Remove label, as it duplicates existing data

ankitects · Aug 21, 2023 · 682c503 · 682c503
1 parent a9e1fd5
commit 682c503
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Showing 2 changed files with 22 additions and 11 deletions.
diff --git a/src/convertor.rs b/src/convertor.rs
@@ -185,14 +185,7 @@ fn convert_to_fsrs_item(
         })
         .collect_vec();
 
-    let last = entries.last().unwrap();
-    Some(FSRSItem {
-        reviews,
-        label: match last.button_chosen {
-            1 => 0.0,
-            2 | 3 | 4 | _ => 1.0,
-        },
-    })
+    Some(FSRSItem { reviews })
 }
 
 pub fn anki_to_fsrs() -> Vec<FSRSItem> {

diff --git a/src/dataset.rs b/src/dataset.rs
@@ -10,7 +10,6 @@ use crate::convertor::anki_to_fsrs;
 #[derive(Debug, Clone, Deserialize, Serialize)]
 pub struct FSRSItem {
     pub reviews: Vec<FSRSReview>,
-    pub label: f32,
 }
 
 #[derive(Debug, Clone, Deserialize, Serialize)]
@@ -69,12 +68,31 @@ impl<B: Backend> Batcher<FSRSItem, FSRSBatch<B>> for FSRSBatcher<B> {
 
         let delta_ts = items
             .iter()
-            .map(|item| Tensor::<B, 1, Float>::from_data(Data::from([item.reviews.last().unwrap().delta_t.elem()])))
+            .map(|item| {
+                Tensor::<B, 1, Float>::from_data(Data::from([item
+                    .reviews
+                    .last()
+                    .unwrap()
+                    .delta_t
+                    .elem()]))
+            })
             .collect();
 
         let labels = items
             .iter()
-            .map(|item| Tensor::<B, 1, Int>::from_data(Data::from([item.label.elem()])))
+            .map(|item| {
+                Tensor::<B, 1, Int>::from_data(Data::from([
+                    match item.reviews.last().unwrap().rating {
+                        1 => 0.0,
+                        2 | 3 | 4 => 1.0,
+                        _ => {
+                            // invalid value, assume it's good
+                            1.0
+                        }
+                    }
+                    .elem(),
+                ]))
+            })
             .collect();
 
         let t_historys = Tensor::cat(t_historys, 0)