com.intel.analytics.bigdl.optim

LocalOptimizer

class LocalOptimizer[T] extends Optimizer[T, MiniBatch[T]]

Optimize a model on a single machine

Linear Supertypes
Optimizer[T, MiniBatch[T]], AnyRef, Any
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Value Members

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

    Definition Classes
    AnyRef
  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  7. var checkSingleton: Boolean

    Attributes
    protected
    Definition Classes
    Optimizer
  8. var checkpointPath: Option[String]

    Attributes
    protected
    Definition Classes
    Optimizer
  9. var checkpointTrigger: Option[Trigger]

    Attributes
    protected
    Definition Classes
    Optimizer
  10. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  11. var computeThresholdbatchSize: Int

    Attributes
    protected
    Definition Classes
    Optimizer
  12. var dropPercentage: Double

    Attributes
    protected
    Definition Classes
    Optimizer
  13. var endWhen: Trigger

    Attributes
    protected
    Definition Classes
    Optimizer
  14. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  15. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  16. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  17. def getCheckpointPath(): Option[String]

    Get the directory of saving checkpoint

    Get the directory of saving checkpoint

    Definition Classes
    Optimizer
  18. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  19. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  20. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  21. var isOverWrite: Boolean

    Attributes
    protected
    Definition Classes
    Optimizer
  22. var maxDropPercentage: Double

    Attributes
    protected
    Definition Classes
    Optimizer
  23. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  24. final def notify(): Unit

    Definition Classes
    AnyRef
  25. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  26. var optimMethod: OptimMethod[T]

    Attributes
    protected
    Definition Classes
    Optimizer
  27. def optimize(): Module[T]

    Trigger the optimization process

    Trigger the optimization process

    returns

    the model to be trained

    Definition Classes
    LocalOptimizerOptimizer
  28. def overWriteCheckpoint(): LocalOptimizer.this.type

    Enable overwrite saving checkpoint

    Enable overwrite saving checkpoint

    Definition Classes
    Optimizer
  29. def prepareInput(): Unit

    Definition Classes
    Optimizer
  30. def setCheckpoint(path: String, trigger: Trigger): LocalOptimizer.this.type

    Set a check point saved at path triggered by trigger

    Set a check point saved at path triggered by trigger

    path

    the directory to save

    trigger

    how often to save the check point

    returns

    the optimizer

    Definition Classes
    Optimizer
  31. def setDropModuleProperty(dropPercentage: Double, maxDropPercentage: Double, batchsize: Int = 100, warmupIteration: Int = 200): LocalOptimizer.this.type

    Set dropping a certain percentage (dropPercentage) of models during distributed training to accelerate, because some cached model may take too long.

    Set dropping a certain percentage (dropPercentage) of models during distributed training to accelerate, because some cached model may take too long.

    dropPercentage

    drop percentage

    maxDropPercentage

    max drop percentage

    batchsize

    batch size

    warmupIteration

    how may iteration to warm up

    returns

    this optimizer

    Definition Classes
    Optimizer
  32. def setEndWhen(endWhen: Trigger): LocalOptimizer.this.type

    When to stop, passed in a Trigger

    When to stop, passed in a Trigger

    endWhen

    when to end

    returns

    the optimizer

    Definition Classes
    Optimizer
  33. def setModel(newModel: Module[T]): LocalOptimizer.this.type

    Set a model to the optimizer

    Set a model to the optimizer

    newModel

    new model

    Definition Classes
    Optimizer
  34. def setOptimMethod(method: OptimMethod[T]): LocalOptimizer.this.type

    Set an optimization method

    Set an optimization method

    method

    optimization method

    Definition Classes
    Optimizer
  35. def setState(state: Table): LocalOptimizer.this.type

    Set a state(learning rate, epochs.

    Set a state(learning rate, epochs...) to the optimizer

    state

    the state to be saved

    Definition Classes
    Optimizer
  36. def setTrainSummary(trainSummary: TrainSummary): LocalOptimizer.this.type

    Enable train summary.

