com.intel.analytics.bigdl.models.vgg

Utils

object Utils

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  1. case class TestParams(folder: String = "./", model: String = "", batchSize: Int = 112) extends Product with Serializable

  2. case class TrainParams(folder: String = "./", checkpoint: Option[String] = scala.None, modelSnapshot: Option[String] = scala.None, stateSnapshot: Option[String] = scala.None, summaryPath: Option[String] = scala.None, batchSize: Int = 112, maxEpoch: Int = 90, overWriteCheckpoint: Boolean = false, learningRate: Double = 0.01, weightDecay: Double = 5.0E-4, graphModel: Boolean = false, maxIteration: Int = 40000, momentum: Double = 0.9, dampening: Double = 0.0, nesterov: Boolean = true, classNumber: Int = 1000, env: String = "local", checkpointIteration: Int = 1000, maxLr: Double = 0.06, warmupEpoch: Option[Int] = scala.None, gradientL2NormThreshold: Option[Double] = scala.None, optimizerVersion: Option[String] = scala.None) extends Product with Serializable

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  18. val testMean: (Double, Double, Double)

  19. val testParser: OptionParser[TestParams]

  20. val testStd: (Double, Double, Double)

  21. def toString(): String

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  22. def trainDataSet(path: String, sc: SparkContext, imageSize: Int, batchSize: Int): BatchDataSet

  23. val trainMean: (Double, Double, Double)

  24. val trainParser: OptionParser[TrainParams]

  25. val trainStd: (Double, Double, Double)

  26. def valDataSet(path: String, sc: SparkContext, imageSize: Int, batchSize: Int): BatchDataSet

  27. final def wait(): Unit

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