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feat(ir): actually get toposort working

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MultisampledNight 2024-01-19 02:59:15 +01:00
parent 4fd35736d5
commit fa2893bc77
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1 changed files with 75 additions and 78 deletions
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153
crates/ir/src/lib.rs
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@ -1,6 +1,5 @@
use std::{collections::BTreeSet, iter, ops::RangeInclusive};
use std::{num::NonZeroUsize, ops::RangeInclusive};
use either::Either;
use instruction::SocketCount;
use serde::{Deserialize, Serialize};
@ -9,7 +8,7 @@ pub mod instruction;
pub mod semi_human;
pub type Map<K, V> = std::collections::BTreeMap<K, V>;
pub type Set<V> = std::collections::BTreeSet<V>;
pub type Set<T> = std::collections::BTreeSet<T>;
/// Gives you a super well typed graph IR for a given human-readable repr.
///
@ -41,8 +40,8 @@ pub fn from_ron(source: &str) -> ron::error::SpannedResult<GraphIr> {
/// to come back to an already visited node.
///
/// Here, if an edge points from _A_ to _B_ (`A --> B`),
/// then _A_ is called a **dependency** of _B_,
/// and _B_ is called a **dependent** of _A_.
/// then _A_ is called a **dependency** or an **input source** of _B_,
/// and _B_ is called a **dependent** or an **output target** of _A_.
///
/// The DAG also enables another neat operation:
/// [Topological sorting](https://en.wikipedia.org/wiki/Topological_sorting).
@ -69,33 +68,8 @@ pub struct GraphIr {
rev_edges: Map<id::Input, id::Output>,
}
// TODO: this impl block, but actually the whole module, screams for tests
impl GraphIr {
/// Look "forwards" in the graph to see what other instructions this instruction feeds into.
///
/// The output slots represent the top-level iterator,
/// and each one's connections are emitted one level below.
///
/// Just [`Iterator::flatten`] if you are not interested in the slots.
///
/// The same caveats as for [`GraphIr::resolve`] apply.
#[must_use]
pub fn dependents(
&self,
subject: &id::Instruction,
) -> Option<impl Iterator<Item = impl Iterator<Item = &id::Instruction>> + '_> {
let (subject, kind) = self.instructions.get_key_value(subject)?;
let SocketCount { inputs, .. } = kind.socket_count();
Some((0..inputs).map(|idx| {
let output = id::Output(socket(subject, idx));
self.edges
.get(&output)
.map_or(Either::Right(iter::empty()), |targets| {
Either::Left(targets.iter().map(|input| &input.socket().belongs_to))
})
}))
}
/// Look "backwards" in the graph,
/// and find out what instructions need to be done before this one.
/// The input slots are visited in order.
@ -105,22 +79,41 @@ impl GraphIr {
///
/// The same caveats as for [`GraphIr::resolve`] apply.
#[must_use]
pub fn dependencies(
pub fn input_sources(
&self,
subject: &id::Instruction,
) -> Option<impl Iterator<Item = Option<&id::Instruction>> + '_> {
) -> Option<impl Iterator<Item = Option<&id::Output>> + '_> {
let (subject, kind) = self.instructions.get_key_value(subject)?;
let SocketCount { inputs, .. } = kind.socket_count();
Some((0..inputs).map(|idx| {
let input = id::Input(socket(subject, idx));
self.rev_edges
.get(&input)
.map(|output| &output.socket().belongs_to)
self.rev_edges.get(&input)
}))
}
/// Look "forwards" in the graph to see what other instructions this instruction feeds into.
///
/// The output slots represent the top-level iterator,
/// and each one's connections are emitted one level below.
///
/// Just [`Iterator::flatten`] if you are not interested in the slots.
///
/// The same caveats as for [`GraphIr::resolve`] apply.
#[must_use]
pub fn output_targets(
&self,
subject: &id::Instruction,
) -> Option<impl Iterator<Item = Option<&Set<id::Input>>> + '_> {
let (subject, kind) = self.instructions.get_key_value(subject)?;
let SocketCount { outputs, .. } = kind.socket_count();
Some((0..outputs).map(|idx| {
let output = id::Output(socket(subject, idx));
self.edges.get(&output)
}))
}
// TODO: this function, but actually the whole module, screams for tests
/// Returns the instruction corresponding to the given ID.
/// Returns [`None`] if there is no such instruction in this graph IR.
