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Fix a bug of is_sortable inference for trial user attrs

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c-bata
2022-12-09 10:41:56 +09:00
parent 72f7dc2180
commit 50cf80bc48
2 changed files with 50 additions and 22 deletions
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python_tests/test_cached_extra_study_property.py
+44 -21
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@@ -6,7 +6,7 @@ import warnings
import optuna
from optuna import create_trial
from optuna.distributions import BaseDistribution
from optuna.distributions import UniformDistribution
from optuna.distributions import FloatDistribution
from optuna.exceptions import ExperimentalWarning
from optuna.trial import TrialState
from optuna_dashboard._cached_extra_study_property import _CachedExtraStudyProperty
@@ -20,12 +20,12 @@ class _CachedExtraStudyPropertySearchSpaceTestCase(TestCase):
def test_same_distributions(self) -> None:
distributions: List[Dict[str, BaseDistribution]] = [
{
"x0": UniformDistribution(low=0, high=10),
"x1": UniformDistribution(low=0, high=10),
"x0": FloatDistribution(low=0, high=10),
"x1": FloatDistribution(low=0, high=10),
},
{
"x0": UniformDistribution(low=0, high=10),
"x1": UniformDistribution(low=0, high=10),
"x0": FloatDistribution(low=0, high=10),
"x1": FloatDistribution(low=0, high=10),
},
]
params = [
@@ -51,12 +51,12 @@ class _CachedExtraStudyPropertySearchSpaceTestCase(TestCase):
def test_different_distributions(self) -> None:
distributions: List[Dict[str, BaseDistribution]] = [
{
"x0": UniformDistribution(low=0, high=10),
"x1": UniformDistribution(low=0, high=10),
"x0": FloatDistribution(low=0, high=10),
"x1": FloatDistribution(low=0, high=10),
},
{
"x0": UniformDistribution(low=0, high=5),
"x1": UniformDistribution(low=0, high=10),
"x0": FloatDistribution(low=0, high=5),
"x1": FloatDistribution(low=0, high=10),
},
]
params = [
@@ -82,15 +82,15 @@ class _CachedExtraStudyPropertySearchSpaceTestCase(TestCase):
def test_dynamic_search_space(self) -> None:
distributions: List[Dict[str, BaseDistribution]] = [
{
"x0": UniformDistribution(low=0, high=10),
"x1": UniformDistribution(low=0, high=10),
"x0": FloatDistribution(low=0, high=10),
"x1": FloatDistribution(low=0, high=10),
},
{
"x0": UniformDistribution(low=0, high=5),
"x0": FloatDistribution(low=0, high=5),
},
{
"x0": UniformDistribution(low=0, high=10),
"x1": UniformDistribution(low=0, high=10),
"x0": FloatDistribution(low=0, high=10),
"x1": FloatDistribution(low=0, high=10),
},
]
params = [
@@ -119,8 +119,8 @@ class _CachedExtraStudyPropertySearchSpaceTestCase(TestCase):
def test_contains_failed_trials(self) -> None:
distributions = {
"x0": UniformDistribution(low=0, high=10),
"x1": UniformDistribution(low=0, high=10),
"x0": FloatDistribution(low=0, high=10),
"x1": FloatDistribution(low=0, high=10),
}
params = {
"x0": 0.5,
@@ -156,7 +156,7 @@ class _CachedExtraStudyPropertyIntermediateTestCase(TestCase):
create_trial(
state=TrialState.COMPLETE,
value=0,
distributions={"x0": UniformDistribution(low=0, high=10)},
distributions={"x0": FloatDistribution(low=0, high=10)},
intermediate_values=iv,
params={"x0": 0.5},
)
@@ -176,7 +176,7 @@ class _CachedExtraStudyPropertyIntermediateTestCase(TestCase):
create_trial(
state=TrialState.COMPLETE,
value=0,
distributions={"x0": UniformDistribution(low=0, high=10)},
distributions={"x0": FloatDistribution(low=0, high=10)},
intermediate_values=iv,
params={"x0": 0.5},
)
@@ -192,7 +192,7 @@ class _CachedExtraStudyPropertyIntermediateTestCase(TestCase):
create_trial(
state=TrialState.COMPLETE,
value=0,
distributions={"x0": UniformDistribution(low=0, high=10)},
distributions={"x0": FloatDistribution(low=0, high=10)},
intermediate_values=iv,
params={"x0": 0.5},
)
@@ -216,8 +216,8 @@ class _CachedExtraStudyPropertyUserAttrs(TestCase):
def test_contains_failed_trials(self) -> None:
distributions = {
"x0": UniformDistribution(low=0, high=10),
"x1": UniformDistribution(low=0, high=10),
"x0": FloatDistribution(low=0, high=10),
"x1": FloatDistribution(low=0, high=10),
}
params = {
"x0": 0.5,
@@ -250,3 +250,26 @@ class _CachedExtraStudyPropertyUserAttrs(TestCase):
cached_extra_study_property.update(trials)
self.assertEqual(len(cached_extra_study_property.union_user_attrs), 3)
def test_infer_sortable(self) -> None:
user_attrs_list = [
{"a": 1, "b": 1, "c": 1, "d": "a"},
{"a": 2, "b": "a", "c": "a", "d": "a"},
{"a": 3, "b": None, "c": 3, "d": "a"},
]
expected = {"a": True, "b": False, "c": False, "d": False}
trials = []
for user_attrs in user_attrs_list:
trials.append(create_trial(
state=TrialState.COMPLETE,
value=0,
distributions={"x0": FloatDistribution(low=0, high=10), "x1": FloatDistribution(low=0, high=10)},
params={"x0": 0.5, "x1": 0.5},
user_attrs=user_attrs,
))
cached_extra_study_property = _CachedExtraStudyProperty()
cached_extra_study_property.update(trials)
actual = {k: v for k, v in cached_extra_study_property.union_user_attrs}
assert actual == expected