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fix: fix kernel bfs resolver issue

This commit is contained in:
2026-06-29 16:56:13 +08:00
parent a62ed05d50
commit 4af8dd97a2
5 changed files with 201 additions and 349 deletions

View File

@@ -186,8 +186,18 @@ impl Dataset {
Ok(())
}
/// The number of available standard values.
pub fn len(&self) -> usize {
self.items.len()
}
/// Get the available standard value by index.
pub fn get(&self, index: usize) -> Option<f64> {
self.items.get(index).map(|i| i.value)
}
/// Get the available standard values as an iterator of `f64`.
pub fn values(&self) -> impl Iterator<Item = f64> {
pub fn values(&self) -> impl Iterator<Item = f64> + Clone {
self.items.iter().map(|i| i.value)
}
}

View File

@@ -2,13 +2,3 @@ pub mod common;
pub mod dataset;
pub mod query;
pub mod resolver;
pub use common::{
Circuit, CircuitDeviceScale, CircuitCalculator, DeviceKind, JointKind, LcrConnError, SubCircuit,
};
pub use dataset::{
from_human_readable_value, get_human_readable_value_scale, to_human_readable_value, Dataset,
DatasetCollection, DatasetItem, UnitScale,
};
pub use query::{Request, Response, ResponseItem, ResponsePriority, MAX_RESPONSE_CNT};
pub use resolver::{BfsResolver, LutResolver, Resolver};

View File

@@ -0,0 +1,26 @@
pub mod bfs;
pub mod lut;
use crate::query::{Request, Response};
use thiserror::Error as TeError;
/// Aggregated error occurs in every resolvers.
#[derive(Debug, TeError)]
pub enum ResolverError {
#[error("{0}")]
BfsResolver(#[from] bfs::BfsResolverError),
#[error("a")]
LutResolver,
}
/// Abstract base trait for all resolvers.
pub trait Resolver {
/// Resolve the request and return the response.
///
/// `request` is the request to resolve.
/// The response containing the best matching circuits.
fn resolve(&self, request: &Request) -> Result<Response, ResolverError>;
}
pub use bfs::BfsResolver;
pub use lut::LutResolver;

