PhillHenry commented on a change in pull request #31535: URL: https://github.com/apache/spark/pull/31535#discussion_r575104665
########## File path: mllib/src/main/scala/org/apache/spark/ml/tuning/ParamRandomBuilder.scala ########## @@ -0,0 +1,145 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * 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 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ml.tuning + +import org.apache.spark.annotation.Since +import org.apache.spark.ml.param._ + +case class Limits[T: Numeric](x: T, y: T) + +abstract class RandomT[T: Numeric] { + def randomT(): T + def randomTLog(n: Int): T +} + +abstract class Generator[T: Numeric] { + def apply(lim: Limits[T]): RandomT[T] +} + +object RandomRanges { + + val rnd = new scala.util.Random + + private[tuning] def randomBigInt0To(x: BigInt): BigInt = { + var randVal = BigInt(x.bitLength, rnd) + while (randVal > x) { + randVal = BigInt(x.bitLength, rnd) + } + randVal + } + + def bigIntBetween(lower: BigInt, upper: BigInt): BigInt = { + val diff: BigInt = upper - lower + randomBigInt0To(diff) + lower + } + + private def randomBigDecimalBetween(lower: BigDecimal, upper: BigDecimal): BigDecimal = { + val zeroCenteredRnd: BigDecimal = BigDecimal(rnd.nextDouble() - 0.5) + val range: BigDecimal = upper - lower + val halfWay: BigDecimal = lower + range / 2 + (zeroCenteredRnd * range) + halfWay + } + + implicit object DoubleGenerator extends Generator[Double] { + def apply(limits: Limits[Double]): RandomT[Double] = new RandomT[Double] { + import limits._ + val lower: Double = math.min(x, y) + val upper: Double = math.max(x, y) + + override def randomTLog(n: Int): Double = + RandomRanges.randomLog(lower, upper, n) + + override def randomT(): Double = + randomBigDecimalBetween(BigDecimal(lower), BigDecimal(upper)).doubleValue + } + } + + implicit object FloatGenerator extends Generator[Float] { + def apply(limits: Limits[Float]): RandomT[Float] = new RandomT[Float] { + import limits._ + val lower: Float = math.min(x, y) + val upper: Float = math.max(x, y) + + override def randomTLog(n: Int): Float = + RandomRanges.randomLog(lower, upper, n).toFloat + + override def randomT(): Float = + randomBigDecimalBetween(BigDecimal(lower), BigDecimal(upper)).floatValue + } + } + + implicit object IntGenerator extends Generator[Int] { + def apply(limits: Limits[Int]): RandomT[Int] = new RandomT[Int] { + import limits._ + val lower: Int = math.min(x, y) + val upper: Int = math.max(x, y) + + override def randomTLog(n: Int): Int = + RandomRanges.randomLog(lower, upper, n).toInt + + override def randomT(): Int = + bigIntBetween(BigInt(lower), BigInt(upper)).intValue + } + } + + implicit object LongGenerator extends Generator[Long] { Review comment: I included it for completeness. I can remove it if you like. ########## File path: mllib/src/main/scala/org/apache/spark/ml/tuning/ParamRandomBuilder.scala ########## @@ -0,0 +1,145 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * 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 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ml.tuning + +import org.apache.spark.annotation.Since +import org.apache.spark.ml.param._ + +case class Limits[T: Numeric](x: T, y: T) + +abstract class RandomT[T: Numeric] { + def randomT(): T + def randomTLog(n: Int): T +} + +abstract class Generator[T: Numeric] { + def apply(lim: Limits[T]): RandomT[T] +} + +object RandomRanges { + + val rnd = new scala.util.Random + + private[tuning] def randomBigInt0To(x: BigInt): BigInt = { + var randVal = BigInt(x.bitLength, rnd) + while (randVal > x) { + randVal = BigInt(x.bitLength, rnd) + } + randVal + } + + def bigIntBetween(lower: BigInt, upper: BigInt): BigInt = { + val diff: BigInt = upper - lower + randomBigInt0To(diff) + lower + } + + private def randomBigDecimalBetween(lower: BigDecimal, upper: BigDecimal): BigDecimal = { + val zeroCenteredRnd: BigDecimal = BigDecimal(rnd.nextDouble() - 0.5) + val range: BigDecimal = upper - lower + val halfWay: BigDecimal = lower + range / 2 + (zeroCenteredRnd * range) + halfWay + } + + implicit object DoubleGenerator extends Generator[Double] { + def apply(limits: Limits[Double]): RandomT[Double] = new RandomT[Double] { + import limits._ + val lower: Double = math.min(x, y) + val upper: Double = math.max(x, y) + + override def randomTLog(n: Int): Double = + RandomRanges.randomLog(lower, upper, n) + + override def randomT(): Double = + randomBigDecimalBetween(BigDecimal(lower), BigDecimal(upper)).doubleValue + } + } + + implicit object FloatGenerator extends Generator[Float] { + def apply(limits: Limits[Float]): RandomT[Float] = new RandomT[Float] { + import limits._ + val lower: Float = math.min(x, y) + val upper: Float = math.max(x, y) + + override def randomTLog(n: Int): Float = + RandomRanges.randomLog(lower, upper, n).toFloat + + override def randomT(): Float = + randomBigDecimalBetween(BigDecimal(lower), BigDecimal(upper)).floatValue + } + } + + implicit object IntGenerator extends Generator[Int] { + def apply(limits: Limits[Int]): RandomT[Int] = new RandomT[Int] { + import limits._ + val lower: Int = math.min(x, y) + val upper: Int = math.max(x, y) + + override def randomTLog(n: Int): Int = + RandomRanges.randomLog(lower, upper, n).toInt + + override def randomT(): Int = + bigIntBetween(BigInt(lower), BigInt(upper)).intValue + } + } + + implicit object LongGenerator extends Generator[Long] { + def apply(limits: Limits[Long]): RandomT[Long] = new RandomT[Long] { + import limits._ + val lower: Long = math.min(x, y) + val upper: Long = math.max(x, y) + + override def randomTLog(n: Int): Long = + RandomRanges.randomLog(lower, upper, n).toLong + + override def randomT(): Long = + bigIntBetween(BigInt(lower), BigInt(upper)).longValue + } + } + + def logN(x: Double, base: Int): Double = math.log(x) / math.log(base) + + def randomLog(lower: Double, upper: Double, n: Int): Double = { + val logLower: Double = logN(lower, n) + val logUpper: Double = logN(upper, n) + val logLimits: Limits[Double] = Limits(logLower, logUpper) + val rndLogged: RandomT[Double] = RandomRanges(logLimits) + math.pow(n, rndLogged.randomT()) + } + + def apply[T: Generator](lim: Limits[T])(implicit t: Generator[T]): RandomT[T] = t(lim) + +} + +/** + * "For any distribution over a sample space with a finite maximum, the maximum of 60 random + * observations lies within the top 5% of the true maximum, with 95% probability" + * - Evaluating Machine Learning Models by Alice Zheng + * https://www.oreilly.com/library/view/evaluating-machine-learning/9781492048756/ch04.html + * + * Note: if you want more sophisticated hyperparameter tuning, consider Python libraries + * such as Hyperopt. + */ +@Since("3.1.0") Review comment: Done. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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