///
@ -133,33 +126,14 @@ impl GraphIr {
pub fn resolve<'ir>(&'ir self, subject: &id::Instruction) -> Option<Instruction<'ir>> {
let (id, kind) = self.instructions.get_key_value(subject)?;
// just try each slot and see if it's connected
// very crude, but it works for a proof of concept
let SocketCount { inputs, outputs } = kind.socket_count();
let socket = |id: &id::Instruction, idx| id::Socket {
belongs_to: id.clone(),
// impossible since the length is limited to a u16 already
#[allow(clippy::cast_possible_truncation)]
idx: id::SocketIdx(idx as u16),
};
let mut inputs_from = vec![None; inputs.into()];
for (idx, slot) in inputs_from.iter_mut().enumerate() {
let input = id::Input(socket(id, idx));
*slot = self.rev_edges.get(&input);
}
let mut outputs_to = vec![None; outputs.into()];
for (idx, slot) in outputs_to.iter_mut().enumerate() {
let output = id::Output(socket(id, idx));
*slot = self.edges.get(&output);
}
let input_sources = self.input_sources(subject)?.collect();
let output_targets = self.output_targets(subject)?.collect();
Some(Instruction {
id,
kind,
inputs_from,
outputs_to,
input_sources,
output_targets,
})
}
@ -187,15 +161,18 @@ impl GraphIr {
///
/// Panics if there are any cycles in the IR, as it needs to be a DAG.
#[must_use]
// yes, this function could actually return an iterator and be lazy
// yes, this function could probably return an iterator and be lazy
// no, not today
pub fn topological_sort(&self) -> Vec<Instruction> {
// count how many incoming edges each vertex has
let nonzero_input_counts: Map<_, usize> =
let mut nonzero_input_counts: Map<_, NonZeroUsize> =
self.rev_edges
.iter()
.fold(Map::new(), |mut count, (input, _)| {
*count.entry(input.socket().belongs_to.clone()).or_default() += 1;
let _ = *count
.entry(input.socket().belongs_to.clone())
.and_modify(|count| *count = count.saturating_add(1))
.or_insert(NonZeroUsize::MIN);
count
});
@ -204,32 +181,52 @@ impl GraphIr {
let no_inputs: Vec<_> = {
let nonzero: Set<_> = nonzero_input_counts.keys().collect();
let all: Set<_> = self.instructions.keys().collect();
all.difference(&nonzero).copied().collect()
all.difference(&nonzero).copied().cloned().collect()
};
let mut active_queue = no_inputs;
// then let's find the order!
let mut order = Vec::new();
let mut active_queue = no_inputs;
while let Some(current) = active_queue.pop() {
// now that this vertex is visited and resolved,
// make sure all dependents notice that
for dependent in self
.dependents(current)
let dependents = self
.output_targets(&current)
.expect("graph to be consistent")
.flatten()
{
dbg!(dependent);
.flatten();
for dependent_input in dependents {
let dependent = &dependent_input.socket().belongs_to;
// how many inputs are connected to this dependent without us?
let count = nonzero_input_counts
.get_mut(dependent)
.expect("connected output must refer to non-zero input");
let new = NonZeroUsize::new(count.get() - 1);
if let Some(new) = new {
// aww, still some
*count = new;
continue;
}
// none, that means this one is free now! let's throw it onto the active queue then
let (now_active, _) = nonzero_input_counts
.remove_entry(dependent)
.expect("connected output must refer to non-zero input");
active_queue.push(now_active);
}
// TODO: check if this instruction is "well-fed", that is, has all the inputs it needs,
// and if not, panic
order.push(self.resolve(current).expect("graph to be consistent"));
order.push(self.resolve(&current).expect("graph to be consistent"));
}
assert!(
!nonzero_input_counts.is_empty(),
nonzero_input_counts.is_empty(),
concat!(
"topological sort didn't cover all instructions\n",
"either there are unconnected inputs, or there is a cycle\n",
@ -250,8 +247,8 @@ pub struct Instruction<'ir> {
pub kind: &'ir instruction::Kind,
// can't have these two public since then a user might corrupt their length
inputs_from: Vec<Option<&'ir id::Output>>,
outputs_to: Vec<Option<&'ir BTreeSet<id::Input>>>,
input_sources: Vec<Option<&'ir id::Output>>,
output_targets: Vec<Option<&'ir Set<id::Input>>>,
}
impl<'ir> Instruction<'ir> {
@ -260,14 +257,14 @@ impl<'ir> Instruction<'ir> {
/// [`None`] means that this input is unfilled,
/// and must be filled before the instruction can be ran.
#[must_use]
pub fn inputs_from(&self) -> &[Option<&'ir id::Output>] {
&self.inputs_from
pub fn input_sources(&self) -> &[Option<&'ir id::Output>] {
&self.input_sources
}
/// To whom outputs are sent. [`None`] means that this output is unused.
/// To whom outputs are sent.
#[must_use]
pub fn outputs_to(&self) -> &[Option<&'ir BTreeSet<id::Input>>] {
&self.outputs_to
pub fn output_targets(&self) -> &[Option<&'ir Set<id::Input>>] {
&self.output_targets
}
}