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Refactor load balance (#424)
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@L-M-Sherlock
L-M-Sherlock committed Jun 14, 2024
1 parent ed32cf8 commit 0d51871
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Showing 2 changed files with 85 additions and 57 deletions.
108 changes: 57 additions & 51 deletions schedule/reschedule.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@
from anki.decks import DeckManager
from anki.utils import ids2str
from aqt.gui_hooks import browser_menus_did_init
from collections import defaultdict


class FSRS:
Expand All @@ -19,8 +20,9 @@ class FSRS:
p_obey_easy_days: float
easy_specific_due_dates: List[int]
p_obey_specific_due_dates: float
due_cnt_perday_from_first_day: Dict[int, int]
learned_cnt_perday_from_today: Dict[int, int]
due_cnt_per_day: Dict[int, int]
due_today: int
reviewed_today: int
card: Card
elapsed_days: int
allow_to_past: bool
Expand All @@ -42,34 +44,32 @@ def __init__(self) -> None:
def set_load_balance(self, did_query=None):
self.enable_load_balance = True
true_due = "CASE WHEN odid==0 THEN due ELSE odue END"
self.due_cnt_perday_from_first_day = {
day: cnt
for day, cnt in mw.col.db.all(
f"""SELECT {true_due}, count()
FROM cards
WHERE type = 2
AND queue != -1
{did_query if did_query is not None else ""}
GROUP BY {true_due}"""
)
}
for day in list(self.due_cnt_perday_from_first_day.keys()):
if day < mw.col.sched.today:
self.due_cnt_perday_from_first_day[mw.col.sched.today] = (
self.due_cnt_perday_from_first_day.get(mw.col.sched.today, 0)
+ self.due_cnt_perday_from_first_day[day]
self.due_cnt_per_day = defaultdict(
int,
{
day: cnt
for day, cnt in mw.col.db.all(
f"""SELECT {true_due}, count()
FROM cards
WHERE type = 2
AND queue != -1
{did_query if did_query is not None else ""}
GROUP BY {true_due}"""
)
self.due_cnt_perday_from_first_day.pop(day)
self.learned_cnt_perday_from_today = {
day: cnt
for day, cnt in mw.col.db.all(
f"""SELECT (id/1000-{mw.col.sched.day_cutoff})/86400, count(distinct cid)
FROM revlog
WHERE ease > 0
AND (type < 3 OR factor != 0)
GROUP BY (id/1000-{mw.col.sched.day_cutoff})/86400"""
)
}
},
)
self.due_today = sum(
due_cnt
for due, due_cnt in self.due_cnt_per_day.items()
if due <= mw.col.sched.today
)
self.reviewed_today = mw.col.db.scalar(
f"""SELECT count(distinct cid)
FROM revlog
WHERE ease > 0
AND (type < 3 OR factor != 0)
AND id/1000 >= {mw.col.sched.day_cutoff - 86400}"""
)

def set_fuzz_factor(self, cid: int, reps: int):
random.seed(rotate_number_by_k(cid, 8) + reps)
Expand All @@ -86,18 +86,23 @@ def apply_fuzz(self, ivl):
else:
return int(self.fuzz_factor * (max_ivl - min_ivl + 1) + min_ivl)
else:
# Load balance
due = self.card.odue if self.card.odid else self.card.due
if due - self.card.ivl + max_ivl <= mw.col.sched.today:
# If the latest possible due date is in the past, skip load balance
return ivl

if self.apply_easy_days:
last_review = get_last_review_date(self.card)
due = self.card.odue if self.card.odid else self.card.due
if due > last_review + max_ivl + 2:
current_ivl = due - last_review
min_ivl, max_ivl = get_fuzz_range(
current_ivl, self.elapsed_days, current_ivl
)
min_num_cards = math.inf

min_workload = math.inf
best_ivl = (max_ivl + min_ivl) // 2 if self.allow_to_past else max_ivl
step = (max_ivl - min_ivl) // 100 + 1
due = self.card.due if self.card.odid == 0 else self.card.odue

if self.easy_days_review_ratio == 0:
obey_easy_days = True
Expand All @@ -107,8 +112,9 @@ def apply_fuzz(self, ivl):
obey_specific_due_dates = (
random.random() < self.p_obey_specific_due_dates
)

for check_ivl in reversed(range(min_ivl, max_ivl + step, step)):
check_due = due + check_ivl - self.card.ivl
check_due = due - self.card.ivl + check_ivl
if (
obey_specific_due_dates
and check_due in self.easy_specific_due_dates
Expand All @@ -121,20 +127,18 @@ def apply_fuzz(self, ivl):

due_date = sched_current_date() + timedelta(days=day_offset)
if obey_easy_days and due_date.weekday() in self.easy_days:
# If the due date is on an easy day, skip
continue

