ensure float list types in ODFV UDFs can be appied

Signed-off-by: Jeff <jeffxl@apple.com>
feast-dev · Nov 12, 2021 · 464e717 · 464e717
1 parent af3dc6b
commit 464e717
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Showing 4 changed files with 22 additions and 10 deletions.
diff --git a/sdk/python/feast/driver_test_data.py b/sdk/python/feast/driver_test_data.py
@@ -125,7 +125,8 @@ def create_driver_hourly_stats_df(drivers, start_date, end_date) -> pd.DataFrame
         np.int32
     )
     dummy_vector = [1.0, 0.0]
-    df_all_drivers["embedding"] = [dummy_vector] * rows
+    df_all_drivers["embedding_double"] = [dummy_vector] * rows
+    df_all_drivers["embedding_float"] = df_all_drivers["embedding_double"]
     df_all_drivers["created"] = pd.to_datetime(pd.Timestamp.now(tz=None).round("ms"))
 
     # Create duplicate rows that should be filtered by created timestamp

diff --git a/sdk/python/tests/integration/feature_repos/universal/feature_views.py b/sdk/python/tests/integration/feature_repos/universal/feature_views.py
@@ -71,14 +71,18 @@ def conv_rate_plus_100_feature_view(
 
 def similarity(features_df: pd.DataFrame) -> pd.DataFrame:
     if features_df.size == 0:
-        return pd.DataFrame({"cos": [0.0]})  # give hint to Feast about return type
-    vectors_a = features_df["embedding"].apply(np.array)
-    vectors_b = features_df["vector"].apply(np.array)
+        # give hint to Feast about return type
+        df = pd.DataFrame({"cos_double": [0.0]})
+        df["cos_float"] = df["cos_double"].astype(np.float32)
+        return df
+    vectors_a = features_df["embedding_double"].apply(np.array)
+    vectors_b = features_df["vector_double"].apply(np.array)
     dot_products = vectors_a.mul(vectors_b).apply(sum)
     norms_q = vectors_a.apply(np.linalg.norm)
     norms_doc = vectors_b.apply(np.linalg.norm)
     df = pd.DataFrame()
-    df["cos"] = dot_products / (norms_q * norms_doc)
+    df["cos_double"] = dot_products / (norms_q * norms_doc)
+    df["cos_float"] = df["cos_double"].astype(np.float32)
     return df
 
 
@@ -88,7 +92,8 @@ def similarity_feature_view(
     features: Optional[List[Feature]] = None,
 ) -> OnDemandFeatureView:
     _features = features or [
-        Feature("cos", ValueType.DOUBLE),
+        Feature("cos_double", ValueType.DOUBLE),
+        Feature("cos_float", ValueType.FLOAT),
     ]
     return OnDemandFeatureView(
         name=similarity.__name__,
@@ -115,7 +120,11 @@ def create_conv_rate_request_data_source():
 
 def create_similarity_request_data_source():
     return RequestDataSource(
-        name="similarity_input", schema={"vector": ValueType.DOUBLE_LIST}
+        name="similarity_input",
+        schema={
+            "vector_double": ValueType.DOUBLE_LIST,
+            "vector_float": ValueType.FLOAT_LIST,
+        },
     )
 
 
@@ -129,7 +138,8 @@ def create_driver_hourly_stats_feature_view(source, infer_features: bool = False
             Feature(name="conv_rate", dtype=ValueType.FLOAT),
             Feature(name="acc_rate", dtype=ValueType.FLOAT),
             Feature(name="avg_daily_trips", dtype=ValueType.INT32),
-            Feature(name="embedding", dtype=ValueType.DOUBLE_LIST),
+            Feature(name="embedding_double", dtype=ValueType.DOUBLE_LIST),
+            Feature(name="embedding_float", dtype=ValueType.FLOAT_LIST),
         ],
         batch_source=source,
         ttl=timedelta(hours=2),

diff --git a/sdk/python/tests/integration/online_store/test_universal_online.py b/sdk/python/tests/integration/online_store/test_universal_online.py
@@ -149,7 +149,8 @@ def test_write_to_online_store(environment, universal_data_sources):
         "conv_rate": [0.85],
         "acc_rate": [0.91],
         "avg_daily_trips": [14],
-        "embedding": [dummy_vector],
+        "embedding_double": [dummy_vector],
+        "embedding_float": [dummy_vector],
         "event_timestamp": [pd.Timestamp(datetime.datetime.utcnow()).round("ms")],
         "created": [pd.Timestamp(datetime.datetime.utcnow()).round("ms")],
     }

diff --git a/sdk/python/tests/integration/registration/test_universal_odfv_feature_inference.py b/sdk/python/tests/integration/registration/test_universal_odfv_feature_inference.py
@@ -43,7 +43,7 @@ def test_infer_odfv_features(environment, universal_data_sources, infer_features
     assert len(odfv.features) == 3
 
     odfv = store.get_on_demand_feature_view("similarity")
-    assert len(odfv.features) == 1
+    assert len(odfv.features) == 2
 
 
 @pytest.mark.integration