View File

@@ -1,251 +1,30 @@
use super::{Resolver, ResolverError};
use crate::common::{
Circuit, CircuitCalculator, CircuitCalculatorError, CircuitError, DeviceKind, JointKind,
};
use crate::dataset::{Dataset, DatasetCollection};
use crate::query::{Request, Response, ResponseError};
use itertools::Itertools;
use ordered_float::OrderedFloat;
use std::cmp::Ordering;
use std::collections::BinaryHeap;
use std::iter::FusedIterator;
use strum::IntoEnumIterator;
use thiserror::Error as TeError;
use super::Resolver;
use crate::common::{Circuit, CircuitCalculator, DeviceKind, JointKind, LcrConnError};
use crate::dataset::{Dataset, DatasetCollection, DatasetItem};
use crate::query::{Request, Response};
// ============================================================================
// Lazy iterator structs for circuit generation
// ============================================================================
// YYC MARK:
// Some circuit are equivalent in topology.
// If we deduplicate these equaivalent circuit in building result,
// there are too complex works.
// So we should deduplicated these equivalent circuit at the beginning,
// i.e. when generating them.
// So following iterator structs are taking this job.
/// Iterator over all possible one-device circuits without repeating equivalent topology.
pub struct OneDeviceCircuitIter<'a> {
items: &'a [DatasetItem],
pos: usize,
/// Error occurs BFS resolver.
#[derive(Debug, TeError)]
pub enum BfsResolverError {
#[error("failed to build circuit: {0}")]
Circuit(#[from] CircuitError),
#[error("failed on computing circuit properties: {0}")]
CircuitCalculator(#[from] CircuitCalculatorError),
#[error("the size of binary heap {0} is invalid")]
BadBinHeapSize(usize),
#[error("fail to build response: {0}")]
Response(#[from] ResponseError),
}
impl<'a> OneDeviceCircuitIter<'a> {
pub fn new(items: &'a [DatasetItem]) -> Self {
Self { items, pos: 0 }
}
}
impl Iterator for OneDeviceCircuitIter<'_> {
type Item = Circuit;
fn next(&mut self) -> Option<Self::Item> {
if self.pos < self.items.len() {
// Every single device is unique so we directly output them.
// This feature is insured by dataset itself.
let circuit = Circuit::from_one_device(self.items[self.pos].value);
self.pos += 1;
Some(circuit)
} else {
None
}
}
}
impl FusedIterator for OneDeviceCircuitIter<'_> {}
/// Iterator over all possible two-device circuits without repeating equivalent topology.
pub struct TwoDeviceCircuitIter<'a> {
items: &'a [DatasetItem],
i: usize,
j: usize,
joint_idx: usize,
}
impl<'a> TwoDeviceCircuitIter<'a> {
pub fn new(items: &'a [DatasetItem]) -> Self {
Self {
items,
i: 0,
j: 0,
joint_idx: 0,
}
}
}
impl Iterator for TwoDeviceCircuitIter<'_> {
type Item = Circuit;
fn next(&mut self) -> Option<Self::Item> {
let n = self.items.len();
if n == 0 {
return None;
}
loop {
if self.joint_idx < JointKind::ALL.len() {
let jk = JointKind::ALL[self.joint_idx];
self.joint_idx += 1;
// The two devices in this circuit is always swapable,
// so we iterate them without repeating.
return Some(Circuit::from_two_devices(
self.items[self.i].value,
self.items[self.j].value,
jk,
));
}
// Advance to next combination
self.joint_idx = 0;
self.j += 1;
if self.j >= n {
self.i += 1;
self.j = self.i;
if self.i >= n {
return None;
}
}
}
}
}
impl FusedIterator for TwoDeviceCircuitIter<'_> {}
/// Iterator over three-device circuits where both joints share the same type.
///
/// In this case, all 3 devices are swapable and are iterated without repeating.
pub struct ThreeDeviceSameJointIter<'a> {
items: &'a [DatasetItem],
i: usize,
j: usize,
k: usize,
joint_idx: usize,
}
impl<'a> ThreeDeviceSameJointIter<'a> {
pub fn new(items: &'a [DatasetItem]) -> Self {
Self {
items,
i: 0,
j: 0,
k: 0,
joint_idx: 0,
}
}
}
impl Iterator for ThreeDeviceSameJointIter<'_> {
type Item = Circuit;
fn next(&mut self) -> Option<Self::Item> {
let n = self.items.len();
if n == 0 {
return None;
}
loop {
if self.joint_idx < JointKind::ALL.len() {
let jk = JointKind::ALL[self.joint_idx];
