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150 changes: 0 additions & 150 deletions
150
core/src/main/scala/com/eharmony/spotz/optimizer/HyperParameter.scala
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core/src/main/scala/com/eharmony/spotz/optimizer/hyperparam/Combinations.scala
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| package com.eharmony.spotz.optimizer.hyperparam | ||
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| import scala.util.Random | ||
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| trait CombinatoricRandomSampler[T] extends RandomSampler[Iterable[Iterable[T]]] | ||
| trait IterableRandomSampler[T] extends RandomSampler[Iterable[T]] | ||
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| /** | ||
| * | ||
| * @param iterable | ||
| * @param k | ||
| * @param x | ||
| * @param replacement | ||
| * @tparam T | ||
| */ | ||
| abstract class AbstractCombinations[T]( | ||
| iterable: Iterable[T], | ||
| k: Int, | ||
| x: Int = 1, | ||
| replacement: Boolean = false) extends Serializable { | ||
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| import org.paukov.combinatorics3.Generator | ||
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| import scala.collection.JavaConverters._ | ||
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| private val values = iterable.toSeq | ||
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| assert(k > 0, "k must be greater than 0") | ||
| assert(k <= values.length, s"k must be less than or equal to length of the iterable, ${values.length}") | ||
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| // TODO: This is hideous! Rewrite this to be more memory efficient by unranking combinations. For now, use a Java lib. | ||
| val combinations = Generator.combination(iterable.asJavaCollection).simple(k).asScala.toIndexedSeq.map(l => l.asScala.toIndexedSeq) | ||
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| /** | ||
| * | ||
| * @param rng | ||
| * @return | ||
| */ | ||
| def combos(rng: Random): Iterable[Iterable[T]] = { | ||
| if (replacement) { | ||
| Seq.fill(x)(combinations(rng.nextInt(combinations.size))) | ||
| } else { | ||
| val indices = collection.mutable.Set[Int]() | ||
| val numElements = scala.math.min(x, combinations.size) | ||
| val ret = new collection.mutable.ArrayBuffer[Iterable[T]](numElements) | ||
| while (indices.size < numElements) { | ||
| val index = rng.nextInt(combinations.size) | ||
| if (!indices.contains(index)) { | ||
| indices.add(index) | ||
| ret += combinations(index) | ||
| } | ||
| } | ||
| ret.toIndexedSeq | ||
| } | ||
| } | ||
| } | ||
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| /** | ||
| * Sample a single combination of K unordered items from the iterable of length N. | ||
| * | ||
| * @param iterable | ||
| * @param k | ||
| * @param replacement | ||
| * @tparam T | ||
| */ | ||
| case class Combination[T]( | ||
| iterable: Iterable[T], | ||
| k: Int, | ||
| replacement: Boolean = false) | ||
| extends AbstractCombinations[T](iterable, k, 1, replacement) with IterableRandomSampler[T] { | ||
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| override def apply(rng: Random): Iterable[T] = combos(rng).head | ||
| } | ||
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| /** | ||
| * Binomial coefficient implementation. Pick K unordered items from an Iterable of N items. | ||
| * Also known as N Choose K, where N is the size of an Iterable and K is the desired number | ||
| * of items to be chosen. This implementation will actually compute all the possible choices | ||
| * and return them as an Iterable. | ||
| * | ||
| * @param iterable an iterable of finite length | ||
| * @param k the number of items to choose | ||
| * @tparam T | ||
| */ | ||
| case class Combinations[T]( | ||
| iterable: Iterable[T], | ||
| k: Int, | ||
| x: Int = 1, | ||
| replacement: Boolean = false) | ||
| extends AbstractCombinations[T](iterable, k, x, replacement) with CombinatoricRandomSampler[T] { | ||
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| override def apply(rng: Random): Iterable[Iterable[T]] = combos(rng) | ||
| } |
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core/src/main/scala/com/eharmony/spotz/optimizer/hyperparam/NormalDistribution.scala
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| import com.eharmony.spotz.optimizer.hyperparam.RandomSampler | ||
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| import scala.util.Random | ||
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| /** | ||
| * Sample from a normal distribution given the mean and standard deviation | ||
| * | ||
| * {{{ | ||
| * val hyperParamSpace = Map( | ||
| * ("x1", NormalDistribution(0, 0.1)) | ||
| * ) | ||
| * }}} | ||
| * | ||
| * @param mean mean | ||
| * @param std standard deviation | ||
| */ | ||
| case class NormalDistribution(mean: Double, std: Double) extends RandomSampler[Double] { | ||
| override def apply(rng: Random): Double = { | ||
| std * rng.nextGaussian() + mean | ||
| } | ||
| } |
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core/src/main/scala/com/eharmony/spotz/optimizer/hyperparam/RandomChoice.scala
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| package com.eharmony.spotz.optimizer.hyperparam | ||
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| import scala.util.Random | ||
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| /** | ||
| * Sample an element from an Iterable of fixed length with uniform random distribution. | ||
| * | ||
| * {{{ | ||
| * val hyperParamSpace = Map( | ||
| * ("x1", RandomChoice(Seq("svm", "logistic"))) | ||
| * ) | ||
| * }}} | ||
| * | ||
| * @param iterable an iterable of type T | ||
| * @tparam T type parameter of iterable | ||
| */ | ||
| case class RandomChoice[T](iterable: Iterable[T]) extends RandomSampler[T] { | ||
| private val values = iterable.toIndexedSeq | ||
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| if (values.length < 1) | ||
| throw new IllegalArgumentException("Empty iterable") | ||
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| override def apply(rng: Random): T = values(rng.nextInt(values.length)) | ||
| } |
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