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Я продолжаю испытывать некоторые странные ошибки при использовании разных значений для параметра слоев [] для MultilayerPerceptronClassifier.МногослойныйПерсопротектор в искры. Слои и странные ошибки

например. для тех же данных:

int[] layers = {100, 98, 2} 
new MultilayerPerceptronClassifier().setLayers(layers).setLabelCol(targetColumn).fit(data); 

я получаю: java.lang.ArrayIndexOutOfBoundsException

With stack trace: 
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1442) 
     at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1441) 
     at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) 
     at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) 
     at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1441) 
     at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) 
     at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) 
     at scala.Option.foreach(Option.scala:257) 
     at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811) 
     at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1667) 
     at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1622) 
     at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1611) 
     at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) 
     at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632) 
     at org.apache.spark.SparkContext.runJob(SparkContext.scala:1890) 
     at org.apache.spark.SparkContext.runJob(SparkContext.scala:1903) 
     at org.apache.spark.SparkContext.runJob(SparkContext.scala:1916) 
     at org.apache.spark.SparkContext.runJob(SparkContext.scala:1930) 
     at org.apache.spark.rdd.RDD.count(RDD.scala:1134) 
     at org.apache.spark.mllib.optimization.LBFGS$.runLBFGS(LBFGS.scala:195) 
     at org.apache.spark.mllib.optimization.LBFGS.optimize(LBFGS.scala:142) 
     at org.apache.spark.ml.ann.FeedForwardTrainer.train(Layer.scala:819) 
     at org.apache.spark.ml.classification.MultilayerPerceptronClassifier.train(MultilayerPerceptronClassifier.scala:262) 
     at org.apache.spark.ml.classification.MultilayerPerceptronClassifier.train(MultilayerPerceptronClassifier.scala:147) 

Теперь я переключение на

int[] layers = {10,8,2} 

все кажется работает. Теперь следующая попытка:

int[] layers = {9,6,2} 

И получил выход, который выглядит гораздо более странно:

org.apache.spark.SparkException: Failed to execute user defined function($anonfun$1: (vector) => double) 
     at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) 
     at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) 
     at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370) 
     at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246) 
     at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240) 
     at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803) 
     at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803) 
     at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
     at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) 
     at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) 
     at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) 
     at org.apache.spark.scheduler.Task.run(Task.scala:86) 
     at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) 
     at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) 
     at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) 
     at java.lang.Thread.run(Thread.java:745) 
Caused by: java.lang.IllegalArgumentException: requirement failed: A & B Dimension mismatch! 
     at scala.Predef$.require(Predef.scala:224) 
     at org.apache.spark.ml.ann.BreezeUtil$.dgemm(BreezeUtil.scala:41) 
     at org.apache.spark.ml.ann.AffineLayerModel.eval(Layer.scala:164) 
     at org.apache.spark.ml.ann.FeedForwardModel.forward(Layer.scala:483) 
     at org.apache.spark.ml.ann.FeedForwardModel.predict(Layer.scala:530) 
     at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:322) 
     at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:296) 
     at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:187) 
     at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:186) 
     ... 16 more 
17/02/08 12:55:34 WARN TaskSetManager: Lost task 0.0 in stage 68.0 (TID 68, localhost): org.apache.spark.SparkException: Failed to execute user defined function($anonfun$1: (vector) => double) 
     at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) 
     at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) 
     at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370) 
     at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246) 
     at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240) 
     at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803) 
     at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803) 
     at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
     at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) 
     at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) 
     at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) 
     at org.apache.spark.scheduler.Task.run(Task.scala:86) 
     at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) 
     at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) 
     at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) 
     at java.lang.Thread.run(Thread.java:745) 
Caused by: java.lang.IllegalArgumentException: requirement failed: A & B Dimension mismatch! 
     at scala.Predef$.require(Predef.scala:224) 
     at org.apache.spark.ml.ann.BreezeUtil$.dgemm(BreezeUtil.scala:41) 
     at org.apache.spark.ml.ann.AffineLayerModel.eval(Layer.scala:164) 
     at org.apache.spark.ml.ann.FeedForwardModel.forward(Layer.scala:483) 
     at org.apache.spark.ml.ann.FeedForwardModel.predict(Layer.scala:530) 
     at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:322) 
     at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:296) 
     at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:187) 
     at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:186) 
     ... 16 more 