self.joint_idx += 1;
return Some(Circuit::from_three_devices(
self.items[self.i].value,
self.items[self.j].value,
jk,
self.items[self.k].value,
jk,
));
}
self.joint_idx = 0;
self.k += 1;
if self.k >= n {
self.j += 1;
self.k = self.j;
if self.j >= n {
self.i += 1;
self.j = self.i;
self.k = self.i;
if self.i >= n {
return None;
}
}
}
}
}
}
impl FusedIterator for ThreeDeviceSameJointIter<'_> {}
/// Iterator over three-device circuits where the two joint types differ.
///
/// In this case, the first 2 devices are swapable and are iterated without repeating,
/// while the third device iterates over all values independently.
pub struct ThreeDeviceDiffJointIter<'a> {
items: &'a [DatasetItem],
i: usize,
j: usize,
k: usize,
joint_idx: usize,
}
impl<'a> ThreeDeviceDiffJointIter<'a> {
pub fn new(items: &'a [DatasetItem]) -> Self {
Self {
items,
i: 0,
j: 0,
k: 0,
joint_idx: 0,
}
}
}
impl Iterator for ThreeDeviceDiffJointIter<'_> {
type Item = Circuit;
fn next(&mut self) -> Option<Self::Item> {
let n = self.items.len();
if n == 0 {
return None;
}
loop {
if self.joint_idx < JointKind::ALL.len() {
let j = JointKind::ALL[self.joint_idx];
self.joint_idx += 1;
return Some(Circuit::from_three_devices(
self.items[self.i].value,
self.items[self.j].value,
j,
self.items[self.k].value,
j.flip(),
));
}
self.joint_idx = 0;
self.k += 1;
if self.k >= n {
self.j += 1;
self.k = 0;
if self.j >= n {
self.i += 1;
self.j = self.i;
self.k = 0;
if self.i >= n {
return None;
}
}
}
}
}
}
impl FusedIterator for ThreeDeviceDiffJointIter<'_> {}
/// Type alias for the chained three-device circuit iterator.
pub type ThreeDeviceCircuitIter<'a> = std::iter::Chain<
ThreeDeviceSameJointIter<'a>,
ThreeDeviceDiffJointIter<'a>,
>;
// ============================================================================
// BfsItem
// ============================================================================
// region: BFS Item
/// The entry used in BFS iteration storing circuit and value.
pub struct BfsItem {
@@ -259,13 +38,11 @@ pub struct BfsItem {
impl BfsItem {
/// Create a new BFS item by computing values eagerly.
///
/// # Errors
///
/// See [`CircuitValueTrait::value`].
pub fn new(circuit: Circuit, ccalc: &CircuitCalculator) -> Result<Self, LcrConnError> {
pub fn new(circuit: Circuit, ccalc: &CircuitCalculator) -> Result<Self, BfsResolverError> {
// YYC MARK:
// The same reason for replacing cached_property like I done in `ResponseItem`.
let value = ccalc.value(&circuit)?;
let unsigned_difference = ccalc.unsigned_difference(&circuit, Some(value))?;
let unsigned_difference = ccalc.unsigned_difference(&circuit, Some(value), None)?;
Ok(Self {
circuit,
value,
@@ -294,30 +71,42 @@ impl BfsItem {
}
}
// ============================================================================
// ResultBucket
// ============================================================================
// endregion
// region Result Bucket
/// An item stored in a [`ResultBucket`].
struct ResultBucketItem {
/// The score associated with this item.
score: f64,
/// The underlying BfsItem.
score: OrderedFloat<f64>,
/// The underlying [BfsItem].
item: BfsItem,
/// Monotonic counter used as a tiebreaker when scores are equal,
/// ensuring that BinaryHeap never compares BfsItem directly.
/// ensuring that BinaryHeap never compares [BfsItem] directly.
seq: usize,
}
impl ResultBucketItem {
fn new(score: f64, item: BfsItem, seq: usize) -> Self {
Self { score, item, seq }
pub fn new(score: f64, item: BfsItem, seq: usize) -> Self {
Self {
score: OrderedFloat(score),
item,
seq,
}
}
pub fn get_score(&self) -> f64 {
self.score.0
}
pub fn into_bfs_item(self) -> BfsItem {
self.item
}
}
impl PartialEq for ResultBucketItem {
fn eq(&self, other: &Self) -> bool {
self.score == other.score && self.seq == other.seq
self.score.eq(&other.score) && self.seq.eq(&other.seq)
}
}
@@ -333,10 +122,9 @@ impl Ord for ResultBucketItem {
fn cmp(&self, other: &Self) -> Ordering {
// BinaryHeap is a max-heap: the greatest element is at the top.
