Discard changes to core/src/test/scala/com/microsoft/azure/synapse/ml…

…/recommendation/SARSpec.scala
microsoft · Sep 7, 2024 · 11dae03 · 11dae03
1 parent 09557ea
commit 11dae03
Showing 1 changed file with 2 additions and 46 deletions.
diff --git a/core/src/test/scala/com/microsoft/azure/synapse/ml/recommendation/SARSpec.scala b/core/src/test/scala/com/microsoft/azure/synapse/ml/recommendation/SARSpec.scala
@@ -17,11 +17,7 @@ class SARSpec extends RankingTestBase with EstimatorFuzzing[SAR] {
       new TestObject(new SAR()
         .setUserCol(recommendationIndexer.getUserOutputCol)
         .setItemCol(recommendationIndexer.getItemOutputCol)
-        .setRatingCol(ratingCol), transformedDf),
-      new TestObject(new SAR()
-        .setUserCol(recommendationIndexer.getUserOutputCol)
-        .setItemCol(recommendationIndexer.getItemOutputCol)
-        .setRatingCol(ratingCol), transformedDfWithStrings)
+        .setRatingCol(ratingCol), transformedDf)
     )
   }
 
@@ -66,41 +62,6 @@ class SARSpec extends RankingTestBase with EstimatorFuzzing[SAR] {
     assert(recs.count == 2)
   }
 
-  test("SAR with string userCol and itemCol") {
-
-    val algo = sar
-      .setSupportThreshold(1)
-      .setSimilarityFunction("jacccard")
-      .setActivityTimeFormat("EEE MMM dd HH:mm:ss Z yyyy")
-
-    val adapter: RankingAdapter = new RankingAdapter()
-      .setK(5)
-      .setRecommender(algo)
-
-    val recopipeline = new Pipeline()
-      .setStages(Array(recommendationIndexer, adapter))
-      .fit(ratingsWithStrings)
-
-    val output = recopipeline.transform(ratingsWithStrings)
-
-    val evaluator: RankingEvaluator = new RankingEvaluator()
-      .setK(5)
-      .setNItems(10)
-
-    assert(evaluator.setMetricName("ndcgAt").evaluate(output) === 0.602819875812812)
-    assert(evaluator.setMetricName("fcp").evaluate(output) === 0.05 ||
-      evaluator.setMetricName("fcp").evaluate(output) === 0.1)
-    assert(evaluator.setMetricName("mrr").evaluate(output) === 1.0)
-
-    val users: DataFrame = spark
-      .createDataFrame(Seq(("user0","item0"),("user1","item1")))
-      .toDF(userColIndex, itemColIndex)
-
-    val recs = recopipeline.stages(1).asInstanceOf[RankingAdapterModel].getRecommenderModel
-      .asInstanceOf[SARModel].recommendForUserSubset(users, 10)
-    assert(recs.count == 2)
-  }
-
   lazy val testFile: String = getClass.getResource("/demoUsage.csv.gz").getPath
   lazy val simCount1: String = getClass.getResource("/sim_count1.csv.gz").getPath
   lazy val simLift1: String = getClass.getResource("/sim_lift1.csv.gz").getPath
@@ -154,12 +115,7 @@ class SARModelSpec extends RankingTestBase with TransformerFuzzing[SARModel] {
         .setUserCol(recommendationIndexer.getUserOutputCol)
         .setItemCol(recommendationIndexer.getItemOutputCol)
         .setRatingCol(ratingCol)
-        .fit(transformedDf), transformedDf),
-      new TestObject(new SAR()
-        .setUserCol(recommendationIndexer.getUserOutputCol)
-        .setItemCol(recommendationIndexer.getItemOutputCol)
-        .setRatingCol(ratingCol)
-        .fit(transformedDfWithStrings), transformedDfWithStrings)
+        .fit(transformedDf), transformedDf)
     )
   }