我正试图在Flink中实现一个自定义转换器,如下所示
its documentation
但当我试图执行的时候
fit
从未调用操作。这就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,当我在内部设置断点时
fitLabeledVectorInfoGain
,例如在行中
input.map
调试程序在那里停止,但是如果我在嵌套映射中也设置了断点,例如下面
println("INSIDE!!!")
它从不停在那里。
有人知道如何调试这个自定义转换器吗?