// We want the entry with the largest score at the top.
match self.score.partial_cmp(&other.score) {
Some(Ordering::Equal) | None => self.seq.cmp(&other.seq),
Some(ord) => ord,
}
self.score
.cmp(&other.score)
.then_with(|| self.seq.cmp(&other.seq))
}
}
@@ -357,11 +145,16 @@ pub struct ResultBucket {
impl ResultBucket {
/// Create a new bucket that holds at most `n` items.
pub fn new(n: usize) -> Self {
Self {
n,
heap: BinaryHeap::new(),
counter: 0,
pub fn new(n: usize) -> Result<Self, BfsResolverError> {
// Check heap size
if n == 0 {
Err(BfsResolverError::BadBinHeapSize(n))
} else {
Ok(Self {
n,
heap: BinaryHeap::new(),
counter: 0,
})
}
}
@@ -375,6 +168,11 @@ impl ResultBucket {
self.heap.is_empty()
}
/// Consume the bucket and return all stored items.
pub fn into_iter(self) -> impl Iterator<Item = BfsItem> {
self.heap.into_iter().map(|entry| entry.item)
}
/// Insert a [`BfsItem`] with the given score.
///
/// If the bucket is not yet full the item is always inserted.
@@ -382,33 +180,30 @@ impl ResultBucket {
/// than the largest score currently in the bucket; the entry
/// with the largest score is then evicted.
///
/// # Returns
///
/// `true` if the item was inserted, `false` otherwise.
/// Returns `true` if the item was inserted, `false` otherwise.
pub fn insert(&mut self, item: BfsItem, score: f64) -> bool {
let entry = ResultBucketItem::new(score, item, self.counter);
if self.heap.len() < self.n {
self.heap.push(entry);
self.counter += 1;
true
} else if score >= self.heap.peek().unwrap().score {
} else if score
>= self
.heap
.peek()
.expect("unexpected blank binary heap")
.get_score()
{
false
} else {
*self.heap.peek_mut().unwrap() = entry;
*self.heap.peek_mut().expect("unexpected blank binary heap") = entry;
self.counter += 1;
true
}
}
/// Consume the bucket and return all stored items.
pub fn into_items(self) -> Vec<BfsItem> {
self.heap.into_iter().map(|entry| entry.item).collect()
}
}
// ============================================================================
// BfsResolver
// ============================================================================
// endregion
/// A resolver that uses brute-force search to find the best matching circuits.
pub struct BfsResolver {
@@ -417,25 +212,72 @@ pub struct BfsResolver {
}
impl BfsResolver {
/// Create a new BFS resolver with the given datasets.
pub fn new(datasets: DatasetCollection) -> Self {
Self { datasets }
}
// YYC MARK:
// Some circuit are equivalent in topology.
// If we deduplicate these equaivalent circuit in building result,
// there are too complex works.
// So we should deduplicated these equivalent circuit at the beginning,
// i.e. when generating them.
// So following iterator structs are taking this job.
/// Iterate all possible circuits with one device without repeating equivalent topology.
pub fn iter_one_device_circuit(dataset: &Dataset) -> OneDeviceCircuitIter<'_> {
OneDeviceCircuitIter::new(dataset.items())
pub fn iter_one_device_circuit(
dataset: &Dataset,
) -> impl Iterator<Item = Result<Circuit, CircuitError>> {
// Every single device is unique so we directly output them.
// This feature is insured by dataset itself.
dataset.values().map(|v1| Circuit::from_one_device(v1))
}
/// Iterate all possible circuits with two devices without repeating equivalent topology.
pub fn iter_two_devices_circuit(dataset: &Dataset) -> TwoDeviceCircuitIter<'_> {
TwoDeviceCircuitIter::new(dataset.items())
pub fn iter_two_devices_circuit(
dataset: &Dataset,
) -> impl Iterator<Item = Result<Circuit, CircuitError>> {
// The two devices in this circuit is always swapable,
// so we iterate them without repeating.
itertools::iproduct!(
dataset.values().array_combinations_with_replacement::<2>(),
JointKind::iter()
)
.map(|([v1, v2], j2)| Circuit::from_two_devices(v1, v2, j2))
}
/// Iterate all possible circuits with three devices without repeating equivalent topology.
pub fn iter_three_devices_circuit(dataset: &Dataset) -> ThreeDeviceCircuitIter<'_> {
