Class

com.intel.analytics.bigdl.optim

Metrics

Related Doc: package optim

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class Metrics extends Serializable

Performance metrics for the training process. Beyond collect local metrics(e.g. throughput) in driver node, it can also be used to collect distributed metrics (e.g. time of some steps among the workers). The is useful for performance analysis.

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Instance Constructors

  1. new Metrics()

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Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. def add(name: String, value: Double): Metrics.this.type

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  5. final def asInstanceOf[T0]: T0

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  6. def clone(): AnyRef

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    protected[java.lang]
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  7. final def eq(arg0: AnyRef): Boolean

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  8. def equals(arg0: Any): Boolean

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  9. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )

  10. def get(name: String, number: Int): Array[Double]

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  11. def get(name: String): (Double, Int)

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  12. final def getClass(): Class[_]

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  13. def hashCode(): Int

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  14. final def isInstanceOf[T0]: Boolean

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  15. final def ne(arg0: AnyRef): Boolean

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  16. final def notify(): Unit

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  17. final def notifyAll(): Unit

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  18. def set(name: String, value: ArrayBuffer[Double], sc: SparkContext): Metrics.this.type

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  19. def set(name: String, value: Double, sc: SparkContext, parallel: Int): Metrics.this.type

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  20. def set(name: String, value: Double, parallel: Int = 1): Metrics.this.type

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  21. def summary(unit: String = "s", scale: Double = 1e9): String

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  22. final def synchronized[T0](arg0: ⇒ T0): T0

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  23. def toString(): String

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  24. final def wait(): Unit

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    @throws( ... )

  25. final def wait(arg0: Long, arg1: Int): Unit

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  26. final def wait(arg0: Long): Unit

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Inherited from Serializable

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