ai.h2o.sparkling.ml.params.HasInitialBiases.scala Maven / Gradle / Ivy
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* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
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package ai.h2o.sparkling.ml.params
import ai.h2o.sparkling.H2OFrame
import org.apache.spark.ml.linalg.DenseVector
trait HasInitialBiases extends H2OAlgoParamsBase {
private val initialBiases = new NullableVectorArrayParam(
this,
"initialBiases",
"A array of weight vectors to be used for bias initialization of every network layer." +
"If this parameter is set, the parameter 'initialWeights' has to be set as well.")
setDefault(initialBiases -> null)
def getInitialBiases(): Array[DenseVector] = $(initialBiases)
def setInitialBiases(value: Array[DenseVector]): this.type = set(initialBiases, value)
private[sparkling] def getInitialBiasesParam(trainingFrame: H2OFrame): Map[String, Any] = {
Map("initial_biases" -> convertVectorArrayToH2OFrameKeyArray(getInitialBiases()))
}
override private[sparkling] def getSWtoH2OParamNameMap(): Map[String, String] = {
super.getSWtoH2OParamNameMap() ++ Map("initialBiases" -> "initial_biases")
}
}