    Enable train summary.

    Definition Classes
    Optimizer
  37. def setValidation(trigger: Trigger, sampleRDD: RDD[Sample[T]], vMethods: Array[ValidationMethod[T]], batchSize: Int, miniBatch: MiniBatch[T]): LocalOptimizer.this.type

    Set validate evaluation

    Set validate evaluation

    trigger

    how often to evaluation validation set

    sampleRDD

    validate data set in type of RDD of Sample

    vMethods

    a set of validation method ValidationMethod

    batchSize

    batch size

    miniBatch

    construct MiniBatch with a specified miniBatch type

    returns

    Definition Classes
    Optimizer
  38. def setValidation(trigger: Trigger, sampleRDD: RDD[Sample[T]], vMethods: Array[ValidationMethod[T]], batchSize: Int): LocalOptimizer.this.type

    Set a validate evaluation

    Set a validate evaluation

    trigger

    how often to evaluation validation set

    sampleRDD

    validate data set in type of RDD of Sample

    vMethods

    a set of validation method ValidationMethod

    batchSize

    batch size

    returns

    this optimizer

    Definition Classes
    Optimizer
  39. def setValidation(trigger: Trigger, sampleRDD: RDD[Sample[T]], vMethods: Array[ValidationMethod[T]], batchSize: Int, featurePaddingParam: PaddingParam[T], labelPaddingParam: PaddingParam[T]): LocalOptimizer.this.type

    Set a validate evaluation

    Set a validate evaluation

    trigger

    how often to evaluation validation set

    sampleRDD

    validate data set in type of RDD of Sample

    vMethods

    a set of validation method ValidationMethod

    batchSize

    batch size

    featurePaddingParam

    feature padding strategy, see com.intel.analytics.bigdl.dataset.PaddingParam for details.

    labelPaddingParam

    label padding strategy, see com.intel.analytics.bigdl.dataset.PaddingParam for details.

    returns

    this optimizer

    Definition Classes
    Optimizer
  40. def setValidation(trigger: Trigger, dataset: DataSet[MiniBatch[T]], vMethods: Array[ValidationMethod[T]]): LocalOptimizer.this.type

    Set a validate evaluation

    Set a validate evaluation

    trigger

    how often to evaluation validation set

    dataset

    validate data set in type of DataSet of MiniBatch

    vMethods

    a set of validation method ValidationMethod

    returns

    this optimizer

    Definition Classes
    Optimizer
  41. def setValidationSummary(validationSummary: ValidationSummary): LocalOptimizer.this.type

    Enable validation summary.

    Enable validation summary.

    Definition Classes
    Optimizer
  42. var state: Table

    Attributes
    protected
    Definition Classes
    Optimizer
  43. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  44. def toString(): String

    Definition Classes
    AnyRef → Any
  45. var trainSummary: Option[TrainSummary]

    Attributes
    protected
    Definition Classes
    Optimizer
  46. var validationDataSet: Option[DataSet[MiniBatch[T]]]

    Attributes
    protected
    Definition Classes
    Optimizer
  47. var validationMethods: Option[Array[ValidationMethod[T]]]

    Attributes
    protected
    Definition Classes
    Optimizer
  48. var validationSummary: Option[ValidationSummary]

    Attributes
    protected
    Definition Classes
    Optimizer
  49. var validationTrigger: Option[Trigger]

    Attributes
    protected
    Definition Classes
    Optimizer
  50. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  51. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  52. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  53. var warmupIterationNum: Int

    Attributes
    protected
    Definition Classes
    Optimizer

Deprecated Value Members

  1. def disableCheckSingleton(): LocalOptimizer.this.type

    make optimizer not check the singleton model on a node

    make optimizer not check the singleton model on a node

    returns

    Definition Classes
    Optimizer
    Annotations
    @deprecated
    Deprecated

    (Since version 0.1.0) Use bigdl.check.singleton instead

Inherited from Optimizer[T, MiniBatch[T]]

Inherited from AnyRef

Inherited from Any

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