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object TensorLogger extends Serializable

Utility to periodically log active tensors See lamp.data.TensorLogger#start

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  6. def detailAllTensorOptions(logger: (String) => Unit): Unit
  7. def detailAllTensors(logger: (String) => Unit): Unit
  8. final def eq(arg0: AnyRef): Boolean
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  9. def equals(arg0: AnyRef): Boolean
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  10. def formatLine(data: TensorTraceData): String
  11. def formatStackTrace(data: TensorTraceData): String
  12. final def getClass(): Class[_ <: AnyRef]
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  15. def logTensorOptions(logger: (String) => Unit, filter: (TensorTraceData, Double) => Boolean, detailMinMs: Double, detailMaxMs: Double, detailNum: Int): Unit
  16. def logTensors(logger: (String) => Unit, filter: (TensorTraceData, Double) => Boolean, detailMinMs: Double, detailMaxMs: Double, detailNum: Int): Unit
  17. def makeLog(nanoTime: Long, data: Seq[TensorTraceData], filter: (TensorTraceData, Double) => Boolean, detailMinMs: Double, detailMaxMs: Double, detailNum: Int): String
  18. def makeStatistic(nanoTime: Long, actives: Seq[TensorTraceData])(filter: (TensorTraceData, Double) => Boolean): (List[(Double, Double, Int)], Seq[(TensorTraceData, Double)], Map[Boolean, Long])
  19. final def ne(arg0: AnyRef): Boolean
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  20. final def notify(): Unit
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  21. final def notifyAll(): Unit
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  22. def queryActiveTensorOptions(): Vector[TensorTraceData]
  23. def queryActiveTensors(): Vector[TensorTraceData]
  24. def start(frequency: FiniteDuration = 5 seconds)(logger: (String) => Unit, filter: (TensorTraceData, Double) => Boolean, detailMinMs: Double, detailMaxMs: Double, detailNum: Int): TensorLogger

    Log active tensors with a given frequency

    Log active tensors with a given frequency

    The log string itself consists of a summary statistics of active tensors and a list of detailed information on some number of active tensors. The detailed information shows the stack trace where the tensor was allocated. The tensors eligible for detail are specified by a filter on their lifetime.

    This method will spawn a new Thread, which repeatedly logs and sleeps until not canceled.

    frequency

    the frequency with which the logging will occur

    logger

    a side effecting lambda which executes the log

    filter

    a predicate taking some information about the tensor and the lifetime of the tensor in milliseconds

    detailMinMs

    minimum lifetime in milliseconds for a tensor to be eligible for detailed logging

    detailMaxMs

    maximum lifetime in milliseconds for a tensor to be eligible for detailed logging

    detailNum

    max number of tensors in the detailed section

    returns

    an instance of TensorLogger whose sole purpose is its cancel() method which stops the logger

  25. final def synchronized[T0](arg0: => T0): T0
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  26. def toString(): String
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  27. final def wait(arg0: Long, arg1: Int): Unit
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  28. final def wait(arg0: Long): Unit
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  29. final def wait(): Unit
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  1. def finalize(): Unit
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    Deprecated

    (Since version 9)

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