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0c6e3eaa93
* Support searching for deck configs by name * Integrate FSRS optimizer into Anki * Hack in a rough implementation of evaluate_weights() * Interrupt calculation if user closes dialog * Fix interrupted error check * log_loss/rmse * Update to latest fsrs commit; add progress info to weight evaluation * Fix progress not appearing when pretrain takes a while * Update to latest commit
50 lines
1.7 KiB
Rust
50 lines
1.7 KiB
Rust
// Copyright: Ankitects Pty Ltd and contributors
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// License: GNU AGPL, version 3 or later; http://www.gnu.org/licenses/agpl.html
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use anki_proto::scheduler::ComputeOptimalRetentionRequest;
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use fsrs_optimizer::find_optimal_retention;
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use fsrs_optimizer::SimulatorConfig;
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use itertools::Itertools;
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use crate::prelude::*;
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#[derive(Default, Clone, Copy, Debug)]
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pub struct ComputeRetentionProgress {
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pub current: u32,
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pub total: u32,
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}
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impl Collection {
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pub fn compute_optimal_retention(
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&mut self,
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req: ComputeOptimalRetentionRequest,
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) -> Result<f32> {
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let mut anki_progress = self.new_progress_handler::<ComputeRetentionProgress>();
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if req.weights.len() != 17 {
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invalid_input!("must have 17 weights");
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}
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let mut weights = [0f64; 17];
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weights
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.iter_mut()
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.set_from(req.weights.into_iter().map(|v| v as f64));
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Ok(find_optimal_retention(
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&SimulatorConfig {
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w: weights,
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deck_size: req.deck_size as usize,
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learn_span: req.days_to_simulate as usize,
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max_cost_perday: req.max_seconds_of_study_per_day as f64,
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max_ivl: req.max_interval as f64,
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recall_cost: req.recall_secs as f64,
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forget_cost: req.forget_secs as f64,
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learn_cost: req.learn_secs as f64,
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},
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|ip| {
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anki_progress
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.update(false, |p| {
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p.total = ip.total as u32;
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p.current = ip.current as u32;
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})
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.is_ok()
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},
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)? as f32)
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}
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}
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