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fix: Fix feature service inference logic #3089

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Merged
feast-ci-bot merged 11 commits into from
Aug 19, 2022
Merged

fix: Fix feature service inference logic #3089

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1e09ad3
Add __init__.py files to allow test files to share names
felixwang9817 Aug 16, 2022
5a5c6f6
Add feature service tests
felixwang9817 Aug 12, 2022
07eaba6
Fix feature service inference logic
felixwang9817 Aug 16, 2022
51174b3
Remove stray `__init__.py` file
felixwang9817 Aug 16, 2022
45ec63c
Fix comments
felixwang9817 Aug 17, 2022
7a43b8f
Add check
felixwang9817 Aug 17, 2022
40d7965
Temp
felixwang9817 Aug 17, 2022
8dfb6db
Address comments
felixwang9817 Aug 17, 2022
c4d9c5a
Fix
felixwang9817 Aug 18, 2022
64dfdef
Address comments
felixwang9817 Aug 18, 2022
31115ac
Fix
felixwang9817 Aug 18, 2022
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Fix 
Signed-off-by: Felix Wang <wangfelix98@gmail.com>
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@felixwang9817
felixwang9817 committed Aug 18, 2022
commit c4d9c5a83fe5ce57931db7014334d2b342089975
48 changes: 29 additions & 19 deletions sdk/python/feast/feature_service.py
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Original file line number Diff line number Diff line change
Expand Up @@ -100,29 +100,33 @@ def infer_features(self, fvs_to_update: Dict[str, FeatureView]):
"""
for feature_grouping in self._features:
if isinstance(feature_grouping, BaseFeatureView):
if feature_grouping.name not in fvs_to_update:
raise FeatureViewMissingDuringFeatureServiceInference(
feature_view_name=feature_grouping.name,
feature_service_name=self.name,
)

projection = feature_grouping.projection

if projection.desired_features:
# The projection wants to select a specific set of inferred features.
# Example: FeatureService(features=[fv[["inferred_feature"]]]), where
# 'fv' is a feature view that was defined without a schema.
# First we validate that the selected features have actually been inferred.
desired_features = set(projection.desired_features)
actual_features = set(
[f.name for f in fvs_to_update[feature_grouping.name].features]
)
assert desired_features.issubset(actual_features)

# Then we extract the selected features and add them to the projection.
projection.features = []
for f in fvs_to_update[feature_grouping.name].features:
if f.name in desired_features:
projection.features.append(f)
if feature_grouping.name in fvs_to_update:
# First we validate that the selected features have actually been inferred.
desired_features = set(projection.desired_features)
actual_features = set(
[
f.name
for f in fvs_to_update[feature_grouping.name].features
]
)
assert desired_features.issubset(actual_features)

# Then we extract the selected features and add them to the projection.
projection.features = []
for f in fvs_to_update[feature_grouping.name].features:
if f.name in desired_features:
projection.features.append(f)
else:
raise FeatureViewMissingDuringFeatureServiceInference(
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feature_view_name=feature_grouping.name,
feature_service_name=self.name,
)

continue

Expand All @@ -136,7 +140,13 @@ def infer_features(self, fvs_to_update: Dict[str, FeatureView]):
# The projection wants to select all possible inferred features.
# Example: FeatureService(features=[fv]), where 'fv' is a feature view that
# was defined without a schema.
projection.features = fvs_to_update[feature_grouping.name].features
if feature_grouping.name in fvs_to_update:
projection.features = fvs_to_update[feature_grouping.name].features
else:
raise FeatureViewMissingDuringFeatureServiceInference(
feature_view_name=feature_grouping.name,
feature_service_name=self.name,
)
else:
raise ValueError(
f"The feature service {self.name} has been provided with an invalid type "
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