///
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/// The output slots represent the top-level iterator,
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/// and each one's connections are emitted one level below.
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///
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/// Just [`Iterator::flatten`] if you are not interested in the slots.
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///
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/// The same caveats as for [`GraphIr::resolve`] apply.
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#[must_use]
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pub fn output_targets(
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&self,
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subject: &id::Instruction,
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) -> Option<impl Iterator<Item = Option<&Set<id::Input>>> + '_> {
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let (subject, kind) = self.instructions.get_key_value(subject)?;
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let SocketCount { outputs, .. } = kind.socket_count();
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Some((0..outputs).map(|idx| {
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let output = id::Output(socket(subject, idx));
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self.edges.get(&output)
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}))
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}
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// TODO: this function, but actually the whole module, screams for tests
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/// Returns the instruction corresponding to the given ID.
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/// Returns [`None`] if there is no such instruction in this graph IR.
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///
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@ -133,33 +126,14 @@ impl GraphIr {
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pub fn resolve<'ir>(&'ir self, subject: &id::Instruction) -> Option<Instruction<'ir>> {
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let (id, kind) = self.instructions.get_key_value(subject)?;
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// just try each slot and see if it's connected
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// very crude, but it works for a proof of concept
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let SocketCount { inputs, outputs } = kind.socket_count();
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let socket = |id: &id::Instruction, idx| id::Socket {
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belongs_to: id.clone(),
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// impossible since the length is limited to a u16 already
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#[allow(clippy::cast_possible_truncation)]
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idx: id::SocketIdx(idx as u16),
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};
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let mut inputs_from = vec![None; inputs.into()];
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for (idx, slot) in inputs_from.iter_mut().enumerate() {
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let input = id::Input(socket(id, idx));
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*slot = self.rev_edges.get(&input);
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}
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let mut outputs_to = vec![None; outputs.into()];
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for (idx, slot) in outputs_to.iter_mut().enumerate() {
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let output = id::Output(socket(id, idx));
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*slot = self.edges.get(&output);
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}
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let input_sources = self.input_sources(subject)?.collect();
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let output_targets = self.output_targets(subject)?.collect();
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Some(Instruction {
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id,
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kind,
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inputs_from,
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outputs_to,
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input_sources,
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output_targets,
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})
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}
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@ -187,15 +161,18 @@ impl GraphIr {
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///
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/// Panics if there are any cycles in the IR, as it needs to be a DAG.
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#[must_use]
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// yes, this function could actually return an iterator and be lazy
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// yes, this function could probably return an iterator and be lazy
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// no, not today
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pub fn topological_sort(&self) -> Vec<Instruction> {
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// count how many incoming edges each vertex has
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let nonzero_input_counts: Map<_, usize> =
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let mut nonzero_input_counts: Map<_, NonZeroUsize> =
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self.rev_edges
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.iter()
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.fold(Map::new(), |mut count, (input, _)| {
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*count.entry(input.socket().belongs_to.clone()).or_default() += 1;
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let _ = *count
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.entry(input.socket().belongs_to.clone())
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.and_modify(|count| *count = count.saturating_add(1))
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.or_insert(NonZeroUsize::MIN);
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count
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});
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@ -204,32 +181,52 @@ impl GraphIr {
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let no_inputs: Vec<_> = {
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let nonzero: Set<_> = nonzero_input_counts.keys().collect();
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let all: Set<_> = self.instructions.keys().collect();
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all.difference(&nonzero).copied().collect()
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all.difference(&nonzero).copied().cloned().collect()
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};
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let mut active_queue = no_inputs;
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// then let's find the order!
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let mut order = Vec::new();
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let mut active_queue = no_inputs;
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while let Some(current) = active_queue.pop() {
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// now that this vertex is visited and resolved,
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// make sure all dependents notice that
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for dependent in self
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.dependents(current)
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let dependents = self
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.output_targets(¤t)
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.expect("graph to be consistent")
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.flatten()
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{
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dbg!(dependent);
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.flatten();
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for dependent_input in dependents {
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let dependent = &dependent_input.socket().belongs_to;
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// how many inputs are connected to this dependent without us?
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let count = nonzero_input_counts
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.get_mut(dependent)
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.expect("connected output must refer to non-zero input");
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let new = NonZeroUsize::new(count.get() - 1);
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if let Some(new) = new {
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// aww, still some
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*count = new;
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continue;
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}
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// none, that means this one is free now! let's throw it onto the active queue then
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let (now_active, _) = nonzero_input_counts
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.remove_entry(dependent)
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.expect("connected output must refer to non-zero input");
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active_queue.push(now_active);
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}
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// TODO: check if this instruction is "well-fed", that is, has all the inputs it needs,
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// and if not, panic
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order.push(self.resolve(current).expect("graph to be consistent"));
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order.push(self.resolve(¤t).expect("graph to be consistent"));
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}
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assert!(
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!nonzero_input_counts.is_empty(),
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nonzero_input_counts.is_empty(),
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concat!(
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"topological sort didn't cover all instructions\n",
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"either there are unconnected inputs, or there is a cycle\n",
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@ -250,8 +247,8 @@ pub struct Instruction<'ir> {
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pub kind: &'ir instruction::Kind,
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// can't have these two public since then a user might corrupt their length
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inputs_from: Vec<Option<&'ir id::Output>>,
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outputs_to: Vec<Option<&'ir BTreeSet<id::Input>>>,
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input_sources: Vec<Option<&'ir id::Output>>,
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output_targets: Vec<Option<&'ir Set<id::Input>>>,
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}
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impl<'ir> Instruction<'ir> {
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@ -260,14 +257,14 @@ impl<'ir> Instruction<'ir> {
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/// [`None`] means that this input is unfilled,
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/// and must be filled before the instruction can be ran.
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#[must_use]
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pub fn inputs_from(&self) -> &[Option<&'ir id::Output>] {
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&self.inputs_from
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pub fn input_sources(&self) -> &[Option<&'ir id::Output>] {
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&self.input_sources
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}
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/// To whom outputs are sent. [`None`] means that this output is unused.
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/// To whom outputs are sent.
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#[must_use]
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pub fn outputs_to(&self) -> &[Option<&'ir BTreeSet<id::Input>>] {
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&self.outputs_to
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pub fn output_targets(&self) -> &[Option<&'ir Set<id::Input>>] {
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&self.output_targets
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}
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}
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