17/02/08 12:55:34 ERROR TaskSetManager: Task 0 in stage 68.0 failed 1 times; aborting job 
17/02/08 12:55:34 INFO TaskSchedulerImpl: Removed TaskSet 68.0, whose tasks have all completed, from pool 
17/02/08 12:55:34 INFO TaskSchedulerImpl: Cancelling stage 68 
17/02/08 12:55:34 INFO DAGScheduler: ResultStage 68 (show at DataPipeline.java:213) failed in 0,910 s 
17/02/08 12:55:34 INFO DAGScheduler: Job 67 failed: show at DataPipeline.java:213, took 0,914385 s 
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 68.0 failed 1 times, most recent failure: Lost task 0.0 in stage 68.0 (TID 68, localhost): org.apache.spark.SparkException: Failed to execute user defined function($anonfun$1: (vector) => double) 
     at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) 
     at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) 
     at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370) 
     at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246) 
     at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240) 
     at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803) 
     at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803) 
     at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
     at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) 
     at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) 
     at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) 
     at org.apache.spark.scheduler.Task.run(Task.scala:86) 
     at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) 
     at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) 
     at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) 
     at java.lang.Thread.run(Thread.java:745) 
Caused by: java.lang.IllegalArgumentException: requirement failed: A & B Dimension mismatch! 
     at scala.Predef$.require(Predef.scala:224) 
     at org.apache.spark.ml.ann.BreezeUtil$.dgemm(BreezeUtil.scala:41) 
     at org.apache.spark.ml.ann.AffineLayerModel.eval(Layer.scala:164) 
     at org.apache.spark.ml.ann.FeedForwardModel.forward(Layer.scala:483) 
     at org.apache.spark.ml.ann.FeedForwardModel.predict(Layer.scala:530) 
     at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:322) 
     at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:296) 
     at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:187) 
     at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:186) 
     ... 16 more 

Driver stacktrace: 
     at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1454) 
     at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1442) 
     at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1441) 
     at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) 
     at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) 
     at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1441) 
     at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) 
     at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) 
     at scala.Option.foreach(Option.scala:257) 
     at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811) 
     at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1667) 
     at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1622) 
     at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1611) 
     at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) 
     at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632) 
     at org.apache.spark.SparkContext.runJob(SparkContext.scala:1890) 
     at org.apache.spark.SparkContext.runJob(SparkContext.scala:1903) 
     at org.apache.spark.SparkContext.runJob(SparkContext.scala:1916) 
     at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:347) 
     at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:39) 
     at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2193) 
     at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) 
     at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2546) 
     at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2192) 
     at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2199) 
     at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1935) 
     at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1934) 
     at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2576) 
     at org.apache.spark.sql.Dataset.head(Dataset.scala:1934) 
     at org.apache.spark.sql.Dataset.take(Dataset.scala:2149) 
     at org.apache.spark.sql.Dataset.showString(Dataset.scala:239) 
     at org.apache.spark.sql.Dataset.show(Dataset.scala:526) 
     at org.apache.spark.sql.Dataset.show(Dataset.scala:486) 
     at org.apache.spark.sql.Dataset.show(Dataset.scala:495) 
     at org.sparkexample.DataPipeline.trainNeuralNetwork(DataPipeline.java:213) 
     at org.sparkexample.DataPipeline.selectModel(DataPipeline.java:184) 
     at org.sparkexample.DataPipeline.main(DataPipeline.java:131) 
     at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) 
     at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) 
     at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) 
     at java.lang.reflect.Method.invoke(Method.java:498) 
     at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:736) 
     at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:185) 
     at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210) 
     at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124) 
     at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) 
Caused by: org.apache.spark.SparkException: Failed to execute user defined function($anonfun$1: (vector) => double) 
     at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) 
     at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) 
     at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370) 
     at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246) 
     at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240) 
     at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803) 
     at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803) 
     at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
     at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) 
     at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) 
     at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) 
     at org.apache.spark.scheduler.Task.run(Task.scala:86) 
     at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) 
     at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) 
     at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) 
     at java.lang.Thread.run(Thread.java:745) 
Caused by: java.lang.IllegalArgumentException: requirement failed: A & B Dimension mismatch! 
     at scala.Predef$.require(Predef.scala:224) 
     at org.apache.spark.ml.ann.BreezeUtil$.dgemm(BreezeUtil.scala:41) 
     at org.apache.spark.ml.ann.AffineLayerModel.eval(Layer.scala:164) 
     at org.apache.spark.ml.ann.FeedForwardModel.forward(Layer.scala:483) 
     at org.apache.spark.ml.ann.FeedForwardModel.predict(Layer.scala:530) 
     at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:322) 
     at org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel.predict(MultilayerPerceptronClassifier.scala:296) 
     at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:187) 
     at org.apache.spark.ml.PredictionModel$$anonfun$1.apply(Predictor.scala:186) 
     ... 16 more 

Так что же я должен перейти на слои. Из документов я вижу, что в основном последний параметр - это число классов, а остальные - произвольный массив разных нейронов.

Реальное количество функций, которые у меня есть и проходят как 1 особенность вектора является 9

ответ

0

Найдено экспериментально, что запрашиваемое количество нейронов для ввода является

numFeatures + 1

Так мое предположение заключается в том, что +1 является результатом предсказанияCol.

Странно, так как Prepare data for MultilayerPerceptronClassifier in scala рекомендует только numFeatures количество нейронов

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