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Progress bar added to learn and populate functions #485

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Progress bar added to learn and populate functions #485

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3 changes: 2 additions & 1 deletion build.sbt
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Original file line number Diff line number Diff line change
Expand Up @@ -66,7 +66,8 @@ lazy val commonSettings = Seq(
"com.gurobi" % "gurobi" % "6.0",
"org.apache.commons" % "commons-math3" % "3.0",
"org.scalatest" % "scalatest_2.11" % "2.2.4",
"ch.qos.logback" % "logback-classic" % "1.1.7"
"ch.qos.logback" % "logback-classic" % "1.1.7",
"me.tongfei" % "progressbar" % "0.5.5"
),
fork := true,
connectInput in run := true,
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13 changes: 10 additions & 3 deletions saul-core/src/main/scala/edu/illinois/cs/cogcomp/saul/classifier/Learnable.scala
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Expand Up @@ -24,6 +24,7 @@ import edu.illinois.cs.cogcomp.saul.lbjrelated.LBJLearnerEquivalent
import edu.illinois.cs.cogcomp.saul.parser.{ IterableToLBJavaParser, LBJavaParserToIterable }
import edu.illinois.cs.cogcomp.saul.test.TestReal
import edu.illinois.cs.cogcomp.saul.util.Logging
import me.tongfei.progressbar.ProgressBar

import scala.reflect.ClassTag

Expand Down Expand Up @@ -226,24 +227,28 @@ abstract class Learnable[T <: AnyRef](val node: Node[T], val parameters: Paramet
logger.debug(classifier.getExtractor.getCompositeChildren.toString)
logger.debug(classifier.getLabeler.toString)
logger.info(s"Learnable: Learn with data of size ${data.size}")
logger.info(s"Training: $iteration iterations remain.")

isTraining = true
val pb = new ProgressBar("Training", iteration)
pb.start()

(iteration to 1 by -1).foreach(remainingIteration => {
if (remainingIteration % 10 == 0)
logger.info(s"Training: $remainingIteration iterations remain.")

node.clearPropertyCache()
data.foreach(classifier.learn)
pb.step()
})

pb.stop()
classifier.doneLearning()
isTraining = false
}

def learnWithDerivedInstances(numIterations: Int, featureVectors: Iterable[FeatureVector]): Unit = {
isTraining = true
val pb = new ProgressBar("Training", numIterations)
pb.start()

val propertyNameSet = feature.map(_.name).toSet
(0 until numIterations).foreach { _ =>
featureVectors.foreach {
Expand All @@ -262,7 +267,9 @@ abstract class Learnable[T <: AnyRef](val node: Node[T], val parameters: Paramet
}
classifier.learn(featureVector)
}
pb.step()
}
pb.stop()
classifier.doneLearning()
isTraining = false
}
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11 changes: 9 additions & 2 deletions saul-core/src/main/scala/edu/illinois/cs/cogcomp/saul/datamodel/node/Node.scala
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Expand Up @@ -12,9 +12,10 @@ import edu.illinois.cs.cogcomp.saul.datamodel.edge.Edge
import edu.illinois.cs.cogcomp.saul.datamodel.property.Property
import edu.illinois.cs.cogcomp.saul.datamodel.property.features.discrete.DiscreteProperty
import edu.illinois.cs.cogcomp.saul.util.Logging

import java.util.concurrent.atomic.AtomicInteger

import me.tongfei.progressbar.ProgressBar

import scala.collection.mutable
import scala.collection.mutable.{ ArrayBuffer, ListBuffer, HashMap => MutableHashMap, LinkedHashSet => MutableSet, Map => MutableMap }
import scala.reflect.ClassTag
Expand Down Expand Up @@ -156,7 +157,13 @@ class Node[T <: AnyRef](val keyFunc: T => Any = (x: T) => x, val tag: ClassTag[T
populateEdge: Boolean = true,
populateJoinNodes: Boolean = true
): Unit = {
ts.foreach(addInstance(_, train, populateEdge, populateJoinNodes))
val pb = new ProgressBar("Population", ts.size)
pb.start()
ts.foreach(i => {
addInstance(i, train, populateEdge, populateJoinNodes)
pb.step()
})
pb.stop()
}

/** Relational operators */
Expand Down