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Mean reciprocal rank (MRR) of leaderboard scores #3451

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Dec 8, 2023
+20 −3
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Mean reciprocal rank (MRR) of leaderboard scores #3451

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23 changes: 20 additions & 3 deletions codalab/apps/web/models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1238,9 +1238,13 @@ def sortkey(x):
for result in results:
for sdef in result['scoredefs']:
if sdef.computed:
operation = getattr(models, sdef.computed_score.operation)
try:
operation = getattr(models, sdef.computed_score.operation)
operation_name = operation.name
except:
operation_name = sdef.computed_score.operation
weights = sdef.computed_score.weights
if (operation.name == 'Avg'):
if (operation_name == 'Avg'):
try:
cnt = len(computed_deps[sdef.id])
if (cnt > 0):
Expand All @@ -1263,6 +1267,18 @@ def sortkey(x):
ranks[sdef.id] = self.rank_values(submission_ids, computed_values, sort_ascending=sdef.sorting=='asc')
except KeyError:
pass
elif (operation_name == 'MRR'):
try:
cnt = len(computed_deps[sdef.id])
if (cnt > 0):
computed_values = {}
for id in submission_ids:
# Mean reciprocal rank computation
computed_values[id] = sum([1.0/ranks[d.id][id] for d in computed_deps[sdef.id]]) / float(cnt)
values[sdef.id] = computed_values
ranks[sdef.id] = self.rank_values(submission_ids, computed_values, sort_ascending=sdef.sorting=='asc')
except KeyError:
pass

# format values
for result in results:
Expand Down Expand Up @@ -2398,7 +2414,8 @@ def save(self, *args, **kwargs):
class SubmissionComputedScore(models.Model):
scoredef = models.OneToOneField(SubmissionScoreDef, related_name='computed_score', on_delete=models.CASCADE)
operation = models.CharField(max_length=10, choices=(('Max', 'Max'),
('Avg', 'Average')))
('Avg', 'Average'),
('MRR', 'MRR')))
weights = models.CharField(max_length=200, null=True, blank=True)


Expand Down
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