due_cards = self.due_cnt_perday_from_first_day.get(
max(check_due, mw.col.sched.today), 0
)
rated_cards = (
self.learned_cnt_perday_from_today.get(0, 0)
if day_offset <= 0
else 0
)
num_cards = due_cards + rated_cards
if num_cards < min_num_cards:
if check_due > mw.col.sched.today:
# If the due date is in the future, the workload is the number of cards due on that day
workload = self.due_cnt_per_day[check_due]
else:
# If the due date is in the past or today, the workload is the number of cards due today plus the number of cards learned today
workload = self.due_today + self.reviewed_today
if workload < min_workload:
best_ivl = check_ivl
min_num_cards = num_cards
min_workload = workload
return best_ivl

def next_interval(self, stability):
Expand Down Expand Up @@ -223,7 +227,7 @@ def reschedule_background(
if specific_due not in fsrs.easy_specific_due_dates:
fsrs.easy_specific_due_dates.append(specific_due)

fsrs.p_obey_specific_due_dates = obey_specific_due_dates(
fsrs.p_obey_specific_due_dates = p_obey_specific_due_dates(
len(fsrs.easy_specific_due_dates), fsrs.easy_days_review_ratio
)
if len(easy_specific_due_dates) > 0:
Expand Down Expand Up @@ -339,14 +343,16 @@ def reschedule_card(cid, fsrs: FSRS, recompute=False):
fsrs.set_card(card)
fsrs.set_fuzz_factor(cid, card.reps)
new_ivl = fsrs.next_interval(s)
due_before = max(card.odue if card.odid else card.due, mw.col.sched.today)
due_before = card.odue if card.odid else card.due
card = update_card_due_ivl(card, new_ivl)
due_after = max(card.odue if card.odid else card.due, mw.col.sched.today)
due_after = card.odue if card.odid else card.due
if fsrs.enable_load_balance:
fsrs.due_cnt_perday_from_first_day[due_before] -= 1
fsrs.due_cnt_perday_from_first_day[due_after] = (
fsrs.due_cnt_perday_from_first_day.get(due_after, 0) + 1
)
fsrs.due_cnt_per_day[due_before] -= 1
fsrs.due_cnt_per_day[due_after] += 1
if due_before <= mw.col.sched.today and due_after > mw.col.sched.today:
fsrs.due_today -= 1
if due_before > mw.col.sched.today and due_after <= mw.col.sched.today:
fsrs.due_today += 1
return card


Expand Down
34 changes: 28 additions & 6 deletions utils.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -192,14 +192,36 @@ def rotate_number_by_k(N, K):


def p_obey_easy_days(num_of_easy_days, easy_days_review_ratio):
"""
Calculate the probability of obeying easy days to ensure the review ratio.
Parameters:
- num_of_easy_days: the number of easy days
- easy_days_review_ratio: the ratio of reviews on easy days
Math:
- A week has 7 days, n easy days, 7 - n non-easy days
- Assume we have y reviews per non-easy day, the number of reviews per easy day is a * y
- The total number of reviews in a week is y * (7 - n) + a * y * n
- The probability of a review on an easy day is the number of reviews on easy days divided by the total number of reviews
- (a * y * n) / (y * (7 - n) + a * y * n) = (a * n) / (a * n + 7 - n)
- The probability of skipping a review on an easy day is 1 - (a * n) / (a * n + 7 - n) = (7 - n) / (a * n + 7 - n)
"""
return (7 - num_of_easy_days) / (
easy_days_review_ratio * num_of_easy_days + 7 - num_of_easy_days
)


def obey_specific_due_dates(num_of_specific_due_dates, easy_days_review_ratio):
return (8 + num_of_specific_due_dates) / (
easy_days_review_ratio * num_of_specific_due_dates
+ 8
+ num_of_specific_due_dates
)
def p_obey_specific_due_dates(num_of_specific_due_dates, easy_days_review_ratio):
"""
Calculate the probability of obeying specific due dates to ensure the review ratio.
Parameters:
- num_of_specific_due_dates: the number of specific due dates
- easy_days_review_ratio: the ratio of reviews on easy days
Math:
- When we have n specific due dates, the number of days to reschedule is 8 + n
- Assume we have y reviews per non-easy day, the number of reviews per easy day is a * y
- The total number of reviews in the days to reschedule is y * 8 + a * y * n
- The probability of a review on a specific due date is the number of reviews on specific due dates divided by the total number of reviews
- (a * y * n) / (y * 8 + a * y * n) = (a * n) / (a * n + 8)
- The probability of skipping a review on a specific due date is 1 - (a * n) / (a * n + 8) = 8 / (a * n + 8)
"""
return 8 / (easy_days_review_ratio * num_of_specific_due_dates + 8)

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