Fix/re-optimize FSRS if short-term param is weird (#3742)

* Fix/re-optimize FSRS if short-term param is weird

* Reset progress when another run is required (dae)

* only count the same-day steps

* Fix flicker when optimizing again (dae)

proto/anki/scheduler.proto

@@ -346,6 +346,7 @@ message ComputeFsrsParamsRequest {
   string search = 1;
   repeated float current_params = 2;
   int64 ignore_revlogs_before_ms = 3;
+  uint32 num_of_relearning_steps = 4;
 }
 
 message ComputeFsrsParamsResponse {

rslib/src/deckconfig/update.rs

@@ -356,12 +356,14 @@ impl Collection {
                 config.inner.param_search.clone()
             };
             let ignore_revlogs_before_ms = ignore_revlogs_before_ms_from_config(config)?;
+            let num_of_relearning_steps = config.inner.relearn_steps.len();
             match self.compute_params(
                 &search,
                 ignore_revlogs_before_ms,
                 idx as u32 + 1,
                 config_len,
                 config.fsrs_params(),
+                num_of_relearning_steps,
             ) {
                 Ok(params) => {
                     println!("{}: {:?}", config.name, params.params);

rslib/src/progress.rs

@@ -122,6 +122,13 @@ pub struct ProgressState {
     pub last_progress: Option<Progress>,
 }
 
+impl ProgressState {
+    pub fn reset(&mut self) {
+        self.want_abort = false;
+        self.last_progress = None;
+    }
+}
+
 #[derive(Clone, Copy, Debug)]
 pub enum Progress {
     MediaSync(MediaSyncProgress),
@@ -320,6 +327,10 @@ impl Collection {
     ) -> ThrottlingProgressHandler<P> {
         ThrottlingProgressHandler::new(self.state.progress.clone())
     }
+
+    pub(crate) fn clear_progress(&mut self) {
+        self.state.progress.lock().unwrap().reset();
+    }
 }
 
 pub(crate) struct Incrementor<'f, F: 'f + FnMut(usize) -> Result<()>> {

rslib/src/scheduler/fsrs/params.rs

@@ -16,6 +16,7 @@ use chrono::NaiveTime;
 use fsrs::CombinedProgressState;
 use fsrs::FSRSItem;
 use fsrs::FSRSReview;
+use fsrs::MemoryState;
 use fsrs::ModelEvaluation;
 use fsrs::FSRS;
 use itertools::Itertools;
@@ -60,8 +61,9 @@ impl Collection {
         current_preset: u32,
         total_presets: u32,
         current_params: &Params,
+        num_of_relearning_steps: usize,
     ) -> Result<ComputeFsrsParamsResponse> {
-        let mut anki_progress = self.new_progress_handler::<ComputeParamsProgress>();
+        self.clear_progress();
         let timing = self.timing_today()?;
         let revlogs = self.revlog_for_srs(search)?;
         let (items, review_count) =
@@ -74,31 +76,38 @@ impl Collection {
                 fsrs_items,
             });
         }
-        anki_progress.update(false, |p| {
-            p.current_preset = current_preset;
-            p.total_presets = total_presets;
-        })?;
         // adapt the progress handler to our built-in progress handling
-        let progress = CombinedProgressState::new_shared();
-        let progress2 = progress.clone();
-        let progress_thread = thread::spawn(move || {
-            let mut finished = false;
-            while !finished {
-                thread::sleep(Duration::from_millis(100));
-                let mut guard = progress.lock().unwrap();
-                if let Err(_err) = anki_progress.update(false, |s| {
-                    s.total_iterations = guard.total() as u32;
-                    s.current_iteration = guard.current() as u32;
-                    s.reviews = review_count as u32;
-                    finished = guard.finished();
-                }) {
-                    guard.want_abort = true;
-                    return;
+
+        let create_progress_thread = || -> Result<_> {
+            let mut anki_progress = self.new_progress_handler::<ComputeParamsProgress>();
+            anki_progress.update(false, |p| {
+                p.current_preset = current_preset;
+                p.total_presets = total_presets;
+            })?;
+            let progress = CombinedProgressState::new_shared();
+            let progress2 = progress.clone();
+            let progress_thread = thread::spawn(move || {
+                let mut finished = false;
+                while !finished {
+                    thread::sleep(Duration::from_millis(100));
+                    let mut guard = progress.lock().unwrap();
+                    if let Err(_err) = anki_progress.update(false, |s| {
+                        s.total_iterations = guard.total() as u32;
+                        s.current_iteration = guard.current() as u32;
+                        s.reviews = review_count as u32;
+                        finished = guard.finished();
+                    }) {
+                        guard.want_abort = true;
+                        return;
+                    }
                 }
-            }
-        });
-        let mut params =
-            FSRS::new(None)?.compute_parameters(items.clone(), Some(progress2), true)?;
+            });
+            Ok((progress2, progress_thread))
+        };
+
+        let (progress, progress_thread) = create_progress_thread()?;
+        let fsrs = FSRS::new(None)?;
+        let mut params = fsrs.compute_parameters(items.clone(), Some(progress.clone()), true)?;
         progress_thread.join().ok();
         if let Ok(fsrs) = FSRS::new(Some(current_params)) {
             let current_rmse = fsrs.evaluate(items.clone(), |_| true)?.rmse_bins;
@@ -107,6 +116,27 @@ impl Collection {
             if current_rmse <= optimized_rmse {
                 params = current_params.to_vec();
             }
+            if num_of_relearning_steps > 1 {
+                let memory_state = MemoryState {
+                    stability: 1.0,
+                    difficulty: 1.0,
+                };
+                let s_fail = optimized_fsrs
+                    .next_states(Some(memory_state), 0.9, 2)?
+                    .again;
+                let mut s_short_term = s_fail.memory;
+                for _ in 0..num_of_relearning_steps {
+                    s_short_term = optimized_fsrs
+                        .next_states(Some(s_short_term), 0.9, 0)?
+                        .good
+                        .memory;
+                }
+                if s_short_term.stability > memory_state.stability {
+                    let (progress, progress_thread) = create_progress_thread()?;
+                    params = fsrs.compute_parameters(items.clone(), Some(progress), false)?;
+                    progress_thread.join().ok();
+                }
+            }
         }
 
         Ok(ComputeFsrsParamsResponse { params, fsrs_items })

rslib/src/scheduler/service/mod.rs

@@ -264,6 +264,7 @@ impl crate::services::SchedulerService for Collection {
             1,
             1,
             &input.current_params,
+            input.num_of_relearning_steps as usize,
         )
     }
 

ts/routes/deck-options/FsrsOptions.svelte

@@ -151,12 +151,23 @@ License: GNU AGPL, version 3 or later; http://www.gnu.org/licenses/agpl.html
             await runWithBackendProgress(
                 async () => {
                     const params = fsrsParams($config);
+                    const RelearningSteps = $config.relearnSteps;
+                    let numOfRelearningStepsInDay = 0;
+                    let accumulatedTime = 0;
+                    for (let i = 0; i < RelearningSteps.length; i++) {
+                        accumulatedTime += RelearningSteps[i];
+                        if (accumulatedTime >= 1440) {
+                            break;
+                        }
+                        numOfRelearningStepsInDay++;
+                    }
                     const resp = await computeFsrsParams({
                         search: $config.paramSearch
                             ? $config.paramSearch
                             : defaultparamSearch,
                         ignoreRevlogsBeforeMs: getIgnoreRevlogsBeforeMs(),
                         currentParams: params,
+                        numOfRelearningSteps: numOfRelearningStepsInDay,
                     });
 
                     const already_optimal =