我试图在flink中实现一个定制的转换器，但当我试图执行它时，它似乎 fit 操作从未被调用。以下是我迄今为止所做的：

class InfoGainTransformer extends Transformer[InfoGainTransformer] {
  import InfoGainTransformer._
  private[this] var counts: Option[collection.immutable.Vector[Map[Key, Double]]] = None
  // here setters for params, as Flink does
}
object InfoGainTransformer {
  // ====================================== Parameters =============================================
  // ...
  // ==================================== Factory methods ==========================================
  // ...
  // ========================================== Operations =========================================
  implicit def fitLabeledVectorInfoGain = new FitOperation[InfoGainTransformer, LabeledVector] {
    override def fit(instance: InfoGainTransformer, fitParameters: ParameterMap, input: DataSet[LabeledVector]): Unit = {
      val counts = collection.immutable.Vector[Map[Key, Double]]()
      input.map {
        v =>
          v.vector.map {
            case (i, value) =>
              println("INSIDE!!!")
              val key = Key(value, v.label)
              val cval = counts(i).getOrElse(key, .0)
              counts(i) + (key -> cval)
          }
      }
    }
  }
  implicit def fitVectorInfoGain[T <: Vector] = new FitOperation[InfoGainTransformer, T] {
    override def fit(instance: InfoGainTransformer, fitParameters: ParameterMap, input: DataSet[T]): Unit = {
      input
    }
  }
  implicit def transformLabeledVectorsInfoGain = {
    new TransformDataSetOperation[InfoGainTransformer, LabeledVector, LabeledVector] {
      override def transformDataSet(
                                     instance: InfoGainTransformer,
                                     transformParameters: ParameterMap,
                                     input: DataSet[LabeledVector]): DataSet[LabeledVector] = input
    }
  }
  implicit def transformVectorsInfoGain[T <: Vector : BreezeVectorConverter : TypeInformation : ClassTag] = {
    new TransformDataSetOperation[InfoGainTransformer, T, T] {
      override def transformDataSet(instance: InfoGainTransformer, transformParameters: ParameterMap, input: DataSet[T]): DataSet[T] = input
    }
  }
}

然后我试着用两种方法：

val scaler = StandardScaler()
val polyFeatures = PolynomialFeatures()
val mlr = MultipleLinearRegression()
val gain = InfoGainTransformer().setK(2)
// Construct the pipeline
val pipeline = scaler
  .chainTransformer(polyFeatures)
  .chainTransformer(gain)
  .chainPredictor(mlr)
val r = pipeline.predict(dataSet map (_.vector))
r.print()

只有我的变压器：

pipeline.fit(dataSet)

在这两种情况下，当我在 fitLabeledVectorInfoGain ，例如在 input.map ，调试器在那里停止，但是如果我也在嵌套Map中设置断点，例如bellow println("INSIDE!!!") ，它永远不会停在那里。
有人知道我如何调试这个自定义转换器吗？