Name: java.lang.ClassCastExceptionMessage: [Lcom.salesforce.op.stages.impl.feature.TextStats; cannot be cast to [Lcom.salesforce.op.stages.impl.feature.TextStats;

// sbt-assembly excludes packages tagged "provided" as belowvalsparkVersion="2.4.4"valscalaTestVersion="3.0.8"libraryDependencies++=Seq("org.scalatest"%%"scalatest"% scalaTestVersion,"org.apache.spark"%%"spark-core"% sparkVersion%"provided","org.apache.spark"%%"spark-mllib"% sparkVersion%"provided","org.apache.spark"%%"spark-sql"% sparkVersion%"provided","com.salesforce.transmogrifai"%%"transmogrifai-core"%"0.7.0")

objectSimpleLauncher {defrun (inputDf:DataFrame,targetCol:String):Unit= {implicitvalspark:SparkSession= getSparkSession(false,"Transmogifai Simple Launcher")        println("Yarn application id:"+ spark.sparkContext.getConf.getAppId)importspark.implicits._// Automated feature engineeringval (target, features)=FeatureBuilder.fromDataFrame[RealNN](inputDf, response= targetCol)valfeatureVector:FeatureLike[OPVector]= features.transmogrify()// Automated feature selectionvalcheckedFeatures:FeatureLike[OPVector]= target.sanityCheck(featureVector, checkSample=1.0, removeBadFeatures=true)// Define the model we want to use (here a simple logistic regression) and get the resulting outputvalprediction:FeatureLike[Prediction]=BinaryClassificationModelSelector.withTrainValidationSplit(            modelTypesToUse=Seq(OpLogisticRegression)        ).setInput(target, checkedFeatures).getOutput()valmodel:OpWorkflowModel=newOpWorkflow().setInputDataset(inputDf).setResultFeatures(prediction).train()        println("Model summary:\n"+ model.summaryPretty())    }}

  test("Titanic simple") {importspark.implicits._// Read Titanic data as a DataFramevalcsvFilePath:String="src/test/resources/data/PassengerDataAll.csv"valpassengersData:DataFrame=DataReaders.Simple.csvCase[Passenger](path=Option(csvFilePath), key= _.id.toString)      .readDataset().toDF()valtruncatedData= passengersData.select("name","age","survived")    truncatedData.show()    truncatedData.printSchema()SimpleLauncher.run(truncatedData,"survived")  }

valpassengers= spark.read.schema(schema)   .option("header","true")   .csv("path_to_csv)SimpleLauncher.run(passengers,"survived")

Name: java.lang.ClassCastExceptionMessage: [Lcom.salesforce.op.stages.impl.feature.TextStats; cannot be cast to [Lcom.salesforce.op.stages.impl.feature.TextStats;StackTrace:   at com.salesforce.op.stages.impl.feature.SmartTextVectorizer.fitFn(SmartTextVectorizer.scala:91)  at com.salesforce.op.stages.base.sequence.SequenceEstimator.fit(SequenceEstimator.scala:99)  at com.salesforce.op.stages.base.sequence.SequenceEstimator.fit(SequenceEstimator.scala:57)  at com.salesforce.op.utils.stages.FitStagesUtil$$anonfun$20.apply(FitStagesUtil.scala:264)  at com.salesforce.op.utils.stages.FitStagesUtil$$anonfun$20.apply(FitStagesUtil.scala:263)  at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)  at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)  at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)  at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)  at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)  at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:186)  at com.salesforce.op.utils.stages.FitStagesUtil$.com$salesforce$op$utils$stages$FitStagesUtil$$fitAndTransformLayer(FitStagesUtil.scala:263)  at com.salesforce.op.utils.stages.FitStagesUtil$$anonfun$17.apply(FitStagesUtil.scala:226)  at com.salesforce.op.utils.stages.FitStagesUtil$$anonfun$17.apply(FitStagesUtil.scala:224)  at scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:57)  at scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:66)  at scala.collection.mutable.ArrayOps$ofRef.foldLeft(ArrayOps.scala:186)  at com.salesforce.op.utils.stages.FitStagesUtil$.fitAndTransformDAG(FitStagesUtil.scala:224)  at com.salesforce.op.OpWorkflow.fitStages(OpWorkflow.scala:407)  at com.salesforce.op.OpWorkflow.train(OpWorkflow.scala:354)  at launchers.SimpleLauncher$.run(SimpleLauncher.scala:35)