SPARK-8484. Styling.

prabeesh · Jul 9, 2015 · 3bc1853 · 3bc1853
1 parent 2aa6f43
commit 3bc1853
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Showing 2 changed files with 42 additions and 7 deletions.
diff --git a/mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala b/mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala
@@ -65,8 +65,6 @@ class TrainValidatorSplit(override val uid: String) extends Estimator[TrainValid
 
   def this() = this(Identifiable.randomUID("cv"))
 
-  private val f2jBLAS = new F2jBLAS
-
   /** @group setParam */
   def setEstimator(value: Estimator[_]): this.type = set(estimator, value)
 
@@ -104,6 +102,7 @@ class TrainValidatorSplit(override val uid: String) extends Estimator[TrainValid
     val validationDataset = sqlCtx.createDataFrame(validation, schema).cache()
 
     // multi-model training
+    logDebug(s"Train split with multiple sets of parameters.")
     val models = est.fit(trainingDataset, epm).asInstanceOf[Seq[Model[_]]]
     trainingDataset.unpersist()
     var i = 0

diff --git a/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala
@@ -18,13 +18,16 @@
 package org.apache.spark.ml.tuning
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.{Estimator, Model}
 import org.apache.spark.ml.classification.LogisticRegression
-import org.apache.spark.ml.evaluation.{BinaryClassificationEvaluator, RegressionEvaluator}
+import org.apache.spark.ml.evaluation.{BinaryClassificationEvaluator, Evaluator, RegressionEvaluator}
 import org.apache.spark.ml.param.ParamMap
+import org.apache.spark.ml.param.shared.HasInputCol
 import org.apache.spark.ml.regression.LinearRegression
-import org.apache.spark.ml.tuning.CrossValidatorSuite.{MyEvaluator, MyEstimator}
-import org.apache.spark.mllib.classification.LogisticRegressionSuite._
+import org.apache.spark.mllib.classification.LogisticRegressionSuite.generateLogisticInput
 import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext}
+import org.apache.spark.sql.DataFrame
+import org.apache.spark.sql.types.StructType
 
 class TrainValidationSplitSuite extends SparkFunSuite with MLlibTestSparkContext {
   test("train validation with logistic regression") {
@@ -81,6 +84,8 @@ class TrainValidationSplitSuite extends SparkFunSuite with MLlibTestSparkContext
   }
 
   test("validateParams should check estimatorParamMaps") {
+    import TrainValidationSplitSuite._
+
     val est = new MyEstimator("est")
     val eval = new MyEvaluator
     val paramMaps = new ParamGridBuilder()
@@ -97,7 +102,38 @@ class TrainValidationSplitSuite extends SparkFunSuite with MLlibTestSparkContext
     val invalidParamMaps = paramMaps :+ ParamMap(est.inputCol -> "")
     cv.setEstimatorParamMaps(invalidParamMaps)
     intercept[IllegalArgumentException] {
-        cv.validateParams()
+      cv.validateParams()
     }
   }
-}
+}
+
+object TrainValidationSplitSuite {
+
+  abstract class MyModel extends Model[MyModel]
+
+  class MyEstimator(override val uid: String) extends Estimator[MyModel] with HasInputCol {
+
+    override def validateParams(): Unit = require($(inputCol).nonEmpty)
+
+    override def fit(dataset: DataFrame): MyModel = {
+      throw new UnsupportedOperationException
+    }
+
+    override def transformSchema(schema: StructType): StructType = {
+      throw new UnsupportedOperationException
+    }
+
+    override def copy(extra: ParamMap): MyEstimator = defaultCopy(extra)
+  }
+
+  class MyEvaluator extends Evaluator {
+
+    override def evaluate(dataset: DataFrame): Double = {
+      throw new UnsupportedOperationException
+    }
+
+    override val uid: String = "eval"
+
+    override def copy(extra: ParamMap): MyEvaluator = defaultCopy(extra)
+  }
+}