ThreeDeviceSameJointIter::new(dataset.items())
.chain(ThreeDeviceDiffJointIter::new(dataset.items()))
pub fn iter_three_devices_circuit(
dataset: &Dataset,
) -> impl Iterator<Item = Result<Circuit, CircuitError>> {
// For generating three devices circuit,
// it should be consisted by 2 parts.
itertools::chain!(
// First, the whole circuit has only one joint type.
// In this case, 3 devices are swapable and we should iterate them without repeating
itertools::iproduct!(
dataset.values().array_combinations_with_replacement::<3>(),
JointKind::iter()
)
.map(|([v1, v2, v3], j)| Circuit::from_three_devices(v1, v2, j, v3, j)),
// Second, if the joint type is different, then the first 2 devices are swapable.
// So we need iterate them without repeating.
itertools::iproduct!(
dataset.values().array_combinations_with_replacement::<2>(),
dataset.values(),
JointKind::iter()
)
.map(|([v1, v2], v3, j)| Circuit::from_three_devices(
v1,
v2,
j,
v3,
j.flip()
)),
)
}
}
impl BfsResolver {
/// Create a new BFS resolver with the given datasets.
pub fn new(datasets: DatasetCollection) -> Self {
Self { datasets }
}
fn pick_dataset(&self, device_kind: DeviceKind) -> &Dataset {
@@ -445,37 +287,47 @@ impl BfsResolver {
DeviceKind::Inductor => self.datasets.inductor_dataset(),
}
}
}
impl Resolver for BfsResolver {
fn resolve(&self, request: &Request) -> Result<Response, LcrConnError> {
fn bfs_iteration(
dataset: &Dataset,
ccalc: &CircuitCalculator,
) -> impl Iterator<Item = Result<BfsItem, BfsResolverError>> {
itertools::chain!(
BfsResolver::iter_one_device_circuit(&dataset),
BfsResolver::iter_two_devices_circuit(&dataset),
BfsResolver::iter_three_devices_circuit(&dataset)
)
.map(|circuit| -> Result<BfsItem, BfsResolverError> { BfsItem::new(circuit?, ccalc) })
}
fn intern_resolve(&self, request: &Request) -> Result<Response, BfsResolverError> {
// Pick dataset from collection
let dataset = self.pick_dataset(request.device_kind);
let dataset = self.pick_dataset(request.get_device_kind());
// Iterate circuit item one by one
let mut bucket = ResultBucket::new(request.count_limit);
let ccalc = CircuitCalculator::new(request.device_kind, request.target_value);
let mut bucket = ResultBucket::new(request.get_count_limit())?;
let ccalc = CircuitCalculator::new(request.get_device_kind(), request.get_target_value())?;
let circuits = Self::iter_one_device_circuit(dataset)
.chain(Self::iter_two_devices_circuit(dataset))
.chain(Self::iter_three_devices_circuit(dataset));
for circuit in circuits {
let item = BfsItem::new(circuit, &ccalc)?;
for item in BfsResolver::bfs_iteration(dataset, &ccalc) {
let item = item?;
// If circuit absolute difference is out of tolerance, skip it directly.
if item.unsigned_difference() > request.tolerance {
if item.unsigned_difference() <= request.get_tolerance() {
// Put it into bucket
let score = item.unsigned_difference();
bucket.insert(item, score);
} else {
continue;
}
// Put it into bucket
bucket.insert(item, item.unsigned_difference());
}
// Return result
let circuits: Vec<Circuit> = bucket
.into_items()
.into_iter()
.map(BfsItem::into_circuit)
.collect();
Response::new(request, circuits)
let circuits = bucket.into_iter().map(|i| i.into_circuit());
Ok(Response::new(request, circuits)?)
}
}
impl Resolver for BfsResolver {
fn resolve(&self, request: &Request) -> Result<Response, ResolverError> {
Ok(self.intern_resolve(request)?)
}
}

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@@ -1,26 +0,0 @@
pub mod bfs;
pub mod lut;
use crate::common::LcrConnError;
use crate::query::{Request, Response};
/// Abstract base trait for all resolvers.
pub trait Resolver {
/// Resolve the request and return the response.
///
/// # Arguments
///
/// * `request` - The request to resolve.
///
/// # Returns
///
/// The response containing the best matching circuits.
///
/// # Errors
///
/// See [`Circuit::compute`](crate::common::Circuit::compute).
fn resolve(&self, request: &Request) -> Result<Response, LcrConnError>;
}
pub use bfs::BfsResolver;
pub use lut::LutResolver;