object TensorLogger extends Serializable
Utility to periodically log active tensors See lamp.data.TensorLogger#start
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- def detailAllTensorOptions(logger: (String) => Unit): Unit
- def detailAllTensors(logger: (String) => Unit): Unit
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- def formatLine(data: TensorTraceData): String
- def formatStackTrace(data: TensorTraceData): String
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- def logTensorOptions(logger: (String) => Unit, filter: (TensorTraceData, Double) => Boolean, detailMinMs: Double, detailMaxMs: Double, detailNum: Int): Unit
- def logTensors(logger: (String) => Unit, filter: (TensorTraceData, Double) => Boolean, detailMinMs: Double, detailMaxMs: Double, detailNum: Int): Unit
- def makeLog(nanoTime: Long, data: Seq[TensorTraceData], filter: (TensorTraceData, Double) => Boolean, detailMinMs: Double, detailMaxMs: Double, detailNum: Int): String
- def makeStatistic(nanoTime: Long, actives: Seq[TensorTraceData])(filter: (TensorTraceData, Double) => Boolean): (List[(Double, Double, Int)], Seq[(TensorTraceData, Double)], Map[Boolean, Long])
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- def queryActiveTensorOptions(): Vector[TensorTraceData]
- def queryActiveTensors(): Vector[TensorTraceData]
- 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
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- Deprecated
(Since version 9)